From 3b70cf22eb96c18e63e31c29aac85fb1e7fdec24 Mon Sep 17 00:00:00 2001 From: Andy Grove Date: Wed, 30 Nov 2022 08:55:46 -0700 Subject: [PATCH 01/36] DataFusion Python 0.7.0 Documentation --- _sources/api.rst.txt | 32 + _sources/api/config.rst.txt | 27 + _sources/api/dataframe.rst.txt | 27 + _sources/api/execution_context.rst.txt | 27 + _sources/api/expression.rst.txt | 27 + _sources/api/functions.rst.txt | 27 + _sources/api/object_store.rst.txt | 27 + _sources/generated/datafusion.Config.rst.txt | 26 + .../generated/datafusion.DataFrame.rst.txt | 47 + .../generated/datafusion.Expression.rst.txt | 28 + .../datafusion.SessionContext.rst.txt | 43 + .../datafusion.functions.functions.rst.txt | 23 + ...tafusion.object_store.object_store.rst.txt | 23 + _sources/index.rst.txt | 291 + _static/DataFusion-Logo-Background-White.png | Bin 0 -> 12401 bytes .../_sphinx_javascript_frameworks_compat.js | 134 + _static/basic.css | 900 ++ _static/doctools.js | 264 + _static/documentation_options.js | 14 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100644 index 000000000..a5d65433d --- /dev/null +++ b/_sources/api.rst.txt @@ -0,0 +1,32 @@ +.. Licensed to the Apache Software Foundation (ASF) under one +.. or more contributor license agreements. See the NOTICE file +.. distributed with this work for additional information +.. regarding copyright ownership. The ASF licenses this file +.. to you under the Apache License, Version 2.0 (the +.. "License"); you may not use this file except in compliance +.. with the License. You may obtain a copy of the License at + +.. http://www.apache.org/licenses/LICENSE-2.0 + +.. Unless required by applicable law or agreed to in writing, +.. software distributed under the License is distributed on an +.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +.. KIND, either express or implied. See the License for the +.. specific language governing permissions and limitations +.. under the License. + +.. _api: + +************* +API Reference +************* + +.. toctree:: + :maxdepth: 2 + + api/config + api/dataframe + api/execution_context + api/expression + api/functions + api/object_store diff --git a/_sources/api/config.rst.txt b/_sources/api/config.rst.txt new file mode 100644 index 000000000..df244aec5 --- /dev/null +++ b/_sources/api/config.rst.txt @@ -0,0 +1,27 @@ +.. Licensed to the Apache Software Foundation (ASF) under one +.. or more contributor license agreements. See the NOTICE file +.. distributed with this work for additional information +.. regarding copyright ownership. The ASF licenses this file +.. to you under the Apache License, Version 2.0 (the +.. "License"); you may not use this file except in compliance +.. with the License. You may obtain a copy of the License at + +.. http://www.apache.org/licenses/LICENSE-2.0 + +.. Unless required by applicable law or agreed to in writing, +.. software distributed under the License is distributed on an +.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +.. KIND, either express or implied. See the License for the +.. specific language governing permissions and limitations +.. under the License. + +.. _api.config: +.. currentmodule:: datafusion + +Config +========= + +.. autosummary:: + :toctree: ../generated/ + + Config diff --git a/_sources/api/dataframe.rst.txt b/_sources/api/dataframe.rst.txt new file mode 100644 index 000000000..0a3c4c8b1 --- /dev/null +++ b/_sources/api/dataframe.rst.txt @@ -0,0 +1,27 @@ +.. Licensed to the Apache Software Foundation (ASF) under one +.. or more contributor license agreements. See the NOTICE file +.. distributed with this work for additional information +.. regarding copyright ownership. The ASF licenses this file +.. to you under the Apache License, Version 2.0 (the +.. "License"); you may not use this file except in compliance +.. with the License. You may obtain a copy of the License at + +.. http://www.apache.org/licenses/LICENSE-2.0 + +.. Unless required by applicable law or agreed to in writing, +.. software distributed under the License is distributed on an +.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +.. KIND, either express or implied. See the License for the +.. specific language governing permissions and limitations +.. under the License. + +.. _api.dataframe: +.. currentmodule:: datafusion + +DataFrame +========= + +.. autosummary:: + :toctree: ../generated/ + + DataFrame diff --git a/_sources/api/execution_context.rst.txt b/_sources/api/execution_context.rst.txt new file mode 100644 index 000000000..5b7e0f82f --- /dev/null +++ b/_sources/api/execution_context.rst.txt @@ -0,0 +1,27 @@ +.. Licensed to the Apache Software Foundation (ASF) under one +.. or more contributor license agreements. See the NOTICE file +.. distributed with this work for additional information +.. regarding copyright ownership. The ASF licenses this file +.. to you under the Apache License, Version 2.0 (the +.. "License"); you may not use this file except in compliance +.. with the License. You may obtain a copy of the License at + +.. http://www.apache.org/licenses/LICENSE-2.0 + +.. Unless required by applicable law or agreed to in writing, +.. software distributed under the License is distributed on an +.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +.. KIND, either express or implied. See the License for the +.. specific language governing permissions and limitations +.. under the License. + +.. _api.execution_context: +.. currentmodule:: datafusion + +SessionContext +================ + +.. autosummary:: + :toctree: ../generated/ + + SessionContext diff --git a/_sources/api/expression.rst.txt b/_sources/api/expression.rst.txt new file mode 100644 index 000000000..45923fb54 --- /dev/null +++ b/_sources/api/expression.rst.txt @@ -0,0 +1,27 @@ +.. Licensed to the Apache Software Foundation (ASF) under one +.. or more contributor license agreements. See the NOTICE file +.. distributed with this work for additional information +.. regarding copyright ownership. The ASF licenses this file +.. to you under the Apache License, Version 2.0 (the +.. "License"); you may not use this file except in compliance +.. with the License. You may obtain a copy of the License at + +.. http://www.apache.org/licenses/LICENSE-2.0 + +.. Unless required by applicable law or agreed to in writing, +.. software distributed under the License is distributed on an +.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +.. KIND, either express or implied. See the License for the +.. specific language governing permissions and limitations +.. under the License. + +.. _api.expression: +.. currentmodule:: datafusion + +Expression +========== + +.. autosummary:: + :toctree: ../generated/ + + Expression diff --git a/_sources/api/functions.rst.txt b/_sources/api/functions.rst.txt new file mode 100644 index 000000000..958606df2 --- /dev/null +++ b/_sources/api/functions.rst.txt @@ -0,0 +1,27 @@ +.. Licensed to the Apache Software Foundation (ASF) under one +.. or more contributor license agreements. See the NOTICE file +.. distributed with this work for additional information +.. regarding copyright ownership. The ASF licenses this file +.. to you under the Apache License, Version 2.0 (the +.. "License"); you may not use this file except in compliance +.. with the License. You may obtain a copy of the License at + +.. http://www.apache.org/licenses/LICENSE-2.0 + +.. Unless required by applicable law or agreed to in writing, +.. software distributed under the License is distributed on an +.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +.. KIND, either express or implied. See the License for the +.. specific language governing permissions and limitations +.. under the License. + +.. _api.functions: +.. currentmodule:: datafusion + +Functions +========= + +.. autosummary:: + :toctree: ../generated/ + + functions.functions diff --git a/_sources/api/object_store.rst.txt b/_sources/api/object_store.rst.txt new file mode 100644 index 000000000..eeb6c4326 --- /dev/null +++ b/_sources/api/object_store.rst.txt @@ -0,0 +1,27 @@ +.. Licensed to the Apache Software Foundation (ASF) under one +.. or more contributor license agreements. See the NOTICE file +.. distributed with this work for additional information +.. regarding copyright ownership. The ASF licenses this file +.. to you under the Apache License, Version 2.0 (the +.. "License"); you may not use this file except in compliance +.. with the License. You may obtain a copy of the License at + +.. http://www.apache.org/licenses/LICENSE-2.0 + +.. Unless required by applicable law or agreed to in writing, +.. software distributed under the License is distributed on an +.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +.. KIND, either express or implied. See the License for the +.. specific language governing permissions and limitations +.. under the License. + +.. _api.object_store: +.. currentmodule:: datafusion.object_store + +ObjectStore +========= + +.. autosummary:: + :toctree: ../generated/ + + object_store \ No newline at end of file diff --git a/_sources/generated/datafusion.Config.rst.txt b/_sources/generated/datafusion.Config.rst.txt new file mode 100644 index 000000000..7554084f2 --- /dev/null +++ b/_sources/generated/datafusion.Config.rst.txt @@ -0,0 +1,26 @@ +datafusion.Config +================= + +.. currentmodule:: datafusion + +.. autoclass:: Config + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~Config.__init__ + ~Config.from_env + ~Config.get + ~Config.get_all + ~Config.set + + + + + + \ No newline at end of file diff --git a/_sources/generated/datafusion.DataFrame.rst.txt b/_sources/generated/datafusion.DataFrame.rst.txt new file mode 100644 index 000000000..e0ddc8651 --- /dev/null +++ b/_sources/generated/datafusion.DataFrame.rst.txt @@ -0,0 +1,47 @@ +datafusion.DataFrame +==================== + +.. currentmodule:: datafusion + +.. autoclass:: DataFrame + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~DataFrame.__init__ + ~DataFrame.aggregate + ~DataFrame.cache + ~DataFrame.collect + ~DataFrame.collect_partitioned + ~DataFrame.distinct + ~DataFrame.except_all + ~DataFrame.explain + ~DataFrame.filter + ~DataFrame.intersect + ~DataFrame.join + ~DataFrame.limit + ~DataFrame.repartition + ~DataFrame.repartition_by_hash + ~DataFrame.schema + ~DataFrame.select + ~DataFrame.select_columns + ~DataFrame.show + ~DataFrame.sort + ~DataFrame.union + ~DataFrame.union_distinct + ~DataFrame.with_column + ~DataFrame.with_column_renamed + ~DataFrame.write_csv + ~DataFrame.write_json + ~DataFrame.write_parquet + + + + + + \ No newline at end of file diff --git a/_sources/generated/datafusion.Expression.rst.txt b/_sources/generated/datafusion.Expression.rst.txt new file mode 100644 index 000000000..92e9b4c5d --- /dev/null +++ b/_sources/generated/datafusion.Expression.rst.txt @@ -0,0 +1,28 @@ +datafusion.Expression +===================== + +.. currentmodule:: datafusion + +.. autoclass:: Expression + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~Expression.__init__ + ~Expression.alias + ~Expression.cast + ~Expression.column + ~Expression.is_null + ~Expression.literal + ~Expression.sort + + + + + + \ No newline at end of file diff --git a/_sources/generated/datafusion.SessionContext.rst.txt b/_sources/generated/datafusion.SessionContext.rst.txt new file mode 100644 index 000000000..965f8b8fc --- /dev/null +++ b/_sources/generated/datafusion.SessionContext.rst.txt @@ -0,0 +1,43 @@ +datafusion.SessionContext +========================= + +.. currentmodule:: datafusion + +.. autoclass:: SessionContext + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~SessionContext.__init__ + ~SessionContext.catalog + ~SessionContext.create_dataframe + ~SessionContext.deregister_table + ~SessionContext.empty_table + ~SessionContext.read_avro + ~SessionContext.read_csv + ~SessionContext.read_json + ~SessionContext.read_parquet + ~SessionContext.register_csv + ~SessionContext.register_dataset + ~SessionContext.register_object_store + ~SessionContext.register_parquet + ~SessionContext.register_record_batches + ~SessionContext.register_table + ~SessionContext.register_udaf + ~SessionContext.register_udf + ~SessionContext.session_id + ~SessionContext.sql + ~SessionContext.table + ~SessionContext.table_exist + ~SessionContext.tables + + + + + + \ No newline at end of file diff --git a/_sources/generated/datafusion.functions.functions.rst.txt b/_sources/generated/datafusion.functions.functions.rst.txt new file mode 100644 index 000000000..eb10a67f0 --- /dev/null +++ b/_sources/generated/datafusion.functions.functions.rst.txt @@ -0,0 +1,23 @@ +datafusion.functions.functions +============================== + +.. automodule:: datafusion.functions.functions + + + + + + + + + + + + + + + + + + + diff --git a/_sources/generated/datafusion.object_store.object_store.rst.txt b/_sources/generated/datafusion.object_store.object_store.rst.txt new file mode 100644 index 000000000..7934ec323 --- /dev/null +++ b/_sources/generated/datafusion.object_store.object_store.rst.txt @@ -0,0 +1,23 @@ +datafusion.object\_store.object\_store +====================================== + +.. automodule:: datafusion.object_store.object_store + + + + + + + + + + + + + + + + + + + diff --git a/_sources/index.rst.txt b/_sources/index.rst.txt new file mode 100644 index 000000000..78f44ea17 --- /dev/null +++ b/_sources/index.rst.txt @@ -0,0 +1,291 @@ +.. Licensed to the Apache Software Foundation (ASF) under one +.. or more contributor license agreements. See the NOTICE file +.. distributed with this work for additional information +.. regarding copyright ownership. The ASF licenses this file +.. to you under the Apache License, Version 2.0 (the +.. "License"); you may not use this file except in compliance +.. with the License. You may obtain a copy of the License at + +.. http://www.apache.org/licenses/LICENSE-2.0 + +.. Unless required by applicable law or agreed to in writing, +.. software distributed under the License is distributed on an +.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +.. KIND, either express or implied. See the License for the +.. specific language governing permissions and limitations +.. under the License. + +==================== +DataFusion in Python +==================== + +This is a Python library that binds to `Apache Arrow `_ in-memory query engine `DataFusion `_. + +Like pyspark, it allows you to build a plan through SQL or a DataFrame API against in-memory data, parquet or CSV files, run it in a multi-threaded environment, and obtain the result back in Python. + +It also allows you to use UDFs and UDAFs for complex operations. + +The major advantage of this library over other execution engines is that this library achieves zero-copy between Python and its execution engine: there is no cost in using UDFs, UDAFs, and collecting the results to Python apart from having to lock the GIL when running those operations. + +Its query engine, DataFusion, is written in `Rust `_, which makes strong assumptions about thread safety and lack of memory leaks. + +Technically, zero-copy is achieved via the `c data interface `_. + +How to use it +============= + +Simple usage: + +.. code-block:: python + + import datafusion + from datafusion import col + import pyarrow + + # create a context + ctx = datafusion.SessionContext() + + # create a RecordBatch and a new DataFrame from it + batch = pyarrow.RecordBatch.from_arrays( + [pyarrow.array([1, 2, 3]), pyarrow.array([4, 5, 6])], + names=["a", "b"], + ) + df = ctx.create_dataframe([[batch]]) + + # create a new statement + df = df.select( + col("a") + col("b"), + col("a") - col("b"), + ) + + # execute and collect the first (and only) batch + result = df.collect()[0] + + assert result.column(0) == pyarrow.array([5, 7, 9]) + assert result.column(1) == pyarrow.array([-3, -3, -3]) + + +We can also execute a query against data stored in CSV + +.. code-block:: bash + + echo "a,b\n1,4\n2,5\n3,6" > example.csv + + +.. code-block:: python + + import datafusion + from datafusion import col + import pyarrow + + # create a context + ctx = datafusion.SessionContext() + + # register a CSV + ctx.register_csv('example', 'example.csv') + + # create a new statement + df = ctx.table('example').select( + col("a") + col("b"), + col("a") - col("b"), + ) + + # execute and collect the first (and only) batch + result = df.collect()[0] + + assert result.column(0) == pyarrow.array([5, 7, 9]) + assert result.column(1) == pyarrow.array([-3, -3, -3]) + + +And how to execute a query against a CSV using SQL: + + +.. code-block:: python + + import datafusion + from datafusion import col + import pyarrow + + # create a context + ctx = datafusion.SessionContext() + + # register a CSV + ctx.register_csv('example', 'example.csv') + + # create a new statement via SQL + df = ctx.sql("SELECT a+b, a-b FROM example") + + # execute and collect the first (and only) batch + result = df.collect()[0] + + assert result.column(0) == pyarrow.array([5, 7, 9]) + assert result.column(1) == pyarrow.array([-3, -3, -3]) + + + +UDFs +---- + +.. code-block:: python + + import pyarrow + from datafusion import udf + + def is_null(array: pyarrow.Array) -> pyarrow.Array: + return array.is_null() + + is_null_arr = udf(is_null, [pyarrow.int64()], pyarrow.bool_(), 'stable') + + # create a context + ctx = datafusion.SessionContext() + + # create a RecordBatch and a new DataFrame from it + batch = pyarrow.RecordBatch.from_arrays( + [pyarrow.array([1, 2, 3]), pyarrow.array([4, 5, 6])], + names=["a", "b"], + ) + df = ctx.create_dataframe([[batch]]) + + df = df.select(is_null_arr(col("a"))) + + result = df.collect()[0] + + assert result.column(0) == pyarrow.array([False] * 3) + + +UDAF +---- + +.. code-block:: python + + import pyarrow + import pyarrow.compute + import datafusion + from datafusion import udaf, Accumulator + from datafusion import col + + + class MyAccumulator(Accumulator): + """ + Interface of a user-defined accumulation. + """ + def __init__(self): + self._sum = pyarrow.scalar(0.0) + + def update(self, values: pyarrow.Array) -> None: + # not nice since pyarrow scalars can't be summed yet. This breaks on `None` + self._sum = pyarrow.scalar(self._sum.as_py() + pyarrow.compute.sum(values).as_py()) + + def merge(self, states: pyarrow.Array) -> None: + # not nice since pyarrow scalars can't be summed yet. This breaks on `None` + self._sum = pyarrow.scalar(self._sum.as_py() + pyarrow.compute.sum(states).as_py()) + + def state(self) -> pyarrow.Array: + return pyarrow.array([self._sum.as_py()]) + + def evaluate(self) -> pyarrow.Scalar: + return self._sum + + # create a context + ctx = datafusion.SessionContext() + + # create a RecordBatch and a new DataFrame from it + batch = pyarrow.RecordBatch.from_arrays( + [pyarrow.array([1, 2, 3]), pyarrow.array([4, 5, 6])], + names=["a", "b"], + ) + df = ctx.create_dataframe([[batch]]) + + my_udaf = udaf(MyAccumulator, pyarrow.float64(), pyarrow.float64(), [pyarrow.float64()], 'stable') + + df = df.aggregate( + [], + [my_udaf(col("a"))] + ) + + result = df.collect()[0] + + assert result.column(0) == pyarrow.array([6.0]) + +How to install (from pip) +========================= + +.. code-block:: shell + + pip install datafusion + +You can verify the installation by running: + +.. code-block:: python + + >>> import datafusion + >>> datafusion.__version__ + '0.6.0' + + +How to develop +============== + +This assumes that you have rust and cargo installed. We use the workflow recommended by `pyo3 `_ and `maturin `_. + +Bootstrap: + +.. code-block:: shell + + # fetch this repo + git clone git@github.com:apache/arrow-datafusion-python.git + # prepare development environment (used to build wheel / install in development) + python3 -m venv venv + # activate the venv + source venv/bin/activate + # update pip itself if necessary + python -m pip install -U pip + # install dependencies (for Python 3.8+) + python -m pip install -r requirements-310.txt + +The tests rely on test data in git submodules. + +.. code-block:: shell + + git submodule init + git submodule update + + +Whenever rust code changes (your changes or via `git pull`): + +.. code-block:: shell + + # make sure you activate the venv using "source venv/bin/activate" first + maturin develop + python -m pytest + + +How to update dependencies +========================== + +To change test dependencies, change the `requirements.in` and run + +.. code-block:: shell + + # install pip-tools (this can be done only once), also consider running in venv + python -m pip install pip-tools + python -m piptools compile --generate-hashes -o requirements-310.txt + + +To update dependencies, run with `-U` + +.. code-block:: shell + + python -m piptools compile -U --generate-hashes -o requirements-310.txt + + +More details about pip-tools `here `_ + + +API reference +============= + +.. toctree:: + :maxdepth: 2 + + api diff --git a/_static/DataFusion-Logo-Background-White.png b/_static/DataFusion-Logo-Background-White.png new file mode 100644 index 0000000000000000000000000000000000000000..023c2373fc4949037ca1e11bfb72e2e469a0bda7 GIT binary patch literal 12401 zcmX9_1vp;s8{USQHZvU`j&3$RZG4(B&2%>#Gfa0Kd^*R}Fx|1~nC_nL&Z+ zujfGBv{^-#oEVzuM>Z3=G;n2^y&z?e`!yY(m(6^^Xa?+BI z?jOD~oAP2GJ>sB)ONyzv&FrP2&8d&xbt(|=tFt9AOh!|W$bi{ga^IOLGj^KO zDlTTOcW-yAyxLC4hAPYlQ{AeYJ+Jq@c8Y60{z-mqeZBrC#hXyv1|DQPoGmqbcV5%- zvLfx%g8P*hh4oCOrQqk&&6wEmh{fN7&UHtfq|SRgJWi|KXs@!~s_o`U@?+;3K9%zQ+x#XMe%5@w&kYbGu{WKnh8UB( z42do0Wq5HZMTmU_O^UUv+6fK5Ja^S8Hwj7PG!7(sZ56jUUX)O~o^0)3g~@!jBrbFN z@9YH%3W^V3&&7fV`>SdRY<|f*`#Pt!_VhO%U-%ckE2OlCzGT+5#}U5#VDZJi`N~Xp z@%HZez_Y>5Jl)+a#JcnRbW|xNuM;K+FE?xpMBB^E&zI>>6V#Y<>SJ9VlE7gVLqw4B zBK%{lURjPvMsBpfP{PL%Iuy0|(iVt?(H?cU9L65l`O0;BOf=kbq0v2y^UeLu$#O7F zWc2-Ql=qDUJ^?{8eOGI=3H4O1<2T*Ta+ZnYOS!l{;A_ zA_7m*L0VSr%4csh^HQBcQ)7S^EEqk_&NpG~&3va9&>aVMo?Wg)k%Hl^OTYXiR?1|X zRu@CV!ldGv)K?du71>OecL=?C8VEG`x~(bj&f|Yxg8eZu>WyQ}GLCITqjwPe+s?u( zBC;55LbN?u%HHL)U69wiIP|m(?vVOU~9Xto~9SoHR`kf-#z%%bWM5xe|F(Z@X~^lo`k=J#}x-EYRH(1TwaULCJ3FZtmhy7*VZ zxj|Ku(^>nL0Q4-Xb{XXnlZ@-CNquXXV{c$XTq_ZlBt%Z<~TIh|rE5y{S*i#g+T7?K3& z#j?Uyze&BQ^h3MKiZdbL_WA-RB4qi}hQ7yfr8A&YtnDlMk0(rO`7jaZ)fnks`C169-2(30SG-FOHLttG_bqxL?1+Hkr$0J5z}ku~jiB+@}rRKyM-LxZ-`g zW1u3^@cC?8SZR>q5UCKHSsZ_j5PUkqrOr_qWic{`P3Ecl6ne*>0ZTTi&0 zk^fuR;}n5H`Txr>+8g*5dgwED`|j9lmwclW19YeYg+2epDgW)^0dH1gmBhR5Tkfw# zG#1g=yXk4tw|&1L`Gr%#yN40)Mk5ZIuS@))HJRS-Q-(oTC4)q2VB=o(>}pxv(<2L? 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Multiple values per key are supported, + * it will always return arrays of strings for the value parts. + */ +jQuery.getQueryParameters = function(s) { + if (typeof s === 'undefined') + s = document.location.search; + var parts = s.substr(s.indexOf('?') + 1).split('&'); + var result = {}; + for (var i = 0; i < parts.length; i++) { + var tmp = parts[i].split('=', 2); + var key = jQuery.urldecode(tmp[0]); + var value = jQuery.urldecode(tmp[1]); + if (key in result) + result[key].push(value); + else + result[key] = [value]; + } + return result; +}; + +/** + * highlight a given string on a jquery object by wrapping it in + * span elements with the given class name. + */ +jQuery.fn.highlightText = function(text, className) { + function highlight(node, addItems) { + if (node.nodeType === 3) { + var val = node.nodeValue; + var pos = val.toLowerCase().indexOf(text); + if (pos >= 0 && + !jQuery(node.parentNode).hasClass(className) && + !jQuery(node.parentNode).hasClass("nohighlight")) { + var span; + var isInSVG = jQuery(node).closest("body, svg, foreignObject").is("svg"); + if (isInSVG) { + span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); + } else { + span = document.createElement("span"); + span.className = className; + } + span.appendChild(document.createTextNode(val.substr(pos, text.length))); + node.parentNode.insertBefore(span, node.parentNode.insertBefore( + document.createTextNode(val.substr(pos + text.length)), + node.nextSibling)); + node.nodeValue = val.substr(0, pos); + if (isInSVG) { + var rect = document.createElementNS("http://www.w3.org/2000/svg", "rect"); + var bbox = node.parentElement.getBBox(); + rect.x.baseVal.value = bbox.x; + rect.y.baseVal.value = bbox.y; + rect.width.baseVal.value = bbox.width; + rect.height.baseVal.value = bbox.height; + rect.setAttribute('class', className); + addItems.push({ + "parent": node.parentNode, + "target": rect}); + } + } + } + else if (!jQuery(node).is("button, select, textarea")) { + jQuery.each(node.childNodes, function() { + highlight(this, addItems); + }); + } + } + var addItems = []; + var result = this.each(function() { + highlight(this, addItems); + }); + for (var i = 0; i < addItems.length; ++i) { + jQuery(addItems[i].parent).before(addItems[i].target); + } + return result; +}; + +/* + * backward compatibility for jQuery.browser + * This will be supported until firefox bug is fixed. + */ +if (!jQuery.browser) { + jQuery.uaMatch = function(ua) { + ua = ua.toLowerCase(); + + var match = /(chrome)[ \/]([\w.]+)/.exec(ua) || + /(webkit)[ \/]([\w.]+)/.exec(ua) || + /(opera)(?:.*version|)[ \/]([\w.]+)/.exec(ua) || + /(msie) ([\w.]+)/.exec(ua) || + ua.indexOf("compatible") < 0 && /(mozilla)(?:.*? rv:([\w.]+)|)/.exec(ua) || + []; + + return { + browser: match[ 1 ] || "", + version: match[ 2 ] || "0" + }; + }; + jQuery.browser = {}; + jQuery.browser[jQuery.uaMatch(navigator.userAgent).browser] = true; +} diff --git a/_static/basic.css b/_static/basic.css new file mode 100644 index 000000000..18495ea08 --- /dev/null +++ b/_static/basic.css @@ -0,0 +1,900 @@ +/* + * basic.css + * ~~~~~~~~~ + * + * Sphinx stylesheet -- basic theme. + * + * :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS. + * :license: BSD, see LICENSE for details. + * + */ + +/* -- main layout ----------------------------------------------------------- */ + +div.clearer { + clear: both; +} + +div.section::after { + display: block; + content: ''; + clear: left; +} + +/* -- relbar ---------------------------------------------------------------- */ + +div.related { + width: 100%; + font-size: 90%; +} + +div.related h3 { + display: none; +} + +div.related ul { + margin: 0; + padding: 0 0 0 10px; + list-style: none; +} + +div.related li { + display: inline; +} + +div.related li.right { + float: right; + margin-right: 5px; +} + +/* -- sidebar --------------------------------------------------------------- */ + +div.sphinxsidebarwrapper { + padding: 10px 5px 0 10px; +} + +div.sphinxsidebar { + float: left; + width: 270px; + margin-left: -100%; + font-size: 90%; + word-wrap: break-word; + overflow-wrap : break-word; +} + +div.sphinxsidebar ul { + list-style: none; +} + +div.sphinxsidebar ul ul, +div.sphinxsidebar ul.want-points { + margin-left: 20px; + list-style: square; +} + +div.sphinxsidebar ul ul { + margin-top: 0; + margin-bottom: 0; +} + +div.sphinxsidebar form { + margin-top: 10px; +} + +div.sphinxsidebar input { + border: 1px solid #98dbcc; + font-family: sans-serif; + font-size: 1em; +} + +div.sphinxsidebar #searchbox form.search { + overflow: hidden; +} + +div.sphinxsidebar #searchbox input[type="text"] { + float: left; + width: 80%; + padding: 0.25em; + box-sizing: border-box; +} + +div.sphinxsidebar #searchbox input[type="submit"] { + float: left; + width: 20%; + border-left: none; + padding: 0.25em; + box-sizing: border-box; +} + + +img { + border: 0; + max-width: 100%; +} + +/* -- search page ----------------------------------------------------------- */ + +ul.search { + margin: 10px 0 0 20px; + padding: 0; +} + +ul.search li { + padding: 5px 0 5px 20px; + background-image: url(file.png); + background-repeat: no-repeat; + background-position: 0 7px; +} + +ul.search li a { + font-weight: bold; +} + +ul.search li p.context { + color: #888; + margin: 2px 0 0 30px; + text-align: left; +} + +ul.keywordmatches li.goodmatch a { + font-weight: bold; +} + +/* -- index page ------------------------------------------------------------ */ + +table.contentstable { + width: 90%; + margin-left: auto; + margin-right: auto; +} + +table.contentstable p.biglink { + line-height: 150%; +} + +a.biglink { + font-size: 1.3em; +} + +span.linkdescr { + font-style: italic; + padding-top: 5px; + font-size: 90%; +} + +/* -- general index --------------------------------------------------------- */ + +table.indextable { + width: 100%; +} + +table.indextable td { + text-align: left; + vertical-align: top; +} + +table.indextable ul { + margin-top: 0; + margin-bottom: 0; + list-style-type: none; +} + +table.indextable > tbody > tr > td > ul { + padding-left: 0em; +} + +table.indextable tr.pcap { + height: 10px; +} + +table.indextable tr.cap { + margin-top: 10px; + background-color: #f2f2f2; +} + +img.toggler { + margin-right: 3px; + margin-top: 3px; + cursor: pointer; +} + +div.modindex-jumpbox { + border-top: 1px solid #ddd; + border-bottom: 1px solid #ddd; + margin: 1em 0 1em 0; + padding: 0.4em; +} + +div.genindex-jumpbox { + border-top: 1px solid #ddd; + border-bottom: 1px solid #ddd; + margin: 1em 0 1em 0; + padding: 0.4em; +} + +/* -- domain module index --------------------------------------------------- */ + +table.modindextable td { + padding: 2px; + border-collapse: collapse; +} + +/* -- general body styles --------------------------------------------------- */ + +div.body { + min-width: 360px; + max-width: 800px; +} + +div.body p, div.body dd, div.body li, div.body blockquote { + -moz-hyphens: auto; + -ms-hyphens: auto; + -webkit-hyphens: auto; + hyphens: auto; +} + +a.headerlink { + visibility: hidden; +} + +h1:hover > a.headerlink, +h2:hover > a.headerlink, +h3:hover > a.headerlink, +h4:hover > a.headerlink, +h5:hover > a.headerlink, +h6:hover > a.headerlink, +dt:hover > a.headerlink, +caption:hover > a.headerlink, +p.caption:hover > a.headerlink, +div.code-block-caption:hover > a.headerlink { + visibility: visible; +} + +div.body p.caption { + text-align: inherit; +} + +div.body td { + text-align: left; +} + +.first { + margin-top: 0 !important; +} + +p.rubric { + margin-top: 30px; + font-weight: bold; +} + +img.align-left, figure.align-left, .figure.align-left, object.align-left { + clear: left; + float: left; + margin-right: 1em; +} + +img.align-right, figure.align-right, .figure.align-right, object.align-right { + clear: right; + float: right; + margin-left: 1em; +} + +img.align-center, figure.align-center, .figure.align-center, object.align-center { + display: block; + margin-left: auto; + margin-right: auto; +} + +img.align-default, figure.align-default, .figure.align-default { + display: block; + margin-left: auto; + margin-right: auto; +} + +.align-left { + text-align: left; +} + +.align-center { + text-align: center; +} + +.align-default { + text-align: center; +} + +.align-right { + text-align: right; +} + +/* -- sidebars -------------------------------------------------------------- */ + +div.sidebar, +aside.sidebar { + margin: 0 0 0.5em 1em; + border: 1px solid #ddb; + padding: 7px; + background-color: #ffe; + width: 40%; + float: right; + clear: right; + overflow-x: auto; +} + +p.sidebar-title { + font-weight: bold; +} +nav.contents, +aside.topic, +div.admonition, div.topic, blockquote { + clear: left; +} + +/* -- topics ---------------------------------------------------------------- */ +nav.contents, +aside.topic, +div.topic { + border: 1px solid #ccc; + padding: 7px; + margin: 10px 0 10px 0; +} + +p.topic-title { + font-size: 1.1em; + font-weight: bold; + margin-top: 10px; +} + +/* -- admonitions ----------------------------------------------------------- */ + +div.admonition { + margin-top: 10px; + margin-bottom: 10px; + padding: 7px; +} + +div.admonition dt { + font-weight: bold; +} + +p.admonition-title { + margin: 0px 10px 5px 0px; + font-weight: bold; +} + +div.body p.centered { + text-align: center; + margin-top: 25px; +} + +/* -- content of sidebars/topics/admonitions -------------------------------- */ + +div.sidebar > :last-child, +aside.sidebar > :last-child, +nav.contents > :last-child, +aside.topic > :last-child, +div.topic > :last-child, +div.admonition > :last-child { + margin-bottom: 0; +} + +div.sidebar::after, +aside.sidebar::after, +nav.contents::after, +aside.topic::after, +div.topic::after, +div.admonition::after, +blockquote::after { + display: block; + content: ''; + clear: both; +} + +/* -- tables ---------------------------------------------------------------- */ + +table.docutils { + margin-top: 10px; + margin-bottom: 10px; + border: 0; + border-collapse: collapse; +} + +table.align-center { + margin-left: auto; + margin-right: auto; +} + +table.align-default { + margin-left: auto; + margin-right: auto; +} + +table caption span.caption-number { + font-style: italic; +} + +table caption span.caption-text { +} + +table.docutils td, table.docutils th { + padding: 1px 8px 1px 5px; + border-top: 0; + border-left: 0; + border-right: 0; + border-bottom: 1px solid #aaa; +} + +th { + text-align: left; + padding-right: 5px; +} + +table.citation { + border-left: solid 1px gray; + margin-left: 1px; +} + +table.citation td { + border-bottom: none; +} + +th > :first-child, +td > :first-child { + margin-top: 0px; +} + +th > :last-child, +td > :last-child { + margin-bottom: 0px; +} + +/* -- figures --------------------------------------------------------------- */ + +div.figure, figure { + margin: 0.5em; + padding: 0.5em; +} + +div.figure p.caption, figcaption { + padding: 0.3em; +} + +div.figure p.caption span.caption-number, +figcaption span.caption-number { + font-style: italic; +} + +div.figure p.caption span.caption-text, +figcaption span.caption-text { +} + +/* -- field list styles ----------------------------------------------------- */ + +table.field-list td, table.field-list th { + border: 0 !important; +} + +.field-list ul { + margin: 0; + padding-left: 1em; +} + +.field-list p { + margin: 0; +} + +.field-name { + -moz-hyphens: manual; + -ms-hyphens: manual; + -webkit-hyphens: manual; + hyphens: manual; +} + +/* -- hlist styles ---------------------------------------------------------- */ + +table.hlist { + margin: 1em 0; +} + +table.hlist td { + vertical-align: top; +} + +/* -- object description styles --------------------------------------------- */ + +.sig { + font-family: 'Consolas', 'Menlo', 'DejaVu Sans Mono', 'Bitstream Vera Sans Mono', monospace; +} + +.sig-name, code.descname { + background-color: transparent; + font-weight: bold; +} + +.sig-name { + font-size: 1.1em; +} + +code.descname { + font-size: 1.2em; +} + +.sig-prename, code.descclassname { + background-color: transparent; +} + +.optional { + font-size: 1.3em; +} + +.sig-paren { + font-size: larger; +} + +.sig-param.n { + font-style: italic; +} + +/* C++ specific styling */ + +.sig-inline.c-texpr, +.sig-inline.cpp-texpr { + font-family: unset; +} + +.sig.c .k, .sig.c .kt, +.sig.cpp .k, .sig.cpp .kt { + color: #0033B3; +} + +.sig.c .m, +.sig.cpp .m { + color: #1750EB; +} + +.sig.c .s, .sig.c .sc, +.sig.cpp .s, .sig.cpp .sc { + color: #067D17; +} + + +/* -- other body styles ----------------------------------------------------- */ + +ol.arabic { + list-style: decimal; +} + +ol.loweralpha { + list-style: lower-alpha; +} + +ol.upperalpha { + list-style: upper-alpha; +} + +ol.lowerroman { + list-style: lower-roman; +} + +ol.upperroman { + list-style: upper-roman; +} + +:not(li) > ol > li:first-child > :first-child, +:not(li) > ul > li:first-child > :first-child { + margin-top: 0px; +} + +:not(li) > ol > li:last-child > :last-child, +:not(li) > ul > li:last-child > :last-child { + margin-bottom: 0px; +} + +ol.simple ol p, +ol.simple ul p, +ul.simple ol p, +ul.simple ul p { + margin-top: 0; +} + +ol.simple > li:not(:first-child) > p, +ul.simple > li:not(:first-child) > p { + margin-top: 0; +} + +ol.simple p, +ul.simple p { + margin-bottom: 0; +} +aside.footnote > span, +div.citation > span { + float: left; +} +aside.footnote > span:last-of-type, +div.citation > span:last-of-type { + padding-right: 0.5em; +} +aside.footnote > p { + margin-left: 2em; +} +div.citation > p { + margin-left: 4em; +} +aside.footnote > p:last-of-type, +div.citation > p:last-of-type { + margin-bottom: 0em; +} +aside.footnote > p:last-of-type:after, +div.citation > p:last-of-type:after { + content: ""; + clear: both; +} + +dl.field-list { + display: grid; + grid-template-columns: fit-content(30%) auto; +} + +dl.field-list > dt { + font-weight: bold; + word-break: break-word; + padding-left: 0.5em; + padding-right: 5px; +} + +dl.field-list > dd { + padding-left: 0.5em; + margin-top: 0em; + margin-left: 0em; + margin-bottom: 0em; +} + +dl { + margin-bottom: 15px; +} + +dd > :first-child { + margin-top: 0px; +} + +dd ul, dd table { + margin-bottom: 10px; +} + +dd { + margin-top: 3px; + margin-bottom: 10px; + margin-left: 30px; +} + +dl > dd:last-child, +dl > dd:last-child > :last-child { + margin-bottom: 0; +} + +dt:target, span.highlighted { + background-color: #fbe54e; +} + +rect.highlighted { + fill: #fbe54e; +} + +dl.glossary dt { + font-weight: bold; + font-size: 1.1em; +} + +.versionmodified { + font-style: italic; +} + +.system-message { + background-color: #fda; + padding: 5px; + border: 3px solid red; +} + +.footnote:target { + background-color: #ffa; +} + +.line-block { + display: block; + margin-top: 1em; + margin-bottom: 1em; +} + +.line-block .line-block { + margin-top: 0; + margin-bottom: 0; + margin-left: 1.5em; +} + +.guilabel, .menuselection { + font-family: sans-serif; +} + +.accelerator { + text-decoration: underline; +} + +.classifier { + font-style: oblique; +} + +.classifier:before { + font-style: normal; + margin: 0 0.5em; + content: ":"; + display: inline-block; +} + +abbr, acronym { + border-bottom: dotted 1px; + cursor: help; +} + +/* -- code displays --------------------------------------------------------- */ + +pre { + overflow: auto; + overflow-y: hidden; /* fixes display issues on Chrome browsers */ +} + +pre, div[class*="highlight-"] { + clear: both; +} + +span.pre { + -moz-hyphens: none; + -ms-hyphens: none; + -webkit-hyphens: none; + hyphens: none; + white-space: nowrap; +} + +div[class*="highlight-"] { + margin: 1em 0; +} + +td.linenos pre { + border: 0; + background-color: transparent; + color: #aaa; +} + +table.highlighttable { + display: block; +} + +table.highlighttable tbody { + display: block; +} + +table.highlighttable tr { + display: flex; +} + +table.highlighttable td { + margin: 0; + padding: 0; +} + +table.highlighttable td.linenos { + padding-right: 0.5em; +} + +table.highlighttable td.code { + flex: 1; + overflow: hidden; +} + +.highlight .hll { + display: block; +} + +div.highlight pre, +table.highlighttable pre { + margin: 0; +} + +div.code-block-caption + div { + margin-top: 0; +} + +div.code-block-caption { + margin-top: 1em; + padding: 2px 5px; + font-size: small; +} + +div.code-block-caption code { + background-color: transparent; +} + +table.highlighttable td.linenos, +span.linenos, +div.highlight span.gp { /* gp: Generic.Prompt */ + user-select: none; + -webkit-user-select: text; /* Safari fallback only */ + -webkit-user-select: none; /* Chrome/Safari */ + -moz-user-select: none; /* Firefox */ + -ms-user-select: none; /* IE10+ */ +} + +div.code-block-caption span.caption-number { + padding: 0.1em 0.3em; + font-style: italic; +} + +div.code-block-caption span.caption-text { +} + +div.literal-block-wrapper { + margin: 1em 0; +} + +code.xref, a code { + background-color: transparent; + font-weight: bold; +} + +h1 code, h2 code, h3 code, h4 code, h5 code, h6 code { + background-color: transparent; +} + +.viewcode-link { + float: right; +} + +.viewcode-back { + float: right; + font-family: sans-serif; +} + +div.viewcode-block:target { + margin: -1px -10px; + padding: 0 10px; +} + +/* -- math display ---------------------------------------------------------- */ + +img.math { + vertical-align: middle; +} + +div.body div.math p { + text-align: center; +} + +span.eqno { + float: right; +} + +span.eqno a.headerlink { + position: absolute; + z-index: 1; +} + +div.math:hover a.headerlink { + visibility: visible; +} + +/* -- printout stylesheet --------------------------------------------------- */ + +@media print { + div.document, + div.documentwrapper, + div.bodywrapper { + margin: 0 !important; + width: 100%; + } + + div.sphinxsidebar, + div.related, + div.footer, + #top-link { + display: none; + } +} \ No newline at end of file diff --git a/_static/doctools.js b/_static/doctools.js new file mode 100644 index 000000000..c3db08d1c --- /dev/null +++ b/_static/doctools.js @@ -0,0 +1,264 @@ +/* + * doctools.js + * ~~~~~~~~~~~ + * + * Base JavaScript utilities for all Sphinx HTML documentation. + * + * :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS. + * :license: BSD, see LICENSE for details. + * + */ +"use strict"; + +const _ready = (callback) => { + if (document.readyState !== "loading") { + callback(); + } else { + document.addEventListener("DOMContentLoaded", callback); + } +}; + +/** + * highlight a given string on a node by wrapping it in + * span elements with the given class name. + */ +const _highlight = (node, addItems, text, className) => { + if (node.nodeType === Node.TEXT_NODE) { + const val = node.nodeValue; + const parent = node.parentNode; + const pos = val.toLowerCase().indexOf(text); + if ( + pos >= 0 && + !parent.classList.contains(className) && + !parent.classList.contains("nohighlight") + ) { + let span; + + const closestNode = parent.closest("body, svg, foreignObject"); + const isInSVG = closestNode && closestNode.matches("svg"); + if (isInSVG) { + span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); + } else { + span = document.createElement("span"); + span.classList.add(className); + } + + span.appendChild(document.createTextNode(val.substr(pos, text.length))); + parent.insertBefore( + span, + parent.insertBefore( + document.createTextNode(val.substr(pos + text.length)), + node.nextSibling + ) + ); + node.nodeValue = val.substr(0, pos); + + if (isInSVG) { + const rect = document.createElementNS( + "http://www.w3.org/2000/svg", + "rect" + ); + const bbox = parent.getBBox(); + rect.x.baseVal.value = bbox.x; + rect.y.baseVal.value = bbox.y; + rect.width.baseVal.value = bbox.width; + rect.height.baseVal.value = bbox.height; + rect.setAttribute("class", className); + addItems.push({ parent: parent, target: rect }); + } + } + } else if (node.matches && !node.matches("button, select, textarea")) { + node.childNodes.forEach((el) => _highlight(el, addItems, text, className)); + } +}; +const _highlightText = (thisNode, text, className) => { + let addItems = []; + _highlight(thisNode, addItems, text, className); + addItems.forEach((obj) => + obj.parent.insertAdjacentElement("beforebegin", obj.target) + ); +}; + +/** + * Small JavaScript module for the documentation. + */ +const Documentation = { + init: () => { + Documentation.highlightSearchWords(); + Documentation.initDomainIndexTable(); + Documentation.initOnKeyListeners(); + }, + + /** + * i18n support + */ + TRANSLATIONS: {}, + PLURAL_EXPR: (n) => (n === 1 ? 0 : 1), + LOCALE: "unknown", + + // gettext and ngettext don't access this so that the functions + // can safely bound to a different name (_ = Documentation.gettext) + gettext: (string) => { + const translated = Documentation.TRANSLATIONS[string]; + switch (typeof translated) { + case "undefined": + return string; // no translation + case "string": + return translated; // translation exists + default: + return translated[0]; // (singular, plural) translation tuple exists + } + }, + + ngettext: (singular, plural, n) => { + const translated = Documentation.TRANSLATIONS[singular]; + if (typeof translated !== "undefined") + return translated[Documentation.PLURAL_EXPR(n)]; + return n === 1 ? singular : plural; + }, + + addTranslations: (catalog) => { + Object.assign(Documentation.TRANSLATIONS, catalog.messages); + Documentation.PLURAL_EXPR = new Function( + "n", + `return (${catalog.plural_expr})` + ); + Documentation.LOCALE = catalog.locale; + }, + + /** + * highlight the search words provided in the url in the text + */ + highlightSearchWords: () => { + const highlight = + new URLSearchParams(window.location.search).get("highlight") || ""; + const terms = highlight.toLowerCase().split(/\s+/).filter(x => x); + if (terms.length === 0) return; // nothing to do + + // There should never be more than one element matching "div.body" + const divBody = document.querySelectorAll("div.body"); + const body = divBody.length ? divBody[0] : document.querySelector("body"); + window.setTimeout(() => { + terms.forEach((term) => _highlightText(body, term, "highlighted")); + }, 10); + + const searchBox = document.getElementById("searchbox"); + if (searchBox === null) return; + searchBox.appendChild( + document + .createRange() + .createContextualFragment( + '

' + + '' + + Documentation.gettext("Hide Search Matches") + + "

" + ) + ); + }, + + /** + * helper function to hide the search marks again + */ + hideSearchWords: () => { + document + .querySelectorAll("#searchbox .highlight-link") + .forEach((el) => el.remove()); + document + .querySelectorAll("span.highlighted") + .forEach((el) => el.classList.remove("highlighted")); + const url = new URL(window.location); + url.searchParams.delete("highlight"); + window.history.replaceState({}, "", url); + }, + + /** + * helper function to focus on search bar + */ + focusSearchBar: () => { + document.querySelectorAll("input[name=q]")[0]?.focus(); + }, + + /** + * Initialise the domain index toggle buttons + */ + initDomainIndexTable: () => { + const toggler = (el) => { + const idNumber = el.id.substr(7); + const toggledRows = document.querySelectorAll(`tr.cg-${idNumber}`); + if (el.src.substr(-9) === "minus.png") { + el.src = `${el.src.substr(0, el.src.length - 9)}plus.png`; + toggledRows.forEach((el) => (el.style.display = "none")); + } else { + el.src = `${el.src.substr(0, el.src.length - 8)}minus.png`; + toggledRows.forEach((el) => (el.style.display = "")); + } + }; + + const togglerElements = document.querySelectorAll("img.toggler"); + togglerElements.forEach((el) => + el.addEventListener("click", (event) => toggler(event.currentTarget)) + ); + togglerElements.forEach((el) => (el.style.display = "")); + if (DOCUMENTATION_OPTIONS.COLLAPSE_INDEX) togglerElements.forEach(toggler); + }, + + initOnKeyListeners: () => { + // only install a listener if it is really needed + if ( + !DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS && + !DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS + ) + return; + + const blacklistedElements = new Set([ + "TEXTAREA", + "INPUT", + "SELECT", + "BUTTON", + ]); + document.addEventListener("keydown", (event) => { + if (blacklistedElements.has(document.activeElement.tagName)) return; // bail for input elements + if (event.altKey || event.ctrlKey || event.metaKey) return; // bail with special keys + + if 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+ factory( global, true ) : + function( w ) { + if ( !w.document ) { + throw new Error( "jQuery requires a window with a document" ); + } + return factory( w ); + }; + } else { + factory( global ); + } + +// Pass this if window is not defined yet +} )( typeof window !== "undefined" ? window : this, function( window, noGlobal ) { + +// Edge <= 12 - 13+, Firefox <=18 - 45+, IE 10 - 11, Safari 5.1 - 9+, iOS 6 - 9.1 +// throw exceptions when non-strict code (e.g., ASP.NET 4.5) accesses strict mode +// arguments.callee.caller (trac-13335). But as of jQuery 3.0 (2016), strict mode should be common +// enough that all such attempts are guarded in a try block. +"use strict"; + +var arr = []; + +var getProto = Object.getPrototypeOf; + +var slice = arr.slice; + +var flat = arr.flat ? function( array ) { + return arr.flat.call( array ); +} : function( array ) { + return arr.concat.apply( [], array ); +}; + + +var push = arr.push; + +var indexOf = arr.indexOf; + +var class2type = {}; + +var toString = class2type.toString; + +var hasOwn = class2type.hasOwnProperty; + +var fnToString = hasOwn.toString; + +var ObjectFunctionString = fnToString.call( Object ); + +var support = {}; + +var isFunction = function isFunction( obj ) { + + // Support: Chrome <=57, Firefox <=52 + // In some browsers, typeof returns "function" for HTML elements + // (i.e., `typeof document.createElement( "object" ) === "function"`). + // We don't want to classify *any* DOM node as a function. + // Support: QtWeb <=3.8.5, WebKit <=534.34, wkhtmltopdf tool <=0.12.5 + // Plus for old WebKit, typeof returns "function" for HTML collections + // (e.g., `typeof document.getElementsByTagName("div") === "function"`). (gh-4756) + return typeof obj === "function" && typeof obj.nodeType !== "number" && + typeof obj.item !== "function"; + }; + + +var isWindow = function isWindow( obj ) { + return obj != null && obj === obj.window; + }; + + +var document = window.document; + + + + var preservedScriptAttributes = { + type: true, + src: true, + nonce: true, + noModule: true + }; + + function DOMEval( code, node, doc ) { + doc = doc || document; + + var i, val, + script = doc.createElement( "script" ); + + script.text = code; + if ( node ) { + for ( i in preservedScriptAttributes ) { + + // Support: Firefox 64+, Edge 18+ + // Some browsers don't support the "nonce" property on scripts. + // On the other hand, just using `getAttribute` is not enough as + // the `nonce` attribute is reset to an empty string whenever it + // becomes browsing-context connected. + // See https://github.com/whatwg/html/issues/2369 + // See https://html.spec.whatwg.org/#nonce-attributes + // The `node.getAttribute` check was added for the sake of + // `jQuery.globalEval` so that it can fake a nonce-containing node + // via an object. + val = node[ i ] || node.getAttribute && node.getAttribute( i ); + if ( val ) { + script.setAttribute( i, val ); + } + } + } + doc.head.appendChild( script ).parentNode.removeChild( script ); + } + + +function toType( obj ) { + if ( obj == null ) { + return obj + ""; + } + + // Support: Android <=2.3 only (functionish RegExp) + return typeof obj === "object" || typeof obj === "function" ? + class2type[ toString.call( obj ) ] || "object" : + typeof obj; +} +/* global Symbol */ +// Defining this global in .eslintrc.json would create a danger of using the global +// unguarded in another place, it seems safer to define global only for this module + + + +var + version = "3.6.0", + + // Define a local copy of jQuery + jQuery = function( selector, context ) { + + // The jQuery object is actually just the init constructor 'enhanced' + // Need init if jQuery is called (just allow error to be thrown if not included) + return new jQuery.fn.init( selector, context ); + }; + +jQuery.fn = jQuery.prototype = { + + // The current version of jQuery being used + jquery: version, + + constructor: jQuery, + + // The default length of a jQuery object is 0 + length: 0, + + toArray: function() { + return slice.call( this ); + }, + + // Get the Nth element in the matched element set OR + // Get the whole matched element set as a clean array + get: function( num ) { + + // Return all the elements in a clean array + if ( num == null ) { + return slice.call( this ); + } + + // Return just the one element from the set + return num < 0 ? this[ num + this.length ] : this[ num ]; + }, + + // Take an array of elements and push it onto the stack + // (returning the new matched element set) + pushStack: function( elems ) { + + // Build a new jQuery matched element set + var ret = jQuery.merge( this.constructor(), elems ); + + // Add the old object onto the stack (as a reference) + ret.prevObject = this; + + // Return the newly-formed element set + return ret; + }, + + // Execute a callback for every element in the matched set. + each: function( callback ) { + return jQuery.each( this, callback ); + }, + + map: function( callback ) { + return this.pushStack( jQuery.map( this, function( elem, i ) { + return callback.call( elem, i, elem ); + } ) ); + }, + + slice: function() { + return this.pushStack( slice.apply( this, arguments ) ); + }, + + first: function() { + return this.eq( 0 ); + }, + + last: function() { + return this.eq( -1 ); + }, + + even: function() { + return this.pushStack( jQuery.grep( this, function( _elem, i ) { + return ( i + 1 ) % 2; + } ) ); + }, + + odd: function() { + return this.pushStack( jQuery.grep( this, function( _elem, i ) { + return i % 2; + } ) ); + }, + + eq: function( i ) { + var len = this.length, + j = +i + ( i < 0 ? len : 0 ); + return this.pushStack( j >= 0 && j < len ? [ this[ j ] ] : [] ); + }, + + end: function() { + return this.prevObject || this.constructor(); + }, + + // For internal use only. + // Behaves like an Array's method, not like a jQuery method. + push: push, + sort: arr.sort, + splice: arr.splice +}; + +jQuery.extend = jQuery.fn.extend = function() { + var options, name, src, copy, copyIsArray, clone, + target = arguments[ 0 ] || {}, + i = 1, + length = arguments.length, + deep = false; + + // Handle a deep copy situation + if ( typeof target === "boolean" ) { + deep = target; + + // Skip the boolean and the target + target = arguments[ i ] || {}; + i++; + } + + // Handle case when target is a string or something (possible in deep copy) + if ( typeof target !== "object" && !isFunction( target ) ) { + target = {}; + } + + // Extend jQuery itself if only one argument is passed + if ( i === length ) { + target = this; + i--; + } + + for ( ; i < length; i++ ) { + + // Only deal with non-null/undefined values + if ( ( options = arguments[ i ] ) != null ) { + + // Extend the base object + for ( name in options ) { + copy = options[ name ]; + + // Prevent Object.prototype pollution + // Prevent never-ending loop + if ( name === "__proto__" || target === copy ) { + continue; + } + + // Recurse if we're merging plain objects or arrays + if ( deep && copy && ( jQuery.isPlainObject( copy ) || + ( copyIsArray = Array.isArray( copy ) ) ) ) { + src = target[ name ]; + + // Ensure proper type for the source value + if ( copyIsArray && !Array.isArray( src ) ) { + clone = []; + } else if ( !copyIsArray && !jQuery.isPlainObject( src ) ) { + clone = {}; + } else { + clone = src; + } + copyIsArray = false; + + // Never move original objects, clone them + target[ name ] = jQuery.extend( deep, clone, copy ); + + // Don't bring in undefined values + } else if ( copy !== undefined ) { + target[ name ] = copy; + } + } + } + } + + // Return the modified object + return target; +}; + +jQuery.extend( { + + // Unique for each copy of jQuery on the page + expando: "jQuery" + ( version + Math.random() ).replace( /\D/g, "" ), + + // Assume jQuery is ready without the ready module + isReady: true, + + error: function( msg ) { + throw new Error( msg ); + }, + + noop: function() {}, + + isPlainObject: function( obj ) { + var proto, Ctor; + + // Detect obvious negatives + // Use toString instead of jQuery.type to catch host objects + if ( !obj || toString.call( obj ) !== "[object Object]" ) { + return false; + } + + proto = getProto( obj ); + + // Objects with no prototype (e.g., `Object.create( null )`) are plain + if ( !proto ) { + return true; + } + + // Objects with prototype are plain iff they were constructed by a global Object function + Ctor = hasOwn.call( proto, "constructor" ) && proto.constructor; + return typeof Ctor === "function" && fnToString.call( Ctor ) === ObjectFunctionString; + }, + + isEmptyObject: function( obj ) { + var name; + + for ( name in obj ) { + return false; + } + return true; + }, + + // Evaluates a script in a provided context; falls back to the global one + // if not specified. + globalEval: function( code, options, doc ) { + DOMEval( code, { nonce: options && options.nonce }, doc ); + }, + + each: function( obj, callback ) { + var length, i = 0; + + if ( isArrayLike( obj ) ) { + length = obj.length; + for ( ; i < length; i++ ) { + if ( callback.call( obj[ i ], i, obj[ i ] ) === false ) { + break; + } + } + } else { + for ( i in obj ) { + if ( callback.call( obj[ i ], i, obj[ i ] ) === false ) { + break; + } + } + } + + return obj; + }, + + // results is for internal usage only + makeArray: function( arr, results ) { + var ret = results || []; + + if ( arr != null ) { + if ( isArrayLike( Object( arr ) ) ) { + jQuery.merge( ret, + typeof arr === "string" ? + [ arr ] : arr + ); + } else { + push.call( ret, arr ); + } + } + + return ret; + }, + + inArray: function( elem, arr, i ) { + return arr == null ? -1 : indexOf.call( arr, elem, i ); + }, + + // Support: Android <=4.0 only, PhantomJS 1 only + // push.apply(_, arraylike) throws on ancient WebKit + merge: function( first, second ) { + var len = +second.length, + j = 0, + i = first.length; + + for ( ; j < len; j++ ) { + first[ i++ ] = second[ j ]; + } + + first.length = i; + + return first; + }, + + grep: function( elems, callback, invert ) { + var callbackInverse, + matches = [], + i = 0, + length = elems.length, + callbackExpect = !invert; + + // Go through the array, only saving the items + // that pass the validator function + for ( ; i < length; i++ ) { + callbackInverse = !callback( elems[ i ], i ); + if ( callbackInverse !== callbackExpect ) { + matches.push( elems[ i ] ); + } + } + + return matches; + }, + + // arg is for internal usage only + map: function( elems, callback, arg ) { + var length, value, + i = 0, + ret = []; + + // Go through the array, translating each of the items to their new values + if ( isArrayLike( elems ) ) { + length = elems.length; + for ( ; i < length; i++ ) { + value = callback( elems[ i ], i, arg ); + + if ( value != null ) { + ret.push( value ); + } + } + + // Go through every key on the object, + } else { + for ( i in elems ) { + value = callback( elems[ i ], i, arg ); + + if ( value != null ) { + ret.push( value ); + } + } + } + + // Flatten any nested arrays + return flat( ret ); + }, + + // A global GUID counter for objects + guid: 1, + + // jQuery.support is not used in Core but other projects attach their + // properties to it so it needs to exist. + support: support +} ); + +if ( typeof Symbol === "function" ) { + jQuery.fn[ Symbol.iterator ] = arr[ Symbol.iterator ]; +} + +// Populate the class2type map +jQuery.each( "Boolean Number String Function Array Date RegExp Object Error Symbol".split( " " ), + function( _i, name ) { + class2type[ "[object " + name + "]" ] = name.toLowerCase(); + } ); + +function isArrayLike( obj ) { + + // Support: real iOS 8.2 only (not reproducible in simulator) + // `in` check used to prevent JIT error (gh-2145) + // hasOwn isn't used here due to false negatives + // regarding Nodelist length in IE + var length = !!obj && "length" in obj && obj.length, + type = toType( obj ); + + if ( isFunction( obj ) || isWindow( obj ) ) { + return false; + } + + return type === "array" || length === 0 || + typeof length === "number" && length > 0 && ( length - 1 ) in obj; +} +var Sizzle = +/*! + * Sizzle CSS Selector Engine v2.3.6 + * https://sizzlejs.com/ + * + * Copyright JS Foundation and other contributors + * Released under the MIT license + * https://js.foundation/ + * + * Date: 2021-02-16 + */ +( function( window ) { +var i, + support, + Expr, + getText, + isXML, + tokenize, + compile, + select, + outermostContext, + sortInput, + hasDuplicate, + + // Local document vars + setDocument, + document, + docElem, + documentIsHTML, + rbuggyQSA, + rbuggyMatches, + matches, + contains, + + // Instance-specific data + expando = "sizzle" + 1 * new Date(), + preferredDoc = window.document, + dirruns = 0, + done = 0, + classCache = createCache(), + tokenCache = createCache(), + compilerCache = createCache(), + nonnativeSelectorCache = createCache(), + sortOrder = function( a, b ) { + if ( a === b ) { + hasDuplicate = true; + } + return 0; + }, + + // Instance methods + hasOwn = ( {} ).hasOwnProperty, + arr = [], + pop = arr.pop, + pushNative = arr.push, + push = arr.push, + slice = arr.slice, + + // Use a stripped-down indexOf as it's faster than native + // https://jsperf.com/thor-indexof-vs-for/5 + indexOf = function( list, elem ) { + var i = 0, + len = list.length; + for ( ; i < len; i++ ) { + if ( list[ i ] === elem ) { + return i; + } + } + return -1; + }, + + booleans = "checked|selected|async|autofocus|autoplay|controls|defer|disabled|hidden|" + + "ismap|loop|multiple|open|readonly|required|scoped", + + // Regular expressions + + // http://www.w3.org/TR/css3-selectors/#whitespace + whitespace = "[\\x20\\t\\r\\n\\f]", + + // https://www.w3.org/TR/css-syntax-3/#ident-token-diagram + identifier = "(?:\\\\[\\da-fA-F]{1,6}" + whitespace + + "?|\\\\[^\\r\\n\\f]|[\\w-]|[^\0-\\x7f])+", + + // Attribute selectors: http://www.w3.org/TR/selectors/#attribute-selectors + attributes = "\\[" + whitespace + "*(" + identifier + ")(?:" + whitespace + + + // Operator (capture 2) + "*([*^$|!~]?=)" + whitespace + + + // "Attribute values must be CSS identifiers [capture 5] + // or strings [capture 3 or capture 4]" + "*(?:'((?:\\\\.|[^\\\\'])*)'|\"((?:\\\\.|[^\\\\\"])*)\"|(" + identifier + "))|)" + + whitespace + "*\\]", + + pseudos = ":(" + identifier + ")(?:\\((" + + + // To reduce the number of selectors needing tokenize in the preFilter, prefer arguments: + // 1. quoted (capture 3; capture 4 or capture 5) + "('((?:\\\\.|[^\\\\'])*)'|\"((?:\\\\.|[^\\\\\"])*)\")|" + + + // 2. simple (capture 6) + "((?:\\\\.|[^\\\\()[\\]]|" + attributes + ")*)|" + + + // 3. anything else (capture 2) + ".*" + + ")\\)|)", + + // Leading and non-escaped trailing whitespace, capturing some non-whitespace characters preceding the latter + rwhitespace = new RegExp( whitespace + "+", "g" ), + rtrim = new RegExp( "^" + whitespace + "+|((?:^|[^\\\\])(?:\\\\.)*)" + + whitespace + "+$", "g" ), + + rcomma = new RegExp( "^" + whitespace + "*," + whitespace + "*" ), + rcombinators = new RegExp( "^" + whitespace + "*([>+~]|" + whitespace + ")" + whitespace + + "*" ), + rdescend = new RegExp( whitespace + "|>" ), + + rpseudo = new RegExp( pseudos ), + ridentifier = new RegExp( "^" + identifier + "$" ), + + matchExpr = { + "ID": new RegExp( "^#(" + identifier + ")" ), + "CLASS": new RegExp( "^\\.(" + identifier + ")" ), + "TAG": new RegExp( "^(" + identifier + "|[*])" ), + "ATTR": new RegExp( "^" + attributes ), + "PSEUDO": new RegExp( "^" + pseudos ), + "CHILD": new RegExp( "^:(only|first|last|nth|nth-last)-(child|of-type)(?:\\(" + + whitespace + "*(even|odd|(([+-]|)(\\d*)n|)" + whitespace + "*(?:([+-]|)" + + whitespace + "*(\\d+)|))" + whitespace + "*\\)|)", "i" ), + "bool": new RegExp( "^(?:" + booleans + ")$", "i" ), + + // For use in libraries implementing .is() + // We use this for POS matching in `select` + "needsContext": new RegExp( "^" + whitespace + + "*[>+~]|:(even|odd|eq|gt|lt|nth|first|last)(?:\\(" + whitespace + + "*((?:-\\d)?\\d*)" + whitespace + "*\\)|)(?=[^-]|$)", "i" ) + }, + + rhtml = /HTML$/i, + rinputs = /^(?:input|select|textarea|button)$/i, + rheader = /^h\d$/i, + + rnative = /^[^{]+\{\s*\[native \w/, + + // Easily-parseable/retrievable ID or TAG or CLASS selectors + rquickExpr = /^(?:#([\w-]+)|(\w+)|\.([\w-]+))$/, + + rsibling = /[+~]/, + + // CSS escapes + // http://www.w3.org/TR/CSS21/syndata.html#escaped-characters + runescape = new RegExp( "\\\\[\\da-fA-F]{1,6}" + whitespace + "?|\\\\([^\\r\\n\\f])", "g" ), + funescape = function( escape, nonHex ) { + var high = "0x" + escape.slice( 1 ) - 0x10000; + + return nonHex ? + + // Strip the backslash prefix from a non-hex escape sequence + nonHex : + + // Replace a hexadecimal escape sequence with the encoded Unicode code point + // Support: IE <=11+ + // For values outside the Basic Multilingual Plane (BMP), manually construct a + // surrogate pair + high < 0 ? + String.fromCharCode( high + 0x10000 ) : + String.fromCharCode( high >> 10 | 0xD800, high & 0x3FF | 0xDC00 ); + }, + + // CSS string/identifier serialization + // https://drafts.csswg.org/cssom/#common-serializing-idioms + rcssescape = /([\0-\x1f\x7f]|^-?\d)|^-$|[^\0-\x1f\x7f-\uFFFF\w-]/g, + fcssescape = function( ch, asCodePoint ) { + if ( asCodePoint ) { + + // U+0000 NULL becomes U+FFFD REPLACEMENT CHARACTER + if ( ch === "\0" ) { + return "\uFFFD"; + } + + // Control characters and (dependent upon position) numbers get escaped as code points + return ch.slice( 0, -1 ) + "\\" + + ch.charCodeAt( ch.length - 1 ).toString( 16 ) + " "; + } + + // Other potentially-special ASCII characters get backslash-escaped + return "\\" + ch; + }, + + // Used for iframes + // See setDocument() + // Removing the function wrapper causes a "Permission Denied" + // error in IE + unloadHandler = function() { + setDocument(); + }, + + inDisabledFieldset = addCombinator( + function( elem ) { + return elem.disabled === true && elem.nodeName.toLowerCase() === "fieldset"; + }, + { dir: "parentNode", next: "legend" } + ); + +// Optimize for push.apply( _, NodeList ) +try { + push.apply( + ( arr = slice.call( preferredDoc.childNodes ) ), + preferredDoc.childNodes + ); + + // Support: Android<4.0 + // Detect silently failing push.apply + // eslint-disable-next-line no-unused-expressions + arr[ preferredDoc.childNodes.length ].nodeType; +} catch ( e ) { + push = { apply: arr.length ? + + // Leverage slice if possible + function( target, els ) { + pushNative.apply( target, slice.call( els ) ); + } : + + // Support: IE<9 + // Otherwise append directly + function( target, els ) { + var j = target.length, + i = 0; + + // Can't trust NodeList.length + while ( ( target[ j++ ] = els[ i++ ] ) ) {} + target.length = j - 1; + } + }; +} + +function Sizzle( selector, context, results, seed ) { + var m, i, elem, nid, match, groups, newSelector, + newContext = context && context.ownerDocument, + + // nodeType defaults to 9, since context defaults to document + nodeType = context ? context.nodeType : 9; + + results = results || []; + + // Return early from calls with invalid selector or context + if ( typeof selector !== "string" || !selector || + nodeType !== 1 && nodeType !== 9 && nodeType !== 11 ) { + + return results; + } + + // Try to shortcut find operations (as opposed to filters) in HTML documents + if ( !seed ) { + setDocument( context ); + context = context || document; + + if ( documentIsHTML ) { + + // If the selector is sufficiently simple, try using a "get*By*" DOM method + // (excepting DocumentFragment context, where the methods don't exist) + if ( nodeType !== 11 && ( match = rquickExpr.exec( selector ) ) ) { + + // ID selector + if ( ( m = match[ 1 ] ) ) { + + // Document context + if ( nodeType === 9 ) { + if ( ( elem = context.getElementById( m ) ) ) { + + // Support: IE, Opera, Webkit + // TODO: identify versions + // getElementById can match elements by name instead of ID + if ( elem.id === m ) { + results.push( elem ); + return results; + } + } else { + return results; + } + + // Element context + } else { + + // Support: IE, Opera, Webkit + // TODO: identify versions + // getElementById can match elements by name instead of ID + if ( newContext && ( elem = newContext.getElementById( m ) ) && + contains( context, elem ) && + elem.id === m ) { + + results.push( elem ); + return results; + } + } + + // Type selector + } else if ( match[ 2 ] ) { + push.apply( results, context.getElementsByTagName( selector ) ); + return results; + + // Class selector + } else if ( ( m = match[ 3 ] ) && support.getElementsByClassName && + context.getElementsByClassName ) { + + push.apply( results, context.getElementsByClassName( m ) ); + return results; + } + } + + // Take advantage of querySelectorAll + if ( support.qsa && + !nonnativeSelectorCache[ selector + " " ] && + ( !rbuggyQSA || !rbuggyQSA.test( selector ) ) && + + // Support: IE 8 only + // Exclude object elements + ( nodeType !== 1 || context.nodeName.toLowerCase() !== "object" ) ) { + + newSelector = selector; + newContext = context; + + // qSA considers elements outside a scoping root when evaluating child or + // descendant combinators, which is not what we want. + // In such cases, we work around the behavior by prefixing every selector in the + // list with an ID selector referencing the scope context. + // The technique has to be used as well when a leading combinator is used + // as such selectors are not recognized by querySelectorAll. + // Thanks to Andrew Dupont for this technique. + if ( nodeType === 1 && + ( rdescend.test( selector ) || rcombinators.test( selector ) ) ) { + + // Expand context for sibling selectors + newContext = rsibling.test( selector ) && testContext( context.parentNode ) || + context; + + // We can use :scope instead of the ID hack if the browser + // supports it & if we're not changing the context. + if ( newContext !== context || !support.scope ) { + + // Capture the context ID, setting it first if necessary + if ( ( nid = context.getAttribute( "id" ) ) ) { + nid = nid.replace( rcssescape, fcssescape ); + } else { + context.setAttribute( "id", ( nid = expando ) ); + } + } + + // Prefix every selector in the list + groups = tokenize( selector ); + i = groups.length; + while ( i-- ) { + groups[ i ] = ( nid ? "#" + nid : ":scope" ) + " " + + toSelector( groups[ i ] ); + } + newSelector = groups.join( "," ); + } + + try { + push.apply( results, + newContext.querySelectorAll( newSelector ) + ); + return results; + } catch ( qsaError ) { + nonnativeSelectorCache( selector, true ); + } finally { + if ( nid === expando ) { + context.removeAttribute( "id" ); + } + } + } + } + } + + // All others + return select( selector.replace( rtrim, "$1" ), context, results, seed ); +} + +/** + * Create key-value caches of limited size + * @returns {function(string, object)} Returns the Object data after storing it on itself with + * property name the (space-suffixed) string and (if the cache is larger than Expr.cacheLength) + * deleting the oldest entry + */ +function createCache() { + var keys = []; + + function cache( key, value ) { + + // Use (key + " ") to avoid collision with native prototype properties (see Issue #157) + if ( keys.push( key + " " ) > Expr.cacheLength ) { + + // Only keep the most recent entries + delete cache[ keys.shift() ]; + } + return ( cache[ key + " " ] = value ); + } + return cache; +} + +/** + * Mark a function for special use by Sizzle + * @param {Function} fn The function to mark + */ +function markFunction( fn ) { + fn[ expando ] = true; + return fn; +} + +/** + * Support testing using an element + * @param {Function} fn Passed the created element and returns a boolean result + */ +function assert( fn ) { + var el = document.createElement( "fieldset" ); + + try { + return !!fn( el ); + } catch ( e ) { + return false; + } finally { + + // Remove from its parent by default + if ( el.parentNode ) { + el.parentNode.removeChild( el ); + } + + // release memory in IE + el = null; + } +} + +/** + * Adds the same handler for all of the specified attrs + * @param {String} attrs Pipe-separated list of attributes + * @param {Function} handler The method that will be applied + */ +function addHandle( attrs, handler ) { + var arr = attrs.split( "|" ), + i = arr.length; + + while ( i-- ) { + Expr.attrHandle[ arr[ i ] ] = handler; + } +} + +/** + * Checks document order of two siblings + * @param {Element} a + * @param {Element} b + * @returns {Number} Returns less than 0 if a precedes b, greater than 0 if a follows b + */ +function siblingCheck( a, b ) { + var cur = b && a, + diff = cur && a.nodeType === 1 && b.nodeType === 1 && + a.sourceIndex - b.sourceIndex; + + // Use IE sourceIndex if available on both nodes + if ( diff ) { + return diff; + } + + // Check if b follows a + if ( cur ) { + while ( ( cur = cur.nextSibling ) ) { + if ( cur === b ) { + return -1; + } + } + } + + return a ? 1 : -1; +} + +/** + * Returns a function to use in pseudos for input types + * @param {String} type + */ +function createInputPseudo( type ) { + return function( elem ) { + var name = elem.nodeName.toLowerCase(); + return name === "input" && elem.type === type; + }; +} + +/** + * Returns a function to use in pseudos for buttons + * @param {String} type + */ +function createButtonPseudo( type ) { + return function( elem ) { + var name = elem.nodeName.toLowerCase(); + return ( name === "input" || name === "button" ) && elem.type === type; + }; +} + +/** + * Returns a function to use in pseudos for :enabled/:disabled + * @param {Boolean} disabled true for :disabled; false for :enabled + */ +function createDisabledPseudo( disabled ) { + + // Known :disabled false positives: fieldset[disabled] > legend:nth-of-type(n+2) :can-disable + return function( elem ) { + + // Only certain elements can match :enabled or :disabled + // https://html.spec.whatwg.org/multipage/scripting.html#selector-enabled + // https://html.spec.whatwg.org/multipage/scripting.html#selector-disabled + if ( "form" in elem ) { + + // Check for inherited disabledness on relevant non-disabled elements: + // * listed form-associated elements in a disabled fieldset + // https://html.spec.whatwg.org/multipage/forms.html#category-listed + // https://html.spec.whatwg.org/multipage/forms.html#concept-fe-disabled + // * option elements in a disabled optgroup + // https://html.spec.whatwg.org/multipage/forms.html#concept-option-disabled + // All such elements have a "form" property. + if ( elem.parentNode && elem.disabled === false ) { + + // Option elements defer to a parent optgroup if present + if ( "label" in elem ) { + if ( "label" in elem.parentNode ) { + return elem.parentNode.disabled === disabled; + } else { + return elem.disabled === disabled; + } + } + + // Support: IE 6 - 11 + // Use the isDisabled shortcut property to check for disabled fieldset ancestors + return elem.isDisabled === disabled || + + // Where there is no isDisabled, check manually + /* jshint -W018 */ + elem.isDisabled !== !disabled && + inDisabledFieldset( elem ) === disabled; + } + + return elem.disabled === disabled; + + // Try to winnow out elements that can't be disabled before trusting the disabled property. + // Some victims get caught in our net (label, legend, menu, track), but it shouldn't + // even exist on them, let alone have a boolean value. + } else if ( "label" in elem ) { + return elem.disabled === disabled; + } + + // Remaining elements are neither :enabled nor :disabled + return false; + }; +} + +/** + * Returns a function to use in pseudos for positionals + * @param {Function} fn + */ +function createPositionalPseudo( fn ) { + return markFunction( function( argument ) { + argument = +argument; + return markFunction( function( seed, matches ) { + var j, + matchIndexes = fn( [], seed.length, argument ), + i = matchIndexes.length; + + // Match elements found at the specified indexes + while ( i-- ) { + if ( seed[ ( j = matchIndexes[ i ] ) ] ) { + seed[ j ] = !( matches[ j ] = seed[ j ] ); + } + } + } ); + } ); +} + +/** + * Checks a node for validity as a Sizzle context + * @param {Element|Object=} context + * @returns {Element|Object|Boolean} The input node if acceptable, otherwise a falsy value + */ +function testContext( context ) { + return context && typeof context.getElementsByTagName !== "undefined" && context; +} + +// Expose support vars for convenience +support = Sizzle.support = {}; + +/** + * Detects XML nodes + * @param {Element|Object} elem An element or a document + * @returns {Boolean} True iff elem is a non-HTML XML node + */ +isXML = Sizzle.isXML = function( elem ) { + var namespace = elem && elem.namespaceURI, + docElem = elem && ( elem.ownerDocument || elem ).documentElement; + + // Support: IE <=8 + // Assume HTML when documentElement doesn't yet exist, such as inside loading iframes + // https://bugs.jquery.com/ticket/4833 + return !rhtml.test( namespace || docElem && docElem.nodeName || "HTML" ); +}; + +/** + * Sets document-related variables once based on the current document + * @param {Element|Object} [doc] An element or document object to use to set the document + * @returns {Object} Returns the current document + */ +setDocument = Sizzle.setDocument = function( node ) { + var hasCompare, subWindow, + doc = node ? node.ownerDocument || node : preferredDoc; + + // Return early if doc is invalid or already selected + // Support: IE 11+, Edge 17 - 18+ + // IE/Edge sometimes throw a "Permission denied" error when strict-comparing + // two documents; shallow comparisons work. + // eslint-disable-next-line eqeqeq + if ( doc == document || doc.nodeType !== 9 || !doc.documentElement ) { + return document; + } + + // Update global variables + document = doc; + docElem = document.documentElement; + documentIsHTML = !isXML( document ); + + // Support: IE 9 - 11+, Edge 12 - 18+ + // Accessing iframe documents after unload throws "permission denied" errors (jQuery #13936) + // Support: IE 11+, Edge 17 - 18+ + // IE/Edge sometimes throw a "Permission denied" error when strict-comparing + // two documents; shallow comparisons work. + // eslint-disable-next-line eqeqeq + if ( preferredDoc != document && + ( subWindow = document.defaultView ) && subWindow.top !== subWindow ) { + + // Support: IE 11, Edge + if ( subWindow.addEventListener ) { + subWindow.addEventListener( "unload", unloadHandler, false ); + + // Support: IE 9 - 10 only + } else if ( subWindow.attachEvent ) { + subWindow.attachEvent( "onunload", unloadHandler ); + } + } + + // Support: IE 8 - 11+, Edge 12 - 18+, Chrome <=16 - 25 only, Firefox <=3.6 - 31 only, + // Safari 4 - 5 only, Opera <=11.6 - 12.x only + // IE/Edge & older browsers don't support the :scope pseudo-class. + // Support: Safari 6.0 only + // Safari 6.0 supports :scope but it's an alias of :root there. + support.scope = assert( function( el ) { + docElem.appendChild( el ).appendChild( document.createElement( "div" ) ); + return typeof el.querySelectorAll !== "undefined" && + !el.querySelectorAll( ":scope fieldset div" ).length; + } ); + + /* Attributes + ---------------------------------------------------------------------- */ + + // Support: IE<8 + // Verify that getAttribute really returns attributes and not properties + // (excepting IE8 booleans) + support.attributes = assert( function( el ) { + el.className = "i"; + return !el.getAttribute( "className" ); + } ); + + /* getElement(s)By* + ---------------------------------------------------------------------- */ + + // Check if getElementsByTagName("*") returns only elements + support.getElementsByTagName = assert( function( el ) { + el.appendChild( document.createComment( "" ) ); + return !el.getElementsByTagName( "*" ).length; + } ); + + // Support: IE<9 + support.getElementsByClassName = rnative.test( document.getElementsByClassName ); + + // Support: IE<10 + // Check if getElementById returns elements by name + // The broken getElementById methods don't pick up programmatically-set names, + // so use a roundabout getElementsByName test + support.getById = assert( function( el ) { + docElem.appendChild( el ).id = expando; + return !document.getElementsByName || !document.getElementsByName( expando ).length; + } ); + + // ID filter and find + if ( support.getById ) { + Expr.filter[ "ID" ] = function( id ) { + var attrId = id.replace( runescape, funescape ); + return function( elem ) { + return elem.getAttribute( "id" ) === attrId; + }; + }; + Expr.find[ "ID" ] = function( id, context ) { + if ( typeof context.getElementById !== "undefined" && documentIsHTML ) { + var elem = context.getElementById( id ); + return elem ? [ elem ] : []; + } + }; + } else { + Expr.filter[ "ID" ] = function( id ) { + var attrId = id.replace( runescape, funescape ); + return function( elem ) { + var node = typeof elem.getAttributeNode !== "undefined" && + elem.getAttributeNode( "id" ); + return node && node.value === attrId; + }; + }; + + // Support: IE 6 - 7 only + // getElementById is not reliable as a find shortcut + Expr.find[ "ID" ] = function( id, context ) { + if ( typeof context.getElementById !== "undefined" && documentIsHTML ) { + var node, i, elems, + elem = context.getElementById( id ); + + if ( elem ) { + + // Verify the id attribute + node = elem.getAttributeNode( "id" ); + if ( node && node.value === id ) { + return [ elem ]; + } + + // Fall back on getElementsByName + elems = context.getElementsByName( id ); + i = 0; + while ( ( elem = elems[ i++ ] ) ) { + node = elem.getAttributeNode( "id" ); + if ( node && node.value === id ) { + return [ elem ]; + } + } + } + + return []; + } + }; + } + + // Tag + Expr.find[ "TAG" ] = support.getElementsByTagName ? + function( tag, context ) { + if ( typeof context.getElementsByTagName !== "undefined" ) { + return context.getElementsByTagName( tag ); + + // DocumentFragment nodes don't have gEBTN + } else if ( support.qsa ) { + return context.querySelectorAll( tag ); + } + } : + + function( tag, context ) { + var elem, + tmp = [], + i = 0, + + // By happy coincidence, a (broken) gEBTN appears on DocumentFragment nodes too + results = context.getElementsByTagName( tag ); + + // Filter out possible comments + if ( tag === "*" ) { + while ( ( elem = results[ i++ ] ) ) { + if ( elem.nodeType === 1 ) { + tmp.push( elem ); + } + } + + return tmp; + } + return results; + }; + + // Class + Expr.find[ "CLASS" ] = support.getElementsByClassName && function( className, context ) { + if ( typeof context.getElementsByClassName !== "undefined" && documentIsHTML ) { + return context.getElementsByClassName( className ); + } + }; + + /* QSA/matchesSelector + ---------------------------------------------------------------------- */ + + // QSA and matchesSelector support + + // matchesSelector(:active) reports false when true (IE9/Opera 11.5) + rbuggyMatches = []; + + // qSa(:focus) reports false when true (Chrome 21) + // We allow this because of a bug in IE8/9 that throws an error + // whenever `document.activeElement` is accessed on an iframe + // So, we allow :focus to pass through QSA all the time to avoid the IE error + // See https://bugs.jquery.com/ticket/13378 + rbuggyQSA = []; + + if ( ( support.qsa = rnative.test( document.querySelectorAll ) ) ) { + + // Build QSA regex + // Regex strategy adopted from Diego Perini + assert( function( el ) { + + var input; + + // Select is set to empty string on purpose + // This is to test IE's treatment of not explicitly + // setting a boolean content attribute, + // since its presence should be enough + // https://bugs.jquery.com/ticket/12359 + docElem.appendChild( el ).innerHTML = "" + + ""; + + // Support: IE8, Opera 11-12.16 + // Nothing should be selected when empty strings follow ^= or $= or *= + // The test attribute must be unknown in Opera but "safe" for WinRT + // https://msdn.microsoft.com/en-us/library/ie/hh465388.aspx#attribute_section + if ( el.querySelectorAll( "[msallowcapture^='']" ).length ) { + rbuggyQSA.push( "[*^$]=" + whitespace + "*(?:''|\"\")" ); + } + + // Support: IE8 + // Boolean attributes and "value" are not treated correctly + if ( !el.querySelectorAll( "[selected]" ).length ) { + rbuggyQSA.push( "\\[" + whitespace + "*(?:value|" + booleans + ")" ); + } + + // Support: Chrome<29, Android<4.4, Safari<7.0+, iOS<7.0+, PhantomJS<1.9.8+ + if ( !el.querySelectorAll( "[id~=" + expando + "-]" ).length ) { + rbuggyQSA.push( "~=" ); + } + + // Support: IE 11+, Edge 15 - 18+ + // IE 11/Edge don't find elements on a `[name='']` query in some cases. + // Adding a temporary attribute to the document before the selection works + // around the issue. + // Interestingly, IE 10 & older don't seem to have the issue. + input = document.createElement( "input" ); + input.setAttribute( "name", "" ); + el.appendChild( input ); + if ( !el.querySelectorAll( "[name='']" ).length ) { + rbuggyQSA.push( "\\[" + whitespace + "*name" + whitespace + "*=" + + whitespace + "*(?:''|\"\")" ); + } + + // Webkit/Opera - :checked should return selected option elements + // http://www.w3.org/TR/2011/REC-css3-selectors-20110929/#checked + // IE8 throws error here and will not see later tests + if ( !el.querySelectorAll( ":checked" ).length ) { + rbuggyQSA.push( ":checked" ); + } + + // Support: Safari 8+, iOS 8+ + // https://bugs.webkit.org/show_bug.cgi?id=136851 + // In-page `selector#id sibling-combinator selector` fails + if ( !el.querySelectorAll( "a#" + expando + "+*" ).length ) { + rbuggyQSA.push( ".#.+[+~]" ); + } + + // Support: Firefox <=3.6 - 5 only + // Old Firefox doesn't throw on a badly-escaped identifier. + el.querySelectorAll( "\\\f" ); + rbuggyQSA.push( "[\\r\\n\\f]" ); + } ); + + assert( function( el ) { + el.innerHTML = "" + + ""; + + // Support: Windows 8 Native Apps + // The type and name attributes are restricted during .innerHTML assignment + var input = document.createElement( "input" ); + input.setAttribute( "type", "hidden" ); + el.appendChild( input ).setAttribute( "name", "D" ); + + // Support: IE8 + // Enforce case-sensitivity of name attribute + if ( el.querySelectorAll( "[name=d]" ).length ) { + rbuggyQSA.push( "name" + whitespace + "*[*^$|!~]?=" ); + } + + // FF 3.5 - :enabled/:disabled and hidden elements (hidden elements are still enabled) + // IE8 throws error here and will not see later tests + if ( el.querySelectorAll( ":enabled" ).length !== 2 ) { + rbuggyQSA.push( ":enabled", ":disabled" ); + } + + // Support: IE9-11+ + // IE's :disabled selector does not pick up the children of disabled fieldsets + docElem.appendChild( el ).disabled = true; + if ( el.querySelectorAll( ":disabled" ).length !== 2 ) { + rbuggyQSA.push( ":enabled", ":disabled" ); + } + + // Support: Opera 10 - 11 only + // Opera 10-11 does not throw on post-comma invalid pseudos + el.querySelectorAll( "*,:x" ); + rbuggyQSA.push( ",.*:" ); + } ); + } + + if ( ( support.matchesSelector = rnative.test( ( matches = docElem.matches || + docElem.webkitMatchesSelector || + docElem.mozMatchesSelector || + docElem.oMatchesSelector || + docElem.msMatchesSelector ) ) ) ) { + + assert( function( el ) { + + // Check to see if it's possible to do matchesSelector + // on a disconnected node (IE 9) + support.disconnectedMatch = matches.call( el, "*" ); + + // This should fail with an exception + // Gecko does not error, returns false instead + matches.call( el, "[s!='']:x" ); + rbuggyMatches.push( "!=", pseudos ); + } ); + } + + rbuggyQSA = rbuggyQSA.length && new RegExp( rbuggyQSA.join( "|" ) ); + rbuggyMatches = rbuggyMatches.length && new RegExp( rbuggyMatches.join( "|" ) ); + + /* Contains + ---------------------------------------------------------------------- */ + hasCompare = rnative.test( docElem.compareDocumentPosition ); + + // Element contains another + // Purposefully self-exclusive + // As in, an element does not contain itself + contains = hasCompare || rnative.test( docElem.contains ) ? + function( a, b ) { + var adown = a.nodeType === 9 ? a.documentElement : a, + bup = b && b.parentNode; + return a === bup || !!( bup && bup.nodeType === 1 && ( + adown.contains ? + adown.contains( bup ) : + a.compareDocumentPosition && a.compareDocumentPosition( bup ) & 16 + ) ); + } : + function( a, b ) { + if ( b ) { + while ( ( b = b.parentNode ) ) { + if ( b === a ) { + return true; + } + } + } + return false; + }; + + /* Sorting + ---------------------------------------------------------------------- */ + + // Document order sorting + sortOrder = hasCompare ? + function( a, b ) { + + // Flag for duplicate removal + if ( a === b ) { + hasDuplicate = true; + return 0; + } + + // Sort on method existence if only one input has compareDocumentPosition + var compare = !a.compareDocumentPosition - !b.compareDocumentPosition; + if ( compare ) { + return compare; + } + + // Calculate position if both inputs belong to the same document + // Support: IE 11+, Edge 17 - 18+ + // IE/Edge sometimes throw a "Permission denied" error when strict-comparing + // two documents; shallow comparisons work. + // eslint-disable-next-line eqeqeq + compare = ( a.ownerDocument || a ) == ( b.ownerDocument || b ) ? + a.compareDocumentPosition( b ) : + + // Otherwise we know they are disconnected + 1; + + // Disconnected nodes + if ( compare & 1 || + ( !support.sortDetached && b.compareDocumentPosition( a ) === compare ) ) { + + // Choose the first element that is related to our preferred document + // Support: IE 11+, Edge 17 - 18+ + // IE/Edge sometimes throw a "Permission denied" error when strict-comparing + // two documents; shallow comparisons work. + // eslint-disable-next-line eqeqeq + if ( a == document || a.ownerDocument == preferredDoc && + contains( preferredDoc, a ) ) { + return -1; + } + + // Support: IE 11+, Edge 17 - 18+ + // IE/Edge sometimes throw a "Permission denied" error when strict-comparing + // two documents; shallow comparisons work. + // eslint-disable-next-line eqeqeq + if ( b == document || b.ownerDocument == preferredDoc && + contains( preferredDoc, b ) ) { + return 1; + } + + // Maintain original order + return sortInput ? + ( indexOf( sortInput, a ) - indexOf( sortInput, b ) ) : + 0; + } + + return compare & 4 ? -1 : 1; + } : + function( a, b ) { + + // Exit early if the nodes are identical + if ( a === b ) { + hasDuplicate = true; + return 0; + } + + var cur, + i = 0, + aup = a.parentNode, + bup = b.parentNode, + ap = [ a ], + bp = [ b ]; + + // Parentless nodes are either documents or disconnected + if ( !aup || !bup ) { + + // Support: IE 11+, Edge 17 - 18+ + // IE/Edge sometimes throw a "Permission denied" error when strict-comparing + // two documents; shallow comparisons work. + /* eslint-disable eqeqeq */ + return a == document ? -1 : + b == document ? 1 : + /* eslint-enable eqeqeq */ + aup ? -1 : + bup ? 1 : + sortInput ? + ( indexOf( sortInput, a ) - indexOf( sortInput, b ) ) : + 0; + + // If the nodes are siblings, we can do a quick check + } else if ( aup === bup ) { + return siblingCheck( a, b ); + } + + // Otherwise we need full lists of their ancestors for comparison + cur = a; + while ( ( cur = cur.parentNode ) ) { + ap.unshift( cur ); + } + cur = b; + while ( ( cur = cur.parentNode ) ) { + bp.unshift( cur ); + } + + // Walk down the tree looking for a discrepancy + while ( ap[ i ] === bp[ i ] ) { + i++; + } + + return i ? + + // Do a sibling check if the nodes have a common ancestor + siblingCheck( ap[ i ], bp[ i ] ) : + + // Otherwise nodes in our document sort first + // Support: IE 11+, Edge 17 - 18+ + // IE/Edge sometimes throw a "Permission denied" error when strict-comparing + // two documents; shallow comparisons work. + /* eslint-disable eqeqeq */ + ap[ i ] == preferredDoc ? -1 : + bp[ i ] == preferredDoc ? 1 : + /* eslint-enable eqeqeq */ + 0; + }; + + return document; +}; + +Sizzle.matches = function( expr, elements ) { + return Sizzle( expr, null, null, elements ); +}; + +Sizzle.matchesSelector = function( elem, expr ) { + setDocument( elem ); + + if ( support.matchesSelector && documentIsHTML && + !nonnativeSelectorCache[ expr + " " ] && + ( !rbuggyMatches || !rbuggyMatches.test( expr ) ) && + ( !rbuggyQSA || !rbuggyQSA.test( expr ) ) ) { + + try { + var ret = matches.call( elem, expr ); + + // IE 9's matchesSelector returns false on disconnected nodes + if ( ret || support.disconnectedMatch || + + // As well, disconnected nodes are said to be in a document + // fragment in IE 9 + elem.document && elem.document.nodeType !== 11 ) { + return ret; + } + } catch ( e ) { + nonnativeSelectorCache( expr, true ); + } + } + + return Sizzle( expr, document, null, [ elem ] ).length > 0; +}; + +Sizzle.contains = function( context, elem ) { + + // Set document vars if needed + // Support: IE 11+, Edge 17 - 18+ + // IE/Edge sometimes throw a "Permission denied" error when strict-comparing + // two documents; shallow comparisons work. + // eslint-disable-next-line eqeqeq + if ( ( context.ownerDocument || context ) != document ) { + setDocument( context ); + } + return contains( context, elem ); +}; + +Sizzle.attr = function( elem, name ) { + + // Set document vars if needed + // Support: IE 11+, Edge 17 - 18+ + // IE/Edge sometimes throw a "Permission denied" error when strict-comparing + // two documents; shallow comparisons work. + // eslint-disable-next-line eqeqeq + if ( ( elem.ownerDocument || elem ) != document ) { + setDocument( elem ); + } + + var fn = Expr.attrHandle[ name.toLowerCase() ], + + // Don't get fooled by Object.prototype properties (jQuery #13807) + val = fn && hasOwn.call( Expr.attrHandle, name.toLowerCase() ) ? + fn( elem, name, !documentIsHTML ) : + undefined; + + return val !== undefined ? + val : + support.attributes || !documentIsHTML ? + elem.getAttribute( name ) : + ( val = elem.getAttributeNode( name ) ) && val.specified ? + val.value : + null; +}; + +Sizzle.escape = function( sel ) { + return ( sel + "" ).replace( rcssescape, fcssescape ); +}; + +Sizzle.error = function( msg ) { + throw new Error( "Syntax error, unrecognized expression: " + msg ); +}; + +/** + * Document sorting and removing duplicates + * @param {ArrayLike} results + */ +Sizzle.uniqueSort = function( results ) { + var elem, + duplicates = [], + j = 0, + i = 0; + + // Unless we *know* we can detect duplicates, assume their presence + hasDuplicate = !support.detectDuplicates; + sortInput = !support.sortStable && results.slice( 0 ); + results.sort( sortOrder ); + + if ( hasDuplicate ) { + while ( ( elem = results[ i++ ] ) ) { + if ( elem === results[ i ] ) { + j = duplicates.push( i ); + } + } + while ( j-- ) { + results.splice( duplicates[ j ], 1 ); + } + } + + // Clear input after sorting to release objects + // See https://github.com/jquery/sizzle/pull/225 + sortInput = null; + + return results; +}; + +/** + * Utility function for retrieving the text value of an array of DOM nodes + * @param {Array|Element} elem + */ +getText = Sizzle.getText = function( elem ) { + var node, + ret = "", + i = 0, + nodeType = elem.nodeType; + + if ( !nodeType ) { + + // If no nodeType, this is expected to be an array + while ( ( node = elem[ i++ ] ) ) { + + // Do not traverse comment nodes + ret += getText( node ); + } + } else if ( nodeType === 1 || nodeType === 9 || nodeType === 11 ) { + + // Use textContent for elements + // innerText usage removed for consistency of new lines (jQuery #11153) + if ( typeof elem.textContent === "string" ) { + return elem.textContent; + } else { + + // Traverse its children + for ( elem = elem.firstChild; elem; elem = elem.nextSibling ) { + ret += getText( elem ); + } + } + } else if ( nodeType === 3 || nodeType === 4 ) { + return elem.nodeValue; + } + + // Do not include comment or processing instruction nodes + + return ret; +}; + +Expr = Sizzle.selectors = { + + // Can be adjusted by the user + cacheLength: 50, + + createPseudo: markFunction, + + match: matchExpr, + + attrHandle: {}, + + find: {}, + + relative: { + ">": { dir: "parentNode", first: true }, + " ": { dir: "parentNode" }, + "+": { dir: "previousSibling", first: true }, + "~": { dir: "previousSibling" } + }, + + preFilter: { + "ATTR": function( match ) { + match[ 1 ] = match[ 1 ].replace( runescape, funescape ); + + // Move the given value to match[3] whether quoted or unquoted + match[ 3 ] = ( match[ 3 ] || match[ 4 ] || + match[ 5 ] || "" ).replace( runescape, funescape ); + + if ( match[ 2 ] === "~=" ) { + match[ 3 ] = " " + match[ 3 ] + " "; + } + + return match.slice( 0, 4 ); + }, + + "CHILD": function( match ) { + + /* matches from matchExpr["CHILD"] + 1 type (only|nth|...) + 2 what (child|of-type) + 3 argument (even|odd|\d*|\d*n([+-]\d+)?|...) + 4 xn-component of xn+y argument ([+-]?\d*n|) + 5 sign of xn-component + 6 x of xn-component + 7 sign of y-component + 8 y of y-component + */ + match[ 1 ] = match[ 1 ].toLowerCase(); + + if ( match[ 1 ].slice( 0, 3 ) === "nth" ) { + + // nth-* requires argument + if ( !match[ 3 ] ) { + Sizzle.error( match[ 0 ] ); + } + + // numeric x and y parameters for Expr.filter.CHILD + // remember that false/true cast respectively to 0/1 + match[ 4 ] = +( match[ 4 ] ? + match[ 5 ] + ( match[ 6 ] || 1 ) : + 2 * ( match[ 3 ] === "even" || match[ 3 ] === "odd" ) ); + match[ 5 ] = +( ( match[ 7 ] + match[ 8 ] ) || match[ 3 ] === "odd" ); + + // other types prohibit arguments + } else if ( match[ 3 ] ) { + Sizzle.error( match[ 0 ] ); + } + + return match; + }, + + "PSEUDO": function( match ) { + var excess, + unquoted = !match[ 6 ] && match[ 2 ]; + + if ( matchExpr[ "CHILD" ].test( match[ 0 ] ) ) { + return null; + } + + // Accept quoted arguments as-is + if ( match[ 3 ] ) { + match[ 2 ] = match[ 4 ] || match[ 5 ] || ""; + + // Strip excess characters from unquoted arguments + } else if ( unquoted && rpseudo.test( unquoted ) && + + // Get excess from tokenize (recursively) + ( excess = tokenize( unquoted, true ) ) && + + // advance to the next closing parenthesis + ( excess = unquoted.indexOf( ")", unquoted.length - excess ) - unquoted.length ) ) { + + // excess is a negative index + match[ 0 ] = match[ 0 ].slice( 0, excess ); + match[ 2 ] = unquoted.slice( 0, excess ); + } + + // Return only captures needed by the pseudo filter method (type and argument) + return match.slice( 0, 3 ); + } + }, + + filter: { + + "TAG": function( nodeNameSelector ) { + var nodeName = nodeNameSelector.replace( runescape, funescape ).toLowerCase(); + return nodeNameSelector === "*" ? + function() { + return true; + } : + function( elem ) { + return elem.nodeName && elem.nodeName.toLowerCase() === nodeName; + }; + }, + + "CLASS": function( className ) { + var pattern = classCache[ className + " " ]; + + return pattern || + ( pattern = new RegExp( "(^|" + whitespace + + ")" + className + "(" + whitespace + "|$)" ) ) && classCache( + className, function( elem ) { + return pattern.test( + typeof elem.className === "string" && elem.className || + typeof elem.getAttribute !== "undefined" && + elem.getAttribute( "class" ) || + "" + ); + } ); + }, + + "ATTR": function( name, operator, check ) { + return function( elem ) { + var result = Sizzle.attr( elem, name ); + + if ( result == null ) { + return operator === "!="; + } + if ( !operator ) { + return true; + } + + result += ""; + + /* eslint-disable max-len */ + + return operator === "=" ? result === check : + operator === "!=" ? result !== check : + operator === "^=" ? check && result.indexOf( check ) === 0 : + operator === "*=" ? check && result.indexOf( check ) > -1 : + operator === "$=" ? check && result.slice( -check.length ) === check : + operator === "~=" ? ( " " + result.replace( rwhitespace, " " ) + " " ).indexOf( check ) > -1 : + operator === "|=" ? result === check || result.slice( 0, check.length + 1 ) === check + "-" : + false; + /* eslint-enable max-len */ + + }; + }, + + "CHILD": function( type, what, _argument, first, last ) { + var simple = type.slice( 0, 3 ) !== "nth", + forward = type.slice( -4 ) !== "last", + ofType = what === "of-type"; + + return first === 1 && last === 0 ? + + // Shortcut for :nth-*(n) + function( elem ) { + return !!elem.parentNode; + } : + + function( elem, _context, xml ) { + var cache, uniqueCache, outerCache, node, nodeIndex, start, + dir = simple !== forward ? "nextSibling" : "previousSibling", + parent = elem.parentNode, + name = ofType && elem.nodeName.toLowerCase(), + useCache = !xml && !ofType, + diff = false; + + if ( parent ) { + + // :(first|last|only)-(child|of-type) + if ( simple ) { + while ( dir ) { + node = elem; + while ( ( node = node[ dir ] ) ) { + if ( ofType ? + node.nodeName.toLowerCase() === name : + node.nodeType === 1 ) { + + return false; + } + } + + // Reverse direction for :only-* (if we haven't yet done so) + start = dir = type === "only" && !start && "nextSibling"; + } + return true; + } + + start = [ forward ? parent.firstChild : parent.lastChild ]; + + // non-xml :nth-child(...) stores cache data on `parent` + if ( forward && useCache ) { + + // Seek `elem` from a previously-cached index + + // ...in a gzip-friendly way + node = parent; + outerCache = node[ expando ] || ( node[ expando ] = {} ); + + // Support: IE <9 only + // Defend against cloned attroperties (jQuery gh-1709) + uniqueCache = outerCache[ node.uniqueID ] || + ( outerCache[ node.uniqueID ] = {} ); + + cache = uniqueCache[ type ] || []; + nodeIndex = cache[ 0 ] === dirruns && cache[ 1 ]; + diff = nodeIndex && cache[ 2 ]; + node = nodeIndex && parent.childNodes[ nodeIndex ]; + + while ( ( node = ++nodeIndex && node && node[ dir ] || + + // Fallback to seeking `elem` from the start + ( diff = nodeIndex = 0 ) || start.pop() ) ) { + + // When found, cache indexes on `parent` and break + if ( node.nodeType === 1 && ++diff && node === elem ) { + uniqueCache[ type ] = [ dirruns, nodeIndex, diff ]; + break; + } + } + + } else { + + // Use previously-cached element index if available + if ( useCache ) { + + // ...in a gzip-friendly way + node = elem; + outerCache = node[ expando ] || ( node[ expando ] = {} ); + + // Support: IE <9 only + // Defend against cloned attroperties (jQuery gh-1709) + uniqueCache = outerCache[ node.uniqueID ] || + ( outerCache[ node.uniqueID ] = {} ); + + cache = uniqueCache[ type ] || []; + nodeIndex = cache[ 0 ] === dirruns && cache[ 1 ]; + diff = nodeIndex; + } + + // xml :nth-child(...) + // or :nth-last-child(...) or :nth(-last)?-of-type(...) + if ( diff === false ) { + + // Use the same loop as above to seek `elem` from the start + while ( ( node = ++nodeIndex && node && node[ dir ] || + ( diff = nodeIndex = 0 ) || start.pop() ) ) { + + if ( ( ofType ? + node.nodeName.toLowerCase() === name : + node.nodeType === 1 ) && + ++diff ) { + + // Cache the index of each encountered element + if ( useCache ) { + outerCache = node[ expando ] || + ( node[ expando ] = {} ); + + // Support: IE <9 only + // Defend against cloned attroperties (jQuery gh-1709) + uniqueCache = outerCache[ node.uniqueID ] || + ( outerCache[ node.uniqueID ] = {} ); + + uniqueCache[ type ] = [ dirruns, diff ]; + } + + if ( node === elem ) { + break; + } + } + } + } + } + + // Incorporate the offset, then check against cycle size + diff -= last; + return diff === first || ( diff % first === 0 && diff / first >= 0 ); + } + }; + }, + + "PSEUDO": function( pseudo, argument ) { + + // pseudo-class names are case-insensitive + // http://www.w3.org/TR/selectors/#pseudo-classes + // Prioritize by case sensitivity in case custom pseudos are added with uppercase letters + // Remember that setFilters inherits from pseudos + var args, + fn = Expr.pseudos[ pseudo ] || Expr.setFilters[ pseudo.toLowerCase() ] || + Sizzle.error( "unsupported pseudo: " + pseudo ); + + // The user may use createPseudo to indicate that + // arguments are needed to create the filter function + // just as Sizzle does + if ( fn[ expando ] ) { + return fn( argument ); + } + + // But maintain support for old signatures + if ( fn.length > 1 ) { + args = [ pseudo, pseudo, "", argument ]; + return Expr.setFilters.hasOwnProperty( pseudo.toLowerCase() ) ? + markFunction( function( seed, matches ) { + var idx, + matched = fn( seed, argument ), + i = matched.length; + while ( i-- ) { + idx = indexOf( seed, matched[ i ] ); + seed[ idx ] = !( matches[ idx ] = matched[ i ] ); + } + } ) : + function( elem ) { + return fn( elem, 0, args ); + }; + } + + return fn; + } + }, + + pseudos: { + + // Potentially complex pseudos + "not": markFunction( function( selector ) { + + // Trim the selector passed to compile + // to avoid treating leading and trailing + // spaces as combinators + var input = [], + results = [], + matcher = compile( selector.replace( rtrim, "$1" ) ); + + return matcher[ expando ] ? + markFunction( function( seed, matches, _context, xml ) { + var elem, + unmatched = matcher( seed, null, xml, [] ), + i = seed.length; + + // Match elements unmatched by `matcher` + while ( i-- ) { + if ( ( elem = unmatched[ i ] ) ) { + seed[ i ] = !( matches[ i ] = elem ); + } + } + } ) : + function( elem, _context, xml ) { + input[ 0 ] = elem; + matcher( input, null, xml, results ); + + // Don't keep the element (issue #299) + input[ 0 ] = null; + return !results.pop(); + }; + } ), + + "has": markFunction( function( selector ) { + return function( elem ) { + return Sizzle( selector, elem ).length > 0; + }; + } ), + + "contains": markFunction( function( text ) { + text = text.replace( runescape, funescape ); + return function( elem ) { + return ( elem.textContent || getText( elem ) ).indexOf( text ) > -1; + }; + } ), + + // "Whether an element is represented by a :lang() selector + // is based solely on the element's language value + // being equal to the identifier C, + // or beginning with the identifier C immediately followed by "-". + // The matching of C against the element's language value is performed case-insensitively. + // The identifier C does not have to be a valid language name." + // http://www.w3.org/TR/selectors/#lang-pseudo + "lang": markFunction( function( lang ) { + + // lang value must be a valid identifier + if ( !ridentifier.test( lang || "" ) ) { + Sizzle.error( "unsupported lang: " + lang ); + } + lang = lang.replace( runescape, funescape ).toLowerCase(); + return function( elem ) { + var elemLang; + do { + if ( ( elemLang = documentIsHTML ? + elem.lang : + elem.getAttribute( "xml:lang" ) || elem.getAttribute( "lang" ) ) ) { + + elemLang = elemLang.toLowerCase(); + return elemLang === lang || elemLang.indexOf( lang + "-" ) === 0; + } + } while ( ( elem = elem.parentNode ) && elem.nodeType === 1 ); + return false; + }; + } ), + + // Miscellaneous + "target": function( elem ) { + var hash = window.location && window.location.hash; + return hash && hash.slice( 1 ) === elem.id; + }, + + "root": function( elem ) { + return elem === docElem; + }, + + "focus": function( elem ) { + return elem === document.activeElement && + ( !document.hasFocus || document.hasFocus() ) && + !!( elem.type || elem.href || ~elem.tabIndex ); + }, + + // Boolean properties + "enabled": createDisabledPseudo( false ), + "disabled": createDisabledPseudo( true ), + + "checked": function( elem ) { + + // In CSS3, :checked should return both checked and selected elements + // http://www.w3.org/TR/2011/REC-css3-selectors-20110929/#checked + var nodeName = elem.nodeName.toLowerCase(); + return ( nodeName === "input" && !!elem.checked ) || + ( nodeName === "option" && !!elem.selected ); + }, + + "selected": function( elem ) { + + // Accessing this property makes selected-by-default + // options in Safari work properly + if ( elem.parentNode ) { + // eslint-disable-next-line no-unused-expressions + elem.parentNode.selectedIndex; + } + + return elem.selected === true; + }, + + // Contents + "empty": function( elem ) { + + // http://www.w3.org/TR/selectors/#empty-pseudo + // :empty is negated by element (1) or content nodes (text: 3; cdata: 4; entity ref: 5), + // but not by others (comment: 8; processing instruction: 7; etc.) + // nodeType < 6 works because attributes (2) do not appear as children + for ( elem = elem.firstChild; elem; elem = elem.nextSibling ) { + if ( elem.nodeType < 6 ) { + return false; + } + } + return true; + }, + + "parent": function( elem ) { + return !Expr.pseudos[ "empty" ]( elem ); + }, + + // Element/input types + "header": function( elem ) { + return rheader.test( elem.nodeName ); + }, + + "input": function( elem ) { + return rinputs.test( elem.nodeName ); + }, + + "button": function( elem ) { + var name = elem.nodeName.toLowerCase(); + return name === "input" && elem.type === "button" || name === "button"; + }, + + "text": function( elem ) { + var attr; + return elem.nodeName.toLowerCase() === "input" && + elem.type === "text" && + + // Support: IE<8 + // New HTML5 attribute values (e.g., "search") appear with elem.type === "text" + ( ( attr = elem.getAttribute( "type" ) ) == null || + attr.toLowerCase() === "text" ); + }, + + // Position-in-collection + "first": createPositionalPseudo( function() { + return [ 0 ]; + } ), + + "last": createPositionalPseudo( function( _matchIndexes, length ) { + return [ length - 1 ]; + } ), + + "eq": createPositionalPseudo( function( _matchIndexes, length, argument ) { + return [ argument < 0 ? argument + length : argument ]; + } ), + + "even": createPositionalPseudo( function( matchIndexes, length ) { + var i = 0; + for ( ; i < length; i += 2 ) { + matchIndexes.push( i ); + } + return matchIndexes; + } ), + + "odd": createPositionalPseudo( function( matchIndexes, length ) { + var i = 1; + for ( ; i < length; i += 2 ) { + matchIndexes.push( i ); + } + return matchIndexes; + } ), + + "lt": createPositionalPseudo( function( matchIndexes, length, argument ) { + var i = argument < 0 ? + argument + length : + argument > length ? + length : + argument; + for ( ; --i >= 0; ) { + matchIndexes.push( i ); + } + return matchIndexes; + } ), + + "gt": createPositionalPseudo( function( matchIndexes, length, argument ) { + var i = argument < 0 ? argument + length : argument; + for ( ; ++i < length; ) { + matchIndexes.push( i ); + } + return matchIndexes; + } ) + } +}; + +Expr.pseudos[ "nth" ] = Expr.pseudos[ "eq" ]; + +// Add button/input type pseudos +for ( i in { radio: true, checkbox: true, file: true, password: true, image: true } ) { + Expr.pseudos[ i ] = createInputPseudo( i ); +} +for ( i in { submit: true, reset: true } ) { + Expr.pseudos[ i ] = createButtonPseudo( i ); +} + +// Easy API for creating new setFilters +function setFilters() {} +setFilters.prototype = Expr.filters = Expr.pseudos; +Expr.setFilters = new setFilters(); + +tokenize = Sizzle.tokenize = function( selector, parseOnly ) { + var matched, match, tokens, type, + soFar, groups, preFilters, + cached = tokenCache[ selector + " " ]; + + if ( cached ) { + return parseOnly ? 0 : cached.slice( 0 ); + } + + soFar = selector; + groups = []; + preFilters = Expr.preFilter; + + while ( soFar ) { + + // Comma and first run + if ( !matched || ( match = rcomma.exec( soFar ) ) ) { + if ( match ) { + + // Don't consume trailing commas as valid + soFar = soFar.slice( match[ 0 ].length ) || soFar; + } + groups.push( ( tokens = [] ) ); + } + + matched = false; + + // Combinators + if ( ( match = rcombinators.exec( soFar ) ) ) { + matched = match.shift(); + tokens.push( { + value: matched, + + // Cast descendant combinators to space + type: match[ 0 ].replace( rtrim, " " ) + } ); + soFar = soFar.slice( matched.length ); + } + + // Filters + for ( type in Expr.filter ) { + if ( ( match = matchExpr[ type ].exec( soFar ) ) && ( !preFilters[ type ] || + ( match = preFilters[ type ]( match ) ) ) ) { + matched = match.shift(); + tokens.push( { + value: matched, + type: type, + matches: match + } ); + soFar = soFar.slice( matched.length ); + } + } + + if ( !matched ) { + break; + } + } + + // Return the length of the invalid excess + // if we're just parsing + // Otherwise, throw an error or return tokens + return parseOnly ? + soFar.length : + soFar ? + Sizzle.error( selector ) : + + // Cache the tokens + tokenCache( selector, groups ).slice( 0 ); +}; + +function toSelector( tokens ) { + var i = 0, + len = tokens.length, + selector = ""; + for ( ; i < len; i++ ) { + selector += tokens[ i ].value; + } + return selector; +} + +function addCombinator( matcher, combinator, base ) { + var dir = combinator.dir, + skip = combinator.next, + key = skip || dir, + checkNonElements = base && key === "parentNode", + doneName = done++; + + return combinator.first ? + + // Check against closest ancestor/preceding element + function( elem, context, xml ) { + while ( ( elem = elem[ dir ] ) ) { + if ( elem.nodeType === 1 || checkNonElements ) { + return matcher( elem, context, xml ); + } + } + return false; + } : + + // Check against all ancestor/preceding elements + function( elem, context, xml ) { + var oldCache, uniqueCache, outerCache, + newCache = [ dirruns, doneName ]; + + // We can't set arbitrary data on XML nodes, so they don't benefit from combinator caching + if ( xml ) { + while ( ( elem = elem[ dir ] ) ) { + if ( elem.nodeType === 1 || checkNonElements ) { + if ( matcher( elem, context, xml ) ) { + return true; + } + } + } + } else { + while ( ( elem = elem[ dir ] ) ) { + if ( elem.nodeType === 1 || checkNonElements ) { + outerCache = elem[ expando ] || ( elem[ expando ] = {} ); + + // Support: IE <9 only + // Defend against cloned attroperties (jQuery gh-1709) + uniqueCache = outerCache[ elem.uniqueID ] || + ( outerCache[ elem.uniqueID ] = {} ); + + if ( skip && skip === elem.nodeName.toLowerCase() ) { + elem = elem[ dir ] || elem; + } else if ( ( oldCache = uniqueCache[ key ] ) && + oldCache[ 0 ] === dirruns && oldCache[ 1 ] === doneName ) { + + // Assign to newCache so results back-propagate to previous elements + return ( newCache[ 2 ] = oldCache[ 2 ] ); + } else { + + // Reuse newcache so results back-propagate to previous elements + uniqueCache[ key ] = newCache; + + // A match means we're done; a fail means we have to keep checking + if ( ( newCache[ 2 ] = matcher( elem, context, xml ) ) ) { + return true; + } + } + } + } + } + return false; + }; +} + +function elementMatcher( matchers ) { + return matchers.length > 1 ? + function( elem, context, xml ) { + var i = matchers.length; + while ( i-- ) { + if ( !matchers[ i ]( elem, context, xml ) ) { + return false; + } + } + return true; + } : + matchers[ 0 ]; +} + +function multipleContexts( selector, contexts, results ) { + var i = 0, + len = contexts.length; + for ( ; i < len; i++ ) { + Sizzle( selector, contexts[ i ], results ); + } + return results; +} + +function condense( unmatched, map, filter, context, xml ) { + var elem, + newUnmatched = [], + i = 0, + len = unmatched.length, + mapped = map != null; + + for ( ; i < len; i++ ) { + if ( ( elem = unmatched[ i ] ) ) { + if ( !filter || filter( elem, context, xml ) ) { + newUnmatched.push( elem ); + if ( mapped ) { + map.push( i ); + } + } + } + } + + return newUnmatched; +} + +function setMatcher( preFilter, selector, matcher, postFilter, postFinder, postSelector ) { + if ( postFilter && !postFilter[ expando ] ) { + postFilter = setMatcher( postFilter ); + } + if ( postFinder && !postFinder[ expando ] ) { + postFinder = setMatcher( postFinder, postSelector ); + } + return markFunction( function( seed, results, context, xml ) { + var temp, i, elem, + preMap = [], + postMap = [], + preexisting = results.length, + + // Get initial elements from seed or context + elems = seed || multipleContexts( + selector || "*", + context.nodeType ? [ context ] : context, + [] + ), + + // Prefilter to get matcher input, preserving a map for seed-results synchronization + matcherIn = preFilter && ( seed || !selector ) ? + condense( elems, preMap, preFilter, context, xml ) : + elems, + + matcherOut = matcher ? + + // If we have a postFinder, or filtered seed, or non-seed postFilter or preexisting results, + postFinder || ( seed ? preFilter : preexisting || postFilter ) ? + + // ...intermediate processing is necessary + [] : + + // ...otherwise use results directly + results : + matcherIn; + + // Find primary matches + if ( matcher ) { + matcher( matcherIn, matcherOut, context, xml ); + } + + // Apply postFilter + if ( postFilter ) { + temp = condense( matcherOut, postMap ); + postFilter( temp, [], context, xml ); + + // Un-match failing elements by moving them back to matcherIn + i = temp.length; + while ( i-- ) { + if ( ( elem = temp[ i ] ) ) { + matcherOut[ postMap[ i ] ] = !( matcherIn[ postMap[ i ] ] = elem ); + } + } + } + + if ( seed ) { + if ( postFinder || preFilter ) { + if ( postFinder ) { + + // Get the final matcherOut by condensing this intermediate into postFinder contexts + temp = []; + i = matcherOut.length; + while ( i-- ) { + if ( ( elem = matcherOut[ i ] ) ) { + + // Restore matcherIn since elem is not yet a final match + temp.push( ( matcherIn[ i ] = elem ) ); + } + } + postFinder( null, ( matcherOut = [] ), temp, xml ); + } + + // Move matched elements from seed to results to keep them synchronized + i = matcherOut.length; + while ( i-- ) { + if ( ( elem = matcherOut[ i ] ) && + ( temp = postFinder ? indexOf( seed, elem ) : preMap[ i ] ) > -1 ) { + + seed[ temp ] = !( results[ temp ] = elem ); + } + } + } + + // Add elements to results, through postFinder if defined + } else { + matcherOut = condense( + matcherOut === results ? + matcherOut.splice( preexisting, matcherOut.length ) : + matcherOut + ); + if ( postFinder ) { + postFinder( null, results, matcherOut, xml ); + } else { + push.apply( results, matcherOut ); + } + } + } ); +} + +function matcherFromTokens( tokens ) { + var checkContext, matcher, j, + len = tokens.length, + leadingRelative = Expr.relative[ tokens[ 0 ].type ], + implicitRelative = leadingRelative || Expr.relative[ " " ], + i = leadingRelative ? 1 : 0, + + // The foundational matcher ensures that elements are reachable from top-level context(s) + matchContext = addCombinator( function( elem ) { + return elem === checkContext; + }, implicitRelative, true ), + matchAnyContext = addCombinator( function( elem ) { + return indexOf( checkContext, elem ) > -1; + }, implicitRelative, true ), + matchers = [ function( elem, context, xml ) { + var ret = ( !leadingRelative && ( xml || context !== outermostContext ) ) || ( + ( checkContext = context ).nodeType ? + matchContext( elem, context, xml ) : + matchAnyContext( elem, context, xml ) ); + + // Avoid hanging onto element (issue #299) + checkContext = null; + return ret; + } ]; + + for ( ; i < len; i++ ) { + if ( ( matcher = Expr.relative[ tokens[ i ].type ] ) ) { + matchers = [ addCombinator( elementMatcher( matchers ), matcher ) ]; + } else { + matcher = Expr.filter[ tokens[ i ].type ].apply( null, tokens[ i ].matches ); + + // Return special upon seeing a positional matcher + if ( matcher[ expando ] ) { + + // Find the next relative operator (if any) for proper handling + j = ++i; + for ( ; j < len; j++ ) { + if ( Expr.relative[ tokens[ j ].type ] ) { + break; + } + } + return setMatcher( + i > 1 && elementMatcher( matchers ), + i > 1 && toSelector( + + // If the preceding token was a descendant combinator, insert an implicit any-element `*` + tokens + .slice( 0, i - 1 ) + .concat( { value: tokens[ i - 2 ].type === " " ? "*" : "" } ) + ).replace( rtrim, "$1" ), + matcher, + i < j && matcherFromTokens( tokens.slice( i, j ) ), + j < len && matcherFromTokens( ( tokens = tokens.slice( j ) ) ), + j < len && toSelector( tokens ) + ); + } + matchers.push( matcher ); + } + } + + return elementMatcher( matchers ); +} + +function matcherFromGroupMatchers( elementMatchers, setMatchers ) { + var bySet = setMatchers.length > 0, + byElement = elementMatchers.length > 0, + superMatcher = function( seed, context, xml, results, outermost ) { + var elem, j, matcher, + matchedCount = 0, + i = "0", + unmatched = seed && [], + setMatched = [], + contextBackup = outermostContext, + + // We must always have either seed elements or outermost context + elems = seed || byElement && Expr.find[ "TAG" ]( "*", outermost ), + + // Use integer dirruns iff this is the outermost matcher + dirrunsUnique = ( dirruns += contextBackup == null ? 1 : Math.random() || 0.1 ), + len = elems.length; + + if ( outermost ) { + + // Support: IE 11+, Edge 17 - 18+ + // IE/Edge sometimes throw a "Permission denied" error when strict-comparing + // two documents; shallow comparisons work. + // eslint-disable-next-line eqeqeq + outermostContext = context == document || context || outermost; + } + + // Add elements passing elementMatchers directly to results + // Support: IE<9, Safari + // Tolerate NodeList properties (IE: "length"; Safari: ) matching elements by id + for ( ; i !== len && ( elem = elems[ i ] ) != null; i++ ) { + if ( byElement && elem ) { + j = 0; + + // Support: IE 11+, Edge 17 - 18+ + // IE/Edge sometimes throw a "Permission denied" error when strict-comparing + // two documents; shallow comparisons work. + // eslint-disable-next-line eqeqeq + if ( !context && elem.ownerDocument != document ) { + setDocument( elem ); + xml = !documentIsHTML; + } + while ( ( matcher = elementMatchers[ j++ ] ) ) { + if ( matcher( elem, context || document, xml ) ) { + results.push( elem ); + break; + } + } + if ( outermost ) { + dirruns = dirrunsUnique; + } + } + + // Track unmatched elements for set filters + if ( bySet ) { + + // They will have gone through all possible matchers + if ( ( elem = !matcher && elem ) ) { + matchedCount--; + } + + // Lengthen the array for every element, matched or not + if ( seed ) { + unmatched.push( elem ); + } + } + } + + // `i` is now the count of elements visited above, and adding it to `matchedCount` + // makes the latter nonnegative. + matchedCount += i; + + // Apply set filters to unmatched elements + // NOTE: This can be skipped if there are no unmatched elements (i.e., `matchedCount` + // equals `i`), unless we didn't visit _any_ elements in the above loop because we have + // no element matchers and no seed. + // Incrementing an initially-string "0" `i` allows `i` to remain a string only in that + // case, which will result in a "00" `matchedCount` that differs from `i` but is also + // numerically zero. + if ( bySet && i !== matchedCount ) { + j = 0; + while ( ( matcher = setMatchers[ j++ ] ) ) { + matcher( unmatched, setMatched, context, xml ); + } + + if ( seed ) { + + // Reintegrate element matches to eliminate the need for sorting + if ( matchedCount > 0 ) { + while ( i-- ) { + if ( !( unmatched[ i ] || setMatched[ i ] ) ) { + setMatched[ i ] = pop.call( results ); + } + } + } + + // Discard index placeholder values to get only actual matches + setMatched = condense( setMatched ); + } + + // Add matches to results + push.apply( results, setMatched ); + + // Seedless set matches succeeding multiple successful matchers stipulate sorting + if ( outermost && !seed && setMatched.length > 0 && + ( matchedCount + setMatchers.length ) > 1 ) { + + Sizzle.uniqueSort( results ); + } + } + + // Override manipulation of globals by nested matchers + if ( outermost ) { + dirruns = dirrunsUnique; + outermostContext = contextBackup; + } + + return unmatched; + }; + + return bySet ? + markFunction( superMatcher ) : + superMatcher; +} + +compile = Sizzle.compile = function( selector, match /* Internal Use Only */ ) { + var i, + setMatchers = [], + elementMatchers = [], + cached = compilerCache[ selector + " " ]; + + if ( !cached ) { + + // Generate a function of recursive functions that can be used to check each element + if ( !match ) { + match = tokenize( selector ); + } + i = match.length; + while ( i-- ) { + cached = matcherFromTokens( match[ i ] ); + if ( cached[ expando ] ) { + setMatchers.push( cached ); + } else { + elementMatchers.push( cached ); + } + } + + // Cache the compiled function + cached = compilerCache( + selector, + matcherFromGroupMatchers( elementMatchers, setMatchers ) + ); + + // Save selector and tokenization + cached.selector = selector; + } + return cached; +}; + +/** + * A low-level selection function that works with Sizzle's compiled + * selector functions + * @param {String|Function} selector A selector or a pre-compiled + * selector function built with Sizzle.compile + * @param {Element} context + * @param {Array} [results] + * @param {Array} [seed] A set of elements to match against + */ +select = Sizzle.select = function( selector, context, results, seed ) { + var i, tokens, token, type, find, + compiled = typeof selector === "function" && selector, + match = !seed && tokenize( ( selector = compiled.selector || selector ) ); + + results = results || []; + + // Try to minimize operations if there is only one selector in the list and no seed + // (the latter of which guarantees us context) + if ( match.length === 1 ) { + + // Reduce context if the leading compound selector is an ID + tokens = match[ 0 ] = match[ 0 ].slice( 0 ); + if ( tokens.length > 2 && ( token = tokens[ 0 ] ).type === "ID" && + context.nodeType === 9 && documentIsHTML && Expr.relative[ tokens[ 1 ].type ] ) { + + context = ( Expr.find[ "ID" ]( token.matches[ 0 ] + .replace( runescape, funescape ), context ) || [] )[ 0 ]; + if ( !context ) { + return results; + + // Precompiled matchers will still verify ancestry, so step up a level + } else if ( compiled ) { + context = context.parentNode; + } + + selector = selector.slice( tokens.shift().value.length ); + } + + // Fetch a seed set for right-to-left matching + i = matchExpr[ "needsContext" ].test( selector ) ? 0 : tokens.length; + while ( i-- ) { + token = tokens[ i ]; + + // Abort if we hit a combinator + if ( Expr.relative[ ( type = token.type ) ] ) { + break; + } + if ( ( find = Expr.find[ type ] ) ) { + + // Search, expanding context for leading sibling combinators + if ( ( seed = find( + token.matches[ 0 ].replace( runescape, funescape ), + rsibling.test( tokens[ 0 ].type ) && testContext( context.parentNode ) || + context + ) ) ) { + + // If seed is empty or no tokens remain, we can return early + tokens.splice( i, 1 ); + selector = seed.length && toSelector( tokens ); + if ( !selector ) { + push.apply( results, seed ); + return results; + } + + break; + } + } + } + } + + // Compile and execute a filtering function if one is not provided + // Provide `match` to avoid retokenization if we modified the selector above + ( compiled || compile( selector, match ) )( + seed, + context, + !documentIsHTML, + results, + !context || rsibling.test( selector ) && testContext( context.parentNode ) || context + ); + return results; +}; + +// One-time assignments + +// Sort stability +support.sortStable = expando.split( "" ).sort( sortOrder ).join( "" ) === expando; + +// Support: Chrome 14-35+ +// Always assume duplicates if they aren't passed to the comparison function +support.detectDuplicates = !!hasDuplicate; + +// Initialize against the default document +setDocument(); + +// Support: Webkit<537.32 - Safari 6.0.3/Chrome 25 (fixed in Chrome 27) +// Detached nodes confoundingly follow *each other* +support.sortDetached = assert( function( el ) { + + // Should return 1, but returns 4 (following) + return el.compareDocumentPosition( document.createElement( "fieldset" ) ) & 1; +} ); + +// Support: IE<8 +// Prevent attribute/property "interpolation" +// https://msdn.microsoft.com/en-us/library/ms536429%28VS.85%29.aspx +if ( !assert( function( el ) { + el.innerHTML = ""; + return el.firstChild.getAttribute( "href" ) === "#"; +} ) ) { + addHandle( "type|href|height|width", function( elem, name, isXML ) { + if ( !isXML ) { + return elem.getAttribute( name, name.toLowerCase() === "type" ? 1 : 2 ); + } + } ); +} + +// Support: IE<9 +// Use defaultValue in place of getAttribute("value") +if ( !support.attributes || !assert( function( el ) { + el.innerHTML = ""; + el.firstChild.setAttribute( "value", "" ); + return el.firstChild.getAttribute( "value" ) === ""; +} ) ) { + addHandle( "value", function( elem, _name, isXML ) { + if ( !isXML && elem.nodeName.toLowerCase() === "input" ) { + return elem.defaultValue; + } + } ); +} + +// Support: IE<9 +// Use getAttributeNode to fetch booleans when getAttribute lies +if ( !assert( function( el ) { + return el.getAttribute( "disabled" ) == null; +} ) ) { + addHandle( booleans, function( elem, name, isXML ) { + var val; + if ( !isXML ) { + return elem[ name ] === true ? name.toLowerCase() : + ( val = elem.getAttributeNode( name ) ) && val.specified ? + val.value : + null; + } + } ); +} + +return Sizzle; + +} )( window ); + + + +jQuery.find = Sizzle; +jQuery.expr = Sizzle.selectors; + +// Deprecated +jQuery.expr[ ":" ] = jQuery.expr.pseudos; +jQuery.uniqueSort = jQuery.unique = Sizzle.uniqueSort; +jQuery.text = Sizzle.getText; +jQuery.isXMLDoc = Sizzle.isXML; +jQuery.contains = Sizzle.contains; +jQuery.escapeSelector = Sizzle.escape; + + + + +var dir = function( elem, dir, until ) { + var matched = [], + truncate = until !== undefined; + + while ( ( elem = elem[ dir ] ) && elem.nodeType !== 9 ) { + if ( elem.nodeType === 1 ) { + if ( truncate && jQuery( elem ).is( until ) ) { + break; + } + matched.push( elem ); + } + } + return matched; +}; + + +var siblings = function( n, elem ) { + var matched = []; + + for ( ; n; n = n.nextSibling ) { + if ( n.nodeType === 1 && n !== elem ) { + matched.push( n ); + } + } + + return matched; +}; + + +var rneedsContext = jQuery.expr.match.needsContext; + + + +function nodeName( elem, name ) { + + return elem.nodeName && elem.nodeName.toLowerCase() === name.toLowerCase(); + +} +var rsingleTag = ( /^<([a-z][^\/\0>:\x20\t\r\n\f]*)[\x20\t\r\n\f]*\/?>(?:<\/\1>|)$/i ); + + + +// Implement the identical functionality for filter and not +function winnow( elements, qualifier, not ) { + if ( isFunction( qualifier ) ) { + return jQuery.grep( elements, function( elem, i ) { + return !!qualifier.call( elem, i, elem ) !== not; + } ); + } + + // Single element + if ( qualifier.nodeType ) { + return jQuery.grep( elements, function( elem ) { + return ( elem === qualifier ) !== not; + } ); + } + + // Arraylike of elements (jQuery, arguments, Array) + if ( typeof qualifier !== "string" ) { + return jQuery.grep( elements, function( elem ) { + return ( indexOf.call( qualifier, elem ) > -1 ) !== not; + } ); + } + + // Filtered directly for both simple and complex selectors + return jQuery.filter( qualifier, elements, not ); +} + +jQuery.filter = function( expr, elems, not ) { + var elem = elems[ 0 ]; + + if ( not ) { + expr = ":not(" + expr + ")"; + } + + if ( elems.length === 1 && elem.nodeType === 1 ) { + return jQuery.find.matchesSelector( elem, expr ) ? [ elem ] : []; + } + + return jQuery.find.matches( expr, jQuery.grep( elems, function( elem ) { + return elem.nodeType === 1; + } ) ); +}; + +jQuery.fn.extend( { + find: function( selector ) { + var i, ret, + len = this.length, + self = this; + + if ( typeof selector !== "string" ) { + return this.pushStack( jQuery( selector ).filter( function() { + for ( i = 0; i < len; i++ ) { + if ( jQuery.contains( self[ i ], this ) ) { + return true; + } + } + } ) ); + } + + ret = this.pushStack( [] ); + + for ( i = 0; i < len; i++ ) { + jQuery.find( selector, self[ i ], ret ); + } + + return len > 1 ? jQuery.uniqueSort( ret ) : ret; + }, + filter: function( selector ) { + return this.pushStack( winnow( this, selector || [], false ) ); + }, + not: function( selector ) { + return this.pushStack( winnow( this, selector || [], true ) ); + }, + is: function( selector ) { + return !!winnow( + this, + + // If this is a positional/relative selector, check membership in the returned set + // so $("p:first").is("p:last") won't return true for a doc with two "p". + typeof selector === "string" && rneedsContext.test( selector ) ? + jQuery( selector ) : + selector || [], + false + ).length; + } +} ); + + +// Initialize a jQuery object + + +// A central reference to the root jQuery(document) +var rootjQuery, + + // A simple way to check for HTML strings + // Prioritize #id over to avoid XSS via location.hash (#9521) + // Strict HTML recognition (#11290: must start with <) + // Shortcut simple #id case for speed + rquickExpr = /^(?:\s*(<[\w\W]+>)[^>]*|#([\w-]+))$/, + + init = jQuery.fn.init = function( selector, context, root ) { + var match, elem; + + // HANDLE: $(""), $(null), $(undefined), $(false) + if ( !selector ) { + return this; + } + + // Method init() accepts an alternate rootjQuery + // so migrate can support jQuery.sub (gh-2101) + root = root || rootjQuery; + + // Handle HTML strings + if ( typeof selector === "string" ) { + if ( selector[ 0 ] === "<" && + selector[ selector.length - 1 ] === ">" && + selector.length >= 3 ) { + + // Assume that strings that start and end with <> are HTML and skip the regex check + match = [ null, selector, null ]; + + } else { + match = rquickExpr.exec( selector ); + } + + // Match html or make sure no context is specified for #id + if ( match && ( match[ 1 ] || !context ) ) { + + // HANDLE: $(html) -> $(array) + if ( match[ 1 ] ) { + context = context instanceof jQuery ? context[ 0 ] : context; + + // Option to run scripts is true for back-compat + // Intentionally let the error be thrown if parseHTML is not present + jQuery.merge( this, jQuery.parseHTML( + match[ 1 ], + context && context.nodeType ? context.ownerDocument || context : document, + true + ) ); + + // HANDLE: $(html, props) + if ( rsingleTag.test( match[ 1 ] ) && jQuery.isPlainObject( context ) ) { + for ( match in context ) { + + // Properties of context are called as methods if possible + if ( isFunction( this[ match ] ) ) { + this[ match ]( context[ match ] ); + + // ...and otherwise set as attributes + } else { + this.attr( match, context[ match ] ); + } + } + } + + return this; + + // HANDLE: $(#id) + } else { + elem = document.getElementById( match[ 2 ] ); + + if ( elem ) { + + // Inject the element directly into the jQuery object + this[ 0 ] = elem; + this.length = 1; + } + return this; + } + + // HANDLE: $(expr, $(...)) + } else if ( !context || context.jquery ) { + return ( context || root ).find( selector ); + + // HANDLE: $(expr, context) + // (which is just equivalent to: $(context).find(expr) + } else { + return this.constructor( context ).find( selector ); + } + + // HANDLE: $(DOMElement) + } else if ( selector.nodeType ) { + this[ 0 ] = selector; + this.length = 1; + return this; + + // HANDLE: $(function) + // Shortcut for document ready + } else if ( isFunction( selector ) ) { + return root.ready !== undefined ? + root.ready( selector ) : + + // Execute immediately if ready is not present + selector( jQuery ); + } + + return jQuery.makeArray( selector, this ); + }; + +// Give the init function the jQuery prototype for later instantiation +init.prototype = jQuery.fn; + +// Initialize central reference +rootjQuery = jQuery( document ); + + +var rparentsprev = /^(?:parents|prev(?:Until|All))/, + + // Methods guaranteed to produce a unique set when starting from a unique set + guaranteedUnique = { + children: true, + contents: true, + next: true, + prev: true + }; + +jQuery.fn.extend( { + has: function( target ) { + var targets = jQuery( target, this ), + l = targets.length; + + return this.filter( function() { + var i = 0; + for ( ; i < l; i++ ) { + if ( jQuery.contains( this, targets[ i ] ) ) { + return true; + } + } + } ); + }, + + closest: function( selectors, context ) { + var cur, + i = 0, + l = this.length, + matched = [], + targets = typeof selectors !== "string" && jQuery( selectors ); + + // Positional selectors never match, since there's no _selection_ context + if ( !rneedsContext.test( selectors ) ) { + for ( ; i < l; i++ ) { + for ( cur = this[ i ]; cur && cur !== context; cur = cur.parentNode ) { + + // Always skip document fragments + if ( cur.nodeType < 11 && ( targets ? + targets.index( cur ) > -1 : + + // Don't pass non-elements to Sizzle + cur.nodeType === 1 && + jQuery.find.matchesSelector( cur, selectors ) ) ) { + + matched.push( cur ); + break; + } + } + } + } + + return this.pushStack( matched.length > 1 ? jQuery.uniqueSort( matched ) : matched ); + }, + + // Determine the position of an element within the set + index: function( elem ) { + + // No argument, return index in parent + if ( !elem ) { + return ( this[ 0 ] && this[ 0 ].parentNode ) ? this.first().prevAll().length : -1; + } + + // Index in selector + if ( typeof elem === "string" ) { + return indexOf.call( jQuery( elem ), this[ 0 ] ); + } + + // Locate the position of the desired element + return indexOf.call( this, + + // If it receives a jQuery object, the first element is used + elem.jquery ? elem[ 0 ] : elem + ); + }, + + add: function( selector, context ) { + return this.pushStack( + jQuery.uniqueSort( + jQuery.merge( this.get(), jQuery( selector, context ) ) + ) + ); + }, + + addBack: function( selector ) { + return this.add( selector == null ? + this.prevObject : this.prevObject.filter( selector ) + ); + } +} ); + +function sibling( cur, dir ) { + while ( ( cur = cur[ dir ] ) && cur.nodeType !== 1 ) {} + return cur; +} + +jQuery.each( { + parent: function( elem ) { + var parent = elem.parentNode; + return parent && parent.nodeType !== 11 ? parent : null; + }, + parents: function( elem ) { + return dir( elem, "parentNode" ); + }, + parentsUntil: function( elem, _i, until ) { + return dir( elem, "parentNode", until ); + }, + next: function( elem ) { + return sibling( elem, "nextSibling" ); + }, + prev: function( elem ) { + return sibling( elem, "previousSibling" ); + }, + nextAll: function( elem ) { + return dir( elem, "nextSibling" ); + }, + prevAll: function( elem ) { + return dir( elem, "previousSibling" ); + }, + nextUntil: function( elem, _i, until ) { + return dir( elem, "nextSibling", until ); + }, + prevUntil: function( elem, _i, until ) { + return dir( elem, "previousSibling", until ); + }, + siblings: function( elem ) { + return siblings( ( elem.parentNode || {} ).firstChild, elem ); + }, + children: function( elem ) { + return siblings( elem.firstChild ); + }, + contents: function( elem ) { + if ( elem.contentDocument != null && + + // Support: IE 11+ + // elements with no `data` attribute has an object + // `contentDocument` with a `null` prototype. + getProto( elem.contentDocument ) ) { + + return elem.contentDocument; + } + + // Support: IE 9 - 11 only, iOS 7 only, Android Browser <=4.3 only + // Treat the template element as a regular one in browsers that + // don't support it. + if ( nodeName( elem, "template" ) ) { + elem = elem.content || elem; + } + + return jQuery.merge( [], elem.childNodes ); + } +}, function( name, fn ) { + jQuery.fn[ name ] = function( until, selector ) { + var matched = jQuery.map( this, fn, until ); + + if ( name.slice( -5 ) !== "Until" ) { + selector = until; + } + + if ( selector && typeof selector === "string" ) { + matched = jQuery.filter( selector, matched ); + } + + if ( this.length > 1 ) { + + // Remove duplicates + if ( !guaranteedUnique[ name ] ) { + jQuery.uniqueSort( matched ); + } + + // Reverse order for parents* and prev-derivatives + if ( rparentsprev.test( name ) ) { + matched.reverse(); + } + } + + return this.pushStack( matched ); + }; +} ); +var rnothtmlwhite = ( /[^\x20\t\r\n\f]+/g ); + + + +// Convert String-formatted options into Object-formatted ones +function createOptions( options ) { + var object = {}; + jQuery.each( options.match( rnothtmlwhite ) || [], function( _, flag ) { + object[ flag ] = true; + } ); + return object; +} + +/* + * Create a callback list using the following parameters: + * + * options: an optional list of space-separated options that will change how + * the callback list behaves or a more traditional option object + * + * By default a callback list will act like an event callback list and can be + * "fired" multiple times. + * + * Possible options: + * + * once: will ensure the callback list can only be fired once (like a Deferred) + * + * memory: will keep track of previous values and will call any callback added + * after the list has been fired right away with the latest "memorized" + * values (like a Deferred) + * + * unique: will ensure a callback can only be added once (no duplicate in the list) + * + * stopOnFalse: interrupt callings when a callback returns false + * + */ +jQuery.Callbacks = function( options ) { + + // Convert options from String-formatted to Object-formatted if needed + // (we check in cache first) + options = typeof options === "string" ? + createOptions( options ) : + jQuery.extend( {}, options ); + + var // Flag to know if list is currently firing + firing, + + // Last fire value for non-forgettable lists + memory, + + // Flag to know if list was already fired + fired, + + // Flag to prevent firing + locked, + + // Actual callback list + list = [], + + // Queue of execution data for repeatable lists + queue = [], + + // Index of currently firing callback (modified by add/remove as needed) + firingIndex = -1, + + // Fire callbacks + fire = function() { + + // Enforce single-firing + locked = locked || options.once; + + // Execute callbacks for all pending executions, + // respecting firingIndex overrides and runtime changes + fired = firing = true; + for ( ; queue.length; firingIndex = -1 ) { + memory = queue.shift(); + while ( ++firingIndex < list.length ) { + + // Run callback and check for early termination + if ( list[ firingIndex ].apply( memory[ 0 ], memory[ 1 ] ) === false && + options.stopOnFalse ) { + + // Jump to end and forget the data so .add doesn't re-fire + firingIndex = list.length; + memory = false; + } + } + } + + // Forget the data if we're done with it + if ( !options.memory ) { + memory = false; + } + + firing = false; + + // Clean up if we're done firing for good + if ( locked ) { + + // Keep an empty list if we have data for future add calls + if ( memory ) { + list = []; + + // Otherwise, this object is spent + } else { + list = ""; + } + } + }, + + // Actual Callbacks object + self = { + + // Add a callback or a collection of callbacks to the list + add: function() { + if ( list ) { + + // If we have memory from a past run, we should fire after adding + if ( memory && !firing ) { + firingIndex = list.length - 1; + queue.push( memory ); + } + + ( function add( args ) { + jQuery.each( args, function( _, arg ) { + if ( isFunction( arg ) ) { + if ( !options.unique || !self.has( arg ) ) { + list.push( arg ); + } + } else if ( arg && arg.length && toType( arg ) !== "string" ) { + + // Inspect recursively + add( arg ); + } + } ); + } )( arguments ); + + if ( memory && !firing ) { + fire(); + } + } + return this; + }, + + // Remove a callback from the list + remove: function() { + jQuery.each( arguments, function( _, arg ) { + var index; + while ( ( index = jQuery.inArray( arg, list, index ) ) > -1 ) { + list.splice( index, 1 ); + + // Handle firing indexes + if ( index <= firingIndex ) { + firingIndex--; + } + } + } ); + return this; + }, + + // Check if a given callback is in the list. + // If no argument is given, return whether or not list has callbacks attached. + has: function( fn ) { + return fn ? + jQuery.inArray( fn, list ) > -1 : + list.length > 0; + }, + + // Remove all callbacks from the list + empty: function() { + if ( list ) { + list = []; + } + return this; + }, + + // Disable .fire and .add + // Abort any current/pending executions + // Clear all callbacks and values + disable: function() { + locked = queue = []; + list = memory = ""; + return this; + }, + disabled: function() { + return !list; + }, + + // Disable .fire + // Also disable .add unless we have memory (since it would have no effect) + // Abort any pending executions + lock: function() { + locked = queue = []; + if ( !memory && !firing ) { + list = memory = ""; + } + return this; + }, + locked: function() { + return !!locked; + }, + + // Call all callbacks with the given context and arguments + fireWith: function( context, args ) { + if ( !locked ) { + args = args || []; + args = [ context, args.slice ? args.slice() : args ]; + queue.push( args ); + if ( !firing ) { + fire(); + } + } + return this; + }, + + // Call all the callbacks with the given arguments + fire: function() { + self.fireWith( this, arguments ); + return this; + }, + + // To know if the callbacks have already been called at least once + fired: function() { + return !!fired; + } + }; + + return self; +}; + + +function Identity( v ) { + return v; +} +function Thrower( ex ) { + throw ex; +} + +function adoptValue( value, resolve, reject, noValue ) { + var method; + + try { + + // Check for promise aspect first to privilege synchronous behavior + if ( value && isFunction( ( method = value.promise ) ) ) { + method.call( value ).done( resolve ).fail( reject ); + + // Other thenables + } else if ( value && isFunction( ( method = value.then ) ) ) { + method.call( value, resolve, reject ); + + // Other non-thenables + } else { + + // Control `resolve` arguments by letting Array#slice cast boolean `noValue` to integer: + // * false: [ value ].slice( 0 ) => resolve( value ) + // * true: [ value ].slice( 1 ) => resolve() + resolve.apply( undefined, [ value ].slice( noValue ) ); + } + + // For Promises/A+, convert exceptions into rejections + // Since jQuery.when doesn't unwrap thenables, we can skip the extra checks appearing in + // Deferred#then to conditionally suppress rejection. + } catch ( value ) { + + // Support: Android 4.0 only + // Strict mode functions invoked without .call/.apply get global-object context + reject.apply( undefined, [ value ] ); + } +} + +jQuery.extend( { + + Deferred: function( func ) { + var tuples = [ + + // action, add listener, callbacks, + // ... .then handlers, argument index, [final state] + [ "notify", "progress", jQuery.Callbacks( "memory" ), + jQuery.Callbacks( "memory" ), 2 ], + [ "resolve", "done", jQuery.Callbacks( "once memory" ), + jQuery.Callbacks( "once memory" ), 0, "resolved" ], + [ "reject", "fail", jQuery.Callbacks( "once memory" ), + jQuery.Callbacks( "once memory" ), 1, "rejected" ] + ], + state = "pending", + promise = { + state: function() { + return state; + }, + always: function() { + deferred.done( arguments ).fail( arguments ); + return this; + }, + "catch": function( fn ) { + return promise.then( null, fn ); + }, + + // Keep pipe for back-compat + pipe: function( /* fnDone, fnFail, fnProgress */ ) { + var fns = arguments; + + return jQuery.Deferred( function( newDefer ) { + jQuery.each( tuples, function( _i, tuple ) { + + // Map tuples (progress, done, fail) to arguments (done, fail, progress) + var fn = isFunction( fns[ tuple[ 4 ] ] ) && fns[ tuple[ 4 ] ]; + + // deferred.progress(function() { bind to newDefer or newDefer.notify }) + // deferred.done(function() { bind to newDefer or newDefer.resolve }) + // deferred.fail(function() { bind to newDefer or newDefer.reject }) + deferred[ tuple[ 1 ] ]( function() { + var returned = fn && fn.apply( this, arguments ); + if ( returned && isFunction( returned.promise ) ) { + returned.promise() + .progress( newDefer.notify ) + .done( newDefer.resolve ) + .fail( newDefer.reject ); + } else { + newDefer[ tuple[ 0 ] + "With" ]( + this, + fn ? [ returned ] : arguments + ); + } + } ); + } ); + fns = null; + } ).promise(); + }, + then: function( onFulfilled, onRejected, onProgress ) { + var maxDepth = 0; + function resolve( depth, deferred, handler, special ) { + return function() { + var that = this, + args = arguments, + mightThrow = function() { + var returned, then; + + // Support: Promises/A+ section 2.3.3.3.3 + // https://promisesaplus.com/#point-59 + // Ignore double-resolution attempts + if ( depth < maxDepth ) { + return; + } + + returned = handler.apply( that, args ); + + // Support: Promises/A+ section 2.3.1 + // https://promisesaplus.com/#point-48 + if ( returned === deferred.promise() ) { + throw new TypeError( "Thenable self-resolution" ); + } + + // Support: Promises/A+ sections 2.3.3.1, 3.5 + // https://promisesaplus.com/#point-54 + // https://promisesaplus.com/#point-75 + // Retrieve `then` only once + then = returned && + + // Support: Promises/A+ section 2.3.4 + // https://promisesaplus.com/#point-64 + // Only check objects and functions for thenability + ( typeof returned === "object" || + typeof returned === "function" ) && + returned.then; + + // Handle a returned thenable + if ( isFunction( then ) ) { + + // Special processors (notify) just wait for resolution + if ( special ) { + then.call( + returned, + resolve( maxDepth, deferred, Identity, special ), + resolve( maxDepth, deferred, Thrower, special ) + ); + + // Normal processors (resolve) also hook into progress + } else { + + // ...and disregard older resolution values + maxDepth++; + + then.call( + returned, + resolve( maxDepth, deferred, Identity, special ), + resolve( maxDepth, deferred, Thrower, special ), + resolve( maxDepth, deferred, Identity, + deferred.notifyWith ) + ); + } + + // Handle all other returned values + } else { + + // Only substitute handlers pass on context + // and multiple values (non-spec behavior) + if ( handler !== Identity ) { + that = undefined; + args = [ returned ]; + } + + // Process the value(s) + // Default process is resolve + ( special || deferred.resolveWith )( that, args ); + } + }, + + // Only normal processors (resolve) catch and reject exceptions + process = special ? + mightThrow : + function() { + try { + mightThrow(); + } catch ( e ) { + + if ( jQuery.Deferred.exceptionHook ) { + jQuery.Deferred.exceptionHook( e, + process.stackTrace ); + } + + // Support: Promises/A+ section 2.3.3.3.4.1 + // https://promisesaplus.com/#point-61 + // Ignore post-resolution exceptions + if ( depth + 1 >= maxDepth ) { + + // Only substitute handlers pass on context + // and multiple values (non-spec behavior) + if ( handler !== Thrower ) { + that = undefined; + args = [ e ]; + } + + deferred.rejectWith( that, args ); + } + } + }; + + // Support: Promises/A+ section 2.3.3.3.1 + // https://promisesaplus.com/#point-57 + // Re-resolve promises immediately to dodge false rejection from + // subsequent errors + if ( depth ) { + process(); + } else { + + // Call an optional hook to record the stack, in case of exception + // since it's otherwise lost when execution goes async + if ( jQuery.Deferred.getStackHook ) { + process.stackTrace = jQuery.Deferred.getStackHook(); + } + window.setTimeout( process ); + } + }; + } + + return jQuery.Deferred( function( newDefer ) { + + // progress_handlers.add( ... ) + tuples[ 0 ][ 3 ].add( + resolve( + 0, + newDefer, + isFunction( onProgress ) ? + onProgress : + Identity, + newDefer.notifyWith + ) + ); + + // fulfilled_handlers.add( ... ) + tuples[ 1 ][ 3 ].add( + resolve( + 0, + newDefer, + isFunction( onFulfilled ) ? + onFulfilled : + Identity + ) + ); + + // rejected_handlers.add( ... ) + tuples[ 2 ][ 3 ].add( + resolve( + 0, + newDefer, + isFunction( onRejected ) ? + onRejected : + Thrower + ) + ); + } ).promise(); + }, + + // Get a promise for this deferred + // If obj is provided, the promise aspect is added to the object + promise: function( obj ) { + return obj != null ? jQuery.extend( obj, promise ) : promise; + } + }, + deferred = {}; + + // Add list-specific methods + jQuery.each( tuples, function( i, tuple ) { + var list = tuple[ 2 ], + stateString = tuple[ 5 ]; + + // promise.progress = list.add + // promise.done = list.add + // promise.fail = list.add + promise[ tuple[ 1 ] ] = list.add; + + // Handle state + if ( stateString ) { + list.add( + function() { + + // state = "resolved" (i.e., fulfilled) + // state = "rejected" + state = stateString; + }, + + // rejected_callbacks.disable + // fulfilled_callbacks.disable + tuples[ 3 - i ][ 2 ].disable, + + // rejected_handlers.disable + // fulfilled_handlers.disable + tuples[ 3 - i ][ 3 ].disable, + + // progress_callbacks.lock + tuples[ 0 ][ 2 ].lock, + + // progress_handlers.lock + tuples[ 0 ][ 3 ].lock + ); + } + + // progress_handlers.fire + // fulfilled_handlers.fire + // rejected_handlers.fire + list.add( tuple[ 3 ].fire ); + + // deferred.notify = function() { deferred.notifyWith(...) } + // deferred.resolve = function() { deferred.resolveWith(...) } + // deferred.reject = function() { deferred.rejectWith(...) } + deferred[ tuple[ 0 ] ] = function() { + deferred[ tuple[ 0 ] + "With" ]( this === deferred ? undefined : this, arguments ); + return this; + }; + + // deferred.notifyWith = list.fireWith + // deferred.resolveWith = list.fireWith + // deferred.rejectWith = list.fireWith + deferred[ tuple[ 0 ] + "With" ] = list.fireWith; + } ); + + // Make the deferred a promise + promise.promise( deferred ); + + // Call given func if any + if ( func ) { + func.call( deferred, deferred ); + } + + // All done! + return deferred; + }, + + // Deferred helper + when: function( singleValue ) { + var + + // count of uncompleted subordinates + remaining = arguments.length, + + // count of unprocessed arguments + i = remaining, + + // subordinate fulfillment data + resolveContexts = Array( i ), + resolveValues = slice.call( arguments ), + + // the primary Deferred + primary = jQuery.Deferred(), + + // subordinate callback factory + updateFunc = function( i ) { + return function( value ) { + resolveContexts[ i ] = this; + resolveValues[ i ] = arguments.length > 1 ? slice.call( arguments ) : value; + if ( !( --remaining ) ) { + primary.resolveWith( resolveContexts, resolveValues ); + } + }; + }; + + // Single- and empty arguments are adopted like Promise.resolve + if ( remaining <= 1 ) { + adoptValue( singleValue, primary.done( updateFunc( i ) ).resolve, primary.reject, + !remaining ); + + // Use .then() to unwrap secondary thenables (cf. gh-3000) + if ( primary.state() === "pending" || + isFunction( resolveValues[ i ] && resolveValues[ i ].then ) ) { + + return primary.then(); + } + } + + // Multiple arguments are aggregated like Promise.all array elements + while ( i-- ) { + adoptValue( resolveValues[ i ], updateFunc( i ), primary.reject ); + } + + return primary.promise(); + } +} ); + + +// These usually indicate a programmer mistake during development, +// warn about them ASAP rather than swallowing them by default. +var rerrorNames = /^(Eval|Internal|Range|Reference|Syntax|Type|URI)Error$/; + +jQuery.Deferred.exceptionHook = function( error, stack ) { + + // Support: IE 8 - 9 only + // Console exists when dev tools are open, which can happen at any time + if ( window.console && window.console.warn && error && rerrorNames.test( error.name ) ) { + window.console.warn( "jQuery.Deferred exception: " + error.message, error.stack, stack ); + } +}; + + + + +jQuery.readyException = function( error ) { + window.setTimeout( function() { + throw error; + } ); +}; + + + + +// The deferred used on DOM ready +var readyList = jQuery.Deferred(); + +jQuery.fn.ready = function( fn ) { + + readyList + .then( fn ) + + // Wrap jQuery.readyException in a function so that the lookup + // happens at the time of error handling instead of callback + // registration. + .catch( function( error ) { + jQuery.readyException( error ); + } ); + + return this; +}; + +jQuery.extend( { + + // Is the DOM ready to be used? Set to true once it occurs. + isReady: false, + + // A counter to track how many items to wait for before + // the ready event fires. See #6781 + readyWait: 1, + + // Handle when the DOM is ready + ready: function( wait ) { + + // Abort if there are pending holds or we're already ready + if ( wait === true ? --jQuery.readyWait : jQuery.isReady ) { + return; + } + + // Remember that the DOM is ready + jQuery.isReady = true; + + // If a normal DOM Ready event fired, decrement, and wait if need be + if ( wait !== true && --jQuery.readyWait > 0 ) { + return; + } + + // If there are functions bound, to execute + readyList.resolveWith( document, [ jQuery ] ); + } +} ); + +jQuery.ready.then = readyList.then; + +// The ready event handler and self cleanup method +function completed() { + document.removeEventListener( "DOMContentLoaded", completed ); + window.removeEventListener( "load", completed ); + jQuery.ready(); +} + +// Catch cases where $(document).ready() is called +// after the browser event has already occurred. +// Support: IE <=9 - 10 only +// Older IE sometimes signals "interactive" too soon +if ( document.readyState === "complete" || + ( document.readyState !== "loading" && !document.documentElement.doScroll ) ) { + + // Handle it asynchronously to allow scripts the opportunity to delay ready + window.setTimeout( jQuery.ready ); + +} else { + + // Use the handy event callback + document.addEventListener( "DOMContentLoaded", completed ); + + // A fallback to window.onload, that will always work + window.addEventListener( "load", completed ); +} + + + + +// Multifunctional method to get and set values of a collection +// The value/s can optionally be executed if it's a function +var access = function( elems, fn, key, value, chainable, emptyGet, raw ) { + var i = 0, + len = elems.length, + bulk = key == null; + + // Sets many values + if ( toType( key ) === "object" ) { + chainable = true; + for ( i in key ) { + access( elems, fn, i, key[ i ], true, emptyGet, raw ); + } + + // Sets one value + } else if ( value !== undefined ) { + chainable = true; + + if ( !isFunction( value ) ) { + raw = true; + } + + if ( bulk ) { + + // Bulk operations run against the entire set + if ( raw ) { + fn.call( elems, value ); + fn = null; + + // ...except when executing function values + } else { + bulk = fn; + fn = function( elem, _key, value ) { + return bulk.call( jQuery( elem ), value ); + }; + } + } + + if ( fn ) { + for ( ; i < len; i++ ) { + fn( + elems[ i ], key, raw ? + value : + value.call( elems[ i ], i, fn( elems[ i ], key ) ) + ); + } + } + } + + if ( chainable ) { + return elems; + } + + // Gets + if ( bulk ) { + return fn.call( elems ); + } + + return len ? fn( elems[ 0 ], key ) : emptyGet; +}; + + +// Matches dashed string for camelizing +var rmsPrefix = /^-ms-/, + rdashAlpha = /-([a-z])/g; + +// Used by camelCase as callback to replace() +function fcamelCase( _all, letter ) { + return letter.toUpperCase(); +} + +// Convert dashed to camelCase; used by the css and data modules +// Support: IE <=9 - 11, Edge 12 - 15 +// Microsoft forgot to hump their vendor prefix (#9572) +function camelCase( string ) { + return string.replace( rmsPrefix, "ms-" ).replace( rdashAlpha, fcamelCase ); +} +var acceptData = function( owner ) { + + // Accepts only: + // - Node + // - Node.ELEMENT_NODE + // - Node.DOCUMENT_NODE + // - Object + // - Any + return owner.nodeType === 1 || owner.nodeType === 9 || !( +owner.nodeType ); +}; + + + + +function Data() { + this.expando = jQuery.expando + Data.uid++; +} + +Data.uid = 1; + +Data.prototype = { + + cache: function( owner ) { + + // Check if the owner object already has a cache + var value = owner[ this.expando ]; + + // If not, create one + if ( !value ) { + value = {}; + + // We can accept data for non-element nodes in modern browsers, + // but we should not, see #8335. + // Always return an empty object. + if ( acceptData( owner ) ) { + + // If it is a node unlikely to be stringify-ed or looped over + // use plain assignment + if ( owner.nodeType ) { + owner[ this.expando ] = value; + + // Otherwise secure it in a non-enumerable property + // configurable must be true to allow the property to be + // deleted when data is removed + } else { + Object.defineProperty( owner, this.expando, { + value: value, + configurable: true + } ); + } + } + } + + return value; + }, + set: function( owner, data, value ) { + var prop, + cache = this.cache( owner ); + + // Handle: [ owner, key, value ] args + // Always use camelCase key (gh-2257) + if ( typeof data === "string" ) { + cache[ camelCase( data ) ] = value; + + // Handle: [ owner, { properties } ] args + } else { + + // Copy the properties one-by-one to the cache object + for ( prop in data ) { + cache[ camelCase( prop ) ] = data[ prop ]; + } + } + return cache; + }, + get: function( owner, key ) { + return key === undefined ? + this.cache( owner ) : + + // Always use camelCase key (gh-2257) + owner[ this.expando ] && owner[ this.expando ][ camelCase( key ) ]; + }, + access: function( owner, key, value ) { + + // In cases where either: + // + // 1. No key was specified + // 2. A string key was specified, but no value provided + // + // Take the "read" path and allow the get method to determine + // which value to return, respectively either: + // + // 1. The entire cache object + // 2. The data stored at the key + // + if ( key === undefined || + ( ( key && typeof key === "string" ) && value === undefined ) ) { + + return this.get( owner, key ); + } + + // When the key is not a string, or both a key and value + // are specified, set or extend (existing objects) with either: + // + // 1. An object of properties + // 2. A key and value + // + this.set( owner, key, value ); + + // Since the "set" path can have two possible entry points + // return the expected data based on which path was taken[*] + return value !== undefined ? value : key; + }, + remove: function( owner, key ) { + var i, + cache = owner[ this.expando ]; + + if ( cache === undefined ) { + return; + } + + if ( key !== undefined ) { + + // Support array or space separated string of keys + if ( Array.isArray( key ) ) { + + // If key is an array of keys... + // We always set camelCase keys, so remove that. + key = key.map( camelCase ); + } else { + key = camelCase( key ); + + // If a key with the spaces exists, use it. + // Otherwise, create an array by matching non-whitespace + key = key in cache ? + [ key ] : + ( key.match( rnothtmlwhite ) || [] ); + } + + i = key.length; + + while ( i-- ) { + delete cache[ key[ i ] ]; + } + } + + // Remove the expando if there's no more data + if ( key === undefined || jQuery.isEmptyObject( cache ) ) { + + // Support: Chrome <=35 - 45 + // Webkit & Blink performance suffers when deleting properties + // from DOM nodes, so set to undefined instead + // https://bugs.chromium.org/p/chromium/issues/detail?id=378607 (bug restricted) + if ( owner.nodeType ) { + owner[ this.expando ] = undefined; + } else { + delete owner[ this.expando ]; + } + } + }, + hasData: function( owner ) { + var cache = owner[ this.expando ]; + return cache !== undefined && !jQuery.isEmptyObject( cache ); + } +}; +var dataPriv = new Data(); + +var dataUser = new Data(); + + + +// Implementation Summary +// +// 1. Enforce API surface and semantic compatibility with 1.9.x branch +// 2. Improve the module's maintainability by reducing the storage +// paths to a single mechanism. +// 3. Use the same single mechanism to support "private" and "user" data. +// 4. _Never_ expose "private" data to user code (TODO: Drop _data, _removeData) +// 5. Avoid exposing implementation details on user objects (eg. expando properties) +// 6. Provide a clear path for implementation upgrade to WeakMap in 2014 + +var rbrace = /^(?:\{[\w\W]*\}|\[[\w\W]*\])$/, + rmultiDash = /[A-Z]/g; + +function getData( data ) { + if ( data === "true" ) { + return true; + } + + if ( data === "false" ) { + return false; + } + + if ( data === "null" ) { + return null; + } + + // Only convert to a number if it doesn't change the string + if ( data === +data + "" ) { + return +data; + } + + if ( rbrace.test( data ) ) { + return JSON.parse( data ); + } + + return data; +} + +function dataAttr( elem, key, data ) { + var name; + + // If nothing was found internally, try to fetch any + // data from the HTML5 data-* attribute + if ( data === undefined && elem.nodeType === 1 ) { + name = "data-" + key.replace( rmultiDash, "-$&" ).toLowerCase(); + data = elem.getAttribute( name ); + + if ( typeof data === "string" ) { + try { + data = getData( data ); + } catch ( e ) {} + + // Make sure we set the data so it isn't changed later + dataUser.set( elem, key, data ); + } else { + data = undefined; + } + } + return data; +} + +jQuery.extend( { + hasData: function( elem ) { + return dataUser.hasData( elem ) || dataPriv.hasData( elem ); + }, + + data: function( elem, name, data ) { + return dataUser.access( elem, name, data ); + }, + + removeData: function( elem, name ) { + dataUser.remove( elem, name ); + }, + + // TODO: Now that all calls to _data and _removeData have been replaced + // with direct calls to dataPriv methods, these can be deprecated. + _data: function( elem, name, data ) { + return dataPriv.access( elem, name, data ); + }, + + _removeData: function( elem, name ) { + dataPriv.remove( elem, name ); + } +} ); + +jQuery.fn.extend( { + data: function( key, value ) { + var i, name, data, + elem = this[ 0 ], + attrs = elem && elem.attributes; + + // Gets all values + if ( key === undefined ) { + if ( this.length ) { + data = dataUser.get( elem ); + + if ( elem.nodeType === 1 && !dataPriv.get( elem, "hasDataAttrs" ) ) { + i = attrs.length; + while ( i-- ) { + + // Support: IE 11 only + // The attrs elements can be null (#14894) + if ( attrs[ i ] ) { + name = attrs[ i ].name; + if ( name.indexOf( "data-" ) === 0 ) { + name = camelCase( name.slice( 5 ) ); + dataAttr( elem, name, data[ name ] ); + } + } + } + dataPriv.set( elem, "hasDataAttrs", true ); + } + } + + return data; + } + + // Sets multiple values + if ( typeof key === "object" ) { + return this.each( function() { + dataUser.set( this, key ); + } ); + } + + return access( this, function( value ) { + var data; + + // The calling jQuery object (element matches) is not empty + // (and therefore has an element appears at this[ 0 ]) and the + // `value` parameter was not undefined. An empty jQuery object + // will result in `undefined` for elem = this[ 0 ] which will + // throw an exception if an attempt to read a data cache is made. + if ( elem && value === undefined ) { + + // Attempt to get data from the cache + // The key will always be camelCased in Data + data = dataUser.get( elem, key ); + if ( data !== undefined ) { + return data; + } + + // Attempt to "discover" the data in + // HTML5 custom data-* attrs + data = dataAttr( elem, key ); + if ( data !== undefined ) { + return data; + } + + // We tried really hard, but the data doesn't exist. + return; + } + + // Set the data... + this.each( function() { + + // We always store the camelCased key + dataUser.set( this, key, value ); + } ); + }, null, value, arguments.length > 1, null, true ); + }, + + removeData: function( key ) { + return this.each( function() { + dataUser.remove( this, key ); + } ); + } +} ); + + +jQuery.extend( { + queue: function( elem, type, data ) { + var queue; + + if ( elem ) { + type = ( type || "fx" ) + "queue"; + queue = dataPriv.get( elem, type ); + + // Speed up dequeue by getting out quickly if this is just a lookup + if ( data ) { + if ( !queue || Array.isArray( data ) ) { + queue = dataPriv.access( elem, type, jQuery.makeArray( data ) ); + } else { + queue.push( data ); + } + } + return queue || []; + } + }, + + dequeue: function( elem, type ) { + type = type || "fx"; + + var queue = jQuery.queue( elem, type ), + startLength = queue.length, + fn = queue.shift(), + hooks = jQuery._queueHooks( elem, type ), + next = function() { + jQuery.dequeue( elem, type ); + }; + + // If the fx queue is dequeued, always remove the progress sentinel + if ( fn === "inprogress" ) { + fn = queue.shift(); + startLength--; + } + + if ( fn ) { + + // Add a progress sentinel to prevent the fx queue from being + // automatically dequeued + if ( type === "fx" ) { + queue.unshift( "inprogress" ); + } + + // Clear up the last queue stop function + delete hooks.stop; + fn.call( elem, next, hooks ); + } + + if ( !startLength && hooks ) { + hooks.empty.fire(); + } + }, + + // Not public - generate a queueHooks object, or return the current one + _queueHooks: function( elem, type ) { + var key = type + "queueHooks"; + return dataPriv.get( elem, key ) || dataPriv.access( elem, key, { + empty: jQuery.Callbacks( "once memory" ).add( function() { + dataPriv.remove( elem, [ type + "queue", key ] ); + } ) + } ); + } +} ); + +jQuery.fn.extend( { + queue: function( type, data ) { + var setter = 2; + + if ( typeof type !== "string" ) { + data = type; + type = "fx"; + setter--; + } + + if ( arguments.length < setter ) { + return jQuery.queue( this[ 0 ], type ); + } + + return data === undefined ? + this : + this.each( function() { + var queue = jQuery.queue( this, type, data ); + + // Ensure a hooks for this queue + jQuery._queueHooks( this, type ); + + if ( type === "fx" && queue[ 0 ] !== "inprogress" ) { + jQuery.dequeue( this, type ); + } + } ); + }, + dequeue: function( type ) { + return this.each( function() { + jQuery.dequeue( this, type ); + } ); + }, + clearQueue: function( type ) { + return this.queue( type || "fx", [] ); + }, + + // Get a promise resolved when queues of a certain type + // are emptied (fx is the type by default) + promise: function( type, obj ) { + var tmp, + count = 1, + defer = jQuery.Deferred(), + elements = this, + i = this.length, + resolve = function() { + if ( !( --count ) ) { + defer.resolveWith( elements, [ elements ] ); + } + }; + + if ( typeof type !== "string" ) { + obj = type; + type = undefined; + } + type = type || "fx"; + + while ( i-- ) { + tmp = dataPriv.get( elements[ i ], type + "queueHooks" ); + if ( tmp && tmp.empty ) { + count++; + tmp.empty.add( resolve ); + } + } + resolve(); + return defer.promise( obj ); + } +} ); +var pnum = ( /[+-]?(?:\d*\.|)\d+(?:[eE][+-]?\d+|)/ ).source; + +var rcssNum = new RegExp( "^(?:([+-])=|)(" + pnum + ")([a-z%]*)$", "i" ); + + +var cssExpand = [ "Top", "Right", "Bottom", "Left" ]; + +var documentElement = document.documentElement; + + + + var isAttached = function( elem ) { + return jQuery.contains( elem.ownerDocument, elem ); + }, + composed = { composed: true }; + + // Support: IE 9 - 11+, Edge 12 - 18+, iOS 10.0 - 10.2 only + // Check attachment across shadow DOM boundaries when possible (gh-3504) + // Support: iOS 10.0-10.2 only + // Early iOS 10 versions support `attachShadow` but not `getRootNode`, + // leading to errors. We need to check for `getRootNode`. + if ( documentElement.getRootNode ) { + isAttached = function( elem ) { + return jQuery.contains( elem.ownerDocument, elem ) || + elem.getRootNode( composed ) === elem.ownerDocument; + }; + } +var isHiddenWithinTree = function( elem, el ) { + + // isHiddenWithinTree might be called from jQuery#filter function; + // in that case, element will be second argument + elem = el || elem; + + // Inline style trumps all + return elem.style.display === "none" || + elem.style.display === "" && + + // Otherwise, check computed style + // Support: Firefox <=43 - 45 + // Disconnected elements can have computed display: none, so first confirm that elem is + // in the document. + isAttached( elem ) && + + jQuery.css( elem, "display" ) === "none"; + }; + + + +function adjustCSS( elem, prop, valueParts, tween ) { + var adjusted, scale, + maxIterations = 20, + currentValue = tween ? + function() { + return tween.cur(); + } : + function() { + return jQuery.css( elem, prop, "" ); + }, + initial = currentValue(), + unit = valueParts && valueParts[ 3 ] || ( jQuery.cssNumber[ prop ] ? "" : "px" ), + + // Starting value computation is required for potential unit mismatches + initialInUnit = elem.nodeType && + ( jQuery.cssNumber[ prop ] || unit !== "px" && +initial ) && + rcssNum.exec( jQuery.css( elem, prop ) ); + + if ( initialInUnit && initialInUnit[ 3 ] !== unit ) { + + // Support: Firefox <=54 + // Halve the iteration target value to prevent interference from CSS upper bounds (gh-2144) + initial = initial / 2; + + // Trust units reported by jQuery.css + unit = unit || initialInUnit[ 3 ]; + + // Iteratively approximate from a nonzero starting point + initialInUnit = +initial || 1; + + while ( maxIterations-- ) { + + // Evaluate and update our best guess (doubling guesses that zero out). + // Finish if the scale equals or crosses 1 (making the old*new product non-positive). + jQuery.style( elem, prop, initialInUnit + unit ); + if ( ( 1 - scale ) * ( 1 - ( scale = currentValue() / initial || 0.5 ) ) <= 0 ) { + maxIterations = 0; + } + initialInUnit = initialInUnit / scale; + + } + + initialInUnit = initialInUnit * 2; + jQuery.style( elem, prop, initialInUnit + unit ); + + // Make sure we update the tween properties later on + valueParts = valueParts || []; + } + + if ( valueParts ) { + initialInUnit = +initialInUnit || +initial || 0; + + // Apply relative offset (+=/-=) if specified + adjusted = valueParts[ 1 ] ? + initialInUnit + ( valueParts[ 1 ] + 1 ) * valueParts[ 2 ] : + +valueParts[ 2 ]; + if ( tween ) { + tween.unit = unit; + tween.start = initialInUnit; + tween.end = adjusted; + } + } + return adjusted; +} + + +var defaultDisplayMap = {}; + +function getDefaultDisplay( elem ) { + var temp, + doc = elem.ownerDocument, + nodeName = elem.nodeName, + display = defaultDisplayMap[ nodeName ]; + + if ( display ) { + return display; + } + + temp = doc.body.appendChild( doc.createElement( nodeName ) ); + display = jQuery.css( temp, "display" ); + + temp.parentNode.removeChild( temp ); + + if ( display === "none" ) { + display = "block"; + } + defaultDisplayMap[ nodeName ] = display; + + return display; +} + +function showHide( elements, show ) { + var display, elem, + values = [], + index = 0, + length = elements.length; + + // Determine new display value for elements that need to change + for ( ; index < length; index++ ) { + elem = elements[ index ]; + if ( !elem.style ) { + continue; + } + + display = elem.style.display; + if ( show ) { + + // Since we force visibility upon cascade-hidden elements, an immediate (and slow) + // check is required in this first loop unless we have a nonempty display value (either + // inline or about-to-be-restored) + if ( display === "none" ) { + values[ index ] = dataPriv.get( elem, "display" ) || null; + if ( !values[ index ] ) { + elem.style.display = ""; + } + } + if ( elem.style.display === "" && isHiddenWithinTree( elem ) ) { + values[ index ] = getDefaultDisplay( elem ); + } + } else { + if ( display !== "none" ) { + values[ index ] = "none"; + + // Remember what we're overwriting + dataPriv.set( elem, "display", display ); + } + } + } + + // Set the display of the elements in a second loop to avoid constant reflow + for ( index = 0; index < length; index++ ) { + if ( values[ index ] != null ) { + elements[ index ].style.display = values[ index ]; + } + } + + return elements; +} + +jQuery.fn.extend( { + show: function() { + return showHide( this, true ); + }, + hide: function() { + return showHide( this ); + }, + toggle: function( state ) { + if ( typeof state === "boolean" ) { + return state ? this.show() : this.hide(); + } + + return this.each( function() { + if ( isHiddenWithinTree( this ) ) { + jQuery( this ).show(); + } else { + jQuery( this ).hide(); + } + } ); + } +} ); +var rcheckableType = ( /^(?:checkbox|radio)$/i ); + +var rtagName = ( /<([a-z][^\/\0>\x20\t\r\n\f]*)/i ); + +var rscriptType = ( /^$|^module$|\/(?:java|ecma)script/i ); + + + +( function() { + var fragment = document.createDocumentFragment(), + div = fragment.appendChild( document.createElement( "div" ) ), + input = document.createElement( "input" ); + + // Support: Android 4.0 - 4.3 only + // Check state lost if the name is set (#11217) + // Support: Windows Web Apps (WWA) + // `name` and `type` must use .setAttribute for WWA (#14901) + input.setAttribute( "type", "radio" ); + input.setAttribute( "checked", "checked" ); + input.setAttribute( "name", "t" ); + + div.appendChild( input ); + + // Support: Android <=4.1 only + // Older WebKit doesn't clone checked state correctly in fragments + support.checkClone = div.cloneNode( true ).cloneNode( true ).lastChild.checked; + + // Support: IE <=11 only + // Make sure textarea (and checkbox) defaultValue is properly cloned + div.innerHTML = ""; + support.noCloneChecked = !!div.cloneNode( true ).lastChild.defaultValue; + + // Support: IE <=9 only + // IE <=9 replaces "; + support.option = !!div.lastChild; +} )(); + + +// We have to close these tags to support XHTML (#13200) +var wrapMap = { + + // XHTML parsers do not magically insert elements in the + // same way that tag soup parsers do. So we cannot shorten + // this by omitting or other required elements. + thead: [ 1, "", "
" ], + col: [ 2, "", "
" ], + tr: [ 2, "", "
" ], + td: [ 3, "", "
" ], + + _default: [ 0, "", "" ] +}; + +wrapMap.tbody = wrapMap.tfoot = wrapMap.colgroup = wrapMap.caption = wrapMap.thead; +wrapMap.th = wrapMap.td; + +// Support: IE <=9 only +if ( !support.option ) { + wrapMap.optgroup = wrapMap.option = [ 1, "" ]; +} + + +function getAll( context, tag ) { + + // Support: IE <=9 - 11 only + // Use typeof to avoid zero-argument method invocation on host objects (#15151) + var ret; + + if ( typeof context.getElementsByTagName !== "undefined" ) { + ret = context.getElementsByTagName( tag || "*" ); + + } else if ( typeof context.querySelectorAll !== "undefined" ) { + ret = context.querySelectorAll( tag || "*" ); + + } else { + ret = []; + } + + if ( tag === undefined || tag && nodeName( context, tag ) ) { + return jQuery.merge( [ context ], ret ); + } + + return ret; +} + + +// Mark scripts as having already been evaluated +function setGlobalEval( elems, refElements ) { + var i = 0, + l = elems.length; + + for ( ; i < l; i++ ) { + dataPriv.set( + elems[ i ], + "globalEval", + !refElements || dataPriv.get( refElements[ i ], "globalEval" ) + ); + } +} + + +var rhtml = /<|&#?\w+;/; + +function buildFragment( elems, context, scripts, selection, ignored ) { + var elem, tmp, tag, wrap, attached, j, + fragment = context.createDocumentFragment(), + nodes = [], + i = 0, + l = elems.length; + + for ( ; i < l; i++ ) { + elem = elems[ i ]; + + if ( elem || elem === 0 ) { + + // Add nodes directly + if ( toType( elem ) === "object" ) { + + // Support: Android <=4.0 only, PhantomJS 1 only + // push.apply(_, arraylike) throws on ancient WebKit + jQuery.merge( nodes, elem.nodeType ? [ elem ] : elem ); + + // Convert non-html into a text node + } else if ( !rhtml.test( elem ) ) { + nodes.push( context.createTextNode( elem ) ); + + // Convert html into DOM nodes + } else { + tmp = tmp || fragment.appendChild( context.createElement( "div" ) ); + + // Deserialize a standard representation + tag = ( rtagName.exec( elem ) || [ "", "" ] )[ 1 ].toLowerCase(); + wrap = wrapMap[ tag ] || wrapMap._default; + tmp.innerHTML = wrap[ 1 ] + jQuery.htmlPrefilter( elem ) + wrap[ 2 ]; + + // Descend through wrappers to the right content + j = wrap[ 0 ]; + while ( j-- ) { + tmp = tmp.lastChild; + } + + // Support: Android <=4.0 only, PhantomJS 1 only + // push.apply(_, arraylike) throws on ancient WebKit + jQuery.merge( nodes, tmp.childNodes ); + + // Remember the top-level container + tmp = fragment.firstChild; + + // Ensure the created nodes are orphaned (#12392) + tmp.textContent = ""; + } + } + } + + // Remove wrapper from fragment + fragment.textContent = ""; + + i = 0; + while ( ( elem = nodes[ i++ ] ) ) { + + // Skip elements already in the context collection (trac-4087) + if ( selection && jQuery.inArray( elem, selection ) > -1 ) { + if ( ignored ) { + ignored.push( elem ); + } + continue; + } + + attached = isAttached( elem ); + + // Append to fragment + tmp = getAll( fragment.appendChild( elem ), "script" ); + + // Preserve script evaluation history + if ( attached ) { + setGlobalEval( tmp ); + } + + // Capture executables + if ( scripts ) { + j = 0; + while ( ( elem = tmp[ j++ ] ) ) { + if ( rscriptType.test( elem.type || "" ) ) { + scripts.push( elem ); + } + } + } + } + + return fragment; +} + + +var rtypenamespace = /^([^.]*)(?:\.(.+)|)/; + +function returnTrue() { + return true; +} + +function returnFalse() { + return false; +} + +// Support: IE <=9 - 11+ +// focus() and blur() are asynchronous, except when they are no-op. +// So expect focus to be synchronous when the element is already active, +// and blur to be synchronous when the element is not already active. +// (focus and blur are always synchronous in other supported browsers, +// this just defines when we can count on it). +function expectSync( elem, type ) { + return ( elem === safeActiveElement() ) === ( type === "focus" ); +} + +// Support: IE <=9 only +// Accessing document.activeElement can throw unexpectedly +// https://bugs.jquery.com/ticket/13393 +function safeActiveElement() { + try { + return document.activeElement; + } catch ( err ) { } +} + +function on( elem, types, selector, data, fn, one ) { + var origFn, type; + + // Types can be a map of types/handlers + if ( typeof types === "object" ) { + + // ( types-Object, selector, data ) + if ( typeof selector !== "string" ) { + + // ( types-Object, data ) + data = data || selector; + selector = undefined; + } + for ( type in types ) { + on( elem, type, selector, data, types[ type ], one ); + } + return elem; + } + + if ( data == null && fn == null ) { + + // ( types, fn ) + fn = selector; + data = selector = undefined; + } else if ( fn == null ) { + if ( typeof selector === "string" ) { + + // ( types, selector, fn ) + fn = data; + data = undefined; + } else { + + // ( types, data, fn ) + fn = data; + data = selector; + selector = undefined; + } + } + if ( fn === false ) { + fn = returnFalse; + } else if ( !fn ) { + return elem; + } + + if ( one === 1 ) { + origFn = fn; + fn = function( event ) { + + // Can use an empty set, since event contains the info + jQuery().off( event ); + return origFn.apply( this, arguments ); + }; + + // Use same guid so caller can remove using origFn + fn.guid = origFn.guid || ( origFn.guid = jQuery.guid++ ); + } + return elem.each( function() { + jQuery.event.add( this, types, fn, data, selector ); + } ); +} + +/* + * Helper functions for managing events -- not part of the public interface. + * Props to Dean Edwards' addEvent library for many of the ideas. + */ +jQuery.event = { + + global: {}, + + add: function( elem, types, handler, data, selector ) { + + var handleObjIn, eventHandle, tmp, + events, t, handleObj, + special, handlers, type, namespaces, origType, + elemData = dataPriv.get( elem ); + + // Only attach events to objects that accept data + if ( !acceptData( elem ) ) { + return; + } + + // Caller can pass in an object of custom data in lieu of the handler + if ( handler.handler ) { + handleObjIn = handler; + handler = handleObjIn.handler; + selector = handleObjIn.selector; + } + + // Ensure that invalid selectors throw exceptions at attach time + // Evaluate against documentElement in case elem is a non-element node (e.g., document) + if ( selector ) { + jQuery.find.matchesSelector( documentElement, selector ); + } + + // Make sure that the handler has a unique ID, used to find/remove it later + if ( !handler.guid ) { + handler.guid = jQuery.guid++; + } + + // Init the element's event structure and main handler, if this is the first + if ( !( events = elemData.events ) ) { + events = elemData.events = Object.create( null ); + } + if ( !( eventHandle = elemData.handle ) ) { + eventHandle = elemData.handle = function( e ) { + + // Discard the second event of a jQuery.event.trigger() and + // when an event is called after a page has unloaded + return typeof jQuery !== "undefined" && jQuery.event.triggered !== e.type ? + jQuery.event.dispatch.apply( elem, arguments ) : undefined; + }; + } + + // Handle multiple events separated by a space + types = ( types || "" ).match( rnothtmlwhite ) || [ "" ]; + t = types.length; + while ( t-- ) { + tmp = rtypenamespace.exec( types[ t ] ) || []; + type = origType = tmp[ 1 ]; + namespaces = ( tmp[ 2 ] || "" ).split( "." ).sort(); + + // There *must* be a type, no attaching namespace-only handlers + if ( !type ) { + continue; + } + + // If event changes its type, use the special event handlers for the changed type + special = jQuery.event.special[ type ] || {}; + + // If selector defined, determine special event api type, otherwise given type + type = ( selector ? special.delegateType : special.bindType ) || type; + + // Update special based on newly reset type + special = jQuery.event.special[ type ] || {}; + + // handleObj is passed to all event handlers + handleObj = jQuery.extend( { + type: type, + origType: origType, + data: data, + handler: handler, + guid: handler.guid, + selector: selector, + needsContext: selector && jQuery.expr.match.needsContext.test( selector ), + namespace: namespaces.join( "." ) + }, handleObjIn ); + + // Init the event handler queue if we're the first + if ( !( handlers = events[ type ] ) ) { + handlers = events[ type ] = []; + handlers.delegateCount = 0; + + // Only use addEventListener if the special events handler returns false + if ( !special.setup || + special.setup.call( elem, data, namespaces, eventHandle ) === false ) { + + if ( elem.addEventListener ) { + elem.addEventListener( type, eventHandle ); + } + } + } + + if ( special.add ) { + special.add.call( elem, handleObj ); + + if ( !handleObj.handler.guid ) { + handleObj.handler.guid = handler.guid; + } + } + + // Add to the element's handler list, delegates in front + if ( selector ) { + handlers.splice( handlers.delegateCount++, 0, handleObj ); + } else { + handlers.push( handleObj ); + } + + // Keep track of which events have ever been used, for event optimization + jQuery.event.global[ type ] = true; + } + + }, + + // Detach an event or set of events from an element + remove: function( elem, types, handler, selector, mappedTypes ) { + + var j, origCount, tmp, + events, t, handleObj, + special, handlers, type, namespaces, origType, + elemData = dataPriv.hasData( elem ) && dataPriv.get( elem ); + + if ( !elemData || !( events = elemData.events ) ) { + return; + } + + // Once for each type.namespace in types; type may be omitted + types = ( types || "" ).match( rnothtmlwhite ) || [ "" ]; + t = types.length; + while ( t-- ) { + tmp = rtypenamespace.exec( types[ t ] ) || []; + type = origType = tmp[ 1 ]; + namespaces = ( tmp[ 2 ] || "" ).split( "." ).sort(); + + // Unbind all events (on this namespace, if provided) for the element + if ( !type ) { + for ( type in events ) { + jQuery.event.remove( elem, type + types[ t ], handler, selector, true ); + } + continue; + } + + special = jQuery.event.special[ type ] || {}; + type = ( selector ? special.delegateType : special.bindType ) || type; + handlers = events[ type ] || []; + tmp = tmp[ 2 ] && + new RegExp( "(^|\\.)" + namespaces.join( "\\.(?:.*\\.|)" ) + "(\\.|$)" ); + + // Remove matching events + origCount = j = handlers.length; + while ( j-- ) { + handleObj = handlers[ j ]; + + if ( ( mappedTypes || origType === handleObj.origType ) && + ( !handler || handler.guid === handleObj.guid ) && + ( !tmp || tmp.test( handleObj.namespace ) ) && + ( !selector || selector === handleObj.selector || + selector === "**" && handleObj.selector ) ) { + handlers.splice( j, 1 ); + + if ( handleObj.selector ) { + handlers.delegateCount--; + } + if ( special.remove ) { + special.remove.call( elem, handleObj ); + } + } + } + + // Remove generic event handler if we removed something and no more handlers exist + // (avoids potential for endless recursion during removal of special event handlers) + if ( origCount && !handlers.length ) { + if ( !special.teardown || + special.teardown.call( elem, namespaces, elemData.handle ) === false ) { + + jQuery.removeEvent( elem, type, elemData.handle ); + } + + delete events[ type ]; + } + } + + // Remove data and the expando if it's no longer used + if ( jQuery.isEmptyObject( events ) ) { + dataPriv.remove( elem, "handle events" ); + } + }, + + dispatch: function( nativeEvent ) { + + var i, j, ret, matched, handleObj, handlerQueue, + args = new Array( arguments.length ), + + // Make a writable jQuery.Event from the native event object + event = jQuery.event.fix( nativeEvent ), + + handlers = ( + dataPriv.get( this, "events" ) || Object.create( null ) + )[ event.type ] || [], + special = jQuery.event.special[ event.type ] || {}; + + // Use the fix-ed jQuery.Event rather than the (read-only) native event + args[ 0 ] = event; + + for ( i = 1; i < arguments.length; i++ ) { + args[ i ] = arguments[ i ]; + } + + event.delegateTarget = this; + + // Call the preDispatch hook for the mapped type, and let it bail if desired + if ( special.preDispatch && special.preDispatch.call( this, event ) === false ) { + return; + } + + // Determine handlers + handlerQueue = jQuery.event.handlers.call( this, event, handlers ); + + // Run delegates first; they may want to stop propagation beneath us + i = 0; + while ( ( matched = handlerQueue[ i++ ] ) && !event.isPropagationStopped() ) { + event.currentTarget = matched.elem; + + j = 0; + while ( ( handleObj = matched.handlers[ j++ ] ) && + !event.isImmediatePropagationStopped() ) { + + // If the event is namespaced, then each handler is only invoked if it is + // specially universal or its namespaces are a superset of the event's. + if ( !event.rnamespace || handleObj.namespace === false || + event.rnamespace.test( handleObj.namespace ) ) { + + event.handleObj = handleObj; + event.data = handleObj.data; + + ret = ( ( jQuery.event.special[ handleObj.origType ] || {} ).handle || + handleObj.handler ).apply( matched.elem, args ); + + if ( ret !== undefined ) { + if ( ( event.result = ret ) === false ) { + event.preventDefault(); + event.stopPropagation(); + } + } + } + } + } + + // Call the postDispatch hook for the mapped type + if ( special.postDispatch ) { + special.postDispatch.call( this, event ); + } + + return event.result; + }, + + handlers: function( event, handlers ) { + var i, handleObj, sel, matchedHandlers, matchedSelectors, + handlerQueue = [], + delegateCount = handlers.delegateCount, + cur = event.target; + + // Find delegate handlers + if ( delegateCount && + + // Support: IE <=9 + // Black-hole SVG instance trees (trac-13180) + cur.nodeType && + + // Support: Firefox <=42 + // Suppress spec-violating clicks indicating a non-primary pointer button (trac-3861) + // https://www.w3.org/TR/DOM-Level-3-Events/#event-type-click + // Support: IE 11 only + // ...but not arrow key "clicks" of radio inputs, which can have `button` -1 (gh-2343) + !( event.type === "click" && event.button >= 1 ) ) { + + for ( ; cur !== this; cur = cur.parentNode || this ) { + + // Don't check non-elements (#13208) + // Don't process clicks on disabled elements (#6911, #8165, #11382, #11764) + if ( cur.nodeType === 1 && !( event.type === "click" && cur.disabled === true ) ) { + matchedHandlers = []; + matchedSelectors = {}; + for ( i = 0; i < delegateCount; i++ ) { + handleObj = handlers[ i ]; + + // Don't conflict with Object.prototype properties (#13203) + sel = handleObj.selector + " "; + + if ( matchedSelectors[ sel ] === undefined ) { + matchedSelectors[ sel ] = handleObj.needsContext ? + jQuery( sel, this ).index( cur ) > -1 : + jQuery.find( sel, this, null, [ cur ] ).length; + } + if ( matchedSelectors[ sel ] ) { + matchedHandlers.push( handleObj ); + } + } + if ( matchedHandlers.length ) { + handlerQueue.push( { elem: cur, handlers: matchedHandlers } ); + } + } + } + } + + // Add the remaining (directly-bound) handlers + cur = this; + if ( delegateCount < handlers.length ) { + handlerQueue.push( { elem: cur, handlers: handlers.slice( delegateCount ) } ); + } + + return handlerQueue; + }, + + addProp: function( name, hook ) { + Object.defineProperty( jQuery.Event.prototype, name, { + enumerable: true, + configurable: true, + + get: isFunction( hook ) ? + function() { + if ( this.originalEvent ) { + return hook( this.originalEvent ); + } + } : + function() { + if ( this.originalEvent ) { + return this.originalEvent[ name ]; + } + }, + + set: function( value ) { + Object.defineProperty( this, name, { + enumerable: true, + configurable: true, + writable: true, + value: value + } ); + } + } ); + }, + + fix: function( originalEvent ) { + return originalEvent[ jQuery.expando ] ? + originalEvent : + new jQuery.Event( originalEvent ); + }, + + special: { + load: { + + // Prevent triggered image.load events from bubbling to window.load + noBubble: true + }, + click: { + + // Utilize native event to ensure correct state for checkable inputs + setup: function( data ) { + + // For mutual compressibility with _default, replace `this` access with a local var. + // `|| data` is dead code meant only to preserve the variable through minification. + var el = this || data; + + // Claim the first handler + if ( rcheckableType.test( el.type ) && + el.click && nodeName( el, "input" ) ) { + + // dataPriv.set( el, "click", ... ) + leverageNative( el, "click", returnTrue ); + } + + // Return false to allow normal processing in the caller + return false; + }, + trigger: function( data ) { + + // For mutual compressibility with _default, replace `this` access with a local var. + // `|| data` is dead code meant only to preserve the variable through minification. + var el = this || data; + + // Force setup before triggering a click + if ( rcheckableType.test( el.type ) && + el.click && nodeName( el, "input" ) ) { + + leverageNative( el, "click" ); + } + + // Return non-false to allow normal event-path propagation + return true; + }, + + // For cross-browser consistency, suppress native .click() on links + // Also prevent it if we're currently inside a leveraged native-event stack + _default: function( event ) { + var target = event.target; + return rcheckableType.test( target.type ) && + target.click && nodeName( target, "input" ) && + dataPriv.get( target, "click" ) || + nodeName( target, "a" ); + } + }, + + beforeunload: { + postDispatch: function( event ) { + + // Support: Firefox 20+ + // Firefox doesn't alert if the returnValue field is not set. + if ( event.result !== undefined && event.originalEvent ) { + event.originalEvent.returnValue = event.result; + } + } + } + } +}; + +// Ensure the presence of an event listener that handles manually-triggered +// synthetic events by interrupting progress until reinvoked in response to +// *native* events that it fires directly, ensuring that state changes have +// already occurred before other listeners are invoked. +function leverageNative( el, type, expectSync ) { + + // Missing expectSync indicates a trigger call, which must force setup through jQuery.event.add + if ( !expectSync ) { + if ( dataPriv.get( el, type ) === undefined ) { + jQuery.event.add( el, type, returnTrue ); + } + return; + } + + // Register the controller as a special universal handler for all event namespaces + dataPriv.set( el, type, false ); + jQuery.event.add( el, type, { + namespace: false, + handler: function( event ) { + var notAsync, result, + saved = dataPriv.get( this, type ); + + if ( ( event.isTrigger & 1 ) && this[ type ] ) { + + // Interrupt processing of the outer synthetic .trigger()ed event + // Saved data should be false in such cases, but might be a leftover capture object + // from an async native handler (gh-4350) + if ( !saved.length ) { + + // Store arguments for use when handling the inner native event + // There will always be at least one argument (an event object), so this array + // will not be confused with a leftover capture object. + saved = slice.call( arguments ); + dataPriv.set( this, type, saved ); + + // Trigger the native event and capture its result + // Support: IE <=9 - 11+ + // focus() and blur() are asynchronous + notAsync = expectSync( this, type ); + this[ type ](); + result = dataPriv.get( this, type ); + if ( saved !== result || notAsync ) { + dataPriv.set( this, type, false ); + } else { + result = {}; + } + if ( saved !== result ) { + + // Cancel the outer synthetic event + event.stopImmediatePropagation(); + event.preventDefault(); + + // Support: Chrome 86+ + // In Chrome, if an element having a focusout handler is blurred by + // clicking outside of it, it invokes the handler synchronously. If + // that handler calls `.remove()` on the element, the data is cleared, + // leaving `result` undefined. We need to guard against this. + return result && result.value; + } + + // If this is an inner synthetic event for an event with a bubbling surrogate + // (focus or blur), assume that the surrogate already propagated from triggering the + // native event and prevent that from happening again here. + // This technically gets the ordering wrong w.r.t. to `.trigger()` (in which the + // bubbling surrogate propagates *after* the non-bubbling base), but that seems + // less bad than duplication. + } else if ( ( jQuery.event.special[ type ] || {} ).delegateType ) { + event.stopPropagation(); + } + + // If this is a native event triggered above, everything is now in order + // Fire an inner synthetic event with the original arguments + } else if ( saved.length ) { + + // ...and capture the result + dataPriv.set( this, type, { + value: jQuery.event.trigger( + + // Support: IE <=9 - 11+ + // Extend with the prototype to reset the above stopImmediatePropagation() + jQuery.extend( saved[ 0 ], jQuery.Event.prototype ), + saved.slice( 1 ), + this + ) + } ); + + // Abort handling of the native event + event.stopImmediatePropagation(); + } + } + } ); +} + +jQuery.removeEvent = function( elem, type, handle ) { + + // This "if" is needed for plain objects + if ( elem.removeEventListener ) { + elem.removeEventListener( type, handle ); + } +}; + +jQuery.Event = function( src, props ) { + + // Allow instantiation without the 'new' keyword + if ( !( this instanceof jQuery.Event ) ) { + return new jQuery.Event( src, props ); + } + + // Event object + if ( src && src.type ) { + this.originalEvent = src; + this.type = src.type; + + // Events bubbling up the document may have been marked as prevented + // by a handler lower down the tree; reflect the correct value. + this.isDefaultPrevented = src.defaultPrevented || + src.defaultPrevented === undefined && + + // Support: Android <=2.3 only + src.returnValue === false ? + returnTrue : + returnFalse; + + // Create target properties + // Support: Safari <=6 - 7 only + // Target should not be a text node (#504, #13143) + this.target = ( src.target && src.target.nodeType === 3 ) ? + src.target.parentNode : + src.target; + + this.currentTarget = src.currentTarget; + this.relatedTarget = src.relatedTarget; + + // Event type + } else { + this.type = src; + } + + // Put explicitly provided properties onto the event object + if ( props ) { + jQuery.extend( this, props ); + } + + // Create a timestamp if incoming event doesn't have one + this.timeStamp = src && src.timeStamp || Date.now(); + + // Mark it as fixed + this[ jQuery.expando ] = true; +}; + +// jQuery.Event is based on DOM3 Events as specified by the ECMAScript Language Binding +// https://www.w3.org/TR/2003/WD-DOM-Level-3-Events-20030331/ecma-script-binding.html +jQuery.Event.prototype = { + constructor: jQuery.Event, + isDefaultPrevented: returnFalse, + isPropagationStopped: returnFalse, + isImmediatePropagationStopped: returnFalse, + isSimulated: false, + + preventDefault: function() { + var e = this.originalEvent; + + this.isDefaultPrevented = returnTrue; + + if ( e && !this.isSimulated ) { + e.preventDefault(); + } + }, + stopPropagation: function() { + var e = this.originalEvent; + + this.isPropagationStopped = returnTrue; + + if ( e && !this.isSimulated ) { + e.stopPropagation(); + } + }, + stopImmediatePropagation: function() { + var e = this.originalEvent; + + this.isImmediatePropagationStopped = returnTrue; + + if ( e && !this.isSimulated ) { + e.stopImmediatePropagation(); + } + + this.stopPropagation(); + } +}; + +// Includes all common event props including KeyEvent and MouseEvent specific props +jQuery.each( { + altKey: true, + bubbles: true, + cancelable: true, + changedTouches: true, + ctrlKey: true, + detail: true, + eventPhase: true, + metaKey: true, + pageX: true, + pageY: true, + shiftKey: true, + view: true, + "char": true, + code: true, + charCode: true, + key: true, + keyCode: true, + button: true, + buttons: true, + clientX: true, + clientY: true, + offsetX: true, + offsetY: true, + pointerId: true, + pointerType: true, + screenX: true, + screenY: true, + targetTouches: true, + toElement: true, + touches: true, + which: true +}, jQuery.event.addProp ); + +jQuery.each( { focus: "focusin", blur: "focusout" }, function( type, delegateType ) { + jQuery.event.special[ type ] = { + + // Utilize native event if possible so blur/focus sequence is correct + setup: function() { + + // Claim the first handler + // dataPriv.set( this, "focus", ... ) + // dataPriv.set( this, "blur", ... ) + leverageNative( this, type, expectSync ); + + // Return false to allow normal processing in the caller + return false; + }, + trigger: function() { + + // Force setup before trigger + leverageNative( this, type ); + + // Return non-false to allow normal event-path propagation + return true; + }, + + // Suppress native focus or blur as it's already being fired + // in leverageNative. + _default: function() { + return true; + }, + + delegateType: delegateType + }; +} ); + +// Create mouseenter/leave events using mouseover/out and event-time checks +// so that event delegation works in jQuery. +// Do the same for pointerenter/pointerleave and pointerover/pointerout +// +// Support: Safari 7 only +// Safari sends mouseenter too often; see: +// https://bugs.chromium.org/p/chromium/issues/detail?id=470258 +// for the description of the bug (it existed in older Chrome versions as well). +jQuery.each( { + mouseenter: "mouseover", + mouseleave: "mouseout", + pointerenter: "pointerover", + pointerleave: "pointerout" +}, function( orig, fix ) { + jQuery.event.special[ orig ] = { + delegateType: fix, + bindType: fix, + + handle: function( event ) { + var ret, + target = this, + related = event.relatedTarget, + handleObj = event.handleObj; + + // For mouseenter/leave call the handler if related is outside the target. + // NB: No relatedTarget if the mouse left/entered the browser window + if ( !related || ( related !== target && !jQuery.contains( target, related ) ) ) { + event.type = handleObj.origType; + ret = handleObj.handler.apply( this, arguments ); + event.type = fix; + } + return ret; + } + }; +} ); + +jQuery.fn.extend( { + + on: function( types, selector, data, fn ) { + return on( this, types, selector, data, fn ); + }, + one: function( types, selector, data, fn ) { + return on( this, types, selector, data, fn, 1 ); + }, + off: function( types, selector, fn ) { + var handleObj, type; + if ( types && types.preventDefault && types.handleObj ) { + + // ( event ) dispatched jQuery.Event + handleObj = types.handleObj; + jQuery( types.delegateTarget ).off( + handleObj.namespace ? + handleObj.origType + "." + handleObj.namespace : + handleObj.origType, + handleObj.selector, + handleObj.handler + ); + return this; + } + if ( typeof types === "object" ) { + + // ( types-object [, selector] ) + for ( type in types ) { + this.off( type, selector, types[ type ] ); + } + return this; + } + if ( selector === false || typeof selector === "function" ) { + + // ( types [, fn] ) + fn = selector; + selector = undefined; + } + if ( fn === false ) { + fn = returnFalse; + } + return this.each( function() { + jQuery.event.remove( this, types, fn, selector ); + } ); + } +} ); + + +var + + // Support: IE <=10 - 11, Edge 12 - 13 only + // In IE/Edge using regex groups here causes severe slowdowns. + // See https://connect.microsoft.com/IE/feedback/details/1736512/ + rnoInnerhtml = /\s*$/g; + +// Prefer a tbody over its parent table for containing new rows +function manipulationTarget( elem, content ) { + if ( nodeName( elem, "table" ) && + nodeName( content.nodeType !== 11 ? content : content.firstChild, "tr" ) ) { + + return jQuery( elem ).children( "tbody" )[ 0 ] || elem; + } + + return elem; +} + +// Replace/restore the type attribute of script elements for safe DOM manipulation +function disableScript( elem ) { + elem.type = ( elem.getAttribute( "type" ) !== null ) + "/" + elem.type; + return elem; +} +function restoreScript( elem ) { + if ( ( elem.type || "" ).slice( 0, 5 ) === "true/" ) { + elem.type = elem.type.slice( 5 ); + } else { + elem.removeAttribute( "type" ); + } + + return elem; +} + +function cloneCopyEvent( src, dest ) { + var i, l, type, pdataOld, udataOld, udataCur, events; + + if ( dest.nodeType !== 1 ) { + return; + } + + // 1. Copy private data: events, handlers, etc. + if ( dataPriv.hasData( src ) ) { + pdataOld = dataPriv.get( src ); + events = pdataOld.events; + + if ( events ) { + dataPriv.remove( dest, "handle events" ); + + for ( type in events ) { + for ( i = 0, l = events[ type ].length; i < l; i++ ) { + jQuery.event.add( dest, type, events[ type ][ i ] ); + } + } + } + } + + // 2. Copy user data + if ( dataUser.hasData( src ) ) { + udataOld = dataUser.access( src ); + udataCur = jQuery.extend( {}, udataOld ); + + dataUser.set( dest, udataCur ); + } +} + +// Fix IE bugs, see support tests +function fixInput( src, dest ) { + var nodeName = dest.nodeName.toLowerCase(); + + // Fails to persist the checked state of a cloned checkbox or radio button. + if ( nodeName === "input" && rcheckableType.test( src.type ) ) { + dest.checked = src.checked; + + // Fails to return the selected option to the default selected state when cloning options + } else if ( nodeName === "input" || nodeName === "textarea" ) { + dest.defaultValue = src.defaultValue; + } +} + +function domManip( collection, args, callback, ignored ) { + + // Flatten any nested arrays + args = flat( args ); + + var fragment, first, scripts, hasScripts, node, doc, + i = 0, + l = collection.length, + iNoClone = l - 1, + value = args[ 0 ], + valueIsFunction = isFunction( value ); + + // We can't cloneNode fragments that contain checked, in WebKit + if ( valueIsFunction || + ( l > 1 && typeof value === "string" && + !support.checkClone && rchecked.test( value ) ) ) { + return collection.each( function( index ) { + var self = collection.eq( index ); + if ( valueIsFunction ) { + args[ 0 ] = value.call( this, index, self.html() ); + } + domManip( self, args, callback, ignored ); + } ); + } + + if ( l ) { + fragment = buildFragment( args, collection[ 0 ].ownerDocument, false, collection, ignored ); + first = fragment.firstChild; + + if ( fragment.childNodes.length === 1 ) { + fragment = first; + } + + // Require either new content or an interest in ignored elements to invoke the callback + if ( first || ignored ) { + scripts = jQuery.map( getAll( fragment, "script" ), disableScript ); + hasScripts = scripts.length; + + // Use the original fragment for the last item + // instead of the first because it can end up + // being emptied incorrectly in certain situations (#8070). + for ( ; i < l; i++ ) { + node = fragment; + + if ( i !== iNoClone ) { + node = jQuery.clone( node, true, true ); + + // Keep references to cloned scripts for later restoration + if ( hasScripts ) { + + // Support: Android <=4.0 only, PhantomJS 1 only + // push.apply(_, arraylike) throws on ancient WebKit + jQuery.merge( scripts, getAll( node, "script" ) ); + } + } + + callback.call( collection[ i ], node, i ); + } + + if ( hasScripts ) { + doc = scripts[ scripts.length - 1 ].ownerDocument; + + // Reenable scripts + jQuery.map( scripts, restoreScript ); + + // Evaluate executable scripts on first document insertion + for ( i = 0; i < hasScripts; i++ ) { + node = scripts[ i ]; + if ( rscriptType.test( node.type || "" ) && + !dataPriv.access( node, "globalEval" ) && + jQuery.contains( doc, node ) ) { + + if ( node.src && ( node.type || "" ).toLowerCase() !== "module" ) { + + // Optional AJAX dependency, but won't run scripts if not present + if ( jQuery._evalUrl && !node.noModule ) { + jQuery._evalUrl( node.src, { + nonce: node.nonce || node.getAttribute( "nonce" ) + }, doc ); + } + } else { + DOMEval( node.textContent.replace( rcleanScript, "" ), node, doc ); + } + } + } + } + } + } + + return collection; +} + +function remove( elem, selector, keepData ) { + var node, + nodes = selector ? jQuery.filter( selector, elem ) : elem, + i = 0; + + for ( ; ( node = nodes[ i ] ) != null; i++ ) { + if ( !keepData && node.nodeType === 1 ) { + jQuery.cleanData( getAll( node ) ); + } + + if ( node.parentNode ) { + if ( keepData && isAttached( node ) ) { + setGlobalEval( getAll( node, "script" ) ); + } + node.parentNode.removeChild( node ); + } + } + + return elem; +} + +jQuery.extend( { + htmlPrefilter: function( html ) { + return html; + }, + + clone: function( elem, dataAndEvents, deepDataAndEvents ) { + var i, l, srcElements, destElements, + clone = elem.cloneNode( true ), + inPage = isAttached( elem ); + + // Fix IE cloning issues + if ( !support.noCloneChecked && ( elem.nodeType === 1 || elem.nodeType === 11 ) && + !jQuery.isXMLDoc( elem ) ) { + + // We eschew Sizzle here for performance reasons: https://jsperf.com/getall-vs-sizzle/2 + destElements = getAll( clone ); + srcElements = getAll( elem ); + + for ( i = 0, l = srcElements.length; i < l; i++ ) { + fixInput( srcElements[ i ], destElements[ i ] ); + } + } + + // Copy the events from the original to the clone + if ( dataAndEvents ) { + if ( deepDataAndEvents ) { + srcElements = srcElements || getAll( elem ); + destElements = destElements || getAll( clone ); + + for ( i = 0, l = srcElements.length; i < l; i++ ) { + cloneCopyEvent( srcElements[ i ], destElements[ i ] ); + } + } else { + cloneCopyEvent( elem, clone ); + } + } + + // Preserve script evaluation history + destElements = getAll( clone, "script" ); + if ( destElements.length > 0 ) { + setGlobalEval( destElements, !inPage && getAll( elem, "script" ) ); + } + + // Return the cloned set + return clone; + }, + + cleanData: function( elems ) { + var data, elem, type, + special = jQuery.event.special, + i = 0; + + for ( ; ( elem = elems[ i ] ) !== undefined; i++ ) { + if ( acceptData( elem ) ) { + if ( ( data = elem[ dataPriv.expando ] ) ) { + if ( data.events ) { + for ( type in data.events ) { + if ( special[ type ] ) { + jQuery.event.remove( elem, type ); + + // This is a shortcut to avoid jQuery.event.remove's overhead + } else { + jQuery.removeEvent( elem, type, data.handle ); + } + } + } + + // Support: Chrome <=35 - 45+ + // Assign undefined instead of using delete, see Data#remove + elem[ dataPriv.expando ] = undefined; + } + if ( elem[ dataUser.expando ] ) { + + // Support: Chrome <=35 - 45+ + // Assign undefined instead of using delete, see Data#remove + elem[ dataUser.expando ] = undefined; + } + } + } + } +} ); + +jQuery.fn.extend( { + detach: function( selector ) { + return remove( this, selector, true ); + }, + + remove: function( selector ) { + return remove( this, selector ); + }, + + text: function( value ) { + return access( this, function( value ) { + return value === undefined ? + jQuery.text( this ) : + this.empty().each( function() { + if ( this.nodeType === 1 || this.nodeType === 11 || this.nodeType === 9 ) { + this.textContent = value; + } + } ); + }, null, value, arguments.length ); + }, + + append: function() { + return domManip( this, arguments, function( elem ) { + if ( this.nodeType === 1 || this.nodeType === 11 || this.nodeType === 9 ) { + var target = manipulationTarget( this, elem ); + target.appendChild( elem ); + } + } ); + }, + + prepend: function() { + return domManip( this, arguments, function( elem ) { + if ( this.nodeType === 1 || this.nodeType === 11 || this.nodeType === 9 ) { + var target = manipulationTarget( this, elem ); + target.insertBefore( elem, target.firstChild ); + } + } ); + }, + + before: function() { + return domManip( this, arguments, function( elem ) { + if ( this.parentNode ) { + this.parentNode.insertBefore( elem, this ); + } + } ); + }, + + after: function() { + return domManip( this, arguments, function( elem ) { + if ( this.parentNode ) { + this.parentNode.insertBefore( elem, this.nextSibling ); + } + } ); + }, + + empty: function() { + var elem, + i = 0; + + for ( ; ( elem = this[ i ] ) != null; i++ ) { + if ( elem.nodeType === 1 ) { + + // Prevent memory leaks + jQuery.cleanData( getAll( elem, false ) ); + + // Remove any remaining nodes + elem.textContent = ""; + } + } + + return this; + }, + + clone: function( dataAndEvents, deepDataAndEvents ) { + dataAndEvents = dataAndEvents == null ? false : dataAndEvents; + deepDataAndEvents = deepDataAndEvents == null ? dataAndEvents : deepDataAndEvents; + + return this.map( function() { + return jQuery.clone( this, dataAndEvents, deepDataAndEvents ); + } ); + }, + + html: function( value ) { + return access( this, function( value ) { + var elem = this[ 0 ] || {}, + i = 0, + l = this.length; + + if ( value === undefined && elem.nodeType === 1 ) { + return elem.innerHTML; + } + + // See if we can take a shortcut and just use innerHTML + if ( typeof value === "string" && !rnoInnerhtml.test( value ) && + !wrapMap[ ( rtagName.exec( value ) || [ "", "" ] )[ 1 ].toLowerCase() ] ) { + + value = jQuery.htmlPrefilter( value ); + + try { + for ( ; i < l; i++ ) { + elem = this[ i ] || {}; + + // Remove element nodes and prevent memory leaks + if ( elem.nodeType === 1 ) { + jQuery.cleanData( getAll( elem, false ) ); + elem.innerHTML = value; + } + } + + elem = 0; + + // If using innerHTML throws an exception, use the fallback method + } catch ( e ) {} + } + + if ( elem ) { + this.empty().append( value ); + } + }, null, value, arguments.length ); + }, + + replaceWith: function() { + var ignored = []; + + // Make the changes, replacing each non-ignored context element with the new content + return domManip( this, arguments, function( elem ) { + var parent = this.parentNode; + + if ( jQuery.inArray( this, ignored ) < 0 ) { + jQuery.cleanData( getAll( this ) ); + if ( parent ) { + parent.replaceChild( elem, this ); + } + } + + // Force callback invocation + }, ignored ); + } +} ); + +jQuery.each( { + appendTo: "append", + prependTo: "prepend", + insertBefore: "before", + insertAfter: "after", + replaceAll: "replaceWith" +}, function( name, original ) { + jQuery.fn[ name ] = function( selector ) { + var elems, + ret = [], + insert = jQuery( selector ), + last = insert.length - 1, + i = 0; + + for ( ; i <= last; i++ ) { + elems = i === last ? this : this.clone( true ); + jQuery( insert[ i ] )[ original ]( elems ); + + // Support: Android <=4.0 only, PhantomJS 1 only + // .get() because push.apply(_, arraylike) throws on ancient WebKit + push.apply( ret, elems.get() ); + } + + return this.pushStack( ret ); + }; +} ); +var rnumnonpx = new RegExp( "^(" + pnum + ")(?!px)[a-z%]+$", "i" ); + +var getStyles = function( elem ) { + + // Support: IE <=11 only, Firefox <=30 (#15098, #14150) + // IE throws on elements created in popups + // FF meanwhile throws on frame elements through "defaultView.getComputedStyle" + var view = elem.ownerDocument.defaultView; + + if ( !view || !view.opener ) { + view = window; + } + + return view.getComputedStyle( elem ); + }; + +var swap = function( elem, options, callback ) { + var ret, name, + old = {}; + + // Remember the old values, and insert the new ones + for ( name in options ) { + old[ name ] = elem.style[ name ]; + elem.style[ name ] = options[ name ]; + } + + ret = callback.call( elem ); + + // Revert the old values + for ( name in options ) { + elem.style[ name ] = old[ name ]; + } + + return ret; +}; + + +var rboxStyle = new RegExp( cssExpand.join( "|" ), "i" ); + + + +( function() { + + // Executing both pixelPosition & boxSizingReliable tests require only one layout + // so they're executed at the same time to save the second computation. + function computeStyleTests() { + + // This is a singleton, we need to execute it only once + if ( !div ) { + return; + } + + container.style.cssText = "position:absolute;left:-11111px;width:60px;" + + "margin-top:1px;padding:0;border:0"; + div.style.cssText = + "position:relative;display:block;box-sizing:border-box;overflow:scroll;" + + "margin:auto;border:1px;padding:1px;" + + "width:60%;top:1%"; + documentElement.appendChild( container ).appendChild( div ); + + var divStyle = window.getComputedStyle( div ); + pixelPositionVal = divStyle.top !== "1%"; + + // Support: Android 4.0 - 4.3 only, Firefox <=3 - 44 + reliableMarginLeftVal = roundPixelMeasures( divStyle.marginLeft ) === 12; + + // Support: Android 4.0 - 4.3 only, Safari <=9.1 - 10.1, iOS <=7.0 - 9.3 + // Some styles come back with percentage values, even though they shouldn't + div.style.right = "60%"; + pixelBoxStylesVal = roundPixelMeasures( divStyle.right ) === 36; + + // Support: IE 9 - 11 only + // Detect misreporting of content dimensions for box-sizing:border-box elements + boxSizingReliableVal = roundPixelMeasures( divStyle.width ) === 36; + + // Support: IE 9 only + // Detect overflow:scroll screwiness (gh-3699) + // Support: Chrome <=64 + // Don't get tricked when zoom affects offsetWidth (gh-4029) + div.style.position = "absolute"; + scrollboxSizeVal = roundPixelMeasures( div.offsetWidth / 3 ) === 12; + + documentElement.removeChild( container ); + + // Nullify the div so it wouldn't be stored in the memory and + // it will also be a sign that checks already performed + div = null; + } + + function roundPixelMeasures( measure ) { + return Math.round( parseFloat( measure ) ); + } + + var pixelPositionVal, boxSizingReliableVal, scrollboxSizeVal, pixelBoxStylesVal, + reliableTrDimensionsVal, reliableMarginLeftVal, + container = document.createElement( "div" ), + div = document.createElement( "div" ); + + // Finish early in limited (non-browser) environments + if ( !div.style ) { + return; + } + + // Support: IE <=9 - 11 only + // Style of cloned element affects source element cloned (#8908) + div.style.backgroundClip = "content-box"; + div.cloneNode( true ).style.backgroundClip = ""; + support.clearCloneStyle = div.style.backgroundClip === "content-box"; + + jQuery.extend( support, { + boxSizingReliable: function() { + computeStyleTests(); + return boxSizingReliableVal; + }, + pixelBoxStyles: function() { + computeStyleTests(); + return pixelBoxStylesVal; + }, + pixelPosition: function() { + computeStyleTests(); + return pixelPositionVal; + }, + reliableMarginLeft: function() { + computeStyleTests(); + return reliableMarginLeftVal; + }, + scrollboxSize: function() { + computeStyleTests(); + return scrollboxSizeVal; + }, + + // Support: IE 9 - 11+, Edge 15 - 18+ + // IE/Edge misreport `getComputedStyle` of table rows with width/height + // set in CSS while `offset*` properties report correct values. + // Behavior in IE 9 is more subtle than in newer versions & it passes + // some versions of this test; make sure not to make it pass there! + // + // Support: Firefox 70+ + // Only Firefox includes border widths + // in computed dimensions. (gh-4529) + reliableTrDimensions: function() { + var table, tr, trChild, trStyle; + if ( reliableTrDimensionsVal == null ) { + table = document.createElement( "table" ); + tr = document.createElement( "tr" ); + trChild = document.createElement( "div" ); + + table.style.cssText = "position:absolute;left:-11111px;border-collapse:separate"; + tr.style.cssText = "border:1px solid"; + + // Support: Chrome 86+ + // Height set through cssText does not get applied. + // Computed height then comes back as 0. + tr.style.height = "1px"; + trChild.style.height = "9px"; + + // Support: Android 8 Chrome 86+ + // In our bodyBackground.html iframe, + // display for all div elements is set to "inline", + // which causes a problem only in Android 8 Chrome 86. + // Ensuring the div is display: block + // gets around this issue. + trChild.style.display = "block"; + + documentElement + .appendChild( table ) + .appendChild( tr ) + .appendChild( trChild ); + + trStyle = window.getComputedStyle( tr ); + reliableTrDimensionsVal = ( parseInt( trStyle.height, 10 ) + + parseInt( trStyle.borderTopWidth, 10 ) + + parseInt( trStyle.borderBottomWidth, 10 ) ) === tr.offsetHeight; + + documentElement.removeChild( table ); + } + return reliableTrDimensionsVal; + } + } ); +} )(); + + +function curCSS( elem, name, computed ) { + var width, minWidth, maxWidth, ret, + + // Support: Firefox 51+ + // Retrieving style before computed somehow + // fixes an issue with getting wrong values + // on detached elements + style = elem.style; + + computed = computed || getStyles( elem ); + + // getPropertyValue is needed for: + // .css('filter') (IE 9 only, #12537) + // .css('--customProperty) (#3144) + if ( computed ) { + ret = computed.getPropertyValue( name ) || computed[ name ]; + + if ( ret === "" && !isAttached( elem ) ) { + ret = jQuery.style( elem, name ); + } + + // A tribute to the "awesome hack by Dean Edwards" + // Android Browser returns percentage for some values, + // but width seems to be reliably pixels. + // This is against the CSSOM draft spec: + // https://drafts.csswg.org/cssom/#resolved-values + if ( !support.pixelBoxStyles() && rnumnonpx.test( ret ) && rboxStyle.test( name ) ) { + + // Remember the original values + width = style.width; + minWidth = style.minWidth; + maxWidth = style.maxWidth; + + // Put in the new values to get a computed value out + style.minWidth = style.maxWidth = style.width = ret; + ret = computed.width; + + // Revert the changed values + style.width = width; + style.minWidth = minWidth; + style.maxWidth = maxWidth; + } + } + + return ret !== undefined ? + + // Support: IE <=9 - 11 only + // IE returns zIndex value as an integer. + ret + "" : + ret; +} + + +function addGetHookIf( conditionFn, hookFn ) { + + // Define the hook, we'll check on the first run if it's really needed. + return { + get: function() { + if ( conditionFn() ) { + + // Hook not needed (or it's not possible to use it due + // to missing dependency), remove it. + delete this.get; + return; + } + + // Hook needed; redefine it so that the support test is not executed again. + return ( this.get = hookFn ).apply( this, arguments ); + } + }; +} + + +var cssPrefixes = [ "Webkit", "Moz", "ms" ], + emptyStyle = document.createElement( "div" ).style, + vendorProps = {}; + +// Return a vendor-prefixed property or undefined +function vendorPropName( name ) { + + // Check for vendor prefixed names + var capName = name[ 0 ].toUpperCase() + name.slice( 1 ), + i = cssPrefixes.length; + + while ( i-- ) { + name = cssPrefixes[ i ] + capName; + if ( name in emptyStyle ) { + return name; + } + } +} + +// Return a potentially-mapped jQuery.cssProps or vendor prefixed property +function finalPropName( name ) { + var final = jQuery.cssProps[ name ] || vendorProps[ name ]; + + if ( final ) { + return final; + } + if ( name in emptyStyle ) { + return name; + } + return vendorProps[ name ] = vendorPropName( name ) || name; +} + + +var + + // Swappable if display is none or starts with table + // except "table", "table-cell", or "table-caption" + // See here for display values: https://developer.mozilla.org/en-US/docs/CSS/display + rdisplayswap = /^(none|table(?!-c[ea]).+)/, + rcustomProp = /^--/, + cssShow = { position: "absolute", visibility: "hidden", display: "block" }, + cssNormalTransform = { + letterSpacing: "0", + fontWeight: "400" + }; + +function setPositiveNumber( _elem, value, subtract ) { + + // Any relative (+/-) values have already been + // normalized at this point + var matches = rcssNum.exec( value ); + return matches ? + + // Guard against undefined "subtract", e.g., when used as in cssHooks + Math.max( 0, matches[ 2 ] - ( subtract || 0 ) ) + ( matches[ 3 ] || "px" ) : + value; +} + +function boxModelAdjustment( elem, dimension, box, isBorderBox, styles, computedVal ) { + var i = dimension === "width" ? 1 : 0, + extra = 0, + delta = 0; + + // Adjustment may not be necessary + if ( box === ( isBorderBox ? "border" : "content" ) ) { + return 0; + } + + for ( ; i < 4; i += 2 ) { + + // Both box models exclude margin + if ( box === "margin" ) { + delta += jQuery.css( elem, box + cssExpand[ i ], true, styles ); + } + + // If we get here with a content-box, we're seeking "padding" or "border" or "margin" + if ( !isBorderBox ) { + + // Add padding + delta += jQuery.css( elem, "padding" + cssExpand[ i ], true, styles ); + + // For "border" or "margin", add border + if ( box !== "padding" ) { + delta += jQuery.css( elem, "border" + cssExpand[ i ] + "Width", true, styles ); + + // But still keep track of it otherwise + } else { + extra += jQuery.css( elem, "border" + cssExpand[ i ] + "Width", true, styles ); + } + + // If we get here with a border-box (content + padding + border), we're seeking "content" or + // "padding" or "margin" + } else { + + // For "content", subtract padding + if ( box === "content" ) { + delta -= jQuery.css( elem, "padding" + cssExpand[ i ], true, styles ); + } + + // For "content" or "padding", subtract border + if ( box !== "margin" ) { + delta -= jQuery.css( elem, "border" + cssExpand[ i ] + "Width", true, styles ); + } + } + } + + // Account for positive content-box scroll gutter when requested by providing computedVal + if ( !isBorderBox && computedVal >= 0 ) { + + // offsetWidth/offsetHeight is a rounded sum of content, padding, scroll gutter, and border + // Assuming integer scroll gutter, subtract the rest and round down + delta += Math.max( 0, Math.ceil( + elem[ "offset" + dimension[ 0 ].toUpperCase() + dimension.slice( 1 ) ] - + computedVal - + delta - + extra - + 0.5 + + // If offsetWidth/offsetHeight is unknown, then we can't determine content-box scroll gutter + // Use an explicit zero to avoid NaN (gh-3964) + ) ) || 0; + } + + return delta; +} + +function getWidthOrHeight( elem, dimension, extra ) { + + // Start with computed style + var styles = getStyles( elem ), + + // To avoid forcing a reflow, only fetch boxSizing if we need it (gh-4322). + // Fake content-box until we know it's needed to know the true value. + boxSizingNeeded = !support.boxSizingReliable() || extra, + isBorderBox = boxSizingNeeded && + jQuery.css( elem, "boxSizing", false, styles ) === "border-box", + valueIsBorderBox = isBorderBox, + + val = curCSS( elem, dimension, styles ), + offsetProp = "offset" + dimension[ 0 ].toUpperCase() + dimension.slice( 1 ); + + // Support: Firefox <=54 + // Return a confounding non-pixel value or feign ignorance, as appropriate. + if ( rnumnonpx.test( val ) ) { + if ( !extra ) { + return val; + } + val = "auto"; + } + + + // Support: IE 9 - 11 only + // Use offsetWidth/offsetHeight for when box sizing is unreliable. + // In those cases, the computed value can be trusted to be border-box. + if ( ( !support.boxSizingReliable() && isBorderBox || + + // Support: IE 10 - 11+, Edge 15 - 18+ + // IE/Edge misreport `getComputedStyle` of table rows with width/height + // set in CSS while `offset*` properties report correct values. + // Interestingly, in some cases IE 9 doesn't suffer from this issue. + !support.reliableTrDimensions() && nodeName( elem, "tr" ) || + + // Fall back to offsetWidth/offsetHeight when value is "auto" + // This happens for inline elements with no explicit setting (gh-3571) + val === "auto" || + + // Support: Android <=4.1 - 4.3 only + // Also use offsetWidth/offsetHeight for misreported inline dimensions (gh-3602) + !parseFloat( val ) && jQuery.css( elem, "display", false, styles ) === "inline" ) && + + // Make sure the element is visible & connected + elem.getClientRects().length ) { + + isBorderBox = jQuery.css( elem, "boxSizing", false, styles ) === "border-box"; + + // Where available, offsetWidth/offsetHeight approximate border box dimensions. + // Where not available (e.g., SVG), assume unreliable box-sizing and interpret the + // retrieved value as a content box dimension. + valueIsBorderBox = offsetProp in elem; + if ( valueIsBorderBox ) { + val = elem[ offsetProp ]; + } + } + + // Normalize "" and auto + val = parseFloat( val ) || 0; + + // Adjust for the element's box model + return ( val + + boxModelAdjustment( + elem, + dimension, + extra || ( isBorderBox ? "border" : "content" ), + valueIsBorderBox, + styles, + + // Provide the current computed size to request scroll gutter calculation (gh-3589) + val + ) + ) + "px"; +} + +jQuery.extend( { + + // Add in style property hooks for overriding the default + // behavior of getting and setting a style property + cssHooks: { + opacity: { + get: function( elem, computed ) { + if ( computed ) { + + // We should always get a number back from opacity + var ret = curCSS( elem, "opacity" ); + return ret === "" ? "1" : ret; + } + } + } + }, + + // Don't automatically add "px" to these possibly-unitless properties + cssNumber: { + "animationIterationCount": true, + "columnCount": true, + "fillOpacity": true, + "flexGrow": true, + "flexShrink": true, + "fontWeight": true, + "gridArea": true, + "gridColumn": true, + "gridColumnEnd": true, + "gridColumnStart": true, + "gridRow": true, + "gridRowEnd": true, + "gridRowStart": true, + "lineHeight": true, + "opacity": true, + "order": true, + "orphans": true, + "widows": true, + "zIndex": true, + "zoom": true + }, + + // Add in properties whose names you wish to fix before + // setting or getting the value + cssProps: {}, + + // Get and set the style property on a DOM Node + style: function( elem, name, value, extra ) { + + // Don't set styles on text and comment nodes + if ( !elem || elem.nodeType === 3 || elem.nodeType === 8 || !elem.style ) { + return; + } + + // Make sure that we're working with the right name + var ret, type, hooks, + origName = camelCase( name ), + isCustomProp = rcustomProp.test( name ), + style = elem.style; + + // Make sure that we're working with the right name. We don't + // want to query the value if it is a CSS custom property + // since they are user-defined. + if ( !isCustomProp ) { + name = finalPropName( origName ); + } + + // Gets hook for the prefixed version, then unprefixed version + hooks = jQuery.cssHooks[ name ] || jQuery.cssHooks[ origName ]; + + // Check if we're setting a value + if ( value !== undefined ) { + type = typeof value; + + // Convert "+=" or "-=" to relative numbers (#7345) + if ( type === "string" && ( ret = rcssNum.exec( value ) ) && ret[ 1 ] ) { + value = adjustCSS( elem, name, ret ); + + // Fixes bug #9237 + type = "number"; + } + + // Make sure that null and NaN values aren't set (#7116) + if ( value == null || value !== value ) { + return; + } + + // If a number was passed in, add the unit (except for certain CSS properties) + // The isCustomProp check can be removed in jQuery 4.0 when we only auto-append + // "px" to a few hardcoded values. + if ( type === "number" && !isCustomProp ) { + value += ret && ret[ 3 ] || ( jQuery.cssNumber[ origName ] ? "" : "px" ); + } + + // background-* props affect original clone's values + if ( !support.clearCloneStyle && value === "" && name.indexOf( "background" ) === 0 ) { + style[ name ] = "inherit"; + } + + // If a hook was provided, use that value, otherwise just set the specified value + if ( !hooks || !( "set" in hooks ) || + ( value = hooks.set( elem, value, extra ) ) !== undefined ) { + + if ( isCustomProp ) { + style.setProperty( name, value ); + } else { + style[ name ] = value; + } + } + + } else { + + // If a hook was provided get the non-computed value from there + if ( hooks && "get" in hooks && + ( ret = hooks.get( elem, false, extra ) ) !== undefined ) { + + return ret; + } + + // Otherwise just get the value from the style object + return style[ name ]; + } + }, + + css: function( elem, name, extra, styles ) { + var val, num, hooks, + origName = camelCase( name ), + isCustomProp = rcustomProp.test( name ); + + // Make sure that we're working with the right name. We don't + // want to modify the value if it is a CSS custom property + // since they are user-defined. + if ( !isCustomProp ) { + name = finalPropName( origName ); + } + + // Try prefixed name followed by the unprefixed name + hooks = jQuery.cssHooks[ name ] || jQuery.cssHooks[ origName ]; + + // If a hook was provided get the computed value from there + if ( hooks && "get" in hooks ) { + val = hooks.get( elem, true, extra ); + } + + // Otherwise, if a way to get the computed value exists, use that + if ( val === undefined ) { + val = curCSS( elem, name, styles ); + } + + // Convert "normal" to computed value + if ( val === "normal" && name in cssNormalTransform ) { + val = cssNormalTransform[ name ]; + } + + // Make numeric if forced or a qualifier was provided and val looks numeric + if ( extra === "" || extra ) { + num = parseFloat( val ); + return extra === true || isFinite( num ) ? num || 0 : val; + } + + return val; + } +} ); + +jQuery.each( [ "height", "width" ], function( _i, dimension ) { + jQuery.cssHooks[ dimension ] = { + get: function( elem, computed, extra ) { + if ( computed ) { + + // Certain elements can have dimension info if we invisibly show them + // but it must have a current display style that would benefit + return rdisplayswap.test( jQuery.css( elem, "display" ) ) && + + // Support: Safari 8+ + // Table columns in Safari have non-zero offsetWidth & zero + // getBoundingClientRect().width unless display is changed. + // Support: IE <=11 only + // Running getBoundingClientRect on a disconnected node + // in IE throws an error. + ( !elem.getClientRects().length || !elem.getBoundingClientRect().width ) ? + swap( elem, cssShow, function() { + return getWidthOrHeight( elem, dimension, extra ); + } ) : + getWidthOrHeight( elem, dimension, extra ); + } + }, + + set: function( elem, value, extra ) { + var matches, + styles = getStyles( elem ), + + // Only read styles.position if the test has a chance to fail + // to avoid forcing a reflow. + scrollboxSizeBuggy = !support.scrollboxSize() && + styles.position === "absolute", + + // To avoid forcing a reflow, only fetch boxSizing if we need it (gh-3991) + boxSizingNeeded = scrollboxSizeBuggy || extra, + isBorderBox = boxSizingNeeded && + jQuery.css( elem, "boxSizing", false, styles ) === "border-box", + subtract = extra ? + boxModelAdjustment( + elem, + dimension, + extra, + isBorderBox, + styles + ) : + 0; + + // Account for unreliable border-box dimensions by comparing offset* to computed and + // faking a content-box to get border and padding (gh-3699) + if ( isBorderBox && scrollboxSizeBuggy ) { + subtract -= Math.ceil( + elem[ "offset" + dimension[ 0 ].toUpperCase() + dimension.slice( 1 ) ] - + parseFloat( styles[ dimension ] ) - + boxModelAdjustment( elem, dimension, "border", false, styles ) - + 0.5 + ); + } + + // Convert to pixels if value adjustment is needed + if ( subtract && ( matches = rcssNum.exec( value ) ) && + ( matches[ 3 ] || "px" ) !== "px" ) { + + elem.style[ dimension ] = value; + value = jQuery.css( elem, dimension ); + } + + return setPositiveNumber( elem, value, subtract ); + } + }; +} ); + +jQuery.cssHooks.marginLeft = addGetHookIf( support.reliableMarginLeft, + function( elem, computed ) { + if ( computed ) { + return ( parseFloat( curCSS( elem, "marginLeft" ) ) || + elem.getBoundingClientRect().left - + swap( elem, { marginLeft: 0 }, function() { + return elem.getBoundingClientRect().left; + } ) + ) + "px"; + } + } +); + +// These hooks are used by animate to expand properties +jQuery.each( { + margin: "", + padding: "", + border: "Width" +}, function( prefix, suffix ) { + jQuery.cssHooks[ prefix + suffix ] = { + expand: function( value ) { + var i = 0, + expanded = {}, + + // Assumes a single number if not a string + parts = typeof value === "string" ? value.split( " " ) : [ value ]; + + for ( ; i < 4; i++ ) { + expanded[ prefix + cssExpand[ i ] + suffix ] = + parts[ i ] || parts[ i - 2 ] || parts[ 0 ]; + } + + return expanded; + } + }; + + if ( prefix !== "margin" ) { + jQuery.cssHooks[ prefix + suffix ].set = setPositiveNumber; + } +} ); + +jQuery.fn.extend( { + css: function( name, value ) { + return access( this, function( elem, name, value ) { + var styles, len, + map = {}, + i = 0; + + if ( Array.isArray( name ) ) { + styles = getStyles( elem ); + len = name.length; + + for ( ; i < len; i++ ) { + map[ name[ i ] ] = jQuery.css( elem, name[ i ], false, styles ); + } + + return map; + } + + return value !== undefined ? + jQuery.style( elem, name, value ) : + jQuery.css( elem, name ); + }, name, value, arguments.length > 1 ); + } +} ); + + +function Tween( elem, options, prop, end, easing ) { + return new Tween.prototype.init( elem, options, prop, end, easing ); +} +jQuery.Tween = Tween; + +Tween.prototype = { + constructor: Tween, + init: function( elem, options, prop, end, easing, unit ) { + this.elem = elem; + this.prop = prop; + this.easing = easing || jQuery.easing._default; + this.options = options; + this.start = this.now = this.cur(); + this.end = end; + this.unit = unit || ( jQuery.cssNumber[ prop ] ? "" : "px" ); + }, + cur: function() { + var hooks = Tween.propHooks[ this.prop ]; + + return hooks && hooks.get ? + hooks.get( this ) : + Tween.propHooks._default.get( this ); + }, + run: function( percent ) { + var eased, + hooks = Tween.propHooks[ this.prop ]; + + if ( this.options.duration ) { + this.pos = eased = jQuery.easing[ this.easing ]( + percent, this.options.duration * percent, 0, 1, this.options.duration + ); + } else { + this.pos = eased = percent; + } + this.now = ( this.end - this.start ) * eased + this.start; + + if ( this.options.step ) { + this.options.step.call( this.elem, this.now, this ); + } + + if ( hooks && hooks.set ) { + hooks.set( this ); + } else { + Tween.propHooks._default.set( this ); + } + return this; + } +}; + +Tween.prototype.init.prototype = Tween.prototype; + +Tween.propHooks = { + _default: { + get: function( tween ) { + var result; + + // Use a property on the element directly when it is not a DOM element, + // or when there is no matching style property that exists. + if ( tween.elem.nodeType !== 1 || + tween.elem[ tween.prop ] != null && tween.elem.style[ tween.prop ] == null ) { + return tween.elem[ tween.prop ]; + } + + // Passing an empty string as a 3rd parameter to .css will automatically + // attempt a parseFloat and fallback to a string if the parse fails. + // Simple values such as "10px" are parsed to Float; + // complex values such as "rotate(1rad)" are returned as-is. + result = jQuery.css( tween.elem, tween.prop, "" ); + + // Empty strings, null, undefined and "auto" are converted to 0. + return !result || result === "auto" ? 0 : result; + }, + set: function( tween ) { + + // Use step hook for back compat. + // Use cssHook if its there. + // Use .style if available and use plain properties where available. + if ( jQuery.fx.step[ tween.prop ] ) { + jQuery.fx.step[ tween.prop ]( tween ); + } else if ( tween.elem.nodeType === 1 && ( + jQuery.cssHooks[ tween.prop ] || + tween.elem.style[ finalPropName( tween.prop ) ] != null ) ) { + jQuery.style( tween.elem, tween.prop, tween.now + tween.unit ); + } else { + tween.elem[ tween.prop ] = tween.now; + } + } + } +}; + +// Support: IE <=9 only +// Panic based approach to setting things on disconnected nodes +Tween.propHooks.scrollTop = Tween.propHooks.scrollLeft = { + set: function( tween ) { + if ( tween.elem.nodeType && tween.elem.parentNode ) { + tween.elem[ tween.prop ] = tween.now; + } + } +}; + +jQuery.easing = { + linear: function( p ) { + return p; + }, + swing: function( p ) { + return 0.5 - Math.cos( p * Math.PI ) / 2; + }, + _default: "swing" +}; + +jQuery.fx = Tween.prototype.init; + +// Back compat <1.8 extension point +jQuery.fx.step = {}; + + + + +var + fxNow, inProgress, + rfxtypes = /^(?:toggle|show|hide)$/, + rrun = /queueHooks$/; + +function schedule() { + if ( inProgress ) { + if ( document.hidden === false && window.requestAnimationFrame ) { + window.requestAnimationFrame( schedule ); + } else { + window.setTimeout( schedule, jQuery.fx.interval ); + } + + jQuery.fx.tick(); + } +} + +// Animations created synchronously will run synchronously +function createFxNow() { + window.setTimeout( function() { + fxNow = undefined; + } ); + return ( fxNow = Date.now() ); +} + +// Generate parameters to create a standard animation +function genFx( type, includeWidth ) { + var which, + i = 0, + attrs = { height: type }; + + // If we include width, step value is 1 to do all cssExpand values, + // otherwise step value is 2 to skip over Left and Right + includeWidth = includeWidth ? 1 : 0; + for ( ; i < 4; i += 2 - includeWidth ) { + which = cssExpand[ i ]; + attrs[ "margin" + which ] = attrs[ "padding" + which ] = type; + } + + if ( includeWidth ) { + attrs.opacity = attrs.width = type; + } + + return attrs; +} + +function createTween( value, prop, animation ) { + var tween, + collection = ( Animation.tweeners[ prop ] || [] ).concat( Animation.tweeners[ "*" ] ), + index = 0, + length = collection.length; + for ( ; index < length; index++ ) { + if ( ( tween = collection[ index ].call( animation, prop, value ) ) ) { + + // We're done with this property + return tween; + } + } +} + +function defaultPrefilter( elem, props, opts ) { + var prop, value, toggle, hooks, oldfire, propTween, restoreDisplay, display, + isBox = "width" in props || "height" in props, + anim = this, + orig = {}, + style = elem.style, + hidden = elem.nodeType && isHiddenWithinTree( elem ), + dataShow = dataPriv.get( elem, "fxshow" ); + + // Queue-skipping animations hijack the fx hooks + if ( !opts.queue ) { + hooks = jQuery._queueHooks( elem, "fx" ); + if ( hooks.unqueued == null ) { + hooks.unqueued = 0; + oldfire = hooks.empty.fire; + hooks.empty.fire = function() { + if ( !hooks.unqueued ) { + oldfire(); + } + }; + } + hooks.unqueued++; + + anim.always( function() { + + // Ensure the complete handler is called before this completes + anim.always( function() { + hooks.unqueued--; + if ( !jQuery.queue( elem, "fx" ).length ) { + hooks.empty.fire(); + } + } ); + } ); + } + + // Detect show/hide animations + for ( prop in props ) { + value = props[ prop ]; + if ( rfxtypes.test( value ) ) { + delete props[ prop ]; + toggle = toggle || value === "toggle"; + if ( value === ( hidden ? "hide" : "show" ) ) { + + // Pretend to be hidden if this is a "show" and + // there is still data from a stopped show/hide + if ( value === "show" && dataShow && dataShow[ prop ] !== undefined ) { + hidden = true; + + // Ignore all other no-op show/hide data + } else { + continue; + } + } + orig[ prop ] = dataShow && dataShow[ prop ] || jQuery.style( elem, prop ); + } + } + + // Bail out if this is a no-op like .hide().hide() + propTween = !jQuery.isEmptyObject( props ); + if ( !propTween && jQuery.isEmptyObject( orig ) ) { + return; + } + + // Restrict "overflow" and "display" styles during box animations + if ( isBox && elem.nodeType === 1 ) { + + // Support: IE <=9 - 11, Edge 12 - 15 + // Record all 3 overflow attributes because IE does not infer the shorthand + // from identically-valued overflowX and overflowY and Edge just mirrors + // the overflowX value there. + opts.overflow = [ style.overflow, style.overflowX, style.overflowY ]; + + // Identify a display type, preferring old show/hide data over the CSS cascade + restoreDisplay = dataShow && dataShow.display; + if ( restoreDisplay == null ) { + restoreDisplay = dataPriv.get( elem, "display" ); + } + display = jQuery.css( elem, "display" ); + if ( display === "none" ) { + if ( restoreDisplay ) { + display = restoreDisplay; + } else { + + // Get nonempty value(s) by temporarily forcing visibility + showHide( [ elem ], true ); + restoreDisplay = elem.style.display || restoreDisplay; + display = jQuery.css( elem, "display" ); + showHide( [ elem ] ); + } + } + + // Animate inline elements as inline-block + if ( display === "inline" || display === "inline-block" && restoreDisplay != null ) { + if ( jQuery.css( elem, "float" ) === "none" ) { + + // Restore the original display value at the end of pure show/hide animations + if ( !propTween ) { + anim.done( function() { + style.display = restoreDisplay; + } ); + if ( restoreDisplay == null ) { + display = style.display; + restoreDisplay = display === "none" ? "" : display; + } + } + style.display = "inline-block"; + } + } + } + + if ( opts.overflow ) { + style.overflow = "hidden"; + anim.always( function() { + style.overflow = opts.overflow[ 0 ]; + style.overflowX = opts.overflow[ 1 ]; + style.overflowY = opts.overflow[ 2 ]; + } ); + } + + // Implement show/hide animations + propTween = false; + for ( prop in orig ) { + + // General show/hide setup for this element animation + if ( !propTween ) { + if ( dataShow ) { + if ( "hidden" in dataShow ) { + hidden = dataShow.hidden; + } + } else { + dataShow = dataPriv.access( elem, "fxshow", { display: restoreDisplay } ); + } + + // Store hidden/visible for toggle so `.stop().toggle()` "reverses" + if ( toggle ) { + dataShow.hidden = !hidden; + } + + // Show elements before animating them + if ( hidden ) { + showHide( [ elem ], true ); + } + + /* eslint-disable no-loop-func */ + + anim.done( function() { + + /* eslint-enable no-loop-func */ + + // The final step of a "hide" animation is actually hiding the element + if ( !hidden ) { + showHide( [ elem ] ); + } + dataPriv.remove( elem, "fxshow" ); + for ( prop in orig ) { + jQuery.style( elem, prop, orig[ prop ] ); + } + } ); + } + + // Per-property setup + propTween = createTween( hidden ? dataShow[ prop ] : 0, prop, anim ); + if ( !( prop in dataShow ) ) { + dataShow[ prop ] = propTween.start; + if ( hidden ) { + propTween.end = propTween.start; + propTween.start = 0; + } + } + } +} + +function propFilter( props, specialEasing ) { + var index, name, easing, value, hooks; + + // camelCase, specialEasing and expand cssHook pass + for ( index in props ) { + name = camelCase( index ); + easing = specialEasing[ name ]; + value = props[ index ]; + if ( Array.isArray( value ) ) { + easing = value[ 1 ]; + value = props[ index ] = value[ 0 ]; + } + + if ( index !== name ) { + props[ name ] = value; + delete props[ index ]; + } + + hooks = jQuery.cssHooks[ name ]; + if ( hooks && "expand" in hooks ) { + value = hooks.expand( value ); + delete props[ name ]; + + // Not quite $.extend, this won't overwrite existing keys. + // Reusing 'index' because we have the correct "name" + for ( index in value ) { + if ( !( index in props ) ) { + props[ index ] = value[ index ]; + specialEasing[ index ] = easing; + } + } + } else { + specialEasing[ name ] = easing; + } + } +} + +function Animation( elem, properties, options ) { + var result, + stopped, + index = 0, + length = Animation.prefilters.length, + deferred = jQuery.Deferred().always( function() { + + // Don't match elem in the :animated selector + delete tick.elem; + } ), + tick = function() { + if ( stopped ) { + return false; + } + var currentTime = fxNow || createFxNow(), + remaining = Math.max( 0, animation.startTime + animation.duration - currentTime ), + + // Support: Android 2.3 only + // Archaic crash bug won't allow us to use `1 - ( 0.5 || 0 )` (#12497) + temp = remaining / animation.duration || 0, + percent = 1 - temp, + index = 0, + length = animation.tweens.length; + + for ( ; index < length; index++ ) { + animation.tweens[ index ].run( percent ); + } + + deferred.notifyWith( elem, [ animation, percent, remaining ] ); + + // If there's more to do, yield + if ( percent < 1 && length ) { + return remaining; + } + + // If this was an empty animation, synthesize a final progress notification + if ( !length ) { + deferred.notifyWith( elem, [ animation, 1, 0 ] ); + } + + // Resolve the animation and report its conclusion + deferred.resolveWith( elem, [ animation ] ); + return false; + }, + animation = deferred.promise( { + elem: elem, + props: jQuery.extend( {}, properties ), + opts: jQuery.extend( true, { + specialEasing: {}, + easing: jQuery.easing._default + }, options ), + originalProperties: properties, + originalOptions: options, + startTime: fxNow || createFxNow(), + duration: options.duration, + tweens: [], + createTween: function( prop, end ) { + var tween = jQuery.Tween( elem, animation.opts, prop, end, + animation.opts.specialEasing[ prop ] || animation.opts.easing ); + animation.tweens.push( tween ); + return tween; + }, + stop: function( gotoEnd ) { + var index = 0, + + // If we are going to the end, we want to run all the tweens + // otherwise we skip this part + length = gotoEnd ? animation.tweens.length : 0; + if ( stopped ) { + return this; + } + stopped = true; + for ( ; index < length; index++ ) { + animation.tweens[ index ].run( 1 ); + } + + // Resolve when we played the last frame; otherwise, reject + if ( gotoEnd ) { + deferred.notifyWith( elem, [ animation, 1, 0 ] ); + deferred.resolveWith( elem, [ animation, gotoEnd ] ); + } else { + deferred.rejectWith( elem, [ animation, gotoEnd ] ); + } + return this; + } + } ), + props = animation.props; + + propFilter( props, animation.opts.specialEasing ); + + for ( ; index < length; index++ ) { + result = Animation.prefilters[ index ].call( animation, elem, props, animation.opts ); + if ( result ) { + if ( isFunction( result.stop ) ) { + jQuery._queueHooks( animation.elem, animation.opts.queue ).stop = + result.stop.bind( result ); + } + return result; + } + } + + jQuery.map( props, createTween, animation ); + + if ( isFunction( animation.opts.start ) ) { + animation.opts.start.call( elem, animation ); + } + + // Attach callbacks from options + animation + .progress( animation.opts.progress ) + .done( animation.opts.done, animation.opts.complete ) + .fail( animation.opts.fail ) + .always( animation.opts.always ); + + jQuery.fx.timer( + jQuery.extend( tick, { + elem: elem, + anim: animation, + queue: animation.opts.queue + } ) + ); + + return animation; +} + +jQuery.Animation = jQuery.extend( Animation, { + + tweeners: { + "*": [ function( prop, value ) { + var tween = this.createTween( prop, value ); + adjustCSS( tween.elem, prop, rcssNum.exec( value ), tween ); + return tween; + } ] + }, + + tweener: function( props, callback ) { + if ( isFunction( props ) ) { + callback = props; + props = [ "*" ]; + } else { + props = props.match( rnothtmlwhite ); + } + + var prop, + index = 0, + length = props.length; + + for ( ; index < length; index++ ) { + prop = props[ index ]; + Animation.tweeners[ prop ] = Animation.tweeners[ prop ] || []; + Animation.tweeners[ prop ].unshift( callback ); + } + }, + + prefilters: [ defaultPrefilter ], + + prefilter: function( callback, prepend ) { + if ( prepend ) { + Animation.prefilters.unshift( callback ); + } else { + Animation.prefilters.push( callback ); + } + } +} ); + +jQuery.speed = function( speed, easing, fn ) { + var opt = speed && typeof speed === "object" ? jQuery.extend( {}, speed ) : { + complete: fn || !fn && easing || + isFunction( speed ) && speed, + duration: speed, + easing: fn && easing || easing && !isFunction( easing ) && easing + }; + + // Go to the end state if fx are off + if ( jQuery.fx.off ) { + opt.duration = 0; + + } else { + if ( typeof opt.duration !== "number" ) { + if ( opt.duration in jQuery.fx.speeds ) { + opt.duration = jQuery.fx.speeds[ opt.duration ]; + + } else { + opt.duration = jQuery.fx.speeds._default; + } + } + } + + // Normalize opt.queue - true/undefined/null -> "fx" + if ( opt.queue == null || opt.queue === true ) { + opt.queue = "fx"; + } + + // Queueing + opt.old = opt.complete; + + opt.complete = function() { + if ( isFunction( opt.old ) ) { + opt.old.call( this ); + } + + if ( opt.queue ) { + jQuery.dequeue( this, opt.queue ); + } + }; + + return opt; +}; + +jQuery.fn.extend( { + fadeTo: function( speed, to, easing, callback ) { + + // Show any hidden elements after setting opacity to 0 + return this.filter( isHiddenWithinTree ).css( "opacity", 0 ).show() + + // Animate to the value specified + .end().animate( { opacity: to }, speed, easing, callback ); + }, + animate: function( prop, speed, easing, callback ) { + var empty = jQuery.isEmptyObject( prop ), + optall = jQuery.speed( speed, easing, callback ), + doAnimation = function() { + + // Operate on a copy of prop so per-property easing won't be lost + var anim = Animation( this, jQuery.extend( {}, prop ), optall ); + + // Empty animations, or finishing resolves immediately + if ( empty || dataPriv.get( this, "finish" ) ) { + anim.stop( true ); + } + }; + + doAnimation.finish = doAnimation; + + return empty || optall.queue === false ? + this.each( doAnimation ) : + this.queue( optall.queue, doAnimation ); + }, + stop: function( type, clearQueue, gotoEnd ) { + var stopQueue = function( hooks ) { + var stop = hooks.stop; + delete hooks.stop; + stop( gotoEnd ); + }; + + if ( typeof type !== "string" ) { + gotoEnd = clearQueue; + clearQueue = type; + type = undefined; + } + if ( clearQueue ) { + this.queue( type || "fx", [] ); + } + + return this.each( function() { + var dequeue = true, + index = type != null && type + "queueHooks", + timers = jQuery.timers, + data = dataPriv.get( this ); + + if ( index ) { + if ( data[ index ] && data[ index ].stop ) { + stopQueue( data[ index ] ); + } + } else { + for ( index in data ) { + if ( data[ index ] && data[ index ].stop && rrun.test( index ) ) { + stopQueue( data[ index ] ); + } + } + } + + for ( index = timers.length; index--; ) { + if ( timers[ index ].elem === this && + ( type == null || timers[ index ].queue === type ) ) { + + timers[ index ].anim.stop( gotoEnd ); + dequeue = false; + timers.splice( index, 1 ); + } + } + + // Start the next in the queue if the last step wasn't forced. + // Timers currently will call their complete callbacks, which + // will dequeue but only if they were gotoEnd. + if ( dequeue || !gotoEnd ) { + jQuery.dequeue( this, type ); + } + } ); + }, + finish: function( type ) { + if ( type !== false ) { + type = type || "fx"; + } + return this.each( function() { + var index, + data = dataPriv.get( this ), + queue = data[ type + "queue" ], + hooks = data[ type + "queueHooks" ], + timers = jQuery.timers, + length = queue ? queue.length : 0; + + // Enable finishing flag on private data + data.finish = true; + + // Empty the queue first + jQuery.queue( this, type, [] ); + + if ( hooks && hooks.stop ) { + hooks.stop.call( this, true ); + } + + // Look for any active animations, and finish them + for ( index = timers.length; index--; ) { + if ( timers[ index ].elem === this && timers[ index ].queue === type ) { + timers[ index ].anim.stop( true ); + timers.splice( index, 1 ); + } + } + + // Look for any animations in the old queue and finish them + for ( index = 0; index < length; index++ ) { + if ( queue[ index ] && queue[ index ].finish ) { + queue[ index ].finish.call( this ); + } + } + + // Turn off finishing flag + delete data.finish; + } ); + } +} ); + +jQuery.each( [ "toggle", "show", "hide" ], function( _i, name ) { + var cssFn = jQuery.fn[ name ]; + jQuery.fn[ name ] = function( speed, easing, callback ) { + return speed == null || typeof speed === "boolean" ? + cssFn.apply( this, arguments ) : + this.animate( genFx( name, true ), speed, easing, callback ); + }; +} ); + +// Generate shortcuts for custom animations +jQuery.each( { + slideDown: genFx( "show" ), + slideUp: genFx( "hide" ), + slideToggle: genFx( "toggle" ), + fadeIn: { opacity: "show" }, + fadeOut: { opacity: "hide" }, + fadeToggle: { opacity: "toggle" } +}, function( name, props ) { + jQuery.fn[ name ] = function( speed, easing, callback ) { + return this.animate( props, speed, easing, callback ); + }; +} ); + +jQuery.timers = []; +jQuery.fx.tick = function() { + var timer, + i = 0, + timers = jQuery.timers; + + fxNow = Date.now(); + + for ( ; i < timers.length; i++ ) { + timer = timers[ i ]; + + // Run the timer and safely remove it when done (allowing for external removal) + if ( !timer() && timers[ i ] === timer ) { + timers.splice( i--, 1 ); + } + } + + if ( !timers.length ) { + jQuery.fx.stop(); + } + fxNow = undefined; +}; + +jQuery.fx.timer = function( timer ) { + jQuery.timers.push( timer ); + jQuery.fx.start(); +}; + +jQuery.fx.interval = 13; +jQuery.fx.start = function() { + if ( inProgress ) { + return; + } + + inProgress = true; + schedule(); +}; + +jQuery.fx.stop = function() { + inProgress = null; +}; + +jQuery.fx.speeds = { + slow: 600, + fast: 200, + + // Default speed + _default: 400 +}; + + +// Based off of the plugin by Clint Helfers, with permission. +// https://web.archive.org/web/20100324014747/http://blindsignals.com/index.php/2009/07/jquery-delay/ +jQuery.fn.delay = function( time, type ) { + time = jQuery.fx ? jQuery.fx.speeds[ time ] || time : time; + type = type || "fx"; + + return this.queue( type, function( next, hooks ) { + var timeout = window.setTimeout( next, time ); + hooks.stop = function() { + window.clearTimeout( timeout ); + }; + } ); +}; + + +( function() { + var input = document.createElement( "input" ), + select = document.createElement( "select" ), + opt = select.appendChild( document.createElement( "option" ) ); + + input.type = "checkbox"; + + // Support: Android <=4.3 only + // Default value for a checkbox should be "on" + support.checkOn = input.value !== ""; + + // Support: IE <=11 only + // Must access selectedIndex to make default options select + support.optSelected = opt.selected; + + // Support: IE <=11 only + // An input loses its value after becoming a radio + input = document.createElement( "input" ); + input.value = "t"; + input.type = "radio"; + support.radioValue = input.value === "t"; +} )(); + + +var boolHook, + attrHandle = jQuery.expr.attrHandle; + +jQuery.fn.extend( { + attr: function( name, value ) { + return access( this, jQuery.attr, name, value, arguments.length > 1 ); + }, + + removeAttr: function( name ) { + return this.each( function() { + jQuery.removeAttr( this, name ); + } ); + } +} ); + +jQuery.extend( { + attr: function( elem, name, value ) { + var ret, hooks, + nType = elem.nodeType; + + // Don't get/set attributes on text, comment and attribute nodes + if ( nType === 3 || nType === 8 || nType === 2 ) { + return; + } + + // Fallback to prop when attributes are not supported + if ( typeof elem.getAttribute === "undefined" ) { + return jQuery.prop( elem, name, value ); + } + + // Attribute hooks are determined by the lowercase version + // Grab necessary hook if one is defined + if ( nType !== 1 || !jQuery.isXMLDoc( elem ) ) { + hooks = jQuery.attrHooks[ name.toLowerCase() ] || + ( jQuery.expr.match.bool.test( name ) ? boolHook : undefined ); + } + + if ( value !== undefined ) { + if ( value === null ) { + jQuery.removeAttr( elem, name ); + return; + } + + if ( hooks && "set" in hooks && + ( ret = hooks.set( elem, value, name ) ) !== undefined ) { + return ret; + } + + elem.setAttribute( name, value + "" ); + return value; + } + + if ( hooks && "get" in hooks && ( ret = hooks.get( elem, name ) ) !== null ) { + return ret; + } + + ret = jQuery.find.attr( elem, name ); + + // Non-existent attributes return null, we normalize to undefined + return ret == null ? undefined : ret; + }, + + attrHooks: { + type: { + set: function( elem, value ) { + if ( !support.radioValue && value === "radio" && + nodeName( elem, "input" ) ) { + var val = elem.value; + elem.setAttribute( "type", value ); + if ( val ) { + elem.value = val; + } + return value; + } + } + } + }, + + removeAttr: function( elem, value ) { + var name, + i = 0, + + // Attribute names can contain non-HTML whitespace characters + // https://html.spec.whatwg.org/multipage/syntax.html#attributes-2 + attrNames = value && value.match( rnothtmlwhite ); + + if ( attrNames && elem.nodeType === 1 ) { + while ( ( name = attrNames[ i++ ] ) ) { + elem.removeAttribute( name ); + } + } + } +} ); + +// Hooks for boolean attributes +boolHook = { + set: function( elem, value, name ) { + if ( value === false ) { + + // Remove boolean attributes when set to false + jQuery.removeAttr( elem, name ); + } else { + elem.setAttribute( name, name ); + } + return name; + } +}; + +jQuery.each( jQuery.expr.match.bool.source.match( /\w+/g ), function( _i, name ) { + var getter = attrHandle[ name ] || jQuery.find.attr; + + attrHandle[ name ] = function( elem, name, isXML ) { + var ret, handle, + lowercaseName = name.toLowerCase(); + + if ( !isXML ) { + + // Avoid an infinite loop by temporarily removing this function from the getter + handle = attrHandle[ lowercaseName ]; + attrHandle[ lowercaseName ] = ret; + ret = getter( elem, name, isXML ) != null ? + lowercaseName : + null; + attrHandle[ lowercaseName ] = handle; + } + return ret; + }; +} ); + + + + +var rfocusable = /^(?:input|select|textarea|button)$/i, + rclickable = /^(?:a|area)$/i; + +jQuery.fn.extend( { + prop: function( name, value ) { + return access( this, jQuery.prop, name, value, arguments.length > 1 ); + }, + + removeProp: function( name ) { + return this.each( function() { + delete this[ jQuery.propFix[ name ] || name ]; + } ); + } +} ); + +jQuery.extend( { + prop: function( elem, name, value ) { + var ret, hooks, + nType = elem.nodeType; + + // Don't get/set properties on text, comment and attribute nodes + if ( nType === 3 || nType === 8 || nType === 2 ) { + return; + } + + if ( nType !== 1 || !jQuery.isXMLDoc( elem ) ) { + + // Fix name and attach hooks + name = jQuery.propFix[ name ] || name; + hooks = jQuery.propHooks[ name ]; + } + + if ( value !== undefined ) { + if ( hooks && "set" in hooks && + ( ret = hooks.set( elem, value, name ) ) !== undefined ) { + return ret; + } + + return ( elem[ name ] = value ); + } + + if ( hooks && "get" in hooks && ( ret = hooks.get( elem, name ) ) !== null ) { + return ret; + } + + return elem[ name ]; + }, + + propHooks: { + tabIndex: { + get: function( elem ) { + + // Support: IE <=9 - 11 only + // elem.tabIndex doesn't always return the + // correct value when it hasn't been explicitly set + // https://web.archive.org/web/20141116233347/http://fluidproject.org/blog/2008/01/09/getting-setting-and-removing-tabindex-values-with-javascript/ + // Use proper attribute retrieval(#12072) + var tabindex = jQuery.find.attr( elem, "tabindex" ); + + if ( tabindex ) { + return parseInt( tabindex, 10 ); + } + + if ( + rfocusable.test( elem.nodeName ) || + rclickable.test( elem.nodeName ) && + elem.href + ) { + return 0; + } + + return -1; + } + } + }, + + propFix: { + "for": "htmlFor", + "class": "className" + } +} ); + +// Support: IE <=11 only +// Accessing the selectedIndex property +// forces the browser to respect setting selected +// on the option +// The getter ensures a default option is selected +// when in an optgroup +// eslint rule "no-unused-expressions" is disabled for this code +// since it considers such accessions noop +if ( !support.optSelected ) { + jQuery.propHooks.selected = { + get: function( elem ) { + + /* eslint no-unused-expressions: "off" */ + + var parent = elem.parentNode; + if ( parent && parent.parentNode ) { + parent.parentNode.selectedIndex; + } + return null; + }, + set: function( elem ) { + + /* eslint no-unused-expressions: "off" */ + + var parent = elem.parentNode; + if ( parent ) { + parent.selectedIndex; + + if ( parent.parentNode ) { + parent.parentNode.selectedIndex; + } + } + } + }; +} + +jQuery.each( [ + "tabIndex", + "readOnly", + "maxLength", + "cellSpacing", + "cellPadding", + "rowSpan", + "colSpan", + "useMap", + "frameBorder", + "contentEditable" +], function() { + jQuery.propFix[ this.toLowerCase() ] = this; +} ); + + + + + // Strip and collapse whitespace according to HTML spec + // https://infra.spec.whatwg.org/#strip-and-collapse-ascii-whitespace + function stripAndCollapse( value ) { + var tokens = value.match( rnothtmlwhite ) || []; + return tokens.join( " " ); + } + + +function getClass( elem ) { + return elem.getAttribute && elem.getAttribute( "class" ) || ""; +} + +function classesToArray( value ) { + if ( Array.isArray( value ) ) { + return value; + } + if ( typeof value === "string" ) { + return value.match( rnothtmlwhite ) || []; + } + return []; +} + +jQuery.fn.extend( { + addClass: function( value ) { + var classes, elem, cur, curValue, clazz, j, finalValue, + i = 0; + + if ( isFunction( value ) ) { + return this.each( function( j ) { + jQuery( this ).addClass( value.call( this, j, getClass( this ) ) ); + } ); + } + + classes = classesToArray( value ); + + if ( classes.length ) { + while ( ( elem = this[ i++ ] ) ) { + curValue = getClass( elem ); + cur = elem.nodeType === 1 && ( " " + stripAndCollapse( curValue ) + " " ); + + if ( cur ) { + j = 0; + while ( ( clazz = classes[ j++ ] ) ) { + if ( cur.indexOf( " " + clazz + " " ) < 0 ) { + cur += clazz + " "; + } + } + + // Only assign if different to avoid unneeded rendering. + finalValue = stripAndCollapse( cur ); + if ( curValue !== finalValue ) { + elem.setAttribute( "class", finalValue ); + } + } + } + } + + return this; + }, + + removeClass: function( value ) { + var classes, elem, cur, curValue, clazz, j, finalValue, + i = 0; + + if ( isFunction( value ) ) { + return this.each( function( j ) { + jQuery( this ).removeClass( value.call( this, j, getClass( this ) ) ); + } ); + } + + if ( !arguments.length ) { + return this.attr( "class", "" ); + } + + classes = classesToArray( value ); + + if ( classes.length ) { + while ( ( elem = this[ i++ ] ) ) { + curValue = getClass( elem ); + + // This expression is here for better compressibility (see addClass) + cur = elem.nodeType === 1 && ( " " + stripAndCollapse( curValue ) + " " ); + + if ( cur ) { + j = 0; + while ( ( clazz = classes[ j++ ] ) ) { + + // Remove *all* instances + while ( cur.indexOf( " " + clazz + " " ) > -1 ) { + cur = cur.replace( " " + clazz + " ", " " ); + } + } + + // Only assign if different to avoid unneeded rendering. + finalValue = stripAndCollapse( cur ); + if ( curValue !== finalValue ) { + elem.setAttribute( "class", finalValue ); + } + } + } + } + + return this; + }, + + toggleClass: function( value, stateVal ) { + var type = typeof value, + isValidValue = type === "string" || Array.isArray( value ); + + if ( typeof stateVal === "boolean" && isValidValue ) { + return stateVal ? this.addClass( value ) : this.removeClass( value ); + } + + if ( isFunction( value ) ) { + return this.each( function( i ) { + jQuery( this ).toggleClass( + value.call( this, i, getClass( this ), stateVal ), + stateVal + ); + } ); + } + + return this.each( function() { + var className, i, self, classNames; + + if ( isValidValue ) { + + // Toggle individual class names + i = 0; + self = jQuery( this ); + classNames = classesToArray( value ); + + while ( ( className = classNames[ i++ ] ) ) { + + // Check each className given, space separated list + if ( self.hasClass( className ) ) { + self.removeClass( className ); + } else { + self.addClass( className ); + } + } + + // Toggle whole class name + } else if ( value === undefined || type === "boolean" ) { + className = getClass( this ); + if ( className ) { + + // Store className if set + dataPriv.set( this, "__className__", className ); + } + + // If the element has a class name or if we're passed `false`, + // then remove the whole classname (if there was one, the above saved it). + // Otherwise bring back whatever was previously saved (if anything), + // falling back to the empty string if nothing was stored. + if ( this.setAttribute ) { + this.setAttribute( "class", + className || value === false ? + "" : + dataPriv.get( this, "__className__" ) || "" + ); + } + } + } ); + }, + + hasClass: function( selector ) { + var className, elem, + i = 0; + + className = " " + selector + " "; + while ( ( elem = this[ i++ ] ) ) { + if ( elem.nodeType === 1 && + ( " " + stripAndCollapse( getClass( elem ) ) + " " ).indexOf( className ) > -1 ) { + return true; + } + } + + return false; + } +} ); + + + + +var rreturn = /\r/g; + +jQuery.fn.extend( { + val: function( value ) { + var hooks, ret, valueIsFunction, + elem = this[ 0 ]; + + if ( !arguments.length ) { + if ( elem ) { + hooks = jQuery.valHooks[ elem.type ] || + jQuery.valHooks[ elem.nodeName.toLowerCase() ]; + + if ( hooks && + "get" in hooks && + ( ret = hooks.get( elem, "value" ) ) !== undefined + ) { + return ret; + } + + ret = elem.value; + + // Handle most common string cases + if ( typeof ret === "string" ) { + return ret.replace( rreturn, "" ); + } + + // Handle cases where value is null/undef or number + return ret == null ? "" : ret; + } + + return; + } + + valueIsFunction = isFunction( value ); + + return this.each( function( i ) { + var val; + + if ( this.nodeType !== 1 ) { + return; + } + + if ( valueIsFunction ) { + val = value.call( this, i, jQuery( this ).val() ); + } else { + val = value; + } + + // Treat null/undefined as ""; convert numbers to string + if ( val == null ) { + val = ""; + + } else if ( typeof val === "number" ) { + val += ""; + + } else if ( Array.isArray( val ) ) { + val = jQuery.map( val, function( value ) { + return value == null ? "" : value + ""; + } ); + } + + hooks = jQuery.valHooks[ this.type ] || jQuery.valHooks[ this.nodeName.toLowerCase() ]; + + // If set returns undefined, fall back to normal setting + if ( !hooks || !( "set" in hooks ) || hooks.set( this, val, "value" ) === undefined ) { + this.value = val; + } + } ); + } +} ); + +jQuery.extend( { + valHooks: { + option: { + get: function( elem ) { + + var val = jQuery.find.attr( elem, "value" ); + return val != null ? + val : + + // Support: IE <=10 - 11 only + // option.text throws exceptions (#14686, #14858) + // Strip and collapse whitespace + // https://html.spec.whatwg.org/#strip-and-collapse-whitespace + stripAndCollapse( jQuery.text( elem ) ); + } + }, + select: { + get: function( elem ) { + var value, option, i, + options = elem.options, + index = elem.selectedIndex, + one = elem.type === "select-one", + values = one ? null : [], + max = one ? index + 1 : options.length; + + if ( index < 0 ) { + i = max; + + } else { + i = one ? index : 0; + } + + // Loop through all the selected options + for ( ; i < max; i++ ) { + option = options[ i ]; + + // Support: IE <=9 only + // IE8-9 doesn't update selected after form reset (#2551) + if ( ( option.selected || i === index ) && + + // Don't return options that are disabled or in a disabled optgroup + !option.disabled && + ( !option.parentNode.disabled || + !nodeName( option.parentNode, "optgroup" ) ) ) { + + // Get the specific value for the option + value = jQuery( option ).val(); + + // We don't need an array for one selects + if ( one ) { + return value; + } + + // Multi-Selects return an array + values.push( value ); + } + } + + return values; + }, + + set: function( elem, value ) { + var optionSet, option, + options = elem.options, + values = jQuery.makeArray( value ), + i = options.length; + + while ( i-- ) { + option = options[ i ]; + + /* eslint-disable no-cond-assign */ + + if ( option.selected = + jQuery.inArray( jQuery.valHooks.option.get( option ), values ) > -1 + ) { + optionSet = true; + } + + /* eslint-enable no-cond-assign */ + } + + // Force browsers to behave consistently when non-matching value is set + if ( !optionSet ) { + elem.selectedIndex = -1; + } + return values; + } + } + } +} ); + +// Radios and checkboxes getter/setter +jQuery.each( [ "radio", "checkbox" ], function() { + jQuery.valHooks[ this ] = { + set: function( elem, value ) { + if ( Array.isArray( value ) ) { + return ( elem.checked = jQuery.inArray( jQuery( elem ).val(), value ) > -1 ); + } + } + }; + if ( !support.checkOn ) { + jQuery.valHooks[ this ].get = function( elem ) { + return elem.getAttribute( "value" ) === null ? "on" : elem.value; + }; + } +} ); + + + + +// Return jQuery for attributes-only inclusion + + +support.focusin = "onfocusin" in window; + + +var rfocusMorph = /^(?:focusinfocus|focusoutblur)$/, + stopPropagationCallback = function( e ) { + e.stopPropagation(); + }; + +jQuery.extend( jQuery.event, { + + trigger: function( event, data, elem, onlyHandlers ) { + + var i, cur, tmp, bubbleType, ontype, handle, special, lastElement, + eventPath = [ elem || document ], + type = hasOwn.call( event, "type" ) ? event.type : event, + namespaces = hasOwn.call( event, "namespace" ) ? event.namespace.split( "." ) : []; + + cur = lastElement = tmp = elem = elem || document; + + // Don't do events on text and comment nodes + if ( elem.nodeType === 3 || elem.nodeType === 8 ) { + return; + } + + // focus/blur morphs to focusin/out; ensure we're not firing them right now + if ( rfocusMorph.test( type + jQuery.event.triggered ) ) { + return; + } + + if ( type.indexOf( "." ) > -1 ) { + + // Namespaced trigger; create a regexp to match event type in handle() + namespaces = type.split( "." ); + type = namespaces.shift(); + namespaces.sort(); + } + ontype = type.indexOf( ":" ) < 0 && "on" + type; + + // Caller can pass in a jQuery.Event object, Object, or just an event type string + event = event[ jQuery.expando ] ? + event : + new jQuery.Event( type, typeof event === "object" && event ); + + // Trigger bitmask: & 1 for native handlers; & 2 for jQuery (always true) + event.isTrigger = onlyHandlers ? 2 : 3; + event.namespace = namespaces.join( "." ); + event.rnamespace = event.namespace ? + new RegExp( "(^|\\.)" + namespaces.join( "\\.(?:.*\\.|)" ) + "(\\.|$)" ) : + null; + + // Clean up the event in case it is being reused + event.result = undefined; + if ( !event.target ) { + event.target = elem; + } + + // Clone any incoming data and prepend the event, creating the handler arg list + data = data == null ? + [ event ] : + jQuery.makeArray( data, [ event ] ); + + // Allow special events to draw outside the lines + special = jQuery.event.special[ type ] || {}; + if ( !onlyHandlers && special.trigger && special.trigger.apply( elem, data ) === false ) { + return; + } + + // Determine event propagation path in advance, per W3C events spec (#9951) + // Bubble up to document, then to window; watch for a global ownerDocument var (#9724) + if ( !onlyHandlers && !special.noBubble && !isWindow( elem ) ) { + + bubbleType = special.delegateType || type; + if ( !rfocusMorph.test( bubbleType + type ) ) { + cur = cur.parentNode; + } + for ( ; cur; cur = cur.parentNode ) { + eventPath.push( cur ); + tmp = cur; + } + + // Only add window if we got to document (e.g., not plain obj or detached DOM) + if ( tmp === ( elem.ownerDocument || document ) ) { + eventPath.push( tmp.defaultView || tmp.parentWindow || window ); + } + } + + // Fire handlers on the event path + i = 0; + while ( ( cur = eventPath[ i++ ] ) && !event.isPropagationStopped() ) { + lastElement = cur; + event.type = i > 1 ? + bubbleType : + special.bindType || type; + + // jQuery handler + handle = ( dataPriv.get( cur, "events" ) || Object.create( null ) )[ event.type ] && + dataPriv.get( cur, "handle" ); + if ( handle ) { + handle.apply( cur, data ); + } + + // Native handler + handle = ontype && cur[ ontype ]; + if ( handle && handle.apply && acceptData( cur ) ) { + event.result = handle.apply( cur, data ); + if ( event.result === false ) { + event.preventDefault(); + } + } + } + event.type = type; + + // If nobody prevented the default action, do it now + if ( !onlyHandlers && !event.isDefaultPrevented() ) { + + if ( ( !special._default || + special._default.apply( eventPath.pop(), data ) === false ) && + acceptData( elem ) ) { + + // Call a native DOM method on the target with the same name as the event. + // Don't do default actions on window, that's where global variables be (#6170) + if ( ontype && isFunction( elem[ type ] ) && !isWindow( elem ) ) { + + // Don't re-trigger an onFOO event when we call its FOO() method + tmp = elem[ ontype ]; + + if ( tmp ) { + elem[ ontype ] = null; + } + + // Prevent re-triggering of the same event, since we already bubbled it above + jQuery.event.triggered = type; + + if ( event.isPropagationStopped() ) { + lastElement.addEventListener( type, stopPropagationCallback ); + } + + elem[ type ](); + + if ( event.isPropagationStopped() ) { + lastElement.removeEventListener( type, stopPropagationCallback ); + } + + jQuery.event.triggered = undefined; + + if ( tmp ) { + elem[ ontype ] = tmp; + } + } + } + } + + return event.result; + }, + + // Piggyback on a donor event to simulate a different one + // Used only for `focus(in | out)` events + simulate: function( type, elem, event ) { + var e = jQuery.extend( + new jQuery.Event(), + event, + { + type: type, + isSimulated: true + } + ); + + jQuery.event.trigger( e, null, elem ); + } + +} ); + +jQuery.fn.extend( { + + trigger: function( type, data ) { + return this.each( function() { + jQuery.event.trigger( type, data, this ); + } ); + }, + triggerHandler: function( type, data ) { + var elem = this[ 0 ]; + if ( elem ) { + return jQuery.event.trigger( type, data, elem, true ); + } + } +} ); + + +// Support: Firefox <=44 +// Firefox doesn't have focus(in | out) events +// Related ticket - https://bugzilla.mozilla.org/show_bug.cgi?id=687787 +// +// Support: Chrome <=48 - 49, Safari <=9.0 - 9.1 +// focus(in | out) events fire after focus & blur events, +// which is spec violation - http://www.w3.org/TR/DOM-Level-3-Events/#events-focusevent-event-order +// Related ticket - https://bugs.chromium.org/p/chromium/issues/detail?id=449857 +if ( !support.focusin ) { + jQuery.each( { focus: "focusin", blur: "focusout" }, function( orig, fix ) { + + // Attach a single capturing handler on the document while someone wants focusin/focusout + var handler = function( event ) { + jQuery.event.simulate( fix, event.target, jQuery.event.fix( event ) ); + }; + + jQuery.event.special[ fix ] = { + setup: function() { + + // Handle: regular nodes (via `this.ownerDocument`), window + // (via `this.document`) & document (via `this`). + var doc = this.ownerDocument || this.document || this, + attaches = dataPriv.access( doc, fix ); + + if ( !attaches ) { + doc.addEventListener( orig, handler, true ); + } + dataPriv.access( doc, fix, ( attaches || 0 ) + 1 ); + }, + teardown: function() { + var doc = this.ownerDocument || this.document || this, + attaches = dataPriv.access( doc, fix ) - 1; + + if ( !attaches ) { + doc.removeEventListener( orig, handler, true ); + dataPriv.remove( doc, fix ); + + } else { + dataPriv.access( doc, fix, attaches ); + } + } + }; + } ); +} +var location = window.location; + +var nonce = { guid: Date.now() }; + +var rquery = ( /\?/ ); + + + +// Cross-browser xml parsing +jQuery.parseXML = function( data ) { + var xml, parserErrorElem; + if ( !data || typeof data !== "string" ) { + return null; + } + + // Support: IE 9 - 11 only + // IE throws on parseFromString with invalid input. + try { + xml = ( new window.DOMParser() ).parseFromString( data, "text/xml" ); + } catch ( e ) {} + + parserErrorElem = xml && xml.getElementsByTagName( "parsererror" )[ 0 ]; + if ( !xml || parserErrorElem ) { + jQuery.error( "Invalid XML: " + ( + parserErrorElem ? + jQuery.map( parserErrorElem.childNodes, function( el ) { + return el.textContent; + } ).join( "\n" ) : + data + ) ); + } + return xml; +}; + + +var + rbracket = /\[\]$/, + rCRLF = /\r?\n/g, + rsubmitterTypes = /^(?:submit|button|image|reset|file)$/i, + rsubmittable = /^(?:input|select|textarea|keygen)/i; + +function buildParams( prefix, obj, traditional, add ) { + var name; + + if ( Array.isArray( obj ) ) { + + // Serialize array item. + jQuery.each( obj, function( i, v ) { + if ( traditional || rbracket.test( prefix ) ) { + + // Treat each array item as a scalar. + add( prefix, v ); + + } else { + + // Item is non-scalar (array or object), encode its numeric index. + buildParams( + prefix + "[" + ( typeof v === "object" && v != null ? i : "" ) + "]", + v, + traditional, + add + ); + } + } ); + + } else if ( !traditional && toType( obj ) === "object" ) { + + // Serialize object item. + for ( name in obj ) { + buildParams( prefix + "[" + name + "]", obj[ name ], traditional, add ); + } + + } else { + + // Serialize scalar item. + add( prefix, obj ); + } +} + +// Serialize an array of form elements or a set of +// key/values into a query string +jQuery.param = function( a, traditional ) { + var prefix, + s = [], + add = function( key, valueOrFunction ) { + + // If value is a function, invoke it and use its return value + var value = isFunction( valueOrFunction ) ? + valueOrFunction() : + valueOrFunction; + + s[ s.length ] = encodeURIComponent( key ) + "=" + + encodeURIComponent( value == null ? "" : value ); + }; + + if ( a == null ) { + return ""; + } + + // If an array was passed in, assume that it is an array of form elements. + if ( Array.isArray( a ) || ( a.jquery && !jQuery.isPlainObject( a ) ) ) { + + // Serialize the form elements + jQuery.each( a, function() { + add( this.name, this.value ); + } ); + + } else { + + // If traditional, encode the "old" way (the way 1.3.2 or older + // did it), otherwise encode params recursively. + for ( prefix in a ) { + buildParams( prefix, a[ prefix ], traditional, add ); + } + } + + // Return the resulting serialization + return s.join( "&" ); +}; + +jQuery.fn.extend( { + serialize: function() { + return jQuery.param( this.serializeArray() ); + }, + serializeArray: function() { + return this.map( function() { + + // Can add propHook for "elements" to filter or add form elements + var elements = jQuery.prop( this, "elements" ); + return elements ? jQuery.makeArray( elements ) : this; + } ).filter( function() { + var type = this.type; + + // Use .is( ":disabled" ) so that fieldset[disabled] works + return this.name && !jQuery( this ).is( ":disabled" ) && + rsubmittable.test( this.nodeName ) && !rsubmitterTypes.test( type ) && + ( this.checked || !rcheckableType.test( type ) ); + } ).map( function( _i, elem ) { + var val = jQuery( this ).val(); + + if ( val == null ) { + return null; + } + + if ( Array.isArray( val ) ) { + return jQuery.map( val, function( val ) { + return { name: elem.name, value: val.replace( rCRLF, "\r\n" ) }; + } ); + } + + return { name: elem.name, value: val.replace( rCRLF, "\r\n" ) }; + } ).get(); + } +} ); + + +var + r20 = /%20/g, + rhash = /#.*$/, + rantiCache = /([?&])_=[^&]*/, + rheaders = /^(.*?):[ \t]*([^\r\n]*)$/mg, + + // #7653, #8125, #8152: local protocol detection + rlocalProtocol = /^(?:about|app|app-storage|.+-extension|file|res|widget):$/, + rnoContent = /^(?:GET|HEAD)$/, + rprotocol = /^\/\//, + + /* Prefilters + * 1) They are useful to introduce custom dataTypes (see ajax/jsonp.js for an example) + * 2) These are called: + * - BEFORE asking for a transport + * - AFTER param serialization (s.data is a string if s.processData is true) + * 3) key is the dataType + * 4) the catchall symbol "*" can be used + * 5) execution will start with transport dataType and THEN continue down to "*" if needed + */ + prefilters = {}, + + /* Transports bindings + * 1) key is the dataType + * 2) the catchall symbol "*" can be used + * 3) selection will start with transport dataType and THEN go to "*" if needed + */ + transports = {}, + + // Avoid comment-prolog char sequence (#10098); must appease lint and evade compression + allTypes = "*/".concat( "*" ), + + // Anchor tag for parsing the document origin + originAnchor = document.createElement( "a" ); + +originAnchor.href = location.href; + +// Base "constructor" for jQuery.ajaxPrefilter and jQuery.ajaxTransport +function addToPrefiltersOrTransports( structure ) { + + // dataTypeExpression is optional and defaults to "*" + return function( dataTypeExpression, func ) { + + if ( typeof dataTypeExpression !== "string" ) { + func = dataTypeExpression; + dataTypeExpression = "*"; + } + + var dataType, + i = 0, + dataTypes = dataTypeExpression.toLowerCase().match( rnothtmlwhite ) || []; + + if ( isFunction( func ) ) { + + // For each dataType in the dataTypeExpression + while ( ( dataType = dataTypes[ i++ ] ) ) { + + // Prepend if requested + if ( dataType[ 0 ] === "+" ) { + dataType = dataType.slice( 1 ) || "*"; + ( structure[ dataType ] = structure[ dataType ] || [] ).unshift( func ); + + // Otherwise append + } else { + ( structure[ dataType ] = structure[ dataType ] || [] ).push( func ); + } + } + } + }; +} + +// Base inspection function for prefilters and transports +function inspectPrefiltersOrTransports( structure, options, originalOptions, jqXHR ) { + + var inspected = {}, + seekingTransport = ( structure === transports ); + + function inspect( dataType ) { + var selected; + inspected[ dataType ] = true; + jQuery.each( structure[ dataType ] || [], function( _, prefilterOrFactory ) { + var dataTypeOrTransport = prefilterOrFactory( options, originalOptions, jqXHR ); + if ( typeof dataTypeOrTransport === "string" && + !seekingTransport && !inspected[ dataTypeOrTransport ] ) { + + options.dataTypes.unshift( dataTypeOrTransport ); + inspect( dataTypeOrTransport ); + return false; + } else if ( seekingTransport ) { + return !( selected = dataTypeOrTransport ); + } + } ); + return selected; + } + + return inspect( options.dataTypes[ 0 ] ) || !inspected[ "*" ] && inspect( "*" ); +} + +// A special extend for ajax options +// that takes "flat" options (not to be deep extended) +// Fixes #9887 +function ajaxExtend( target, src ) { + var key, deep, + flatOptions = jQuery.ajaxSettings.flatOptions || {}; + + for ( key in src ) { + if ( src[ key ] !== undefined ) { + ( flatOptions[ key ] ? target : ( deep || ( deep = {} ) ) )[ key ] = src[ key ]; + } + } + if ( deep ) { + jQuery.extend( true, target, deep ); + } + + return target; +} + +/* Handles responses to an ajax request: + * - finds the right dataType (mediates between content-type and expected dataType) + * - returns the corresponding response + */ +function ajaxHandleResponses( s, jqXHR, responses ) { + + var ct, type, finalDataType, firstDataType, + contents = s.contents, + dataTypes = s.dataTypes; + + // Remove auto dataType and get content-type in the process + while ( dataTypes[ 0 ] === "*" ) { + dataTypes.shift(); + if ( ct === undefined ) { + ct = s.mimeType || jqXHR.getResponseHeader( "Content-Type" ); + } + } + + // Check if we're dealing with a known content-type + if ( ct ) { + for ( type in contents ) { + if ( contents[ type ] && contents[ type ].test( ct ) ) { + dataTypes.unshift( type ); + break; + } + } + } + + // Check to see if we have a response for the expected dataType + if ( dataTypes[ 0 ] in responses ) { + finalDataType = dataTypes[ 0 ]; + } else { + + // Try convertible dataTypes + for ( type in responses ) { + if ( !dataTypes[ 0 ] || s.converters[ type + " " + dataTypes[ 0 ] ] ) { + finalDataType = type; + break; + } + if ( !firstDataType ) { + firstDataType = type; + } + } + + // Or just use first one + finalDataType = finalDataType || firstDataType; + } + + // If we found a dataType + // We add the dataType to the list if needed + // and return the corresponding response + if ( finalDataType ) { + if ( finalDataType !== dataTypes[ 0 ] ) { + dataTypes.unshift( finalDataType ); + } + return responses[ finalDataType ]; + } +} + +/* Chain conversions given the request and the original response + * Also sets the responseXXX fields on the jqXHR instance + */ +function ajaxConvert( s, response, jqXHR, isSuccess ) { + var conv2, current, conv, tmp, prev, + converters = {}, + + // Work with a copy of dataTypes in case we need to modify it for conversion + dataTypes = s.dataTypes.slice(); + + // Create converters map with lowercased keys + if ( dataTypes[ 1 ] ) { + for ( conv in s.converters ) { + converters[ conv.toLowerCase() ] = s.converters[ conv ]; + } + } + + current = dataTypes.shift(); + + // Convert to each sequential dataType + while ( current ) { + + if ( s.responseFields[ current ] ) { + jqXHR[ s.responseFields[ current ] ] = response; + } + + // Apply the dataFilter if provided + if ( !prev && isSuccess && s.dataFilter ) { + response = s.dataFilter( response, s.dataType ); + } + + prev = current; + current = dataTypes.shift(); + + if ( current ) { + + // There's only work to do if current dataType is non-auto + if ( current === "*" ) { + + current = prev; + + // Convert response if prev dataType is non-auto and differs from current + } else if ( prev !== "*" && prev !== current ) { + + // Seek a direct converter + conv = converters[ prev + " " + current ] || converters[ "* " + current ]; + + // If none found, seek a pair + if ( !conv ) { + for ( conv2 in converters ) { + + // If conv2 outputs current + tmp = conv2.split( " " ); + if ( tmp[ 1 ] === current ) { + + // If prev can be converted to accepted input + conv = converters[ prev + " " + tmp[ 0 ] ] || + converters[ "* " + tmp[ 0 ] ]; + if ( conv ) { + + // Condense equivalence converters + if ( conv === true ) { + conv = converters[ conv2 ]; + + // Otherwise, insert the intermediate dataType + } else if ( converters[ conv2 ] !== true ) { + current = tmp[ 0 ]; + dataTypes.unshift( tmp[ 1 ] ); + } + break; + } + } + } + } + + // Apply converter (if not an equivalence) + if ( conv !== true ) { + + // Unless errors are allowed to bubble, catch and return them + if ( conv && s.throws ) { + response = conv( response ); + } else { + try { + response = conv( response ); + } catch ( e ) { + return { + state: "parsererror", + error: conv ? e : "No conversion from " + prev + " to " + current + }; + } + } + } + } + } + } + + return { state: "success", data: response }; +} + +jQuery.extend( { + + // Counter for holding the number of active queries + active: 0, + + // Last-Modified header cache for next request + lastModified: {}, + etag: {}, + + ajaxSettings: { + url: location.href, + type: "GET", + isLocal: rlocalProtocol.test( location.protocol ), + global: true, + processData: true, + async: true, + contentType: "application/x-www-form-urlencoded; charset=UTF-8", + + /* + timeout: 0, + data: null, + dataType: null, + username: null, + password: null, + cache: null, + throws: false, + traditional: false, + headers: {}, + */ + + accepts: { + "*": allTypes, + text: "text/plain", + html: "text/html", + xml: "application/xml, text/xml", + json: "application/json, text/javascript" + }, + + contents: { + xml: /\bxml\b/, + html: /\bhtml/, + json: /\bjson\b/ + }, + + responseFields: { + xml: "responseXML", + text: "responseText", + json: "responseJSON" + }, + + // Data converters + // Keys separate source (or catchall "*") and destination types with a single space + converters: { + + // Convert anything to text + "* text": String, + + // Text to html (true = no transformation) + "text html": true, + + // Evaluate text as a json expression + "text json": JSON.parse, + + // Parse text as xml + "text xml": jQuery.parseXML + }, + + // For options that shouldn't be deep extended: + // you can add your own custom options here if + // and when you create one that shouldn't be + // deep extended (see ajaxExtend) + flatOptions: { + url: true, + context: true + } + }, + + // Creates a full fledged settings object into target + // with both ajaxSettings and settings fields. + // If target is omitted, writes into ajaxSettings. + ajaxSetup: function( target, settings ) { + return settings ? + + // Building a settings object + ajaxExtend( ajaxExtend( target, jQuery.ajaxSettings ), settings ) : + + // Extending ajaxSettings + ajaxExtend( jQuery.ajaxSettings, target ); + }, + + ajaxPrefilter: addToPrefiltersOrTransports( prefilters ), + ajaxTransport: addToPrefiltersOrTransports( transports ), + + // Main method + ajax: function( url, options ) { + + // If url is an object, simulate pre-1.5 signature + if ( typeof url === "object" ) { + options = url; + url = undefined; + } + + // Force options to be an object + options = options || {}; + + var transport, + + // URL without anti-cache param + cacheURL, + + // Response headers + responseHeadersString, + responseHeaders, + + // timeout handle + timeoutTimer, + + // Url cleanup var + urlAnchor, + + // Request state (becomes false upon send and true upon completion) + completed, + + // To know if global events are to be dispatched + fireGlobals, + + // Loop variable + i, + + // uncached part of the url + uncached, + + // Create the final options object + s = jQuery.ajaxSetup( {}, options ), + + // Callbacks context + callbackContext = s.context || s, + + // Context for global events is callbackContext if it is a DOM node or jQuery collection + globalEventContext = s.context && + ( callbackContext.nodeType || callbackContext.jquery ) ? + jQuery( callbackContext ) : + jQuery.event, + + // Deferreds + deferred = jQuery.Deferred(), + completeDeferred = jQuery.Callbacks( "once memory" ), + + // Status-dependent callbacks + statusCode = s.statusCode || {}, + + // Headers (they are sent all at once) + requestHeaders = {}, + requestHeadersNames = {}, + + // Default abort message + strAbort = "canceled", + + // Fake xhr + jqXHR = { + readyState: 0, + + // Builds headers hashtable if needed + getResponseHeader: function( key ) { + var match; + if ( completed ) { + if ( !responseHeaders ) { + responseHeaders = {}; + while ( ( match = rheaders.exec( responseHeadersString ) ) ) { + responseHeaders[ match[ 1 ].toLowerCase() + " " ] = + ( responseHeaders[ match[ 1 ].toLowerCase() + " " ] || [] ) + .concat( match[ 2 ] ); + } + } + match = responseHeaders[ key.toLowerCase() + " " ]; + } + return match == null ? null : match.join( ", " ); + }, + + // Raw string + getAllResponseHeaders: function() { + return completed ? responseHeadersString : null; + }, + + // Caches the header + setRequestHeader: function( name, value ) { + if ( completed == null ) { + name = requestHeadersNames[ name.toLowerCase() ] = + requestHeadersNames[ name.toLowerCase() ] || name; + requestHeaders[ name ] = value; + } + return this; + }, + + // Overrides response content-type header + overrideMimeType: function( type ) { + if ( completed == null ) { + s.mimeType = type; + } + return this; + }, + + // Status-dependent callbacks + statusCode: function( map ) { + var code; + if ( map ) { + if ( completed ) { + + // Execute the appropriate callbacks + jqXHR.always( map[ jqXHR.status ] ); + } else { + + // Lazy-add the new callbacks in a way that preserves old ones + for ( code in map ) { + statusCode[ code ] = [ statusCode[ code ], map[ code ] ]; + } + } + } + return this; + }, + + // Cancel the request + abort: function( statusText ) { + var finalText = statusText || strAbort; + if ( transport ) { + transport.abort( finalText ); + } + done( 0, finalText ); + return this; + } + }; + + // Attach deferreds + deferred.promise( jqXHR ); + + // Add protocol if not provided (prefilters might expect it) + // Handle falsy url in the settings object (#10093: consistency with old signature) + // We also use the url parameter if available + s.url = ( ( url || s.url || location.href ) + "" ) + .replace( rprotocol, location.protocol + "//" ); + + // Alias method option to type as per ticket #12004 + s.type = options.method || options.type || s.method || s.type; + + // Extract dataTypes list + s.dataTypes = ( s.dataType || "*" ).toLowerCase().match( rnothtmlwhite ) || [ "" ]; + + // A cross-domain request is in order when the origin doesn't match the current origin. + if ( s.crossDomain == null ) { + urlAnchor = document.createElement( "a" ); + + // Support: IE <=8 - 11, Edge 12 - 15 + // IE throws exception on accessing the href property if url is malformed, + // e.g. http://example.com:80x/ + try { + urlAnchor.href = s.url; + + // Support: IE <=8 - 11 only + // Anchor's host property isn't correctly set when s.url is relative + urlAnchor.href = urlAnchor.href; + s.crossDomain = originAnchor.protocol + "//" + originAnchor.host !== + urlAnchor.protocol + "//" + urlAnchor.host; + } catch ( e ) { + + // If there is an error parsing the URL, assume it is crossDomain, + // it can be rejected by the transport if it is invalid + s.crossDomain = true; + } + } + + // Convert data if not already a string + if ( s.data && s.processData && typeof s.data !== "string" ) { + s.data = jQuery.param( s.data, s.traditional ); + } + + // Apply prefilters + inspectPrefiltersOrTransports( prefilters, s, options, jqXHR ); + + // If request was aborted inside a prefilter, stop there + if ( completed ) { + return jqXHR; + } + + // We can fire global events as of now if asked to + // Don't fire events if jQuery.event is undefined in an AMD-usage scenario (#15118) + fireGlobals = jQuery.event && s.global; + + // Watch for a new set of requests + if ( fireGlobals && jQuery.active++ === 0 ) { + jQuery.event.trigger( "ajaxStart" ); + } + + // Uppercase the type + s.type = s.type.toUpperCase(); + + // Determine if request has content + s.hasContent = !rnoContent.test( s.type ); + + // Save the URL in case we're toying with the If-Modified-Since + // and/or If-None-Match header later on + // Remove hash to simplify url manipulation + cacheURL = s.url.replace( rhash, "" ); + + // More options handling for requests with no content + if ( !s.hasContent ) { + + // Remember the hash so we can put it back + uncached = s.url.slice( cacheURL.length ); + + // If data is available and should be processed, append data to url + if ( s.data && ( s.processData || typeof s.data === "string" ) ) { + cacheURL += ( rquery.test( cacheURL ) ? "&" : "?" ) + s.data; + + // #9682: remove data so that it's not used in an eventual retry + delete s.data; + } + + // Add or update anti-cache param if needed + if ( s.cache === false ) { + cacheURL = cacheURL.replace( rantiCache, "$1" ); + uncached = ( rquery.test( cacheURL ) ? "&" : "?" ) + "_=" + ( nonce.guid++ ) + + uncached; + } + + // Put hash and anti-cache on the URL that will be requested (gh-1732) + s.url = cacheURL + uncached; + + // Change '%20' to '+' if this is encoded form body content (gh-2658) + } else if ( s.data && s.processData && + ( s.contentType || "" ).indexOf( "application/x-www-form-urlencoded" ) === 0 ) { + s.data = s.data.replace( r20, "+" ); + } + + // Set the If-Modified-Since and/or If-None-Match header, if in ifModified mode. + if ( s.ifModified ) { + if ( jQuery.lastModified[ cacheURL ] ) { + jqXHR.setRequestHeader( "If-Modified-Since", jQuery.lastModified[ cacheURL ] ); + } + if ( jQuery.etag[ cacheURL ] ) { + jqXHR.setRequestHeader( "If-None-Match", jQuery.etag[ cacheURL ] ); + } + } + + // Set the correct header, if data is being sent + if ( s.data && s.hasContent && s.contentType !== false || options.contentType ) { + jqXHR.setRequestHeader( "Content-Type", s.contentType ); + } + + // Set the Accepts header for the server, depending on the dataType + jqXHR.setRequestHeader( + "Accept", + s.dataTypes[ 0 ] && s.accepts[ s.dataTypes[ 0 ] ] ? + s.accepts[ s.dataTypes[ 0 ] ] + + ( s.dataTypes[ 0 ] !== "*" ? ", " + allTypes + "; q=0.01" : "" ) : + s.accepts[ "*" ] + ); + + // Check for headers option + for ( i in s.headers ) { + jqXHR.setRequestHeader( i, s.headers[ i ] ); + } + + // Allow custom headers/mimetypes and early abort + if ( s.beforeSend && + ( s.beforeSend.call( callbackContext, jqXHR, s ) === false || completed ) ) { + + // Abort if not done already and return + return jqXHR.abort(); + } + + // Aborting is no longer a cancellation + strAbort = "abort"; + + // Install callbacks on deferreds + completeDeferred.add( s.complete ); + jqXHR.done( s.success ); + jqXHR.fail( s.error ); + + // Get transport + transport = inspectPrefiltersOrTransports( transports, s, options, jqXHR ); + + // If no transport, we auto-abort + if ( !transport ) { + done( -1, "No Transport" ); + } else { + jqXHR.readyState = 1; + + // Send global event + if ( fireGlobals ) { + globalEventContext.trigger( "ajaxSend", [ jqXHR, s ] ); + } + + // If request was aborted inside ajaxSend, stop there + if ( completed ) { + return jqXHR; + } + + // Timeout + if ( s.async && s.timeout > 0 ) { + timeoutTimer = window.setTimeout( function() { + jqXHR.abort( "timeout" ); + }, s.timeout ); + } + + try { + completed = false; + transport.send( requestHeaders, done ); + } catch ( e ) { + + // Rethrow post-completion exceptions + if ( completed ) { + throw e; + } + + // Propagate others as results + done( -1, e ); + } + } + + // Callback for when everything is done + function done( status, nativeStatusText, responses, headers ) { + var isSuccess, success, error, response, modified, + statusText = nativeStatusText; + + // Ignore repeat invocations + if ( completed ) { + return; + } + + completed = true; + + // Clear timeout if it exists + if ( timeoutTimer ) { + window.clearTimeout( timeoutTimer ); + } + + // Dereference transport for early garbage collection + // (no matter how long the jqXHR object will be used) + transport = undefined; + + // Cache response headers + responseHeadersString = headers || ""; + + // Set readyState + jqXHR.readyState = status > 0 ? 4 : 0; + + // Determine if successful + isSuccess = status >= 200 && status < 300 || status === 304; + + // Get response data + if ( responses ) { + response = ajaxHandleResponses( s, jqXHR, responses ); + } + + // Use a noop converter for missing script but not if jsonp + if ( !isSuccess && + jQuery.inArray( "script", s.dataTypes ) > -1 && + jQuery.inArray( "json", s.dataTypes ) < 0 ) { + s.converters[ "text script" ] = function() {}; + } + + // Convert no matter what (that way responseXXX fields are always set) + response = ajaxConvert( s, response, jqXHR, isSuccess ); + + // If successful, handle type chaining + if ( isSuccess ) { + + // Set the If-Modified-Since and/or If-None-Match header, if in ifModified mode. + if ( s.ifModified ) { + modified = jqXHR.getResponseHeader( "Last-Modified" ); + if ( modified ) { + jQuery.lastModified[ cacheURL ] = modified; + } + modified = jqXHR.getResponseHeader( "etag" ); + if ( modified ) { + jQuery.etag[ cacheURL ] = modified; + } + } + + // if no content + if ( status === 204 || s.type === "HEAD" ) { + statusText = "nocontent"; + + // if not modified + } else if ( status === 304 ) { + statusText = "notmodified"; + + // If we have data, let's convert it + } else { + statusText = response.state; + success = response.data; + error = response.error; + isSuccess = !error; + } + } else { + + // Extract error from statusText and normalize for non-aborts + error = statusText; + if ( status || !statusText ) { + statusText = "error"; + if ( status < 0 ) { + status = 0; + } + } + } + + // Set data for the fake xhr object + jqXHR.status = status; + jqXHR.statusText = ( nativeStatusText || statusText ) + ""; + + // Success/Error + if ( isSuccess ) { + deferred.resolveWith( callbackContext, [ success, statusText, jqXHR ] ); + } else { + deferred.rejectWith( callbackContext, [ jqXHR, statusText, error ] ); + } + + // Status-dependent callbacks + jqXHR.statusCode( statusCode ); + statusCode = undefined; + + if ( fireGlobals ) { + globalEventContext.trigger( isSuccess ? "ajaxSuccess" : "ajaxError", + [ jqXHR, s, isSuccess ? success : error ] ); + } + + // Complete + completeDeferred.fireWith( callbackContext, [ jqXHR, statusText ] ); + + if ( fireGlobals ) { + globalEventContext.trigger( "ajaxComplete", [ jqXHR, s ] ); + + // Handle the global AJAX counter + if ( !( --jQuery.active ) ) { + jQuery.event.trigger( "ajaxStop" ); + } + } + } + + return jqXHR; + }, + + getJSON: function( url, data, callback ) { + return jQuery.get( url, data, callback, "json" ); + }, + + getScript: function( url, callback ) { + return jQuery.get( url, undefined, callback, "script" ); + } +} ); + +jQuery.each( [ "get", "post" ], function( _i, method ) { + jQuery[ method ] = function( url, data, callback, type ) { + + // Shift arguments if data argument was omitted + if ( isFunction( data ) ) { + type = type || callback; + callback = data; + data = undefined; + } + + // The url can be an options object (which then must have .url) + return jQuery.ajax( jQuery.extend( { + url: url, + type: method, + dataType: type, + data: data, + success: callback + }, jQuery.isPlainObject( url ) && url ) ); + }; +} ); + +jQuery.ajaxPrefilter( function( s ) { + var i; + for ( i in s.headers ) { + if ( i.toLowerCase() === "content-type" ) { + s.contentType = s.headers[ i ] || ""; + } + } +} ); + + +jQuery._evalUrl = function( url, options, doc ) { + return jQuery.ajax( { + url: url, + + // Make this explicit, since user can override this through ajaxSetup (#11264) + type: "GET", + dataType: "script", + cache: true, + async: false, + global: false, + + // Only evaluate the response if it is successful (gh-4126) + // dataFilter is not invoked for failure responses, so using it instead + // of the default converter is kludgy but it works. + converters: { + "text script": function() {} + }, + dataFilter: function( response ) { + jQuery.globalEval( response, options, doc ); + } + } ); +}; + + +jQuery.fn.extend( { + wrapAll: function( html ) { + var wrap; + + if ( this[ 0 ] ) { + if ( isFunction( html ) ) { + html = html.call( this[ 0 ] ); + } + + // The elements to wrap the target around + wrap = jQuery( html, this[ 0 ].ownerDocument ).eq( 0 ).clone( true ); + + if ( this[ 0 ].parentNode ) { + wrap.insertBefore( this[ 0 ] ); + } + + wrap.map( function() { + var elem = this; + + while ( elem.firstElementChild ) { + elem = elem.firstElementChild; + } + + return elem; + } ).append( this ); + } + + return this; + }, + + wrapInner: function( html ) { + if ( isFunction( html ) ) { + return this.each( function( i ) { + jQuery( this ).wrapInner( html.call( this, i ) ); + } ); + } + + return this.each( function() { + var self = jQuery( this ), + contents = self.contents(); + + if ( contents.length ) { + contents.wrapAll( html ); + + } else { + self.append( html ); + } + } ); + }, + + wrap: function( html ) { + var htmlIsFunction = isFunction( html ); + + return this.each( function( i ) { + jQuery( this ).wrapAll( htmlIsFunction ? html.call( this, i ) : html ); + } ); + }, + + unwrap: function( selector ) { + this.parent( selector ).not( "body" ).each( function() { + jQuery( this ).replaceWith( this.childNodes ); + } ); + return this; + } +} ); + + +jQuery.expr.pseudos.hidden = function( elem ) { + return !jQuery.expr.pseudos.visible( elem ); +}; +jQuery.expr.pseudos.visible = function( elem ) { + return !!( elem.offsetWidth || elem.offsetHeight || elem.getClientRects().length ); +}; + + + + +jQuery.ajaxSettings.xhr = function() { + try { + return new window.XMLHttpRequest(); + } catch ( e ) {} +}; + +var xhrSuccessStatus = { + + // File protocol always yields status code 0, assume 200 + 0: 200, + + // Support: IE <=9 only + // #1450: sometimes IE returns 1223 when it should be 204 + 1223: 204 + }, + xhrSupported = jQuery.ajaxSettings.xhr(); + +support.cors = !!xhrSupported && ( "withCredentials" in xhrSupported ); +support.ajax = xhrSupported = !!xhrSupported; + +jQuery.ajaxTransport( function( options ) { + var callback, errorCallback; + + // Cross domain only allowed if supported through XMLHttpRequest + if ( support.cors || xhrSupported && !options.crossDomain ) { + return { + send: function( headers, complete ) { + var i, + xhr = options.xhr(); + + xhr.open( + options.type, + options.url, + options.async, + options.username, + options.password + ); + + // Apply custom fields if provided + if ( options.xhrFields ) { + for ( i in options.xhrFields ) { + xhr[ i ] = options.xhrFields[ i ]; + } + } + + // Override mime type if needed + if ( options.mimeType && xhr.overrideMimeType ) { + xhr.overrideMimeType( options.mimeType ); + } + + // X-Requested-With header + // For cross-domain requests, seeing as conditions for a preflight are + // akin to a jigsaw puzzle, we simply never set it to be sure. + // (it can always be set on a per-request basis or even using ajaxSetup) + // For same-domain requests, won't change header if already provided. + if ( !options.crossDomain && !headers[ "X-Requested-With" ] ) { + headers[ "X-Requested-With" ] = "XMLHttpRequest"; + } + + // Set headers + for ( i in headers ) { + xhr.setRequestHeader( i, headers[ i ] ); + } + + // Callback + callback = function( type ) { + return function() { + if ( callback ) { + callback = errorCallback = xhr.onload = + xhr.onerror = xhr.onabort = xhr.ontimeout = + xhr.onreadystatechange = null; + + if ( type === "abort" ) { + xhr.abort(); + } else if ( type === "error" ) { + + // Support: IE <=9 only + // On a manual native abort, IE9 throws + // errors on any property access that is not readyState + if ( typeof xhr.status !== "number" ) { + complete( 0, "error" ); + } else { + complete( + + // File: protocol always yields status 0; see #8605, #14207 + xhr.status, + xhr.statusText + ); + } + } else { + complete( + xhrSuccessStatus[ xhr.status ] || xhr.status, + xhr.statusText, + + // Support: IE <=9 only + // IE9 has no XHR2 but throws on binary (trac-11426) + // For XHR2 non-text, let the caller handle it (gh-2498) + ( xhr.responseType || "text" ) !== "text" || + typeof xhr.responseText !== "string" ? + { binary: xhr.response } : + { text: xhr.responseText }, + xhr.getAllResponseHeaders() + ); + } + } + }; + }; + + // Listen to events + xhr.onload = callback(); + errorCallback = xhr.onerror = xhr.ontimeout = callback( "error" ); + + // Support: IE 9 only + // Use onreadystatechange to replace onabort + // to handle uncaught aborts + if ( xhr.onabort !== undefined ) { + xhr.onabort = errorCallback; + } else { + xhr.onreadystatechange = function() { + + // Check readyState before timeout as it changes + if ( xhr.readyState === 4 ) { + + // Allow onerror to be called first, + // but that will not handle a native abort + // Also, save errorCallback to a variable + // as xhr.onerror cannot be accessed + window.setTimeout( function() { + if ( callback ) { + errorCallback(); + } + } ); + } + }; + } + + // Create the abort callback + callback = callback( "abort" ); + + try { + + // Do send the request (this may raise an exception) + xhr.send( options.hasContent && options.data || null ); + } catch ( e ) { + + // #14683: Only rethrow if this hasn't been notified as an error yet + if ( callback ) { + throw e; + } + } + }, + + abort: function() { + if ( callback ) { + callback(); + } + } + }; + } +} ); + + + + +// Prevent auto-execution of scripts when no explicit dataType was provided (See gh-2432) +jQuery.ajaxPrefilter( function( s ) { + if ( s.crossDomain ) { + s.contents.script = false; + } +} ); + +// Install script dataType +jQuery.ajaxSetup( { + accepts: { + script: "text/javascript, application/javascript, " + + "application/ecmascript, application/x-ecmascript" + }, + contents: { + script: /\b(?:java|ecma)script\b/ + }, + converters: { + "text script": function( text ) { + jQuery.globalEval( text ); + return text; + } + } +} ); + +// Handle cache's special case and crossDomain +jQuery.ajaxPrefilter( "script", function( s ) { + if ( s.cache === undefined ) { + s.cache = false; + } + if ( s.crossDomain ) { + s.type = "GET"; + } +} ); + +// Bind script tag hack transport +jQuery.ajaxTransport( "script", function( s ) { + + // This transport only deals with cross domain or forced-by-attrs requests + if ( s.crossDomain || s.scriptAttrs ) { + var script, callback; + return { + send: function( _, complete ) { + script = jQuery( " + {% endmacro %} \ No newline at end of file diff --git a/api.html b/api.html new file mode 100644 index 000000000..c47e4600f --- /dev/null +++ b/api.html @@ -0,0 +1,315 @@ + + + + + + + + + API Reference — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ © Copyright 2022, Apache Software Foundation.
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+Created using Sphinx 5.1.1.
+

+
+ +
+
+ + \ No newline at end of file diff --git a/api/config.html b/api/config.html new file mode 100644 index 000000000..9173ec898 --- /dev/null +++ b/api/config.html @@ -0,0 +1,294 @@ + + + + + + + + + Config — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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datafusion.Config

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+ © Copyright 2022, Apache Software Foundation.
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+Created using Sphinx 5.1.1.
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+ + \ No newline at end of file diff --git a/api/dataframe.html b/api/dataframe.html new file mode 100644 index 000000000..28b89e13c --- /dev/null +++ b/api/dataframe.html @@ -0,0 +1,294 @@ + + + + + + + + + DataFrame — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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DataFrame

+ + + + + + +

DataFrame

A PyDataFrame is a representation of a logical plan and an API to compose statements.

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datafusion.Config

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+ © Copyright 2022, Apache Software Foundation.
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+Created using Sphinx 5.1.1.
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+ + \ No newline at end of file diff --git a/api/execution_context.html b/api/execution_context.html new file mode 100644 index 000000000..e6578c5a2 --- /dev/null +++ b/api/execution_context.html @@ -0,0 +1,294 @@ + + + + + + + + + SessionContext — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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SessionContext

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SessionContext

PySessionContext is able to plan and execute DataFusion plans.

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+Created using Sphinx 5.1.1.
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+ + \ No newline at end of file diff --git a/api/expression.html b/api/expression.html new file mode 100644 index 000000000..6e881acf8 --- /dev/null +++ b/api/expression.html @@ -0,0 +1,294 @@ + + + + + + + + + Expression — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Expression

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Expression

An PyExpr that can be used on a DataFrame

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+Created using Sphinx 5.1.1.
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+ + \ No newline at end of file diff --git a/api/functions.html b/api/functions.html new file mode 100644 index 000000000..98f1511ce --- /dev/null +++ b/api/functions.html @@ -0,0 +1,294 @@ + + + + + + + + + Functions — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+Created using Sphinx 5.1.1.
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+ + \ No newline at end of file diff --git a/api/object_store.html b/api/object_store.html new file mode 100644 index 000000000..0aca95f7a --- /dev/null +++ b/api/object_store.html @@ -0,0 +1,294 @@ + + + + + + + + + ObjectStore — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ © Copyright 2022, Apache Software Foundation.
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+Created using Sphinx 5.1.1.
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+ + \ No newline at end of file diff --git a/generated/datafusion.Config.html b/generated/datafusion.Config.html new file mode 100644 index 000000000..65b79ab85 --- /dev/null +++ b/generated/datafusion.Config.html @@ -0,0 +1,342 @@ + + + + + + + + + datafusion.Config — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+

datafusion.Config

+
+
+class datafusion.Config
+

Bases: object

+
+
+__init__()
+
+ +

Methods

+ + + + + + + + + + + + + + + + + + +

__init__()

from_env

Get configurations from environment variables

get

Get a configuration option

get_all

Get all configuration options

set

Set a configuration option

+
+
+static from_env()
+

Get configurations from environment variables

+
+ +
+
+get()
+

Get a configuration option

+
+ +
+
+get_all()
+

Get all configuration options

+
+ +
+
+set()
+

Set a configuration option

+
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+

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Config

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DataFrame

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+ © Copyright 2022, Apache Software Foundation.
+

+
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+

+Created using Sphinx 5.1.1.
+

+
+ +
+
+ + \ No newline at end of file diff --git a/generated/datafusion.DataFrame.html b/generated/datafusion.DataFrame.html new file mode 100644 index 000000000..09e3782c5 --- /dev/null +++ b/generated/datafusion.DataFrame.html @@ -0,0 +1,532 @@ + + + + + + + + + datafusion.DataFrame — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ +
+

datafusion.DataFrame

+
+
+class datafusion.DataFrame
+

Bases: object

+

A PyDataFrame is a representation of a logical plan and an API to compose statements. +Use it to build a plan and .collect() to execute the plan and collect the result. +The actual execution of a plan runs natively on Rust and Arrow on a multi-threaded environment.

+
+
+__init__()
+
+ +

Methods

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

__init__()

aggregate

cache

Cache DataFrame.

collect

Executes the plan, returning a list of `RecordBatch`es. Unless some order is specified in the plan, there is no guarantee of the order of the result.

collect_partitioned

Executes this DataFrame and collects all results into a vector of vector of RecordBatch maintaining the input partitioning.

distinct

Filter out duplicate rows

except_all

Calculate the exception of two `DataFrame`s. The two `DataFrame`s must have exactly the same schema.

explain

Print the query plan

filter

intersect

Calculate the intersection of two `DataFrame`s. The two `DataFrame`s must have exactly the same schema.

join

limit

repartition

Repartition a DataFrame based on a logical partitioning scheme.

repartition_by_hash

Repartition a DataFrame based on a logical partitioning scheme.

schema

Returns the schema from the logical plan

select

select_columns

show

Print the result, 20 lines by default

sort

union

Calculate the union of two `DataFrame`s, preserving duplicate rows.The two `DataFrame`s must have exactly the same schema

union_distinct

Calculate the distinct union of two `DataFrame`s. The two `DataFrame`s must have exactly the same schema.

with_column

with_column_renamed

Rename one column by applying a new projection.

write_csv

Write a DataFrame to a CSV file.

write_json

Executes a query and writes the results to a partitioned JSON file.

write_parquet

Write a DataFrame to a Parquet file.

+
+
+aggregate()
+
+ +
+
+cache()
+

Cache DataFrame.

+
+ +
+
+collect()
+

Executes the plan, returning a list of `RecordBatch`es. +Unless some order is specified in the plan, there is no +guarantee of the order of the result.

+
+ +
+
+collect_partitioned()
+

Executes this DataFrame and collects all results into a vector of vector of RecordBatch +maintaining the input partitioning.

+
+ +
+
+distinct()
+

Filter out duplicate rows

+
+ +
+
+except_all()
+

Calculate the exception of two `DataFrame`s. The two `DataFrame`s must have exactly the same schema

+
+ +
+
+explain()
+

Print the query plan

+
+ +
+
+filter()
+
+ +
+
+intersect()
+

Calculate the intersection of two `DataFrame`s. The two `DataFrame`s must have exactly the same schema

+
+ +
+
+join()
+
+ +
+
+limit()
+
+ +
+
+repartition()
+

Repartition a DataFrame based on a logical partitioning scheme.

+
+ +
+
+repartition_by_hash()
+

Repartition a DataFrame based on a logical partitioning scheme.

+
+ +
+
+schema()
+

Returns the schema from the logical plan

+
+ +
+
+select()
+
+ +
+
+select_columns()
+
+ +
+
+show()
+

Print the result, 20 lines by default

+
+ +
+
+sort()
+
+ +
+
+union()
+

Calculate the union of two `DataFrame`s, preserving duplicate rows.The +two `DataFrame`s must have exactly the same schema

+
+ +
+
+union_distinct()
+

Calculate the distinct union of two `DataFrame`s. The +two `DataFrame`s must have exactly the same schema

+
+ +
+
+with_column()
+
+ +
+
+with_column_renamed()
+

Rename one column by applying a new projection. This is a no-op if the column to be +renamed does not exist.

+
+ +
+
+write_csv()
+

Write a DataFrame to a CSV file.

+
+ +
+
+write_json()
+

Executes a query and writes the results to a partitioned JSON file.

+
+ +
+
+write_parquet()
+

Write a DataFrame to a Parquet file.

+
+ +
+ +
+ + +
+ + + +
+ + +
+

previous

+

DataFrame

+
+ + +
+

next

+

SessionContext

+
+ + +
+ +
+ + +
+
+ + +
+
+ +
+

+ © Copyright 2022, Apache Software Foundation.
+

+
+ +
+

+Created using Sphinx 5.1.1.
+

+
+ +
+
+ + \ No newline at end of file diff --git a/generated/datafusion.Expression.html b/generated/datafusion.Expression.html new file mode 100644 index 000000000..d0c6d8c0b --- /dev/null +++ b/generated/datafusion.Expression.html @@ -0,0 +1,357 @@ + + + + + + + + + datafusion.Expression — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+
+ + + + +
+ + +
+ + +
+
+
+
+ + + + +
+ + +
+ + + +
+ +
+ + +
+ + Edit this page + +
+ +
+ + +
+ + + + + + +
+ +
+ +
+

datafusion.Expression

+
+
+class datafusion.Expression
+

Bases: object

+

An PyExpr that can be used on a DataFrame

+
+
+__init__()
+
+ +

Methods

+ + + + + + + + + + + + + + + + + + + + + + + + +

__init__()

alias

assign a name to the PyExpr

cast

column

is_null

literal

sort

Create a sort PyExpr from an existing PyExpr.

+
+
+alias()
+

assign a name to the PyExpr

+
+ +
+
+cast()
+
+ +
+
+static column()
+
+ +
+
+is_null()
+
+ +
+
+static literal()
+
+ +
+
+sort()
+

Create a sort PyExpr from an existing PyExpr.

+
+ +
+ +
+ + +
+ + + +
+ + +
+

previous

+

Expression

+
+ + +
+

next

+

Functions

+
+ + +
+ +
+ + +
+
+ + +
+
+ +
+

+ © Copyright 2022, Apache Software Foundation.
+

+
+ +
+

+Created using Sphinx 5.1.1.
+

+
+ +
+
+ + \ No newline at end of file diff --git a/generated/datafusion.SessionContext.html b/generated/datafusion.SessionContext.html new file mode 100644 index 000000000..08ee3f3cf --- /dev/null +++ b/generated/datafusion.SessionContext.html @@ -0,0 +1,479 @@ + + + + + + + + + datafusion.SessionContext — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+
+ + + + +
+ + +
+ + +
+
+
+
+ + + + +
+ + +
+ + + +
+ +
+ + +
+ + Edit this page + +
+ +
+ + +
+ + + + + + +
+ +
+ +
+

datafusion.SessionContext

+
+
+class datafusion.SessionContext
+

Bases: object

+

PySessionContext is able to plan and execute DataFusion plans. +It has a powerful optimizer, a physical planner for local execution, and a +multi-threaded execution engine to perform the execution.

+
+
+__init__()
+
+ +

Methods

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

__init__()

catalog

create_dataframe

deregister_table

empty_table

read_avro

read_csv

read_json

read_parquet

register_csv

register_dataset

register_object_store

Register a an object store with the given name

register_parquet

register_record_batches

register_table

register_udaf

register_udf

session_id

sql

Returns a PyDataFrame whose plan corresponds to the SQL statement.

table

table_exist

tables

+
+
+catalog()
+
+ +
+
+create_dataframe()
+
+ +
+
+deregister_table()
+
+ +
+
+empty_table()
+
+ +
+
+read_avro()
+
+ +
+
+read_csv()
+
+ +
+
+read_json()
+
+ +
+
+read_parquet()
+
+ +
+
+register_csv()
+
+ +
+
+register_dataset()
+
+ +
+
+register_object_store()
+

Register a an object store with the given name

+
+ +
+
+register_parquet()
+
+ +
+
+register_record_batches()
+
+ +
+
+register_table()
+
+ +
+
+register_udaf()
+
+ +
+
+register_udf()
+
+ +
+
+session_id()
+
+ +
+
+sql()
+

Returns a PyDataFrame whose plan corresponds to the SQL statement.

+
+ +
+
+table()
+
+ +
+
+table_exist()
+
+ +
+
+tables()
+
+ +
+ +
+ + +
+ + + +
+ + +
+

previous

+

SessionContext

+
+ + +
+

next

+

Expression

+
+ + +
+ +
+ + +
+
+ + +
+
+ +
+

+ © Copyright 2022, Apache Software Foundation.
+

+
+ +
+

+Created using Sphinx 5.1.1.
+

+
+ +
+
+ + \ No newline at end of file diff --git a/generated/datafusion.functions.functions.html b/generated/datafusion.functions.functions.html new file mode 100644 index 000000000..7705f782a --- /dev/null +++ b/generated/datafusion.functions.functions.html @@ -0,0 +1,655 @@ + + + + + + + + + datafusion.functions.functions — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+
+ + + + +
+ + +
+ + +
+
+
+
+ + + + +
+ + +
+ + + +
+ +
+ + +
+ + Edit this page + +
+ +
+ + +
+ + + + + + +
+ +
+ +
+

datafusion.functions.functions

+
+
+datafusion.functions.functions.abs()
+
+ +
+
+datafusion.functions.functions.acos()
+
+ +
+
+datafusion.functions.functions.alias()
+

Creates a new Alias expression

+
+ +
+
+datafusion.functions.functions.approx_distinct()
+
+ +
+
+datafusion.functions.functions.array()
+
+ +
+
+datafusion.functions.functions.ascii()
+

Returns the numeric code of the first character of the argument. In UTF8 encoding, returns the Unicode code point of the character. In other multibyte encodings, the argument must be an ASCII character.

+
+ +
+
+datafusion.functions.functions.asin()
+
+ +
+
+datafusion.functions.functions.atan()
+
+ +
+
+datafusion.functions.functions.avg()
+
+ +
+
+datafusion.functions.functions.bit_length()
+

Returns number of bits in the string (8 times the octet_length).

+
+ +
+
+datafusion.functions.functions.btrim()
+

Removes the longest string containing only characters in characters (a space by default) from the start and end of string.

+
+ +
+
+datafusion.functions.functions.ceil()
+
+ +
+
+datafusion.functions.functions.character_length()
+

Returns number of characters in the string.

+
+ +
+
+datafusion.functions.functions.chr()
+

Returns the character with the given code.

+
+ +
+
+datafusion.functions.functions.concat()
+

Concatenates the text representations of all the arguments. +NULL arguments are ignored.

+
+ +
+
+datafusion.functions.functions.concat_ws()
+

Concatenates all but the first argument, with separators. +The first argument is used as the separator string, and should not be NULL. +Other NULL arguments are ignored.

+
+ +
+
+datafusion.functions.functions.cos()
+
+ +
+
+datafusion.functions.functions.count()
+
+ +
+
+datafusion.functions.functions.digest()
+

Computes a binary hash of the given data. type is the algorithm to use. +Standard algorithms are md5, sha224, sha256, sha384, sha512, blake2s, blake2b, and blake3.

+
+ +
+
+datafusion.functions.functions.exp()
+
+ +
+
+datafusion.functions.functions.floor()
+
+ +
+
+datafusion.functions.functions.in_list()
+
+ +
+
+datafusion.functions.functions.initcap()
+

Converts the first letter of each word to upper case and the rest to lower case. Words are sequences of alphanumeric characters separated by non-alphanumeric characters.

+
+ +
+
+datafusion.functions.functions.left()
+

Returns first n characters in the string, or when n is negative, returns all but last |n| characters.

+
+ +
+
+datafusion.functions.functions.ln()
+
+ +
+
+datafusion.functions.functions.log10()
+
+ +
+
+datafusion.functions.functions.log2()
+
+ +
+
+datafusion.functions.functions.lower()
+

Converts the string to all lower case

+
+ +
+
+datafusion.functions.functions.lpad()
+

Extends the string to length length by prepending the characters fill (a space by default). If the string is already longer than length then it is truncated (on the right).

+
+ +
+
+datafusion.functions.functions.ltrim()
+

Removes the longest string containing only characters in characters (a space by default) from the start of string.

+
+ +
+
+datafusion.functions.functions.max()
+
+ +
+
+datafusion.functions.functions.md5()
+

Computes the MD5 hash of the argument, with the result written in hexadecimal.

+
+ +
+
+datafusion.functions.functions.min()
+
+ +
+
+datafusion.functions.functions.now()
+

Current date and time

+
+ +
+
+datafusion.functions.functions.octet_length()
+

Returns number of bytes in the string. Since this version of the function accepts type character directly, it will not strip trailing spaces.

+
+ +
+
+datafusion.functions.functions.order_by()
+

Creates a new Sort expression

+
+ +
+
+datafusion.functions.functions.random()
+

Returns a random value in the range 0.0 <= x < 1.0

+
+ +
+
+datafusion.functions.functions.regexp_match()
+
+ +
+
+datafusion.functions.functions.regexp_replace()
+

Replaces substring(s) matching a POSIX regular expression

+
+ +
+
+datafusion.functions.functions.repeat()
+

Repeats string the specified number of times.

+
+ +
+
+datafusion.functions.functions.replace()
+

Replaces all occurrences in string of substring from with substring to.

+
+ +
+
+datafusion.functions.functions.reverse()
+

Reverses the order of the characters in the string.

+
+ +
+
+datafusion.functions.functions.right()
+

Returns last n characters in the string, or when n is negative, returns all but first |n| characters.

+
+ +
+
+datafusion.functions.functions.round()
+
+ +
+
+datafusion.functions.functions.rpad()
+

Extends the string to length length by appending the characters fill (a space by default). If the string is already longer than length then it is truncated.

+
+ +
+
+datafusion.functions.functions.rtrim()
+

Removes the longest string containing only characters in characters (a space by default) from the end of string.

+
+ +
+
+datafusion.functions.functions.sha224()
+
+ +
+
+datafusion.functions.functions.sha256()
+
+ +
+
+datafusion.functions.functions.sha384()
+
+ +
+
+datafusion.functions.functions.sha512()
+
+ +
+
+datafusion.functions.functions.signum()
+
+ +
+
+datafusion.functions.functions.sin()
+
+ +
+
+datafusion.functions.functions.split_part()
+

Splits string at occurrences of delimiter and returns the n’th field (counting from one).

+
+ +
+
+datafusion.functions.functions.sqrt()
+
+ +
+
+datafusion.functions.functions.starts_with()
+

Returns true if string starts with prefix.

+
+ +
+
+datafusion.functions.functions.strpos()
+

Returns starting index of specified substring within string, or zero if it’s not present. (Same as position(substring in string), but note the reversed argument order.)

+
+ +
+
+datafusion.functions.functions.substr()
+
+ +
+
+datafusion.functions.functions.sum()
+
+ +
+
+datafusion.functions.functions.tan()
+
+ +
+
+datafusion.functions.functions.to_hex()
+

Converts the number to its equivalent hexadecimal representation.

+
+ +
+
+datafusion.functions.functions.to_timestamp()
+
+ +
+
+datafusion.functions.functions.translate()
+

Replaces each character in string that matches a character in the from set with the corresponding character in the to set. If from is longer than to, occurrences of the extra characters in from are deleted.

+
+ +
+
+datafusion.functions.functions.trim()
+

Removes the longest string containing only characters in characters (a space by default) from the start, end, or both ends (BOTH is the default) of string.

+
+ +
+
+datafusion.functions.functions.trunc()
+
+ +
+
+datafusion.functions.functions.upper()
+

Converts the string to all upper case.

+
+ +
+
+datafusion.functions.functions.window()
+

Creates a new Window function expression

+
+ +
+ + +
+ + + +
+ + +
+

previous

+

Functions

+
+ + +
+

next

+

ObjectStore

+
+ + +
+ +
+ + +
+
+ + +
+
+ +
+

+ © Copyright 2022, Apache Software Foundation.
+

+
+ +
+

+Created using Sphinx 5.1.1.
+

+
+ +
+
+ + \ No newline at end of file diff --git a/generated/datafusion.object_store.object_store.html b/generated/datafusion.object_store.object_store.html new file mode 100644 index 000000000..f048e6030 --- /dev/null +++ b/generated/datafusion.object_store.object_store.html @@ -0,0 +1,303 @@ + + + + + + + + + datafusion.object_store.object_store — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+
+ + + + +
+ + +
+ + +
+
+
+
+ + + + +
+ + +
+ + + +
+ +
+ + +
+ + Edit this page + +
+ +
+ + +
+ + + + + + +
+ +
+ +
+

datafusion.object_store.object_store

+
+
+class datafusion.object_store.object_store.AmazonS3
+

Bases: object

+
+ +
+
+class datafusion.object_store.object_store.GoogleCloud
+

Bases: object

+
+ +
+
+class datafusion.object_store.object_store.LocalFileSystem
+

Bases: object

+
+ +
+
+class datafusion.object_store.object_store.MicrosoftAzure
+

Bases: object

+
+ +
+ + +
+ + + +
+ + +
+

previous

+

ObjectStore

+
+ +
+ +
+ + +
+
+ + +
+
+ +
+

+ © Copyright 2022, Apache Software Foundation.
+

+
+ +
+

+Created using Sphinx 5.1.1.
+

+
+ +
+
+ + \ No newline at end of file diff --git a/genindex.html b/genindex.html new file mode 100644 index 000000000..5499f2688 --- /dev/null +++ b/genindex.html @@ -0,0 +1,714 @@ + + + + + + + + Index — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+
+ + + + +
+ + +
+ + +
+
+
+
+ + + + +
+ +
+ + + + + + +
+ +
+ + +

Index

+ +
+ _ + | A + | B + | C + | D + | E + | F + | G + | I + | J + | L + | M + | N + | O + | R + | S + | T + | U + | W + +
+

_

+ + +
+ +

A

+ + + +
+ +

B

+ + + +
+ +

C

+ + + +
+ +

D

+ + + +
+ +

E

+ + + +
+ +

F

+ + + +
+ +

G

+ + + +
+ +

I

+ + + +
+ +

J

+ + +
+ +

L

+ + + +
+ +

M

+ + + +
+ +

N

+ + +
+ +

O

+ + + +
+ +

R

+ + + +
+ +

S

+ + + +
+ +

T

+ + + +
+ +

U

+ + + +
+ +

W

+ + + +
+ + + +
+ + + +
+
+ +
+ + +
+
+ + +
+
+ +
+

+ © Copyright 2022, Apache Software Foundation.
+

+
+ +
+

+Created using Sphinx 5.1.1.
+

+
+ +
+
+ + \ No newline at end of file diff --git a/index.html b/index.html new file mode 100644 index 000000000..3f05cc533 --- /dev/null +++ b/index.html @@ -0,0 +1,557 @@ + + + + + + + + + DataFusion in Python — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+
+ + + + +
+ + +
+ + +
+
+
+
+ + + + +
+ + +
+ +
+ On this page +
+ + +
+ +
+ + +
+ + Edit this page + +
+ +
+ + +
+ + + + + + +
+ +
+ +
+

DataFusion in Python

+

This is a Python library that binds to Apache Arrow in-memory query engine DataFusion.

+

Like pyspark, it allows you to build a plan through SQL or a DataFrame API against in-memory data, parquet or CSV files, run it in a multi-threaded environment, and obtain the result back in Python.

+

It also allows you to use UDFs and UDAFs for complex operations.

+

The major advantage of this library over other execution engines is that this library achieves zero-copy between Python and its execution engine: there is no cost in using UDFs, UDAFs, and collecting the results to Python apart from having to lock the GIL when running those operations.

+

Its query engine, DataFusion, is written in Rust, which makes strong assumptions about thread safety and lack of memory leaks.

+

Technically, zero-copy is achieved via the c data interface.

+
+

How to use it

+

Simple usage:

+
import datafusion
+from datafusion import col
+import pyarrow
+
+# create a context
+ctx = datafusion.SessionContext()
+
+# create a RecordBatch and a new DataFrame from it
+batch = pyarrow.RecordBatch.from_arrays(
+    [pyarrow.array([1, 2, 3]), pyarrow.array([4, 5, 6])],
+    names=["a", "b"],
+)
+df = ctx.create_dataframe([[batch]])
+
+# create a new statement
+df = df.select(
+    col("a") + col("b"),
+    col("a") - col("b"),
+)
+
+# execute and collect the first (and only) batch
+result = df.collect()[0]
+
+assert result.column(0) == pyarrow.array([5, 7, 9])
+assert result.column(1) == pyarrow.array([-3, -3, -3])
+
+
+

We can also execute a query against data stored in CSV

+
echo "a,b\n1,4\n2,5\n3,6" > example.csv
+
+
+
import datafusion
+from datafusion import col
+import pyarrow
+
+# create a context
+ctx = datafusion.SessionContext()
+
+# register a CSV
+ctx.register_csv('example', 'example.csv')
+
+# create a new statement
+df = ctx.table('example').select(
+    col("a") + col("b"),
+    col("a") - col("b"),
+)
+
+# execute and collect the first (and only) batch
+result = df.collect()[0]
+
+assert result.column(0) == pyarrow.array([5, 7, 9])
+assert result.column(1) == pyarrow.array([-3, -3, -3])
+
+
+

And how to execute a query against a CSV using SQL:

+
import datafusion
+from datafusion import col
+import pyarrow
+
+# create a context
+ctx = datafusion.SessionContext()
+
+# register a CSV
+ctx.register_csv('example', 'example.csv')
+
+# create a new statement via SQL
+df = ctx.sql("SELECT a+b, a-b FROM example")
+
+# execute and collect the first (and only) batch
+result = df.collect()[0]
+
+assert result.column(0) == pyarrow.array([5, 7, 9])
+assert result.column(1) == pyarrow.array([-3, -3, -3])
+
+
+
+

UDFs

+
import pyarrow
+from datafusion import udf
+
+def is_null(array: pyarrow.Array) -> pyarrow.Array:
+    return array.is_null()
+
+is_null_arr = udf(is_null, [pyarrow.int64()], pyarrow.bool_(), 'stable')
+
+# create a context
+ctx = datafusion.SessionContext()
+
+# create a RecordBatch and a new DataFrame from it
+batch = pyarrow.RecordBatch.from_arrays(
+    [pyarrow.array([1, 2, 3]), pyarrow.array([4, 5, 6])],
+    names=["a", "b"],
+)
+df = ctx.create_dataframe([[batch]])
+
+df = df.select(is_null_arr(col("a")))
+
+result = df.collect()[0]
+
+assert result.column(0) == pyarrow.array([False] * 3)
+
+
+
+
+

UDAF

+
import pyarrow
+import pyarrow.compute
+import datafusion
+from datafusion import udaf, Accumulator
+from datafusion import col
+
+
+class MyAccumulator(Accumulator):
+    """
+    Interface of a user-defined accumulation.
+    """
+    def __init__(self):
+        self._sum = pyarrow.scalar(0.0)
+
+    def update(self, values: pyarrow.Array) -> None:
+        # not nice since pyarrow scalars can't be summed yet. This breaks on `None`
+        self._sum = pyarrow.scalar(self._sum.as_py() + pyarrow.compute.sum(values).as_py())
+
+    def merge(self, states: pyarrow.Array) -> None:
+        # not nice since pyarrow scalars can't be summed yet. This breaks on `None`
+        self._sum = pyarrow.scalar(self._sum.as_py() + pyarrow.compute.sum(states).as_py())
+
+    def state(self) -> pyarrow.Array:
+        return pyarrow.array([self._sum.as_py()])
+
+    def evaluate(self) -> pyarrow.Scalar:
+        return self._sum
+
+# create a context
+ctx = datafusion.SessionContext()
+
+# create a RecordBatch and a new DataFrame from it
+batch = pyarrow.RecordBatch.from_arrays(
+    [pyarrow.array([1, 2, 3]), pyarrow.array([4, 5, 6])],
+    names=["a", "b"],
+)
+df = ctx.create_dataframe([[batch]])
+
+my_udaf = udaf(MyAccumulator, pyarrow.float64(), pyarrow.float64(), [pyarrow.float64()], 'stable')
+
+df = df.aggregate(
+    [],
+    [my_udaf(col("a"))]
+)
+
+result = df.collect()[0]
+
+assert result.column(0) == pyarrow.array([6.0])
+
+
+
+
+
+

How to install (from pip)

+
pip install datafusion
+
+
+

You can verify the installation by running:

+
>>> import datafusion
+>>> datafusion.__version__
+'0.6.0'
+
+
+
+
+

How to develop

+

This assumes that you have rust and cargo installed. We use the workflow recommended by pyo3 and maturin.

+

Bootstrap:

+
# fetch this repo
+git clone git@github.com:apache/arrow-datafusion-python.git
+# prepare development environment (used to build wheel / install in development)
+python3 -m venv venv
+# activate the venv
+source venv/bin/activate
+# update pip itself if necessary
+python -m pip install -U pip
+# install dependencies (for Python 3.8+)
+python -m pip install -r requirements-310.txt
+
+
+

The tests rely on test data in git submodules.

+
git submodule init
+git submodule update
+
+
+

Whenever rust code changes (your changes or via git pull):

+
# make sure you activate the venv using "source venv/bin/activate" first
+maturin develop
+python -m pytest
+
+
+
+
+

How to update dependencies

+

To change test dependencies, change the requirements.in and run

+
# install pip-tools (this can be done only once), also consider running in venv
+python -m pip install pip-tools
+python -m piptools compile --generate-hashes -o requirements-310.txt
+
+
+

To update dependencies, run with -U

+
python -m piptools compile -U --generate-hashes -o requirements-310.txt
+
+
+

More details about pip-tools here

+
+
+

API reference

+
+ +
+
+
+ + +
+ + + +
+ +
+

next

+

API Reference

+
+ + +
+ +
+ + +
+
+ + +
+
+ +
+

+ © Copyright 2022, Apache Software Foundation.
+

+
+ +
+

+Created using Sphinx 5.1.1.
+

+
+ +
+
+ + \ No newline at end of file diff --git a/objects.inv b/objects.inv new file mode 100644 index 0000000000000000000000000000000000000000..3307cf4ebbef2a21f9766280bd8cb252f6f21197 GIT binary patch literal 1456 zcmV;h1yA}TAX9K?X>NERX>N99Zgg*Qc_4OWa&u{KZXhxWBOp+6Z)#;@bUGkGa&m8X zAVgtwVMcXxX>V={BOq2~a&u{KZaN?eBOp|0Wgv28ZDDC{WMy(7Z)PBLXlZjGW@&6? zAZc?TV{dJ6a%FRKWn>_Ab7^j8AbMqh(uDXAK<(L7yGB#_QO>%#I&5r~KB#@kkH-g8Xukj3c9EONm8W)BudG}Sxm?vSr z|H1?{CcF<5kf5oBXdRuJ-K91Yzx*1mf?*ROTyjfDiORsHD!QE&Yn2g@A3j(KSWg&2 zh46tgKRKd5-QlyQ8BBWZXnC1)h41DPX_9D2TyK9!Mp^0;r-T4zy#q;3wdK~eLF5k} zabvmkIb7H=$Y;j%d}b~vm;Qh;7Z$WX9+wVhyt@5O`MhAkGwyM48jjJ30wtS0NvTQw z!Hv7gGwP8Ce(&;{N8HU`WYT!#rfTbvrnJXvE~MA^sc^*q6K%_F+BgOUN;F7!%Hvag ztGNZj%!hB}oAK$en(1!(_X2*}Uw`d#4aPJPbuoQuO(#fKBrx-tRB&p10vR>dD{p3~ z&nI$2WHBcpn2!`LbTsvfocC~>;JwyuF3q;Evy-9NH=jYgA|$V8GuI+if`ZoIAfz%l z>@j?6MBw%Y?(q+rSh^7?8j$67kB4`&6cPHN6&ifjs&FHF-turGeD*qV3%>~)w8?4s zrHMhl2DN!BGf88W22`OX9HN0K9gz*SE`K+uQi%6-qfkUNMixNfoBAi=5eofXU|`YQ zS%C@cxUpz>Kan06ZXe_hOnX#uRaCgC`83WQ=~Tn(ZmVgHJG!ZK4kylC!C9p_5=`N1 z91?X@kv!LG*W0zC%4tpa=pu%3jxSRGKZdGdDZa)>f-SLe`vn0qu_?Ne)jY!%VZa5t zMoKkh<(j(8#IaPPODO5~cgv`dt-%*sK%$W76Bh9V47v*Ja%_oMD1{!xToS?Yr>p#n zg;De=6A+_cia=k%gi7u|EgU^iCjQ&va_48!y&V=r4!M~MC z1bh{$h!)fQM=>g%xq#Qbv5+mM`<*kbjEe2kk3xfI*>nC|-A2DIT1G}P>R8OdbOlGo zbJppYV>%Tb8P~a>z#P_z<|?2$4~>n!M2eNd?q@{{pI*L&|3M5IB!i=spc@cfI~R)s z%kpJN`4QAvX?|#ieBXKOd9bxxNC2Q!>zOAIJNNtV60Cci+l$_T3`EXQGdP~OuGz^xKRi9ne zeg3U}yq3p7>#LK{=z6f@wsqfa9s9o1`fgf}yQ$NA+({$uSf99~$LKlZWcJtn+3)o0 z&wYQk*Mr&abR5ieZ)z`moYng K2>u5}tykyDF33s% literal 0 HcmV?d00001 diff --git a/py-modindex.html b/py-modindex.html new file mode 100644 index 000000000..b039246d2 --- /dev/null +++ b/py-modindex.html @@ -0,0 +1,277 @@ + + + + + + + + Python Module Index — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+
+ + + + +
+ + +
+ + +
+
+
+
+ + + + +
+ +
+ + + + + + +
+ +
+ + +

Python Module Index

+ +
+ d +
+ + + + + + + + + + + + + +
 
+ d
+ datafusion +
    + datafusion.functions.functions +
    + datafusion.object_store.object_store +
+ + +
+ + + +
+
+ +
+ + +
+
+ + +
+
+ +
+

+ © Copyright 2022, Apache Software Foundation.
+

+
+ +
+

+Created using Sphinx 5.1.1.
+

+
+ +
+
+ + \ No newline at end of file diff --git a/search.html b/search.html new file mode 100644 index 000000000..401203150 --- /dev/null +++ b/search.html @@ -0,0 +1,281 @@ + + + + + + + + Search — Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+
+ + + + +
+ + +
+ + +
+
+
+
+ + + + +
+ +
+ + + + + + +
+ +
+ +

Search

+ + + + +

+ Searching for multiple words only shows matches that contain + all words. +

+ + +
+ + + +
+ + + +
+ +
+ + +
+ + + +
+
+ +
+ + +
+
+ + +
+
+ +
+

+ © Copyright 2022, Apache Software Foundation.
+

+
+ +
+

+Created using Sphinx 5.1.1.
+

+
+ +
+
+ + \ No newline at end of file diff --git a/searchindex.js b/searchindex.js new file mode 100644 index 000000000..c435ee224 --- /dev/null +++ b/searchindex.js @@ -0,0 +1 @@ +Search.setIndex({"docnames": ["api", "api/config", "api/dataframe", "api/execution_context", "api/expression", "api/functions", "api/object_store", "generated/datafusion.Config", "generated/datafusion.DataFrame", "generated/datafusion.Expression", "generated/datafusion.SessionContext", "generated/datafusion.functions.functions", "generated/datafusion.object_store.object_store", "index"], "filenames": ["api.rst", "api/config.rst", "api/dataframe.rst", "api/execution_context.rst", "api/expression.rst", "api/functions.rst", "api/object_store.rst", "generated/datafusion.Config.rst", "generated/datafusion.DataFrame.rst", "generated/datafusion.Expression.rst", "generated/datafusion.SessionContext.rst", "generated/datafusion.functions.functions.rst", "generated/datafusion.object_store.object_store.rst", "index.rst"], "titles": ["API Reference", "Config", "DataFrame", "SessionContext", "Expression", "Functions", "ObjectStore", "datafusion.Config", "datafusion.DataFrame", "datafusion.Expression", "datafusion.SessionContext", "datafusion.functions.functions", "datafusion.object_store.object_store", "DataFusion in Python"], "terms": {"config": [0, 13], "datafus": 0, "datafram": [0, 9, 13], "sessioncontext": [0, 13], "express": [0, 11, 13], "function": [0, 13], "objectstor": [0, 13], "object_stor": 0, "class": [7, 8, 9, 10, 12, 13], "base": [7, 8, 9, 10, 12], "object": [7, 8, 9, 10, 12], "__init__": [7, 8, 9, 10, 13], "method": [7, 8, 9, 10], "static": [7, 9], "from_env": 7, "get": 7, "configur": 7, "from": [7, 8, 9, 11], "environ": [7, 8, 13], "variabl": 7, "option": 7, "get_al": 7, "all": [7, 8, 11], "set": [7, 11], "A": 8, "pydatafram": [8, 10], "i": [8, 10, 11, 13], "represent": [8, 11], "logic": 8, "plan": [8, 10, 13], "an": [8, 9, 10, 11], "api": 8, "compos": 8, "statement": [8, 10, 13], "us": [8, 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"to_timestamp"], [11, 3, 1, "", "translate"], [11, 3, 1, "", "trim"], [11, 3, 1, "", "trunc"], [11, 3, 1, "", "upper"], [11, 3, 1, "", "window"]], "datafusion.object_store": [[12, 2, 0, "-", "object_store"]], "datafusion.object_store.object_store": [[12, 0, 1, "", "AmazonS3"], [12, 0, 1, "", "GoogleCloud"], [12, 0, 1, "", "LocalFileSystem"], [12, 0, 1, "", "MicrosoftAzure"]]}, "objtypes": {"0": "py:class", "1": "py:method", "2": "py:module", "3": "py:function"}, "objnames": {"0": ["py", "class", "Python class"], "1": ["py", "method", "Python method"], "2": ["py", "module", "Python module"], "3": ["py", "function", "Python function"]}, "titleterms": {"api": [0, 13], "refer": [0, 13], "config": [1, 7], "datafram": [2, 8], "sessioncontext": [3, 10], "express": [4, 9], "function": [5, 11], "objectstor": 6, "datafus": [7, 8, 9, 10, 11, 12, 13], "object_stor": 12, "python": 13, "how": 13, "us": 13, "udf": 13, "udaf": 13, "instal": 13, "from": 13, "pip": 13, "develop": 13, "updat": 13, "depend": 13}, "envversion": {"sphinx.domains.c": 2, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 6, "sphinx.domains.index": 1, "sphinx.domains.javascript": 2, "sphinx.domains.math": 2, "sphinx.domains.python": 3, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.viewcode": 1, "sphinx": 56}}) \ No newline at end of file From 195a4785ec1e1f923902143562bdbeb42eac7e84 Mon Sep 17 00:00:00 2001 From: Martin Grigorov Date: Tue, 6 Dec 2022 22:43:26 +0200 Subject: [PATCH 02/36] Issue #39 - Add .asf.yaml for asf-site (#106) Signed-off-by: Martin Tzvetanov Grigorov Co-authored-by: Sutou Kouhei --- .asf.yaml | 34 ++++++++++++++++++++++++++++++++++ 1 file changed, 34 insertions(+) create mode 100644 .asf.yaml diff --git a/.asf.yaml b/.asf.yaml new file mode 100644 index 000000000..0e22a5e81 --- /dev/null +++ b/.asf.yaml @@ -0,0 +1,34 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +notifications: + commits: commits@arrow.apache.org + issues_status: issues@arrow.apache.org + issues_comment: github@arrow.apache.org + pullrequests: github@arrow.apache.org +github: + description: "Apache Arrow DataFusion Python Bindings" + homepage: https://arrow.apache.org/datafusion-python/ + enabled_merge_buttons: + squash: true + merge: false + rebase: false + features: + issues: true +publish: + whoami: asf-site + subdir: datafusion-python From cb9db9f003f6a607851ff637c83dd12f1b5e3da6 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Fri, 14 Apr 2023 16:35:54 +0000 Subject: [PATCH 03/36] Publish built docs triggered by 5c90187207e218393297ff3cbe4f08b69049d224 --- .asf.yaml | 11 +- _sources/api/expression.rst.txt | 4 +- .../generated/datafusion.DataFrame.rst.txt | 10 + _sources/generated/datafusion.Expr.rst.txt | 31 + .../generated/datafusion.Expression.rst.txt | 28 - .../datafusion.SessionContext.rst.txt | 7 + _static/doctools.js | 130 +- _static/pygments.css | 1 + _static/searchtools.js | 74 +- _static/sphinx_highlight.js | 144 ++ api.html | 17 +- api/config.html | 13 +- api/dataframe.html | 13 +- api/execution_context.html | 13 +- api/expression.html | 29 +- api/functions.html | 19 +- api/object_store.html | 13 +- generated/datafusion.Config.html | 88 +- generated/datafusion.DataFrame.html | 539 ++++++- ...n.Expression.html => datafusion.Expr.html} | 205 ++- generated/datafusion.SessionContext.html | 437 +++++- generated/datafusion.functions.functions.html | 1347 ++++++++++++++++- .../datafusion.object_store.object_store.html | 56 +- genindex.html | 199 ++- index.html | 45 +- objects.inv | Bin 1456 -> 1819 bytes py-modindex.html | 9 +- search.html | 9 +- searchindex.js | 2 +- 29 files changed, 2976 insertions(+), 517 deletions(-) create mode 100644 _sources/generated/datafusion.Expr.rst.txt delete mode 100644 _sources/generated/datafusion.Expression.rst.txt create mode 100644 _static/sphinx_highlight.js rename generated/{datafusion.Expression.html => datafusion.Expr.html} (52%) diff --git a/.asf.yaml b/.asf.yaml index 0e22a5e81..f27975c84 100644 --- a/.asf.yaml +++ b/.asf.yaml @@ -17,18 +17,23 @@ notifications: commits: commits@arrow.apache.org - issues_status: issues@arrow.apache.org - issues_comment: github@arrow.apache.org + issues: github@arrow.apache.org pullrequests: github@arrow.apache.org + jira_options: link label worklog github: description: "Apache Arrow DataFusion Python Bindings" - homepage: https://arrow.apache.org/datafusion-python/ + homepage: https://arrow.apache.org/datafusion enabled_merge_buttons: squash: true merge: false rebase: false features: issues: true + +staging: + whoami: asf-staging + subdir: datafusion-python + publish: whoami: asf-site subdir: datafusion-python diff --git a/_sources/api/expression.rst.txt b/_sources/api/expression.rst.txt index 45923fb54..30137d135 100644 --- a/_sources/api/expression.rst.txt +++ b/_sources/api/expression.rst.txt @@ -18,10 +18,10 @@ .. _api.expression: .. currentmodule:: datafusion -Expression +Expr ========== .. autosummary:: :toctree: ../generated/ - Expression + Expr diff --git a/_sources/generated/datafusion.DataFrame.rst.txt b/_sources/generated/datafusion.DataFrame.rst.txt index e0ddc8651..aa70c2825 100644 --- a/_sources/generated/datafusion.DataFrame.rst.txt +++ b/_sources/generated/datafusion.DataFrame.rst.txt @@ -18,13 +18,18 @@ ~DataFrame.cache ~DataFrame.collect ~DataFrame.collect_partitioned + ~DataFrame.count + ~DataFrame.describe ~DataFrame.distinct ~DataFrame.except_all + ~DataFrame.execution_plan ~DataFrame.explain ~DataFrame.filter ~DataFrame.intersect ~DataFrame.join ~DataFrame.limit + ~DataFrame.logical_plan + ~DataFrame.optimized_logical_plan ~DataFrame.repartition ~DataFrame.repartition_by_hash ~DataFrame.schema @@ -32,6 +37,11 @@ ~DataFrame.select_columns ~DataFrame.show ~DataFrame.sort + ~DataFrame.to_arrow_table + ~DataFrame.to_pandas + ~DataFrame.to_polars + ~DataFrame.to_pydict + ~DataFrame.to_pylist ~DataFrame.union ~DataFrame.union_distinct ~DataFrame.with_column diff --git a/_sources/generated/datafusion.Expr.rst.txt b/_sources/generated/datafusion.Expr.rst.txt new file mode 100644 index 000000000..955ee039a --- /dev/null +++ b/_sources/generated/datafusion.Expr.rst.txt @@ -0,0 +1,31 @@ +datafusion.Expr +=============== + +.. currentmodule:: datafusion + +.. autoclass:: Expr + + + .. automethod:: __init__ + + + .. rubric:: Methods + + .. autosummary:: + + ~Expr.__init__ + ~Expr.alias + ~Expr.canonical_name + ~Expr.cast + ~Expr.column + ~Expr.display_name + ~Expr.is_null + ~Expr.literal + ~Expr.sort + ~Expr.to_variant + + + + + + \ No newline at end of file diff --git a/_sources/generated/datafusion.Expression.rst.txt b/_sources/generated/datafusion.Expression.rst.txt deleted file mode 100644 index 92e9b4c5d..000000000 --- a/_sources/generated/datafusion.Expression.rst.txt +++ /dev/null @@ -1,28 +0,0 @@ -datafusion.Expression -===================== - -.. currentmodule:: datafusion - -.. autoclass:: Expression - - - .. automethod:: __init__ - - - .. rubric:: Methods - - .. autosummary:: - - ~Expression.__init__ - ~Expression.alias - ~Expression.cast - ~Expression.column - ~Expression.is_null - ~Expression.literal - ~Expression.sort - - - - - - \ No newline at end of file diff --git a/_sources/generated/datafusion.SessionContext.rst.txt b/_sources/generated/datafusion.SessionContext.rst.txt index 965f8b8fc..8ef3db621 100644 --- a/_sources/generated/datafusion.SessionContext.rst.txt +++ b/_sources/generated/datafusion.SessionContext.rst.txt @@ -16,8 +16,15 @@ ~SessionContext.__init__ ~SessionContext.catalog ~SessionContext.create_dataframe + ~SessionContext.create_dataframe_from_logical_plan ~SessionContext.deregister_table ~SessionContext.empty_table + ~SessionContext.execute + ~SessionContext.from_arrow_table + ~SessionContext.from_pandas + ~SessionContext.from_polars + ~SessionContext.from_pydict + ~SessionContext.from_pylist ~SessionContext.read_avro ~SessionContext.read_csv ~SessionContext.read_json diff --git a/_static/doctools.js b/_static/doctools.js index c3db08d1c..527b876ca 100644 --- a/_static/doctools.js +++ b/_static/doctools.js @@ -10,6 +10,13 @@ */ "use strict"; +const BLACKLISTED_KEY_CONTROL_ELEMENTS = new Set([ + "TEXTAREA", + "INPUT", + "SELECT", + "BUTTON", +]); + const _ready = (callback) => { if (document.readyState !== "loading") { callback(); @@ -18,73 +25,11 @@ const _ready = (callback) => { } }; -/** - * highlight a given string on a node by wrapping it in - * span elements with the given class name. - */ -const _highlight = (node, addItems, text, className) => { - if (node.nodeType === Node.TEXT_NODE) { - const val = node.nodeValue; - const parent = node.parentNode; - const pos = val.toLowerCase().indexOf(text); - if ( - pos >= 0 && - !parent.classList.contains(className) && - !parent.classList.contains("nohighlight") - ) { - let span; - - const closestNode = parent.closest("body, svg, foreignObject"); - const isInSVG = closestNode && closestNode.matches("svg"); - if (isInSVG) { - span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); - } else { - span = document.createElement("span"); - span.classList.add(className); - } - - span.appendChild(document.createTextNode(val.substr(pos, text.length))); - parent.insertBefore( - span, - parent.insertBefore( - document.createTextNode(val.substr(pos + text.length)), - node.nextSibling - ) - ); - node.nodeValue = val.substr(0, pos); - - if (isInSVG) { - const rect = document.createElementNS( - "http://www.w3.org/2000/svg", - "rect" - ); - const bbox = parent.getBBox(); - rect.x.baseVal.value = bbox.x; - rect.y.baseVal.value = bbox.y; - rect.width.baseVal.value = bbox.width; - rect.height.baseVal.value = bbox.height; - rect.setAttribute("class", className); - addItems.push({ parent: parent, target: rect }); - } - } - } else if (node.matches && !node.matches("button, select, textarea")) { - node.childNodes.forEach((el) => _highlight(el, addItems, text, className)); - } -}; -const _highlightText = (thisNode, text, className) => { - let addItems = []; - _highlight(thisNode, addItems, text, className); - addItems.forEach((obj) => - obj.parent.insertAdjacentElement("beforebegin", obj.target) - ); -}; - /** * Small JavaScript module for the documentation. */ const Documentation = { init: () => { - Documentation.highlightSearchWords(); Documentation.initDomainIndexTable(); Documentation.initOnKeyListeners(); }, @@ -126,51 +71,6 @@ const Documentation = { Documentation.LOCALE = catalog.locale; }, - /** - * highlight the search words provided in the url in the text - */ - highlightSearchWords: () => { - const highlight = - new URLSearchParams(window.location.search).get("highlight") || ""; - const terms = highlight.toLowerCase().split(/\s+/).filter(x => x); - if (terms.length === 0) return; // nothing to do - - // There should never be more than one element matching "div.body" - const divBody = document.querySelectorAll("div.body"); - const body = divBody.length ? divBody[0] : document.querySelector("body"); - window.setTimeout(() => { - terms.forEach((term) => _highlightText(body, term, "highlighted")); - }, 10); - - const searchBox = document.getElementById("searchbox"); - if (searchBox === null) return; - searchBox.appendChild( - document - .createRange() - .createContextualFragment( - '

' + - '' + - Documentation.gettext("Hide Search Matches") + - "

" - ) - ); - }, - - /** - * helper function to hide the search marks again - */ - hideSearchWords: () => { - document - .querySelectorAll("#searchbox .highlight-link") - .forEach((el) => el.remove()); - document - .querySelectorAll("span.highlighted") - .forEach((el) => el.classList.remove("highlighted")); - const url = new URL(window.location); - url.searchParams.delete("highlight"); - window.history.replaceState({}, "", url); - }, - /** * helper function to focus on search bar */ @@ -210,15 +110,11 @@ const Documentation = { ) return; - const blacklistedElements = new Set([ - "TEXTAREA", - "INPUT", - "SELECT", - "BUTTON", - ]); document.addEventListener("keydown", (event) => { - if (blacklistedElements.has(document.activeElement.tagName)) return; // bail for input elements - if (event.altKey || event.ctrlKey || event.metaKey) return; // bail with special keys + // bail for input elements + if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; + // bail with special keys + if (event.altKey || event.ctrlKey || event.metaKey) return; if (!event.shiftKey) { switch (event.key) { @@ -240,10 +136,6 @@ const Documentation = { event.preventDefault(); } break; - case "Escape": - if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) break; - Documentation.hideSearchWords(); - event.preventDefault(); } } diff --git a/_static/pygments.css b/_static/pygments.css index c5d3a660a..f227e5c6e 100644 --- a/_static/pygments.css +++ b/_static/pygments.css @@ -54,6 +54,7 @@ span.linenos.special { color: #000000; background-color: #ffffc0; padding-left: .highlight .nt { color: #204a87; font-weight: bold } /* Name.Tag */ .highlight .nv { color: #000000 } /* Name.Variable */ .highlight .ow { color: #204a87; font-weight: bold } /* Operator.Word */ +.highlight .pm { color: #000000; font-weight: bold } /* Punctuation.Marker */ .highlight .w { color: #f8f8f8 } /* Text.Whitespace */ .highlight .mb { color: #0000cf; font-weight: bold } /* Literal.Number.Bin */ .highlight .mf { color: #0000cf; font-weight: bold } /* Literal.Number.Float */ diff --git a/_static/searchtools.js b/_static/searchtools.js index f2fb7d5cf..e89e34d4e 100644 --- a/_static/searchtools.js +++ b/_static/searchtools.js @@ -57,14 +57,14 @@ const _removeChildren = (element) => { const _escapeRegExp = (string) => string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string -const _displayItem = (item, highlightTerms, searchTerms) => { +const _displayItem = (item, searchTerms) => { const docBuilder = DOCUMENTATION_OPTIONS.BUILDER; const docUrlRoot = DOCUMENTATION_OPTIONS.URL_ROOT; const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX; const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX; const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY; - const [docName, title, anchor, descr] = item; + const [docName, title, anchor, descr, score, _filename] = item; let listItem = document.createElement("li"); let requestUrl; @@ -82,10 +82,9 @@ const _displayItem = (item, highlightTerms, searchTerms) => { requestUrl = docUrlRoot + docName + docFileSuffix; linkUrl = docName + docLinkSuffix; } - const params = new URLSearchParams(); - params.set("highlight", [...highlightTerms].join(" ")); let linkEl = listItem.appendChild(document.createElement("a")); - linkEl.href = linkUrl + "?" + params.toString() + anchor; + linkEl.href = linkUrl + anchor; + linkEl.dataset.score = score; linkEl.innerHTML = title; if (descr) listItem.appendChild(document.createElement("span")).innerHTML = @@ -96,7 +95,7 @@ const _displayItem = (item, highlightTerms, searchTerms) => { .then((data) => { if (data) listItem.appendChild( - Search.makeSearchSummary(data, searchTerms, highlightTerms) + Search.makeSearchSummary(data, searchTerms) ); }); Search.output.appendChild(listItem); @@ -116,15 +115,14 @@ const _finishSearch = (resultCount) => { const _displayNextItem = ( results, resultCount, - highlightTerms, searchTerms ) => { // results left, load the summary and display it // this is intended to be dynamic (don't sub resultsCount) if (results.length) { - _displayItem(results.pop(), highlightTerms, searchTerms); + _displayItem(results.pop(), searchTerms); setTimeout( - () => _displayNextItem(results, resultCount, highlightTerms, searchTerms), + () => _displayNextItem(results, resultCount, searchTerms), 5 ); } @@ -237,6 +235,12 @@ const Search = { * execute search (requires search index to be loaded) */ query: (query) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + const allTitles = Search._index.alltitles; + const indexEntries = Search._index.indexentries; + // stem the search terms and add them to the correct list const stemmer = new Stemmer(); const searchTerms = new Set(); @@ -264,6 +268,10 @@ const Search = { } }); + if (SPHINX_HIGHLIGHT_ENABLED) { // set in sphinx_highlight.js + localStorage.setItem("sphinx_highlight_terms", [...highlightTerms].join(" ")) + } + // console.debug("SEARCH: searching for:"); // console.info("required: ", [...searchTerms]); // console.info("excluded: ", [...excludedTerms]); @@ -272,6 +280,40 @@ const Search = { let results = []; _removeChildren(document.getElementById("search-progress")); + const queryLower = query.toLowerCase(); + for (const [title, foundTitles] of Object.entries(allTitles)) { + if (title.toLowerCase().includes(queryLower) && (queryLower.length >= title.length/2)) { + for (const [file, id] of foundTitles) { + let score = Math.round(100 * queryLower.length / title.length) + results.push([ + docNames[file], + titles[file] !== title ? `${titles[file]} > ${title}` : title, + id !== null ? "#" + id : "", + null, + score, + filenames[file], + ]); + } + } + } + + // search for explicit entries in index directives + for (const [entry, foundEntries] of Object.entries(indexEntries)) { + if (entry.includes(queryLower) && (queryLower.length >= entry.length/2)) { + for (const [file, id] of foundEntries) { + let score = Math.round(100 * queryLower.length / entry.length) + results.push([ + docNames[file], + titles[file], + id ? "#" + id : "", + null, + score, + filenames[file], + ]); + } + } + } + // lookup as object objectTerms.forEach((term) => results.push(...Search.performObjectSearch(term, objectTerms)) @@ -318,7 +360,7 @@ const Search = { // console.info("search results:", Search.lastresults); // print the results - _displayNextItem(results, results.length, highlightTerms, searchTerms); + _displayNextItem(results, results.length, searchTerms); }, /** @@ -399,8 +441,8 @@ const Search = { // prepare search const terms = Search._index.terms; const titleTerms = Search._index.titleterms; - const docNames = Search._index.docnames; const filenames = Search._index.filenames; + const docNames = Search._index.docnames; const titles = Search._index.titles; const scoreMap = new Map(); @@ -497,11 +539,9 @@ const Search = { /** * helper function to return a node containing the * search summary for a given text. keywords is a list - * of stemmed words, highlightWords is the list of normal, unstemmed - * words. the first one is used to find the occurrence, the - * latter for highlighting it. + * of stemmed words. */ - makeSearchSummary: (htmlText, keywords, highlightWords) => { + makeSearchSummary: (htmlText, keywords) => { const text = Search.htmlToText(htmlText); if (text === "") return null; @@ -519,10 +559,6 @@ const Search = { summary.classList.add("context"); summary.textContent = top + text.substr(startWithContext, 240).trim() + tail; - highlightWords.forEach((highlightWord) => - _highlightText(summary, highlightWord, "highlighted") - ); - return summary; }, }; diff --git a/_static/sphinx_highlight.js b/_static/sphinx_highlight.js new file mode 100644 index 000000000..aae669d7e --- /dev/null +++ b/_static/sphinx_highlight.js @@ -0,0 +1,144 @@ +/* Highlighting utilities for Sphinx HTML documentation. */ +"use strict"; + +const SPHINX_HIGHLIGHT_ENABLED = true + +/** + * highlight a given string on a node by wrapping it in + * span elements with the given class name. + */ +const _highlight = (node, addItems, text, className) => { + if (node.nodeType === Node.TEXT_NODE) { + const val = node.nodeValue; + const parent = node.parentNode; + const pos = val.toLowerCase().indexOf(text); + if ( + pos >= 0 && + !parent.classList.contains(className) && + !parent.classList.contains("nohighlight") + ) { + let span; + + const closestNode = parent.closest("body, svg, foreignObject"); + const isInSVG = closestNode && closestNode.matches("svg"); + if (isInSVG) { + span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); + } else { + span = document.createElement("span"); + span.classList.add(className); + } + + span.appendChild(document.createTextNode(val.substr(pos, text.length))); + parent.insertBefore( + span, + parent.insertBefore( + document.createTextNode(val.substr(pos + text.length)), + node.nextSibling + ) + ); + node.nodeValue = val.substr(0, pos); + + if (isInSVG) { + const rect = document.createElementNS( + "http://www.w3.org/2000/svg", + "rect" + ); + const bbox = parent.getBBox(); + rect.x.baseVal.value = bbox.x; + rect.y.baseVal.value = bbox.y; + rect.width.baseVal.value = bbox.width; + rect.height.baseVal.value = bbox.height; + rect.setAttribute("class", className); + addItems.push({ parent: parent, target: rect }); + } + } + } else if (node.matches && !node.matches("button, select, textarea")) { + node.childNodes.forEach((el) => _highlight(el, addItems, text, className)); + } +}; +const _highlightText = (thisNode, text, className) => { + let addItems = []; + _highlight(thisNode, addItems, text, className); + addItems.forEach((obj) => + obj.parent.insertAdjacentElement("beforebegin", obj.target) + ); +}; + +/** + * Small JavaScript module for the documentation. + */ +const SphinxHighlight = { + + /** + * highlight the search words provided in localstorage in the text + */ + highlightSearchWords: () => { + if (!SPHINX_HIGHLIGHT_ENABLED) return; // bail if no highlight + + // get and clear terms from localstorage + const url = new URL(window.location); + const highlight = + localStorage.getItem("sphinx_highlight_terms") + || url.searchParams.get("highlight") + || ""; + localStorage.removeItem("sphinx_highlight_terms") + url.searchParams.delete("highlight"); + window.history.replaceState({}, "", url); + + // get individual terms from highlight string + const terms = highlight.toLowerCase().split(/\s+/).filter(x => x); + if (terms.length === 0) return; // nothing to do + + // There should never be more than one element matching "div.body" + const divBody = document.querySelectorAll("div.body"); + const body = divBody.length ? divBody[0] : document.querySelector("body"); + window.setTimeout(() => { + terms.forEach((term) => _highlightText(body, term, "highlighted")); + }, 10); + + const searchBox = document.getElementById("searchbox"); + if (searchBox === null) return; + searchBox.appendChild( + document + .createRange() + .createContextualFragment( + '

' + + '' + + _("Hide Search Matches") + + "

" + ) + ); + }, + + /** + * helper function to hide the search marks again + */ + hideSearchWords: () => { + document + .querySelectorAll("#searchbox .highlight-link") + .forEach((el) => el.remove()); + document + .querySelectorAll("span.highlighted") + .forEach((el) => el.classList.remove("highlighted")); + localStorage.removeItem("sphinx_highlight_terms") + }, + + initEscapeListener: () => { + // only install a listener if it is really needed + if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return; + + document.addEventListener("keydown", (event) => { + // bail for input elements + if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; + // bail with special keys + if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return; + if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) { + SphinxHighlight.hideSearchWords(); + event.preventDefault(); + } + }); + }, +}; + +_ready(SphinxHighlight.highlightSearchWords); +_ready(SphinxHighlight.initEscapeListener); diff --git a/api.html b/api.html index c47e4600f..2905f0b2b 100644 --- a/api.html +++ b/api.html @@ -4,7 +4,7 @@ - + API Reference — Arrow DataFusion documentation @@ -34,6 +34,7 @@ + @@ -135,7 +136,7 @@
  • - Expression + Expr @@ -214,7 +215,7 @@
    - + Edit this page
    @@ -249,8 +250,8 @@
  • datafusion.SessionContext
    • -
  • Expression
    • +
  • + + datafusion.io + +
  • datafusion.object_store @@ -450,13 +465,13 @@

    Module Contents
    -abstract build_table(input_item: Any, table_name: str, **kwarg) → datafusion.common.SqlTable
    +abstract build_table(input_item: Any, table_name: str, **kwarg: Any) → datafusion.common.SqlTable

    Create a table from the input source.

    -abstract is_correct_input(input_item: Any, table_name: str, **kwargs) → bool
    +abstract is_correct_input(input_item: Any, table_name: str, **kwargs: Any) → bool

    Returns True if the input is valid.

    diff --git a/autoapi/datafusion/input/index.html b/autoapi/datafusion/input/index.html index 896164da6..1f368148a 100644 --- a/autoapi/datafusion/input/index.html +++ b/autoapi/datafusion/input/index.html @@ -127,6 +127,11 @@

    @@ -307,6 +317,11 @@

    • +
  • + + datafusion.io + +
  • datafusion.object_store @@ -365,6 +380,47 @@ Submodules
    • +
  • + + Classes + +
    • +
  • + + Package Contents + + +
    • @@ -398,6 +454,39 @@

    Submodulesdatafusion.input.location + +
    +

    Classes

    + + + + + + +

    LocationInputPlugin

    Input Plugin for everything.

    +
    +
    +

    Package Contents

    +
    +
    +class datafusion.input.LocationInputPlugin
    +

    Bases: datafusion.input.base.BaseInputSource

    +

    Input Plugin for everything.

    +

    This can be read in from a file (on disk, remote etc.).

    +
    +
    +build_table(input_item: str, table_name: str, **kwargs: Any) → datafusion.common.SqlTable
    +

    Create a table from the input source.

    +
    + +
    +
    +is_correct_input(input_item: Any, table_name: str, **kwargs: Any) → bool
    +

    Returns True if the input is valid.

    +
    + +
    +
    diff --git a/autoapi/datafusion/input/location/index.html b/autoapi/datafusion/input/location/index.html index 9d4668215..2be427480 100644 --- a/autoapi/datafusion/input/location/index.html +++ b/autoapi/datafusion/input/location/index.html @@ -34,7 +34,7 @@ - + @@ -127,6 +127,11 @@

    @@ -307,6 +317,11 @@ +

  • + + datafusion.io + +
  • datafusion.object_store @@ -445,13 +460,13 @@

    Module Contents
    -build_table(input_file: str, table_name: str, **kwargs) → datafusion.common.SqlTable
    +build_table(input_item: str, table_name: str, **kwargs: Any) → datafusion.common.SqlTable

    Create a table from the input source.

    -is_correct_input(input_item: Any, table_name: str, **kwargs)
    +is_correct_input(input_item: Any, table_name: str, **kwargs: Any) → bool

    Returns True if the input is valid.

    @@ -473,10 +488,10 @@

    Module Contentsdatafusion.input.base

     - +

    next

    -

    datafusion.object_store

    +

    datafusion.io

     diff --git a/autoapi/datafusion/io/index.html b/autoapi/datafusion/io/index.html new file mode 100644 index 000000000..3ce943551 --- /dev/null +++ b/autoapi/datafusion/io/index.html @@ -0,0 +1,639 @@ + + + + + + + + datafusion.io — Apache Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + +
    +
    + + + + +
    + + +
    + + +
    +
    +
    +
    + + + + +
    + + +
    + +
    + On this page +
    + + +
    + +
    + +
    + + +
    + + + + + + +
    + +
    + +
    +

    datafusion.io

    +

    IO read functions using global context.

    +
    +

    Functions

    + + + + + + + + + + + + + + + +

    read_avro(→ datafusion.dataframe.DataFrame)

    Create a DataFrame for reading Avro data source.

    read_csv(→ datafusion.dataframe.DataFrame)

    Read a CSV data source.

    read_json(→ datafusion.dataframe.DataFrame)

    Read a line-delimited JSON data source.

    read_parquet(→ datafusion.dataframe.DataFrame)

    Read a Parquet source into a Dataframe.

    +
    +
    +

    Module Contents

    +
    +
    +datafusion.io.read_avro(path: str | pathlib.Path, schema: pyarrow.Schema | None = None, file_partition_cols: list[tuple[str, str]] | None = None, file_extension: str = '.avro') → datafusion.dataframe.DataFrame
    +

    Create a DataFrame for reading Avro data source.

    +

    This function will use the global context. Any functions or tables registered +with another context may not be accessible when used with a DataFrame created +using this function.

    +
    +
    Parameters:
    +
      +

    • path – Path to the Avro file.

      • +

    • schema – The data source schema.

      • +

    • file_partition_cols – Partition columns.

      • +

    • file_extension – File extension to select.

      • +
    +
    +
    Returns:
    +

    DataFrame representation of the read Avro file

    +
    +
    +
    + +
    +
    +datafusion.io.read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str]] | None = None, file_compression_type: str | None = None) → datafusion.dataframe.DataFrame
    +

    Read a CSV data source.

    +

    This function will use the global context. Any functions or tables registered +with another context may not be accessible when used with a DataFrame created +using this function.

    +
    +
    Parameters:
    +
      +

    • path – Path to the CSV file

      • +

    • schema – An optional schema representing the CSV files. If None, the +CSV reader will try to infer it based on data in file.

      • +

    • has_header – Whether the CSV file have a header. If schema inference +is run on a file with no headers, default column names are +created.

      • +

    • delimiter – An optional column delimiter.

      • +

    • schema_infer_max_records – Maximum number of rows to read from CSV +files for schema inference if needed.

      • +

    • file_extension – File extension; only files with this extension are +selected for data input.

      • +

    • table_partition_cols – Partition columns.

      • +

    • file_compression_type – File compression type.

      • +
    +
    +
    Returns:
    +

    DataFrame representation of the read CSV files

    +
    +
    +
    + +
    +
    +datafusion.io.read_json(path: str | pathlib.Path, schema: pyarrow.Schema | None = None, schema_infer_max_records: int = 1000, file_extension: str = '.json', table_partition_cols: list[tuple[str, str]] | None = None, file_compression_type: str | None = None) → datafusion.dataframe.DataFrame
    +

    Read a line-delimited JSON data source.

    +

    This function will use the global context. Any functions or tables registered +with another context may not be accessible when used with a DataFrame created +using this function.

    +
    +
    Parameters:
    +
      +

    • path – Path to the JSON file.

      • +

    • schema – The data source schema.

      • +

    • schema_infer_max_records – Maximum number of rows to read from JSON +files for schema inference if needed.

      • +

    • file_extension – File extension; only files with this extension are +selected for data input.

      • +

    • table_partition_cols – Partition columns.

      • +

    • file_compression_type – File compression type.

      • +
    +
    +
    Returns:
    +

    DataFrame representation of the read JSON files.

    +
    +
    +
    + +
    +
    +datafusion.io.read_parquet(path: str | pathlib.Path, table_partition_cols: list[tuple[str, str]] | None = None, parquet_pruning: bool = True, file_extension: str = '.parquet', skip_metadata: bool = True, schema: pyarrow.Schema | None = None, file_sort_order: list[list[datafusion.expr.Expr]] | None = None) → datafusion.dataframe.DataFrame
    +

    Read a Parquet source into a Dataframe.

    +

    This function will use the global context. Any functions or tables registered +with another context may not be accessible when used with a DataFrame created +using this function.

    +
    +
    Parameters:
    +
      +

    • path – Path to the Parquet file.

      • +

    • table_partition_cols – Partition columns.

      • +

    • parquet_pruning – Whether the parquet reader should use the predicate +to prune row groups.

      • +

    • file_extension – File extension; only files with this extension are +selected for data input.

      • +

    • skip_metadata – Whether the parquet reader should skip any metadata +that may be in the file schema. This can help avoid schema +conflicts due to metadata.

      • +

    • schema – An optional schema representing the parquet files. If None, +the parquet reader will try to infer it based on data in the +file.

      • +

    • file_sort_order – Sort order for the file.

      • +
    +
    +
    Returns:
    +

    DataFrame representation of the read Parquet files

    +
    +
    +
    + +
    +
    + + +
    + + + +
    + + +
    +

    previous

    +

    datafusion.input.location

    +
    +     + +
    +

    next

    +

    datafusion.object_store

    +
    + +     +
    + +
    + + +
    +
    + + + + +
    +
    + +
    +

    + © Copyright 2019-2024, Apache Software Foundation.
    +

    +
    + +
    +

    +Created using Sphinx 8.1.3.
    +

    +
    + +
    +

    Apache Arrow DataFusion, Arrow DataFusion, Apache, the Apache feather logo, and the Apache Arrow DataFusion project logo

    +

    are either registered trademarks or trademarks of The Apache Software Foundation in the United States and other countries.

    +
    +
    +
    + + + + \ No newline at end of file diff --git a/autoapi/datafusion/object_store/index.html b/autoapi/datafusion/object_store/index.html index 71ad4a83f..b27718f02 100644 --- a/autoapi/datafusion/object_store/index.html +++ b/autoapi/datafusion/object_store/index.html @@ -35,7 +35,7 @@ - + @@ -127,6 +127,11 @@

    @@ -307,6 +317,11 @@

    • +
  • + + datafusion.io + +
  • datafusion.object_store @@ -499,11 +514,11 @@

    Module Contents +

    previous

    -

    datafusion.input.location

    +

    datafusion.io

     diff --git a/autoapi/datafusion/plan/index.html b/autoapi/datafusion/plan/index.html index ddf72b353..df79d85d4 100644 --- a/autoapi/datafusion/plan/index.html +++ b/autoapi/datafusion/plan/index.html @@ -127,6 +127,11 @@

    @@ -307,6 +317,11 @@

    • +
  • + + datafusion.io + +
  • datafusion.object_store @@ -608,7 +623,7 @@

    Module Contents
    -children() → List[ExecutionPlan]
    +children() → list[ExecutionPlan]

    Get a list of children ExecutionPlan that act as inputs to this plan.

    The returned list will be empty for leaf nodes such as scans, will contain a single value for unary nodes, or two values for binary nodes (such as joins).

    @@ -707,7 +722,7 @@

    Module Contents
    -inputs() → List[LogicalPlan]
    +inputs() → list[LogicalPlan]

    Returns the list of inputs to the logical plan.

    diff --git a/autoapi/datafusion/record_batch/index.html b/autoapi/datafusion/record_batch/index.html index f322281dc..edeb5af68 100644 --- a/autoapi/datafusion/record_batch/index.html +++ b/autoapi/datafusion/record_batch/index.html @@ -127,6 +127,11 @@

    @@ -307,6 +317,11 @@

    • +
  • + + datafusion.io + +
  • datafusion.object_store @@ -497,7 +512,7 @@

    Classes¶ - + @@ -510,13 +525,13 @@

    Module Contents
    class datafusion.record_batch.RecordBatch(record_batch: datafusion._internal.RecordBatch)
    -

    This class is essentially a wrapper for pyarrow.RecordBatch.

    +

    This class is essentially a wrapper for pa.RecordBatch.

    This constructor is generally not called by the end user.

    See the RecordBatchStream iterator for generating this class.

    to_pyarrow() → pyarrow.RecordBatch
    -

    Convert to pyarrow.RecordBatch.

    +

    Convert to pa.RecordBatch.

    diff --git a/autoapi/datafusion/substrait/index.html b/autoapi/datafusion/substrait/index.html index 9b71cde55..87028dab2 100644 --- a/autoapi/datafusion/substrait/index.html +++ b/autoapi/datafusion/substrait/index.html @@ -127,6 +127,11 @@

    @@ -307,6 +317,11 @@ +

  • + + datafusion.io + +
  • datafusion.object_store diff --git a/autoapi/datafusion/udf/index.html b/autoapi/datafusion/udf/index.html index 5452e5911..9f0f67409 100644 --- a/autoapi/datafusion/udf/index.html +++ b/autoapi/datafusion/udf/index.html @@ -126,6 +126,11 @@

    @@ -306,6 +316,11 @@

    • +
  • + + datafusion.io + +
  • datafusion.object_store @@ -654,6 +669,42 @@
    • +
  • + + + + WindowUDF._create_window_udf() + + + +
    • +
  • + + + + WindowUDF._create_window_udf_decorator() + + + +
    • +
  • + + + + WindowUDF._get_default_name() + + + +
    • +
  • + + + + WindowUDF._normalize_input_types() + + + +
  • @@ -684,10 +735,28 @@
  • - + + + + udaf + + + +
    • +
  • + + + + udf + + + +
    • +
  • + - _W + udwf @@ -725,7 +794,13 @@

    Attributes

    • - + + + + + + + @@ -770,13 +845,13 @@

    Module Contents
    -abstract merge(states: List[pyarrow.Array]) → None
    +abstract merge(states: list[pyarrow.Array]) → None

    Merge a set of states.

    -abstract state() → List[pyarrow.Scalar]
    +abstract state() → list[pyarrow.Scalar]

    Return the current state.

    @@ -790,12 +865,12 @@

    Module Contents
    -class datafusion.udf.AggregateUDF(name: str | None, accumulator: Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str)
    +class datafusion.udf.AggregateUDF(name: str, accumulator: Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str)

    Class for performing scalar user-defined functions (UDF).

    Aggregate UDFs operate on a group of rows and return a single value. See also ScalarUDF for operating on a row by row basis.

    Instantiate a user-defined aggregate function (UDAF).

    -

    See udaf() for a convenience function and argument +

    See udaf() for a convenience function and argument descriptions.

    @@ -807,44 +882,78 @@

    Module Contents
    -static udaf(accum: Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → AggregateUDF
    -

    Create a new User-Defined Aggregate Function.

    -

    If your Accumulator can be instantiated with no arguments, you -can simply pass it’s type as accum. If you need to pass additional arguments -to it’s constructor, you can define a lambda or a factory method. During runtime -the Accumulator will be constructed for every instance in -which this UDAF is used. The following examples are all valid.

    -
    import pyarrow as pa
-import pyarrow.compute as pc
-
-class Summarize(Accumulator):
-    def __init__(self, bias: float = 0.0):
-        self._sum = pa.scalar(bias)
-
-    def state(self) -> List[pa.Scalar]:
-        return [self._sum]
-
-    def update(self, values: pa.Array) -> None:
-        self._sum = pa.scalar(self._sum.as_py() + pc.sum(values).as_py())
-
-    def merge(self, states: List[pa.Array]) -> None:
-        self._sum = pa.scalar(self._sum.as_py() + pc.sum(states[0]).as_py())
-
-    def evaluate(self) -> pa.Scalar:
-        return self._sum
-
-def sum_bias_10() -> Summarize:
-    return Summarize(10.0)
-
-udaf1 = udaf(Summarize, pa.float64(), pa.float64(), [pa.float64()], "immutable")
-udaf2 = udaf(sum_bias_10, pa.float64(), pa.float64(), [pa.float64()], "immutable")
-udaf3 = udaf(lambda: Summarize(20.0), pa.float64(), pa.float64(), [pa.float64()], "immutable")
-
    -
    +static udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, AggregateUDF]

    +
    +static udaf(accum: Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → AggregateUDF
    +

    Create a new User-Defined Aggregate Function (UDAF).

    +

    This class allows you to define an aggregate function that can be used in +data aggregation or window function calls.

    +
    +
    Usage:
      +
    • +
      As a function: Call `udaf(accum, input_types, return_type, state_type,

      volatility, name)`.

      +
      +
      +
      • +
    • +
      As a decorator: Use `@udaf(input_types, return_type, state_type,

      volatility, name)`.

      +
      +
      +
      • +
    +

    When using udaf as a decorator, do not pass `accum` explicitly.

    +
    +
    +

    Function example:

    +
    +

    If your :py:class:Accumulator can be instantiated with no arguments, you +can simply pass it’s type as accum. If you need to pass additional +arguments to it’s constructor, you can define a lambda or a factory method. +During runtime the :py:class:Accumulator will be constructed for every +instance in which this UDAF is used. The following examples are all valid. +``` +import pyarrow as pa +import pyarrow.compute as pc

    +
    +
    class Summarize(Accumulator):
    +
    def __init__(self, bias: float = 0.0):

    self._sum = pa.scalar(bias)

    +
    +
    def state(self) -> list[pa.Scalar]:

    return [self._sum]

    +
    +
    def update(self, values: pa.Array) -> None:

    self._sum = pa.scalar(self._sum.as_py() + pc.sum(values).as_py())

    +
    +
    def merge(self, states: list[pa.Array]) -> None:

    self._sum = pa.scalar(self._sum.as_py() + pc.sum(states[0]).as_py())

    +
    +
    def evaluate(self) -> pa.Scalar:

    return self._sum

    +
    +
    +
    +
    def sum_bias_10() -> Summarize:

    return Summarize(10.0)

    +
    +
    udaf1 = udaf(Summarize, pa.float64(), pa.float64(), [pa.float64()],

    “immutable”)

    +
    +
    udaf2 = udaf(sum_bias_10, pa.float64(), pa.float64(), [pa.float64()],

    “immutable”)

    +
    +
    udaf3 = udaf(lambda: Summarize(20.0), pa.float64(), pa.float64(),

    [pa.float64()], “immutable”)

    +
    +
    +

    ```

    +
    +
    +
    Decorator example:

    ``` +@udaf(pa.float64(), pa.float64(), [pa.float64()], “immutable”) +def udf4() -> Summarize:

    +
    +

    return Summarize(10.0)

    +
    +

    ```

    +
    +
    Parameters:
      -

    • accum – The accumulator python function.

      • +

    • accum – The accumulator python function. Only needed when calling as a +function. Skip this argument when using `udaf` as a decorator.

    • input_types – The data types of the arguments to accum.

    • return_type – The data type of the return value.

    • state_type – The data types of the intermediate accumulation.

      • @@ -868,12 +977,12 @@

      Module Contents
      -class datafusion.udf.ScalarUDF(name: str | None, func: Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)
      +class datafusion.udf.ScalarUDF(name: str, func: Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)

      Class for performing scalar user-defined functions (UDF).

      Scalar UDFs operate on a row by row basis. See also AggregateUDF for operating on a group of rows.

      Instantiate a scalar user-defined function (UDF).

      -

      See helper method udf() for argument details.

      +

      See helper method udf() for argument details.

      __call__(*args: datafusion.expr.Expr) → datafusion.expr.Expr
      @@ -884,28 +993,56 @@

      Module Contents
      -static udf(func: Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → ScalarUDF
      -

      Create a new User-Defined Function.

      +static udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, ScalarUDF] +
      +static udf(func: Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → ScalarUDF
      +

      Create a new User-Defined Function (UDF).

      +

      This class can be used both as a function and as a decorator.

      +
      +
      Usage:
        +

      • As a function: Call udf(func, input_types, return_type, volatility, +name).

        • +

      • As a decorator: Use @udf(input_types, return_type, volatility, +name). In this case, do not pass func explicitly.

        • +
      +
      +
      Parameters:
        -

      • func – A callable python function.

        • -

      • input_types – The data types of the arguments to func. This list -must be of the same length as the number of arguments.

        • -

      • return_type – The data type of the return value from the python -function.

        • -

      • volatility – See Volatility for allowed values.

        • -

      • name – A descriptive name for the function.

        • +

      • func (Callable, optional) – Only needed when calling as a function. +Skip this argument when using udf as a decorator.

        • +

      • input_types (list[pa.DataType]) – The data types of the arguments +to func. This list must be of the same length as the number of +arguments.

        • +

      • return_type (_R) – The data type of the return value from the function.

        • +

      • volatility (Volatility | str) – See Volatility for allowed values.

        • +

      • name (Optional[str]) – A descriptive name for the function.

      Returns:
      -

      -
      A user-defined aggregate function, which can be used in either data

      aggregation or window function calls.

      -
      -
      -

      +

      A user-defined function that can be used in SQL expressions, +data aggregation, or window function calls.

      +

      Example

      +

      Using `udf` as a function: +``` +def double_func(x):

      +
      +

      return x * 2

      +
      +

      double_udf = udf(double_func, [pa.int32()], pa.int32(), +“volatile”, “double_it”) +```

      +

      Using `udf` as a decorator: +``` +@udf([pa.int32()], pa.int32(), “volatile”, “double_it”) +def double_udf(x):

      +
      +

      return x * 2

      +
      +

      ```

      @@ -925,7 +1062,7 @@

      Module Contents
      -__str__()
      +__str__() → str

      Returns the string equivalent.

      @@ -1022,9 +1159,12 @@

      Module Contentsrow_number(), rank(), -dense_rank(), percent_rank(), -cume_dist(), lead(), +row_number(), +rank(), +dense_rank(), +percent_rank(), +cume_dist(), +lead(), and lag().

      It produces the result of all rows in a single pass. It expects to receive the entire partition as the value and @@ -1139,12 +1279,12 @@

      Module Contents
      -class datafusion.udf.WindowUDF(name: str | None, func: Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str)
      +class datafusion.udf.WindowUDF(name: str, func: Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str)

      Class for performing window user-defined functions (UDF).

      Window UDFs operate on a partition of rows. See also ScalarUDF for operating on a row by row basis.

      Instantiate a user-defined window function (UDWF).

      -

      See udwf() for a convenience function and argument +

      See udwf() for a convenience function and argument descriptions.

      @@ -1155,44 +1295,86 @@

      Module Contents -
      -static udwf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
      -

      Create a new User-Defined Window Function.

      -

      If your WindowEvaluator can be instantiated with no arguments, you -can simply pass it’s type as func. If you need to pass additional arguments -to it’s constructor, you can define a lambda or a factory method. During runtime -the WindowEvaluator will be constructed for every instance in -which this UDWF is used. The following examples are all valid.

      -
      import pyarrow as pa
+
      
+static _create_window_udf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
      
+
      Create a WindowUDF instance from function arguments.
      
+

      -class BiasedNumbers(WindowEvaluator): - def __init__(self, start: int = 0) -> None: - self.start = start +
      +
      +static _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → Callable[[Callable[[], WindowEvaluator]], Callable[Ellipsis, datafusion.expr.Expr]]
      +

      Create a decorator for a WindowUDF.

      +
      - def evaluate_all(self, values: list[pa.Array], num_rows: int) -> pa.Array: - return pa.array([self.start + i for i in range(num_rows)]) +
      +
      +static _get_default_name(func: Callable) → str
      +

      Get the default name for a function based on its attributes.

      +
      -def bias_10() -> BiasedNumbers: - return BiasedNumbers(10) +
      +
      +static _normalize_input_types(input_types: pyarrow.DataType | list[pyarrow.DataType]) → list[pyarrow.DataType]
      +

      Convert a single DataType to a list if needed.

      +
      -udwf1 = udwf(BiasedNumbers, pa.int64(), pa.int64(), "immutable") -udwf2 = udwf(bias_10, pa.int64(), pa.int64(), "immutable") -udwf3 = udwf(lambda: BiasedNumbers(20), pa.int64(), pa.int64(), "immutable") - - +
      +
      +static udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, WindowUDF]
      +
      +static udwf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
      +

      Create a new User-Defined Window Function (UDWF).

      +

      This class can be used both as a function and as a decorator.

      +
      +
      Usage:
        +

      • As a function: Call udwf(func, input_types, return_type, volatility, +name).

        • +

      • As a decorator: Use @udwf(input_types, return_type, volatility, +name). When using udwf as a decorator, do not pass `func` +explicitly.

        • +
      +
      +
      Function example:

      ``` +import pyarrow as pa

      +
      +
      class BiasedNumbers(WindowEvaluator):
      +
      def __init__(self, start: int = 0) -> None:

      self.start = start

      +
      +
      def evaluate_all(self, values: list[pa.Array],

      num_rows: int) -> pa.Array: +return pa.array([self.start + i for i in range(num_rows)])

      +
      +
      +
      +
      def bias_10() -> BiasedNumbers:

      return BiasedNumbers(10)

      +
      +
      +

      udwf1 = udwf(BiasedNumbers, pa.int64(), pa.int64(), “immutable”) +udwf2 = udwf(bias_10, pa.int64(), pa.int64(), “immutable”) +udwf3 = udwf(lambda: BiasedNumbers(20), pa.int64(), pa.int64(), “immutable”)

      +

      ```

      +
      +
      Decorator example:

      ``` +@udwf(pa.int64(), pa.int64(), “immutable”) +def biased_numbers() -> BiasedNumbers:

      +
      +

      return BiasedNumbers(10)

      +
      +

      ```

      +
      +
      Parameters:
        -

      • func – A callable to create the window function.

        • -

      • input_types – The data types of the arguments to func.

        • +

      • func – Only needed when calling as a function. Skip this argument when +using `udwf` as a decorator.

        • +

      • input_types – The data types of the arguments.

      • return_type – The data type of the return value.

      • volatility – See Volatility for allowed values.

        • -

      • arguments – A list of arguments to pass in to the __init__ method for accum.

      • name – A descriptive name for the function.

      Returns:
      -

      A user-defined window function.

      +

      A user-defined window function that can be used in window function calls.

      @@ -1210,8 +1392,18 @@

      Module Contents -
      -datafusion.udf._W
      +
      +datafusion.udf.udaf
      +

    + +
    +
    +datafusion.udf.udf
    +
    + +
    +
    +datafusion.udf.udwf
    diff --git a/autoapi/index.html b/autoapi/index.html index da449fcf0..40c2c4c10 100644 --- a/autoapi/index.html +++ b/autoapi/index.html @@ -35,7 +35,7 @@ - + @@ -127,6 +127,11 @@

    @@ -307,6 +317,11 @@ +

  • + + datafusion.io + +
  • datafusion.object_store @@ -392,6 +407,7 @@

    API Referencedatafusion.input.location

    • +
  • datafusion.io
  • datafusion.object_store
  • datafusion.plan
  • datafusion.record_batch
    • @@ -415,11 +431,11 @@

    API Reference +

    previous

    -

    Introduction

    +

    Python Extensions

     diff --git a/contributor-guide/ffi.html b/contributor-guide/ffi.html new file mode 100644 index 000000000..7abc76616 --- /dev/null +++ b/contributor-guide/ffi.html @@ -0,0 +1,649 @@ + + + + + + + + Python Extensions — Apache Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + +
    +
    + + + + +
    + + + + + +
    +
    +
    +
    + + + + +
    + + +
    + +
    + On this page +
    + + +
    + +
    + +
    + + +
    + + + + + + +
    + +
    + +
    +

    Python Extensions

    +

    The DataFusion in Python project is designed to allow users to extend its functionality in a few core +areas. Ideally many users would like to package their extensions as a Python package and easily +integrate that package with this project. This page serves to describe some of the challenges we face +when doing these integrations and the approach our project uses.

    +
    +

    The Primary Issue

    +

    Suppose you wish to use DataFusion and you have a custom data source that can produce tables that +can then be queried against, similar to how you can register a CSV or +Parquet file. In DataFusion terminology, you likely want to implement a +Custom Table Provider. In an effort to make your data source +as performant as possible and to utilize the features of DataFusion, you may decide to write +your source in Rust and then expose it through PyO3 as a Python library.

    +

    At first glance, it may appear the best way to do this is to add the datafusion-python +crate as a dependency, provide a PyTable, and then to register it with the +SessionContext. Unfortunately, this will not work.

    +

    When you produce your code as a Python library and it needs to interact with the DataFusion +library, at the lowest level they communicate through an Application Binary Interface (ABI). +The acronym sounds similar to API (Application Programming Interface), but it is distinctly +different.

    +

    The ABI sets the standard for how these libraries can share data and functions between each +other. One of the key differences between Rust and other programming languages is that Rust +does not have a stable ABI. What this means in practice is that if you compile a Rust library +with one version of the rustc compiler and I compile another library to interface with it +but I use a different version of the compiler, there is no guarantee the interface will be +the same.

    +

    In practice, this means that a Python library built with datafusion-python as a Rust +dependency will generally not be compatible with the DataFusion Python package, even +if they reference the same version of datafusion-python. If you attempt to do this, it may +work on your local computer if you have built both packages with the same optimizations. +This can sometimes lead to a false expectation that the code will work, but it frequently +breaks the moment you try to use your package against the released packages.

    +

    You can find more information about the Rust ABI in their +online documentation.

    +
    +
    +

    The FFI Approach

    +

    Rust supports interacting with other programming languages through it’s Foreign Function +Interface (FFI). The advantage of using the FFI is that it enables you to write data structures +and functions that have a stable ABI. The allows you to use Rust code with C, Python, and +other languages. In fact, the PyO3 library uses the FFI to share data +and functions between Python and Rust.

    +

    The approach we are taking in the DataFusion in Python project is to incrementally expose +more portions of the DataFusion project via FFI interfaces. This allows users to write Rust +code that does not require the datafusion-python crate as a dependency, expose their +code in Python via PyO3, and have it interact with the DataFusion Python package.

    +

    Early adopters of this approach include delta-rs +who has adapted their Table Provider for use in `datafusion-python` with only a few lines +of code. Also, the DataFusion Python project uses the existing definitions from +Apache Arrow CStream Interface +to support importing and exporting tables. Any Python package that supports reading +the Arrow C Stream interface can work with DataFusion Python out of the box! You can read +more about working with Arrow sources in the Data Sources +page.

    +

    To learn more about the Foreign Function Interface in Rust, the +Rustonomicon is a good resource.

    +
    +
    +

    Inspiration from Arrow

    +

    DataFusion is built upon Apache Arrow. The canonical Python +Arrow implementation, pyarrow provides +an excellent way to share Arrow data between Python projects without performing any copy +operations on the data. They do this by using a well defined set of interfaces. You can +find the details about their stream interface +here. The +Rust Arrow Implementation also supports these +C style definitions via the Foreign Function Interface.

    +

    In addition to using these interfaces to transfer Arrow data between libraries, pyarrow +goes one step further to make sharing the interfaces easier in Python. They do this +by exposing PyCapsules that contain the expected functionality.

    +

    You can learn more about PyCapsules from the official +Python online documentation. PyCapsules +have excellent support in PyO3 already. The +PyO3 online documentation is a good source +for more details on using PyCapsules in Rust.

    +

    Two lessons we leverage from the Arrow project in DataFusion Python are:

    +
      +

    • We reuse the existing Arrow FFI functionality wherever possible.

      • +

    • We expose PyCapsules that contain a FFI stable struct.

      • +
    +
    +
    +

    Implementation Details

    +

    The bulk of the code necessary to perform our FFI operations is in the upstream +DataFusion core repository. You can review the code and +documentation in the datafusion-ffi crate.

    +

    Our FFI implementation is narrowly focused at sharing data and functions with Rust backed +libraries. This allows us to use the abi_stable crate. +This is an excellent crate that allows for easy conversion between Rust native types +and FFI-safe alternatives. For example, if you needed to pass a Vec<String> via FFI, +you can simply convert it to a RVec<RString> in an intuitive manner. It also supports +features like RResult and ROption that do not have an obvious translation to a +C equivalent.

    +

    The datafusion-ffi crate has been designed to make it easy to convert from DataFusion +traits into their FFI counterparts. For example, if you have defined a custom +TableProvider +and you want to create a sharable FFI counterpart, you could write:

    +
    let my_provider = MyTableProvider::default();
+let ffi_provider = FFI_TableProvider::new(Arc::new(my_provider), false, None);
+
    +
    +

    If you were interfacing with a library that provided the above FFI_TableProvider and +you needed to turn it back into an TableProvider, you can turn it into a +ForeignTableProvider with implements the TableProvider trait.

    +
    let foreign_provider: ForeignTableProvider = ffi_provider.into();
+
    +
    +

    If you review the code in datafusion-ffi you will find that each of the traits we share +across the boundary has two portions, one with a FFI_ prefix and one with a Foreign +prefix. This is used to distinguish which side of the FFI boundary that struct is +designed to be used on. The structures with the FFI_ prefix are to be used on the +provider of the structure. In the example we’re showing, this means the code that has +written the underlying TableProvider implementation to access your custom data source. +The structures with the Foreign prefix are to be used by the receiver. In this case, +it is the datafusion-python library.

    +

    In order to share these FFI structures, we need to wrap them in some kind of Python object +that can be used to interface from one package to another. As described in the above +section on our inspiration from Arrow, we use PyCapsule. We can create a PyCapsule +for our provider thusly:

    +
    let name = CString::new("datafusion_table_provider")?;
+let my_capsule = PyCapsule::new_bound(py, provider, Some(name))?;
+
    +
    +

    On the receiving side, turn this pycapsule object into the FFI_TableProvider, which +can then be turned into a ForeignTableProvider the associated code is:

    +
    let capsule = capsule.downcast::<PyCapsule>()?;
+let provider = unsafe { capsule.reference::<FFI_TableProvider>() };
+
    +
    +

    By convention the datafusion-python library expects a Python object that has a +TableProvider PyCapsule to have this capsule accessible by calling a function named +__datafusion_table_provider__. You can see a complete working example of how to +share a TableProvider from one python library to DataFusion Python in the +repository examples folder.

    +

    This section has been written using TableProvider as an example. It is the first +extension that has been written using this approach and the most thoroughly implemented. +As we continue to expose more of the DataFusion features, we intend to follow this same +design pattern.

    +
    +
    +

    Alternative Approach

    +

    Suppose you needed to expose some other features of DataFusion and you could not wait +for the upstream repository to implement the FFI approach we describe. In this case +you decide to create your dependency on the datafusion-python crate instead.

    +

    As we discussed, this is not guaranteed to work across different compiler versions and +optimization levels. If you wish to go down this route, there are two approaches we +have identified you can use.

    +
      +

    1. Re-export all of datafusion-python yourself with your extensions built in.

      2. +

    2. Carefully synchonize your software releases with the datafusion-python CI build +system so that your libraries use the exact same compiler, features, and +optimization level.

      3. +
    +

    We currently do not recommend either of these approaches as they are difficult to +maintain over a long period. Additionally, they require a tight version coupling +between libraries.

    +
    +
    +

    Status of Work

    +

    At the time of this writing, the FFI features are under active development. To see +the latest status, we recommend reviewing the code in the datafusion-ffi crate.

    +
    +
    + + +
    + + + +
    + + +
    +

    previous

    +

    Introduction

    +
    +     + +
    +

    next

    +

    API Reference

    +
    + +     +
    + +
    + + +
    +
    + + + + +
    +
    + +
    +

    + © Copyright 2019-2024, Apache Software Foundation.
    +

    +
    + +
    +

    +Created using Sphinx 8.1.3.
    +

    +
    + +
    +

    Apache Arrow DataFusion, Arrow DataFusion, Apache, the Apache feather logo, and the Apache Arrow DataFusion project logo

    +

    are either registered trademarks or trademarks of The Apache Software Foundation in the United States and other countries.

    +
    +
    +
    + + + + \ No newline at end of file diff --git a/contributor-guide/introduction.html b/contributor-guide/introduction.html index 1ff78cefd..6a97a45fb 100644 --- a/contributor-guide/introduction.html +++ b/contributor-guide/introduction.html @@ -34,7 +34,7 @@ - + @@ -127,6 +127,11 @@

    @@ -307,6 +317,11 @@ +

  • + + datafusion.io + +
  • datafusion.object_store @@ -484,7 +499,7 @@

    Improving Build Speed.pyo3_build_config it will be ignored by git.

    implementation=CPython
-version=3.8
+version=3.9
 shared=true
 abi3=true
 lib_name=python3.12
@@ -528,10 +543,10 @@ 
    Improving Build SpeedSQL
    - +

    next

    -

    API Reference

    +

    Python Extensions

     diff --git a/genindex.html b/genindex.html index 6d7fa3c19..6d65db2fd 100644 --- a/genindex.html +++ b/genindex.html @@ -124,6 +124,11 @@

    @@ -304,6 +314,11 @@

    • +
  • + + datafusion.io + +
  • datafusion.object_store @@ -526,8 +541,6 @@

    _

  • (datafusion.expr.Expr attribute)
    • - -

    + @@ -826,10 +863,10 @@

    B

  • bit_length() (in module datafusion.functions)
    • - - + @@ -1077,6 +1116,13 @@

    D

    +
  • + datafusion.io + +
  • @@ -1115,11 +1161,11 @@

    D

  • date_bin() (in module datafusion.functions) -
    • -
  • date_part() (in module datafusion.functions)
    • - + - + + - + + + + + + - + + + + @@ -2029,10 +2735,13 @@

    Classes

    - + + + + - + @@ -2042,28 +2751,25 @@

    Classes

    Functions

    RecordBatch

    This class is essentially a wrapper for pyarrow.RecordBatch.

    This class is essentially a wrapper for pa.RecordBatch.

    RecordBatchStream

    This class represents a stream of record batches.

    _R

    _W

    udaf

    udf

    udwf

    - +
  • global_ctx() (datafusion.context.SessionContext class method) +
  • GoogleCloud (in module datafusion.object_store)
  • GroupingSet (in module datafusion.expr) @@ -1433,6 +1481,8 @@

    I

  • InSubquery (in module datafusion.expr)
  • intersect() (datafusion.dataframe.DataFrame method) +
    • +
  • into_view() (datafusion.dataframe.DataFrame method)
  • is_causal() (datafusion.udf.WindowEvaluator method)
    • @@ -1440,14 +1490,16 @@

    I

  • is_current_row() (datafusion.expr.WindowFrameBound method) -
    • -
  • is_following() (datafusion.expr.WindowFrameBound method)
  • read_avro() (datafusion.context.SessionContext method) + +
  • read_csv() (datafusion.context.SessionContext method) + +
  • read_json() (datafusion.context.SessionContext method) + +
  • read_parquet() (datafusion.context.SessionContext method) + +
  • read_table() (datafusion.context.SessionContext method)
  • record_batch (datafusion.record_batch.RecordBatch attribute) @@ -1891,6 +1973,8 @@

    R

  • (class in datafusion.record_batch)
    • +
  • regexp_count() (in module datafusion.functions) +
  • regexp_like() (in module datafusion.functions)
  • regexp_match() (in module datafusion.functions) @@ -1909,6 +1993,8 @@

    R

  • register_object_store() (datafusion.context.SessionContext method)
    • +
  • ScalarVariable (in module datafusion.expr)
    • -
  • schema() (datafusion.catalog.Table method) +
  • schema (datafusion.catalog.Table property)
    • +
  • schema() (datafusion.dataframe.DataFrame method) +
  • schema_name() (datafusion.Expr method)
    • @@ -806,6 +831,33 @@ +
  • + + + + Expr.abs() + + + +
    • +
  • + + + + Expr.acos() + + + +
    • +
  • + + + + Expr.acosh() + + + +
  • @@ -815,6 +867,123 @@
    • +
  • + + + + Expr.array_dims() + + + +
    • +
  • + + + + Expr.array_distinct() + + + +
    • +
  • + + + + Expr.array_empty() + + + +
    • +
  • + + + + Expr.array_length() + + + +
    • +
  • + + + + Expr.array_ndims() + + + +
    • +
  • + + + + Expr.array_pop_back() + + + +
    • +
  • + + + + Expr.array_pop_front() + + + +
    • +
  • + + + + Expr.arrow_typeof() + + + +
    • +
  • + + + + Expr.ascii() + + + +
    • +
  • + + + + Expr.asin() + + + +
    • +
  • + + + + Expr.asinh() + + + +
    • +
  • + + + + Expr.atan() + + + +
    • +
  • + + + + Expr.atanh() + + + +
  • @@ -824,6 +993,24 @@
    • +
  • + + + + Expr.bit_length() + + + +
    • +
  • + + + + Expr.btrim() + + + +
  • @@ -833,6 +1020,15 @@
    • +
  • + + + + Expr.cardinality() + + + +
  • @@ -842,6 +1038,51 @@
    • +
  • + + + + Expr.cbrt() + + + +
    • +
  • + + + + Expr.ceil() + + + +
    • +
  • + + + + Expr.char_length() + + + +
    • +
  • + + + + Expr.character_length() + + + +
    • +
  • + + + + Expr.chr() + + + +
  • @@ -860,6 +1101,42 @@
    • +
  • + + + + Expr.cos() + + + +
    • +
  • + + + + Expr.cosh() + + + +
    • +
  • + + + + Expr.cot() + + + +
    • +
  • + + + + Expr.degrees() + + + +
  • @@ -878,6 +1155,33 @@
    • +
  • + + + + Expr.empty() + + + +
    • +
  • + + + + Expr.exp() + + + +
    • +
  • + + + + Expr.factorial() + + + +
  • @@ -905,6 +1209,42 @@
    • +
  • + + + + Expr.flatten() + + + +
    • +
  • + + + + Expr.floor() + + + +
    • +
  • + + + + Expr.from_unixtime() + + + +
    • +
  • + + + + Expr.initcap() + + + +
  • @@ -923,6 +1263,69 @@
    • +
  • + + + + Expr.isnan() + + + +
    • +
  • + + + + Expr.iszero() + + + +
    • +
  • + + + + Expr.length() + + + +
    • +
  • + + + + Expr.list_dims() + + + +
    • +
  • + + + + Expr.list_distinct() + + + +
    • +
  • + + + + Expr.list_length() + + + +
    • +
  • + + + + Expr.list_ndims() + + + +
  • @@ -932,6 +1335,60 @@
    • +
  • + + + + Expr.ln() + + + +
    • +
  • + + + + Expr.log10() + + + +
    • +
  • + + + + Expr.log2() + + + +
    • +
  • + + + + Expr.lower() + + + +
    • +
  • + + + + Expr.ltrim() + + + +
    • +
  • + + + + Expr.md5() + + + +
  • @@ -941,110 +1398,263 @@
    • +
  • + + + + Expr.octet_length() + + + +
  • - Expr.order_by() + Expr.order_by() + + + +
    • +
  • + + + + Expr.over() + + + +
    • +
  • + + + + Expr.partition_by() + + + +
    • +
  • + + + + Expr.python_value() + + + +
    • +
  • + + + + Expr.radians() + + + +
    • +
  • + + + + Expr.reverse() + + + +
    • +
  • + + + + Expr.rex_call_operands() + + + +
    • +
  • + + + + Expr.rex_call_operator() + + + +
    • +
  • + + + + Expr.rex_type() + + + +
    • +
  • + + + + Expr.rtrim() + + + +
    • +
  • + + + + Expr.schema_name() + + + +
    • +
  • + + + + Expr.sha224() + + + +
    • +
  • + + + + Expr.sha256() + + + +
    • +
  • + + + + Expr.sha384() + + + +
    • +
  • + + + + Expr.sha512() + + + +
    • +
  • + + + + Expr.signum() + + + +
    • +
  • + + + + Expr.sin()
  • - + - Expr.over() + Expr.sinh()
  • - + - Expr.partition_by() + Expr.sort()
  • - + - Expr.python_value() + Expr.sqrt()
  • - + - Expr.rex_call_operands() + Expr.string_literal()
  • - + - Expr.rex_call_operator() + Expr.tan()
  • - + - Expr.rex_type() + Expr.tanh()
  • - + - Expr.schema_name() + Expr.to_hex()
  • - + - Expr.sort() + Expr.to_variant()
  • - + - Expr.string_literal() + Expr.trim()
  • - + - Expr.to_variant() + Expr.types()
  • - + - Expr.types() + Expr.upper() @@ -1688,6 +2298,71 @@
    • +
  • + + + + TableFunction + + + + +
  • @@ -1810,19 +2485,10 @@
  • - - - - col() - - - -
    • -
  • - + - column() + configure_formatter() @@ -1890,6 +2556,24 @@
    • +
  • + + + + col + + + +
    • +
  • + + + + column + + + +
  • @@ -1908,6 +2592,15 @@
    • +
  • + + + + udtf + + + +
  • @@ -1950,10 +2643,12 @@

    Submodules @@ -1971,13 +2668,22 @@

    Attributes

    • DFSchema

    col

    column

    udaf

    udf

    udwf

    udtf

    udwf

    Table

    DataFusion table.

    WindowFrame

    TableFunction

    Class for performing user-defined table functions (UDTF).

    WindowFrame

    Defines a window frame for performing window operations.

    WindowUDF

    WindowUDF

    Class for performing window user-defined functions (UDF).
    - - - - - + + - + - + - + - + - + - + @@ -2103,7 +2809,7 @@

    Package Contents
    -class datafusion.AggregateUDF(name: str, accumulator: Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str)
    +class datafusion.AggregateUDF(name: str, accumulator: Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str)

    Class for performing scalar user-defined functions (UDF).

    Aggregate UDFs operate on a group of rows and return a single value. See also ScalarUDF for operating on a row by row basis.

    @@ -2120,78 +2826,67 @@

    Package Contents
    -static udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, AggregateUDF]
    +static udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, AggregateUDF]
    -static udaf(accum: Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → AggregateUDF
    +static udaf(accum: Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → AggregateUDF

    Create a new User-Defined Aggregate Function (UDAF).

    -

    This class allows you to define an aggregate function that can be used in +

    This class allows you to define an aggregate function that can be used in data aggregation or window function calls.

    -
    +
    Usage:
      -
    • -
      As a function: Call `udaf(accum, input_types, return_type, state_type,

      volatility, name)`.

      -
      -
      -
      • -
    • -
      As a decorator: Use `@udaf(input_types, return_type, state_type,

      volatility, name)`.

      -
      -
      -
      • +

    • As a function: udaf(accum, input_types, return_type, state_type, volatility, name).

      • +

    • As a decorator: @udaf(input_types, return_type, state_type, volatility, name). +When using udaf as a decorator, do not pass accum explicitly.

    -

    When using udaf as a decorator, do not pass `accum` explicitly.

    -

    Function example:

    -
    -

    If your :py:class:Accumulator can be instantiated with no arguments, you +

    Function example:

    +

    If your Accumulator can be instantiated with no arguments, you can simply pass it’s type as accum. If you need to pass additional arguments to it’s constructor, you can define a lambda or a factory method. -During runtime the :py:class:Accumulator will be constructed for every -instance in which this UDAF is used. The following examples are all valid. -``` -import pyarrow as pa -import pyarrow.compute as pc

    -
    -
    class Summarize(Accumulator):
    -
    def __init__(self, bias: float = 0.0):

    self._sum = pa.scalar(bias)

    -
    -
    def state(self) -> list[pa.Scalar]:

    return [self._sum]

    -
    -
    def update(self, values: pa.Array) -> None:

    self._sum = pa.scalar(self._sum.as_py() + pc.sum(values).as_py())

    -
    -
    def merge(self, states: list[pa.Array]) -> None:

    self._sum = pa.scalar(self._sum.as_py() + pc.sum(states[0]).as_py())

    -
    -
    def evaluate(self) -> pa.Scalar:

    return self._sum

    -
    -
    -
    -
    def sum_bias_10() -> Summarize:

    return Summarize(10.0)

    -
    -
    udaf1 = udaf(Summarize, pa.float64(), pa.float64(), [pa.float64()],

    “immutable”)

    -
    -
    udaf2 = udaf(sum_bias_10, pa.float64(), pa.float64(), [pa.float64()],

    “immutable”)

    -
    -
    udaf3 = udaf(lambda: Summarize(20.0), pa.float64(), pa.float64(),

    [pa.float64()], “immutable”)

    -
    -
    -

    ```

    -
    -
    -
    Decorator example:

    ``` -@udaf(pa.float64(), pa.float64(), [pa.float64()], “immutable”) -def udf4() -> Summarize:

    -
    -

    return Summarize(10.0)

    -
    -

    ```

    -
    -
    +During runtime the Accumulator will be constructed for every +instance in which this UDAF is used. The following examples are all valid:

    +
    import pyarrow as pa
+import pyarrow.compute as pc
+
+class Summarize(Accumulator):
+    def __init__(self, bias: float = 0.0):
+        self._sum = pa.scalar(bias)
+
+    def state(self) -> list[pa.Scalar]:
+        return [self._sum]
+
+    def update(self, values: pa.Array) -> None:
+        self._sum = pa.scalar(self._sum.as_py() + pc.sum(values).as_py())
+
+    def merge(self, states: list[pa.Array]) -> None:
+        self._sum = pa.scalar(self._sum.as_py() + pc.sum(states[0]).as_py())
+
+    def evaluate(self) -> pa.Scalar:
+        return self._sum
+
+def sum_bias_10() -> Summarize:
+    return Summarize(10.0)
+
+udaf1 = udaf(Summarize, pa.float64(), pa.float64(), [pa.float64()],
+    "immutable")
+udaf2 = udaf(sum_bias_10, pa.float64(), pa.float64(), [pa.float64()],
+    "immutable")
+udaf3 = udaf(lambda: Summarize(20.0), pa.float64(), pa.float64(),
+    [pa.float64()], "immutable")
+
    +
    +

    Decorator example::

    +
    @udaf(pa.float64(), pa.float64(), [pa.float64()], "immutable")
+def udf4() -> Summarize:
+    return Summarize(10.0)
+
    +
    Parameters:
      -

    • accum – The accumulator python function. Only needed when calling as a -function. Skip this argument when using `udaf` as a decorator.

      • +

    • accum – The accumulator python function. Only needed when calling as a +function. Skip this argument when using udaf as a decorator.

    • input_types – The data types of the arguments to accum.

    • return_type – The data type of the return value.

    • state_type – The data types of the intermediate accumulation.

      • @@ -2376,76 +3071,197 @@

      Package Contents -
      -__le__(rhs: Any) → Expr
      -

      Less than or equal to.

      -

      Accepts either an expression or any valid PyArrow scalar literal value.

      +
      +__le__(rhs: Any) → Expr
      +

      Less than or equal to.

      +

      Accepts either an expression or any valid PyArrow scalar literal value.

      +

    + +
    +
    +__lt__(rhs: Any) → Expr
    +

    Less than.

    +

    Accepts either an expression or any valid PyArrow scalar literal value.

    +
    + +
    +
    +__mod__(rhs: Any) → Expr
    +

    Modulo operator (%).

    +

    Accepts either an expression or any valid PyArrow scalar literal value.

    +
    + +
    +
    +__mul__(rhs: Any) → Expr
    +

    Multiplication operator.

    +

    Accepts either an expression or any valid PyArrow scalar literal value.

    +
    + +
    +
    +__ne__(rhs: object) → Expr
    +

    Not equal to.

    +

    Accepts either an expression or any valid PyArrow scalar literal value.

    +
    + +
    +
    +__or__(rhs: Expr) → Expr
    +

    Logical OR.

    +
    + +
    +
    +__repr__() → str
    +

    Generate a string representation of this expression.

    +
    + +
    +
    +__richcmp__(other: Expr, op: int) → Expr
    +

    Comparison operator.

    +
    + +
    +
    +__sub__(rhs: Any) → Expr
    +

    Subtraction operator.

    +

    Accepts either an expression or any valid PyArrow scalar literal value.

    +
    + +
    +
    +__truediv__(rhs: Any) → Expr
    +

    Division operator.

    +

    Accepts either an expression or any valid PyArrow scalar literal value.

    +
    + +
    +
    +abs() → Expr
    +

    Return the absolute value of a given number.

    +
    +

    Returns:

    +
    +
    Expr

    A new expression representing the absolute value of the input expression.

    +
    +
    +
    +
    + +
    +
    +acos() → Expr
    +

    Returns the arc cosine or inverse cosine of a number.

    +
    +

    Returns:

    +
    +
    Expr

    A new expression representing the arc cosine of the input expression.

    +
    +
    +
    +
    + +
    +
    +acosh() → Expr
    +

    Returns inverse hyperbolic cosine.

    +
    + +
    +
    +alias(name: str, metadata: dict[str, str] | None = None) → Expr
    +

    Assign a name to the expression.

    +
    +
    Parameters:
    +
      +

    • name – The name to assign to the expression.

      • +

    • metadata – Optional metadata to attach to the expression.

      • +
    +
    +
    Returns:
    +

    A new expression with the assigned name.

    +
    +
    +
    + +
    +
    +array_dims() → Expr
    +

    Returns an array of the array’s dimensions.

    +
    + +
    +
    +array_distinct() → Expr
    +

    Returns distinct values from the array after removing duplicates.

    +
    + +
    +
    +array_empty() → Expr
    +

    Returns a boolean indicating whether the array is empty.

    -
    -__lt__(rhs: Any) → Expr
    -

    Less than.

    -

    Accepts either an expression or any valid PyArrow scalar literal value.

    +
    +array_length() → Expr
    +

    Returns the length of the array.

    -
    -__mod__(rhs: Any) → Expr
    -

    Modulo operator (%).

    -

    Accepts either an expression or any valid PyArrow scalar literal value.

    +
    +array_ndims() → Expr
    +

    Returns the number of dimensions of the array.

    -
    -__mul__(rhs: Any) → Expr
    -

    Multiplication operator.

    -

    Accepts either an expression or any valid PyArrow scalar literal value.

    +
    +array_pop_back() → Expr
    +

    Returns the array without the last element.

    -
    -__ne__(rhs: object) → Expr
    -

    Not equal to.

    -

    Accepts either an expression or any valid PyArrow scalar literal value.

    +
    +array_pop_front() → Expr
    +

    Returns the array without the first element.

    -
    -__or__(rhs: Expr) → Expr
    -

    Logical OR.

    +
    +arrow_typeof() → Expr
    +

    Returns the Arrow type of the expression.

    -
    -__repr__() → str
    -

    Generate a string representation of this expression.

    +
    +ascii() → Expr
    +

    Returns the numeric code of the first character of the argument.

    -
    -__richcmp__(other: Expr, op: int) → Expr
    -

    Comparison operator.

    +
    +asin() → Expr
    +

    Returns the arc sine or inverse sine of a number.

    -
    -__sub__(rhs: Any) → Expr
    -

    Subtraction operator.

    -

    Accepts either an expression or any valid PyArrow scalar literal value.

    +
    +asinh() → Expr
    +

    Returns inverse hyperbolic sine.

    -
    -__truediv__(rhs: Any) → Expr
    -

    Division operator.

    -

    Accepts either an expression or any valid PyArrow scalar literal value.

    +
    +atan() → Expr
    +

    Returns inverse tangent of a number.

    -
    -alias(name: str) → Expr
    -

    Assign a name to the expression.

    +
    +atanh() → Expr
    +

    Returns inverse hyperbolic tangent.

    @@ -2463,18 +3279,66 @@

    Package Contents +
    +bit_length() → Expr
    +

    Returns the number of bits in the string argument.

    +

    + +
    +
    +btrim() → Expr
    +

    Removes all characters, spaces by default, from both sides of a string.

    +
    +
    canonical_name() → str

    Returns a complete string representation of this expression.

    +
    +
    +cardinality() → Expr
    +

    Returns the total number of elements in the array.

    +
    +
    cast(to: pyarrow.DataType[Any] | type[float | int | str | bool]) → Expr

    Cast to a new data type.

    +
    +
    +cbrt() → Expr
    +

    Returns the cube root of a number.

    +
    + +
    +
    +ceil() → Expr
    +

    Returns the nearest integer greater than or equal to argument.

    +
    + +
    +
    +char_length() → Expr
    +

    The number of characters in the string.

    +
    + +
    +
    +character_length() → Expr
    +

    Returns the number of characters in the argument.

    +
    + +
    +
    +chr() → Expr
    +

    Converts the Unicode code point to a UTF8 character.

    +
    +
    static column(value: str) → Expr
    @@ -2487,6 +3351,30 @@

    Package Contents +
    +cos() → Expr
    +

    Returns the cosine of the argument.

    +

    + +
    +
    +cosh() → Expr
    +

    Returns the hyperbolic cosine of the argument.

    +
    + +
    +
    +cot() → Expr
    +

    Returns the cotangent of the argument.

    +
    + +
    +
    +degrees() → Expr
    +

    Converts the argument from radians to degrees.

    +
    +
    display_name() → str
    @@ -2503,6 +3391,24 @@

    Package Contentsbuild() is called.

    +
    +
    +empty() → Expr
    +

    This is an alias for array_empty().

    +
    + +
    +
    +exp() → Expr
    +

    Returns the exponential of the argument.

    +
    + +
    +
    +factorial() → Expr
    +

    Returns the factorial of the argument.

    +
    +
    fill_nan(value: Any | Expr | None = None) → Expr
    @@ -2524,6 +3430,32 @@

    Package Contentsbuild() is called.

    +
    +
    +flatten() → Expr
    +

    Flattens an array of arrays into a single array.

    +
    + +
    +
    +floor() → Expr
    +

    Returns the nearest integer less than or equal to the argument.

    +
    + +
    +
    +from_unixtime() → Expr
    +

    Converts an integer to RFC3339 timestamp format string.

    +
    + +
    +
    +initcap() → Expr
    +

    Set the initial letter of each word to capital.

    +

    Converts the first letter of each word in string to uppercase and the +remaining characters to lowercase.

    +
    +
    is_not_null() → Expr
    @@ -2536,6 +3468,52 @@

    Package ContentsTrue if this expression is null.

    +
    +
    +isnan() → Expr
    +

    Returns true if a given number is +NaN or -NaN otherwise returns false.

    +
    + +
    +
    +iszero() → Expr
    +

    Returns true if a given number is +0.0 or -0.0 otherwise returns false.

    +
    + +
    +
    +length() → Expr
    +

    The number of characters in the string.

    +
    + +
    +
    +list_dims() → Expr
    +

    Returns an array of the array’s dimensions.

    +

    This is an alias for array_dims().

    +
    + +
    +
    +list_distinct() → Expr
    +

    Returns distinct values from the array after removing duplicates.

    +

    This is an alias for array_distinct().

    +
    + +
    +
    +list_length() → Expr
    +

    Returns the length of the array.

    +

    This is an alias for array_length().

    +
    + +
    +
    +list_ndims() → Expr
    +

    Returns the number of dimensions of the array.

    +

    This is an alias for array_ndims().

    +
    +
    static literal(value: Any) → Expr
    @@ -2543,6 +3521,42 @@

    Package Contentsvalue must be a valid PyArrow scalar value or easily castable to one.

    +
    +
    +ln() → Expr
    +

    Returns the natural logarithm (base e) of the argument.

    +
    + +
    +
    +log10() → Expr
    +

    Base 10 logarithm of the argument.

    +
    + +
    +
    +log2() → Expr
    +

    Base 2 logarithm of the argument.

    +
    + +
    +
    +lower() → Expr
    +

    Converts a string to lowercase.

    +
    + +
    +
    +ltrim() → Expr
    +

    Removes all characters, spaces by default, from the beginning of a string.

    +
    + +
    +
    +md5() → Expr
    +

    Computes an MD5 128-bit checksum for a string expression.

    +
    +
    null_treatment(null_treatment: datafusion.common.NullTreatment) → ExprFuncBuilder
    @@ -2552,6 +3566,12 @@

    Package Contentsbuild() is called.

    +
    +
    +octet_length() → Expr
    +

    Returns the number of bytes of a string.

    +
    +
    order_by(*exprs: Expr | SortExpr) → ExprFuncBuilder
    @@ -2596,6 +3616,18 @@

    Package Contents +
    +radians() → Expr
    +

    Converts the argument from degrees to radians.

    +

    + +
    +
    +reverse() → Expr
    +

    Reverse the string argument.

    +
    +
    rex_call_operands() → list[Expr]
    @@ -2621,6 +3653,12 @@

    Package ContentsRexType.

    +
    +
    +rtrim() → Expr
    +

    Removes all characters, spaces by default, from the end of a string.

    +
    +
    schema_name() → str
    @@ -2628,6 +3666,48 @@

    Package Contents +
    +sha224() → Expr
    +

    Computes the SHA-224 hash of a binary string.

    +

    + +
    +
    +sha256() → Expr
    +

    Computes the SHA-256 hash of a binary string.

    +
    + +
    +
    +sha384() → Expr
    +

    Computes the SHA-384 hash of a binary string.

    +
    + +
    +
    +sha512() → Expr
    +

    Computes the SHA-512 hash of a binary string.

    +
    + +
    +
    +signum() → Expr
    +

    Returns the sign of the argument (-1, 0, +1).

    +
    + +
    +
    +sin() → Expr
    +

    Returns the sine of the argument.

    +
    + +
    +
    +sinh() → Expr
    +

    Returns the hyperbolic sine of the argument.

    +
    +
    sort(ascending: bool = True, nulls_first: bool = True) → SortExpr
    @@ -2642,6 +3722,12 @@

    Package Contents +
    +sqrt() → Expr
    +

    Returns the square root of the argument.

    +

    +
    static string_literal(value: str) → Expr
    @@ -2653,12 +3739,36 @@

    Package Contentshttps://github.com/apache/datafusion/blob/86740bfd3d9831d6b7c1d0e1bf4a21d91598a0ac/datafusion/functions/src/core/arrow_cast.rs#L179

    +
    +
    +tan() → Expr
    +

    Returns the tangent of the argument.

    +
    + +
    +
    +tanh() → Expr
    +

    Returns the hyperbolic tangent of the argument.

    +
    + +
    +
    +to_hex() → Expr
    +

    Converts an integer to a hexadecimal string.

    +
    +
    to_variant() → Any

    Convert this expression into a python object if possible.

    +
    +
    +trim() → Expr
    +

    Removes all characters, spaces by default, from both sides of a string.

    +
    +
    types() → datafusion.common.DataTypeMap
    @@ -2671,6 +3781,12 @@

    Package Contents +
    +upper() → Expr
    +

    Converts a string to uppercase.

    +

    +
    variant_name() → str
    @@ -3082,7 +4198,7 @@

    Package Contents
    -class datafusion.ScalarUDF(name: str, func: Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)
    +class datafusion.ScalarUDF(name: str, func: Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)

    Class for performing scalar user-defined functions (UDF).

    Scalar UDFs operate on a row by row basis. See also AggregateUDF for operating on a group of rows.

    @@ -3098,30 +4214,29 @@

    Package Contents
    -static udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, ScalarUDF]
    +static udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, ScalarUDF]
    -static udf(func: Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → ScalarUDF
    +static udf(func: Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → ScalarUDF

    Create a new User-Defined Function (UDF).

    -

    This class can be used both as a function and as a decorator.

    +

    This class can be used both as either a function or a decorator.

    Usage:
      -

    • As a function: Call udf(func, input_types, return_type, volatility, -name).

      • -

    • As a decorator: Use @udf(input_types, return_type, volatility, -name). In this case, do not pass func explicitly.

      • +

    • As a function: udf(func, input_types, return_type, volatility, name).

      • +

    • As a decorator: @udf(input_types, return_type, volatility, name). +When used a decorator, do not pass func explicitly.

    Parameters:
      -

    • func (Callable, optional) – Only needed when calling as a function. -Skip this argument when using udf as a decorator.

      • +

    • func (Callable, optional) – Only needed when calling as a function. +Skip this argument when using udf as a decorator.

    • input_types (list[pa.DataType]) – The data types of the arguments -to func. This list must be of the same length as the number of +to func. This list must be of the same length as the number of arguments.

    • return_type (_R) – The data type of the return value from the function.

      • -

    • volatility (Volatility | str) – See Volatility for allowed values.

      • +

    • volatility (Volatility | str) – See Volatility for allowed values.

    • name (Optional[str]) – A descriptive name for the function.

    @@ -3130,24 +4245,19 @@

    Package ContentsExample

    -

    Using `udf` as a function: -``` -def double_func(x):

    -
    -

    return x * 2

    -
    -

    double_udf = udf(double_func, [pa.int32()], pa.int32(), -“volatile”, “double_it”) -```

    -

    Using `udf` as a decorator: -``` -@udf([pa.int32()], pa.int32(), “volatile”, “double_it”) -def double_udf(x):

    -
    -

    return x * 2

    -
    -

    ```

    +

    Example: Using udf as a function:

    +
    def double_func(x):
+    return x * 2
+double_udf = udf(double_func, [pa.int32()], pa.int32(),
+"volatile", "double_it")
+
    +
    +

    Example: Using udf as a decorator:

    +
    @udf([pa.int32()], pa.int32(), "volatile", "double_it")
+def double_udf(x):
+    return x * 2
+
    +

    @@ -3389,6 +4499,54 @@

    Package Contents +
    +class datafusion.TableFunction(name: str, func: Callable[[], any])
    +

    Class for performing user-defined table functions (UDTF).

    +

    Table functions generate new table providers based on the +input expressions.

    +

    Instantiate a user-defined table function (UDTF).

    +

    See udtf() for a convenience function and argument +descriptions.

    +
    +
    +__call__(*args: datafusion.expr.Expr) → Any
    +

    Execute the UDTF and return a table provider.

    +
    + +
    +
    +__repr__() → str
    +

    User printable representation.

    +
    + +
    +
    +static _create_table_udf(func: Callable[Ellipsis, Any], name: str) → TableFunction
    +

    Create a TableFunction instance from function arguments.

    +
    + +
    +
    +static _create_table_udf_decorator(name: str | None = None) → Callable[[Callable[[], WindowEvaluator]], Callable[Ellipsis, datafusion.expr.Expr]]
    +

    Create a decorator for a WindowUDF.

    +
    + +
    +
    +static udtf(name: str) → Callable[Ellipsis, Any]
    +
    +static udtf(func: Callable[[], Any], name: str) → TableFunction
    +

    Create a new User-Defined Table Function (UDTF).

    +
    + +
    +
    +_udtf
    +
    + +

    +
    class datafusion.WindowFrame(units: str, start_bound: Any | None, end_bound: Any | None)
    @@ -3434,7 +4592,7 @@

    Package Contents
    -class datafusion.WindowUDF(name: str, func: Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str)
    +class datafusion.WindowUDF(name: str, func: Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str)

    Class for performing window user-defined functions (UDF).

    Window UDFs operate on a partition of rows. See also ScalarUDF for operating on a row by row basis.

    @@ -3451,13 +4609,13 @@

    Package Contents
    -static _create_window_udf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
    +static _create_window_udf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF

    Create a WindowUDF instance from function arguments.

    -static _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → Callable[[Callable[[], WindowEvaluator]], Callable[Ellipsis, datafusion.expr.Expr]]
    +static _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → Callable[[Callable[[], WindowEvaluator]], Callable[Ellipsis, datafusion.expr.Expr]]

    Create a decorator for a WindowUDF.

    @@ -3475,53 +4633,49 @@

    Package Contents
    -static udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, WindowUDF]
    +static udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, WindowUDF]
    -static udwf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
    +static udwf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF

    Create a new User-Defined Window Function (UDWF).

    -

    This class can be used both as a function and as a decorator.

    -
    +

    This class can be used both as either a function or a decorator.

    +
    Usage:
      -

    • As a function: Call udwf(func, input_types, return_type, volatility, -name).

      • -

    • As a decorator: Use @udwf(input_types, return_type, volatility, -name). When using udwf as a decorator, do not pass `func` -explicitly.

      • +

    • As a function: udwf(func, input_types, return_type, volatility, name).

      • +

    • As a decorator: @udwf(input_types, return_type, volatility, name). +When using udwf as a decorator, do not pass func explicitly.

    -
    Function example:

    ``` -import pyarrow as pa

    -
    -
    class BiasedNumbers(WindowEvaluator):
    -
    def __init__(self, start: int = 0) -> None:

    self.start = start

    -
    -
    def evaluate_all(self, values: list[pa.Array],

    num_rows: int) -> pa.Array: -return pa.array([self.start + i for i in range(num_rows)])

    -
    -
    -
    -
    def bias_10() -> BiasedNumbers:

    return BiasedNumbers(10)

    -
    -
    -

    udwf1 = udwf(BiasedNumbers, pa.int64(), pa.int64(), “immutable”) -udwf2 = udwf(bias_10, pa.int64(), pa.int64(), “immutable”) -udwf3 = udwf(lambda: BiasedNumbers(20), pa.int64(), pa.int64(), “immutable”)

    -

    ```

    -
    -
    Decorator example:

    ``` -@udwf(pa.int64(), pa.int64(), “immutable”) -def biased_numbers() -> BiasedNumbers:

    -
    -

    return BiasedNumbers(10)

    -
    -

    ```

    -
    +

    Function example:

    +
    import pyarrow as pa
+
+class BiasedNumbers(WindowEvaluator):
+    def __init__(self, start: int = 0) -> None:
+        self.start = start
+
+    def evaluate_all(self, values: list[pa.Array],
+        num_rows: int) -> pa.Array:
+        return pa.array([self.start + i for i in range(num_rows)])
+
+def bias_10() -> BiasedNumbers:
+    return BiasedNumbers(10)
+
+udwf1 = udwf(BiasedNumbers, pa.int64(), pa.int64(), "immutable")
+udwf2 = udwf(bias_10, pa.int64(), pa.int64(), "immutable")
+udwf3 = udwf(lambda: BiasedNumbers(20), pa.int64(), pa.int64(), "immutable")
+
    +
    +

    Decorator example:

    +
    @udwf(pa.int64(), pa.int64(), "immutable")
+def biased_numbers() -> BiasedNumbers:
+    return BiasedNumbers(10)
+
    +
    Parameters:
      -

    • func – Only needed when calling as a function. Skip this argument when -using `udwf` as a decorator.

      • +

    • func – Only needed when calling as a function. Skip this argument when +using udwf as a decorator.

    • input_types – The data types of the arguments.

    • return_type – The data type of the return value.

    • volatility – See Volatility for allowed values.

      • @@ -3542,15 +4696,30 @@

      Package Contents -
      -datafusion.col(value: str) → expr.Expr
      -

      Create a column expression.

      -

    - -
    -
    -datafusion.column(value: str) → expr.Expr
    -

    Create a column expression.

    +
    +datafusion.configure_formatter(**kwargs: Any) → None
    +

    Configure the global DataFrame HTML formatter.

    +

    This function creates a new formatter with the provided configuration +and sets it as the global formatter for all DataFrames.

    +
    +
    Parameters:
    +

    **kwargs – Formatter configuration parameters like max_cell_length, +max_width, max_height, enable_cell_expansion, etc.

    +
    +
    Raises:
    +

    ValueError – If any invalid parameters are provided

    +
    +
    +

    Example

    +
    >>> from datafusion.html_formatter import configure_formatter
+>>> configure_formatter(
+...     max_cell_length=50,
+...     max_height=500,
+...     enable_cell_expansion=True,
+...     use_shared_styles=True
+... )
+
    +
    @@ -3680,6 +4849,16 @@

    Package Contentsdatafusion.DFSchema

    +
    +
    +datafusion.col: Col
    +
    + +
    +
    +datafusion.column: Col
    +
    +
    datafusion.udaf
    @@ -3690,6 +4869,11 @@

    Package Contentsdatafusion.udf

    +
    +
    +datafusion.udtf
    +
    +
    datafusion.udwf
    diff --git a/autoapi/datafusion/input/base/index.html b/autoapi/datafusion/input/base/index.html index 5c55d0bda..b7958e532 100644 --- a/autoapi/datafusion/input/base/index.html +++ b/autoapi/datafusion/input/base/index.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/autoapi/datafusion/input/index.html b/autoapi/datafusion/input/index.html index 1f368148a..299228ad0 100644 --- a/autoapi/datafusion/input/index.html +++ b/autoapi/datafusion/input/index.html @@ -35,7 +35,7 @@ - + @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • @@ -496,11 +521,11 @@

    Package Contents +

    previous

    -

    datafusion.functions

    +

    datafusion.html_formatter

     diff --git a/autoapi/datafusion/input/location/index.html b/autoapi/datafusion/input/location/index.html index 2be427480..f0890e2a2 100644 --- a/autoapi/datafusion/input/location/index.html +++ b/autoapi/datafusion/input/location/index.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/autoapi/datafusion/io/index.html b/autoapi/datafusion/io/index.html index 3ce943551..726ec2633 100644 --- a/autoapi/datafusion/io/index.html +++ b/autoapi/datafusion/io/index.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/autoapi/datafusion/object_store/index.html b/autoapi/datafusion/object_store/index.html index b27718f02..d3a249fb5 100644 --- a/autoapi/datafusion/object_store/index.html +++ b/autoapi/datafusion/object_store/index.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/autoapi/datafusion/plan/index.html b/autoapi/datafusion/plan/index.html index df79d85d4..bfb70723c 100644 --- a/autoapi/datafusion/plan/index.html +++ b/autoapi/datafusion/plan/index.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/autoapi/datafusion/record_batch/index.html b/autoapi/datafusion/record_batch/index.html index edeb5af68..3db4e2b6f 100644 --- a/autoapi/datafusion/record_batch/index.html +++ b/autoapi/datafusion/record_batch/index.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/autoapi/datafusion/substrait/index.html b/autoapi/datafusion/substrait/index.html index 87028dab2..9443e482e 100644 --- a/autoapi/datafusion/substrait/index.html +++ b/autoapi/datafusion/substrait/index.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/autoapi/datafusion/udf/index.html b/autoapi/datafusion/udf/index.html index 9f0f67409..a6ff5e142 100644 --- a/autoapi/datafusion/udf/index.html +++ b/autoapi/datafusion/udf/index.html @@ -34,6 +34,7 @@ + @@ -116,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -274,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -294,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -346,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • @@ -368,403 +394,9 @@
    -
    - On this page -
    @@ -786,627 +418,7 @@

    datafusion.udf

    -

    Provides the user-defined functions for evaluation of dataframes.

    -
    -

    Attributes

    -

    col(→ expr.Expr)

    Create a column expression.

    column(→ expr.Expr)

    Create a column expression.

    configure_formatter(→ None)

    Configure the global DataFrame HTML formatter.

    lit(→ expr.Expr)

    lit(→ expr.Expr)

    Create a literal expression.

    literal(→ expr.Expr)

    literal(→ expr.Expr)

    Create a literal expression.

    read_avro(→ datafusion.dataframe.DataFrame)

    read_avro(→ datafusion.dataframe.DataFrame)

    Create a DataFrame for reading Avro data source.

    read_csv(→ datafusion.dataframe.DataFrame)

    read_csv(→ datafusion.dataframe.DataFrame)

    Read a CSV data source.

    read_json(→ datafusion.dataframe.DataFrame)

    read_json(→ datafusion.dataframe.DataFrame)

    Read a line-delimited JSON data source.

    read_parquet(→ datafusion.dataframe.DataFrame)

    read_parquet(→ datafusion.dataframe.DataFrame)

    Read a Parquet source into a Dataframe.
    - - - - - - - - - - - - - - -

    _R

    udaf

    udf

    udwf

    - -
    -

    Classes

    - - - - - - - - - - - - - - - - - - - - - -

    Accumulator

    Defines how an AggregateUDF accumulates values.

    AggregateUDF

    Class for performing scalar user-defined functions (UDF).

    ScalarUDF

    Class for performing scalar user-defined functions (UDF).

    Volatility

    Defines how stable or volatile a function is.

    WindowEvaluator

    Evaluator class for user-defined window functions (UDWF).

    WindowUDF

    Class for performing window user-defined functions (UDF).

    -
    -
    -

    Module Contents

    -
    -
    -class datafusion.udf.Accumulator
    -

    Defines how an AggregateUDF accumulates values.

    -
    -
    -abstract evaluate() → pyarrow.Scalar
    -

    Return the resultant value.

    -
    - -
    -
    -abstract merge(states: list[pyarrow.Array]) → None
    -

    Merge a set of states.

    -
    - -
    -
    -abstract state() → list[pyarrow.Scalar]
    -

    Return the current state.

    -
    - -
    -
    -abstract update(*values: pyarrow.Array) → None
    -

    Evaluate an array of values and update state.

    -
    - -
    - -
    -
    -class datafusion.udf.AggregateUDF(name: str, accumulator: Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str)
    -

    Class for performing scalar user-defined functions (UDF).

    -

    Aggregate UDFs operate on a group of rows and return a single value. See -also ScalarUDF for operating on a row by row basis.

    -

    Instantiate a user-defined aggregate function (UDAF).

    -

    See udaf() for a convenience function and argument -descriptions.

    -
    -
    -__call__(*args: datafusion.expr.Expr) → datafusion.expr.Expr
    -

    Execute the UDAF.

    -

    This function is not typically called by an end user. These calls will -occur during the evaluation of the dataframe.

    -
    - -
    -
    -static udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, AggregateUDF]
    -
    -static udaf(accum: Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → AggregateUDF
    -

    Create a new User-Defined Aggregate Function (UDAF).

    -

    This class allows you to define an aggregate function that can be used in -data aggregation or window function calls.

    -
    -
    Usage:
      -
    • -
      As a function: Call `udaf(accum, input_types, return_type, state_type,

      volatility, name)`.

      -
      -
      -
      • -
    • -
      As a decorator: Use `@udaf(input_types, return_type, state_type,

      volatility, name)`.

      -
      -
      -
      • -
    -

    When using udaf as a decorator, do not pass `accum` explicitly.

    -
    -
    -

    Function example:

    -
    -

    If your :py:class:Accumulator can be instantiated with no arguments, you -can simply pass it’s type as accum. If you need to pass additional -arguments to it’s constructor, you can define a lambda or a factory method. -During runtime the :py:class:Accumulator will be constructed for every -instance in which this UDAF is used. The following examples are all valid. -``` -import pyarrow as pa -import pyarrow.compute as pc

    -
    -
    class Summarize(Accumulator):
    -
    def __init__(self, bias: float = 0.0):

    self._sum = pa.scalar(bias)

    -
    -
    def state(self) -> list[pa.Scalar]:

    return [self._sum]

    -
    -
    def update(self, values: pa.Array) -> None:

    self._sum = pa.scalar(self._sum.as_py() + pc.sum(values).as_py())

    -
    -
    def merge(self, states: list[pa.Array]) -> None:

    self._sum = pa.scalar(self._sum.as_py() + pc.sum(states[0]).as_py())

    -
    -
    def evaluate(self) -> pa.Scalar:

    return self._sum

    -
    -
    -
    -
    def sum_bias_10() -> Summarize:

    return Summarize(10.0)

    -
    -
    udaf1 = udaf(Summarize, pa.float64(), pa.float64(), [pa.float64()],

    “immutable”)

    -
    -
    udaf2 = udaf(sum_bias_10, pa.float64(), pa.float64(), [pa.float64()],

    “immutable”)

    -
    -
    udaf3 = udaf(lambda: Summarize(20.0), pa.float64(), pa.float64(),

    [pa.float64()], “immutable”)

    -
    -
    -

    ```

    -
    -
    -
    Decorator example:

    ``` -@udaf(pa.float64(), pa.float64(), [pa.float64()], “immutable”) -def udf4() -> Summarize:

    -
    -

    return Summarize(10.0)

    -
    -

    ```

    -
    -
    -
    -
    Parameters:
    -
      -

    • accum – The accumulator python function. Only needed when calling as a -function. Skip this argument when using `udaf` as a decorator.

      • -

    • input_types – The data types of the arguments to accum.

      • -

    • return_type – The data type of the return value.

      • -

    • state_type – The data types of the intermediate accumulation.

      • -

    • volatility – See Volatility for allowed values.

      • -

    • name – A descriptive name for the function.

      • -
    -
    -
    Returns:
    -

    A user-defined aggregate function, which can be used in either data -aggregation or window function calls.

    -
    -
    -
    - -
    -
    -_udaf
    -
    - -
    - -
    -
    -class datafusion.udf.ScalarUDF(name: str, func: Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)
    -

    Class for performing scalar user-defined functions (UDF).

    -

    Scalar UDFs operate on a row by row basis. See also AggregateUDF for -operating on a group of rows.

    -

    Instantiate a scalar user-defined function (UDF).

    -

    See helper method udf() for argument details.

    -
    -
    -__call__(*args: datafusion.expr.Expr) → datafusion.expr.Expr
    -

    Execute the UDF.

    -

    This function is not typically called by an end user. These calls will -occur during the evaluation of the dataframe.

    -
    - -
    -
    -static udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, ScalarUDF]
    -
    -static udf(func: Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → ScalarUDF
    -

    Create a new User-Defined Function (UDF).

    -

    This class can be used both as a function and as a decorator.

    -
    -
    Usage:
      -

    • As a function: Call udf(func, input_types, return_type, volatility, -name).

      • -

    • As a decorator: Use @udf(input_types, return_type, volatility, -name). In this case, do not pass func explicitly.

      • -
    -
    -
    -
    -
    Parameters:
    -
      -

    • func (Callable, optional) – Only needed when calling as a function. -Skip this argument when using udf as a decorator.

      • -

    • input_types (list[pa.DataType]) – The data types of the arguments -to func. This list must be of the same length as the number of -arguments.

      • -

    • return_type (_R) – The data type of the return value from the function.

      • -

    • volatility (Volatility | str) – See Volatility for allowed values.

      • -

    • name (Optional[str]) – A descriptive name for the function.

      • -
    -
    -
    Returns:
    -

    A user-defined function that can be used in SQL expressions, -data aggregation, or window function calls.

    -
    -
    -

    Example

    -

    Using `udf` as a function: -``` -def double_func(x):

    -
    -

    return x * 2

    -
    -

    double_udf = udf(double_func, [pa.int32()], pa.int32(), -“volatile”, “double_it”) -```

    -

    Using `udf` as a decorator: -``` -@udf([pa.int32()], pa.int32(), “volatile”, “double_it”) -def double_udf(x):

    -
    -

    return x * 2

    -
    -

    ```

    -
    - -
    -
    -_udf
    -
    - -
    - -
    -
    -class datafusion.udf.Volatility(*args, **kwds)
    -

    Bases: enum.Enum

    -

    Defines how stable or volatile a function is.

    -

    When setting the volatility of a function, you can either pass this -enumeration or a str. The str equivalent is the lower case value of the -name (“immutable”, “stable”, or “volatile”).

    -
    -
    -__str__() → str
    -

    Returns the string equivalent.

    -
    - -
    -
    -Immutable = 1
    -

    An immutable function will always return the same output when given the -same input.

    -

    DataFusion will attempt to inline immutable functions during planning.

    -
    - -
    -
    -Stable = 2
    -

    Returns the same value for a given input within a single queries.

    -

    A stable function may return different values given the same input across -different queries but must return the same value for a given input within a -query. An example of this is the Now function. DataFusion will attempt to -inline Stable functions during planning, when possible. For query -select col1, now() from t1, it might take a while to execute but now() -column will be the same for each output row, which is evaluated during -planning.

    -
    - -
    -
    -Volatile = 3
    -

    A volatile function may change the return value from evaluation to -evaluation.

    -

    Multiple invocations of a volatile function may return different results -when used in the same query. An example of this is the random() function. -DataFusion can not evaluate such functions during planning. In the query -select col1, random() from t1, random() function will be evaluated -for each output row, resulting in a unique random value for each row.

    -
    - -
    - -
    -
    -class datafusion.udf.WindowEvaluator
    -

    Evaluator class for user-defined window functions (UDWF).

    -

    It is up to the user to decide which evaluate function is appropriate.

    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    uses_window_frame

    supports_bounded_execution

    include_rank

    function_to_implement

    False (default)

    False (default)

    False (default)

    evaluate_all

    False

    True

    False

    evaluate

    False

    True/False

    True

    evaluate_all_with_rank

    True

    True/False

    True/False

    evaluate

    -
    -
    -evaluate(values: list[pyarrow.Array], eval_range: tuple[int, int]) → pyarrow.Scalar
    -

    Evaluate window function on a range of rows in an input partition.

    -

    This is the simplest and most general function to implement -but also the least performant as it creates output one row at -a time. It is typically much faster to implement stateful -evaluation using one of the other specialized methods on this -trait.

    -

    Returns a [ScalarValue] that is the value of the window -function within range for the entire partition. Argument -values contains the evaluation result of function arguments -and evaluation results of ORDER BY expressions. If function has a -single argument, values[1..] will contain ORDER BY expression results.

    -
    - -
    -
    -evaluate_all(values: list[pyarrow.Array], num_rows: int) → pyarrow.Array
    -

    Evaluate a window function on an entire input partition.

    -

    This function is called once per input partition for window functions that -do not use values from the window frame, such as -row_number(), -rank(), -dense_rank(), -percent_rank(), -cume_dist(), -lead(), -and lag().

    -

    It produces the result of all rows in a single pass. It -expects to receive the entire partition as the value and -must produce an output column with one output row for every -input row.

    -

    num_rows is required to correctly compute the output in case -len(values) == 0

    -

    Implementing this function is an optimization. Certain window -functions are not affected by the window frame definition or -the query doesn’t have a frame, and evaluate skips the -(costly) window frame boundary calculation and the overhead of -calling evaluate for each output row.

    -

    For example, the LAG built in window function does not use -the values of its window frame (it can be computed in one shot -on the entire partition with Self::evaluate_all regardless of the -window defined in the OVER clause)

    -
    lag(x, 1) OVER (ORDER BY z ROWS BETWEEN 2 PRECEDING AND 3 FOLLOWING)
-
    -
    -

    However, avg() computes the average in the window and thus -does use its window frame.

    -
    avg(x) OVER (PARTITION BY y ORDER BY z ROWS BETWEEN 2 PRECEDING AND 3 FOLLOWING)
-
    -
    -
    - -
    -
    -evaluate_all_with_rank(num_rows: int, ranks_in_partition: list[tuple[int, int]]) → pyarrow.Array
    -

    Called for window functions that only need the rank of a row.

    -

    Evaluate the partition evaluator against the partition using -the row ranks. For example, rank(col("a")) produces

    -
    a | rank
-- + ----
-A | 1
-A | 1
-C | 3
-D | 4
-D | 4
-
    -
    -

    For this case, num_rows would be 5 and the -ranks_in_partition would be called with

    -
    [
-    (0,1),
-    (2,2),
-    (3,4),
-]
-
    -
    -

    The user must implement this method if include_rank returns True.

    -
    - -
    -
    -get_range(idx: int, num_rows: int) → tuple[int, int]
    -

    Return the range for the window fuction.

    -

    If uses_window_frame flag is false. This method is used to -calculate required range for the window function during -stateful execution.

    -

    Generally there is no required range, hence by default this -returns smallest range(current row). e.g seeing current row is -enough to calculate window result (such as row_number, rank, -etc)

    -
    -
    Parameters:
    -
      -

    • idx: – Current index:

      • -

    • num_rows – Number of rows.

      • -
    -
    -
    -
    - -
    -
    -include_rank() → bool
    -

    Can this function be evaluated with (only) rank?

    -
    - -
    -
    -is_causal() → bool
    -

    Get whether evaluator needs future data for its result.

    -
    - -
    -
    -memoize() → None
    -

    Perform a memoize operation to improve performance.

    -

    When the window frame has a fixed beginning (e.g UNBOUNDED -PRECEDING), some functions such as FIRST_VALUE and -NTH_VALUE do not need the (unbounded) input once they have -seen a certain amount of input.

    -

    memoize is called after each input batch is processed, and -such functions can save whatever they need

    -
    - -
    -
    -supports_bounded_execution() → bool
    -

    Can the window function be incrementally computed using bounded memory?

    -
    - -
    -
    -uses_window_frame() → bool
    -

    Does the window function use the values from the window frame?

    -
    - -
    - -
    -
    -class datafusion.udf.WindowUDF(name: str, func: Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str)
    -

    Class for performing window user-defined functions (UDF).

    -

    Window UDFs operate on a partition of rows. See -also ScalarUDF for operating on a row by row basis.

    -

    Instantiate a user-defined window function (UDWF).

    -

    See udwf() for a convenience function and argument -descriptions.

    -
    -
    -__call__(*args: datafusion.expr.Expr) → datafusion.expr.Expr
    -

    Execute the UDWF.

    -

    This function is not typically called by an end user. These calls will -occur during the evaluation of the dataframe.

    -
    - -
    -
    -static _create_window_udf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
    -

    Create a WindowUDF instance from function arguments.

    -
    - -
    -
    -static _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → Callable[[Callable[[], WindowEvaluator]], Callable[Ellipsis, datafusion.expr.Expr]]
    -

    Create a decorator for a WindowUDF.

    -
    - -
    -
    -static _get_default_name(func: Callable) → str
    -

    Get the default name for a function based on its attributes.

    -
    - -
    -
    -static _normalize_input_types(input_types: pyarrow.DataType | list[pyarrow.DataType]) → list[pyarrow.DataType]
    -

    Convert a single DataType to a list if needed.

    -
    - -
    -
    -static udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, WindowUDF]
    -
    -static udwf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
    -

    Create a new User-Defined Window Function (UDWF).

    -

    This class can be used both as a function and as a decorator.

    -
    -
    Usage:
      -

    • As a function: Call udwf(func, input_types, return_type, volatility, -name).

      • -

    • As a decorator: Use @udwf(input_types, return_type, volatility, -name). When using udwf as a decorator, do not pass `func` -explicitly.

      • -
    -
    -
    Function example:

    ``` -import pyarrow as pa

    -
    -
    class BiasedNumbers(WindowEvaluator):
    -
    def __init__(self, start: int = 0) -> None:

    self.start = start

    -
    -
    def evaluate_all(self, values: list[pa.Array],

    num_rows: int) -> pa.Array: -return pa.array([self.start + i for i in range(num_rows)])

    -
    -
    -
    -
    def bias_10() -> BiasedNumbers:

    return BiasedNumbers(10)

    -
    -
    -

    udwf1 = udwf(BiasedNumbers, pa.int64(), pa.int64(), “immutable”) -udwf2 = udwf(bias_10, pa.int64(), pa.int64(), “immutable”) -udwf3 = udwf(lambda: BiasedNumbers(20), pa.int64(), pa.int64(), “immutable”)

    -

    ```

    -
    -
    Decorator example:

    ``` -@udwf(pa.int64(), pa.int64(), “immutable”) -def biased_numbers() -> BiasedNumbers:

    -
    -

    return BiasedNumbers(10)

    -
    -

    ```

    -
    -
    -
    -
    Parameters:
    -
      -

    • func – Only needed when calling as a function. Skip this argument when -using `udwf` as a decorator.

      • -

    • input_types – The data types of the arguments.

      • -

    • return_type – The data type of the return value.

      • -

    • volatility – See Volatility for allowed values.

      • -

    • name – A descriptive name for the function.

      • -
    -
    -
    Returns:
    -

    A user-defined window function that can be used in window function calls.

    -
    -
    -
    - -
    -
    -_udwf
    -
    - -
    - -
    -
    -datafusion.udf._R
    -
    - -
    -
    -datafusion.udf.udaf
    -
    - -
    -
    -datafusion.udf.udf
    -
    - -
    -
    -datafusion.udf.udwf
    -
    - -
    +

    Deprecated module for user defined functions.

    @@ -1422,6 +434,13 @@

    Module Contentsdatafusion.substrait

     + +
    +

    next

    +

    datafusion.unparser

    +
    + +     diff --git a/autoapi/datafusion/unparser/index.html b/autoapi/datafusion/unparser/index.html new file mode 100644 index 000000000..33d59e041 --- /dev/null +++ b/autoapi/datafusion/unparser/index.html @@ -0,0 +1,682 @@ + + + + + + + + datafusion.unparser — Apache Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + +
    +
    + + + + +
    + + +
    + + +
    +
    +
    +
    + + + + +
    + + +
    + +
    + On this page +
    + + +
    + +
    + +
    + + +
    + + + + + + +
    + +
    + +
    +

    datafusion.unparser

    +

    This module provides support for unparsing datafusion plans to SQL.

    +

    For additional information about unparsing, see https://docs.rs/datafusion-sql/latest/datafusion_sql/unparser/index.html

    +
    +

    Classes

    + + + + + + + + + +

    Dialect

    DataFusion data catalog.

    Unparser

    DataFusion unparser.

    +
    +
    +

    Module Contents

    +
    +
    +class datafusion.unparser.Dialect(dialect: datafusion._internal.unparser.Dialect)
    +

    DataFusion data catalog.

    +

    This constructor is not typically called by the end user.

    +
    +
    +static default() → Dialect
    +

    Create a new default dialect.

    +
    + +
    +
    +static duckdb() → Dialect
    +

    Create a new DuckDB dialect.

    +
    + +
    +
    +static mysql() → Dialect
    +

    Create a new MySQL dialect.

    +
    + +
    +
    +static postgres() → Dialect
    +

    Create a new PostgreSQL dialect.

    +
    + +
    +
    +static sqlite() → Dialect
    +

    Create a new SQLite dialect.

    +
    + +
    +
    +dialect
    +
    + +
    + +
    +
    +class datafusion.unparser.Unparser(dialect: Dialect)
    +

    DataFusion unparser.

    +

    This constructor is not typically called by the end user.

    +
    +
    +plan_to_sql(plan: datafusion.plan.LogicalPlan) → str
    +

    Convert a logical plan to a SQL string.

    +
    + +
    +
    +with_pretty(pretty: bool) → Unparser
    +

    Set the pretty flag.

    +
    + +
    +
    +unparser
    +
    + +
    + +
    +
    + + +
    + + + +
    + + +
    +

    previous

    +

    datafusion.udf

    +
    +     + +
    +

    next

    +

    datafusion.user_defined

    +
    + +     +
    + +
    + + +
    +
    + + + + +
    +
    + +
    +

    + © Copyright 2019-2024, Apache Software Foundation.
    +

    +
    + +
    +

    +Created using Sphinx 8.1.3.
    +

    +
    + +
    +

    Apache Arrow DataFusion, Arrow DataFusion, Apache, the Apache feather logo, and the Apache Arrow DataFusion project logo

    +

    are either registered trademarks or trademarks of The Apache Software Foundation in the United States and other countries.

    +
    +
    +
    + + + + \ No newline at end of file diff --git a/autoapi/datafusion/user_defined/index.html b/autoapi/datafusion/user_defined/index.html new file mode 100644 index 000000000..40d8f0714 --- /dev/null +++ b/autoapi/datafusion/user_defined/index.html @@ -0,0 +1,1597 @@ + + + + + + + + datafusion.user_defined — Apache Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + +
    +
    + + + + +
    + + +
    + + +
    +
    +
    +
    + + + + +
    + + +
    + +
    + On this page +
    + + +
    + +
    + +
    + + +
    + + + + + + +
    + +
    + +
    +

    datafusion.user_defined

    +

    Provides the user-defined functions for evaluation of dataframes.

    +
    +

    Attributes

    + + + + + + + + + + + + + + + + + + +

    _R

    udaf

    udf

    udtf

    udwf

    +
    +
    +

    Classes

    + + + + + + + + + + + + + + + + + + + + + + + + +

    Accumulator

    Defines how an AggregateUDF accumulates values.

    AggregateUDF

    Class for performing scalar user-defined functions (UDF).

    ScalarUDF

    Class for performing scalar user-defined functions (UDF).

    TableFunction

    Class for performing user-defined table functions (UDTF).

    Volatility

    Defines how stable or volatile a function is.

    WindowEvaluator

    Evaluator class for user-defined window functions (UDWF).

    WindowUDF

    Class for performing window user-defined functions (UDF).

    +
    +
    +

    Module Contents

    +
    +
    +class datafusion.user_defined.Accumulator
    +

    Defines how an AggregateUDF accumulates values.

    +
    +
    +abstract evaluate() → pyarrow.Scalar
    +

    Return the resultant value.

    +
    + +
    +
    +abstract merge(states: list[pyarrow.Array]) → None
    +

    Merge a set of states.

    +
    + +
    +
    +abstract state() → list[pyarrow.Scalar]
    +

    Return the current state.

    +
    + +
    +
    +abstract update(*values: pyarrow.Array) → None
    +

    Evaluate an array of values and update state.

    +
    + +
    + +
    +
    +class datafusion.user_defined.AggregateUDF(name: str, accumulator: Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str)
    +

    Class for performing scalar user-defined functions (UDF).

    +

    Aggregate UDFs operate on a group of rows and return a single value. See +also ScalarUDF for operating on a row by row basis.

    +

    Instantiate a user-defined aggregate function (UDAF).

    +

    See udaf() for a convenience function and argument +descriptions.

    +
    +
    +__call__(*args: datafusion.expr.Expr) → datafusion.expr.Expr
    +

    Execute the UDAF.

    +

    This function is not typically called by an end user. These calls will +occur during the evaluation of the dataframe.

    +
    + +
    +
    +static udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, AggregateUDF]
    +
    +static udaf(accum: Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → AggregateUDF
    +

    Create a new User-Defined Aggregate Function (UDAF).

    +

    This class allows you to define an aggregate function that can be used in +data aggregation or window function calls.

    +
    +
    Usage:
      +

    • As a function: udaf(accum, input_types, return_type, state_type, volatility, name).

      • +

    • As a decorator: @udaf(input_types, return_type, state_type, volatility, name). +When using udaf as a decorator, do not pass accum explicitly.

      • +
    +
    +
    +

    Function example:

    +

    If your Accumulator can be instantiated with no arguments, you +can simply pass it’s type as accum. If you need to pass additional +arguments to it’s constructor, you can define a lambda or a factory method. +During runtime the Accumulator will be constructed for every +instance in which this UDAF is used. The following examples are all valid:

    +
    import pyarrow as pa
+import pyarrow.compute as pc
+
+class Summarize(Accumulator):
+    def __init__(self, bias: float = 0.0):
+        self._sum = pa.scalar(bias)
+
+    def state(self) -> list[pa.Scalar]:
+        return [self._sum]
+
+    def update(self, values: pa.Array) -> None:
+        self._sum = pa.scalar(self._sum.as_py() + pc.sum(values).as_py())
+
+    def merge(self, states: list[pa.Array]) -> None:
+        self._sum = pa.scalar(self._sum.as_py() + pc.sum(states[0]).as_py())
+
+    def evaluate(self) -> pa.Scalar:
+        return self._sum
+
+def sum_bias_10() -> Summarize:
+    return Summarize(10.0)
+
+udaf1 = udaf(Summarize, pa.float64(), pa.float64(), [pa.float64()],
+    "immutable")
+udaf2 = udaf(sum_bias_10, pa.float64(), pa.float64(), [pa.float64()],
+    "immutable")
+udaf3 = udaf(lambda: Summarize(20.0), pa.float64(), pa.float64(),
+    [pa.float64()], "immutable")
+
    +
    +

    Decorator example::

    +
    @udaf(pa.float64(), pa.float64(), [pa.float64()], "immutable")
+def udf4() -> Summarize:
+    return Summarize(10.0)
+
    +
    +
    +
    Parameters:
    +
      +

    • accum – The accumulator python function. Only needed when calling as a +function. Skip this argument when using udaf as a decorator.

      • +

    • input_types – The data types of the arguments to accum.

      • +

    • return_type – The data type of the return value.

      • +

    • state_type – The data types of the intermediate accumulation.

      • +

    • volatility – See Volatility for allowed values.

      • +

    • name – A descriptive name for the function.

      • +
    +
    +
    Returns:
    +

    A user-defined aggregate function, which can be used in either data +aggregation or window function calls.

    +
    +
    +
    + +
    +
    +_udaf
    +
    + +
    + +
    +
    +class datafusion.user_defined.ScalarUDF(name: str, func: Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)
    +

    Class for performing scalar user-defined functions (UDF).

    +

    Scalar UDFs operate on a row by row basis. See also AggregateUDF for +operating on a group of rows.

    +

    Instantiate a scalar user-defined function (UDF).

    +

    See helper method udf() for argument details.

    +
    +
    +__call__(*args: datafusion.expr.Expr) → datafusion.expr.Expr
    +

    Execute the UDF.

    +

    This function is not typically called by an end user. These calls will +occur during the evaluation of the dataframe.

    +
    + +
    +
    +static udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, ScalarUDF]
    +
    +static udf(func: Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → ScalarUDF
    +

    Create a new User-Defined Function (UDF).

    +

    This class can be used both as either a function or a decorator.

    +
    +
    Usage:
      +

    • As a function: udf(func, input_types, return_type, volatility, name).

      • +

    • As a decorator: @udf(input_types, return_type, volatility, name). +When used a decorator, do not pass func explicitly.

      • +
    +
    +
    +
    +
    Parameters:
    +
      +

    • func (Callable, optional) – Only needed when calling as a function. +Skip this argument when using udf as a decorator.

      • +

    • input_types (list[pa.DataType]) – The data types of the arguments +to func. This list must be of the same length as the number of +arguments.

      • +

    • return_type (_R) – The data type of the return value from the function.

      • +

    • volatility (Volatility | str) – See Volatility for allowed values.

      • +

    • name (Optional[str]) – A descriptive name for the function.

      • +
    +
    +
    Returns:
    +

    A user-defined function that can be used in SQL expressions, +data aggregation, or window function calls.

    +
    +
    +

    Example: Using udf as a function:

    +
    def double_func(x):
+    return x * 2
+double_udf = udf(double_func, [pa.int32()], pa.int32(),
+"volatile", "double_it")
+
    +
    +

    Example: Using udf as a decorator:

    +
    @udf([pa.int32()], pa.int32(), "volatile", "double_it")
+def double_udf(x):
+    return x * 2
+
    +
    +
    + +
    +
    +_udf
    +
    + +
    + +
    +
    +class datafusion.user_defined.TableFunction(name: str, func: Callable[[], any])
    +

    Class for performing user-defined table functions (UDTF).

    +

    Table functions generate new table providers based on the +input expressions.

    +

    Instantiate a user-defined table function (UDTF).

    +

    See udtf() for a convenience function and argument +descriptions.

    +
    +
    +__call__(*args: datafusion.expr.Expr) → Any
    +

    Execute the UDTF and return a table provider.

    +
    + +
    +
    +__repr__() → str
    +

    User printable representation.

    +
    + +
    +
    +static _create_table_udf(func: Callable[Ellipsis, Any], name: str) → TableFunction
    +

    Create a TableFunction instance from function arguments.

    +
    + +
    +
    +static _create_table_udf_decorator(name: str | None = None) → Callable[[Callable[[], WindowEvaluator]], Callable[Ellipsis, datafusion.expr.Expr]]
    +

    Create a decorator for a WindowUDF.

    +
    + +
    +
    +static udtf(name: str) → Callable[Ellipsis, Any]
    +
    +static udtf(func: Callable[[], Any], name: str) → TableFunction
    +

    Create a new User-Defined Table Function (UDTF).

    +
    + +
    +
    +_udtf
    +
    + +
    + +
    +
    +class datafusion.user_defined.Volatility(*args, **kwds)
    +

    Bases: enum.Enum

    +

    Defines how stable or volatile a function is.

    +

    When setting the volatility of a function, you can either pass this +enumeration or a str. The str equivalent is the lower case value of the +name (“immutable”, “stable”, or “volatile”).

    +
    +
    +__str__() → str
    +

    Returns the string equivalent.

    +
    + +
    +
    +Immutable = 1
    +

    An immutable function will always return the same output when given the +same input.

    +

    DataFusion will attempt to inline immutable functions during planning.

    +
    + +
    +
    +Stable = 2
    +

    Returns the same value for a given input within a single queries.

    +

    A stable function may return different values given the same input across +different queries but must return the same value for a given input within a +query. An example of this is the Now function. DataFusion will attempt to +inline Stable functions during planning, when possible. For query +select col1, now() from t1, it might take a while to execute but now() +column will be the same for each output row, which is evaluated during +planning.

    +
    + +
    +
    +Volatile = 3
    +

    A volatile function may change the return value from evaluation to +evaluation.

    +

    Multiple invocations of a volatile function may return different results +when used in the same query. An example of this is the random() function. +DataFusion can not evaluate such functions during planning. In the query +select col1, random() from t1, random() function will be evaluated +for each output row, resulting in a unique random value for each row.

    +
    + +
    + +
    +
    +class datafusion.user_defined.WindowEvaluator
    +

    Evaluator class for user-defined window functions (UDWF).

    +

    It is up to the user to decide which evaluate function is appropriate.

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

    uses_window_frame

    supports_bounded_execution

    include_rank

    function_to_implement

    False (default)

    False (default)

    False (default)

    evaluate_all

    False

    True

    False

    evaluate

    False

    True/False

    True

    evaluate_all_with_rank

    True

    True/False

    True/False

    evaluate

    +
    +
    +evaluate(values: list[pyarrow.Array], eval_range: tuple[int, int]) → pyarrow.Scalar
    +

    Evaluate window function on a range of rows in an input partition.

    +

    This is the simplest and most general function to implement +but also the least performant as it creates output one row at +a time. It is typically much faster to implement stateful +evaluation using one of the other specialized methods on this +trait.

    +

    Returns a [ScalarValue] that is the value of the window +function within range for the entire partition. Argument +values contains the evaluation result of function arguments +and evaluation results of ORDER BY expressions. If function has a +single argument, values[1..] will contain ORDER BY expression results.

    +
    + +
    +
    +evaluate_all(values: list[pyarrow.Array], num_rows: int) → pyarrow.Array
    +

    Evaluate a window function on an entire input partition.

    +

    This function is called once per input partition for window functions that +do not use values from the window frame, such as +row_number(), +rank(), +dense_rank(), +percent_rank(), +cume_dist(), +lead(), +and lag().

    +

    It produces the result of all rows in a single pass. It +expects to receive the entire partition as the value and +must produce an output column with one output row for every +input row.

    +

    num_rows is required to correctly compute the output in case +len(values) == 0

    +

    Implementing this function is an optimization. Certain window +functions are not affected by the window frame definition or +the query doesn’t have a frame, and evaluate skips the +(costly) window frame boundary calculation and the overhead of +calling evaluate for each output row.

    +

    For example, the LAG built in window function does not use +the values of its window frame (it can be computed in one shot +on the entire partition with Self::evaluate_all regardless of the +window defined in the OVER clause)

    +
    lag(x, 1) OVER (ORDER BY z ROWS BETWEEN 2 PRECEDING AND 3 FOLLOWING)
+
    +
    +

    However, avg() computes the average in the window and thus +does use its window frame.

    +
    avg(x) OVER (PARTITION BY y ORDER BY z ROWS BETWEEN 2 PRECEDING AND 3 FOLLOWING)
+
    +
    +
    + +
    +
    +evaluate_all_with_rank(num_rows: int, ranks_in_partition: list[tuple[int, int]]) → pyarrow.Array
    +

    Called for window functions that only need the rank of a row.

    +

    Evaluate the partition evaluator against the partition using +the row ranks. For example, rank(col("a")) produces

    +
    a | rank
+- + ----
+A | 1
+A | 1
+C | 3
+D | 4
+D | 4
+
    +
    +

    For this case, num_rows would be 5 and the +ranks_in_partition would be called with

    +
    [
+    (0,1),
+    (2,2),
+    (3,4),
+]
+
    +
    +

    The user must implement this method if include_rank returns True.

    +
    + +
    +
    +get_range(idx: int, num_rows: int) → tuple[int, int]
    +

    Return the range for the window fuction.

    +

    If uses_window_frame flag is false. This method is used to +calculate required range for the window function during +stateful execution.

    +

    Generally there is no required range, hence by default this +returns smallest range(current row). e.g seeing current row is +enough to calculate window result (such as row_number, rank, +etc)

    +
    +
    Parameters:
    +
      +

    • idx: – Current index:

      • +

    • num_rows – Number of rows.

      • +
    +
    +
    +
    + +
    +
    +include_rank() → bool
    +

    Can this function be evaluated with (only) rank?

    +
    + +
    +
    +is_causal() → bool
    +

    Get whether evaluator needs future data for its result.

    +
    + +
    +
    +memoize() → None
    +

    Perform a memoize operation to improve performance.

    +

    When the window frame has a fixed beginning (e.g UNBOUNDED +PRECEDING), some functions such as FIRST_VALUE and +NTH_VALUE do not need the (unbounded) input once they have +seen a certain amount of input.

    +

    memoize is called after each input batch is processed, and +such functions can save whatever they need

    +
    + +
    +
    +supports_bounded_execution() → bool
    +

    Can the window function be incrementally computed using bounded memory?

    +
    + +
    +
    +uses_window_frame() → bool
    +

    Does the window function use the values from the window frame?

    +
    + +
    + +
    +
    +class datafusion.user_defined.WindowUDF(name: str, func: Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str)
    +

    Class for performing window user-defined functions (UDF).

    +

    Window UDFs operate on a partition of rows. See +also ScalarUDF for operating on a row by row basis.

    +

    Instantiate a user-defined window function (UDWF).

    +

    See udwf() for a convenience function and argument +descriptions.

    +
    +
    +__call__(*args: datafusion.expr.Expr) → datafusion.expr.Expr
    +

    Execute the UDWF.

    +

    This function is not typically called by an end user. These calls will +occur during the evaluation of the dataframe.

    +
    + +
    +
    +static _create_window_udf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
    +

    Create a WindowUDF instance from function arguments.

    +
    + +
    +
    +static _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → Callable[[Callable[[], WindowEvaluator]], Callable[Ellipsis, datafusion.expr.Expr]]
    +

    Create a decorator for a WindowUDF.

    +
    + +
    +
    +static _get_default_name(func: Callable) → str
    +

    Get the default name for a function based on its attributes.

    +
    + +
    +
    +static _normalize_input_types(input_types: pyarrow.DataType | list[pyarrow.DataType]) → list[pyarrow.DataType]
    +

    Convert a single DataType to a list if needed.

    +
    + +
    +
    +static udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, WindowUDF]
    +
    +static udwf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
    +

    Create a new User-Defined Window Function (UDWF).

    +

    This class can be used both as either a function or a decorator.

    +
    +
    Usage:
      +

    • As a function: udwf(func, input_types, return_type, volatility, name).

      • +

    • As a decorator: @udwf(input_types, return_type, volatility, name). +When using udwf as a decorator, do not pass func explicitly.

      • +
    +
    +
    +

    Function example:

    +
    import pyarrow as pa
+
+class BiasedNumbers(WindowEvaluator):
+    def __init__(self, start: int = 0) -> None:
+        self.start = start
+
+    def evaluate_all(self, values: list[pa.Array],
+        num_rows: int) -> pa.Array:
+        return pa.array([self.start + i for i in range(num_rows)])
+
+def bias_10() -> BiasedNumbers:
+    return BiasedNumbers(10)
+
+udwf1 = udwf(BiasedNumbers, pa.int64(), pa.int64(), "immutable")
+udwf2 = udwf(bias_10, pa.int64(), pa.int64(), "immutable")
+udwf3 = udwf(lambda: BiasedNumbers(20), pa.int64(), pa.int64(), "immutable")
+
    +
    +

    Decorator example:

    +
    @udwf(pa.int64(), pa.int64(), "immutable")
+def biased_numbers() -> BiasedNumbers:
+    return BiasedNumbers(10)
+
    +
    +
    +
    Parameters:
    +
      +

    • func – Only needed when calling as a function. Skip this argument when +using udwf as a decorator.

      • +

    • input_types – The data types of the arguments.

      • +

    • return_type – The data type of the return value.

      • +

    • volatility – See Volatility for allowed values.

      • +

    • name – A descriptive name for the function.

      • +
    +
    +
    Returns:
    +

    A user-defined window function that can be used in window function calls.

    +
    +
    +
    + +
    +
    +_udwf
    +
    + +
    + +
    +
    +datafusion.user_defined._R
    +
    + +
    +
    +datafusion.user_defined.udaf
    +
    + +
    +
    +datafusion.user_defined.udf
    +
    + +
    +
    +datafusion.user_defined.udtf
    +
    + +
    +
    +datafusion.user_defined.udwf
    +
    + +
    +
    + + +
    + + + +
    + + +
    +

    previous

    +

    datafusion.unparser

    +
    +     +
    + +
    + + +
    +
    + + + + +
    +
    + +
    +

    + © Copyright 2019-2024, Apache Software Foundation.
    +

    +
    + +
    +

    +Created using Sphinx 8.1.3.
    +

    +
    + +
    +

    Apache Arrow DataFusion, Arrow DataFusion, Apache, the Apache feather logo, and the Apache Arrow DataFusion project logo

    +

    are either registered trademarks or trademarks of The Apache Software Foundation in the United States and other countries.

    +
    +
    +
    + + + + \ No newline at end of file diff --git a/autoapi/index.html b/autoapi/index.html index 40c2c4c10..b8d920eaf 100644 --- a/autoapi/index.html +++ b/autoapi/index.html @@ -117,6 +117,11 @@ Data Sources

    • +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • @@ -398,10 +423,12 @@

    API Referencedatafusion diff --git a/contributor-guide/ffi.html b/contributor-guide/ffi.html index 7abc76616..2607e7220 100644 --- a/contributor-guide/ffi.html +++ b/contributor-guide/ffi.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/contributor-guide/introduction.html b/contributor-guide/introduction.html index 6a97a45fb..a8c329ba2 100644 --- a/contributor-guide/introduction.html +++ b/contributor-guide/introduction.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/genindex.html b/genindex.html index 6d65db2fd..3044426d6 100644 --- a/genindex.html +++ b/genindex.html @@ -114,6 +114,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -272,6 +277,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -292,6 +302,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -344,6 +359,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • @@ -442,13 +467,19 @@

    _

  • __call__() (datafusion.AggregateUDF method)
    • - - + -
  • _create_window_udf() (datafusion.udf.WindowUDF static method) +
  • _build_expandable_cell() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
    • +
  • _build_html_footer() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
    • +
  • _build_html_header() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
    • +
  • _build_regular_cell() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
    • +
  • _build_table_body() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
    • +
  • _build_table_container_start() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
    • +
  • _build_table_header() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
    • +
  • _create_table_udf() (datafusion.TableFunction static method) + +
    • +
  • _create_table_udf_decorator() (datafusion.TableFunction static method) + +
    • +
  • _create_window_udf() (datafusion.user_defined.WindowUDF static method)
    • -
  • _create_window_udf_decorator() (datafusion.udf.WindowUDF static method) +
  • _create_window_udf_decorator() (datafusion.user_defined.WindowUDF static method)
    • -
  • _get_default_name() (datafusion.udf.WindowUDF static method) +
  • _custom_cell_builder (datafusion.html_formatter.DataFrameHtmlFormatter attribute) +
    • +
  • _custom_header_builder (datafusion.html_formatter.DataFrameHtmlFormatter attribute) +
    • +
  • _default_formatter (datafusion.html_formatter.FormatterManager attribute) +
    • +
  • _format_cell_value() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
    • +
  • _get_cell_value() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
    • +
  • _get_default_css() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
    • +
  • _get_default_name() (datafusion.user_defined.WindowUDF static method)
    • -
  • _normalize_input_types() (datafusion.udf.WindowUDF static method) +
  • _get_javascript() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
    • +
  • _normalize_input_types() (datafusion.user_defined.WindowUDF static method)
    • +
  • _refresh_formatter_reference() (in module datafusion.html_formatter) +
  • _repr_html_() (datafusion.dataframe.DataFrame method) +
    • +
  • _styles_loaded (datafusion.html_formatter.DataFrameHtmlFormatter attribute)
  • _to_pyarrow_types (datafusion.Expr attribute) @@ -667,24 +746,36 @@

    _

  • (datafusion.expr.Expr attribute)
    • +
  • _type_formatters (datafusion.html_formatter.DataFrameHtmlFormatter attribute) +
  • _udaf (datafusion.AggregateUDF attribute)
  • _udf (datafusion.ScalarUDF attribute)
    • +
  • _udtf (datafusion.TableFunction attribute) + +
    • -
  • _udwf (datafusion.udf.WindowUDF attribute) +
  • _udwf (datafusion.user_defined.WindowUDF attribute)
    • +
  • _validate_bool() (in module datafusion.html_formatter) +
    • +
  • _validate_positive_int() (in module datafusion.html_formatter) +
  • _window_frame (datafusion.expr.Window attribute)
    • @@ -693,18 +784,36 @@

    _

    A

    - + @@ -861,8 +1048,14 @@

    B

  • bit_and() (in module datafusion.functions)
    • -
  • bit_length() (in module datafusion.functions) +
  • bit_length() (datafusion.Expr method) + +
  • bit_or() (in module datafusion.functions)
    • @@ -875,8 +1068,14 @@

    B

  • BROTLI (datafusion.dataframe.Compression attribute)
    • -
  • btrim() (in module datafusion.functions) +
  • btrim() (datafusion.Expr method) + +
  • build_table() (datafusion.input.base.BaseInputSource method)
    • -
  • cardinality() (in module datafusion.functions) +
  • cardinality() (datafusion.Expr method) + +
  • Case (in module datafusion.expr)
  • case() (in module datafusion.functions) @@ -933,34 +1138,74 @@

    C

  • catalog() (datafusion.context.SessionContext method)
    • -
  • cbrt() (in module datafusion.functions) +
  • cbrt() (datafusion.Expr method) + +
    • +
  • ceil() (datafusion.Expr method) + +
    • +
  • CellFormatter (class in datafusion.html_formatter)
    • -
  • char_length() (in module datafusion.functions) +
  • char_length() (datafusion.Expr method) + +
    • +
  • character_length() (datafusion.Expr method) + +
  • children() (datafusion.ExecutionPlan method)
    • -
  • chr() (in module datafusion.functions) +
  • chr() (datafusion.Expr method) + +
  • coalesce() (in module datafusion.functions)
    • -
  • col() (in module datafusion) +
  • col (in module datafusion)
    • +
  • col() (in module datafusion.functions) +
  • collect() (datafusion.dataframe.DataFrame method)
  • collect_partitioned() (datafusion.dataframe.DataFrame method)
    • +
  • column (in module datafusion) + +
  • Column (in module datafusion.expr)
    • @@ -969,8 +1214,6 @@

    C

  • column_name() (datafusion.Expr method) @@ -993,18 +1236,44 @@

    C

  • (datafusion.RuntimeEnvBuilder attribute)
  • (datafusion.SessionConfig attribute) +
    • + +
  • configure_formatter() (in module datafusion) + +
  • Consumer (class in datafusion.substrait) +
    • +
  • CopyTo (in module datafusion.expr)
  • corr() (in module datafusion.functions)
    • -
  • cos() (in module datafusion.functions) +
  • cos() (datafusion.Expr method) + +
    • +
  • cosh() (datafusion.Expr method) + +
    • +
  • cot() (datafusion.Expr method) + +
  • count() (datafusion.dataframe.DataFrame method)
    • @@ -1054,6 +1337,8 @@

    D

  • DataFrame (class in datafusion.dataframe) +
    • +
  • DataFrameHtmlFormatter (class in datafusion.html_formatter)
  • datafusion @@ -1067,6 +1352,13 @@

    D

    • +
  • + datafusion.col + +
  • @@ -1095,6 +1387,13 @@

    D

    • +
  • + datafusion.html_formatter + +
  • @@ -1158,16 +1457,30 @@

    D

    • +
  • + datafusion.unparser + +
    • +
  • + datafusion.user_defined + +
  • date_bin() (in module datafusion.functions)
    • - - + +
  • Deallocate (in module datafusion.expr) +
  • decode() (in module datafusion.functions)
    • -
  • degrees() (in module datafusion.functions) +
  • default() (datafusion.unparser.Dialect static method) +
    • +
  • DefaultStyleProvider (class in datafusion.html_formatter) +
    • +
  • degrees() (datafusion.Expr method) + +
  • dense_rank() (in module datafusion.functions)
  • deregister_table() (datafusion.context.SessionContext method)
  • describe() (datafusion.dataframe.DataFrame method) +
    • +
  • DescribeTable (in module datafusion.expr)
  • deserialize() (datafusion.substrait.Serde static method)
    • @@ -1195,6 +1522,10 @@

    D

  • df (datafusion.dataframe.DataFrame attribute)
  • DFSchema (in module datafusion) +
    • +
  • Dialect (class in datafusion.unparser) +
    • +
  • dialect (datafusion.unparser.Dialect attribute)
  • digest() (in module datafusion.functions)
    • @@ -1246,9 +1577,19 @@

    D

  • (datafusion.expr.Expr method)
    • +
  • DmlStatement (in module datafusion.expr) +
  • drop() (datafusion.dataframe.DataFrame method) +
    • +
  • DropCatalogSchema (in module datafusion.expr) +
    • +
  • DropFunction (in module datafusion.expr)
  • DropTable (in module datafusion.expr) +
    • +
  • DropView (in module datafusion.expr) +
    • +
  • duckdb() (datafusion.unparser.Dialect static method)
    • @@ -1256,11 +1597,19 @@

    D

    E

    + - - +
  • Exists (in module datafusion.expr)
    • -
  • exp() (in module datafusion.functions) +
  • exp() (datafusion.Expr method) + +
  • Explain (in module datafusion.expr)
  • explain() (datafusion.dataframe.DataFrame method) @@ -1336,7 +1693,15 @@

    E

    F

    -
  • fill_null() (datafusion.Expr method) +
  • fill_null() (datafusion.dataframe.DataFrame method)
    • @@ -1364,12 +1731,28 @@

    F

  • first_value() (in module datafusion.functions)
    • -
  • flatten() (in module datafusion.functions) +
  • flatten() (datafusion.Expr method) + +
    • +
  • floor() (datafusion.Expr method) + +
    • @@ -1408,14 +1797,34 @@

    G

    		•
  • is_current_row() (datafusion.expr.WindowFrameBound method)
    • -     		+
    @@ -1582,8 +2009,14 @@

    L

  • left() (in module datafusion.functions)
    • -
  • length() (in module datafusion.functions) +
  • length() (datafusion.Expr method) + +
  • levenshtein() (in module datafusion.functions)
  • Like (in module datafusion.expr) @@ -1598,10 +2031,22 @@

    L

  • list_concat() (in module datafusion.functions)
    • -
  • list_dims() (in module datafusion.functions) +
  • list_dims() (datafusion.Expr method) + +
    • +
  • list_distinct() (datafusion.Expr method) + +
  • list_element() (in module datafusion.functions)
  • list_except() (in module datafusion.functions) @@ -1614,10 +2059,22 @@

    L

  • list_join() (in module datafusion.functions)
    • -
  • list_length() (in module datafusion.functions) +
  • list_length() (datafusion.Expr method) + +
    • +
  • list_ndims() (datafusion.Expr method) + +
  • list_position() (in module datafusion.functions)
  • list_positions() (in module datafusion.functions) @@ -1666,8 +2123,14 @@

    L

  • (in module datafusion)
    • -
  • ln() (in module datafusion.functions) +
  • ln() (datafusion.Expr method) + +
  • LocalFileSystem (in module datafusion.object_store)
  • LocationInputPlugin (class in datafusion.input) @@ -1678,10 +2141,22 @@

    L

  • log() (in module datafusion.functions)
    • -
  • log10() (in module datafusion.functions) +
  • log10() (datafusion.Expr method) + +
    • +
  • log2() (datafusion.Expr method) + +
  • logical_plan() (datafusion.dataframe.DataFrame method)
  • LogicalPlan (class in datafusion) @@ -1690,12 +2165,24 @@

    L

  • (class in datafusion.plan)
    • -
  • lower() (in module datafusion.functions) +
  • lower() (datafusion.Expr method) + +
  • lpad() (in module datafusion.functions)
    • -
  • ltrim() (in module datafusion.functions) +
  • ltrim() (datafusion.Expr method) + +
  • LZ4 (datafusion.dataframe.Compression attribute)
  • LZ4_RAW (datafusion.dataframe.Compression attribute) @@ -1714,23 +2201,39 @@

    M

  • max() (in module datafusion.functions)
    • -
  • md5() (in module datafusion.functions) +
  • max_cell_length (datafusion.html_formatter.DataFrameHtmlFormatter attribute) +
    • +
  • max_height (datafusion.html_formatter.DataFrameHtmlFormatter attribute)
    • +
  • max_memory_bytes (datafusion.html_formatter.DataFrameHtmlFormatter attribute) +
    • +
  • max_width (datafusion.html_formatter.DataFrameHtmlFormatter attribute) +
    • +
  • md5() (datafusion.Expr method) + +
  • mean() (in module datafusion.functions)
  • median() (in module datafusion.functions)
    • -
  • memoize() (datafusion.udf.WindowEvaluator method) +
  • memoize() (datafusion.user_defined.WindowEvaluator method)
  • merge() (datafusion.Accumulator method)
  • MicrosoftAzure (in module datafusion.object_store)
  • min() (in module datafusion.functions) +
    • +
  • min_rows_display (datafusion.html_formatter.DataFrameHtmlFormatter attribute)
  • module @@ -1739,6 +2242,8 @@

    M

  • datafusion
  • datafusion.catalog +
    • +
  • datafusion.col
  • datafusion.context
    • @@ -1747,6 +2252,8 @@

    M

  • datafusion.expr
  • datafusion.functions +
    • +
  • datafusion.html_formatter
  • datafusion.input
    • @@ -1765,9 +2272,17 @@

    M

  • datafusion.substrait
  • datafusion.udf +
    • +
  • datafusion.unparser +
    • +
  • datafusion.user_defined
    • +

    N

    @@ -1823,7 +2338,15 @@

    N

    O

    + - - + - + + + + + + + + + + + + +
    +
  • table_exist() (datafusion.context.SessionContext method)
    • +
  • TableFunction (class in datafusion) + +
  • TableProviderExportable (class in datafusion.context)
  • TableScan (in module datafusion.expr)
  • tail() (datafusion.dataframe.DataFrame method)
    • -
  • tan() (in module datafusion.functions) +
  • tan() (datafusion.Expr method) + +
    • +
  • tanh() (datafusion.Expr method) + +
  • to_arrow_table() (datafusion.dataframe.DataFrame method)
    • -
  • to_hex() (in module datafusion.functions) +
  • to_hex() (datafusion.Expr method) + +
  • to_pandas() (datafusion.dataframe.DataFrame method)
  • to_polars() (datafusion.dataframe.DataFrame method) @@ -2317,12 +2968,28 @@

    T

  • (datafusion.plan.LogicalPlan method)
    • +
  • TransactionAccessMode (in module datafusion.expr) +
    • +
  • TransactionConclusion (in module datafusion.expr) +
    • +
  • TransactionEnd (in module datafusion.expr) +
    • +
  • TransactionIsolationLevel (in module datafusion.expr) +
    • +
  • TransactionStart (in module datafusion.expr) +
  • transform() (datafusion.dataframe.DataFrame method)
  • translate() (in module datafusion.functions)
    • -
  • trim() (in module datafusion.functions) +
  • trim() (datafusion.Expr method) + +
  • trunc() (in module datafusion.functions)
  • TryCast (in module datafusion.expr) @@ -2342,34 +3009,46 @@

    U

  • udaf (in module datafusion)
  • udaf() (datafusion.AggregateUDF static method)
  • udf (in module datafusion)
  • udf() (datafusion.ScalarUDF static method)
    • +
  • udtf (in module datafusion) + +
    • +
  • udtf() (datafusion.TableFunction static method) + +
  • udwf (in module datafusion)
    • -
  • udwf() (datafusion.udf.WindowUDF static method) +
  • udwf() (datafusion.user_defined.WindowUDF static method)
    • -
  • WindowEvaluator (class in datafusion.udf) +
  • WindowEvaluator (class in datafusion.user_defined)
  • WindowExpr (in module datafusion.expr)
    • @@ -2472,7 +3165,7 @@

    W

  • WindowUDF (class in datafusion)
  • with_allow_ddl() (datafusion.context.SQLOptions method) @@ -2523,14 +3216,14 @@

    W

  • (datafusion.RuntimeEnvBuilder method)
    • -     		diff --git a/objects.inv b/objects.inv index b94584081409bbada82a892fc86efc5b9e475192..da03cabba9cb48d4da33f9ea456f318ceee93134 100644 GIT binary patch delta 7762 zcmV-Y9+qkjE-}Na}mGe5N-8Z#$$rY( zpMPRJqube97x`a&vb+D8-c9xiX0Ow)}D;|sk5nI%a|@;pgk@-$1Tj4UmSXf4^IGB+E8 zYiQ$g_SXEFi`D3Ys;{4=d(P=vXzaD&j=SD`A zZUdNQi>Q)qIe)PQ(s0awc|`r(Z)sX-^Vefe_~_C(pqO4NX(?lR=@Czo=cKIjH@f5x zndzG4nWP*lj~P=YhdW?gV$*XCMO{i!B&8HuKoLtKHM5_RR8&5rhF?;tcX41X;xk&x zhz4Cs(~e1&#WiD3;Sd!19RRYTAP`gMw16OK00`q7(|_IoKsiL=W>DgY5_#jvZ5K=z|h)k zMOEEFmSRZu;khGHiswY{N^fSy-6C12$V`z`Kp@t!jGU3^d`M|bvy2r`Af*{kH3*Cr zrQU&%a(~KKdJTf&U}aT`GFg!H8yL)(#2ldH>z*c-u_%=?7R_KB01;jFns5L_Y&I5D zKT{f;lLgZ-9b#cd;Ubce5-vDPNuJnAglL$|7&pUW^stc<72A{2g^Wf}md7I2M8edz zC6QE9Fr17fh`cH|2n3|@McV`bCP6A<+gwIhl7G_JTWRKe0Lm4}q<}Cc=(da}$ao8O zY5Jj%jKmHOOP1SlmxExc93VSpc!`DNrfj31k;`0&=$zOY%8IkCX3?F1ai&ue+xnPF zxX=()Wl0c}_{PW74=N+4R%akjwA>6-5N}d72V~T9EV#SlAh%~adGyeg$F`eXtbYD$ zJb&X=G~zjW$jbrj@FM#ql3>S!L`zC^L8D(og)uaN8m^F;u~`?f&wjCquBZJ1Q*>_1 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  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • @@ -399,6 +424,11 @@

    Python Module Index

    		    datafusion.catalog
        + datafusion.col +
        @@ -419,6 +449,11 @@

    Python Module Index

    		    datafusion.functions
        + datafusion.html_formatter +
        @@ -464,6 +499,16 @@

    Python Module Index

    		    datafusion.udf
        + datafusion.unparser +
        + datafusion.user_defined +
    diff --git a/search.html b/search.html index 6461c9167..6602d8b2f 100644 --- a/search.html +++ b/search.html @@ -121,6 +121,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -279,6 +284,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -299,6 +309,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -351,6 +366,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/searchindex.js b/searchindex.js index 143eae672..bd9247ebd 100644 --- a/searchindex.js +++ b/searchindex.js @@ -1 +1 @@ -Search.setIndex({"alltitles": {"API Reference": [[15, null]], "Aggregate Functions": [[20, "aggregate-functions"], [27, "aggregate-functions"], [29, "aggregate-functions"]], "Aggregation": [[20, null]], "Alternative Approach": [[16, "alternative-approach"]], "Arrays": [[22, "arrays"]], "Arrow": [[33, null]], "Attributes": [[3, "attributes"], [5, "attributes"], [10, "attributes"], [14, "attributes"]], "Available Functions": [[29, "available-functions"]], "Avro": [[34, null]], "Basic Operations": [[21, null]], "Boolean": [[22, "boolean"]], "CSV": [[35, null]], "Casting": [[23, "casting"]], "Classes": [[0, "classes"], [1, "classes"], [2, "classes"], [3, "classes"], [5, "classes"], [6, "classes"], [7, "classes"], [8, "classes"], [11, "classes"], [12, "classes"], [13, "classes"], [14, "classes"]], "Column": [[22, "column"]], "Column Selections": [[26, 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"datafusion.record_batch": [[12, "module-datafusion.record_batch", false]], "datafusion.substrait": [[13, "module-datafusion.substrait", false]], "datafusion.udf": [[14, "module-datafusion.udf", false]], "date_bin() (in module datafusion.functions)": [[4, "datafusion.functions.date_bin", false]], "date_part() (in module datafusion.functions)": [[4, "datafusion.functions.date_part", false]], "date_trunc() (in module datafusion.functions)": [[4, "datafusion.functions.date_trunc", false]], "datepart() (in module datafusion.functions)": [[4, "datafusion.functions.datepart", false]], "datetrunc() (in module datafusion.functions)": [[4, "datafusion.functions.datetrunc", false]], "db (datafusion.catalog.database attribute)": [[0, "datafusion.catalog.Database.db", false]], "db (datafusion.database attribute)": [[5, "datafusion.Database.db", false]], "decode() (in module datafusion.functions)": [[4, "datafusion.functions.decode", false]], "degrees() (in module datafusion.functions)": [[4, 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module datafusion.functions)": [[4, "datafusion.functions.in_list", false]], "include_rank() (datafusion.udf.windowevaluator method)": [[14, "datafusion.udf.WindowEvaluator.include_rank", false]], "initcap() (in module datafusion.functions)": [[4, "datafusion.functions.initcap", false]], "inlist (in module datafusion.expr)": [[3, "datafusion.expr.InList", false]], "inputs() (datafusion.logicalplan method)": [[5, "datafusion.LogicalPlan.inputs", false]], "inputs() (datafusion.plan.logicalplan method)": [[11, "datafusion.plan.LogicalPlan.inputs", false]], "insubquery (in module datafusion.expr)": [[3, "datafusion.expr.InSubquery", false]], "intersect() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.intersect", false]], "into_view() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.into_view", false]], "is_causal() (datafusion.udf.windowevaluator method)": [[14, "datafusion.udf.WindowEvaluator.is_causal", false]], "is_correct_input() (datafusion.input.base.baseinputsource method)": [[6, "datafusion.input.base.BaseInputSource.is_correct_input", false]], "is_correct_input() (datafusion.input.location.locationinputplugin method)": [[8, "datafusion.input.location.LocationInputPlugin.is_correct_input", false]], "is_correct_input() (datafusion.input.locationinputplugin method)": [[7, "datafusion.input.LocationInputPlugin.is_correct_input", false]], "is_current_row() (datafusion.expr.windowframebound method)": [[3, "datafusion.expr.WindowFrameBound.is_current_row", false]], "is_following() (datafusion.expr.windowframebound method)": [[3, "datafusion.expr.WindowFrameBound.is_following", false]], "is_not_null() (datafusion.expr method)": [[5, "datafusion.Expr.is_not_null", false]], "is_not_null() (datafusion.expr.expr method)": [[3, "datafusion.expr.Expr.is_not_null", false]], "is_null() (datafusion.expr method)": [[5, "datafusion.Expr.is_null", false]], "is_null() (datafusion.expr.expr method)": [[3, 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false]], "serde (class in datafusion.substrait)": [[15, "datafusion.substrait.Serde", false]], "serialize() (datafusion.substrait.serde static method)": [[15, "datafusion.substrait.Serde.serialize", false]], "serialize_bytes() (datafusion.substrait.serde static method)": [[15, "datafusion.substrait.Serde.serialize_bytes", false]], "serialize_to_plan() (datafusion.substrait.serde static method)": [[15, "datafusion.substrait.Serde.serialize_to_plan", false]], "session_id() (datafusion.context.sessioncontext method)": [[2, "datafusion.context.SessionContext.session_id", false]], "sessionconfig (class in datafusion)": [[7, "datafusion.SessionConfig", false]], "sessionconfig (class in datafusion.context)": [[2, "datafusion.context.SessionConfig", false]], "sessioncontext (class in datafusion.context)": [[2, "datafusion.context.SessionContext", false]], "set() (datafusion.context.sessionconfig method)": [[2, "datafusion.context.SessionConfig.set", false]], "set() (datafusion.sessionconfig 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a/user-guide/basics.html b/user-guide/basics.html index ab965779a..3596aa2c1 100644 --- a/user-guide/basics.html +++ b/user-guide/basics.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • @@ -413,8 +438,9 @@

    Concepts

    -

    In this section, we will cover a basic example to introduce a few key concepts. We will use the same -source file as described in the Introduction, the Pokemon data set.

    +

    In this section, we will cover a basic example to introduce a few key concepts. We will use the +2021 Yellow Taxi Trip Records (download), +from the TLC Trip Record Data.

    In [1]: from datafusion import SessionContext, col, lit, functions as f
 
 In [2]: ctx = SessionContext()
@@ -483,6 +509,7 @@ 
    DataFrameSessionContext, such as read_csv, and can then be modified by
 calling the transformation methods, such as filter(), select(), aggregate(),
 and limit() to build up a query definition.
    
+
    For more details on working with DataFrames, including visualization options and conversion to other formats, see DataFrames.

    Expressions

    diff --git a/user-guide/common-operations/aggregations.html b/user-guide/common-operations/aggregations.html index 9235368c2..f35abc6c5 100644 --- a/user-guide/common-operations/aggregations.html +++ b/user-guide/common-operations/aggregations.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • @@ -579,15 +604,15 @@

    Distinct | Type 1 | Type 2 List | +----------+--------------------------------------------------+ | Bug | [, Grass, Flying, Poison] | -| Poison | [, Flying, Ground] | -| Electric | [, Steel, Flying] | +| Poison | [, Ground, Flying] | +| Electric | [Flying, Steel, ] | | Fairy | [] | -| Normal | [, Flying, Fairy] | +| Normal | [Flying, Fairy, ] | | Ice | [Flying, Psychic] | | Grass | [Psychic, , Poison] | -| Fire | [Dragon, Flying, ] | -| Water | [Fighting, Flying, Psychic, Poison, , Dark, Ice] | -| Ground | [Rock, ] | +| Fire | [Flying, , Dragon] | +| Water | [Ice, Flying, , Fighting, Dark, Psychic, Poison] | +| Ground | [, Rock] | +----------+--------------------------------------------------+ Data truncated. @@ -602,15 +627,15 @@

    Distinct +----------+------------------------------------------------+ | Type 1 | Type 2 List | +----------+------------------------------------------------+ -| Bug | [Flying, Grass, Poison] | -| Poison | [Flying, Ground] | +| Bug | [Poison, Grass, Flying] | +| Poison | [Ground, Flying] | | Electric | [Flying, Steel] | | Normal | [Flying, Fairy] | | Ice | [Flying, Psychic] | -| Grass | [Poison, Psychic] | +| Grass | [Psychic, Poison] | | Fire | [Flying, Dragon] | -| Water | [Psychic, Flying, Fighting, Dark, Poison, Ice] | -| Rock | [Ground, Water, Flying] | +| Water | [Dark, Poison, Psychic, Flying, Ice, Fighting] | +| Rock | [Flying, Water, Ground] | | Ghost | [Poison] | +----------+------------------------------------------------+ Data truncated. @@ -621,15 +646,15 @@

    Distinct +----------+------------------------------------------------+ | Type 1 | Type 2 List | +----------+------------------------------------------------+ -| Bug | [Flying, Grass, Poison] | -| Poison | [Flying, Ground] | +| Bug | [Grass, Flying, Poison] | +| Poison | [Ground, Flying] | | Electric | [Steel, Flying] | | Fairy | | | Normal | [Fairy, Flying] | -| Ice | [Flying, Psychic] | +| Ice | [Psychic, Flying] | | Grass | [Psychic, Poison] | -| Fire | [Flying, Dragon] | -| Water | [Ice, Dark, Fighting, Flying, Poison, Psychic] | +| Fire | [Dragon, Flying] | +| Water | [Ice, Flying, Poison, Dark, Psychic, Fighting] | | Ground | [Rock] | +----------+------------------------------------------------+ Data truncated. diff --git a/user-guide/common-operations/basic-info.html b/user-guide/common-operations/basic-info.html index f7c661210..3657b7419 100644 --- a/user-guide/common-operations/basic-info.html +++ b/user-guide/common-operations/basic-info.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • @@ -414,11 +439,11 @@

    Basic Operations+-----+---------+--------+--------+ | nrs | names | random | groups | +-----+---------+--------+--------+ -| 1 | python | 832 | A | -| 2 | ruby | 669 | A | -| 3 | java | 803 | B | -| 4 | haskell | 531 | C | -| 5 | go | 774 | B | +| 1 | python | 316 | A | +| 2 | ruby | 698 | A | +| 3 | java | 568 | B | +| 4 | haskell | 804 | C | +| 5 | go | 513 | B | +-----+---------+--------+--------+ @@ -429,8 +454,8 @@

    Basic Operations+-----+--------+--------+--------+ | nrs | names | random | groups | +-----+--------+--------+--------+ -| 1 | python | 832 | A | -| 2 | ruby | 669 | A | +| 1 | python | 316 | A | +| 2 | ruby | 698 | A | +-----+--------+--------+--------+ @@ -448,28 +473,28 @@

    Basic Operations
    In [8]: df.to_pandas()
 Out[8]: 
    nrs    names  random groups
-0    1   python     832      A
-1    2     ruby     669      A
-2    3     java     803      B
-3    4  haskell     531      C
-4    5       go     774      B
+0    1   python     316      A
+1    2     ruby     698      A
+2    3     java     568      B
+3    4  haskell     804      C
+4    5       go     513      B

    describe() shows a quick statistic summary of your data:

    In [9]: df.describe()
 Out[9]: 
 DataFrame()
-+------------+--------------------+-------+--------------------+--------+
-| describe   | nrs                | names | random             | groups |
-+------------+--------------------+-------+--------------------+--------+
-| count      | 5.0                | 5     | 5.0                | 5      |
-| null_count | 0.0                | 0     | 0.0                | 0      |
-| mean       | 3.0                | null  | 721.8              | null   |
-| std        | 1.5811388300841898 | null  | 123.14097612086726 | null   |
-| min        | 1.0                | go    | 531.0              | A      |
-| max        | 5.0                | ruby  | 832.0              | C      |
-| median     | 3.0                | null  | 774.0              | null   |
-+------------+--------------------+-------+--------------------+--------+
++------------+--------------------+-------+-------------------+--------+
+| describe   | nrs                | names | random            | groups |
++------------+--------------------+-------+-------------------+--------+
+| count      | 5.0                | 5     | 5.0               | 5      |
+| null_count | 0.0                | 0     | 0.0               | 0      |
+| mean       | 3.0                | null  | 579.8             | null   |
+| std        | 1.5811388300841898 | null  | 186.0301050905471 | null   |
+| min        | 1.0                | go    | 316.0             | A      |
+| max        | 5.0                | ruby  | 804.0             | C      |
+| median     | 3.0                | null  | 568.0             | null   |
++------------+--------------------+-------+-------------------+--------+

    diff --git a/user-guide/common-operations/expressions.html b/user-guide/common-operations/expressions.html index 0fe3e2938..291245092 100644 --- a/user-guide/common-operations/expressions.html +++ b/user-guide/common-operations/expressions.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/user-guide/common-operations/functions.html b/user-guide/common-operations/functions.html index 803c2669e..61123ed4d 100644 --- a/user-guide/common-operations/functions.html +++ b/user-guide/common-operations/functions.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • @@ -375,35 +400,54 @@ @@ -426,7 +456,7 @@

    User-Defined FunctionsScalar Functions

    When writing a user-defined function that can operate on a row by row basis, these are called Scalar Functions. You can define your own scalar function by calling -udf() .

    +udf() .

    The basic definition of a scalar UDF is a python function that takes one or more pyarrow arrays and returns a single array as output. DataFusion scalar UDFs operate on an entire batch of records at a time, though the @@ -512,9 +542,9 @@

    Scalar Functions

    Aggregate Functions

    -

    The udaf() function allows you to define User-Defined +

    The udaf() function allows you to define User-Defined Aggregate Functions (UDAFs). To use this you must implement an -Accumulator that determines how the aggregation is performed.

    +Accumulator that determines how the aggregation is performed.

    When defining a UDAF there are four methods you need to implement. The update function takes the array(s) of input and updates the internal state of the accumulator. You should define this function to have as many input arguments as you will pass when calling the UDAF. Since aggregation may be @@ -568,8 +598,8 @@

    Aggregate Functions

    Window Functions

    To implement a User-Defined Window Function (UDWF) you must call the -udwf() function using a class that implements the abstract -class WindowEvaluator.

    +udwf() function using a class that implements the abstract +class WindowEvaluator.

    There are three methods of evaluation of UDWFs.

    diff --git a/user-guide/common-operations/windows.html b/user-guide/common-operations/windows.html index 4b2be12cd..dcd5e5058 100644 --- a/user-guide/common-operations/windows.html +++ b/user-guide/common-operations/windows.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/user-guide/configuration.html b/user-guide/configuration.html index b29bfff4a..5cd45975a 100644 --- a/user-guide/configuration.html +++ b/user-guide/configuration.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/user-guide/data-sources.html b/user-guide/data-sources.html index 64be39f69..f1be5894f 100644 --- a/user-guide/data-sources.html +++ b/user-guide/data-sources.html @@ -34,7 +34,7 @@ - + @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • @@ -650,10 +675,10 @@

    Custom Table ProviderConcepts

     - +

    next

    -

    Common Operations

    +

    DataFrames

     diff --git a/user-guide/dataframe.html b/user-guide/dataframe.html new file mode 100644 index 000000000..2c27110bd --- /dev/null +++ b/user-guide/dataframe.html @@ -0,0 +1,705 @@ + + + + + + + + DataFrames — Apache Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + +
    +
    + + + + +
    + + +
    + + +
    +
    +
    +
    + + + + +
    + + +
    + +
    + On this page +
    + + +
    + +
    + +
    + + +
    + + + + + + +
    + +
    + +
    +

    DataFrames

    +
    +

    Overview

    +

    DataFusion’s DataFrame API provides a powerful interface for building and executing queries against data sources. +It offers a familiar API similar to pandas and other DataFrame libraries, but with the performance benefits of Rust +and Arrow.

    +

    A DataFrame represents a logical plan that can be composed through operations like filtering, projection, and aggregation. +The actual execution happens when terminal operations like collect() or show() are called.

    +
    +
    +

    Basic Usage

    +
    import datafusion
+from datafusion import col, lit
+
+# Create a context and register a data source
+ctx = datafusion.SessionContext()
+ctx.register_csv("my_table", "path/to/data.csv")
+
+# Create and manipulate a DataFrame
+df = ctx.sql("SELECT * FROM my_table")
+
+# Or use the DataFrame API directly
+df = (ctx.table("my_table")
+      .filter(col("age") > lit(25))
+      .select([col("name"), col("age")]))
+
+# Execute and collect results
+result = df.collect()
+
+# Display the first few rows
+df.show()
+
    +
    +
    +
    +

    HTML Rendering

    +

    When working in Jupyter notebooks or other environments that support HTML rendering, DataFrames will +automatically display as formatted HTML tables, making it easier to visualize your data.

    +

    The _repr_html_ method is called automatically by Jupyter to render a DataFrame. This method +controls how DataFrames appear in notebook environments, providing a richer visualization than +plain text output.

    +
    +
    +

    Customizing HTML Rendering

    +

    You can customize how DataFrames are rendered in HTML by configuring the formatter:

    +
    from datafusion.html_formatter import configure_formatter
+
+# Change the default styling
+configure_formatter(
+    max_cell_length=25,        # Maximum characters in a cell before truncation
+    max_width=1000,            # Maximum width in pixels
+    max_height=300,            # Maximum height in pixels
+    max_memory_bytes=2097152,  # Maximum memory for rendering (2MB)
+    min_rows_display=20,       # Minimum number of rows to display
+    repr_rows=10,              # Number of rows to display in __repr__
+    enable_cell_expansion=True,# Allow expanding truncated cells
+    custom_css=None,           # Additional custom CSS
+    show_truncation_message=True, # Show message when data is truncated
+    style_provider=None,       # Custom styling provider
+    use_shared_styles=True     # Share styles across tables
+)
+
    +
    +

    The formatter settings affect all DataFrames displayed after configuration.

    +
    +
    +

    Custom Style Providers

    +

    For advanced styling needs, you can create a custom style provider:

    +
    from datafusion.html_formatter import StyleProvider, configure_formatter
+
+class MyStyleProvider(StyleProvider):
+    def get_table_styles(self):
+        return {
+            "table": "border-collapse: collapse; width: 100%;",
+            "th": "background-color: #007bff; color: white; padding: 8px; text-align: left;",
+            "td": "border: 1px solid #ddd; padding: 8px;",
+            "tr:nth-child(even)": "background-color: #f2f2f2;",
+        }
+
+    def get_value_styles(self, dtype, value):
+        """Return custom styles for specific values"""
+        if dtype == "float" and value < 0:
+            return "color: red;"
+        return None
+
+# Apply the custom style provider
+configure_formatter(style_provider=MyStyleProvider())
+
    +
    +
    +
    +

    Performance Optimization with Shared Styles

    +

    The use_shared_styles parameter (enabled by default) optimizes performance when displaying +multiple DataFrames in notebook environments:

    +
    +
    +

    When use_shared_styles=True: +- CSS styles and JavaScript are included only once per notebook session +- This reduces HTML output size and prevents style duplication +- Improves rendering performance with many DataFrames +- Applies consistent styling across all DataFrames

    +
    +
    +

    Creating a Custom Formatter

    +

    For complete control over rendering, you can implement a custom formatter:

    +
    from datafusion.html_formatter import Formatter, get_formatter
+
+class MyFormatter(Formatter):
+    def format_html(self, batches, schema, has_more=False, table_uuid=None):
+        # Create your custom HTML here
+        html = "<div class='my-custom-table'>"
+        # ... formatting logic ...
+        html += "</div>"
+        return html
+
+# Set as the global formatter
+configure_formatter(formatter_class=MyFormatter)
+
+# Or use the formatter just for specific operations
+formatter = get_formatter()
+custom_html = formatter.format_html(batches, schema)
+
    +
    +
    +
    +

    Managing Formatters

    +

    Reset to default formatting:

    +
    from datafusion.html_formatter import reset_formatter
+
+# Reset to default settings
+reset_formatter()
+
    +
    +

    Get the current formatter settings:

    +
    from datafusion.html_formatter import get_formatter
+
+formatter = get_formatter()
+print(formatter.max_rows)
+print(formatter.theme)
+
    +
    +
    +
    +

    Contextual Formatting

    +

    You can also use a context manager to temporarily change formatting settings:

    +
    from datafusion.html_formatter import formatting_context
+
+# Default formatting
+df.show()
+
+# Temporarily use different formatting
+with formatting_context(max_rows=100, theme="dark"):
+    df.show()  # Will use the temporary settings
+
+# Back to default formatting
+df.show()
+
    +
    +
    +
    +

    Memory and Display Controls

    +

    You can control how much data is displayed and how much memory is used for rendering:

    +
    +
    configure_formatter(
+    max_memory_bytes=4 * 1024 * 1024,  # 4MB maximum memory for display
+    min_rows_display=50,               # Always show at least 50 rows
+    repr_rows=20                       # Show 20 rows in __repr__ output
+)
+
    +
    +
    +

    These parameters help balance comprehensive data display against performance considerations.

    +
    +
    + + +
    + + + +
    + + +
    +

    previous

    +

    Data Sources

    +
    +     + +
    +

    next

    +

    Common Operations

    +
    + +     +
    + +
    + + +
    +
    + + + + +
    +
    + +
    +

    + © Copyright 2019-2024, Apache Software Foundation.
    +

    +
    + +
    +

    +Created using Sphinx 8.1.3.
    +

    +
    + +
    +

    Apache Arrow DataFusion, Arrow DataFusion, Apache, the Apache feather logo, and the Apache Arrow DataFusion project logo

    +

    are either registered trademarks or trademarks of The Apache Software Foundation in the United States and other countries.

    +
    +
    +
    + + + + \ No newline at end of file diff --git a/user-guide/introduction.html b/user-guide/introduction.html index 64f713781..70d4f4a8b 100644 --- a/user-guide/introduction.html +++ b/user-guide/introduction.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • @@ -415,7 +440,7 @@

    Installation
    In [1]: import datafusion
 
 In [2]: datafusion.__version__
-Out[2]: '46.0.0'
+Out[2]: '47.0.0'

    In this documentation we will also show some examples for how DataFusion integrates diff --git a/user-guide/io/arrow.html b/user-guide/io/arrow.html index caa0e63f7..7abc1d48d 100644 --- a/user-guide/io/arrow.html +++ b/user-guide/io/arrow.html @@ -117,6 +117,11 @@ Data Sources +

  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/user-guide/io/avro.html b/user-guide/io/avro.html index 9c18f51b1..11306da96 100644 --- a/user-guide/io/avro.html +++ b/user-guide/io/avro.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/user-guide/io/csv.html b/user-guide/io/csv.html index 880ce7757..c07f7780c 100644 --- a/user-guide/io/csv.html +++ b/user-guide/io/csv.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/user-guide/io/index.html b/user-guide/io/index.html index b42512dc9..b2bfcab97 100644 --- a/user-guide/io/index.html +++ b/user-guide/io/index.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/user-guide/io/json.html b/user-guide/io/json.html index 52d537771..627d4866b 100644 --- a/user-guide/io/json.html +++ b/user-guide/io/json.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/user-guide/io/parquet.html b/user-guide/io/parquet.html index 71d033864..168fd0121 100644 --- a/user-guide/io/parquet.html +++ b/user-guide/io/parquet.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/user-guide/io/table_provider.html b/user-guide/io/table_provider.html index 410623c36..215ed51f9 100644 --- a/user-guide/io/table_provider.html +++ b/user-guide/io/table_provider.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • diff --git a/user-guide/sql.html b/user-guide/sql.html index e8d46a507..52eda7921 100644 --- a/user-guide/sql.html +++ b/user-guide/sql.html @@ -117,6 +117,11 @@ Data Sources +
  • + + DataFrames + +
  • Common Operations @@ -275,6 +280,11 @@ datafusion.catalog
    • +
  • + + datafusion.col + +
  • datafusion.context @@ -295,6 +305,11 @@ datafusion.functions
    • +
  • + + datafusion.html_formatter + +
  • datafusion.input @@ -347,6 +362,16 @@ datafusion.udf
    • +
  • + + datafusion.unparser + +
    • +
  • + + datafusion.user_defined + +
    • From 80655fc48dd251f0564592b1a41acb04e2bf0e20 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sat, 12 Jul 2025 11:50:09 +0000 Subject: [PATCH 27/36] Publish built docs triggered by f10d3b892b81f48b4dfc2ccd848d9c2ad5a1c4a7 --- .../autoapi/datafusion/catalog/index.rst.txt | 211 ++- _sources/autoapi/datafusion/col/index.rst.txt | 29 - .../autoapi/datafusion/context/index.rst.txt | 53 +- .../datafusion/dataframe/index.rst.txt | 354 +++- .../dataframe_formatter/index.rst.txt | 488 +++++ .../autoapi/datafusion/expr/index.rst.txt | 17 + .../datafusion/html_formatter/index.rst.txt | 499 +----- _sources/autoapi/datafusion/index.rst.txt | 482 ++++- _sources/autoapi/datafusion/io/index.rst.txt | 8 +- _sources/autoapi/datafusion/udf/index.rst.txt | 11 - .../datafusion/user_defined/index.rst.txt | 102 +- _sources/contributor-guide/ffi.rst.txt | 2 +- _sources/index.rst.txt | 2 +- _sources/user-guide/basics.rst.txt | 2 +- .../common-operations/functions.rst.txt | 2 +- _sources/user-guide/data-sources.rst.txt | 56 + _sources/user-guide/dataframe/index.rst.txt | 209 +++ .../rendering.rst.txt} | 106 +- autoapi/datafusion/catalog/index.html | 513 +++++- autoapi/datafusion/col/index.html | 540 ------ autoapi/datafusion/context/index.html | 180 +- autoapi/datafusion/dataframe/index.html | 1130 +++++++++++- .../datafusion/dataframe_formatter/index.html | 1533 ++++++++++++++++ autoapi/datafusion/expr/index.html | 95 +- autoapi/datafusion/functions/index.html | 51 +- autoapi/datafusion/html_formatter/index.html | 1136 +----------- autoapi/datafusion/index.html | 1578 ++++++++++++++--- autoapi/datafusion/input/base/index.html | 51 +- autoapi/datafusion/input/index.html | 51 +- autoapi/datafusion/input/location/index.html | 51 +- autoapi/datafusion/io/index.html | 59 +- autoapi/datafusion/object_store/index.html | 51 +- autoapi/datafusion/plan/index.html | 51 +- autoapi/datafusion/record_batch/index.html | 51 +- autoapi/datafusion/substrait/index.html | 57 +- autoapi/datafusion/udf/index.html | 479 ----- autoapi/datafusion/unparser/index.html | 57 +- autoapi/datafusion/user_defined/index.html | 272 ++- autoapi/index.html | 54 +- contributor-guide/ffi.html | 53 +- contributor-guide/introduction.html | 51 +- genindex.html | 580 ++++-- index.html | 51 +- objects.inv | Bin 7830 -> 8733 bytes py-modindex.html | 62 +- search.html | 51 +- searchindex.js | 2 +- user-guide/basics.html | 53 +- .../common-operations/aggregations.html | 91 +- user-guide/common-operations/basic-info.html | 85 +- user-guide/common-operations/expressions.html | 51 +- user-guide/common-operations/functions.html | 71 +- user-guide/common-operations/index.html | 57 +- user-guide/common-operations/joins.html | 51 +- .../common-operations/select-and-filter.html | 51 +- .../common-operations/udf-and-udfa.html | 51 +- user-guide/common-operations/views.html | 51 +- user-guide/common-operations/windows.html | 51 +- user-guide/configuration.html | 51 +- user-guide/data-sources.html | 184 +- user-guide/dataframe/index.html | 706 ++++++++ .../rendering.html} | 315 ++-- user-guide/introduction.html | 53 +- user-guide/io/arrow.html | 51 +- user-guide/io/avro.html | 51 +- user-guide/io/csv.html | 51 +- user-guide/io/index.html | 51 +- user-guide/io/json.html | 51 +- user-guide/io/parquet.html | 51 +- user-guide/io/table_provider.html | 51 +- user-guide/sql.html | 51 +- 71 files changed, 9439 insertions(+), 4464 deletions(-) delete mode 100644 _sources/autoapi/datafusion/col/index.rst.txt create mode 100644 _sources/autoapi/datafusion/dataframe_formatter/index.rst.txt delete mode 100644 _sources/autoapi/datafusion/udf/index.rst.txt create mode 100644 _sources/user-guide/dataframe/index.rst.txt rename _sources/user-guide/{dataframe.rst.txt => dataframe/rendering.rst.txt} (72%) delete mode 100644 autoapi/datafusion/col/index.html create mode 100644 autoapi/datafusion/dataframe_formatter/index.html delete mode 100644 autoapi/datafusion/udf/index.html create mode 100644 user-guide/dataframe/index.html rename user-guide/{dataframe.html => dataframe/rendering.html} (65%) diff --git a/_sources/autoapi/datafusion/catalog/index.rst.txt b/_sources/autoapi/datafusion/catalog/index.rst.txt index fbf71c621..9364aae2e 100644 --- a/_sources/autoapi/datafusion/catalog/index.rst.txt +++ b/_sources/autoapi/datafusion/catalog/index.rst.txt @@ -15,64 +15,253 @@ Classes .. autoapisummary:: datafusion.catalog.Catalog - datafusion.catalog.Database + datafusion.catalog.CatalogProvider + datafusion.catalog.Schema + datafusion.catalog.SchemaProvider datafusion.catalog.Table Module Contents --------------- -.. py:class:: Catalog(catalog: datafusion._internal.Catalog) +.. py:class:: Catalog(catalog: datafusion._internal.catalog.RawCatalog) DataFusion data catalog. This constructor is not typically called by the end user. - .. py:method:: database(name: str = 'public') -> Database + .. py:method:: __repr__() -> str + + Print a string representation of the catalog. + + + + .. py:method:: database(name: str = 'public') -> Schema + + Returns the database with the given ``name`` from this catalog. + + + + .. py:method:: deregister_schema(name: str, cascade: bool = True) -> Schema | None + + Deregister a schema from this catalog. + + + + .. py:method:: memory_catalog() -> Catalog + :staticmethod: + + + Create an in-memory catalog provider. + + + + .. py:method:: names() -> set[str] + + This is an alias for `schema_names`. + + + + .. py:method:: register_schema(name, schema) -> Schema | None + + Register a schema with this catalog. + + + + .. py:method:: schema(name: str = 'public') -> Schema Returns the database with the given ``name`` from this catalog. - .. py:method:: names() -> list[str] + .. py:method:: schema_names() -> set[str] - Returns the list of databases in this catalog. + Returns the list of schemas in this catalog. .. py:attribute:: catalog -.. py:class:: Database(db: datafusion._internal.Database) +.. py:class:: CatalogProvider + + Bases: :py:obj:`abc.ABC` + + + Abstract class for defining a Python based Catalog Provider. - DataFusion Database. + + .. py:method:: deregister_schema(name: str, cascade: bool) -> None + + Remove a schema from this catalog. + + This method is optional. If your catalog provides a fixed list of schemas, you + do not need to implement this method. + + :param name: The name of the schema to remove. + :param cascade: If true, deregister the tables within the schema. + + + + .. py:method:: register_schema(name: str, schema: SchemaProviderExportable | SchemaProvider | Schema) -> None + + Add a schema to this catalog. + + This method is optional. If your catalog provides a fixed list of schemas, you + do not need to implement this method. + + + + .. py:method:: schema(name: str) -> Schema | None + :abstractmethod: + + + Retrieve a specific schema from this catalog. + + + + .. py:method:: schema_names() -> set[str] + :abstractmethod: + + + Set of the names of all schemas in this catalog. + + + +.. py:class:: Schema(schema: datafusion._internal.catalog.RawSchema) + + DataFusion Schema. This constructor is not typically called by the end user. + .. py:method:: __repr__() -> str + + Print a string representation of the schema. + + + + .. py:method:: deregister_table(name: str) -> None + + Deregister a table provider from this schema. + + + + .. py:method:: memory_schema() -> Schema + :staticmethod: + + + Create an in-memory schema provider. + + + .. py:method:: names() -> set[str] - Returns the list of all tables in this database. + This is an alias for `table_names`. + + + + .. py:method:: register_table(name, table) -> None + + Register a table provider in this schema. .. py:method:: table(name: str) -> Table - Return the table with the given ``name`` from this database. + Return the table with the given ``name`` from this schema. + + + + .. py:method:: table_names() -> set[str] + + Returns the list of all tables in this schema. + + + + .. py:attribute:: _raw_schema + + +.. py:class:: SchemaProvider + + Bases: :py:obj:`abc.ABC` + + + Abstract class for defining a Python based Schema Provider. + + + .. py:method:: deregister_table(name, cascade: bool) -> None + + Remove a table from this schema. + + This method is optional. If your schema provides a fixed list of tables, you do + not need to implement this method. + + + + .. py:method:: owner_name() -> str | None + Returns the owner of the schema. + This is an optional method. The default return is None. - .. py:attribute:: db -.. py:class:: Table(table: datafusion._internal.Table) + .. py:method:: register_table(name: str, table: Table) -> None + + Add a table from this schema. + + This method is optional. If your schema provides a fixed list of tables, you do + not need to implement this method. + + + + .. py:method:: table(name: str) -> Table | None + :abstractmethod: + + + Retrieve a specific table from this schema. + + + + .. py:method:: table_exist(name: str) -> bool + :abstractmethod: + + + Returns true if the table exists in this schema. + + + + .. py:method:: table_names() -> set[str] + :abstractmethod: + + + Set of the names of all tables in this schema. + + + +.. py:class:: Table(table: datafusion._internal.catalog.RawTable) DataFusion table. This constructor is not typically called by the end user. + .. py:method:: __repr__() -> str + + Print a string representation of the table. + + + + .. py:method:: from_dataset(dataset: pyarrow.dataset.Dataset) -> Table + :staticmethod: + + + Turn a pyarrow Dataset into a Table. + + + .. py:property:: kind :type: str diff --git a/_sources/autoapi/datafusion/col/index.rst.txt b/_sources/autoapi/datafusion/col/index.rst.txt deleted file mode 100644 index 138a35e7d..000000000 --- a/_sources/autoapi/datafusion/col/index.rst.txt +++ /dev/null @@ -1,29 +0,0 @@ -datafusion.col -============== - -.. py:module:: datafusion.col - -.. autoapi-nested-parse:: - - Col class. - - - -Attributes ----------- - -.. autoapisummary:: - - datafusion.col.col - datafusion.col.column - - -Module Contents ---------------- - -.. py:data:: col - :type: Col - -.. py:data:: column - :type: Col - diff --git a/_sources/autoapi/datafusion/context/index.rst.txt b/_sources/autoapi/datafusion/context/index.rst.txt index 12c4965c9..672346d67 100644 --- a/_sources/autoapi/datafusion/context/index.rst.txt +++ b/_sources/autoapi/datafusion/context/index.rst.txt @@ -16,6 +16,7 @@ Classes datafusion.context.ArrowArrayExportable datafusion.context.ArrowStreamExportable + datafusion.context.CatalogProviderExportable datafusion.context.RuntimeConfig datafusion.context.RuntimeEnvBuilder datafusion.context.SQLOptions @@ -53,6 +54,19 @@ Module Contents .. py:method:: __arrow_c_stream__(requested_schema: object | None = None) -> object +.. py:class:: CatalogProviderExportable + + Bases: :py:obj:`Protocol` + + + Type hint for object that has __datafusion_catalog_provider__ PyCapsule. + + https://docs.rs/datafusion/latest/datafusion/catalog/trait.CatalogProvider.html + + + .. py:method:: __datafusion_catalog_provider__() -> object + + .. py:class:: RuntimeConfig Bases: :py:obj:`RuntimeEnvBuilder` @@ -411,12 +425,29 @@ Module Contents df = ctx.read_csv("data.csv") + .. py:method:: __repr__() -> str + + Print a string representation of the Session Context. + + + + .. py:method:: _convert_table_partition_cols(table_partition_cols: list[tuple[str, str | pyarrow.DataType]]) -> list[tuple[str, pyarrow.DataType]] + :staticmethod: + + + .. py:method:: catalog(name: str = 'datafusion') -> datafusion.catalog.Catalog Retrieve a catalog by name. + .. py:method:: catalog_names() -> set[str] + + Returns the list of catalogs in this context. + + + .. py:method:: create_dataframe(partitions: list[list[pyarrow.RecordBatch]], name: str | None = None, schema: pyarrow.Schema | None = None) -> datafusion.dataframe.DataFrame Create and return a dataframe using the provided partitions. @@ -544,7 +575,7 @@ Module Contents - .. py:method:: read_avro(path: str | pathlib.Path, schema: pyarrow.Schema | None = None, file_partition_cols: list[tuple[str, str]] | None = None, file_extension: str = '.avro') -> datafusion.dataframe.DataFrame + .. py:method:: read_avro(path: str | pathlib.Path, schema: pyarrow.Schema | None = None, file_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_extension: str = '.avro') -> datafusion.dataframe.DataFrame Create a :py:class:`DataFrame` for reading Avro data source. @@ -557,7 +588,7 @@ Module Contents - .. py:method:: read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str]] | None = None, file_compression_type: str | None = None) -> datafusion.dataframe.DataFrame + .. py:method:: read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None) -> datafusion.dataframe.DataFrame Read a CSV data source. @@ -579,7 +610,7 @@ Module Contents - .. py:method:: read_json(path: str | pathlib.Path, schema: pyarrow.Schema | None = None, schema_infer_max_records: int = 1000, file_extension: str = '.json', table_partition_cols: list[tuple[str, str]] | None = None, file_compression_type: str | None = None) -> datafusion.dataframe.DataFrame + .. py:method:: read_json(path: str | pathlib.Path, schema: pyarrow.Schema | None = None, schema_infer_max_records: int = 1000, file_extension: str = '.json', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None) -> datafusion.dataframe.DataFrame Read a line-delimited JSON data source. @@ -596,7 +627,7 @@ Module Contents - .. py:method:: read_parquet(path: str | pathlib.Path, table_partition_cols: list[tuple[str, str]] | None = None, parquet_pruning: bool = True, file_extension: str = '.parquet', skip_metadata: bool = True, schema: pyarrow.Schema | None = None, file_sort_order: list[list[datafusion.expr.Expr | datafusion.expr.SortExpr]] | None = None) -> datafusion.dataframe.DataFrame + .. py:method:: read_parquet(path: str | pathlib.Path, table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, parquet_pruning: bool = True, file_extension: str = '.parquet', skip_metadata: bool = True, schema: pyarrow.Schema | None = None, file_sort_order: list[list[datafusion.expr.Expr | datafusion.expr.SortExpr]] | None = None) -> datafusion.dataframe.DataFrame Read a Parquet source into a :py:class:`~datafusion.dataframe.Dataframe`. @@ -628,7 +659,7 @@ Module Contents - .. py:method:: register_avro(name: str, path: str | pathlib.Path, schema: pyarrow.Schema | None = None, file_extension: str = '.avro', table_partition_cols: list[tuple[str, str]] | None = None) -> None + .. py:method:: register_avro(name: str, path: str | pathlib.Path, schema: pyarrow.Schema | None = None, file_extension: str = '.avro', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None) -> None Register an Avro file as a table. @@ -643,6 +674,12 @@ Module Contents + .. py:method:: register_catalog_provider(name: str, provider: CatalogProviderExportable | datafusion.catalog.CatalogProvider | datafusion.catalog.Catalog) -> None + + Register a catalog provider. + + + .. py:method:: register_csv(name: str, path: str | pathlib.Path | list[str | pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', file_compression_type: str | None = None) -> None Register a CSV file as a table. @@ -674,7 +711,7 @@ Module Contents - .. py:method:: register_json(name: str, path: str | pathlib.Path, schema: pyarrow.Schema | None = None, schema_infer_max_records: int = 1000, file_extension: str = '.json', table_partition_cols: list[tuple[str, str]] | None = None, file_compression_type: str | None = None) -> None + .. py:method:: register_json(name: str, path: str | pathlib.Path, schema: pyarrow.Schema | None = None, schema_infer_max_records: int = 1000, file_extension: str = '.json', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None) -> None Register a JSON file as a table. @@ -693,7 +730,7 @@ Module Contents - .. py:method:: register_listing_table(name: str, path: str | pathlib.Path, table_partition_cols: list[tuple[str, str]] | None = None, file_extension: str = '.parquet', schema: pyarrow.Schema | None = None, file_sort_order: list[list[datafusion.expr.Expr | datafusion.expr.SortExpr]] | None = None) -> None + .. py:method:: register_listing_table(name: str, path: str | pathlib.Path, table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_extension: str = '.parquet', schema: pyarrow.Schema | None = None, file_sort_order: list[list[datafusion.expr.Expr | datafusion.expr.SortExpr]] | None = None) -> None Register multiple files as a single table. @@ -720,7 +757,7 @@ Module Contents - .. py:method:: register_parquet(name: str, path: str | pathlib.Path, table_partition_cols: list[tuple[str, str]] | None = None, parquet_pruning: bool = True, file_extension: str = '.parquet', skip_metadata: bool = True, schema: pyarrow.Schema | None = None, file_sort_order: list[list[datafusion.expr.SortExpr]] | None = None) -> None + .. py:method:: register_parquet(name: str, path: str | pathlib.Path, table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, parquet_pruning: bool = True, file_extension: str = '.parquet', skip_metadata: bool = True, schema: pyarrow.Schema | None = None, file_sort_order: list[list[datafusion.expr.SortExpr]] | None = None) -> None Register a Parquet file as a table. diff --git a/_sources/autoapi/datafusion/dataframe/index.rst.txt b/_sources/autoapi/datafusion/dataframe/index.rst.txt index 5262d74fc..f0272cc79 100644 --- a/_sources/autoapi/datafusion/dataframe/index.rst.txt +++ b/_sources/autoapi/datafusion/dataframe/index.rst.txt @@ -18,6 +18,8 @@ Classes datafusion.dataframe.Compression datafusion.dataframe.DataFrame + datafusion.dataframe.ParquetColumnOptions + datafusion.dataframe.ParquetWriterOptions Module Contents @@ -100,7 +102,7 @@ Module Contents create a :py:class:`DataFrame`. - .. py:method:: __arrow_c_stream__(requested_schema: pyarrow.Schema) -> Any + .. py:method:: __arrow_c_stream__(requested_schema: object | None = None) -> object Export an Arrow PyCapsule Stream. @@ -202,6 +204,17 @@ Module Contents + .. py:method:: default_str_repr(batches: list[pyarrow.RecordBatch], schema: pyarrow.Schema, has_more: bool, table_uuid: str | None = None) -> str + :staticmethod: + + + Return the default string representation of a DataFrame. + + This method is used by the default formatter and implemented in Rust for + performance reasons. + + + .. py:method:: describe() -> DataFrame Return the statistics for this DataFrame. @@ -269,17 +282,15 @@ Module Contents - .. py:method:: explain(verbose: bool = False, analyze: bool = False) -> DataFrame + .. py:method:: explain(verbose: bool = False, analyze: bool = False) -> None - Return a DataFrame with the explanation of its plan so far. + Print an explanation of the DataFrame's plan so far. If ``analyze`` is specified, runs the plan and reports metrics. :param verbose: If ``True``, more details will be included. :param analyze: If ``Tru`e``, the plan will run and metrics reported. - :returns: DataFrame with the explanation of its plan. - .. py:method:: fill_null(value: Any, subset: list[str] | None = None) -> DataFrame @@ -673,7 +684,9 @@ Module Contents - .. py:method:: write_parquet(path: str | pathlib.Path, compression: Union[str, Compression] = Compression.ZSTD, compression_level: int | None = None) -> None + .. py:method:: write_parquet(path: str | pathlib.Path, compression: str, compression_level: int | None = None) -> None + write_parquet(path: str | pathlib.Path, compression: Compression = Compression.ZSTD, compression_level: int | None = None) -> None + write_parquet(path: str | pathlib.Path, compression: ParquetWriterOptions, compression_level: None = None) -> None Execute the :py:class:`DataFrame` and write the results to a Parquet file. @@ -694,6 +707,335 @@ Module Contents + .. py:method:: write_parquet_with_options(path: str | pathlib.Path, options: ParquetWriterOptions) -> None + + Execute the :py:class:`DataFrame` and write the results to a Parquet file. + + Allows advanced writer options to be set with `ParquetWriterOptions`. + + :param path: Path of the Parquet file to write. + :param options: Sets the writer parquet options (see `ParquetWriterOptions`). + + + .. py:attribute:: df +.. py:class:: ParquetColumnOptions(encoding: Optional[str] = None, dictionary_enabled: Optional[bool] = None, compression: Optional[str] = None, statistics_enabled: Optional[str] = None, bloom_filter_enabled: Optional[bool] = None, bloom_filter_fpp: Optional[float] = None, bloom_filter_ndv: Optional[int] = None) + + Parquet options for individual columns. + + Contains the available options that can be applied for an individual Parquet column, + replacing the global options in `ParquetWriterOptions`. + + .. attribute:: encoding + + Sets encoding for the column path. Valid values are: `plain`, + `plain_dictionary`, `rle`, `bit_packed`, `delta_binary_packed`, + `delta_length_byte_array`, `delta_byte_array`, `rle_dictionary`, and + `byte_stream_split`. These values are not case-sensitive. If `None`, uses + the default parquet options + + .. attribute:: dictionary_enabled + + Sets if dictionary encoding is enabled for the column path. + If `None`, uses the default parquet options + + .. attribute:: compression + + Sets default parquet compression codec for the column path. Valid + values are `uncompressed`, `snappy`, `gzip(level)`, `lzo`, `brotli(level)`, + `lz4`, `zstd(level)`, and `lz4_raw`. These values are not case-sensitive. If + `None`, uses the default parquet options. + + .. attribute:: statistics_enabled + + Sets if statistics are enabled for the column Valid values + are: `none`, `chunk`, and `page` These values are not case sensitive. If + `None`, uses the default parquet options. + + .. attribute:: bloom_filter_enabled + + Sets if bloom filter is enabled for the column path. If + `None`, uses the default parquet options. + + .. attribute:: bloom_filter_fpp + + Sets bloom filter false positive probability for the column + path. If `None`, uses the default parquet options. + + .. attribute:: bloom_filter_ndv + + Sets bloom filter number of distinct values. If `None`, uses + the default parquet options. + + Initialize the ParquetColumnOptions. + + + .. py:attribute:: bloom_filter_enabled + :value: None + + + + .. py:attribute:: bloom_filter_fpp + :value: None + + + + .. py:attribute:: bloom_filter_ndv + :value: None + + + + .. py:attribute:: compression + :value: None + + + + .. py:attribute:: dictionary_enabled + :value: None + + + + .. py:attribute:: encoding + :value: None + + + + .. py:attribute:: statistics_enabled + :value: None + + + +.. py:class:: ParquetWriterOptions(data_pagesize_limit: int = 1024 * 1024, write_batch_size: int = 1024, writer_version: str = '1.0', skip_arrow_metadata: bool = False, compression: Optional[str] = 'zstd(3)', compression_level: Optional[int] = None, dictionary_enabled: Optional[bool] = True, dictionary_page_size_limit: int = 1024 * 1024, statistics_enabled: Optional[str] = 'page', max_row_group_size: int = 1024 * 1024, created_by: str = 'datafusion-python', column_index_truncate_length: Optional[int] = 64, statistics_truncate_length: Optional[int] = None, data_page_row_count_limit: int = 20000, encoding: Optional[str] = None, bloom_filter_on_write: bool = False, bloom_filter_fpp: Optional[float] = None, bloom_filter_ndv: Optional[int] = None, allow_single_file_parallelism: bool = True, maximum_parallel_row_group_writers: int = 1, maximum_buffered_record_batches_per_stream: int = 2, column_specific_options: Optional[dict[str, ParquetColumnOptions]] = None) + + Advanced parquet writer options. + + Allows settings the writer options that apply to the entire file. Some options can + also be set on a column by column basis, with the field `column_specific_options` + (see `ParquetColumnOptions`). + + .. attribute:: data_pagesize_limit + + Sets best effort maximum size of data page in bytes. + + .. attribute:: write_batch_size + + Sets write_batch_size in bytes. + + .. attribute:: writer_version + + Sets parquet writer version. Valid values are `1.0` and + `2.0`. + + .. attribute:: skip_arrow_metadata + + Skip encoding the embedded arrow metadata in the + KV_meta. + + .. attribute:: compression + + Compression type to use. Default is "zstd(3)". + Available compression types are + - "uncompressed": No compression. + - "snappy": Snappy compression. + - "gzip(n)": Gzip compression with level n. + - "brotli(n)": Brotli compression with level n. + - "lz4": LZ4 compression. + - "lz4_raw": LZ4_RAW compression. + - "zstd(n)": Zstandard compression with level n. + + .. attribute:: dictionary_enabled + + Sets if dictionary encoding is enabled. If None, uses + the default parquet writer setting. + + .. attribute:: dictionary_page_size_limit + + Sets best effort maximum dictionary page size, + in bytes. + + .. attribute:: statistics_enabled + + Sets if statistics are enabled for any column Valid + values are `none`, `chunk`, and `page`. If None, uses the default + parquet writer setting. + + .. attribute:: max_row_group_size + + Target maximum number of rows in each row group + (defaults to 1M rows). Writing larger row groups requires more memory to + write, but can get better compression and be faster to read. + + .. attribute:: created_by + + Sets "created by" property. + + .. attribute:: column_index_truncate_length + + Sets column index truncate length. + + .. attribute:: statistics_truncate_length + + Sets statistics truncate length. If None, uses + the default parquet writer setting. + + .. attribute:: data_page_row_count_limit + + Sets best effort maximum number of rows in a data + page. + + .. attribute:: encoding + + Sets default encoding for any column. Valid values are `plain`, + `plain_dictionary`, `rle`, `bit_packed`, `delta_binary_packed`, + `delta_length_byte_array`, `delta_byte_array`, `rle_dictionary`, and + `byte_stream_split`. If None, uses the default parquet writer setting. + + .. attribute:: bloom_filter_on_write + + Write bloom filters for all columns when creating + parquet files. + + .. attribute:: bloom_filter_fpp + + Sets bloom filter false positive probability. If None, + uses the default parquet writer setting + + .. attribute:: bloom_filter_ndv + + Sets bloom filter number of distinct values. If None, uses + the default parquet writer setting. + + .. attribute:: allow_single_file_parallelism + + Controls whether DataFusion will attempt to + speed up writing parquet files by serializing them in parallel. Each + column in each row group in each output file are serialized in parallel + leveraging a maximum possible core count of n_files * n_row_groups * + n_columns. + + .. attribute:: maximum_parallel_row_group_writers + + By default parallel parquet writer is + tuned for minimum memory usage in a streaming execution plan. You may + see a performance benefit when writing large parquet files by increasing + `maximum_parallel_row_group_writers` and + `maximum_buffered_record_batches_per_stream` if your system has idle + cores and can tolerate additional memory usage. Boosting these values is + likely worthwhile when writing out already in-memory data, such as from + a cached data frame. + + .. attribute:: maximum_buffered_record_batches_per_stream + + See + `maximum_parallel_row_group_writers`. + + .. attribute:: column_specific_options + + Overrides options for specific columns. If a column + is not a part of this dictionary, it will use the parameters provided here. + + Initialize the ParquetWriterOptions. + + + .. py:attribute:: allow_single_file_parallelism + :value: True + + + + .. py:attribute:: bloom_filter_fpp + :value: None + + + + .. py:attribute:: bloom_filter_ndv + :value: None + + + + .. py:attribute:: bloom_filter_on_write + :value: False + + + + .. py:attribute:: column_index_truncate_length + :value: 64 + + + + .. py:attribute:: column_specific_options + :value: None + + + + .. py:attribute:: created_by + :value: 'datafusion-python' + + + + .. py:attribute:: data_page_row_count_limit + :value: 20000 + + + + .. py:attribute:: data_pagesize_limit + :value: 1048576 + + + + .. py:attribute:: dictionary_enabled + :value: True + + + + .. py:attribute:: dictionary_page_size_limit + :value: 1048576 + + + + .. py:attribute:: encoding + :value: None + + + + .. py:attribute:: max_row_group_size + :value: 1048576 + + + + .. py:attribute:: maximum_buffered_record_batches_per_stream + :value: 2 + + + + .. py:attribute:: maximum_parallel_row_group_writers + :value: 1 + + + + .. py:attribute:: skip_arrow_metadata + :value: False + + + + .. py:attribute:: statistics_enabled + :value: 'page' + + + + .. py:attribute:: statistics_truncate_length + :value: None + + + + .. py:attribute:: write_batch_size + :value: 1024 + + + + .. py:attribute:: writer_version + :value: '1.0' + + + diff --git a/_sources/autoapi/datafusion/dataframe_formatter/index.rst.txt b/_sources/autoapi/datafusion/dataframe_formatter/index.rst.txt new file mode 100644 index 000000000..ad3e62b5d --- /dev/null +++ b/_sources/autoapi/datafusion/dataframe_formatter/index.rst.txt @@ -0,0 +1,488 @@ +datafusion.dataframe_formatter +============================== + +.. py:module:: datafusion.dataframe_formatter + +.. autoapi-nested-parse:: + + HTML formatting utilities for DataFusion DataFrames. + + + +Classes +------- + +.. autoapisummary:: + + datafusion.dataframe_formatter.CellFormatter + datafusion.dataframe_formatter.DataFrameHtmlFormatter + datafusion.dataframe_formatter.DefaultStyleProvider + datafusion.dataframe_formatter.FormatterManager + datafusion.dataframe_formatter.StyleProvider + + +Functions +--------- + +.. autoapisummary:: + + datafusion.dataframe_formatter._refresh_formatter_reference + datafusion.dataframe_formatter._validate_bool + datafusion.dataframe_formatter._validate_positive_int + datafusion.dataframe_formatter.configure_formatter + datafusion.dataframe_formatter.get_formatter + datafusion.dataframe_formatter.reset_formatter + datafusion.dataframe_formatter.set_formatter + + +Module Contents +--------------- + +.. py:class:: CellFormatter + + Bases: :py:obj:`Protocol` + + + Protocol for cell value formatters. + + + .. py:method:: __call__(value: Any) -> str + + Format a cell value to string representation. + + + +.. py:class:: DataFrameHtmlFormatter(max_cell_length: int = 25, max_width: int = 1000, max_height: int = 300, max_memory_bytes: int = 2 * 1024 * 1024, min_rows_display: int = 20, repr_rows: int = 10, enable_cell_expansion: bool = True, custom_css: Optional[str] = None, show_truncation_message: bool = True, style_provider: Optional[StyleProvider] = None, use_shared_styles: bool = True) + + Configurable HTML formatter for DataFusion DataFrames. + + This class handles the HTML rendering of DataFrames for display in + Jupyter notebooks and other rich display contexts. + + This class supports extension through composition. Key extension points: + - Provide a custom StyleProvider for styling cells and headers + - Register custom formatters for specific types + - Provide custom cell builders for specialized cell rendering + + :param max_cell_length: Maximum characters to display in a cell before truncation + :param max_width: Maximum width of the HTML table in pixels + :param max_height: Maximum height of the HTML table in pixels + :param max_memory_bytes: Maximum memory in bytes for rendered data (default: 2MB) + :param min_rows_display: Minimum number of rows to display + :param repr_rows: Default number of rows to display in repr output + :param enable_cell_expansion: Whether to add expand/collapse buttons for long cell + values + :param custom_css: Additional CSS to include in the HTML output + :param show_truncation_message: Whether to display a message when data is truncated + :param style_provider: Custom provider for cell and header styles + :param use_shared_styles: Whether to load styles and scripts only once per notebook + session + + Initialize the HTML formatter. + + :param max_cell_length: Maximum length of cell content before truncation. + :type max_cell_length: int, default 25 + :param max_width: Maximum width of the displayed table in pixels. + :type max_width: int, default 1000 + :param max_height: Maximum height of the displayed table in pixels. + :type max_height: int, default 300 + :param max_memory_bytes: Maximum memory in bytes for rendered data. + :type max_memory_bytes: int, default 2097152 (2MB) + :param min_rows_display: Minimum number of rows to display. + :type min_rows_display: int, default 20 + :param repr_rows: Default number of rows to display in repr output. + :type repr_rows: int, default 10 + :param enable_cell_expansion: Whether to allow cells to expand when clicked. + :type enable_cell_expansion: bool, default True + :param custom_css: Custom CSS to apply to the HTML table. + :type custom_css: str, optional + :param show_truncation_message: Whether to show a message indicating that content has been truncated. + :type show_truncation_message: bool, default True + :param style_provider: Provider of CSS styles for the HTML table. If None, DefaultStyleProvider + is used. + :type style_provider: StyleProvider, optional + :param use_shared_styles: Whether to use shared styles across multiple tables. + :type use_shared_styles: bool, default True + :param Raises: + :param ------: + :param ValueError: If max_cell_length, max_width, max_height, max_memory_bytes, + min_rows_display, or repr_rows is not a positive integer. + :param TypeError: If enable_cell_expansion, show_truncation_message, or use_shared_styles is + not a boolean, + or if custom_css is provided but is not a string, + or if style_provider is provided but does not implement the StyleProvider + protocol. + + + .. py:method:: _build_expandable_cell(formatted_value: str, row_count: int, col_idx: int, table_uuid: str) -> str + + Build an expandable cell for long content. + + + + .. py:method:: _build_html_footer(has_more: bool) -> list[str] + + Build the HTML footer with JavaScript and messages. + + + + .. py:method:: _build_html_header() -> list[str] + + Build the HTML header with CSS styles. + + + + .. py:method:: _build_regular_cell(formatted_value: str) -> str + + Build a regular table cell. + + + + .. py:method:: _build_table_body(batches: list, table_uuid: str) -> list[str] + + Build the HTML table body with data rows. + + + + .. py:method:: _build_table_container_start() -> list[str] + + Build the opening tags for the table container. + + + + .. py:method:: _build_table_header(schema: Any) -> list[str] + + Build the HTML table header with column names. + + + + .. py:method:: _format_cell_value(value: Any) -> str + + Format a cell value for display. + + Uses registered type formatters if available. + + :param value: The cell value to format + + :returns: Formatted cell value as string + + + + .. py:method:: _get_cell_value(column: Any, row_idx: int) -> Any + + Extract a cell value from a column. + + :param column: Arrow array + :param row_idx: Row index + + :returns: The raw cell value + + + + .. py:method:: _get_default_css() -> str + + Get default CSS styles for the HTML table. + + + + .. py:method:: _get_javascript() -> str + + Get JavaScript code for interactive elements. + + + + .. py:method:: format_html(batches: list, schema: Any, has_more: bool = False, table_uuid: str | None = None) -> str + + Format record batches as HTML. + + This method is used by DataFrame's _repr_html_ implementation and can be + called directly when custom HTML rendering is needed. + + :param batches: List of Arrow RecordBatch objects + :param schema: Arrow Schema object + :param has_more: Whether there are more batches not shown + :param table_uuid: Unique ID for the table, used for JavaScript interactions + + :returns: HTML string representation of the data + + :raises TypeError: If schema is invalid and no batches are provided + + + + .. py:method:: format_str(batches: list, schema: Any, has_more: bool = False, table_uuid: str | None = None) -> str + + Format record batches as a string. + + This method is used by DataFrame's __repr__ implementation and can be + called directly when string rendering is needed. + + :param batches: List of Arrow RecordBatch objects + :param schema: Arrow Schema object + :param has_more: Whether there are more batches not shown + :param table_uuid: Unique ID for the table, used for JavaScript interactions + + :returns: String representation of the data + + :raises TypeError: If schema is invalid and no batches are provided + + + + .. py:method:: register_formatter(type_class: type, formatter: CellFormatter) -> None + + Register a custom formatter for a specific data type. + + :param type_class: The type to register a formatter for + :param formatter: Function that takes a value of the given type and returns + a formatted string + + + + .. py:method:: set_custom_cell_builder(builder: Callable[[Any, int, int, str], str]) -> None + + Set a custom cell builder function. + + :param builder: Function that takes (value, row, col, table_id) and returns HTML + + + + .. py:method:: set_custom_header_builder(builder: Callable[[Any], str]) -> None + + Set a custom header builder function. + + :param builder: Function that takes a field and returns HTML + + + + .. py:attribute:: _custom_cell_builder + :type: Optional[Callable[[Any, int, int, str], str]] + :value: None + + + + .. py:attribute:: _custom_header_builder + :type: Optional[Callable[[Any], str]] + :value: None + + + + .. py:attribute:: _type_formatters + :type: dict[type, CellFormatter] + + + .. py:attribute:: custom_css + :value: None + + + + .. py:attribute:: enable_cell_expansion + :value: True + + + + .. py:attribute:: max_cell_length + :value: 25 + + + + .. py:attribute:: max_height + :value: 300 + + + + .. py:attribute:: max_memory_bytes + :value: 2097152 + + + + .. py:attribute:: max_width + :value: 1000 + + + + .. py:attribute:: min_rows_display + :value: 20 + + + + .. py:attribute:: repr_rows + :value: 10 + + + + .. py:attribute:: show_truncation_message + :value: True + + + + .. py:attribute:: style_provider + + + .. py:attribute:: use_shared_styles + :value: True + + + +.. py:class:: DefaultStyleProvider + + Default implementation of StyleProvider. + + + .. py:method:: get_cell_style() -> str + + Get the CSS style for table cells. + + :returns: CSS style string + + + + .. py:method:: get_header_style() -> str + + Get the CSS style for header cells. + + :returns: CSS style string + + + +.. py:class:: FormatterManager + + Manager class for the global DataFrame HTML formatter instance. + + + .. py:method:: get_formatter() -> DataFrameHtmlFormatter + :classmethod: + + + Get the current global DataFrame HTML formatter. + + :returns: The global HTML formatter instance + + + + .. py:method:: set_formatter(formatter: DataFrameHtmlFormatter) -> None + :classmethod: + + + Set the global DataFrame HTML formatter. + + :param formatter: The formatter instance to use globally + + + + .. py:attribute:: _default_formatter + :type: DataFrameHtmlFormatter + + +.. py:class:: StyleProvider + + Bases: :py:obj:`Protocol` + + + Protocol for HTML style providers. + + + .. py:method:: get_cell_style() -> str + + Get the CSS style for table cells. + + + + .. py:method:: get_header_style() -> str + + Get the CSS style for header cells. + + + +.. py:function:: _refresh_formatter_reference() -> None + + Refresh formatter reference in any modules using it. + + This helps ensure that changes to the formatter are reflected in existing + DataFrames that might be caching the formatter reference. + + +.. py:function:: _validate_bool(value: Any, param_name: str) -> None + + Validate that a parameter is a boolean. + + :param value: The value to validate + :param param_name: Name of the parameter (used in error message) + + :raises TypeError: If the value is not a boolean + + +.. py:function:: _validate_positive_int(value: Any, param_name: str) -> None + + Validate that a parameter is a positive integer. + + :param value: The value to validate + :param param_name: Name of the parameter (used in error message) + + :raises ValueError: If the value is not a positive integer + + +.. py:function:: configure_formatter(**kwargs: Any) -> None + + Configure the global DataFrame HTML formatter. + + This function creates a new formatter with the provided configuration + and sets it as the global formatter for all DataFrames. + + :param \*\*kwargs: Formatter configuration parameters like max_cell_length, + max_width, max_height, enable_cell_expansion, etc. + + :raises ValueError: If any invalid parameters are provided + + .. rubric:: Example + + >>> from datafusion.html_formatter import configure_formatter + >>> configure_formatter( + ... max_cell_length=50, + ... max_height=500, + ... enable_cell_expansion=True, + ... use_shared_styles=True + ... ) + + +.. py:function:: get_formatter() -> DataFrameHtmlFormatter + + Get the current global DataFrame HTML formatter. + + This function is used by the DataFrame._repr_html_ implementation to access + the shared formatter instance. It can also be used directly when custom + HTML rendering is needed. + + :returns: The global HTML formatter instance + + .. rubric:: Example + + >>> from datafusion.html_formatter import get_formatter + >>> formatter = get_formatter() + >>> formatter.max_cell_length = 50 # Increase cell length + + +.. py:function:: reset_formatter() -> None + + Reset the global DataFrame HTML formatter to default settings. + + This function creates a new formatter with default configuration + and sets it as the global formatter for all DataFrames. + + .. rubric:: Example + + >>> from datafusion.html_formatter import reset_formatter + >>> reset_formatter() # Reset formatter to default settings + + +.. py:function:: set_formatter(formatter: DataFrameHtmlFormatter) -> None + + Set the global DataFrame HTML formatter. + + :param formatter: The formatter instance to use globally + + .. rubric:: Example + + >>> from datafusion.html_formatter import get_formatter, set_formatter + >>> custom_formatter = DataFrameHtmlFormatter(max_cell_length=100) + >>> set_formatter(custom_formatter) + + diff --git a/_sources/autoapi/datafusion/expr/index.rst.txt b/_sources/autoapi/datafusion/expr/index.rst.txt index 51caf4b2f..81bb5b5a0 100644 --- a/_sources/autoapi/datafusion/expr/index.rst.txt +++ b/_sources/autoapi/datafusion/expr/index.rst.txt @@ -677,6 +677,17 @@ Module Contents + .. py:method:: literal_with_metadata(value: Any, metadata: dict[str, str]) -> Expr + :staticmethod: + + + Creates a new expression representing a scalar value with metadata. + + :param value: A valid PyArrow scalar value or easily castable to one. + :param metadata: Metadata to attach to the expression. + + + .. py:method:: ln() -> Expr Returns the natural logarithm (base e) of the argument. @@ -1068,6 +1079,12 @@ Module Contents parameter must be set. + .. py:method:: __repr__() -> str + + Print a string representation of the window frame. + + + .. py:method:: get_frame_units() -> str Returns the window frame units for the bounds. diff --git a/_sources/autoapi/datafusion/html_formatter/index.rst.txt b/_sources/autoapi/datafusion/html_formatter/index.rst.txt index b00cced17..2b9efd822 100644 --- a/_sources/autoapi/datafusion/html_formatter/index.rst.txt +++ b/_sources/autoapi/datafusion/html_formatter/index.rst.txt @@ -5,504 +5,7 @@ datafusion.html_formatter .. autoapi-nested-parse:: - HTML formatting utilities for DataFusion DataFrames. + Deprecated module for dataframe formatting. -Classes -------- - -.. autoapisummary:: - - datafusion.html_formatter.CellFormatter - datafusion.html_formatter.DataFrameHtmlFormatter - datafusion.html_formatter.DefaultStyleProvider - datafusion.html_formatter.FormatterManager - datafusion.html_formatter.StyleProvider - - -Functions ---------- - -.. autoapisummary:: - - datafusion.html_formatter._refresh_formatter_reference - datafusion.html_formatter._validate_bool - datafusion.html_formatter._validate_positive_int - datafusion.html_formatter.configure_formatter - datafusion.html_formatter.get_formatter - datafusion.html_formatter.reset_formatter - datafusion.html_formatter.reset_styles_loaded_state - datafusion.html_formatter.set_formatter - - -Module Contents ---------------- - -.. py:class:: CellFormatter - - Bases: :py:obj:`Protocol` - - - Protocol for cell value formatters. - - - .. py:method:: __call__(value: Any) -> str - - Format a cell value to string representation. - - - -.. py:class:: DataFrameHtmlFormatter(max_cell_length: int = 25, max_width: int = 1000, max_height: int = 300, max_memory_bytes: int = 2 * 1024 * 1024, min_rows_display: int = 20, repr_rows: int = 10, enable_cell_expansion: bool = True, custom_css: Optional[str] = None, show_truncation_message: bool = True, style_provider: Optional[StyleProvider] = None, use_shared_styles: bool = True) - - Configurable HTML formatter for DataFusion DataFrames. - - This class handles the HTML rendering of DataFrames for display in - Jupyter notebooks and other rich display contexts. - - This class supports extension through composition. Key extension points: - - Provide a custom StyleProvider for styling cells and headers - - Register custom formatters for specific types - - Provide custom cell builders for specialized cell rendering - - :param max_cell_length: Maximum characters to display in a cell before truncation - :param max_width: Maximum width of the HTML table in pixels - :param max_height: Maximum height of the HTML table in pixels - :param max_memory_bytes: Maximum memory in bytes for rendered data (default: 2MB) - :param min_rows_display: Minimum number of rows to display - :param repr_rows: Default number of rows to display in repr output - :param enable_cell_expansion: Whether to add expand/collapse buttons for long cell - values - :param custom_css: Additional CSS to include in the HTML output - :param show_truncation_message: Whether to display a message when data is truncated - :param style_provider: Custom provider for cell and header styles - :param use_shared_styles: Whether to load styles and scripts only once per notebook - session - - Initialize the HTML formatter. - - :param max_cell_length: Maximum length of cell content before truncation. - :type max_cell_length: int, default 25 - :param max_width: Maximum width of the displayed table in pixels. - :type max_width: int, default 1000 - :param max_height: Maximum height of the displayed table in pixels. - :type max_height: int, default 300 - :param max_memory_bytes: Maximum memory in bytes for rendered data. - :type max_memory_bytes: int, default 2097152 (2MB) - :param min_rows_display: Minimum number of rows to display. - :type min_rows_display: int, default 20 - :param repr_rows: Default number of rows to display in repr output. - :type repr_rows: int, default 10 - :param enable_cell_expansion: Whether to allow cells to expand when clicked. - :type enable_cell_expansion: bool, default True - :param custom_css: Custom CSS to apply to the HTML table. - :type custom_css: str, optional - :param show_truncation_message: Whether to show a message indicating that content has been truncated. - :type show_truncation_message: bool, default True - :param style_provider: Provider of CSS styles for the HTML table. If None, DefaultStyleProvider - is used. - :type style_provider: StyleProvider, optional - :param use_shared_styles: Whether to use shared styles across multiple tables. - :type use_shared_styles: bool, default True - :param Raises: - :param ------: - :param ValueError: If max_cell_length, max_width, max_height, max_memory_bytes, - min_rows_display, or repr_rows is not a positive integer. - :param TypeError: If enable_cell_expansion, show_truncation_message, or use_shared_styles is - not a boolean, - or if custom_css is provided but is not a string, - or if style_provider is provided but does not implement the StyleProvider - protocol. - - - .. py:method:: _build_expandable_cell(formatted_value: str, row_count: int, col_idx: int, table_uuid: str) -> str - - Build an expandable cell for long content. - - - - .. py:method:: _build_html_footer(has_more: bool) -> list[str] - - Build the HTML footer with JavaScript and messages. - - - - .. py:method:: _build_html_header() -> list[str] - - Build the HTML header with CSS styles. - - - - .. py:method:: _build_regular_cell(formatted_value: str) -> str - - Build a regular table cell. - - - - .. py:method:: _build_table_body(batches: list, table_uuid: str) -> list[str] - - Build the HTML table body with data rows. - - - - .. py:method:: _build_table_container_start() -> list[str] - - Build the opening tags for the table container. - - - - .. py:method:: _build_table_header(schema: Any) -> list[str] - - Build the HTML table header with column names. - - - - .. py:method:: _format_cell_value(value: Any) -> str - - Format a cell value for display. - - Uses registered type formatters if available. - - :param value: The cell value to format - - :returns: Formatted cell value as string - - - - .. py:method:: _get_cell_value(column: Any, row_idx: int) -> Any - - Extract a cell value from a column. - - :param column: Arrow array - :param row_idx: Row index - - :returns: The raw cell value - - - - .. py:method:: _get_default_css() -> str - - Get default CSS styles for the HTML table. - - - - .. py:method:: _get_javascript() -> str - - Get JavaScript code for interactive elements. - - - - .. py:method:: format_html(batches: list, schema: Any, has_more: bool = False, table_uuid: str | None = None) -> str - - Format record batches as HTML. - - This method is used by DataFrame's _repr_html_ implementation and can be - called directly when custom HTML rendering is needed. - - :param batches: List of Arrow RecordBatch objects - :param schema: Arrow Schema object - :param has_more: Whether there are more batches not shown - :param table_uuid: Unique ID for the table, used for JavaScript interactions - - :returns: HTML string representation of the data - - :raises TypeError: If schema is invalid and no batches are provided - - - - .. py:method:: is_styles_loaded() -> bool - :classmethod: - - - Check if HTML styles have been loaded in the current session. - - This method is primarily intended for debugging UI rendering issues - related to style loading. - - :returns: True if styles have been loaded, False otherwise - - .. rubric:: Example - - >>> from datafusion.html_formatter import DataFrameHtmlFormatter - >>> DataFrameHtmlFormatter.is_styles_loaded() - False - - - - .. py:method:: register_formatter(type_class: type, formatter: CellFormatter) -> None - - Register a custom formatter for a specific data type. - - :param type_class: The type to register a formatter for - :param formatter: Function that takes a value of the given type and returns - a formatted string - - - - .. py:method:: set_custom_cell_builder(builder: Callable[[Any, int, int, str], str]) -> None - - Set a custom cell builder function. - - :param builder: Function that takes (value, row, col, table_id) and returns HTML - - - - .. py:method:: set_custom_header_builder(builder: Callable[[Any], str]) -> None - - Set a custom header builder function. - - :param builder: Function that takes a field and returns HTML - - - - .. py:attribute:: _custom_cell_builder - :type: Optional[Callable[[Any, int, int, str], str]] - :value: None - - - - .. py:attribute:: _custom_header_builder - :type: Optional[Callable[[Any], str]] - :value: None - - - - .. py:attribute:: _styles_loaded - :value: False - - - - .. py:attribute:: _type_formatters - :type: dict[type, CellFormatter] - - - .. py:attribute:: custom_css - :value: None - - - - .. py:attribute:: enable_cell_expansion - :value: True - - - - .. py:attribute:: max_cell_length - :value: 25 - - - - .. py:attribute:: max_height - :value: 300 - - - - .. py:attribute:: max_memory_bytes - :value: 2097152 - - - - .. py:attribute:: max_width - :value: 1000 - - - - .. py:attribute:: min_rows_display - :value: 20 - - - - .. py:attribute:: repr_rows - :value: 10 - - - - .. py:attribute:: show_truncation_message - :value: True - - - - .. py:attribute:: style_provider - - - .. py:attribute:: use_shared_styles - :value: True - - - -.. py:class:: DefaultStyleProvider - - Default implementation of StyleProvider. - - - .. py:method:: get_cell_style() -> str - - Get the CSS style for table cells. - - :returns: CSS style string - - - - .. py:method:: get_header_style() -> str - - Get the CSS style for header cells. - - :returns: CSS style string - - - -.. py:class:: FormatterManager - - Manager class for the global DataFrame HTML formatter instance. - - - .. py:method:: get_formatter() -> DataFrameHtmlFormatter - :classmethod: - - - Get the current global DataFrame HTML formatter. - - :returns: The global HTML formatter instance - - - - .. py:method:: set_formatter(formatter: DataFrameHtmlFormatter) -> None - :classmethod: - - - Set the global DataFrame HTML formatter. - - :param formatter: The formatter instance to use globally - - - - .. py:attribute:: _default_formatter - :type: DataFrameHtmlFormatter - - -.. py:class:: StyleProvider - - Bases: :py:obj:`Protocol` - - - Protocol for HTML style providers. - - - .. py:method:: get_cell_style() -> str - - Get the CSS style for table cells. - - - - .. py:method:: get_header_style() -> str - - Get the CSS style for header cells. - - - -.. py:function:: _refresh_formatter_reference() -> None - - Refresh formatter reference in any modules using it. - - This helps ensure that changes to the formatter are reflected in existing - DataFrames that might be caching the formatter reference. - - -.. py:function:: _validate_bool(value: Any, param_name: str) -> None - - Validate that a parameter is a boolean. - - :param value: The value to validate - :param param_name: Name of the parameter (used in error message) - - :raises TypeError: If the value is not a boolean - - -.. py:function:: _validate_positive_int(value: Any, param_name: str) -> None - - Validate that a parameter is a positive integer. - - :param value: The value to validate - :param param_name: Name of the parameter (used in error message) - - :raises ValueError: If the value is not a positive integer - - -.. py:function:: configure_formatter(**kwargs: Any) -> None - - Configure the global DataFrame HTML formatter. - - This function creates a new formatter with the provided configuration - and sets it as the global formatter for all DataFrames. - - :param \*\*kwargs: Formatter configuration parameters like max_cell_length, - max_width, max_height, enable_cell_expansion, etc. - - :raises ValueError: If any invalid parameters are provided - - .. rubric:: Example - - >>> from datafusion.html_formatter import configure_formatter - >>> configure_formatter( - ... max_cell_length=50, - ... max_height=500, - ... enable_cell_expansion=True, - ... use_shared_styles=True - ... ) - - -.. py:function:: get_formatter() -> DataFrameHtmlFormatter - - Get the current global DataFrame HTML formatter. - - This function is used by the DataFrame._repr_html_ implementation to access - the shared formatter instance. It can also be used directly when custom - HTML rendering is needed. - - :returns: The global HTML formatter instance - - .. rubric:: Example - - >>> from datafusion.html_formatter import get_formatter - >>> formatter = get_formatter() - >>> formatter.max_cell_length = 50 # Increase cell length - - -.. py:function:: reset_formatter() -> None - - Reset the global DataFrame HTML formatter to default settings. - - This function creates a new formatter with default configuration - and sets it as the global formatter for all DataFrames. - - .. rubric:: Example - - >>> from datafusion.html_formatter import reset_formatter - >>> reset_formatter() # Reset formatter to default settings - - -.. py:function:: reset_styles_loaded_state() -> None - - Reset the styles loaded state to force reloading of styles. - - This can be useful when switching between notebook sessions or - when styles need to be refreshed. - - .. rubric:: Example - - >>> from datafusion.html_formatter import reset_styles_loaded_state - >>> reset_styles_loaded_state() # Force styles to reload in next render - - -.. py:function:: set_formatter(formatter: DataFrameHtmlFormatter) -> None - - Set the global DataFrame HTML formatter. - - :param formatter: The formatter instance to use globally - - .. rubric:: Example - - >>> from datafusion.html_formatter import get_formatter, set_formatter - >>> custom_formatter = DataFrameHtmlFormatter(max_cell_length=100) - >>> set_formatter(custom_formatter) - - diff --git a/_sources/autoapi/datafusion/index.rst.txt b/_sources/autoapi/datafusion/index.rst.txt index 07c99bf68..0b19b1d40 100644 --- a/_sources/autoapi/datafusion/index.rst.txt +++ b/_sources/autoapi/datafusion/index.rst.txt @@ -19,9 +19,9 @@ Submodules :maxdepth: 1 /autoapi/datafusion/catalog/index - /autoapi/datafusion/col/index /autoapi/datafusion/context/index /autoapi/datafusion/dataframe/index + /autoapi/datafusion/dataframe_formatter/index /autoapi/datafusion/expr/index /autoapi/datafusion/functions/index /autoapi/datafusion/html_formatter/index @@ -31,7 +31,6 @@ Submodules /autoapi/datafusion/plan/index /autoapi/datafusion/record_batch/index /autoapi/datafusion/substrait/index - /autoapi/datafusion/udf/index /autoapi/datafusion/unparser/index /autoapi/datafusion/user_defined/index @@ -62,6 +61,8 @@ Classes datafusion.ExecutionPlan datafusion.Expr datafusion.LogicalPlan + datafusion.ParquetColumnOptions + datafusion.ParquetWriterOptions datafusion.RecordBatch datafusion.RecordBatchStream datafusion.RuntimeEnvBuilder @@ -150,6 +151,23 @@ Package Contents + .. py:method:: __repr__() -> str + + Print a string representation of the Aggregate UDF. + + + + .. py:method:: from_pycapsule(func: AggregateUDFExportable) -> AggregateUDF + :staticmethod: + + + Create an Aggregate UDF from AggregateUDF PyCapsule object. + + This function will instantiate a Aggregate UDF that uses a DataFusion + AggregateUDF that is exported via the FFI bindings. + + + .. py:method:: udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: Optional[str] = None) -> Callable[Ellipsis, AggregateUDF] udaf(accum: Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: Optional[str] = None) -> AggregateUDF :staticmethod: @@ -210,6 +228,10 @@ Package Contents :param accum: The accumulator python function. Only needed when calling as a function. Skip this argument when using ``udaf`` as a decorator. + If you have a Rust backed AggregateUDF within a PyCapsule, you can + pass this parameter and ignore the rest. They will be determined + directly from the underlying function. See the online documentation + for more information. :param input_types: The data types of the arguments to ``accum``. :param return_type: The data type of the return value. :param state_type: The data types of the intermediate accumulation. @@ -224,48 +246,74 @@ Package Contents .. py:attribute:: _udaf -.. py:class:: Catalog(catalog: datafusion._internal.Catalog) +.. py:class:: Catalog(catalog: datafusion._internal.catalog.RawCatalog) DataFusion data catalog. This constructor is not typically called by the end user. - .. py:method:: database(name: str = 'public') -> Database + .. py:method:: __repr__() -> str - Returns the database with the given ``name`` from this catalog. + Print a string representation of the catalog. - .. py:method:: names() -> list[str] + .. py:method:: database(name: str = 'public') -> Schema - Returns the list of databases in this catalog. + Returns the database with the given ``name`` from this catalog. - .. py:attribute:: catalog + .. py:method:: deregister_schema(name: str, cascade: bool = True) -> Schema | None + Deregister a schema from this catalog. -.. py:class:: Database(db: datafusion._internal.Database) - DataFusion Database. - This constructor is not typically called by the end user. + .. py:method:: memory_catalog() -> Catalog + :staticmethod: + + + Create an in-memory catalog provider. + .. py:method:: names() -> set[str] - Returns the list of all tables in this database. + This is an alias for `schema_names`. + + + + .. py:method:: register_schema(name, schema) -> Schema | None + + Register a schema with this catalog. + + + + .. py:method:: schema(name: str = 'public') -> Schema + + Returns the database with the given ``name`` from this catalog. + + + + .. py:method:: schema_names() -> set[str] + Returns the list of schemas in this catalog. - .. py:method:: table(name: str) -> Table - Return the table with the given ``name`` from this database. + .. py:attribute:: catalog + +.. py:class:: Database(schema: datafusion._internal.catalog.RawSchema) + Bases: :py:obj:`Schema` - .. py:attribute:: db + + See `Schema`. + + This constructor is not typically called by the end user. .. py:class:: ExecutionPlan(plan: datafusion._internal.ExecutionPlan) @@ -850,6 +898,17 @@ Package Contents + .. py:method:: literal_with_metadata(value: Any, metadata: dict[str, str]) -> Expr + :staticmethod: + + + Creates a new expression representing a scalar value with metadata. + + :param value: A valid PyArrow scalar value or easily castable to one. + :param metadata: Metadata to attach to the expression. + + + .. py:method:: ln() -> Expr Returns the natural logarithm (base e) of the argument. @@ -1244,6 +1303,324 @@ Package Contents .. py:attribute:: _raw_plan +.. py:class:: ParquetColumnOptions(encoding: Optional[str] = None, dictionary_enabled: Optional[bool] = None, compression: Optional[str] = None, statistics_enabled: Optional[str] = None, bloom_filter_enabled: Optional[bool] = None, bloom_filter_fpp: Optional[float] = None, bloom_filter_ndv: Optional[int] = None) + + Parquet options for individual columns. + + Contains the available options that can be applied for an individual Parquet column, + replacing the global options in `ParquetWriterOptions`. + + .. attribute:: encoding + + Sets encoding for the column path. Valid values are: `plain`, + `plain_dictionary`, `rle`, `bit_packed`, `delta_binary_packed`, + `delta_length_byte_array`, `delta_byte_array`, `rle_dictionary`, and + `byte_stream_split`. These values are not case-sensitive. If `None`, uses + the default parquet options + + .. attribute:: dictionary_enabled + + Sets if dictionary encoding is enabled for the column path. + If `None`, uses the default parquet options + + .. attribute:: compression + + Sets default parquet compression codec for the column path. Valid + values are `uncompressed`, `snappy`, `gzip(level)`, `lzo`, `brotli(level)`, + `lz4`, `zstd(level)`, and `lz4_raw`. These values are not case-sensitive. If + `None`, uses the default parquet options. + + .. attribute:: statistics_enabled + + Sets if statistics are enabled for the column Valid values + are: `none`, `chunk`, and `page` These values are not case sensitive. If + `None`, uses the default parquet options. + + .. attribute:: bloom_filter_enabled + + Sets if bloom filter is enabled for the column path. If + `None`, uses the default parquet options. + + .. attribute:: bloom_filter_fpp + + Sets bloom filter false positive probability for the column + path. If `None`, uses the default parquet options. + + .. attribute:: bloom_filter_ndv + + Sets bloom filter number of distinct values. If `None`, uses + the default parquet options. + + Initialize the ParquetColumnOptions. + + + .. py:attribute:: bloom_filter_enabled + :value: None + + + + .. py:attribute:: bloom_filter_fpp + :value: None + + + + .. py:attribute:: bloom_filter_ndv + :value: None + + + + .. py:attribute:: compression + :value: None + + + + .. py:attribute:: dictionary_enabled + :value: None + + + + .. py:attribute:: encoding + :value: None + + + + .. py:attribute:: statistics_enabled + :value: None + + + +.. py:class:: ParquetWriterOptions(data_pagesize_limit: int = 1024 * 1024, write_batch_size: int = 1024, writer_version: str = '1.0', skip_arrow_metadata: bool = False, compression: Optional[str] = 'zstd(3)', compression_level: Optional[int] = None, dictionary_enabled: Optional[bool] = True, dictionary_page_size_limit: int = 1024 * 1024, statistics_enabled: Optional[str] = 'page', max_row_group_size: int = 1024 * 1024, created_by: str = 'datafusion-python', column_index_truncate_length: Optional[int] = 64, statistics_truncate_length: Optional[int] = None, data_page_row_count_limit: int = 20000, encoding: Optional[str] = None, bloom_filter_on_write: bool = False, bloom_filter_fpp: Optional[float] = None, bloom_filter_ndv: Optional[int] = None, allow_single_file_parallelism: bool = True, maximum_parallel_row_group_writers: int = 1, maximum_buffered_record_batches_per_stream: int = 2, column_specific_options: Optional[dict[str, ParquetColumnOptions]] = None) + + Advanced parquet writer options. + + Allows settings the writer options that apply to the entire file. Some options can + also be set on a column by column basis, with the field `column_specific_options` + (see `ParquetColumnOptions`). + + .. attribute:: data_pagesize_limit + + Sets best effort maximum size of data page in bytes. + + .. attribute:: write_batch_size + + Sets write_batch_size in bytes. + + .. attribute:: writer_version + + Sets parquet writer version. Valid values are `1.0` and + `2.0`. + + .. attribute:: skip_arrow_metadata + + Skip encoding the embedded arrow metadata in the + KV_meta. + + .. attribute:: compression + + Compression type to use. Default is "zstd(3)". + Available compression types are + - "uncompressed": No compression. + - "snappy": Snappy compression. + - "gzip(n)": Gzip compression with level n. + - "brotli(n)": Brotli compression with level n. + - "lz4": LZ4 compression. + - "lz4_raw": LZ4_RAW compression. + - "zstd(n)": Zstandard compression with level n. + + .. attribute:: dictionary_enabled + + Sets if dictionary encoding is enabled. If None, uses + the default parquet writer setting. + + .. attribute:: dictionary_page_size_limit + + Sets best effort maximum dictionary page size, + in bytes. + + .. attribute:: statistics_enabled + + Sets if statistics are enabled for any column Valid + values are `none`, `chunk`, and `page`. If None, uses the default + parquet writer setting. + + .. attribute:: max_row_group_size + + Target maximum number of rows in each row group + (defaults to 1M rows). Writing larger row groups requires more memory to + write, but can get better compression and be faster to read. + + .. attribute:: created_by + + Sets "created by" property. + + .. attribute:: column_index_truncate_length + + Sets column index truncate length. + + .. attribute:: statistics_truncate_length + + Sets statistics truncate length. If None, uses + the default parquet writer setting. + + .. attribute:: data_page_row_count_limit + + Sets best effort maximum number of rows in a data + page. + + .. attribute:: encoding + + Sets default encoding for any column. Valid values are `plain`, + `plain_dictionary`, `rle`, `bit_packed`, `delta_binary_packed`, + `delta_length_byte_array`, `delta_byte_array`, `rle_dictionary`, and + `byte_stream_split`. If None, uses the default parquet writer setting. + + .. attribute:: bloom_filter_on_write + + Write bloom filters for all columns when creating + parquet files. + + .. attribute:: bloom_filter_fpp + + Sets bloom filter false positive probability. If None, + uses the default parquet writer setting + + .. attribute:: bloom_filter_ndv + + Sets bloom filter number of distinct values. If None, uses + the default parquet writer setting. + + .. attribute:: allow_single_file_parallelism + + Controls whether DataFusion will attempt to + speed up writing parquet files by serializing them in parallel. Each + column in each row group in each output file are serialized in parallel + leveraging a maximum possible core count of n_files * n_row_groups * + n_columns. + + .. attribute:: maximum_parallel_row_group_writers + + By default parallel parquet writer is + tuned for minimum memory usage in a streaming execution plan. You may + see a performance benefit when writing large parquet files by increasing + `maximum_parallel_row_group_writers` and + `maximum_buffered_record_batches_per_stream` if your system has idle + cores and can tolerate additional memory usage. Boosting these values is + likely worthwhile when writing out already in-memory data, such as from + a cached data frame. + + .. attribute:: maximum_buffered_record_batches_per_stream + + See + `maximum_parallel_row_group_writers`. + + .. attribute:: column_specific_options + + Overrides options for specific columns. If a column + is not a part of this dictionary, it will use the parameters provided here. + + Initialize the ParquetWriterOptions. + + + .. py:attribute:: allow_single_file_parallelism + :value: True + + + + .. py:attribute:: bloom_filter_fpp + :value: None + + + + .. py:attribute:: bloom_filter_ndv + :value: None + + + + .. py:attribute:: bloom_filter_on_write + :value: False + + + + .. py:attribute:: column_index_truncate_length + :value: 64 + + + + .. py:attribute:: column_specific_options + :value: None + + + + .. py:attribute:: created_by + :value: 'datafusion-python' + + + + .. py:attribute:: data_page_row_count_limit + :value: 20000 + + + + .. py:attribute:: data_pagesize_limit + :value: 1048576 + + + + .. py:attribute:: dictionary_enabled + :value: True + + + + .. py:attribute:: dictionary_page_size_limit + :value: 1048576 + + + + .. py:attribute:: encoding + :value: None + + + + .. py:attribute:: max_row_group_size + :value: 1048576 + + + + .. py:attribute:: maximum_buffered_record_batches_per_stream + :value: 2 + + + + .. py:attribute:: maximum_parallel_row_group_writers + :value: 1 + + + + .. py:attribute:: skip_arrow_metadata + :value: False + + + + .. py:attribute:: statistics_enabled + :value: 'page' + + + + .. py:attribute:: statistics_truncate_length + :value: None + + + + .. py:attribute:: write_batch_size + :value: 1024 + + + + .. py:attribute:: writer_version + :value: '1.0' + + + .. py:class:: RecordBatch(record_batch: datafusion._internal.RecordBatch) This class is essentially a wrapper for :py:class:`pa.RecordBatch`. @@ -1494,8 +1871,26 @@ Package Contents + .. py:method:: __repr__() -> str + + Print a string representation of the Scalar UDF. + + + + .. py:method:: from_pycapsule(func: ScalarUDFExportable) -> ScalarUDF + :staticmethod: + + + Create a Scalar UDF from ScalarUDF PyCapsule object. + + This function will instantiate a Scalar UDF that uses a DataFusion + ScalarUDF that is exported via the FFI bindings. + + + .. py:method:: udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: Optional[str] = None) -> Callable[Ellipsis, ScalarUDF] udf(func: Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: Optional[str] = None) -> ScalarUDF + udf(func: ScalarUDFExportable) -> ScalarUDF :staticmethod: @@ -1509,7 +1904,10 @@ Package Contents When used a decorator, do **not** pass ``func`` explicitly. :param func: Only needed when calling as a function. - Skip this argument when using ``udf`` as a decorator. + Skip this argument when using `udf` as a decorator. If you have a Rust + backed ScalarUDF within a PyCapsule, you can pass this parameter + and ignore the rest. They will be determined directly from the + underlying function. See the online documentation for more information. :type func: Callable, optional :param input_types: The data types of the arguments to ``func``. This list must be of the same length as the number of @@ -1699,13 +2097,27 @@ Package Contents .. py:attribute:: config_internal -.. py:class:: Table(table: datafusion._internal.Table) +.. py:class:: Table(table: datafusion._internal.catalog.RawTable) DataFusion table. This constructor is not typically called by the end user. + .. py:method:: __repr__() -> str + + Print a string representation of the table. + + + + .. py:method:: from_dataset(dataset: pyarrow.dataset.Dataset) -> Table + :staticmethod: + + + Turn a pyarrow Dataset into a Table. + + + .. py:property:: kind :type: str @@ -1791,6 +2203,12 @@ Package Contents parameter must be set. + .. py:method:: __repr__() -> str + + Print a string representation of the window frame. + + + .. py:method:: get_frame_units() -> str Returns the window frame units for the bounds. @@ -1834,6 +2252,12 @@ Package Contents + .. py:method:: __repr__() -> str + + Print a string representation of the Window UDF. + + + .. py:method:: _create_window_udf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: Optional[str] = None) -> WindowUDF :staticmethod: @@ -1866,6 +2290,17 @@ Package Contents + .. py:method:: from_pycapsule(func: WindowUDFExportable) -> WindowUDF + :staticmethod: + + + Create a Window UDF from WindowUDF PyCapsule object. + + This function will instantiate a Window UDF that uses a DataFusion + WindowUDF that is exported via the FFI bindings. + + + .. py:method:: udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: Optional[str] = None) -> Callable[Ellipsis, WindowUDF] udwf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: Optional[str] = None) -> WindowUDF :staticmethod: @@ -1907,7 +2342,10 @@ Package Contents return BiasedNumbers(10) :param func: Only needed when calling as a function. Skip this argument when - using ``udwf`` as a decorator. + using ``udwf`` as a decorator. If you have a Rust backed WindowUDF + within a PyCapsule, you can pass this parameter and ignore the rest. + They will be determined directly from the underlying function. See + the online documentation for more information. :param input_types: The data types of the arguments. :param return_type: The data type of the return value. :param volatility: See :py:class:`Volatility` for allowed values. @@ -1953,7 +2391,7 @@ Package Contents Create a literal expression. -.. py:function:: read_avro(path: str | pathlib.Path, schema: pyarrow.Schema | None = None, file_partition_cols: list[tuple[str, str]] | None = None, file_extension: str = '.avro') -> datafusion.dataframe.DataFrame +.. py:function:: read_avro(path: str | pathlib.Path, schema: pyarrow.Schema | None = None, file_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_extension: str = '.avro') -> datafusion.dataframe.DataFrame Create a :py:class:`DataFrame` for reading Avro data source. @@ -1969,7 +2407,7 @@ Package Contents :returns: DataFrame representation of the read Avro file -.. py:function:: read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str]] | None = None, file_compression_type: str | None = None) -> datafusion.dataframe.DataFrame +.. py:function:: read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None) -> datafusion.dataframe.DataFrame Read a CSV data source. @@ -1994,7 +2432,7 @@ Package Contents :returns: DataFrame representation of the read CSV files -.. py:function:: read_json(path: str | pathlib.Path, schema: pyarrow.Schema | None = None, schema_infer_max_records: int = 1000, file_extension: str = '.json', table_partition_cols: list[tuple[str, str]] | None = None, file_compression_type: str | None = None) -> datafusion.dataframe.DataFrame +.. py:function:: read_json(path: str | pathlib.Path, schema: pyarrow.Schema | None = None, schema_infer_max_records: int = 1000, file_extension: str = '.json', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None) -> datafusion.dataframe.DataFrame Read a line-delimited JSON data source. @@ -2014,7 +2452,7 @@ Package Contents :returns: DataFrame representation of the read JSON files. -.. py:function:: read_parquet(path: str | pathlib.Path, table_partition_cols: list[tuple[str, str]] | None = None, parquet_pruning: bool = True, file_extension: str = '.parquet', skip_metadata: bool = True, schema: pyarrow.Schema | None = None, file_sort_order: list[list[datafusion.expr.Expr]] | None = None) -> datafusion.dataframe.DataFrame +.. py:function:: read_parquet(path: str | pathlib.Path, table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, parquet_pruning: bool = True, file_extension: str = '.parquet', skip_metadata: bool = True, schema: pyarrow.Schema | None = None, file_sort_order: list[list[datafusion.expr.Expr]] | None = None) -> datafusion.dataframe.DataFrame Read a Parquet source into a :py:class:`~datafusion.dataframe.Dataframe`. diff --git a/_sources/autoapi/datafusion/io/index.rst.txt b/_sources/autoapi/datafusion/io/index.rst.txt index 79ef20e5e..bb80c1cd3 100644 --- a/_sources/autoapi/datafusion/io/index.rst.txt +++ b/_sources/autoapi/datafusion/io/index.rst.txt @@ -23,7 +23,7 @@ Functions Module Contents --------------- -.. py:function:: read_avro(path: str | pathlib.Path, schema: pyarrow.Schema | None = None, file_partition_cols: list[tuple[str, str]] | None = None, file_extension: str = '.avro') -> datafusion.dataframe.DataFrame +.. py:function:: read_avro(path: str | pathlib.Path, schema: pyarrow.Schema | None = None, file_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_extension: str = '.avro') -> datafusion.dataframe.DataFrame Create a :py:class:`DataFrame` for reading Avro data source. @@ -39,7 +39,7 @@ Module Contents :returns: DataFrame representation of the read Avro file -.. py:function:: read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str]] | None = None, file_compression_type: str | None = None) -> datafusion.dataframe.DataFrame +.. py:function:: read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None) -> datafusion.dataframe.DataFrame Read a CSV data source. @@ -64,7 +64,7 @@ Module Contents :returns: DataFrame representation of the read CSV files -.. py:function:: read_json(path: str | pathlib.Path, schema: pyarrow.Schema | None = None, schema_infer_max_records: int = 1000, file_extension: str = '.json', table_partition_cols: list[tuple[str, str]] | None = None, file_compression_type: str | None = None) -> datafusion.dataframe.DataFrame +.. py:function:: read_json(path: str | pathlib.Path, schema: pyarrow.Schema | None = None, schema_infer_max_records: int = 1000, file_extension: str = '.json', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None) -> datafusion.dataframe.DataFrame Read a line-delimited JSON data source. @@ -84,7 +84,7 @@ Module Contents :returns: DataFrame representation of the read JSON files. -.. py:function:: read_parquet(path: str | pathlib.Path, table_partition_cols: list[tuple[str, str]] | None = None, parquet_pruning: bool = True, file_extension: str = '.parquet', skip_metadata: bool = True, schema: pyarrow.Schema | None = None, file_sort_order: list[list[datafusion.expr.Expr]] | None = None) -> datafusion.dataframe.DataFrame +.. py:function:: read_parquet(path: str | pathlib.Path, table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, parquet_pruning: bool = True, file_extension: str = '.parquet', skip_metadata: bool = True, schema: pyarrow.Schema | None = None, file_sort_order: list[list[datafusion.expr.Expr]] | None = None) -> datafusion.dataframe.DataFrame Read a Parquet source into a :py:class:`~datafusion.dataframe.Dataframe`. diff --git a/_sources/autoapi/datafusion/udf/index.rst.txt b/_sources/autoapi/datafusion/udf/index.rst.txt deleted file mode 100644 index c11c9e6c8..000000000 --- a/_sources/autoapi/datafusion/udf/index.rst.txt +++ /dev/null @@ -1,11 +0,0 @@ -datafusion.udf -============== - -.. py:module:: datafusion.udf - -.. autoapi-nested-parse:: - - Deprecated module for user defined functions. - - - diff --git a/_sources/autoapi/datafusion/user_defined/index.rst.txt b/_sources/autoapi/datafusion/user_defined/index.rst.txt index d6c30ab16..728ace0a6 100644 --- a/_sources/autoapi/datafusion/user_defined/index.rst.txt +++ b/_sources/autoapi/datafusion/user_defined/index.rst.txt @@ -28,11 +28,14 @@ Classes datafusion.user_defined.Accumulator datafusion.user_defined.AggregateUDF + datafusion.user_defined.AggregateUDFExportable datafusion.user_defined.ScalarUDF + datafusion.user_defined.ScalarUDFExportable datafusion.user_defined.TableFunction datafusion.user_defined.Volatility datafusion.user_defined.WindowEvaluator datafusion.user_defined.WindowUDF + datafusion.user_defined.WindowUDFExportable Module Contents @@ -97,6 +100,23 @@ Module Contents + .. py:method:: __repr__() -> str + + Print a string representation of the Aggregate UDF. + + + + .. py:method:: from_pycapsule(func: AggregateUDFExportable) -> AggregateUDF + :staticmethod: + + + Create an Aggregate UDF from AggregateUDF PyCapsule object. + + This function will instantiate a Aggregate UDF that uses a DataFusion + AggregateUDF that is exported via the FFI bindings. + + + .. py:method:: udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: Optional[str] = None) -> Callable[Ellipsis, AggregateUDF] udaf(accum: Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: Optional[str] = None) -> AggregateUDF :staticmethod: @@ -157,6 +177,10 @@ Module Contents :param accum: The accumulator python function. Only needed when calling as a function. Skip this argument when using ``udaf`` as a decorator. + If you have a Rust backed AggregateUDF within a PyCapsule, you can + pass this parameter and ignore the rest. They will be determined + directly from the underlying function. See the online documentation + for more information. :param input_types: The data types of the arguments to ``accum``. :param return_type: The data type of the return value. :param state_type: The data types of the intermediate accumulation. @@ -171,6 +195,17 @@ Module Contents .. py:attribute:: _udaf +.. py:class:: AggregateUDFExportable + + Bases: :py:obj:`Protocol` + + + Type hint for object that has __datafusion_aggregate_udf__ PyCapsule. + + + .. py:method:: __datafusion_aggregate_udf__() -> object + + .. py:class:: ScalarUDF(name: str, func: Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str) Class for performing scalar user-defined functions (UDF). @@ -192,8 +227,26 @@ Module Contents + .. py:method:: __repr__() -> str + + Print a string representation of the Scalar UDF. + + + + .. py:method:: from_pycapsule(func: ScalarUDFExportable) -> ScalarUDF + :staticmethod: + + + Create a Scalar UDF from ScalarUDF PyCapsule object. + + This function will instantiate a Scalar UDF that uses a DataFusion + ScalarUDF that is exported via the FFI bindings. + + + .. py:method:: udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: Optional[str] = None) -> Callable[Ellipsis, ScalarUDF] udf(func: Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: Optional[str] = None) -> ScalarUDF + udf(func: ScalarUDFExportable) -> ScalarUDF :staticmethod: @@ -207,7 +260,10 @@ Module Contents When used a decorator, do **not** pass ``func`` explicitly. :param func: Only needed when calling as a function. - Skip this argument when using ``udf`` as a decorator. + Skip this argument when using `udf` as a decorator. If you have a Rust + backed ScalarUDF within a PyCapsule, you can pass this parameter + and ignore the rest. They will be determined directly from the + underlying function. See the online documentation for more information. :type func: Callable, optional :param input_types: The data types of the arguments to ``func``. This list must be of the same length as the number of @@ -241,6 +297,17 @@ Module Contents .. py:attribute:: _udf +.. py:class:: ScalarUDFExportable + + Bases: :py:obj:`Protocol` + + + Type hint for object that has __datafusion_scalar_udf__ PyCapsule. + + + .. py:method:: __datafusion_scalar_udf__() -> object + + .. py:class:: TableFunction(name: str, func: Callable[[], any]) Class for performing user-defined table functions (UDTF). @@ -544,6 +611,12 @@ Module Contents + .. py:method:: __repr__() -> str + + Print a string representation of the Window UDF. + + + .. py:method:: _create_window_udf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: Optional[str] = None) -> WindowUDF :staticmethod: @@ -576,6 +649,17 @@ Module Contents + .. py:method:: from_pycapsule(func: WindowUDFExportable) -> WindowUDF + :staticmethod: + + + Create a Window UDF from WindowUDF PyCapsule object. + + This function will instantiate a Window UDF that uses a DataFusion + WindowUDF that is exported via the FFI bindings. + + + .. py:method:: udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: Optional[str] = None) -> Callable[Ellipsis, WindowUDF] udwf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: Optional[str] = None) -> WindowUDF :staticmethod: @@ -617,7 +701,10 @@ Module Contents return BiasedNumbers(10) :param func: Only needed when calling as a function. Skip this argument when - using ``udwf`` as a decorator. + using ``udwf`` as a decorator. If you have a Rust backed WindowUDF + within a PyCapsule, you can pass this parameter and ignore the rest. + They will be determined directly from the underlying function. See + the online documentation for more information. :param input_types: The data types of the arguments. :param return_type: The data type of the return value. :param volatility: See :py:class:`Volatility` for allowed values. @@ -630,6 +717,17 @@ Module Contents .. py:attribute:: _udwf +.. py:class:: WindowUDFExportable + + Bases: :py:obj:`Protocol` + + + Type hint for object that has __datafusion_window_udf__ PyCapsule. + + + .. py:method:: __datafusion_window_udf__() -> object + + .. py:data:: _R .. py:data:: udaf diff --git a/_sources/contributor-guide/ffi.rst.txt b/_sources/contributor-guide/ffi.rst.txt index c1f9806b3..a40af1234 100644 --- a/_sources/contributor-guide/ffi.rst.txt +++ b/_sources/contributor-guide/ffi.rst.txt @@ -176,7 +176,7 @@ By convention the ``datafusion-python`` library expects a Python object that has ``TableProvider`` PyCapsule to have this capsule accessible by calling a function named ``__datafusion_table_provider__``. You can see a complete working example of how to share a ``TableProvider`` from one python library to DataFusion Python in the -`repository examples folder `_. +`repository examples folder `_. This section has been written using ``TableProvider`` as an example. It is the first extension that has been written using this approach and the most thoroughly implemented. diff --git a/_sources/index.rst.txt b/_sources/index.rst.txt index c18793822..adec60f48 100644 --- a/_sources/index.rst.txt +++ b/_sources/index.rst.txt @@ -72,7 +72,7 @@ Example user-guide/introduction user-guide/basics user-guide/data-sources - user-guide/dataframe + user-guide/dataframe/index user-guide/common-operations/index user-guide/io/index user-guide/configuration diff --git a/_sources/user-guide/basics.rst.txt b/_sources/user-guide/basics.rst.txt index 2975d9a6b..7c6820461 100644 --- a/_sources/user-guide/basics.rst.txt +++ b/_sources/user-guide/basics.rst.txt @@ -73,7 +73,7 @@ DataFrames are typically created by calling a method on :py:class:`~datafusion.c calling the transformation methods, such as :py:func:`~datafusion.dataframe.DataFrame.filter`, :py:func:`~datafusion.dataframe.DataFrame.select`, :py:func:`~datafusion.dataframe.DataFrame.aggregate`, and :py:func:`~datafusion.dataframe.DataFrame.limit` to build up a query definition. -For more details on working with DataFrames, including visualization options and conversion to other formats, see :doc:`dataframe`. +For more details on working with DataFrames, including visualization options and conversion to other formats, see :doc:`dataframe/index`. Expressions ----------- diff --git a/_sources/user-guide/common-operations/functions.rst.txt b/_sources/user-guide/common-operations/functions.rst.txt index d458d3eb0..ccb47a4e7 100644 --- a/_sources/user-guide/common-operations/functions.rst.txt +++ b/_sources/user-guide/common-operations/functions.rst.txt @@ -132,7 +132,7 @@ The function :py:func:`~datafusion.functions.in_list` allows to check a column f Handling Missing Values -===================== +======================= DataFusion provides methods to handle missing values in DataFrames: diff --git a/_sources/user-guide/data-sources.rst.txt b/_sources/user-guide/data-sources.rst.txt index ba5967c97..9c95d58e0 100644 --- a/_sources/user-guide/data-sources.rst.txt +++ b/_sources/user-guide/data-sources.rst.txt @@ -185,3 +185,59 @@ the interface as describe in the :ref:`Custom Table Provider `_ is provided in the DataFusion repository. + +Catalog +======= + +A common technique for organizing tables is using a three level hierarchical approach. DataFusion +supports this form of organizing using the :py:class:`~datafusion.catalog.Catalog`, +:py:class:`~datafusion.catalog.Schema`, and :py:class:`~datafusion.catalog.Table`. By default, +a :py:class:`~datafusion.context.SessionContext` comes with a single Catalog and a single Schema +with the names ``datafusion`` and ``default``, respectively. + +The default implementation uses an in-memory approach to the catalog and schema. We have support +for adding additional in-memory catalogs and schemas. This can be done like in the following +example: + +.. code-block:: python + + from datafusion.catalog import Catalog, Schema + + my_catalog = Catalog.memory_catalog() + my_schema = Schema.memory_schema() + + my_catalog.register_schema("my_schema_name", my_schema) + + ctx.register_catalog("my_catalog_name", my_catalog) + +You could then register tables in ``my_schema`` and access them either through the DataFrame +API or via sql commands such as ``"SELECT * from my_catalog_name.my_schema_name.my_table"``. + +User Defined Catalog and Schema +------------------------------- + +If the in-memory catalogs are insufficient for your uses, there are two approaches you can take +to implementing a custom catalog and/or schema. In the below discussion, we describe how to +implement these for a Catalog, but the approach to implementing for a Schema is nearly +identical. + +DataFusion supports Catalogs written in either Rust or Python. If you write a Catalog in Rust, +you will need to export it as a Python library via PyO3. There is a complete example of a +catalog implemented this way in the +`examples folder `_ +of our repository. Writing catalog providers in Rust provides typically can lead to significant +performance improvements over the Python based approach. + +To implement a Catalog in Python, you will need to inherit from the abstract base class +:py:class:`~datafusion.catalog.CatalogProvider`. There are examples in the +`unit tests `_ of +implementing a basic Catalog in Python where we simply keep a dictionary of the +registered Schemas. + +One important note for developers is that when we have a Catalog defined in Python, we have +two different ways of accessing this Catalog. First, we register the catalog with a Rust +wrapper. This allows for any rust based code to call the Python functions as necessary. +Second, if the user access the Catalog via the Python API, we identify this and return back +the original Python object that implements the Catalog. This is an important distinction +for developers because we do *not* return a Python wrapper around the Rust wrapper of the +original Python object. diff --git a/_sources/user-guide/dataframe/index.rst.txt b/_sources/user-guide/dataframe/index.rst.txt new file mode 100644 index 000000000..f69485af7 --- /dev/null +++ b/_sources/user-guide/dataframe/index.rst.txt @@ -0,0 +1,209 @@ +.. Licensed to the Apache Software Foundation (ASF) under one +.. or more contributor license agreements. See the NOTICE file +.. distributed with this work for additional information +.. regarding copyright ownership. The ASF licenses this file +.. to you under the Apache License, Version 2.0 (the +.. "License"); you may not use this file except in compliance +.. with the License. You may obtain a copy of the License at + +.. http://www.apache.org/licenses/LICENSE-2.0 + +.. Unless required by applicable law or agreed to in writing, +.. software distributed under the License is distributed on an +.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +.. KIND, either express or implied. See the License for the +.. specific language governing permissions and limitations +.. under the License. + +DataFrames +========== + +Overview +-------- + +The ``DataFrame`` class is the core abstraction in DataFusion that represents tabular data and operations +on that data. DataFrames provide a flexible API for transforming data through various operations such as +filtering, projection, aggregation, joining, and more. + +A DataFrame represents a logical plan that is lazily evaluated. The actual execution occurs only when +terminal operations like ``collect()``, ``show()``, or ``to_pandas()`` are called. + +Creating DataFrames +------------------- + +DataFrames can be created in several ways: + +* From SQL queries via a ``SessionContext``: + + .. code-block:: python + + from datafusion import SessionContext + + ctx = SessionContext() + df = ctx.sql("SELECT * FROM your_table") + +* From registered tables: + + .. code-block:: python + + df = ctx.table("your_table") + +* From various data sources: + + .. code-block:: python + + # From CSV files (see :ref:`io_csv` for detailed options) + df = ctx.read_csv("path/to/data.csv") + + # From Parquet files (see :ref:`io_parquet` for detailed options) + df = ctx.read_parquet("path/to/data.parquet") + + # From JSON files (see :ref:`io_json` for detailed options) + df = ctx.read_json("path/to/data.json") + + # From Avro files (see :ref:`io_avro` for detailed options) + df = ctx.read_avro("path/to/data.avro") + + # From Pandas DataFrame + import pandas as pd + pandas_df = pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]}) + df = ctx.from_pandas(pandas_df) + + # From Arrow data + import pyarrow as pa + batch = pa.RecordBatch.from_arrays( + [pa.array([1, 2, 3]), pa.array([4, 5, 6])], + names=["a", "b"] + ) + df = ctx.from_arrow(batch) + +For detailed information about reading from different data sources, see the :doc:`I/O Guide <../io/index>`. +For custom data sources, see :ref:`io_custom_table_provider`. + +Common DataFrame Operations +--------------------------- + +DataFusion's DataFrame API offers a wide range of operations: + +.. code-block:: python + + from datafusion import column, literal + + # Select specific columns + df = df.select("col1", "col2") + + # Select with expressions + df = df.select(column("a") + column("b"), column("a") - column("b")) + + # Filter rows + df = df.filter(column("age") > literal(25)) + + # Add computed columns + df = df.with_column("full_name", column("first_name") + literal(" ") + column("last_name")) + + # Multiple column additions + df = df.with_columns( + (column("a") + column("b")).alias("sum"), + (column("a") * column("b")).alias("product") + ) + + # Sort data + df = df.sort(column("age").sort(ascending=False)) + + # Join DataFrames + df = df1.join(df2, on="user_id", how="inner") + + # Aggregate data + from datafusion import functions as f + df = df.aggregate( + [], # Group by columns (empty for global aggregation) + [f.sum(column("amount")).alias("total_amount")] + ) + + # Limit rows + df = df.limit(100) + + # Drop columns + df = df.drop("temporary_column") + +Terminal Operations +------------------- + +To materialize the results of your DataFrame operations: + +.. code-block:: python + + # Collect all data as PyArrow RecordBatches + result_batches = df.collect() + + # Convert to various formats + pandas_df = df.to_pandas() # Pandas DataFrame + polars_df = df.to_polars() # Polars DataFrame + arrow_table = df.to_arrow_table() # PyArrow Table + py_dict = df.to_pydict() # Python dictionary + py_list = df.to_pylist() # Python list of dictionaries + + # Display results + df.show() # Print tabular format to console + + # Count rows + count = df.count() + +HTML Rendering +-------------- + +When working in Jupyter notebooks or other environments that support HTML rendering, DataFrames will +automatically display as formatted HTML tables. For detailed information about customizing HTML +rendering, formatting options, and advanced styling, see :doc:`rendering`. + +Core Classes +------------ + +**DataFrame** + The main DataFrame class for building and executing queries. + + See: :py:class:`datafusion.DataFrame` + +**SessionContext** + The primary entry point for creating DataFrames from various data sources. + + Key methods for DataFrame creation: + + * :py:meth:`~datafusion.SessionContext.read_csv` - Read CSV files + * :py:meth:`~datafusion.SessionContext.read_parquet` - Read Parquet files + * :py:meth:`~datafusion.SessionContext.read_json` - Read JSON files + * :py:meth:`~datafusion.SessionContext.read_avro` - Read Avro files + * :py:meth:`~datafusion.SessionContext.table` - Access registered tables + * :py:meth:`~datafusion.SessionContext.sql` - Execute SQL queries + * :py:meth:`~datafusion.SessionContext.from_pandas` - Create from Pandas DataFrame + * :py:meth:`~datafusion.SessionContext.from_arrow` - Create from Arrow data + + See: :py:class:`datafusion.SessionContext` + +Expression Classes +------------------ + +**Expr** + Represents expressions that can be used in DataFrame operations. + + See: :py:class:`datafusion.Expr` + +**Functions for creating expressions:** + +* :py:func:`datafusion.column` - Reference a column by name +* :py:func:`datafusion.literal` - Create a literal value expression + +Built-in Functions +------------------ + +DataFusion provides many built-in functions for data manipulation: + +* :py:mod:`datafusion.functions` - Mathematical, string, date/time, and aggregation functions + +For a complete list of available functions, see the :py:mod:`datafusion.functions` module documentation. + + +.. toctree:: + :maxdepth: 1 + + rendering diff --git a/_sources/user-guide/dataframe.rst.txt b/_sources/user-guide/dataframe/rendering.rst.txt similarity index 72% rename from _sources/user-guide/dataframe.rst.txt rename to _sources/user-guide/dataframe/rendering.rst.txt index 11e3d7e72..4c37c7471 100644 --- a/_sources/user-guide/dataframe.rst.txt +++ b/_sources/user-guide/dataframe/rendering.rst.txt @@ -15,59 +15,37 @@ .. specific language governing permissions and limitations .. under the License. -DataFrames -========== +HTML Rendering in Jupyter +========================= -Overview --------- +When working in Jupyter notebooks or other environments that support rich HTML display, +DataFusion DataFrames automatically render as nicely formatted HTML tables. This functionality +is provided by the ``_repr_html_`` method, which is automatically called by Jupyter to provide +a richer visualization than plain text output. -DataFusion's DataFrame API provides a powerful interface for building and executing queries against data sources. -It offers a familiar API similar to pandas and other DataFrame libraries, but with the performance benefits of Rust -and Arrow. +Basic HTML Rendering +-------------------- -A DataFrame represents a logical plan that can be composed through operations like filtering, projection, and aggregation. -The actual execution happens when terminal operations like ``collect()`` or ``show()`` are called. - -Basic Usage ------------ +In a Jupyter environment, simply displaying a DataFrame object will trigger HTML rendering: .. code-block:: python - import datafusion - from datafusion import col, lit - - # Create a context and register a data source - ctx = datafusion.SessionContext() - ctx.register_csv("my_table", "path/to/data.csv") - - # Create and manipulate a DataFrame - df = ctx.sql("SELECT * FROM my_table") - - # Or use the DataFrame API directly - df = (ctx.table("my_table") - .filter(col("age") > lit(25)) - .select([col("name"), col("age")])) - - # Execute and collect results - result = df.collect() - - # Display the first few rows - df.show() + # Will display as HTML table in Jupyter + df -HTML Rendering --------------- + # Explicit display also uses HTML rendering + display(df) -When working in Jupyter notebooks or other environments that support HTML rendering, DataFrames will -automatically display as formatted HTML tables, making it easier to visualize your data. +Customizing HTML Rendering +--------------------------- -The ``_repr_html_`` method is called automatically by Jupyter to render a DataFrame. This method -controls how DataFrames appear in notebook environments, providing a richer visualization than -plain text output. +DataFusion provides extensive customization options for HTML table rendering through the +``datafusion.html_formatter`` module. -Customizing HTML Rendering --------------------------- +Configuring the HTML Formatter +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -You can customize how DataFrames are rendered in HTML by configuring the formatter: +You can customize how DataFrames are rendered by configuring the formatter: .. code-block:: python @@ -91,7 +69,7 @@ You can customize how DataFrames are rendered in HTML by configuring the formatt The formatter settings affect all DataFrames displayed after configuration. Custom Style Providers ----------------------- +----------------------- For advanced styling needs, you can create a custom style provider: @@ -118,11 +96,13 @@ For advanced styling needs, you can create a custom style provider: configure_formatter(style_provider=MyStyleProvider()) Performance Optimization with Shared Styles -------------------------------------------- +-------------------------------------------- + The ``use_shared_styles`` parameter (enabled by default) optimizes performance when displaying multiple DataFrames in notebook environments: - .. code-block:: python +.. code-block:: python + from datafusion.html_formatter import StyleProvider, configure_formatter # Default: Use shared styles (recommended for notebooks) configure_formatter(use_shared_styles=True) @@ -137,7 +117,7 @@ When ``use_shared_styles=True``: - Applies consistent styling across all DataFrames Creating a Custom Formatter ---------------------------- +---------------------------- For complete control over rendering, you can implement a custom formatter: @@ -183,7 +163,7 @@ Get the current formatter settings: print(formatter.theme) Contextual Formatting ---------------------- +---------------------- You can also use a context manager to temporarily change formatting settings: @@ -206,12 +186,38 @@ Memory and Display Controls You can control how much data is displayed and how much memory is used for rendering: - .. code-block:: python - +.. code-block:: python + configure_formatter( max_memory_bytes=4 * 1024 * 1024, # 4MB maximum memory for display min_rows_display=50, # Always show at least 50 rows repr_rows=20 # Show 20 rows in __repr__ output ) -These parameters help balance comprehensive data display against performance considerations. \ No newline at end of file +These parameters help balance comprehensive data display against performance considerations. + +Best Practices +-------------- + +1. **Global Configuration**: Use ``configure_formatter()`` at the beginning of your notebook to set up consistent formatting for all DataFrames. + +2. **Memory Management**: Set appropriate ``max_memory_bytes`` limits to prevent performance issues with large datasets. + +3. **Shared Styles**: Keep ``use_shared_styles=True`` (default) for better performance in notebooks with multiple DataFrames. + +4. **Reset When Needed**: Call ``reset_formatter()`` when you want to start fresh with default settings. + +5. **Cell Expansion**: Use ``enable_cell_expansion=True`` when cells might contain longer content that users may want to see in full. + +Additional Resources +-------------------- + +* :doc:`../dataframe/index` - Complete guide to using DataFrames +* :doc:`../io/index` - I/O Guide for reading data from various sources +* :doc:`../data-sources` - Comprehensive data sources guide +* :ref:`io_csv` - CSV file reading +* :ref:`io_parquet` - Parquet file reading +* :ref:`io_json` - JSON file reading +* :ref:`io_avro` - Avro file reading +* :ref:`io_custom_table_provider` - Custom table providers +* `API Reference `_ - Full API reference diff --git a/autoapi/datafusion/catalog/index.html b/autoapi/datafusion/catalog/index.html index 7629a570a..64d0e67c9 100644 --- a/autoapi/datafusion/catalog/index.html +++ b/autoapi/datafusion/catalog/index.html @@ -34,7 +34,7 @@ - + @@ -117,17 +117,29 @@ Data Sources -
  • - +
  • + DataFrames + + +
  • Common Operations - -
    • -
  • - - datafusion.col - -
  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
    • +
  • + + datafusion.dataframe_formatter + +
  • datafusion.expr @@ -314,8 +326,8 @@ datafusion.input - -
    • -
  • - - datafusion.udf - -
  • datafusion.unparser @@ -419,6 +426,15 @@
  • - + + + + CatalogProvider + + + + +
    • +
  • + - Database + Schema +
    • +
  • + + + + SchemaProvider + + + + +
    • +
  • + + + + RecordBatch + + + + +
    • +
  • + + + + RecordBatchStream + + + + +
    • +
  • + + + + RuntimeEnvBuilder + + + + +
    • +
  • + + + + SQLOptions + + + + +
    • +
  • + + + + ScalarUDF + + + + +
    • +
  • + + + + SessionConfig + + + + +
    • +
  • + + + + Table + + + + +
    • +
  • + TableFunction @@ -2372,6 +2984,15 @@
    • +
  • + + + + ScalarUDFExportable + + + + +
  • @@ -759,6 +842,15 @@
    • +
  • + + + + WindowUDF.__repr__() + + + +
  • @@ -795,6 +887,15 @@
    • +
  • + + + + WindowUDF.from_pycapsule() + + + +
  • @@ -815,6 +916,26 @@
    • +
  • + + + + WindowUDFExportable + + + + +
  • @@ -918,9 +1039,15 @@

    Classes

    AggregateUDF

    Class for performing scalar user-defined functions (UDF).

    -

    ScalarUDF

    +

    AggregateUDFExportable

    +

    Type hint for object that has __datafusion_aggregate_udf__ PyCapsule.

    + +

    ScalarUDF

    Class for performing scalar user-defined functions (UDF).

    +

    ScalarUDFExportable

    +

    Type hint for object that has __datafusion_scalar_udf__ PyCapsule.

    +

    TableFunction

    Class for performing user-defined table functions (UDTF).

    @@ -933,6 +1060,9 @@

    Classes

    WindowUDF

    Class for performing window user-defined functions (UDF).

    +

    WindowUDFExportable

    +

    Type hint for object that has __datafusion_window_udf__ PyCapsule.

    + @@ -985,6 +1115,20 @@

    Module Contents +
    +__repr__() → str
    +

    Print a string representation of the Aggregate UDF.

    +
    + +
    +
    +static from_pycapsule(func: AggregateUDFExportable) → AggregateUDF
    +

    Create an Aggregate UDF from AggregateUDF PyCapsule object.

    +

    This function will instantiate a Aggregate UDF that uses a DataFusion +AggregateUDF that is exported via the FFI bindings.

    +
    +
    static udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, AggregateUDF]
    @@ -1047,7 +1191,11 @@

    Module ContentsParameters:

    +
    class datafusion.user_defined.ScalarUDF(name: str, func: Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)
    @@ -1085,11 +1245,27 @@

    Module Contents +
    +__repr__() → str
    +

    Print a string representation of the Scalar UDF.

    +

    + +
    +
    +static from_pycapsule(func: ScalarUDFExportable) → ScalarUDF
    +

    Create a Scalar UDF from ScalarUDF PyCapsule object.

    +

    This function will instantiate a Scalar UDF that uses a DataFusion +ScalarUDF that is exported via the FFI bindings.

    +
    +
    static udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, ScalarUDF]
    static udf(func: Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → ScalarUDF
    +
    +static udf(func: ScalarUDFExportable) → ScalarUDF

    Create a new User-Defined Function (UDF).

    This class can be used both as either a function or a decorator.

    @@ -1104,7 +1280,10 @@

    Module ContentsParameters:

    +
    class datafusion.user_defined.TableFunction(name: str, func: Callable[[], any])
    @@ -1430,6 +1621,12 @@

    Module Contents +
    +__repr__() → str
    +

    Print a string representation of the Window UDF.

    +

    +
    static _create_window_udf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
    @@ -1454,6 +1651,14 @@

    Module Contents +
    +static from_pycapsule(func: WindowUDFExportable) → WindowUDF
    +

    Create a Window UDF from WindowUDF PyCapsule object.

    +

    This function will instantiate a Window UDF that uses a DataFusion +WindowUDF that is exported via the FFI bindings.

    +

    +
    static udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, WindowUDF]
    @@ -1498,7 +1703,10 @@

    Module ContentsParameters:

    +
    datafusion.user_defined._R
    diff --git a/autoapi/index.html b/autoapi/index.html index b8d920eaf..b79037d04 100644 --- a/autoapi/index.html +++ b/autoapi/index.html @@ -117,17 +117,29 @@ Data Sources

    • -
  • - +
  • + DataFrames + + +
  • Common Operations - -
    • -
  • - - datafusion.col - -
  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
    • +
  • + + datafusion.dataframe_formatter + +
  • datafusion.expr @@ -314,8 +326,8 @@ datafusion.input - -
    • -
  • - - datafusion.udf - -
  • datafusion.unparser @@ -423,9 +430,9 @@

    API Referencedatafusion diff --git a/contributor-guide/ffi.html b/contributor-guide/ffi.html index 2607e7220..518ae0ef7 100644 --- a/contributor-guide/ffi.html +++ b/contributor-guide/ffi.html @@ -117,17 +117,29 @@ Data Sources

    • -
  • - +
  • + DataFrames + + +
  • Common Operations - -
    • -
  • - - datafusion.col - -
  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
    • +
  • + + datafusion.dataframe_formatter + +
  • datafusion.expr @@ -314,8 +326,8 @@ datafusion.input - -
    • -
  • - - datafusion.udf - -
  • datafusion.unparser @@ -585,7 +592,7 @@

    Implementation DetailsTableProvider PyCapsule to have this capsule accessible by calling a function named __datafusion_table_provider__. You can see a complete working example of how to share a TableProvider from one python library to DataFusion Python in the -repository examples folder.

    +repository examples folder.

    This section has been written using TableProvider as an example. It is the first extension that has been written using this approach and the most thoroughly implemented. As we continue to expose more of the DataFusion features, we intend to follow this same diff --git a/contributor-guide/introduction.html b/contributor-guide/introduction.html index a8c329ba2..5df6002ce 100644 --- a/contributor-guide/introduction.html +++ b/contributor-guide/introduction.html @@ -117,17 +117,29 @@ Data Sources

    • -
  • - +
  • + DataFrames + + +
  • Common Operations - -
    • -
  • - - datafusion.col - -
  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
    • +
  • + + datafusion.dataframe_formatter + +
  • datafusion.expr @@ -314,8 +326,8 @@ datafusion.input - -
    • -
  • - - datafusion.udf - -
  • datafusion.unparser diff --git a/genindex.html b/genindex.html index 3044426d6..145252ef5 100644 --- a/genindex.html +++ b/genindex.html @@ -114,17 +114,29 @@ Data Sources
    • -
  • - +
  • + DataFrames + + +
  • Common Operations - -
    • -
  • - - datafusion.col - -
  • datafusion.context @@ -292,6 +299,11 @@ datafusion.dataframe
    • +
  • + + datafusion.dataframe_formatter + +
  • datafusion.expr @@ -311,8 +323,8 @@ datafusion.input - -
    • -
  • - - datafusion.udf - -
  • datafusion.unparser @@ -467,7 +474,7 @@

    _

  • __call__() (datafusion.AggregateUDF method)
    • +
  • __datafusion_aggregate_udf__() (datafusion.user_defined.AggregateUDFExportable method) +
    • +
  • __datafusion_catalog_provider__() (datafusion.context.CatalogProviderExportable method) +
    • +
  • __datafusion_scalar_udf__() (datafusion.user_defined.ScalarUDFExportable method) +
  • __datafusion_table_provider__() (datafusion.context.TableProviderExportable method) +
    • +
  • __datafusion_window_udf__() (datafusion.user_defined.WindowUDFExportable method)
  • __eq__() (datafusion.Expr method) @@ -578,9 +593,21 @@

    _

  • (datafusion.expr.Expr attribute)
    • -
  • __repr__() (datafusion.dataframe.DataFrame method) +
  • __repr__() (datafusion.AggregateUDF method)
    • + + - -
  • _custom_cell_builder (datafusion.html_formatter.DataFrameHtmlFormatter attribute) +
  • _custom_cell_builder (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
    • -
  • _custom_header_builder (datafusion.html_formatter.DataFrameHtmlFormatter attribute) +
  • _custom_header_builder (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
    • -
  • _default_formatter (datafusion.html_formatter.FormatterManager attribute) +
  • _default_formatter (datafusion.dataframe_formatter.FormatterManager attribute)
    • -
  • _format_cell_value() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
  • _format_cell_value() (datafusion.dataframe_formatter.DataFrameHtmlFormatter method)
    • -
  • _get_cell_value() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
  • _get_cell_value() (datafusion.dataframe_formatter.DataFrameHtmlFormatter method)
    • -
  • _get_default_css() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
  • _get_default_css() (datafusion.dataframe_formatter.DataFrameHtmlFormatter method)
  • _get_default_name() (datafusion.user_defined.WindowUDF static method) @@ -708,7 +753,7 @@

    _

  • (datafusion.WindowUDF static method)
    • -
  • _get_javascript() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
  • _get_javascript() (datafusion.dataframe_formatter.DataFrameHtmlFormatter method)
  • _normalize_input_types() (datafusion.user_defined.WindowUDF static method) @@ -734,11 +779,11 @@

    _

  • (datafusion.plan.LogicalPlan attribute)
    • -
  • _refresh_formatter_reference() (in module datafusion.html_formatter) +
  • _raw_schema (datafusion.catalog.Schema attribute)
    • -
  • _repr_html_() (datafusion.dataframe.DataFrame method) +
  • _refresh_formatter_reference() (in module datafusion.dataframe_formatter)
    • -
  • _styles_loaded (datafusion.html_formatter.DataFrameHtmlFormatter attribute) +
  • _repr_html_() (datafusion.dataframe.DataFrame method)
  • _to_pyarrow_types (datafusion.Expr attribute) @@ -746,7 +791,7 @@

    _

  • (datafusion.expr.Expr attribute)
    • -
  • _type_formatters (datafusion.html_formatter.DataFrameHtmlFormatter attribute) +
  • _type_formatters (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
  • _udaf (datafusion.AggregateUDF attribute) @@ -772,9 +817,9 @@

    _

  • (datafusion.WindowUDF attribute)
    • -
  • _validate_bool() (in module datafusion.html_formatter) +
  • _validate_bool() (in module datafusion.dataframe_formatter)
    • -
  • _validate_positive_int() (in module datafusion.html_formatter) +
  • _validate_positive_int() (in module datafusion.dataframe_formatter)
  • _window_frame (datafusion.expr.Window attribute)
    • @@ -826,6 +871,8 @@

    A

  • (class in datafusion.user_defined)
    • +
  • AggregateUDFExportable (class in datafusion.user_defined) +
  • Alias (in module datafusion.expr)
  • alias() (datafusion.Expr method) @@ -834,6 +881,12 @@

    A

  • (datafusion.expr.Expr method)
  • (in module datafusion.functions) +
    • + +
  • allow_single_file_parallelism (datafusion.dataframe.ParquetWriterOptions attribute), [1] + +
  • AmazonS3 (in module datafusion.object_store) @@ -900,6 +953,8 @@

    A

  • array_join() (in module datafusion.functions)
    • + + -
  • catalog() (datafusion.context.SessionContext method) +
    • +
  • catalog_names() (datafusion.context.SessionContext method) +
    • +
  • CatalogProvider (class in datafusion.catalog) +
    • +
  • CatalogProviderExportable (class in datafusion.context)
  • cbrt() (datafusion.Expr method) @@ -1154,7 +1245,7 @@

    C

  • (in module datafusion.functions)
    • -
  • CellFormatter (class in datafusion.html_formatter) +
  • CellFormatter (class in datafusion.dataframe_formatter)
  • char_length() (datafusion.Expr method) @@ -1189,11 +1280,7 @@

    C

  • coalesce() (in module datafusion.functions)
  • col (in module datafusion) - -
  • col() (in module datafusion.functions)
  • collect() (datafusion.dataframe.DataFrame method) @@ -1201,29 +1288,47 @@

    C

  • collect_partitioned() (datafusion.dataframe.DataFrame method)
  • column (in module datafusion) - -
  • Column (in module datafusion.expr)
    • - - + @@ -1324,12 +1435,20 @@

    C

    D

    - + + - - + @@ -1911,14 +2081,14 @@

    I

  • is_following() (datafusion.expr.WindowFrameBound method)
    • + + - - + + - @@ -2295,9 +2493,7 @@

    N

  • nanvl() (in module datafusion.functions) @@ -2375,6 +2571,8 @@

    O

  • overlay() (in module datafusion.functions) +
    • +
  • owner_name() (datafusion.catalog.SchemaProvider method)
  • - datafusion.col + datafusion.context
  • - datafusion.context + datafusion.dataframe
  • - datafusion.dataframe + datafusion.dataframe_formatter
  • @@ -1450,13 +1569,6 @@

    D

    • -
  • - datafusion.udf - -
  • @@ -1479,25 +1591,21 @@

    D

  • date_trunc() (in module datafusion.functions)
    • -
  • dense_rank() (in module datafusion.functions)
    • -
  • deregister_table() (datafusion.context.SessionContext method) +
  • deregister_schema() (datafusion.Catalog method) + +
    • +
  • deregister_table() (datafusion.catalog.Schema method) + +
  • describe() (datafusion.dataframe.DataFrame method)
  • DescribeTable (in module datafusion.expr) @@ -1527,6 +1649,22 @@

    D

  • dialect (datafusion.unparser.Dialect attribute)
    • +
  • dictionary_enabled (datafusion.dataframe.ParquetColumnOptions attribute), [1] + +
    • +
  • dictionary_page_size_limit (datafusion.dataframe.ParquetWriterOptions attribute), [1] + +
  • digest() (in module datafusion.functions)
  • display() (datafusion.ExecutionPlan method) @@ -1609,7 +1747,7 @@

    E

  • EmptyRelation (in module datafusion.expr)
    • -
  • enable_cell_expansion (datafusion.html_formatter.DataFrameHtmlFormatter attribute) +
  • enable_cell_expansion (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
  • enable_url_table() (datafusion.context.SessionContext method)
    • @@ -1617,6 +1755,16 @@

    E

    +
  • encoding (datafusion.dataframe.ParquetColumnOptions attribute), [1] + +
  • end() (datafusion.expr.CaseBuilder method) @@ -1635,12 +1783,12 @@

    E

  • evaluate_all_with_rank() (datafusion.user_defined.WindowEvaluator method)
    • +     		- +
  • from_pycapsule() (datafusion.AggregateUDF static method) + +
  • from_pydict() (datafusion.context.SessionContext method) @@ -1797,18 +1967,18 @@

    G

    		•  -
  • get_header_style() (datafusion.html_formatter.DefaultStyleProvider method) +
  • get_header_style() (datafusion.dataframe_formatter.DefaultStyleProvider method)
    		• +
  • literal_with_metadata() (datafusion.Expr static method) + +
  • ln() (datafusion.Expr method) @@ -2201,14 +2375,32 @@

    M

  • max() (in module datafusion.functions)
    • -
  • max_cell_length (datafusion.html_formatter.DataFrameHtmlFormatter attribute) +
  • max_cell_length (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute) +
    • +
  • max_height (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute) +
    • +
  • max_memory_bytes (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute) +
    • +
  • max_row_group_size (datafusion.dataframe.ParquetWriterOptions attribute), [1] + +
    • +
  • max_width (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
    • -
  • max_memory_bytes (datafusion.html_formatter.DataFrameHtmlFormatter attribute) +
  • maximum_buffered_record_batches_per_stream (datafusion.dataframe.ParquetWriterOptions attribute), [1] + +
    • +
  • maximum_parallel_row_group_writers (datafusion.dataframe.ParquetWriterOptions attribute), [1] + +
  • md5() (datafusion.Expr method)
    • +     		-
    @@ -2382,6 +2580,18 @@

    O

    P

    + - - +
    +
  • ScalarUDFExportable (class in datafusion.user_defined) +
  • ScalarVariable (in module datafusion.expr) +
    • +
  • Schema (class in datafusion.catalog)
  • schema (datafusion.catalog.Table property) @@ -2658,14 +2886,32 @@

    S

  • (datafusion.Table property)
    • -
  • schema() (datafusion.dataframe.DataFrame method) +
  • schema() (datafusion.Catalog method) + +
  • schema_name() (datafusion.Expr method)
    • +
  • schema_names() (datafusion.Catalog method) + +
    • +
  • SchemaProvider (class in datafusion.catalog) +
  • select() (datafusion.dataframe.DataFrame method)
  • select_columns() (datafusion.dataframe.DataFrame method) @@ -2694,14 +2940,14 @@

    S

  • (datafusion.SessionConfig method)
    • -
  • set_custom_cell_builder() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
  • set_custom_cell_builder() (datafusion.dataframe_formatter.DataFrameHtmlFormatter method)
    • -
  • set_custom_header_builder() (datafusion.html_formatter.DataFrameHtmlFormatter method) +
  • set_custom_header_builder() (datafusion.dataframe_formatter.DataFrameHtmlFormatter method)
    • -
  • set_formatter() (datafusion.html_formatter.FormatterManager class method) +
  • set_formatter() (datafusion.dataframe_formatter.FormatterManager class method)
  • SetVariable (in module datafusion.expr) @@ -2740,7 +2986,7 @@

    S

  • show() (datafusion.dataframe.DataFrame method)
    • -
  • show_truncation_message (datafusion.html_formatter.DataFrameHtmlFormatter attribute) +
  • show_truncation_message (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
  • signum() (datafusion.Expr method) @@ -2768,6 +3014,12 @@

    S

  • (datafusion.expr.Expr method)
  • (in module datafusion.functions) +
    • + +
  • skip_arrow_metadata (datafusion.dataframe.ParquetWriterOptions attribute), [1] + +
  • SNAPPY (datafusion.dataframe.Compression attribute) @@ -2814,6 +3066,22 @@

    S

    • +
  • statistics_enabled (datafusion.dataframe.ParquetColumnOptions attribute), [1] + +
    • +
  • statistics_truncate_length (datafusion.dataframe.ParquetWriterOptions attribute), [1] + +
  • stddev() (in module datafusion.functions) @@ -2834,9 +3102,9 @@

    S

  • struct() (in module datafusion.functions)
    • -
  • style_provider (datafusion.html_formatter.DataFrameHtmlFormatter attribute) +
  • style_provider (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
    • -
  • StyleProvider (class in datafusion.html_formatter) +
  • StyleProvider (class in datafusion.dataframe_formatter)
  • Subquery (in module datafusion.expr)
    • @@ -2870,16 +3138,26 @@

    T

  • (datafusion.Table attribute)
    • -
  • table() (datafusion.catalog.Database method) +
  • table() (datafusion.catalog.Schema method)
    • +
  • table_exist() (datafusion.catalog.SchemaProvider method) + +
    • -
  • table_exist() (datafusion.context.SessionContext method) +
  • table_names() (datafusion.catalog.Schema method) + +
  • TableFunction (class in datafusion)
    • -
  • use_shared_styles (datafusion.html_formatter.DataFrameHtmlFormatter attribute) +
  • use_shared_styles (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
  • uses_window_frame() (datafusion.user_defined.WindowEvaluator method)
    • @@ -3168,6 +3446,8 @@

    W

  • (class in datafusion.user_defined)
    • +
  • WindowUDFExportable (class in datafusion.user_defined) +
  • with_allow_ddl() (datafusion.context.SQLOptions method)
    • -
    diff --git a/index.html b/index.html index e143b33fc..cf0938eb3 100644 --- a/index.html +++ b/index.html @@ -116,17 +116,29 @@ Data Sources -
  • - +
  • + DataFrames + + +
  • Common Operations - -
    • -
  • - - datafusion.col - -
  • datafusion.context @@ -294,6 +301,11 @@ datafusion.dataframe
    • +
  • + + datafusion.dataframe_formatter + +
  • datafusion.expr @@ -313,8 +325,8 @@ datafusion.input - -
    • -
  • - - datafusion.udf - -
  • datafusion.unparser diff --git a/objects.inv b/objects.inv index da03cabba9cb48d4da33f9ea456f318ceee93134..e1fa1a7374b9965764d9053e9351ef3d5796b99d 100644 GIT binary patch delta 8674 zcmV<8Asyb9J)K05g@4VRTX)+ww#VQ7DZJL4S8Ea{>2&5T7pLQ%H1WhqyUx6DK_n!h zApr&eWhtNj;6hTAEQ%npx7?T35y9UdBre&1PA{Kbl1d9w zvcG5T<-aqY(amh7i~Mgs+13ACUR~@G%wDHyRa80ALRwau6Mv;HpAVq=88f;jc||mJ z8KZh7vKU%H2QsEWscKPN0FiG0j=@9*3E*q=w=->FiQ zTFlLcrj<5--Q|SCPykxr0Z)>Lq^$EdxfSj+(-q4zNjX#=Gp0-qx4^i>rso=p>U(@C zw16U(L~3ULm87Eb88!TpO1+H(YZ0H(QbtthQkr^9vVSbD8hZ+dpwRCCkR=6ym@=mY z1W5xx7+;(E1^~(-UQP~?6Entupj0^kg+sg*Apsz=ZH^HifttjjNYP(9k74O5ElLPd zTX&)#t*t-Nq^9_zL8_Vqk+iI6#?~;jHd|3ex0j_DlKpsYiIn0Y(c9A7r*V%+<|;B% zBoz>dRevlaXCyiwQX11NV+9mQX~t6x0;5H#w;-gP@}*vZpg7pODn*&hN%{>8W=vuZ z@aF55CKjpDuUG$o807Psy=2SmW8k>_j(=ZKUZhGM&l93WFI7>pr1O6M{fL0KM)SP=Xo#Y+BnV1;l_%C&C-!qCNyZ3| z?I|QR??*-Fg>Jkjj9tnjJX4@N9c?C9o`0QhiNydk*p44SENMlquU`T{Ui}mgdGRwq zPF_8a?Uof=@+!KBqUXZ^ro)top4w2~;}NFD^JM~KPsC5~0nG1dk*w$@9Jp<}ihqv4 zlBFc&YR!JYQe)ke`kB#we_b?$|5KO8cv)!$!-{u!I-o^&Xm><@uc&_OW_v%C)?ikX z8{RS4Y@Q2KAbtufp`6TfnvH8dEPFOqXHk}8HLk~M@N7L+<3)f*DvDB4)ofT8gMS%- z&sb{zAaXmkFkS_yP@am+7$IZXKYs&!5R7dM{~W6^p)ovvHde$8!XNC_(Mrz)lR3I-0SF``}+9^`Q{7Jd1Tl5 z$chc?A-4J zklCjG8f-Q~7X@5$F`ONxcgfMMBe} zY(|(dtGPY+iqDPxof)GDTunY`yqUmfjsRVvH(ZA@D0{6 zAfhGSrz9sbCg?&-0Dp+M&}GF==yzCE78hz^hk}Z;up`!an~3pa{kQG|Gra`66wt5L zK3P!>^r*fS?AzgBSU=B^WOPBQTsKh^+|J+F1&kwVXOdxjA!I?ErwjtV^aGisG=s2u zUI2`3I)c{8ht%;&nr{h;i2JSCjnB}j@uyD~F#hxjXRoc-*=rj^?q*X8sY9B}V~r7T>-XjSFVn<_t{ZMf zdUa&)4wCqR+xoExd4s+3x;~eOs6t!mH4g9Hb{|uf>nk-;`cZbUO>9y`D zM>*QtnuRWcM)Ct^3n#18-!+>sB;XI2P~xTna~}nz4aI{atv5&pj{E26nf$3jF2FOk z2KSzSGRGEj2Z-VEUG)mua0(!S{I0yGkbg1yh(gv7Ig!{JTN}y%TO$uy#+j%oNEPo>U zEGiFYP+2pIXWlCR&xB=o65n%7wm&Q{q)=2=YN~~`?|LMjLqWVN+l-TjV)SvGKbl znqgO`=~5L(dyb|rGR@glS3Dh+nm!w?Dg{MNnhXy-;B7KriV}-WHz_T(b${}~Q*i4a zodC4>D(7f-UeVh3A!~ZmRScb>;e*fnj1UMo2y`laMG0E@I+rnp_>C|EB4}b`s(^J! z!DJ@_4d2H5MuCr5i=V1t=VA)>gJ#J&)H<#@XOKwd+hj$C54fHx73P6AnNBecKTl8m zej|mZvJz;$M#zb9Q`wp@w0|#+=}bqsC`71)`6t8(1UVI882IVCo5TN0lF)H8(~(?4Ye4-RIMF!w%o-(Y+p}JAdvVsUFD}qa-Jt zl+>gAa+LCj(~NrbUX9Y5bT&?p@=pWGV@|u9)J9=X!0UO+e~iimTx0!tx^7fs{pWPu z5r^mX^-#}7sYf2D*O!UsQ!+8(ki9yi4={pGlZHtI0GzGr+fN;2kvzP=p1oR))8 z$J_O3zZ$0v_<4H%(|=Uy@rV2MWno;G8vluWKCUmFbO>Od^gqW+!yOFRXN^6Zl%=S{ z0{gNuuBV-LfMB2YxLy|0aJqgmRT}IYcRjB6n{fDGpYW^k!eb63?33;5_Vy!01-a(! zZW-aEx4UWfmgf2Uu4;%~d|Y&_T5yc;c-?kt;NRwk^F8iy*?*boQCXfPbmJz2t$Sxm zM=YWuWykpvErb}e;)rhudVT-m$QGe``si&;3O@mfXnu|K(fUB&|a2RWXLT9LM#g_79)uhhD7^iyZEZFh6 zE0pnrAdIZ6C|j=dQ|F?N?Kj_Qs-8M84=j7)Vqx4)Qz*M?U*=@{lzC~lMD7nXpQ7Qo z{R^@V3-wg*L)q{Daf9tiUP>oFj}5k`$MfsT?>wkJuP^HL{K53!p?ZK|@r^-pC zXrflc&W*ZEovAK+L-F1!2A;owBRXr%XZQ4HsH1(Es2j_fve8z6-+V-3^p}4qIBN$B zd;K_i&3lv&ck<%-J|&Oz)p_;L+vJ|Mtvz)kOC()Ls#d$7>@QSOp3>p-69DwrBxjjj z-k8@Rs(;U?SPI27TibIP^*NL$9Z?Z4`>6N87Buzg+>)q*bW;wl6xlSxOG7r*>~(j; 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    • -
  • - +
  • + DataFrames + + +
  • Common Operations - -
    • -
  • - - datafusion.col - -
  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
    • +
  • + + datafusion.dataframe_formatter + +
  • datafusion.expr @@ -314,8 +326,8 @@ datafusion.input - -
    • -
  • - - datafusion.udf - -
  • datafusion.unparser @@ -427,17 +434,17 @@

    Python Module Index

        -     datafusion.col + datafusion.context     - datafusion.context + datafusion.dataframe     - datafusion.dataframe + datafusion.dataframe_formatter @@ -494,11 +501,6 @@

    Python Module Index

        datafusion.substrait - - -     - datafusion.udf -     diff --git a/search.html b/search.html index 6602d8b2f..5339967e5 100644 --- a/search.html +++ b/search.html @@ -121,17 +121,29 @@ Data Sources
    • -
  • - +
  • + DataFrames + + +
  • Common Operations - -
    • -
  • - - datafusion.col - -
  • datafusion.context @@ -299,6 +306,11 @@ datafusion.dataframe
    • +
  • + + datafusion.dataframe_formatter + +
  • datafusion.expr @@ -318,8 +330,8 @@ datafusion.input - -
    • -
  • - - datafusion.udf - -
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false]], "cbrt() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.cbrt", false]], "cbrt() (in module datafusion.functions)": [[5, "datafusion.functions.cbrt", false]], "ceil() (datafusion.expr method)": [[7, "datafusion.Expr.ceil", false]], "ceil() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.ceil", false]], "ceil() (in module datafusion.functions)": [[5, "datafusion.functions.ceil", false]], "cellformatter (class in datafusion.html_formatter)": [[6, "datafusion.html_formatter.CellFormatter", false]], "char_length() (datafusion.expr method)": [[7, "datafusion.Expr.char_length", false]], "char_length() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.char_length", false]], "char_length() (in module datafusion.functions)": [[5, "datafusion.functions.char_length", false]], "character_length() (datafusion.expr method)": [[7, "datafusion.Expr.character_length", false]], "character_length() (datafusion.expr.expr method)": [[4, 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"locationinputplugin (class in datafusion.input.location)": [[10, "datafusion.input.location.LocationInputPlugin", false]], "log() (in module datafusion.functions)": [[5, "datafusion.functions.log", false]], "log10() (datafusion.expr method)": [[7, "datafusion.Expr.log10", false]], "log10() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.log10", false]], "log10() (in module datafusion.functions)": [[5, "datafusion.functions.log10", false]], "log2() (datafusion.expr method)": [[7, "datafusion.Expr.log2", false]], "log2() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.log2", false]], "log2() (in module datafusion.functions)": [[5, "datafusion.functions.log2", false]], "logical_plan() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.logical_plan", false]], "logicalplan (class in datafusion)": [[7, "datafusion.LogicalPlan", false]], "logicalplan (class in datafusion.plan)": [[13, "datafusion.plan.LogicalPlan", false]], "lower() (datafusion.expr method)": [[7, "datafusion.Expr.lower", false]], "lower() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.lower", false]], "lower() (in module datafusion.functions)": [[5, "datafusion.functions.lower", false]], "lpad() (in module datafusion.functions)": [[5, "datafusion.functions.lpad", false]], "ltrim() (datafusion.expr method)": [[7, "datafusion.Expr.ltrim", false]], "ltrim() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.ltrim", false]], "ltrim() (in module datafusion.functions)": [[5, "datafusion.functions.ltrim", false]], "lz4 (datafusion.dataframe.compression attribute)": [[2, "datafusion.dataframe.Compression.LZ4", false]], "lz4_raw (datafusion.dataframe.compression attribute)": [[2, "datafusion.dataframe.Compression.LZ4_RAW", false]], "make_array() (in module datafusion.functions)": [[5, "datafusion.functions.make_array", false]], "make_date() (in module datafusion.functions)": [[5, "datafusion.functions.make_date", false]], "make_list() (in module datafusion.functions)": [[5, "datafusion.functions.make_list", false]], "max() (in module datafusion.functions)": [[5, "datafusion.functions.max", false]], "max_cell_length (datafusion.dataframe_formatter.dataframehtmlformatter attribute)": [[3, "datafusion.dataframe_formatter.DataFrameHtmlFormatter.max_cell_length", false]], "max_height (datafusion.dataframe_formatter.dataframehtmlformatter attribute)": [[3, "datafusion.dataframe_formatter.DataFrameHtmlFormatter.max_height", false]], "max_memory_bytes (datafusion.dataframe_formatter.dataframehtmlformatter attribute)": [[3, "datafusion.dataframe_formatter.DataFrameHtmlFormatter.max_memory_bytes", false]], "max_row_group_size (datafusion.dataframe.parquetwriteroptions attribute)": [[2, "datafusion.dataframe.ParquetWriterOptions.max_row_group_size", false], [2, "id19", false]], "max_row_group_size (datafusion.parquetwriteroptions attribute)": [[7, "datafusion.ParquetWriterOptions.max_row_group_size", false], [7, "id20", false]], "max_width (datafusion.dataframe_formatter.dataframehtmlformatter attribute)": [[3, "datafusion.dataframe_formatter.DataFrameHtmlFormatter.max_width", false]], "maximum_buffered_record_batches_per_stream (datafusion.dataframe.parquetwriteroptions attribute)": [[2, "datafusion.dataframe.ParquetWriterOptions.maximum_buffered_record_batches_per_stream", false], [2, "id20", false]], "maximum_buffered_record_batches_per_stream (datafusion.parquetwriteroptions attribute)": [[7, "datafusion.ParquetWriterOptions.maximum_buffered_record_batches_per_stream", false], [7, "id21", false]], "maximum_parallel_row_group_writers (datafusion.dataframe.parquetwriteroptions attribute)": [[2, "datafusion.dataframe.ParquetWriterOptions.maximum_parallel_row_group_writers", false], [2, "id21", false]], "maximum_parallel_row_group_writers (datafusion.parquetwriteroptions attribute)": [[7, "datafusion.ParquetWriterOptions.maximum_parallel_row_group_writers", false], [7, "id22", false]], "md5() (datafusion.expr method)": [[7, "datafusion.Expr.md5", false]], "md5() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.md5", false]], "md5() (in module datafusion.functions)": [[5, "datafusion.functions.md5", false]], "mean() (in module datafusion.functions)": [[5, "datafusion.functions.mean", false]], "median() (in module datafusion.functions)": [[5, "datafusion.functions.median", false]], "memoize() (datafusion.user_defined.windowevaluator method)": [[17, "datafusion.user_defined.WindowEvaluator.memoize", false]], "memory_catalog() (datafusion.catalog static method)": [[7, "datafusion.Catalog.memory_catalog", false]], "memory_catalog() (datafusion.catalog.catalog static method)": [[0, "datafusion.catalog.Catalog.memory_catalog", false]], "memory_schema() (datafusion.catalog.schema static method)": [[0, "datafusion.catalog.Schema.memory_schema", false]], "merge() (datafusion.accumulator method)": [[7, "datafusion.Accumulator.merge", false]], "merge() (datafusion.user_defined.accumulator method)": [[17, "datafusion.user_defined.Accumulator.merge", false]], "microsoftazure (in module datafusion.object_store)": [[12, "datafusion.object_store.MicrosoftAzure", false]], "min() (in module datafusion.functions)": [[5, "datafusion.functions.min", false]], "min_rows_display (datafusion.dataframe_formatter.dataframehtmlformatter attribute)": [[3, "datafusion.dataframe_formatter.DataFrameHtmlFormatter.min_rows_display", false]], "module": [[0, "module-datafusion.catalog", false], [1, "module-datafusion.context", false], [2, "module-datafusion.dataframe", false], [3, "module-datafusion.dataframe_formatter", false], [4, "module-datafusion.expr", false], [5, "module-datafusion.functions", false], [6, "module-datafusion.html_formatter", false], [7, "module-datafusion", false], [8, "module-datafusion.input.base", false], [9, "module-datafusion.input", false], [10, "module-datafusion.input.location", false], [11, "module-datafusion.io", false], [12, "module-datafusion.object_store", false], [13, "module-datafusion.plan", false], [14, "module-datafusion.record_batch", false], [15, "module-datafusion.substrait", false], [16, "module-datafusion.unparser", false], [17, "module-datafusion.user_defined", false]], "mysql() (datafusion.unparser.dialect static method)": [[16, "datafusion.unparser.Dialect.mysql", false]], "named_struct() (in module datafusion.functions)": [[5, "datafusion.functions.named_struct", false]], "names() (datafusion.catalog method)": [[7, "datafusion.Catalog.names", false]], "names() (datafusion.catalog.catalog method)": [[0, "datafusion.catalog.Catalog.names", false]], "names() (datafusion.catalog.schema method)": [[0, "datafusion.catalog.Schema.names", false]], "nanvl() (in module datafusion.functions)": [[5, "datafusion.functions.nanvl", false]], "negative (in module datafusion.expr)": [[4, "datafusion.expr.Negative", false]], "next() (datafusion.record_batch.recordbatchstream method)": [[14, "datafusion.record_batch.RecordBatchStream.next", false]], "next() (datafusion.recordbatchstream method)": [[7, "datafusion.RecordBatchStream.next", false]], "not (in module datafusion.expr)": [[4, "datafusion.expr.Not", false]], "now() (in module datafusion.functions)": [[5, "datafusion.functions.now", false]], "nth_value() (in module datafusion.functions)": [[5, "datafusion.functions.nth_value", false]], "ntile() (in module datafusion.functions)": [[5, "datafusion.functions.ntile", false]], "null_treatment() (datafusion.expr method)": [[7, "datafusion.Expr.null_treatment", false]], "null_treatment() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.null_treatment", false]], "nullif() (in module datafusion.functions)": [[5, "datafusion.functions.nullif", false]], "nulls_first() (datafusion.expr.sortexpr method)": [[4, "datafusion.expr.SortExpr.nulls_first", false]], "nvl() (in module datafusion.functions)": [[5, "datafusion.functions.nvl", false]], "octet_length() 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19, "import": 38, "improv": 20, "inner": 28, "input": [8, 9, 10], "inspir": 19, "instal": [20, 21, 37], "introduct": [20, 37], "io": [11, 41], "issu": 19, "join": 28, "json": 42, "jupyt": 36, "lake": 34, "left": 28, "librari": 34, "liter": 25, "local": 34, "locat": 10, "manag": 36, "mathemat": 26, "memori": [34, 36], "miss": 26, "modul": [0, 1, 2, 3, 4, 5, 8, 10, 11, 12, 13, 14, 15, 16, 17], "null": [23, 32], "object": 34, "object_stor": 12, "oper": [24, 27, 35], "optim": 36, "option": 30, "order": [23, 32], "other": [26, 34], "overview": 35, "packag": [7, 9], "paramet": [23, 32], "parquet": 43, "partit": 32, "perform": 36, "plan": 13, "practic": 36, "pre": 20, "primari": 19, "provid": [34, 36, 44], "python": [19, 20, 21], "record_batch": 14, "refer": 18, "regist": 31, "render": [35, 36], "resourc": 36, "return": [4, 5, 7], "run": 20, "rust": 20, "scalar": 30, "schema": 34, "select": 29, "semi": 28, "separ": 20, "session": 22, "set": [23, 32], "share": 36, "sourc": 34, "speed": 20, "sql": 45, "statu": 19, "store": 34, "string": 26, "struct": 25, "style": 36, "submodul": [7, 9], "substrait": 15, "tabl": [30, 34, 44], "tempor": 26, "termin": 35, "treatment": [23, 32], "udwf": 30, "unpars": 16, "updat": 20, "user": [30, 34], "user_defin": 17, "valu": 26, "view": 31, "window": [30, 32], "work": 19}}) \ No newline at end of file diff --git a/user-guide/basics.html b/user-guide/basics.html index 3596aa2c1..c0247bdb3 100644 --- a/user-guide/basics.html +++ b/user-guide/basics.html @@ -117,17 +117,29 @@ Data Sources
    • -
  • - +
  • + DataFrames + + +
  • Common Operations - -
    • -
  • - - datafusion.col - -
  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
    • +
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  • datafusion.expr @@ -314,8 +326,8 @@ datafusion.input - -
    • -
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  • datafusion.unparser @@ -509,7 +516,7 @@

    DataFrameSessionContext, such as read_csv, and can then be modified by calling the transformation methods, such as filter(), select(), aggregate(), and limit() to build up a query definition.

    -

    For more details on working with DataFrames, including visualization options and conversion to other formats, see DataFrames.

    +

    For more details on working with DataFrames, including visualization options and conversion to other formats, see DataFrames.

    Expressions

    diff --git a/user-guide/common-operations/aggregations.html b/user-guide/common-operations/aggregations.html index f35abc6c5..ca33f66bf 100644 --- a/user-guide/common-operations/aggregations.html +++ b/user-guide/common-operations/aggregations.html @@ -117,17 +117,29 @@ Data Sources

    • -
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  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
    • +
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    • -
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  • datafusion.unparser @@ -603,16 +610,16 @@

    Distinct +----------+--------------------------------------------------+ | Type 1 | Type 2 List | +----------+--------------------------------------------------+ -| Bug | [, Grass, Flying, Poison] | -| Poison | [, Ground, Flying] | -| Electric | [Flying, Steel, ] | +| Bug | [Poison, Grass, Flying, ] | +| Poison | [Ground, , Flying] | +| Electric | [, Flying, Steel] | | Fairy | [] | -| Normal | [Flying, Fairy, ] | +| Normal | [Flying, , Fairy] | | Ice | [Flying, Psychic] | -| Grass | [Psychic, , Poison] | -| Fire | [Flying, , Dragon] | -| Water | [Ice, Flying, , Fighting, Dark, Psychic, Poison] | -| Ground | [, Rock] | +| Grass | [Poison, Psychic, ] | +| Fire | [Dragon, Flying, ] | +| Water | [Poison, , Ice, Psychic, Dark, Fighting, Flying] | +| Ground | [Rock, ] | +----------+--------------------------------------------------+ Data truncated. @@ -627,15 +634,15 @@

    Distinct +----------+------------------------------------------------+ | Type 1 | Type 2 List | +----------+------------------------------------------------+ -| Bug | [Poison, Grass, Flying] | -| Poison | [Ground, Flying] | +| Bug | [Grass, Flying, Poison] | +| Poison | [Flying, Ground] | | Electric | [Flying, Steel] | -| Normal | [Flying, Fairy] | -| Ice | [Flying, Psychic] | -| Grass | [Psychic, Poison] | +| Normal | [Fairy, Flying] | +| Ice | [Psychic, Flying] | +| Grass | [Poison, Psychic] | | Fire | [Flying, Dragon] | -| Water | [Dark, Poison, Psychic, Flying, Ice, Fighting] | -| Rock | [Flying, Water, Ground] | +| Water | [Flying, Ice, Psychic, Poison, Fighting, Dark] | +| Rock | [Ground, Water, Flying] | | Ghost | [Poison] | +----------+------------------------------------------------+ Data truncated. @@ -646,15 +653,15 @@

    Distinct +----------+------------------------------------------------+ | Type 1 | Type 2 List | +----------+------------------------------------------------+ -| Bug | [Grass, Flying, Poison] | +| Bug | [Flying, Poison, Grass] | | Poison | [Ground, Flying] | -| Electric | [Steel, Flying] | +| Electric | [Flying, Steel] | | Fairy | | | Normal | [Fairy, Flying] | -| Ice | [Psychic, Flying] | -| Grass | [Psychic, Poison] | +| Ice | [Flying, Psychic] | +| Grass | [Poison, Psychic] | | Fire | [Dragon, Flying] | -| Water | [Ice, Flying, Poison, Dark, Psychic, Fighting] | +| Water | [Fighting, Flying, Dark, Ice, Psychic, Poison] | | Ground | [Rock] | +----------+------------------------------------------------+ Data truncated. diff --git a/user-guide/common-operations/basic-info.html b/user-guide/common-operations/basic-info.html index 3657b7419..14b992d36 100644 --- a/user-guide/common-operations/basic-info.html +++ b/user-guide/common-operations/basic-info.html @@ -117,17 +117,29 @@ Data Sources

    • -
  • - +
  • + DataFrames + + +
  • Common Operations - -
    • -
  • - - datafusion.col - -
  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
    • +
  • + + datafusion.dataframe_formatter + +
  • datafusion.expr @@ -314,8 +326,8 @@ datafusion.input - -
    • -
  • - - datafusion.udf - -
  • datafusion.unparser @@ -439,11 +446,11 @@

    Basic Operations+-----+---------+--------+--------+ | nrs | names | random | groups | +-----+---------+--------+--------+ -| 1 | python | 316 | A | -| 2 | ruby | 698 | A | -| 3 | java | 568 | B | -| 4 | haskell | 804 | C | -| 5 | go | 513 | B | +| 1 | python | 105 | A | +| 2 | ruby | 554 | A | +| 3 | java | 798 | B | +| 4 | haskell | 168 | C | +| 5 | go | 799 | B | +-----+---------+--------+--------+ @@ -454,8 +461,8 @@

    Basic Operations+-----+--------+--------+--------+ | nrs | names | random | groups | +-----+--------+--------+--------+ -| 1 | python | 316 | A | -| 2 | ruby | 698 | A | +| 1 | python | 105 | A | +| 2 | ruby | 554 | A | +-----+--------+--------+--------+ @@ -473,11 +480,11 @@

    Basic Operations
    In [8]: df.to_pandas()
 Out[8]: 
    nrs    names  random groups
-0    1   python     316      A
-1    2     ruby     698      A
-2    3     java     568      B
-3    4  haskell     804      C
-4    5       go     513      B
+0    1   python     105      A
+1    2     ruby     554      A
+2    3     java     798      B
+3    4  haskell     168      C
+4    5       go     799      B

    describe() shows a quick statistic summary of your data:

    @@ -489,11 +496,11 @@

    Basic Operations+------------+--------------------+-------+-------------------+--------+ | count | 5.0 | 5 | 5.0 | 5 | | null_count | 0.0 | 0 | 0.0 | 0 | -| mean | 3.0 | null | 579.8 | null | -| std | 1.5811388300841898 | null | 186.0301050905471 | null | -| min | 1.0 | go | 316.0 | A | -| max | 5.0 | ruby | 804.0 | C | -| median | 3.0 | null | 568.0 | null | +| mean | 3.0 | null | 484.8 | null | +| std | 1.5811388300841898 | null | 333.9965568684803 | null | +| min | 1.0 | go | 105.0 | A | +| max | 5.0 | ruby | 799.0 | C | +| median | 3.0 | null | 554.0 | null | +------------+--------------------+-------+-------------------+--------+ diff --git a/user-guide/common-operations/expressions.html b/user-guide/common-operations/expressions.html index 291245092..d9c4d3512 100644 --- a/user-guide/common-operations/expressions.html +++ b/user-guide/common-operations/expressions.html @@ -117,17 +117,29 @@ Data Sources

    • -
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    • -
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  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
    • +
  • + + datafusion.dataframe_formatter + +
  • datafusion.expr @@ -314,8 +326,8 @@ datafusion.input - -
    • -
  • - - datafusion.udf - -
  • datafusion.unparser diff --git a/user-guide/common-operations/functions.html b/user-guide/common-operations/functions.html index 61123ed4d..c3863d4ae 100644 --- a/user-guide/common-operations/functions.html +++ b/user-guide/common-operations/functions.html @@ -117,17 +117,29 @@ Data Sources
    • -
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  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
    • +
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  • datafusion.expr @@ -314,8 +326,8 @@ datafusion.input - -
    • -
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  • datafusion.unparser @@ -549,16 +556,16 @@

    Temporal +--------------------------------+ | now() | +--------------------------------+ -| 2025-05-28T18:37:38.343210340Z | -| 2025-05-28T18:37:38.343210340Z | -| 2025-05-28T18:37:38.343210340Z | -| 2025-05-28T18:37:38.343210340Z | -| 2025-05-28T18:37:38.343210340Z | -| 2025-05-28T18:37:38.343210340Z | -| 2025-05-28T18:37:38.343210340Z | -| 2025-05-28T18:37:38.343210340Z | -| 2025-05-28T18:37:38.343210340Z | -| 2025-05-28T18:37:38.343210340Z | +| 2025-07-12T11:49:57.473788797Z | +| 2025-07-12T11:49:57.473788797Z | +| 2025-07-12T11:49:57.473788797Z | +| 2025-07-12T11:49:57.473788797Z | +| 2025-07-12T11:49:57.473788797Z | +| 2025-07-12T11:49:57.473788797Z | +| 2025-07-12T11:49:57.473788797Z | +| 2025-07-12T11:49:57.473788797Z | +| 2025-07-12T11:49:57.473788797Z | +| 2025-07-12T11:49:57.473788797Z | +--------------------------------+ Data truncated. diff --git a/user-guide/common-operations/index.html b/user-guide/common-operations/index.html index af2c61f84..aa8a5bfbf 100644 --- a/user-guide/common-operations/index.html +++ b/user-guide/common-operations/index.html @@ -35,7 +35,7 @@ - + @@ -117,17 +117,29 @@ Data Sources

    • -
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  • + DataFrames + + +
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    • -
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  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
    • +
  • + + datafusion.dataframe_formatter + +
  • datafusion.expr @@ -314,8 +326,8 @@ datafusion.input - -
    • -
  • - - datafusion.udf - -
  • datafusion.unparser @@ -482,11 +489,11 @@

    Common Operations +

    previous

    -

    DataFrames

    +

    HTML Rendering in Jupyter

     diff --git a/user-guide/common-operations/joins.html b/user-guide/common-operations/joins.html index 3dc655715..56ae4eaaa 100644 --- a/user-guide/common-operations/joins.html +++ b/user-guide/common-operations/joins.html @@ -117,17 +117,29 @@ Data Sources

    • -
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  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
    • +
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    • -
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  • datafusion.unparser diff --git a/user-guide/common-operations/select-and-filter.html b/user-guide/common-operations/select-and-filter.html index 29f8d8a15..180cd0c9f 100644 --- a/user-guide/common-operations/select-and-filter.html +++ b/user-guide/common-operations/select-and-filter.html @@ -117,17 +117,29 @@ Data Sources
    • -
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  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
    • +
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  • datafusion.expr @@ -314,8 +326,8 @@ datafusion.input - -
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  • datafusion.unparser diff --git a/user-guide/common-operations/udf-and-udfa.html b/user-guide/common-operations/udf-and-udfa.html index a5edf506f..45ac30e2d 100644 --- a/user-guide/common-operations/udf-and-udfa.html +++ b/user-guide/common-operations/udf-and-udfa.html @@ -117,17 +117,29 @@ Data Sources
    • -
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  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
    • +
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  • datafusion.unparser diff --git a/user-guide/common-operations/views.html b/user-guide/common-operations/views.html index be6a9584f..118a2ea93 100644 --- a/user-guide/common-operations/views.html +++ b/user-guide/common-operations/views.html @@ -117,17 +117,29 @@ Data Sources
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  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
    • +
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  • datafusion.unparser diff --git a/user-guide/common-operations/windows.html b/user-guide/common-operations/windows.html index dcd5e5058..4ac5a0952 100644 --- a/user-guide/common-operations/windows.html +++ b/user-guide/common-operations/windows.html @@ -117,17 +117,29 @@ Data Sources
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  • datafusion.unparser diff --git a/user-guide/configuration.html b/user-guide/configuration.html index 5cd45975a..f62b79b39 100644 --- a/user-guide/configuration.html +++ b/user-guide/configuration.html @@ -117,17 +117,29 @@ Data Sources
    • -
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  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
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    • -
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  • datafusion.unparser diff --git a/user-guide/data-sources.html b/user-guide/data-sources.html index f1be5894f..a2a08fc28 100644 --- a/user-guide/data-sources.html +++ b/user-guide/data-sources.html @@ -34,7 +34,7 @@ - + @@ -117,17 +117,29 @@ Data Sources
    • -
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  • datafusion.context @@ -295,6 +302,11 @@ datafusion.dataframe
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    • -
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  • datafusion.unparser @@ -400,40 +407,59 @@
    • +
  • + + + + SessionContext._convert_file_sort_order() + + + +
  • @@ -1734,6 +1743,15 @@

    Module Contents +
    +static _convert_file_sort_order(file_sort_order: collections.abc.Sequence[collections.abc.Sequence[datafusion.expr.SortKey]] | None) → list[list[datafusion._internal.expr.SortExpr]] | None
    +

    Convert nested SortKey sequences into raw sort expressions.

    +

    Each SortKey can be a column name string, an Expr, or a +SortExpr and will be converted using +datafusion.expr.sort_list_to_raw_sort_list().

    +
    +
    static _convert_table_partition_cols(table_partition_cols: list[tuple[str, str | pyarrow.DataType]]) → list[tuple[str, pyarrow.DataType]]
    @@ -1991,7 +2009,7 @@

    Module Contents
    -read_parquet(path: str | pathlib.Path, table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, parquet_pruning: bool = True, file_extension: str = '.parquet', skip_metadata: bool = True, schema: pyarrow.Schema | None = None, file_sort_order: list[list[datafusion.expr.Expr | datafusion.expr.SortExpr]] | None = None) → datafusion.dataframe.DataFrame
    +read_parquet(path: str | pathlib.Path, table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, parquet_pruning: bool = True, file_extension: str = '.parquet', skip_metadata: bool = True, schema: pyarrow.Schema | None = None, file_sort_order: collections.abc.Sequence[collections.abc.Sequence[datafusion.expr.SortKey]] | None = None) → datafusion.dataframe.DataFrame

    Read a Parquet source into a Dataframe.

    Parameters:
    @@ -2008,7 +2026,9 @@

    Module Contentsstr), an expression +(Expr), or a SortExpr.

    • Returns:
    @@ -2116,7 +2136,7 @@

    Module Contents
    -register_listing_table(name: str, path: str | pathlib.Path, table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_extension: str = '.parquet', schema: pyarrow.Schema | None = None, file_sort_order: list[list[datafusion.expr.Expr | datafusion.expr.SortExpr]] | None = None) → None
    +register_listing_table(name: str, path: str | pathlib.Path, table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_extension: str = '.parquet', schema: pyarrow.Schema | None = None, file_sort_order: collections.abc.Sequence[collections.abc.Sequence[datafusion.expr.SortKey]] | None = None) → None

    Register multiple files as a single table.

    Registers a Table that can assemble multiple files from locations in an ObjectStore @@ -2129,7 +2149,9 @@

    Module Contentsstr), an expression +(Expr), or a SortExpr.

    @@ -2152,7 +2174,7 @@

    Module Contents
    -register_parquet(name: str, path: str | pathlib.Path, table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, parquet_pruning: bool = True, file_extension: str = '.parquet', skip_metadata: bool = True, schema: pyarrow.Schema | None = None, file_sort_order: list[list[datafusion.expr.SortExpr]] | None = None) → None
    +register_parquet(name: str, path: str | pathlib.Path, table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, parquet_pruning: bool = True, file_extension: str = '.parquet', skip_metadata: bool = True, schema: pyarrow.Schema | None = None, file_sort_order: collections.abc.Sequence[collections.abc.Sequence[datafusion.expr.SortKey]] | None = None) → None

    Register a Parquet file as a table.

    The registered table can be referenced from SQL statement executed against this context.

    @@ -2170,7 +2192,9 @@

    Module Contentsstr), an expression +(Expr), or a SortExpr.

    diff --git a/autoapi/datafusion/dataframe/index.html b/autoapi/datafusion/dataframe/index.html index 965fe819c..3c61a0aae 100644 --- a/autoapi/datafusion/dataframe/index.html +++ b/autoapi/datafusion/dataframe/index.html @@ -1015,42 +1015,6 @@ +

    For example:

    +
    lead(col("b"), order_by="ts")
+
    +
    @@ -4799,7 +4834,7 @@

    Returns:
    -datafusion.functions.nth_value(expression: datafusion.expr.Expr, n: int, filter: datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.Expr | datafusion.expr.SortExpr] | datafusion.expr.Expr | datafusion.expr.SortExpr | None = None, null_treatment: datafusion.common.NullTreatment = NullTreatment.RESPECT_NULLS) → datafusion.expr.Expr
    +datafusion.functions.nth_value(expression: datafusion.expr.Expr, n: int, filter: datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None, null_treatment: datafusion.common.NullTreatment = NullTreatment.RESPECT_NULLS) → datafusion.expr.Expr

    Returns the n-th value in a group of values.

    This aggregate function will return the n-th value in the partition.

    If using the builder functions described in ref:_aggregation this function ignores @@ -4810,16 +4845,21 @@

    Returns:

    expression – Argument to perform bitwise calculation on

  • n – Index of value to return. Starts at 1.

  • filter – If provided, only compute against rows for which the filter is True

    • -

  • order_by – Set the ordering of the expression to evaluate

    • +

  • order_by – Set the ordering of the expression to evaluate. Accepts +column names or expressions.

  • null_treatment – Assign whether to respect or ignore null values.

    • +

    For example:

    +
    df.select(nth_value(col("a"), 2, order_by="ts"))
+
    +
    -datafusion.functions.ntile(groups: int, partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.Expr | datafusion.expr.SortExpr] | datafusion.expr.Expr | datafusion.expr.SortExpr | None = None) → datafusion.expr.Expr
    +datafusion.functions.ntile(groups: int, partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None) → datafusion.expr.Expr

    Create a n-tile window function.

    This window function orders the window frame into a give number of groups based on the ordering criteria. It then returns which group the current row is assigned to. @@ -4842,10 +4882,15 @@

    Returns:

    • groups – Number of groups for the n-tile to be divided into.

    • partition_by – Expressions to partition the window frame on.

      • -

    • order_by – Set ordering within the window frame.

      • +

    • order_by – Set ordering within the window frame. Accepts +column names or expressions.

    +

    For example:

    +
    ntile(3, order_by="points")
+
    +
    @@ -4883,7 +4928,7 @@

    Returns:
    -datafusion.functions.percent_rank(partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.Expr | datafusion.expr.SortExpr] | datafusion.expr.Expr | datafusion.expr.SortExpr | None = None) → datafusion.expr.Expr
    +datafusion.functions.percent_rank(partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None) → datafusion.expr.Expr

    Create a percent_rank window function.

    This window function is similar to rank() except that the returned values are the percentage from 0.0 to 1.0 from first to last. Here is an example of a @@ -4903,10 +4948,15 @@

    Returns:Parameters:

    • partition_by – Expressions to partition the window frame on.

      • -

    • order_by – Set ordering within the window frame.

      • +

    • order_by – Set ordering within the window frame. Accepts +column names or expressions.

    +

    For example:

    +
    percent_rank(order_by="points")
+
    +
    @@ -4948,11 +4998,11 @@

    Returns:
    -datafusion.functions.rank(partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.Expr | datafusion.expr.SortExpr] | datafusion.expr.Expr | datafusion.expr.SortExpr | None = None) → datafusion.expr.Expr
    +datafusion.functions.rank(partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None) → datafusion.expr.Expr

    Create a rank window function.

    Returns the rank based upon the window order. Consecutive equal values will receive the same rank, but the next different value will not be consecutive but rather the -number of rows that preceed it plus one. This is similar to Olympic medals. If two +number of rows that precede it plus one. This is similar to Olympic medals. If two people tie for gold, the next place is bronze. There would be no silver medal. Here is an example of a dataframe with a window ordered by descending points and the associated rank.

    @@ -4971,10 +5021,15 @@

    Returns:Parameters:

    • partition_by – Expressions to partition the window frame on.

      • -

    • order_by – Set ordering within the window frame.

      • +

    • order_by – Set ordering within the window frame. Accepts +column names or expressions.

    +

    For example:

    +
    rank(order_by="points")
+
    +
    @@ -5217,7 +5272,7 @@

    Returns:
    -datafusion.functions.row_number(partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.Expr | datafusion.expr.SortExpr] | datafusion.expr.Expr | datafusion.expr.SortExpr | None = None) → datafusion.expr.Expr
    +datafusion.functions.row_number(partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None) → datafusion.expr.Expr

    Create a row number window function.

    Returns the row number of the window function.

    Here is an example of the row_number on a simple DataFrame:

    @@ -5235,10 +5290,15 @@

    Returns:Parameters:

    • partition_by – Expressions to partition the window frame on.

      • -

    • order_by – Set ordering within the window frame.

      • +

    • order_by – Set ordering within the window frame. Accepts +column names or expressions.

    +

    For example:

    +
    row_number(order_by="points")
+
    +
    @@ -5358,10 +5418,10 @@

    Returns:
    -datafusion.functions.string_agg(expression: datafusion.expr.Expr, delimiter: str, filter: datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.Expr | datafusion.expr.SortExpr] | datafusion.expr.Expr | datafusion.expr.SortExpr | None = None) → datafusion.expr.Expr
    +datafusion.functions.string_agg(expression: datafusion.expr.Expr, delimiter: str, filter: datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None) → datafusion.expr.Expr

    Concatenates the input strings.

    This aggregate function will concatenate input strings, ignoring null values, and -seperating them with the specified delimiter. Non-string values will be converted to +separating them with the specified delimiter. Non-string values will be converted to their string equivalents.

    If using the builder functions described in ref:_aggregation this function ignores the options distinct and null_treatment.

    @@ -5371,10 +5431,15 @@

    Returns:

    expression – Argument to perform bitwise calculation on

  • delimiter – Text to place between each value of expression

  • filter – If provided, only compute against rows for which the filter is True

    • -

  • order_by – Set the ordering of the expression to evaluate

    • +

  • order_by – Set the ordering of the expression to evaluate. Accepts +column names or expressions.

    • +

    For example:

    +
    df.select(string_agg(col("a"), ",", order_by="b"))
+
    +
    @@ -5573,7 +5638,7 @@

    Returns:
    -datafusion.functions.window(name: str, args: list[datafusion.expr.Expr], partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.Expr | datafusion.expr.SortExpr] | datafusion.expr.Expr | datafusion.expr.SortExpr | None = None, window_frame: datafusion.expr.WindowFrame | None = None, ctx: datafusion.context.SessionContext | None = None) → datafusion.expr.Expr
    +datafusion.functions.window(name: str, args: list[datafusion.expr.Expr], partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None, window_frame: datafusion.expr.WindowFrame | None = None, filter: datafusion.expr.Expr | None = None, distinct: bool = False, ctx: datafusion.context.SessionContext | None = None) → datafusion.expr.Expr

    Creates a new Window function expression.

    This interface will soon be deprecated. Instead of using this interface, users should call the window functions directly. For example, to perform a @@ -5581,6 +5646,10 @@

    Returns:
    df.select(functions.lag(col("a")).partition_by(col("b")).build())
    +

    The order_by parameter accepts column names or expressions, e.g.:

    +
    window("lag", [col("a")], order_by="ts")
+
    +

    diff --git a/autoapi/datafusion/index.html b/autoapi/datafusion/index.html index 390ae840d..a6b550708 100644 --- a/autoapi/datafusion/index.html +++ b/autoapi/datafusion/index.html @@ -1929,42 +1929,6 @@     -
  • allow_single_file_parallelism (datafusion.dataframe.ParquetWriterOptions attribute), [1] +
  • allow_single_file_parallelism (datafusion.dataframe.ParquetWriterOptions attribute)
  • AmazonS3 (in module datafusion.object_store) @@ -1113,38 +1115,38 @@

    B

  • bit_xor() (in module datafusion.functions)
    • -
  • bloom_filter_enabled (datafusion.dataframe.ParquetColumnOptions attribute), [1] +
  • bloom_filter_enabled (datafusion.dataframe.ParquetColumnOptions attribute)
    • -
  • bloom_filter_fpp (datafusion.dataframe.ParquetColumnOptions attribute), [1] +
  • bloom_filter_fpp (datafusion.dataframe.ParquetColumnOptions attribute)
    • -
  • column_index_truncate_length (datafusion.dataframe.ParquetWriterOptions attribute), [1] +
  • column_index_truncate_length (datafusion.dataframe.ParquetWriterOptions attribute)
    • @@ -1311,22 +1313,18 @@

    C

  • (datafusion.expr.Expr method)
    • -
  • column_specific_options (datafusion.dataframe.ParquetWriterOptions attribute), [1] +
  • column_specific_options (datafusion.dataframe.ParquetWriterOptions attribute)
  • Compression (class in datafusion.dataframe)
    • -
  • compression (datafusion.dataframe.ParquetColumnOptions attribute), [1] +
  • compression (datafusion.dataframe.ParquetColumnOptions attribute)
  • concat() (in module datafusion.functions) @@ -1401,10 +1399,10 @@

    C

  • CreateCatalogSchema (in module datafusion.expr)
    • -
  • created_by (datafusion.dataframe.ParquetWriterOptions attribute), [1] +
  • created_by (datafusion.dataframe.ParquetWriterOptions attribute)
  • CreateExternalTable (in module datafusion.expr) @@ -1435,16 +1433,16 @@

    C

    D

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"regr_sxy() (in module datafusion.functions)": [[5, "datafusion.functions.regr_sxy", false]], "regr_syy() (in module datafusion.functions)": [[5, "datafusion.functions.regr_syy", false]], "repartition (in module datafusion.expr)": [[4, "datafusion.expr.Repartition", false]], "repartition() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.repartition", false]], "repartition_by_hash() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.repartition_by_hash", false]], "repeat() (in module datafusion.functions)": [[5, "datafusion.functions.repeat", false]], "replace() (in module datafusion.functions)": [[5, "datafusion.functions.replace", false]], "repr_rows (datafusion.dataframe_formatter.dataframehtmlformatter attribute)": [[3, "datafusion.dataframe_formatter.DataFrameHtmlFormatter.repr_rows", false]], "reset_formatter() (in module datafusion.dataframe_formatter)": [[3, "datafusion.dataframe_formatter.reset_formatter", false]], "reverse() (datafusion.expr method)": [[7, "datafusion.Expr.reverse", false]], "reverse() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.reverse", false]], "reverse() (in module datafusion.functions)": [[5, "datafusion.functions.reverse", false]], "rex_call_operands() (datafusion.expr method)": [[7, "datafusion.Expr.rex_call_operands", false]], "rex_call_operands() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.rex_call_operands", false]], "rex_call_operator() (datafusion.expr method)": [[7, "datafusion.Expr.rex_call_operator", false]], "rex_call_operator() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.rex_call_operator", false]], "rex_type() (datafusion.expr method)": [[7, "datafusion.Expr.rex_type", false]], "rex_type() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.rex_type", false]], "right() (in module datafusion.functions)": [[5, "datafusion.functions.right", false]], "round() (in module datafusion.functions)": [[5, 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false]], "schema_name() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.schema_name", false]], "schema_names() (datafusion.catalog method)": [[7, "datafusion.Catalog.schema_names", false]], "schema_names() (datafusion.catalog.catalog method)": [[0, "datafusion.catalog.Catalog.schema_names", false]], "schema_names() (datafusion.catalog.catalogprovider method)": [[0, "datafusion.catalog.CatalogProvider.schema_names", false]], "schemaprovider (class in datafusion.catalog)": [[0, "datafusion.catalog.SchemaProvider", false]], "select() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.select", false]], "select_columns() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.select_columns", false]], "serde (class in datafusion.substrait)": [[15, "datafusion.substrait.Serde", false]], "serialize() (datafusion.substrait.serde static method)": [[15, "datafusion.substrait.Serde.serialize", false]], "serialize_bytes() 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b/user-guide/common-operations/aggregations.html index f9fe3ca36..e4326f106 100644 --- a/user-guide/common-operations/aggregations.html +++ b/user-guide/common-operations/aggregations.html @@ -610,15 +610,15 @@

    Distinct +----------+--------------------------------------------------+ | Type 1 | Type 2 List | +----------+--------------------------------------------------+ -| Bug | [, Grass, Poison, Flying] | -| Poison | [Flying, Ground, ] | +| Bug | [Poison, , Grass, Flying] | +| Poison | [Ground, , Flying] | | Electric | [Steel, Flying, ] | | Fairy | [] | -| Normal | [Fairy, , Flying] | -| Ice | [Flying, Psychic] | +| Normal | [, Flying, Fairy] | +| Ice | [Psychic, Flying] | | Grass | [, Psychic, Poison] | -| Fire | [, Dragon, Flying] | -| Water | [Fighting, Ice, Dark, Flying, , Poison, Psychic] | +| Fire | [, Flying, Dragon] | +| Water | [, Dark, Poison, Psychic, Flying, Ice, Fighting] | | Ground | [, Rock] | +----------+--------------------------------------------------+ Data truncated. @@ -634,15 +634,15 @@

    Distinct +----------+------------------------------------------------+ | Type 1 | Type 2 List | +----------+------------------------------------------------+ -| Bug | [Grass, Flying, Poison] | +| Bug | [Poison, Grass, Flying] | | Poison | [Flying, Ground] | | Electric | [Flying, Steel] | | Normal | [Flying, Fairy] | | Ice | [Psychic, Flying] | -| Grass | [Psychic, Poison] | +| Grass | [Poison, Psychic] | | Fire | [Dragon, Flying] | -| Water | [Fighting, Flying, Poison, Psychic, Dark, Ice] | -| Rock | [Water, Flying, Ground] | +| Water | [Poison, Psychic, Flying, Fighting, Ice, Dark] | +| Rock | [Flying, Ground, Water] | | Ghost | [Poison] | +----------+------------------------------------------------+ Data truncated. @@ -653,15 +653,15 @@

    Distinct +----------+------------------------------------------------+ | Type 1 | Type 2 List | +----------+------------------------------------------------+ -| Bug | [Poison, Grass, Flying] | +| Bug | [Flying, Grass, Poison] | | Poison | [Flying, Ground] | -| Electric | [Flying, Steel] | +| Electric | [Steel, Flying] | | Fairy | | | Normal | [Fairy, Flying] | | Ice | [Flying, Psychic] | | Grass | [Psychic, Poison] | | Fire | [Dragon, Flying] | -| Water | [Dark, Flying, Poison, Ice, Fighting, Psychic] | +| Water | [Ice, Psychic, Fighting, Dark, Poison, Flying] | | Ground | [Rock] | +----------+------------------------------------------------+ Data truncated. diff --git a/user-guide/common-operations/basic-info.html b/user-guide/common-operations/basic-info.html index c4d5beae8..5f5186e73 100644 --- a/user-guide/common-operations/basic-info.html +++ b/user-guide/common-operations/basic-info.html @@ -446,11 +446,11 @@

    Basic Operations+-----+---------+--------+--------+ | nrs | names | random | groups | +-----+---------+--------+--------+ -| 1 | python | 653 | A | -| 2 | ruby | 417 | A | -| 3 | java | 408 | B | -| 4 | haskell | 196 | C | -| 5 | go | 840 | B | +| 1 | python | 968 | A | +| 2 | ruby | 979 | A | +| 3 | java | 177 | B | +| 4 | haskell | 423 | C | +| 5 | go | 795 | B | +-----+---------+--------+--------+ @@ -461,8 +461,8 @@

    Basic Operations+-----+--------+--------+--------+ | nrs | names | random | groups | +-----+--------+--------+--------+ -| 1 | python | 653 | A | -| 2 | ruby | 417 | A | +| 1 | python | 968 | A | +| 2 | ruby | 979 | A | +-----+--------+--------+--------+ @@ -480,28 +480,28 @@

    Basic Operations
    In [8]: df.to_pandas()
 Out[8]: 
    nrs    names  random groups
-0    1   python     653      A
-1    2     ruby     417      A
-2    3     java     408      B
-3    4  haskell     196      C
-4    5       go     840      B
+0    1   python     968      A
+1    2     ruby     979      A
+2    3     java     177      B
+3    4  haskell     423      C
+4    5       go     795      B

    describe() shows a quick statistic summary of your data:

    In [9]: df.describe()
 Out[9]: 
 DataFrame()
-+------------+--------------------+-------+--------------------+--------+
-| describe   | nrs                | names | random             | groups |
-+------------+--------------------+-------+--------------------+--------+
-| count      | 5.0                | 5     | 5.0                | 5      |
-| null_count | 0.0                | 0     | 0.0                | 0      |
-| mean       | 3.0                | null  | 502.8              | null   |
-| std        | 1.5811388300841898 | null  | 248.36404731764216 | null   |
-| min        | 1.0                | go    | 196.0              | A      |
-| max        | 5.0                | ruby  | 840.0              | C      |
-| median     | 3.0                | null  | 417.0              | null   |
-+------------+--------------------+-------+--------------------+--------+
++------------+--------------------+-------+-------------------+--------+
+| describe   | nrs                | names | random            | groups |
++------------+--------------------+-------+-------------------+--------+
+| count      | 5.0                | 5     | 5.0               | 5      |
+| null_count | 0.0                | 0     | 0.0               | 0      |
+| mean       | 3.0                | null  | 668.4             | null   |
+| std        | 1.5811388300841898 | null  | 354.9490104226239 | null   |
+| min        | 1.0                | go    | 177.0             | A      |
+| max        | 5.0                | ruby  | 979.0             | C      |
+| median     | 3.0                | null  | 795.0             | null   |
++------------+--------------------+-------+-------------------+--------+
    diff --git a/user-guide/common-operations/expressions.html b/user-guide/common-operations/expressions.html index d9c4d3512..f2358ca39 100644 --- a/user-guide/common-operations/expressions.html +++ b/user-guide/common-operations/expressions.html @@ -497,7 +497,7 @@

    Boolean

    Arrays

    For columns that contain arrays of values, you can access individual elements of the array by index -using bracket indexing. This is similar to callling the function +using bracket indexing. This is similar to calling the function datafusion.functions.array_element(), except that array indexing using brackets is 0 based, similar to Python arrays and array_element is 1 based indexing to be compatible with other SQL approaches.

    @@ -523,18 +523,31 @@

    ArraysIndexing an element of an array via [] starts at index 0 whereas array_element() starts at index 1.

    +

    Starting in DataFusion 49.0.0 you can also create slices of array elements using +slice syntax from Python.

    +
    In [9]: df.select(col("a")[1:3].alias("second_two_elements"))
+Out[9]: 
+DataFrame()
++---------------------+
+| second_two_elements |
++---------------------+
+| [2, 3]              |
+| [5, 6]              |
++---------------------+
+
    +

    To check if an array is empty, you can use the function datafusion.functions.array_empty() or datafusion.functions.empty. This function returns a boolean indicating whether the array is empty.

    -
    In [9]: from datafusion import SessionContext, col
+
    In [10]: from datafusion import SessionContext, col
 
-In [10]: from datafusion.functions import array_empty
+In [11]: from datafusion.functions import array_empty
 
-In [11]: ctx = SessionContext()
+In [12]: ctx = SessionContext()
 
-In [12]: df = ctx.from_pydict({"a": [[], [1, 2, 3]]})
+In [13]: df = ctx.from_pydict({"a": [[], [1, 2, 3]]})
 
-In [13]: df.select(array_empty(col("a")).alias("is_empty"))
-Out[13]: 
+In [14]: df.select(array_empty(col("a")).alias("is_empty"))
+Out[14]: 
 DataFrame()
 +----------+
 | is_empty |
@@ -547,16 +560,16 @@ 
    ArraysIn this example, the is_empty column will contain True for the first row and False for the second row.
    
 
    To get the total number of elements in an array, you can use the function datafusion.functions.cardinality().
 This function returns an integer indicating the total number of elements in the array.
    
-
    In [14]: from datafusion import SessionContext, col
+
    In [15]: from datafusion import SessionContext, col
 
-In [15]: from datafusion.functions import cardinality
+In [16]: from datafusion.functions import cardinality
 
-In [16]: ctx = SessionContext()
+In [17]: ctx = SessionContext()
 
-In [17]: df = ctx.from_pydict({"a": [[1, 2, 3], [4, 5, 6]]})
+In [18]: df = ctx.from_pydict({"a": [[1, 2, 3], [4, 5, 6]]})
 
-In [18]: df.select(cardinality(col("a")).alias("num_elements"))
-Out[18]: 
+In [19]: df.select(cardinality(col("a")).alias("num_elements"))
+Out[19]: 
 DataFrame()
 +--------------+
 | num_elements |
@@ -569,16 +582,16 @@ 
    ArraysIn this example, the num_elements column will contain 3 for both rows.
    
 
    To concatenate two arrays, you can use the function datafusion.functions.array_cat() or datafusion.functions.array_concat().
 These functions return a new array that is the concatenation of the input arrays.
    
-
    In [19]: from datafusion import SessionContext, col
+
    In [20]: from datafusion import SessionContext, col
 
-In [20]: from datafusion.functions import array_cat, array_concat
+In [21]: from datafusion.functions import array_cat, array_concat
 
-In [21]: ctx = SessionContext()
+In [22]: ctx = SessionContext()
 
-In [22]: df = ctx.from_pydict({"a": [[1, 2, 3]], "b": [[4, 5, 6]]})
+In [23]: df = ctx.from_pydict({"a": [[1, 2, 3]], "b": [[4, 5, 6]]})
 
-In [23]: df.select(array_cat(col("a"), col("b")).alias("concatenated_array"))
-Out[23]: 
+In [24]: df.select(array_cat(col("a"), col("b")).alias("concatenated_array"))
+Out[24]: 
 DataFrame()
 +--------------------+
 | concatenated_array |
@@ -590,16 +603,16 @@ 
    ArraysIn this example, the concatenated_array column will contain [1, 2, 3, 4, 5, 6].
    
 
    To repeat the elements of an array a specified number of times, you can use the function datafusion.functions.array_repeat().
 This function returns a new array with the elements repeated.
    
-
    In [24]: from datafusion import SessionContext, col, literal
+
    In [25]: from datafusion import SessionContext, col, literal
 
-In [25]: from datafusion.functions import array_repeat
+In [26]: from datafusion.functions import array_repeat
 
-In [26]: ctx = SessionContext()
+In [27]: ctx = SessionContext()
 
-In [27]: df = ctx.from_pydict({"a": [[1, 2, 3]]})
+In [28]: df = ctx.from_pydict({"a": [[1, 2, 3]]})
 
-In [28]: df.select(array_repeat(col("a"), literal(2)).alias("repeated_array"))
-Out[28]: 
+In [29]: df.select(array_repeat(col("a"), literal(2)).alias("repeated_array"))
+Out[29]: 
 DataFrame()
 +------------------------+
 | repeated_array         |
@@ -614,14 +627,14 @@ 
    ArraysStructs
    
 
    Columns that contain struct elements can be accessed using the bracket notation as if they were
 Python dictionary style objects. This expects a string key as the parameter passed.
    
-
    In [29]: ctx = SessionContext()
+
    In [30]: ctx = SessionContext()
 
-In [30]: data = {"a": [{"size": 15, "color": "green"}, {"size": 10, "color": "blue"}]}
+In [31]: data = {"a": [{"size": 15, "color": "green"}, {"size": 10, "color": "blue"}]}
 
-In [31]: df = ctx.from_pydict(data)
+In [32]: df = ctx.from_pydict(data)
 
-In [32]: df.select(col("a")["size"].alias("a_size"))
-Out[32]: 
+In [33]: df.select(col("a")["size"].alias("a_size"))
+Out[33]: 
 DataFrame()
 +--------+
 | a_size |
@@ -638,17 +651,17 @@ 
    Functionsalias() is a function that takes
 as it input a single expression and returns an expression in which the name of the expression has changed.
    
 
    The following example shows a series of expressions that are built up from functions operating on expressions.
    
-
    In [33]: from datafusion import SessionContext
+
    In [34]: from datafusion import SessionContext
 
-In [34]: from datafusion import column, lit
+In [35]: from datafusion import column, lit
 
-In [35]: from datafusion import functions as f
+In [36]: from datafusion import functions as f
 
-In [36]: import random
+In [37]: import random
 
-In [37]: ctx = SessionContext()
+In [38]: ctx = SessionContext()
 
-In [38]: df = ctx.from_pydict(
+In [39]: df = ctx.from_pydict(
    ....:     {
    ....:         "name": ["Albert", "Becca", "Carlos", "Dante"],
    ....:         "age": [42, 67, 27, 71],
@@ -658,20 +671,20 @@ 
    Functions....: )
    ....: 
 
-In [39]: age_col = col("age")
+In [40]: age_col = col("age")
 
-In [40]: renamed_age = age_col.alias("age_in_years")
+In [41]: renamed_age = age_col.alias("age_in_years")
 
-In [41]: start_age = age_col - col("years_in_position")
+In [42]: start_age = age_col - col("years_in_position")
 
-In [42]: started_young = start_age < lit(18)
+In [43]: started_young = start_age < lit(18)
 
-In [43]: can_retire = age_col > lit(65)
+In [44]: can_retire = age_col > lit(65)
 
-In [44]: long_timer = started_young & can_retire
+In [45]: long_timer = started_young & can_retire
 
-In [45]: df.filter(long_timer).select(col("name"), renamed_age, col("years_in_position"))
-Out[45]: 
+In [46]: df.filter(long_timer).select(col("name"), renamed_age, col("years_in_position"))
+Out[46]: 
 DataFrame()
 +-------+--------------+-------------------+
 | name  | age_in_years | years_in_position |
diff --git a/user-guide/common-operations/functions.html b/user-guide/common-operations/functions.html
index 916147c19..cfc85464f 100644
--- a/user-guide/common-operations/functions.html
+++ b/user-guide/common-operations/functions.html
@@ -556,16 +556,16 @@ 
    Temporal
 +--------------------------------+
 | now()                          |
 +--------------------------------+
-| 2025-08-29T01:44:48.517857695Z |
-| 2025-08-29T01:44:48.517857695Z |
-| 2025-08-29T01:44:48.517857695Z |
-| 2025-08-29T01:44:48.517857695Z |
-| 2025-08-29T01:44:48.517857695Z |
-| 2025-08-29T01:44:48.517857695Z |
-| 2025-08-29T01:44:48.517857695Z |
-| 2025-08-29T01:44:48.517857695Z |
-| 2025-08-29T01:44:48.517857695Z |
-| 2025-08-29T01:44:48.517857695Z |
+| 2025-09-17T19:32:40.245872298Z |
+| 2025-09-17T19:32:40.245872298Z |
+| 2025-09-17T19:32:40.245872298Z |
+| 2025-09-17T19:32:40.245872298Z |
+| 2025-09-17T19:32:40.245872298Z |
+| 2025-09-17T19:32:40.245872298Z |
+| 2025-09-17T19:32:40.245872298Z |
+| 2025-09-17T19:32:40.245872298Z |
+| 2025-09-17T19:32:40.245872298Z |
+| 2025-09-17T19:32:40.245872298Z |
 +--------------------------------+
 Data truncated.
 
    
diff --git a/user-guide/common-operations/windows.html b/user-guide/common-operations/windows.html
index 4ac5a0952..ac2682ab1 100644
--- a/user-guide/common-operations/windows.html
+++ b/user-guide/common-operations/windows.html
@@ -470,11 +470,11 @@
 
    In this section you will learn about window functions. A window function utilizes values from one or
 multiple rows to produce a result for each individual row, unlike an aggregate function that
 provides a single value for multiple rows.
    
-
    The window functions are availble in the functions module.
    
+
    The window functions are available in the functions module.
    
 
    We’ll use the pokemon dataset (from Ritchie Vink) in the following examples.
    
 
    In [1]: from datafusion import SessionContext
 
-In [2]: from datafusion import col
+In [2]: from datafusion import col, lit
 
 In [3]: from datafusion import functions as f
 
@@ -590,8 +590,8 @@ 
    Window Frame
 
  • If an order_by clause is set, the default window frame is defined as the rows between
-unbounded preceeding and the current row.
    • 
-
  • If an order_by is not set, the default frame is defined as the rows betwene unbounded
+unbounded preceding and the current row.
    • 
+
  • If an order_by is not set, the default frame is defined as the rows between unbounded
 and unbounded following (the entire partition).
    • 
 
 
    Window Frames are defined by three parameters: unit type, starting bound, and ending bound.
    
@@ -606,17 +606,15 @@ 
    Window Frameorder_by clause.
    
 
 
    In this example we perform a “rolling average” of the speed of the current Pokemon and the
-two preceeding rows.
    
-
    In [9]: from datafusion.expr import WindowFrame
+two preceding rows.
    
+
    In [9]: from datafusion.expr import Window, WindowFrame
 
 In [10]: df.select(
    ....:     col('"Name"'),
    ....:     col('"Speed"'),
-   ....:     f.window("avg",
-   ....:         [col('"Speed"')],
-   ....:         order_by=[col('"Speed"')],
-   ....:         window_frame=WindowFrame("rows", 2, 0)
-   ....:     ).alias("Previous Speed")
+   ....:     f.avg(col('"Speed"'))
+   ....:     .over(Window(window_frame=WindowFrame("rows", 2, 0), order_by=[col('"Speed"')]))
+   ....:     .alias("Previous Speed"),
    ....: )
    ....: 
 Out[10]: 
@@ -652,21 +650,27 @@ 
    Null TreatmentType 2 column that are null.
    
 
    In [11]: from datafusion.common import NullTreatment
 
-In [12]: df.filter(col('"Type 1"') ==  lit("Bug")).select(
+In [12]: df.filter(col('"Type 1"') == lit("Bug")).select(
    ....:     '"Name"',
    ....:     '"Type 2"',
-   ....:     f.window("last_value", [col('"Type 2"')])
-   ....:         .window_frame(WindowFrame("rows", None, 0))
-   ....:         .order_by(col('"Speed"'))
-   ....:         .null_treatment(NullTreatment.IGNORE_NULLS)
-   ....:         .build()
-   ....:         .alias("last_wo_null"),
-   ....:     f.window("last_value", [col('"Type 2"')])
-   ....:         .window_frame(WindowFrame("rows", None, 0))
-   ....:         .order_by(col('"Speed"'))
-   ....:         .null_treatment(NullTreatment.RESPECT_NULLS)
-   ....:         .build()
-   ....:         .alias("last_with_null")
+   ....:     f.last_value(col('"Type 2"'))
+   ....:     .over(
+   ....:         Window(
+   ....:             window_frame=WindowFrame("rows", None, 0),
+   ....:             order_by=[col('"Speed"')],
+   ....:             null_treatment=NullTreatment.IGNORE_NULLS,
+   ....:         )
+   ....:     )
+   ....:     .alias("last_wo_null"),
+   ....:     f.last_value(col('"Type 2"'))
+   ....:     .over(
+   ....:         Window(
+   ....:             window_frame=WindowFrame("rows", None, 0),
+   ....:             order_by=[col('"Speed"')],
+   ....:             null_treatment=NullTreatment.RESPECT_NULLS,
+   ....:         )
+   ....:     )
+   ....:     .alias("last_with_null"),
    ....: )
    ....: 
 Out[12]: 
diff --git a/user-guide/configuration.html b/user-guide/configuration.html
index f62b79b39..87ebc3ee6 100644
--- a/user-guide/configuration.html
+++ b/user-guide/configuration.html
@@ -401,9 +401,33 @@
               
               
    
                 
+
    
+     On this page
+
    
 
     
               
    
               
@@ -451,8 +475,126 @@ 
    Configurationprint(ctx)
 
    
 
    
-
    You can read more about available SessionConfig options in the rust DataFusion Configuration guide,
+
    
+
    Maximizing CPU Usage
    
+
    DataFusion uses partitions to parallelize work. For small queries the
+default configuration (number of CPU cores) is often sufficient, but to
+fully utilize available hardware you can tune how many partitions are
+created and when DataFusion will repartition data automatically.
    
+
    Configure a SessionContext with a higher partition count:
    
+
    from datafusion import SessionConfig, SessionContext
+
+# allow up to 16 concurrent partitions
+config = SessionConfig().with_target_partitions(16)
+ctx = SessionContext(config)
+
    
+
    
+
    Automatic repartitioning for joins, aggregations, window functions and
+other operations can be enabled to increase parallelism:
    
+
    config = (
+    SessionConfig()
+    .with_target_partitions(16)
+    .with_repartition_joins(True)
+    .with_repartition_aggregations(True)
+    .with_repartition_windows(True)
+)
+
    
+
    
+
    Manual repartitioning is available on DataFrames when you need precise
+control:
    
+
    from datafusion import col
+
+df = ctx.read_parquet("data.parquet")
+
+# Evenly divide into 16 partitions
+df = df.repartition(16)
+
+# Or partition by the hash of a column
+df = df.repartition_by_hash(col("a"), num=16)
+
+result = df.collect()
+
    
+
    
+
    
+
    Benchmark Example
    
+
    The repository includes a benchmark script that demonstrates how to maximize CPU usage
+with DataFusion. The benchmarks/max_cpu_usage.py script shows a practical example
+of configuring DataFusion for optimal parallelism.
    
+
    You can run the benchmark script to see the impact of different configuration settings:
    
+
    # Run with default settings (uses all CPU cores)
+python benchmarks/max_cpu_usage.py
+
+# Run with specific number of rows and partitions
+python benchmarks/max_cpu_usage.py --rows 5000000 --partitions 16
+
+# See all available options
+python benchmarks/max_cpu_usage.py --help
+
    
+
    
+
    Here’s an example showing the performance difference between single and multiple partitions:
    
+
    # Single partition - slower processing
+$ python benchmarks/max_cpu_usage.py --rows=10000000 --partitions 1
+Processed 10000000 rows using 1 partitions in 0.107s
+
+# Multiple partitions - faster processing
+$ python benchmarks/max_cpu_usage.py --rows=10000000 --partitions 10
+Processed 10000000 rows using 10 partitions in 0.038s
+
    
+
    
+
    This example demonstrates nearly 3x performance improvement (0.107s vs 0.038s) when using
+10 partitions instead of 1, showcasing how proper partitioning can significantly improve
+CPU utilization and query performance.
    
+
    The script demonstrates several key optimization techniques:
    
+
      
+
    1. Higher target partition count: Uses with_target_partitions() to set the number of concurrent partitions
      2. 
+
    2. Automatic repartitioning: Enables repartitioning for joins, aggregations, and window functions
      3. 
+
    3. Manual repartitioning: Uses repartition() to ensure all partitions are utilized
      4. 
+
    4. CPU-intensive operations: Performs aggregations that can benefit from parallelization
      5. 
+
    
+
    The benchmark creates synthetic data and measures the time taken to perform a sum aggregation
+across the specified number of partitions. This helps you understand how partition configuration
+affects performance on your specific hardware.
    
+
    
+
    Important Considerations
    
+
    The provided benchmark script demonstrates partitioning concepts using synthetic in-memory data
+and simple aggregation operations. While useful for understanding basic configuration principles,
+actual performance in production environments may vary significantly based on numerous factors:
    
+
    Data Sources and I/O Characteristics:
    
+
      
+
    • Table providers: Performance differs greatly between Parquet files, CSV files, databases, and cloud storage
      • 
+
    • Storage type: Local SSD, network-attached storage, and cloud storage have vastly different characteristics
      • 
+
    • Network latency: Remote data sources introduce additional latency considerations
      • 
+
    • File sizes and distribution: Large files may benefit differently from partitioning than many small files
      • 
+
    
+
    Query and Workload Characteristics:
    
+
      
+
    • Operation complexity: Simple aggregations versus complex joins, window functions, or nested queries
      • 
+
    • Data distribution: Skewed data may not partition evenly, affecting parallel efficiency
      • 
+
    • Memory usage: Large datasets may require different memory management strategies
      • 
+
    • Concurrent workloads: Multiple queries running simultaneously affect resource allocation
      • 
+
    
+
    Hardware and Environment Factors:
    
+
      
+
    • CPU architecture: Different processors have varying parallel processing capabilities
      • 
+
    • Available memory: Limited RAM may require different optimization strategies
      • 
+
    • System load: Other applications competing for resources affect DataFusion performance
      • 
+
    
+
    Recommendations for Production Use:
    
+
    To optimize DataFusion for your specific use case, it is strongly recommended to:
    
+
      
+
    1. Create custom benchmarks using your actual data sources, formats, and query patterns
      2. 
+
    2. Test with representative data volumes that match your production workloads
      3. 
+
    3. Measure end-to-end performance including data loading, processing, and result handling
      4. 
+
    4. Evaluate different configuration combinations for your specific hardware and workload
      5. 
+
    5. Monitor resource utilization (CPU, memory, I/O) to identify bottlenecks in your environment
      6. 
+
    
+
    This approach will provide more accurate insights into how DataFusion configuration options
+will impact your particular applications and infrastructure.
    
+
    For more information about available SessionConfig options, see the rust DataFusion Configuration guide,
 and about RuntimeEnvBuilder options in the rust online API documentation.
    
+
    
+
    
+

    diff --git a/user-guide/data-sources.html b/user-guide/data-sources.html index a2a08fc28..a97fd0274 100644 --- a/user-guide/data-sources.html +++ b/user-guide/data-sources.html @@ -438,8 +438,8 @@
  • - - Iceberg + + Apache Iceberg
  • @@ -487,7 +487,7 @@

    DataFusion provides a wide variety of ways to get data into a DataFrame to perform operations.

    Local file

    -

    DataFusion has the abilty to read from a variety of popular file formats, such as Parquet, +

    DataFusion has the ability to read from a variety of popular file formats, such as Parquet, CSV, JSON, and AVRO.

    In [1]: from datafusion import SessionContext
 
@@ -628,7 +628,7 @@ 
    Other DataFrame LibrariesPolars and Pandas.
 Since DataFusion version 42.0.0, any DataFrame library that supports the Arrow FFI PyCapsule
 interface can be imported to DataFusion using the
-from_arrow() function. Older verions of Polars may
+from_arrow() function. Older versions of Polars may
 not support the arrow interface. In those cases, you can still import via the
 from_polars() function.
    
 
    import pandas as pd
@@ -674,16 +674,44 @@ 
    Delta Lake
-
    Iceberg
    
-
    Coming soon!
    
+
    
+
    Apache Iceberg
    
+
    DataFusion 45.0.0 and later support the ability to register Apache Iceberg tables as table providers through the Custom Table Provider interface.
    
+
    This requires either the pyiceberg library (>=0.10.0) or the pyiceberg-core library (>=0.5.0).
    
+
      
+
    • The pyiceberg-core library exposes Iceberg Rust’s implementation of the Custom Table Provider interface as python bindings.
      • 
+
    • The pyiceberg library utilizes the pyiceberg-core python bindings under the hood and provides a native way for Python users to interact with the DataFusion.
      • 
+
    
+
    from datafusion import SessionContext
+from pyiceberg.catalog import load_catalog
+import pyarrow as pa
+
+# Load catalog and create/load a table
+catalog = load_catalog("catalog", type="in-memory")
+catalog.create_namespace_if_not_exists("default")
+
+# Create some sample data
+data = pa.table({"x": [1, 2, 3], "y": [4, 5, 6]})
+iceberg_table = catalog.create_table("default.test", schema=data.schema)
+iceberg_table.append(data)
+
+# Register the table with DataFusion
+ctx = SessionContext()
+ctx.register_table_provider("test", iceberg_table)
+
+# Query the table using DataFusion
+ctx.table("test").show()
+
    
+
    
+
    Note that the Datafusion integration rely on features from the Iceberg Rust implementation instead of the PyIceberg implementation.
+Features that are available in PyIceberg but not yet in Iceberg Rust will not be available when using DataFusion.
    
 
    
 
    
 
    Custom Table Provider
    
 
    You can implement a custom Data Provider in Rust and expose it to DataFusion through the
 the interface as describe in the Custom Table Provider
 section. This is an advanced topic, but a
-user example
+user example
 is provided in the DataFusion repository.
    diff --git a/user-guide/dataframe/index.html b/user-guide/dataframe/index.html index c463e85cd..cf5c2acd0 100644 --- a/user-guide/dataframe/index.html +++ b/user-guide/dataframe/index.html @@ -422,6 +422,11 @@ Common DataFrame Operations
    • +
  • + + Column Names as Function Arguments + +
  • Terminal Operations @@ -571,6 +576,46 @@

    Common DataFrame Operations +

    Column Names as Function Arguments

    +

    Some DataFrame methods accept column names when an argument refers to an +existing column. These include:

    +
      +

    • select()

      • +

    • sort()

      • +

    • drop()

      • +

    • join() (on argument)

      • +

    • aggregate() (grouping columns)

      • +
    +

    See the full function documentation for details on any specific function.

    +

    Note that join_on() expects col()/column() expressions rather than plain strings.

    +

    For such methods, you can pass column names directly:

    +
    from datafusion import col, functions as f
+
+df.sort('id')
+df.aggregate('id', [f.count(col('value'))])
+
    +
    +

    The same operation can also be written with explicit column expressions, using either col() or column():

    +
    from datafusion import col, column, functions as f
+
+df.sort(col('id'))
+df.aggregate(column('id'), [f.count(col('value'))])
+
    +
    +

    Note that column() is an alias of col(), so you can use either name; the example above shows both in action.

    +

    Whenever an argument represents an expression—such as in +filter() or +with_column()—use col() to reference +columns. The comparison and arithmetic operators on Expr will automatically +convert any non-Expr value into a literal expression, so writing

    +
    from datafusion import col
+df.filter(col("age") > 21)
+
    +
    +

    is equivalent to using lit(21) explicitly. Use lit() (also available +as literal()) when you need to construct a literal expression directly.

    +

    Terminal Operations

    To materialize the results of your DataFrame operations:

    diff --git a/user-guide/introduction.html b/user-guide/introduction.html index e04de54ea..df9a43faf 100644 --- a/user-guide/introduction.html +++ b/user-guide/introduction.html @@ -447,7 +447,7 @@

    Installation
    In [1]: import datafusion
 
 In [2]: datafusion.__version__
-Out[2]: '49.0.0'
+Out[2]: '50.0.0'

    In this documentation we will also show some examples for how DataFusion integrates From 77d9838c085845dd7a1b80236d71416d30e8f09a Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Thu, 16 Oct 2025 17:13:59 +0000 Subject: [PATCH 30/36] Publish built docs triggered by 5646693c2b9f040e8801606f5916b24221738774 --- .../autoapi/datafusion/catalog/index.rst.txt | 40 +++- .../autoapi/datafusion/context/index.rst.txt | 22 +- .../datafusion/dataframe/index.rst.txt | 138 +++++++++-- _sources/autoapi/datafusion/index.rst.txt | 73 +++++- _sources/contributor-guide/ffi.rst.txt | 63 ++++- .../contributor-guide/introduction.rst.txt | 4 + _sources/user-guide/data-sources.rst.txt | 4 +- _sources/user-guide/io/table_provider.rst.txt | 20 +- autoapi/datafusion/catalog/index.html | 67 ++++-- autoapi/datafusion/context/index.html | 21 +- autoapi/datafusion/dataframe/index.html | 225 ++++++++++++++++-- autoapi/datafusion/index.html | 169 +++++++++++-- contributor-guide/ffi.html | 56 +++++ contributor-guide/introduction.html | 3 + genindex.html | 74 ++++-- objects.inv | Bin 8586 -> 8766 bytes searchindex.js | 2 +- .../common-operations/aggregations.html | 32 +-- user-guide/common-operations/basic-info.html | 34 +-- user-guide/common-operations/functions.html | 20 +- user-guide/data-sources.html | 2 +- user-guide/introduction.html | 2 +- user-guide/io/table_provider.html | 22 +- 23 files changed, 887 insertions(+), 206 deletions(-) diff --git a/_sources/autoapi/datafusion/catalog/index.rst.txt b/_sources/autoapi/datafusion/catalog/index.rst.txt index 9364aae2e..50fec8af3 100644 --- a/_sources/autoapi/datafusion/catalog/index.rst.txt +++ b/_sources/autoapi/datafusion/catalog/index.rst.txt @@ -63,7 +63,7 @@ Module Contents - .. py:method:: register_schema(name, schema) -> Schema | None + .. py:method:: register_schema(name: str, schema: Schema | SchemaProvider | SchemaProviderExportable) -> Schema | None Register a schema with this catalog. @@ -162,9 +162,9 @@ Module Contents - .. py:method:: register_table(name, table) -> None + .. py:method:: register_table(name: str, table: Table | datafusion.context.TableProviderExportable | datafusion.DataFrame | pyarrow.dataset.Dataset) -> None - Register a table provider in this schema. + Register a table in this schema. @@ -191,7 +191,7 @@ Module Contents Abstract class for defining a Python based Schema Provider. - .. py:method:: deregister_table(name, cascade: bool) -> None + .. py:method:: deregister_table(name: str, cascade: bool) -> None Remove a table from this schema. @@ -208,9 +208,9 @@ Module Contents - .. py:method:: register_table(name: str, table: Table) -> None + .. py:method:: register_table(name: str, table: Table | datafusion.context.TableProviderExportable | Any) -> None - Add a table from this schema. + Add a table to this schema. This method is optional. If your schema provides a fixed list of tables, you do not need to implement this method. @@ -241,11 +241,20 @@ Module Contents -.. py:class:: Table(table: datafusion._internal.catalog.RawTable) +.. py:class:: Table(table: Table | datafusion.context.TableProviderExportable | datafusion.DataFrame | pyarrow.dataset.Dataset) - DataFusion table. + A DataFusion table. - This constructor is not typically called by the end user. + Internally we currently support the following types of tables: + + - Tables created using built-in DataFusion methods, such as + reading from CSV or Parquet + - pyarrow datasets + - DataFusion DataFrames, which will be converted into a view + - Externally provided tables implemented with the FFI PyCapsule + interface (advanced) + + Constructor. .. py:method:: __repr__() -> str @@ -258,8 +267,16 @@ Module Contents :staticmethod: - Turn a pyarrow Dataset into a Table. + Turn a :mod:`pyarrow.dataset` ``Dataset`` into a :class:`Table`. + + + .. py:attribute:: __slots__ + :value: ('_inner',) + + + + .. py:attribute:: _inner .. py:property:: kind @@ -276,6 +293,3 @@ Module Contents Returns the schema associated with this table. - .. py:attribute:: table - - diff --git a/_sources/autoapi/datafusion/context/index.rst.txt b/_sources/autoapi/datafusion/context/index.rst.txt index 4725845e2..3641fe8e6 100644 --- a/_sources/autoapi/datafusion/context/index.rst.txt +++ b/_sources/autoapi/datafusion/context/index.rst.txt @@ -663,14 +663,10 @@ Module Contents - .. py:method:: read_table(table: datafusion.catalog.Table) -> datafusion.dataframe.DataFrame + .. py:method:: read_table(table: datafusion.catalog.Table | TableProviderExportable | datafusion.dataframe.DataFrame | pyarrow.dataset.Dataset) -> datafusion.dataframe.DataFrame Creates a :py:class:`~datafusion.dataframe.DataFrame` from a table. - For a :py:class:`~datafusion.catalog.Table` such as a - :py:class:`~datafusion.catalog.ListingTable`, create a - :py:class:`~datafusion.dataframe.DataFrame`. - .. py:method:: register_avro(name: str, path: str | pathlib.Path, schema: pyarrow.Schema | None = None, file_extension: str = '.avro', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None) -> None @@ -809,23 +805,23 @@ Module Contents - .. py:method:: register_table(name: str, table: datafusion.catalog.Table) -> None + .. py:method:: register_table(name: str, table: datafusion.catalog.Table | TableProviderExportable | datafusion.dataframe.DataFrame | pyarrow.dataset.Dataset) -> None - Register a :py:class: `~datafusion.catalog.Table` as a table. + Register a :py:class:`~datafusion.Table` with this context. - The registered table can be referenced from SQL statement executed against. + The registered table can be referenced from SQL statements executed against + this context. :param name: Name of the resultant table. - :param table: DataFusion table to add to the session context. + :param table: Any object that can be converted into a :class:`Table`. - .. py:method:: register_table_provider(name: str, provider: TableProviderExportable) -> None + .. py:method:: register_table_provider(name: str, provider: datafusion.catalog.Table | TableProviderExportable | datafusion.dataframe.DataFrame | pyarrow.dataset.Dataset) -> None Register a table provider. - This table provider must have a method called ``__datafusion_table_provider__`` - which returns a PyCapsule that exposes a ``FFI_TableProvider``. + Deprecated: use :meth:`register_table` instead. @@ -855,7 +851,7 @@ Module Contents .. py:method:: register_view(name: str, df: datafusion.dataframe.DataFrame) -> None - Register a :py:class: `~datafusion.detaframe.DataFrame` as a view. + Register a :py:class:`~datafusion.dataframe.DataFrame` as a view. :param name: The name to register the view under. :type name: str diff --git a/_sources/autoapi/datafusion/dataframe/index.rst.txt b/_sources/autoapi/datafusion/dataframe/index.rst.txt index cfc715bb1..8898ceaf0 100644 --- a/_sources/autoapi/datafusion/dataframe/index.rst.txt +++ b/_sources/autoapi/datafusion/dataframe/index.rst.txt @@ -18,6 +18,8 @@ Classes datafusion.dataframe.Compression datafusion.dataframe.DataFrame + datafusion.dataframe.DataFrameWriteOptions + datafusion.dataframe.InsertOp datafusion.dataframe.ParquetColumnOptions datafusion.dataframe.ParquetWriterOptions @@ -240,10 +242,20 @@ Module Contents Drop arbitrary amount of columns. - :param columns: Column names to drop from the dataframe. + Column names are case-sensitive and do not require double quotes like + other operations such as `select`. Leading and trailing double quotes + are allowed and will be automatically stripped if present. + + :param columns: Column names to drop from the dataframe. Both ``column_name`` + and ``"column_name"`` are accepted. :returns: DataFrame with those columns removed in the projection. + Example Usage:: + + df.drop('ID_For_Students') # Works + df.drop('"ID_For_Students"') # Also works (quotes stripped) + .. py:method:: except_all(other: DataFrame) -> DataFrame @@ -361,9 +373,19 @@ Module Contents - .. py:method:: into_view() -> pyarrow.Table + .. py:method:: into_view() -> datafusion.catalog.Table - Convert DataFrame as a ViewTable which can be used in register_table. + Convert ``DataFrame`` into a :class:`~datafusion.Table`. + + .. rubric:: Examples + + >>> from datafusion import SessionContext + >>> ctx = SessionContext() + >>> df = ctx.sql("SELECT 1 AS value") + >>> view = df.into_view() + >>> ctx.register_table("values_view", view) + >>> df.collect() # The DataFrame is still usable + >>> ctx.sql("SELECT value FROM values_view").collect() @@ -436,6 +458,27 @@ Module Contents + .. py:method:: parse_sql_expr(expr: str) -> datafusion.expr.Expr + + Creates logical expression from a SQL query text. + + The expression is created and processed against the current schema. + + Example:: + + from datafusion import col, lit + df.parse_sql_expr("a > 1") + + should produce: + + col("a") > lit(1) + + :param expr: Expression string to be converted to datafusion expression + + :returns: Logical expression . + + + .. py:method:: repartition(num: int) -> DataFrame Repartition a DataFrame into ``num`` partitions. @@ -693,47 +736,54 @@ Module Contents - .. py:method:: write_csv(path: str | pathlib.Path, with_header: bool = False) -> None + .. py:method:: write_csv(path: str | pathlib.Path, with_header: bool = False, write_options: DataFrameWriteOptions | None = None) -> None Execute the :py:class:`DataFrame` and write the results to a CSV file. :param path: Path of the CSV file to write. :param with_header: If true, output the CSV header row. + :param write_options: Options that impact how the DataFrame is written. - .. py:method:: write_json(path: str | pathlib.Path) -> None + .. py:method:: write_json(path: str | pathlib.Path, write_options: DataFrameWriteOptions | None = None) -> None Execute the :py:class:`DataFrame` and write the results to a JSON file. :param path: Path of the JSON file to write. + :param write_options: Options that impact how the DataFrame is written. - .. py:method:: write_parquet(path: str | pathlib.Path, compression: str, compression_level: int | None = None) -> None - write_parquet(path: str | pathlib.Path, compression: Compression = Compression.ZSTD, compression_level: int | None = None) -> None - write_parquet(path: str | pathlib.Path, compression: ParquetWriterOptions, compression_level: None = None) -> None + .. py:method:: write_parquet(path: str | pathlib.Path, compression: str, compression_level: int | None = None, write_options: DataFrameWriteOptions | None = None) -> None + write_parquet(path: str | pathlib.Path, compression: Compression = Compression.ZSTD, compression_level: int | None = None, write_options: DataFrameWriteOptions | None = None) -> None + write_parquet(path: str | pathlib.Path, compression: ParquetWriterOptions, compression_level: None = None, write_options: DataFrameWriteOptions | None = None) -> None Execute the :py:class:`DataFrame` and write the results to a Parquet file. + Available compression types are: + + - "uncompressed": No compression. + - "snappy": Snappy compression. + - "gzip": Gzip compression. + - "brotli": Brotli compression. + - "lz4": LZ4 compression. + - "lz4_raw": LZ4_RAW compression. + - "zstd": Zstandard compression. + + LZO compression is not yet implemented in arrow-rs and is therefore + excluded. + :param path: Path of the Parquet file to write. :param compression: Compression type to use. Default is "ZSTD". - Available compression types are: - - "uncompressed": No compression. - - "snappy": Snappy compression. - - "gzip": Gzip compression. - - "brotli": Brotli compression. - - "lz4": LZ4 compression. - - "lz4_raw": LZ4_RAW compression. - - "zstd": Zstandard compression. - :param Note: LZO is not yet implemented in arrow-rs and is therefore excluded. :param compression_level: Compression level to use. For ZSTD, the recommended range is 1 to 22, with the default being 4. Higher levels provide better compression but slower speed. + :param write_options: Options that impact how the DataFrame is written. - .. py:method:: write_parquet_with_options(path: str | pathlib.Path, options: ParquetWriterOptions) -> None + .. py:method:: write_parquet_with_options(path: str | pathlib.Path, options: ParquetWriterOptions, write_options: DataFrameWriteOptions | None = None) -> None Execute the :py:class:`DataFrame` and write the results to a Parquet file. @@ -741,12 +791,64 @@ Module Contents :param path: Path of the Parquet file to write. :param options: Sets the writer parquet options (see `ParquetWriterOptions`). + :param write_options: Options that impact how the DataFrame is written. + + + + .. py:method:: write_table(table_name: str, write_options: DataFrameWriteOptions | None = None) -> None + + Execute the :py:class:`DataFrame` and write the results to a table. + + The table must be registered with the session to perform this operation. + Not all table providers support writing operations. See the individual + implementations for details. .. py:attribute:: df +.. py:class:: DataFrameWriteOptions(insert_operation: InsertOp | None = None, single_file_output: bool = False, partition_by: str | collections.abc.Sequence[str] | None = None, sort_by: datafusion.expr.Expr | datafusion.expr.SortExpr | collections.abc.Sequence[datafusion.expr.Expr] | collections.abc.Sequence[datafusion.expr.SortExpr] | None = None) + + Writer options for DataFrame. + + There is no guarantee the table provider supports all writer options. + See the individual implementation and documentation for details. + + Instantiate writer options for DataFrame. + + + .. py:attribute:: _raw_write_options + + +.. py:class:: InsertOp(*args, **kwds) + + Bases: :py:obj:`enum.Enum` + + + Insert operation mode. + + These modes are used by the table writing feature to define how record + batches should be written to a table. + + + .. py:attribute:: APPEND + + Appends new rows to the existing table without modifying any existing rows. + + + .. py:attribute:: OVERWRITE + + Overwrites all existing rows in the table with the new rows. + + + .. py:attribute:: REPLACE + + Replace existing rows that collide with the inserted rows. + + Replacement is typically based on a unique key or primary key. + + .. py:class:: ParquetColumnOptions(encoding: Optional[str] = None, dictionary_enabled: Optional[bool] = None, compression: Optional[str] = None, statistics_enabled: Optional[str] = None, bloom_filter_enabled: Optional[bool] = None, bloom_filter_fpp: Optional[float] = None, bloom_filter_ndv: Optional[int] = None) Parquet options for individual columns. diff --git a/_sources/autoapi/datafusion/index.rst.txt b/_sources/autoapi/datafusion/index.rst.txt index 507c6ee19..e4208b05c 100644 --- a/_sources/autoapi/datafusion/index.rst.txt +++ b/_sources/autoapi/datafusion/index.rst.txt @@ -57,9 +57,11 @@ Classes datafusion.Accumulator datafusion.AggregateUDF datafusion.Catalog + datafusion.DataFrameWriteOptions datafusion.Database datafusion.ExecutionPlan datafusion.Expr + datafusion.InsertOp datafusion.LogicalPlan datafusion.ParquetColumnOptions datafusion.ParquetWriterOptions @@ -285,7 +287,7 @@ Package Contents - .. py:method:: register_schema(name, schema) -> Schema | None + .. py:method:: register_schema(name: str, schema: Schema | SchemaProvider | SchemaProviderExportable) -> Schema | None Register a schema with this catalog. @@ -306,6 +308,19 @@ Package Contents .. py:attribute:: catalog +.. py:class:: DataFrameWriteOptions(insert_operation: InsertOp | None = None, single_file_output: bool = False, partition_by: str | collections.abc.Sequence[str] | None = None, sort_by: datafusion.expr.Expr | datafusion.expr.SortExpr | collections.abc.Sequence[datafusion.expr.Expr] | collections.abc.Sequence[datafusion.expr.SortExpr] | None = None) + + Writer options for DataFrame. + + There is no guarantee the table provider supports all writer options. + See the individual implementation and documentation for details. + + Instantiate writer options for DataFrame. + + + .. py:attribute:: _raw_write_options + + .. py:class:: Database(schema: datafusion._internal.catalog.RawSchema) Bases: :py:obj:`Schema` @@ -1224,6 +1239,34 @@ Package Contents .. py:attribute:: expr +.. py:class:: InsertOp(*args, **kwds) + + Bases: :py:obj:`enum.Enum` + + + Insert operation mode. + + These modes are used by the table writing feature to define how record + batches should be written to a table. + + + .. py:attribute:: APPEND + + Appends new rows to the existing table without modifying any existing rows. + + + .. py:attribute:: OVERWRITE + + Overwrites all existing rows in the table with the new rows. + + + .. py:attribute:: REPLACE + + Replace existing rows that collide with the inserted rows. + + Replacement is typically based on a unique key or primary key. + + .. py:class:: LogicalPlan(plan: datafusion._internal.LogicalPlan) Logical Plan. @@ -2025,11 +2068,20 @@ Package Contents .. py:attribute:: config_internal -.. py:class:: Table(table: datafusion._internal.catalog.RawTable) +.. py:class:: Table(table: Table | datafusion.context.TableProviderExportable | datafusion.DataFrame | pyarrow.dataset.Dataset) - DataFusion table. + A DataFusion table. - This constructor is not typically called by the end user. + Internally we currently support the following types of tables: + + - Tables created using built-in DataFusion methods, such as + reading from CSV or Parquet + - pyarrow datasets + - DataFusion DataFrames, which will be converted into a view + - Externally provided tables implemented with the FFI PyCapsule + interface (advanced) + + Constructor. .. py:method:: __repr__() -> str @@ -2042,10 +2094,18 @@ Package Contents :staticmethod: - Turn a pyarrow Dataset into a Table. + Turn a :mod:`pyarrow.dataset` ``Dataset`` into a :class:`Table`. + + + + .. py:attribute:: __slots__ + :value: ('_inner',) + .. py:attribute:: _inner + + .. py:property:: kind :type: str @@ -2060,9 +2120,6 @@ Package Contents Returns the schema associated with this table. - .. py:attribute:: table - - .. py:class:: TableFunction(name: str, func: Callable[[], any]) Class for performing user-defined table functions (UDTF). diff --git a/_sources/contributor-guide/ffi.rst.txt b/_sources/contributor-guide/ffi.rst.txt index e201db71e..64413866f 100644 --- a/_sources/contributor-guide/ffi.rst.txt +++ b/_sources/contributor-guide/ffi.rst.txt @@ -34,7 +34,7 @@ as performant as possible and to utilize the features of DataFusion, you may dec your source in Rust and then expose it through `PyO3 `_ as a Python library. At first glance, it may appear the best way to do this is to add the ``datafusion-python`` -crate as a dependency, provide a ``PyTable``, and then to register it with the +crate as a dependency, provide a ``PyTable``, and then to register it with the ``SessionContext``. Unfortunately, this will not work. When you produce your code as a Python library and it needs to interact with the DataFusion @@ -137,6 +137,67 @@ and you want to create a sharable FFI counterpart, you could write: let my_provider = MyTableProvider::default(); let ffi_provider = FFI_TableProvider::new(Arc::new(my_provider), false, None); +.. _ffi_pyclass_mutability: + +PyO3 class mutability guidelines +-------------------------------- + +PyO3 bindings should present immutable wrappers whenever a struct stores shared or +interior-mutable state. In practice this means that any ``#[pyclass]`` containing an +``Arc>`` or similar synchronized primitive must opt into ``#[pyclass(frozen)]`` +unless there is a compelling reason not to. + +The :mod:`datafusion` configuration helpers illustrate the preferred pattern. The +``PyConfig`` class in :file:`src/config.rs` stores an ``Arc>`` and is +explicitly frozen so callers interact with configuration state through provided methods +instead of mutating the container directly: + +.. code-block:: rust + + #[pyclass(name = "Config", module = "datafusion", subclass, frozen)] + #[derive(Clone)] + pub(crate) struct PyConfig { + config: Arc>, + } + +The same approach applies to execution contexts. ``PySessionContext`` in +:file:`src/context.rs` stays frozen even though it shares mutable state internally via +``SessionContext``. This ensures PyO3 tracks borrows correctly while Python-facing APIs +clone the inner ``SessionContext`` or return new wrappers instead of mutating the +existing instance in place: + +.. code-block:: rust + + #[pyclass(frozen, name = "SessionContext", module = "datafusion", subclass)] + #[derive(Clone)] + pub struct PySessionContext { + pub ctx: SessionContext, + } + +Occasionally a type must remain mutable—for example when PyO3 attribute setters need to +update fields directly. In these rare cases add an inline justification so reviewers and +future contributors understand why ``frozen`` is unsafe to enable. ``DataTypeMap`` in +:file:`src/common/data_type.rs` includes such a comment because PyO3 still needs to track +field updates: + +.. code-block:: rust + + // TODO: This looks like this needs pyo3 tracking so leaving unfrozen for now + #[derive(Debug, Clone)] + #[pyclass(name = "DataTypeMap", module = "datafusion.common", subclass)] + pub struct DataTypeMap { + #[pyo3(get, set)] + pub arrow_type: PyDataType, + #[pyo3(get, set)] + pub python_type: PythonType, + #[pyo3(get, set)] + pub sql_type: SqlType, + } + +When reviewers encounter a mutable ``#[pyclass]`` without a comment, they should request +an explanation or ask that ``frozen`` be added. Keeping these wrappers frozen by default +helps avoid subtle bugs stemming from PyO3's interior mutability tracking. + If you were interfacing with a library that provided the above ``FFI_TableProvider`` and you needed to turn it back into an ``TableProvider``, you can turn it into a ``ForeignTableProvider`` with implements the ``TableProvider`` trait. diff --git a/_sources/contributor-guide/introduction.rst.txt b/_sources/contributor-guide/introduction.rst.txt index 6cb05c62d..33c2b274c 100644 --- a/_sources/contributor-guide/introduction.rst.txt +++ b/_sources/contributor-guide/introduction.rst.txt @@ -26,6 +26,10 @@ We welcome and encourage contributions of all kinds, such as: In addition to submitting new PRs, we have a healthy tradition of community members reviewing each other’s PRs. Doing so is a great way to help the community as well as get more familiar with Rust and the relevant codebases. +Before opening a pull request that touches PyO3 bindings, please review the +:ref:`PyO3 class mutability guidelines ` so you can flag missing +``#[pyclass(frozen)]`` annotations during development and review. + How to develop -------------- diff --git a/_sources/user-guide/data-sources.rst.txt b/_sources/user-guide/data-sources.rst.txt index a9b119b93..26f1303c4 100644 --- a/_sources/user-guide/data-sources.rst.txt +++ b/_sources/user-guide/data-sources.rst.txt @@ -154,11 +154,11 @@ as Delta Lake. This will require a recent version of from deltalake import DeltaTable delta_table = DeltaTable("path_to_table") - ctx.register_table_provider("my_delta_table", delta_table) + ctx.register_table("my_delta_table", delta_table) df = ctx.table("my_delta_table") df.show() -On older versions of ``deltalake`` (prior to 0.22) you can use the +On older versions of ``deltalake`` (prior to 0.22) you can use the `Arrow DataSet `_ interface to import to DataFusion, but this does not support features such as filter push down which can lead to a significant performance difference. diff --git a/_sources/user-guide/io/table_provider.rst.txt b/_sources/user-guide/io/table_provider.rst.txt index bd1d6b80f..29e5d9880 100644 --- a/_sources/user-guide/io/table_provider.rst.txt +++ b/_sources/user-guide/io/table_provider.rst.txt @@ -37,22 +37,26 @@ A complete example can be found in the `examples folder , ) -> PyResult> { - let name = CString::new("datafusion_table_provider").unwrap(); + let name = cr"datafusion_table_provider".into(); - let provider = Arc::new(self.clone()) - .map_err(|e| PyRuntimeError::new_err(e.to_string()))?; - let provider = FFI_TableProvider::new(Arc::new(provider), false); + let provider = Arc::new(self.clone()); + let provider = FFI_TableProvider::new(provider, false, None); PyCapsule::new_bound(py, provider, Some(name.clone())) } } -Once you have this library available, in python you can register your table provider -to the ``SessionContext``. +Once you have this library available, you can construct a +:py:class:`~datafusion.Table` in Python and register it with the +``SessionContext``. .. code-block:: python + from datafusion import SessionContext, Table + + ctx = SessionContext() provider = MyTableProvider() - ctx.register_table_provider("my_table", provider) - ctx.table("my_table").show() + ctx.register_table("capsule_table", provider) + + ctx.table("capsule_table").show() diff --git a/autoapi/datafusion/catalog/index.html b/autoapi/datafusion/catalog/index.html index 64d0e67c9..862ded08f 100644 --- a/autoapi/datafusion/catalog/index.html +++ b/autoapi/datafusion/catalog/index.html @@ -732,28 +732,37 @@

  • - + - Table.kind + Table.__slots__
  • - + - Table.schema + Table._inner + + + +
    • +
  • + + + + Table.kind
  • - + - Table.table + Table.schema @@ -803,7 +812,7 @@

    Classes

    •  - +
    -
  • encoding (datafusion.dataframe.ParquetColumnOptions attribute), [1] +
  • encoding (datafusion.dataframe.ParquetColumnOptions attribute)
  • end() (datafusion.expr.CaseBuilder method)
  • ends_with() (in module datafusion.functions) +
    • +
  • ensure_expr() (in module datafusion.expr) +
    • +
  • ensure_expr_list() (in module datafusion.expr)
  • evaluate() (datafusion.Accumulator method) @@ -1830,6 +1832,8 @@

    E

  • expr() (datafusion.expr.SortExpr method) +
    • +
  • EXPR_TYPE_ERROR (in module datafusion.expr)
  • Extension (in module datafusion.expr)
    • @@ -2381,24 +2385,24 @@

    M

  • max_memory_bytes (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
    • -
  • max_row_group_size (datafusion.dataframe.ParquetWriterOptions attribute), [1] +
  • max_row_group_size (datafusion.dataframe.ParquetWriterOptions attribute)
  • max_width (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
    • -
  • maximum_buffered_record_batches_per_stream (datafusion.dataframe.ParquetWriterOptions attribute), [1] +
  • maximum_buffered_record_batches_per_stream (datafusion.dataframe.ParquetWriterOptions attribute)
    • -
  • maximum_parallel_row_group_writers (datafusion.dataframe.ParquetWriterOptions attribute), [1] +
  • maximum_parallel_row_group_writers (datafusion.dataframe.ParquetWriterOptions attribute)
  • md5() (datafusion.Expr method) @@ -3016,10 +3020,10 @@

    S

  • (in module datafusion.functions)
    • -
  • skip_arrow_metadata (datafusion.dataframe.ParquetWriterOptions attribute), [1] +
  • skip_arrow_metadata (datafusion.dataframe.ParquetWriterOptions attribute)
  • SNAPPY (datafusion.dataframe.Compression attribute) @@ -3035,6 +3039,8 @@

    S

  • SortExpr (class in datafusion.expr) +
    • +
  • SortKey (in module datafusion.expr)
  • split_part() (in module datafusion.functions)
    • @@ -3068,20 +3074,20 @@

    S

  • (datafusion.user_defined.Accumulator method)
    • -
  • statistics_enabled (datafusion.dataframe.ParquetColumnOptions attribute), [1] +
  • statistics_enabled (datafusion.dataframe.ParquetColumnOptions attribute)
    • -
  • statistics_truncate_length (datafusion.dataframe.ParquetWriterOptions attribute), [1] +
  • statistics_truncate_length (datafusion.dataframe.ParquetWriterOptions attribute)
  • stddev() (in module datafusion.functions) @@ -3590,10 +3596,10 @@

    W

  • (datafusion.RuntimeEnvBuilder method)
    • -
  • write_batch_size (datafusion.dataframe.ParquetWriterOptions attribute), [1] +
  • write_batch_size (datafusion.dataframe.ParquetWriterOptions attribute)
  • write_csv() (datafusion.dataframe.DataFrame method) @@ -3604,10 +3610,10 @@

    W

  • write_parquet_with_options() (datafusion.dataframe.DataFrame method)
    • -
  • writer_version (datafusion.dataframe.ParquetWriterOptions attribute), [1] +
  • writer_version (datafusion.dataframe.ParquetWriterOptions attribute)

    • Abstract class for defining a Python based Schema Provider.

    Table

    DataFusion table.

    A DataFusion table.
    @@ -847,7 +856,7 @@

    Module Contents
    -register_schema(name, schema) → Schema | None
    +register_schema(name: str, schema: Schema | SchemaProvider | SchemaProviderExportable) → Schema | None

    Register a schema with this catalog.

    @@ -944,8 +953,8 @@

    Module Contents
    -register_table(name, table) → None
    -

    Register a table provider in this schema.

    +register_table(name: str, table: Table | datafusion.context.TableProviderExportable | datafusion.DataFrame | pyarrow.dataset.Dataset) → None +

    Register a table in this schema.

    @@ -974,7 +983,7 @@

    Module Contents
    -deregister_table(name, cascade: bool) → None
    +deregister_table(name: str, cascade: bool) → None

    Remove a table from this schema.

    This method is optional. If your schema provides a fixed list of tables, you do not need to implement this method.

    @@ -989,8 +998,8 @@

    Module Contents
    -register_table(name: str, table: Table) → None
    -

    Add a table from this schema.

    +register_table(name: str, table: Table | datafusion.context.TableProviderExportable | Any) → None +

    Add a table to this schema.

    This method is optional. If your schema provides a fixed list of tables, you do not need to implement this method.

    @@ -1017,9 +1026,18 @@

    Module Contents
    -class datafusion.catalog.Table(table: datafusion._internal.catalog.RawTable)
    -

    DataFusion table.

    -

    This constructor is not typically called by the end user.

    +class datafusion.catalog.Table(table: Table | datafusion.context.TableProviderExportable | datafusion.DataFrame | pyarrow.dataset.Dataset) +

    A DataFusion table.

    +

    Internally we currently support the following types of tables:

    +
      +

    • Tables created using built-in DataFusion methods, such as +reading from CSV or Parquet

      • +

    • pyarrow datasets

      • +

    • DataFusion DataFrames, which will be converted into a view

      • +

    • Externally provided tables implemented with the FFI PyCapsule +interface (advanced)

      • +
    +

    Constructor.

    __repr__() → str
    @@ -1029,9 +1047,19 @@

    Module Contents
    static from_dataset(dataset: pyarrow.dataset.Dataset) → Table
    -

    Turn a pyarrow Dataset into a Table.

    +

    Turn a pyarrow.dataset Dataset into a Table.

    +
    +
    +__slots__ = ('_inner',)
    +
    + +
    +
    +_inner
    +
    +
    property kind: str
    @@ -1044,11 +1072,6 @@

    Module Contents -
    -table
    -

    -
    diff --git a/autoapi/datafusion/context/index.html b/autoapi/datafusion/context/index.html index 6ab8fbc0c..cfd76c86e 100644 --- a/autoapi/datafusion/context/index.html +++ b/autoapi/datafusion/context/index.html @@ -2039,11 +2039,8 @@

    Module Contents
    -read_table(table: datafusion.catalog.Table) → datafusion.dataframe.DataFrame
    +read_table(table: datafusion.catalog.Table | TableProviderExportable | datafusion.dataframe.DataFrame | pyarrow.dataset.Dataset) → datafusion.dataframe.DataFrame

    Creates a DataFrame from a table.

    -

    For a Table such as a -ListingTable, create a -DataFrame.

    @@ -2218,14 +2215,15 @@

    Module Contents
    -register_table(name: str, table: datafusion.catalog.Table) → None
    -

    Register a :py:class: ~datafusion.catalog.Table as a table.

    -

    The registered table can be referenced from SQL statement executed against.

    +register_table(name: str, table: datafusion.catalog.Table | TableProviderExportable | datafusion.dataframe.DataFrame | pyarrow.dataset.Dataset) → None +

    Register a Table with this context.

    +

    The registered table can be referenced from SQL statements executed against +this context.

    Parameters:

    • name – Name of the resultant table.

      • -

    • table – DataFusion table to add to the session context.

      • +

    • table – Any object that can be converted into a Table.

    @@ -2233,10 +2231,9 @@

    Module Contents
    -register_table_provider(name: str, provider: TableProviderExportable) → None
    +register_table_provider(name: str, provider: datafusion.catalog.Table | TableProviderExportable | datafusion.dataframe.DataFrame | pyarrow.dataset.Dataset) → None

    Register a table provider.

    -

    This table provider must have a method called __datafusion_table_provider__ -which returns a PyCapsule that exposes a FFI_TableProvider.

    +

    Deprecated: use register_table() instead.

    @@ -2266,7 +2263,7 @@

    Module Contents
    register_view(name: str, df: datafusion.dataframe.DataFrame) → None
    -

    Register a :py:class: ~datafusion.detaframe.DataFrame as a view.

    +

    Register a DataFrame as a view.

    Parameters:

    • +
  • + + + + DataFrameWriteOptions + + + + +
    • +
  • + + + + InsertOp + + + + +
  • @@ -1308,6 +1384,12 @@

    Classes

    DataFrame

    Two dimensional table representation of data.

    +

    DataFrameWriteOptions

    +

    Writer options for DataFrame.

    + +

    InsertOp

    +

    Insert operation mode.

    +

    ParquetColumnOptions

    Parquet options for individual columns.

    @@ -1568,14 +1650,23 @@

    Module Contents drop(*columns: str) → DataFrame

    Drop arbitrary amount of columns.

    +

    Column names are case-sensitive and do not require double quotes like +other operations such as select. Leading and trailing double quotes +are allowed and will be automatically stripped if present.

    Parameters:
    -

    columns – Column names to drop from the dataframe.

    +

    columns – Column names to drop from the dataframe. Both column_name +and "column_name" are accepted.

    Returns:

    DataFrame with those columns removed in the projection.

    +

    Example Usage:

    +
    df.drop('ID_For_Students')      # Works
+df.drop('"ID_For_Students"')    # Also works (quotes stripped)
+
    +
    @@ -1727,8 +1818,18 @@

    Module Contents
    -into_view() → pyarrow.Table
    -

    Convert DataFrame as a ViewTable which can be used in register_table.

    +into_view() → datafusion.catalog.Table +

    Convert DataFrame into a Table.

    +

    Examples

    +
    >>> from datafusion import SessionContext
+>>> ctx = SessionContext()
+>>> df = ctx.sql("SELECT 1 AS value")
+>>> view = df.into_view()
+>>> ctx.register_table("values_view", view)
+>>> df.collect()  # The DataFrame is still usable
+>>> ctx.sql("SELECT value FROM values_view").collect()
+
    +

    @@ -1824,6 +1925,30 @@

    Module Contents +
    +parse_sql_expr(expr: str) → datafusion.expr.Expr
    +

    Creates logical expression from a SQL query text.

    +

    The expression is created and processed against the current schema.

    +

    Example:

    +
    from datafusion import col, lit
+df.parse_sql_expr("a > 1")
+
+should produce:
+
+col("a") > lit(1)
+
    +
    +
    +
    Parameters:
    +

    expr – Expression string to be converted to datafusion expression

    +
    +
    Returns:
    +

    Logical expression .

    +
    +
    +

    +
    repartition(num: int) → DataFrame
    @@ -2159,13 +2284,14 @@

    Module Contents
    -write_csv(path: str | pathlib.Path, with_header: bool = False) → None
    +write_csv(path: str | pathlib.Path, with_header: bool = False, write_options: DataFrameWriteOptions | None = None) → None

    Execute the DataFrame and write the results to a CSV file.

    Parameters:

    • path – Path of the CSV file to write.

    • with_header – If true, output the CSV header row.

      • +

    • write_options – Options that impact how the DataFrame is written.

    @@ -2173,40 +2299,47 @@

    Module Contents
    -write_json(path: str | pathlib.Path) → None
    +write_json(path: str | pathlib.Path, write_options: DataFrameWriteOptions | None = None) → None

    Execute the DataFrame and write the results to a JSON file.

    Parameters:
    -

    path – Path of the JSON file to write.

    +
      +

    • path – Path of the JSON file to write.

      • +

    • write_options – Options that impact how the DataFrame is written.

      • +

    -write_parquet(path: str | pathlib.Path, compression: str, compression_level: int | None = None) → None
    +write_parquet(path: str | pathlib.Path, compression: str, compression_level: int | None = None, write_options: DataFrameWriteOptions | None = None) → None
    -write_parquet(path: str | pathlib.Path, compression: Compression = Compression.ZSTD, compression_level: int | None = None) → None
    +write_parquet(path: str | pathlib.Path, compression: Compression = Compression.ZSTD, compression_level: int | None = None, write_options: DataFrameWriteOptions | None = None) → None
    -write_parquet(path: str | pathlib.Path, compression: ParquetWriterOptions, compression_level: None = None) → None
    +write_parquet(path: str | pathlib.Path, compression: ParquetWriterOptions, compression_level: None = None, write_options: DataFrameWriteOptions | None = None) → None

    Execute the DataFrame and write the results to a Parquet file.

    +

    Available compression types are:

    +
      +

    • “uncompressed”: No compression.

      • +

    • “snappy”: Snappy compression.

      • +

    • “gzip”: Gzip compression.

      • +

    • “brotli”: Brotli compression.

      • +

    • “lz4”: LZ4 compression.

      • +

    • “lz4_raw”: LZ4_RAW compression.

      • +

    • “zstd”: Zstandard compression.

      • +
    +

    LZO compression is not yet implemented in arrow-rs and is therefore +excluded.

    Parameters:

    • path – Path of the Parquet file to write.

      • -

    • compression – Compression type to use. Default is “ZSTD”. -Available compression types are: -- “uncompressed”: No compression. -- “snappy”: Snappy compression. -- “gzip”: Gzip compression. -- “brotli”: Brotli compression. -- “lz4”: LZ4 compression. -- “lz4_raw”: LZ4_RAW compression. -- “zstd”: Zstandard compression.

      • -

    • Note – LZO is not yet implemented in arrow-rs and is therefore excluded.

      • +

    • compression – Compression type to use. Default is “ZSTD”.

    • compression_level – Compression level to use. For ZSTD, the recommended range is 1 to 22, with the default being 4. Higher levels provide better compression but slower speed.

      • +

    • write_options – Options that impact how the DataFrame is written.

    @@ -2214,7 +2347,7 @@

    Module Contents
    -write_parquet_with_options(path: str | pathlib.Path, options: ParquetWriterOptions) → None
    +write_parquet_with_options(path: str | pathlib.Path, options: ParquetWriterOptions, write_options: DataFrameWriteOptions | None = None) → None

    Execute the DataFrame and write the results to a Parquet file.

    Allows advanced writer options to be set with ParquetWriterOptions.

    @@ -2222,11 +2355,21 @@

    Module Contents

    • path – Path of the Parquet file to write.

    • options – Sets the writer parquet options (see ParquetWriterOptions).

      • +

    • write_options – Options that impact how the DataFrame is written.

    +
    +
    +write_table(table_name: str, write_options: DataFrameWriteOptions | None = None) → None
    +

    Execute the DataFrame and write the results to a table.

    +

    The table must be registered with the session to perform this operation. +Not all table providers support writing operations. See the individual +implementations for details.

    +
    +
    df
    @@ -2234,6 +2377,48 @@

    Module Contents +
    +class datafusion.dataframe.DataFrameWriteOptions(insert_operation: InsertOp | None = None, single_file_output: bool = False, partition_by: str | collections.abc.Sequence[str] | None = None, sort_by: datafusion.expr.Expr | datafusion.expr.SortExpr | collections.abc.Sequence[datafusion.expr.Expr] | collections.abc.Sequence[datafusion.expr.SortExpr] | None = None)
    +

    Writer options for DataFrame.

    +

    There is no guarantee the table provider supports all writer options. +See the individual implementation and documentation for details.

    +

    Instantiate writer options for DataFrame.

    +
    +
    +_raw_write_options
    +
    + +

    + +
    +
    +class datafusion.dataframe.InsertOp(*args, **kwds)
    +

    Bases: enum.Enum

    +

    Insert operation mode.

    +

    These modes are used by the table writing feature to define how record +batches should be written to a table.

    +
    +
    +APPEND
    +

    Appends new rows to the existing table without modifying any existing rows.

    +
    + +
    +
    +OVERWRITE
    +

    Overwrites all existing rows in the table with the new rows.

    +
    + +
    +
    +REPLACE
    +

    Replace existing rows that collide with the inserted rows.

    +

    Replacement is typically based on a unique key or primary key.

    +
    + +
    +
    class datafusion.dataframe.ParquetColumnOptions(encoding: str | None = None, dictionary_enabled: bool | None = None, compression: str | None = None, statistics_enabled: str | None = None, bloom_filter_enabled: bool | None = None, bloom_filter_fpp: float | None = None, bloom_filter_ndv: int | None = None)
    diff --git a/autoapi/datafusion/index.html b/autoapi/datafusion/index.html index a6b550708..fab8b5105 100644 --- a/autoapi/datafusion/index.html +++ b/autoapi/datafusion/index.html @@ -627,6 +627,26 @@

    • +
  • + + + + DataFrameWriteOptions + + + + +
  • @@ -1819,6 +1839,44 @@
    • +
  • + + + + InsertOp + + + + +
  • @@ -2630,28 +2688,37 @@
  • - + - Table.kind + Table.__slots__
  • - + - Table.schema + Table._inner
  • - + - Table.table + Table.kind + + + +
    • +
  • + + + + Table.schema @@ -3088,15 +3155,21 @@

    Classes

    Catalog

    DataFusion data catalog.

    -

    Database

    +

    DataFrameWriteOptions

    +

    Writer options for DataFrame.

    + +

    Database

    See Schema.

    -

    ExecutionPlan

    +

    ExecutionPlan

    Represent nodes in the DataFusion Physical Plan.

    -

    Expr

    +

    Expr

    Expression object.

    +

    InsertOp

    +

    Insert operation mode.

    +

    LogicalPlan

    Logical Plan.

    @@ -3125,7 +3198,7 @@

    Classes

    Session configuration options.

    Table

    -

    DataFusion table.

    +

    A DataFusion table.

    TableFunction

    Class for performing user-defined table functions (UDTF).

    @@ -3355,7 +3428,7 @@

    Package Contents
    -register_schema(name, schema) → Schema | None
    +register_schema(name: str, schema: Schema | SchemaProvider | SchemaProviderExportable) → Schema | None

    Register a schema with this catalog.

    @@ -3378,6 +3451,20 @@

    Package Contents +
    +class datafusion.DataFrameWriteOptions(insert_operation: InsertOp | None = None, single_file_output: bool = False, partition_by: str | collections.abc.Sequence[str] | None = None, sort_by: datafusion.expr.Expr | datafusion.expr.SortExpr | collections.abc.Sequence[datafusion.expr.Expr] | collections.abc.Sequence[datafusion.expr.SortExpr] | None = None)
    +

    Writer options for DataFrame.

    +

    There is no guarantee the table provider supports all writer options. +See the individual implementation and documentation for details.

    +

    Instantiate writer options for DataFrame.

    +
    +
    +_raw_write_options
    +
    + +
    +
    class datafusion.Database(schema: datafusion._internal.catalog.RawSchema)
    @@ -4299,6 +4386,34 @@

    Returns:

    +
    +
    +class datafusion.InsertOp(*args, **kwds)
    +

    Bases: enum.Enum

    +

    Insert operation mode.

    +

    These modes are used by the table writing feature to define how record +batches should be written to a table.

    +
    +
    +APPEND
    +

    Appends new rows to the existing table without modifying any existing rows.

    +
    + +
    +
    +OVERWRITE
    +

    Overwrites all existing rows in the table with the new rows.

    +
    + +
    +
    +REPLACE
    +

    Replace existing rows that collide with the inserted rows.

    +

    Replacement is typically based on a unique key or primary key.

    +
    + +
    +
    class datafusion.LogicalPlan(plan: datafusion._internal.LogicalPlan)
    @@ -5196,9 +5311,18 @@

    Returns:
    -class datafusion.Table(table: datafusion._internal.catalog.RawTable)
    -

    DataFusion table.

    -

    This constructor is not typically called by the end user.

    +class datafusion.Table(table: Table | datafusion.context.TableProviderExportable | datafusion.DataFrame | pyarrow.dataset.Dataset) +

    A DataFusion table.

    +

    Internally we currently support the following types of tables:

    +
      +

    • Tables created using built-in DataFusion methods, such as +reading from CSV or Parquet

      • +

    • pyarrow datasets

      • +

    • DataFusion DataFrames, which will be converted into a view

      • +

    • Externally provided tables implemented with the FFI PyCapsule +interface (advanced)

      • +
    +

    Constructor.

    __repr__() → str
    @@ -5208,9 +5332,19 @@

    Returns:
    static from_dataset(dataset: pyarrow.dataset.Dataset) → Table
    -

    Turn a pyarrow Dataset into a Table.

    +

    Turn a pyarrow.dataset Dataset into a Table.

    +
    +
    +__slots__ = ('_inner',)
    +
    + +
    +
    +_inner
    +
    +
    property kind: str
    @@ -5223,11 +5357,6 @@

    Returns:

    Returns the schema associated with this table.

    -
    -
    -table
    -
    -
    diff --git a/contributor-guide/ffi.html b/contributor-guide/ffi.html index 0439f3231..1c61dffea 100644 --- a/contributor-guide/ffi.html +++ b/contributor-guide/ffi.html @@ -427,6 +427,11 @@ Implementation Details

    • +
  • + + PyO3 class mutability guidelines + +
  • Alternative Approach @@ -560,6 +565,57 @@

    Implementation Detailslet ffi_provider = FFI_TableProvider::new(Arc::new(my_provider), false, None); + +
    +

    PyO3 class mutability guidelines

    +

    PyO3 bindings should present immutable wrappers whenever a struct stores shared or +interior-mutable state. In practice this means that any #[pyclass] containing an +Arc<RwLock<_>> or similar synchronized primitive must opt into #[pyclass(frozen)] +unless there is a compelling reason not to.

    +

    The datafusion configuration helpers illustrate the preferred pattern. The +PyConfig class in src/config.rs stores an Arc<RwLock<ConfigOptions>> and is +explicitly frozen so callers interact with configuration state through provided methods +instead of mutating the container directly:

    +
    #[pyclass(name = "Config", module = "datafusion", subclass, frozen)]
+#[derive(Clone)]
+pub(crate) struct PyConfig {
+    config: Arc<RwLock<ConfigOptions>>,
+}
+
    +
    +

    The same approach applies to execution contexts. PySessionContext in +src/context.rs stays frozen even though it shares mutable state internally via +SessionContext. This ensures PyO3 tracks borrows correctly while Python-facing APIs +clone the inner SessionContext or return new wrappers instead of mutating the +existing instance in place:

    +
    #[pyclass(frozen, name = "SessionContext", module = "datafusion", subclass)]
+#[derive(Clone)]
+pub struct PySessionContext {
+    pub ctx: SessionContext,
+}
+
    +
    +

    Occasionally a type must remain mutable—for example when PyO3 attribute setters need to +update fields directly. In these rare cases add an inline justification so reviewers and +future contributors understand why frozen is unsafe to enable. DataTypeMap in +src/common/data_type.rs includes such a comment because PyO3 still needs to track +field updates:

    +
    // TODO: This looks like this needs pyo3 tracking so leaving unfrozen for now
+#[derive(Debug, Clone)]
+#[pyclass(name = "DataTypeMap", module = "datafusion.common", subclass)]
+pub struct DataTypeMap {
+    #[pyo3(get, set)]
+    pub arrow_type: PyDataType,
+    #[pyo3(get, set)]
+    pub python_type: PythonType,
+    #[pyo3(get, set)]
+    pub sql_type: SqlType,
+}
+
    +
    +

    When reviewers encounter a mutable #[pyclass] without a comment, they should request +an explanation or ask that frozen be added. Keeping these wrappers frozen by default +helps avoid subtle bugs stemming from PyO3’s interior mutability tracking.

    If you were interfacing with a library that provided the above FFI_TableProvider and you needed to turn it back into an TableProvider, you can turn it into a ForeignTableProvider with implements the TableProvider trait.

    diff --git a/contributor-guide/introduction.html b/contributor-guide/introduction.html index 37db30084..255f40973 100644 --- a/contributor-guide/introduction.html +++ b/contributor-guide/introduction.html @@ -463,6 +463,9 @@

    IntroductionPyO3 class mutability guidelines so you can flag missing +#[pyclass(frozen)] annotations during development and review.

    How to develop

    This assumes that you have rust and cargo installed. We use the workflow recommended by diff --git a/genindex.html b/genindex.html index ed00262d7..b07a6ea90 100644 --- a/genindex.html +++ b/genindex.html @@ -679,6 +679,12 @@

    _

    • +
  • __slots__ (datafusion.catalog.Table attribute) + +
  • __str__() (datafusion.user_defined.Volatility method) @@ -757,6 +763,12 @@

    _

  • _get_javascript() (datafusion.dataframe_formatter.DataFrameHtmlFormatter method)
    • +
  • _inner (datafusion.catalog.Table attribute) + +
  • _normalize_input_types() (datafusion.user_defined.WindowUDF static method)
      @@ -783,6 +795,12 @@

      _

  • _raw_schema (datafusion.catalog.Schema attribute)
    • +
  • _raw_write_options (datafusion.dataframe.DataFrameWriteOptions attribute) + +
  • _refresh_formatter_reference() (in module datafusion.dataframe_formatter)
  • _repr_html_() (datafusion.dataframe.DataFrame method) @@ -895,6 +913,12 @@

    A

  • Analyze (in module datafusion.expr)
    • +
  • APPEND (datafusion.dataframe.InsertOp attribute) + +
  • approx_distinct() (in module datafusion.functions)
  • approx_median() (in module datafusion.functions) @@ -952,11 +976,11 @@

    A

  • array_indexof() (in module datafusion.functions)
  • array_intersect() (in module datafusion.functions) -
    • -
  • array_join() (in module datafusion.functions)
    • - +
  • overlay() (in module datafusion.functions)
    • +
  • OVERWRITE (datafusion.dataframe.InsertOp attribute) + +
  • owner_name() (datafusion.catalog.SchemaProvider method)
    • @@ -2596,6 +2638,8 @@

    P

  • (class in datafusion.dataframe)
    • +
  • parse_sql_expr() (datafusion.dataframe.DataFrame method) +
  • partition_by() (datafusion.Expr method)
      @@ -2808,6 +2852,12 @@

      R

    • repeat() (in module datafusion.functions)
      • +
    • REPLACE (datafusion.dataframe.InsertOp attribute) + +
    • replace() (in module datafusion.functions)
    • repr_rows (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute) @@ -3136,12 +3186,6 @@

      T

      • -
    • table (datafusion.catalog.Table attribute) - -
    • table() (datafusion.catalog.Schema method) @@ -3609,6 +3653,8 @@

      W

    • write_parquet() (datafusion.dataframe.DataFrame method)
    • write_parquet_with_options() (datafusion.dataframe.DataFrame method) +
      • +
    • write_table() (datafusion.dataframe.DataFrame method)
    • writer_version (datafusion.dataframe.ParquetWriterOptions attribute) diff --git a/objects.inv b/objects.inv index 827143a5eafab807d6c5bf70080ef7a6496196d2..0b9573a421130024304493ebf10bf8f7a1b5bce8 100644 GIT binary patch delta 8705 zcmV+cBL3ZqL%u|ihkspn+cwh2@AWBsPM=$=+jP5U&)zw<({+w> zF>8PRk@1YKr%PSrKlo&q|95dY*(R7?rD;`EInhE|R+5AkP(bQ#( z>ZQnHXa$uEAe7QzxvI)6j7l%qtS1@VcAPFqG)`s zGHTv9Q<};|rGHCWka%Q43n4d2=Xv9JoD@{WW5AyimXkz2=FPjOHb3_A;QP&=@1)7Y zAChVMq15K08r^&j(x!9bVm)P`NLs9)lN(wEYh<_!Kn%RFPsi=HL4ZoyPZ{omO z#AmdW5f!?WrXG_li>t<-!XYU18vtZMK_I5gX#qjf01(DkroI7ya)_6cL*&E^iy$af z4nW}$Z$(G|h-{l<#7CeeaVS#sm(F8Yx=f1_g4EWX=tpboPc*41{%DY@W+enFuZAs}&Mk6T8V-ZUt zVM^PQNNQ)?fN(OFAo8l71yInRZN&WW9&tTGUIUv2BW5GQg2YEcx$fLWinvy&- zy-W;;xJ9x^W^7%|#p0*G#53MRBc7wX(Hy|GFS1`E3AT?(w4_8AG z9XyM*C&VhcoVJTr(YYx%=2o6q|DxE>m474|BRsaJkkq^%6`dEl_Rc$YDUa|>f%0^; znP7Q#z9kj|&|o{R3$dgndGqG40FYn)77zLP?*KXZ<)_$gS+NDLqKhbcJ`7+wOo`~J z4fQP^VQM^IBrx_w`~)As{GJxclCI++D`EzR(cepe4y9eOiC|P^8U2;4UkF6c_J3@C 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(in module datafusion.functions)": [[5, "datafusion.functions.list_slice", false]], "list_sort() (in module datafusion.functions)": [[5, "datafusion.functions.list_sort", false]], "list_to_string() (in module datafusion.functions)": [[5, "datafusion.functions.list_to_string", false]], "list_union() (in module datafusion.functions)": [[5, "datafusion.functions.list_union", false]], "lit() (in module datafusion)": [[7, "datafusion.lit", false]], "literal (in module datafusion.expr)": [[4, "datafusion.expr.Literal", false]], "literal() (datafusion.expr static method)": [[7, "datafusion.Expr.literal", false]], "literal() (datafusion.expr.expr static method)": [[4, "datafusion.expr.Expr.literal", false]], "literal() (in module datafusion)": [[7, "datafusion.literal", false]], "literal_with_metadata() (datafusion.expr static method)": [[7, "datafusion.Expr.literal_with_metadata", false]], "literal_with_metadata() (datafusion.expr.expr static method)": [[4, 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"max_memory_bytes (datafusion.dataframe_formatter.dataframehtmlformatter attribute)": [[3, "datafusion.dataframe_formatter.DataFrameHtmlFormatter.max_memory_bytes", false]], "max_row_group_size (datafusion.dataframe.parquetwriteroptions attribute)": [[2, "datafusion.dataframe.ParquetWriterOptions.max_row_group_size", false]], "max_row_group_size (datafusion.parquetwriteroptions attribute)": [[7, "datafusion.ParquetWriterOptions.max_row_group_size", false]], "max_width (datafusion.dataframe_formatter.dataframehtmlformatter attribute)": [[3, "datafusion.dataframe_formatter.DataFrameHtmlFormatter.max_width", false]], "maximum_buffered_record_batches_per_stream (datafusion.dataframe.parquetwriteroptions attribute)": [[2, "datafusion.dataframe.ParquetWriterOptions.maximum_buffered_record_batches_per_stream", false]], "maximum_buffered_record_batches_per_stream (datafusion.parquetwriteroptions attribute)": [[7, "datafusion.ParquetWriterOptions.maximum_buffered_record_batches_per_stream", false]], "maximum_parallel_row_group_writers (datafusion.dataframe.parquetwriteroptions attribute)": [[2, "datafusion.dataframe.ParquetWriterOptions.maximum_parallel_row_group_writers", false]], "maximum_parallel_row_group_writers (datafusion.parquetwriteroptions attribute)": [[7, "datafusion.ParquetWriterOptions.maximum_parallel_row_group_writers", false]], "md5() (datafusion.expr method)": [[7, "datafusion.Expr.md5", false]], "md5() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.md5", false]], "md5() (in module datafusion.functions)": [[5, "datafusion.functions.md5", false]], "mean() (in module datafusion.functions)": [[5, "datafusion.functions.mean", false]], "median() (in module datafusion.functions)": [[5, "datafusion.functions.median", false]], "memoize() (datafusion.user_defined.windowevaluator method)": [[17, "datafusion.user_defined.WindowEvaluator.memoize", false]], "memory_catalog() (datafusion.catalog static method)": [[7, "datafusion.Catalog.memory_catalog", false]], "memory_catalog() (datafusion.catalog.catalog static method)": [[0, "datafusion.catalog.Catalog.memory_catalog", false]], "memory_schema() (datafusion.catalog.schema static method)": [[0, "datafusion.catalog.Schema.memory_schema", false]], "merge() (datafusion.accumulator method)": [[7, "datafusion.Accumulator.merge", false]], "merge() (datafusion.user_defined.accumulator method)": [[17, "datafusion.user_defined.Accumulator.merge", false]], "microsoftazure (in module datafusion.object_store)": [[12, "datafusion.object_store.MicrosoftAzure", false]], "min() (in module datafusion.functions)": [[5, "datafusion.functions.min", false]], "min_rows_display (datafusion.dataframe_formatter.dataframehtmlformatter attribute)": [[3, "datafusion.dataframe_formatter.DataFrameHtmlFormatter.min_rows_display", false]], "module": [[0, "module-datafusion.catalog", false], [1, "module-datafusion.context", false], [2, "module-datafusion.dataframe", false], [3, 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"datafusion.catalog.Catalog.names", false]], "names() (datafusion.catalog.schema method)": [[0, "datafusion.catalog.Schema.names", false]], "nanvl() (in module datafusion.functions)": [[5, "datafusion.functions.nanvl", false]], "negative (in module datafusion.expr)": [[4, "datafusion.expr.Negative", false]], "next() (datafusion.record_batch.recordbatchstream method)": [[14, "datafusion.record_batch.RecordBatchStream.next", false]], "next() (datafusion.recordbatchstream method)": [[7, "datafusion.RecordBatchStream.next", false]], "not (in module datafusion.expr)": [[4, "datafusion.expr.Not", false]], "now() (in module datafusion.functions)": [[5, "datafusion.functions.now", false]], "nth_value() (in module datafusion.functions)": [[5, "datafusion.functions.nth_value", false]], "ntile() (in module datafusion.functions)": [[5, "datafusion.functions.ntile", false]], "null_treatment() (datafusion.expr method)": [[7, "datafusion.Expr.null_treatment", false]], "null_treatment() 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false]], "parquetcolumnoptions (class in datafusion.dataframe)": [[2, "datafusion.dataframe.ParquetColumnOptions", false]], "parquetwriteroptions (class in datafusion)": [[7, "datafusion.ParquetWriterOptions", false]], "parquetwriteroptions (class in datafusion.dataframe)": [[2, "datafusion.dataframe.ParquetWriterOptions", false]], "partition_by() (datafusion.expr method)": [[7, "datafusion.Expr.partition_by", false]], "partition_by() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.partition_by", false]], "partition_count (datafusion.executionplan property)": [[7, "datafusion.ExecutionPlan.partition_count", false]], "partition_count (datafusion.plan.executionplan property)": [[13, "datafusion.plan.ExecutionPlan.partition_count", false]], "partitioning (in module datafusion.expr)": [[4, "datafusion.expr.Partitioning", false]], "percent_rank() (in module datafusion.functions)": [[5, "datafusion.functions.percent_rank", false]], "pi() (in module datafusion.functions)": [[5, 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"coalesce() (in module datafusion.functions)": [[5, "datafusion.functions.coalesce", false]], "col (in module datafusion)": [[7, "datafusion.col", false]], "col() (in module datafusion.functions)": [[5, "datafusion.functions.col", false]], "collect() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.collect", false]], "collect_partitioned() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.collect_partitioned", false]], "column (in module datafusion)": [[7, "datafusion.column", false]], "column (in module datafusion.expr)": [[4, "datafusion.expr.Column", false]], "column() (datafusion.expr static method)": [[7, "datafusion.Expr.column", false]], "column() (datafusion.expr.expr static method)": [[4, "datafusion.expr.Expr.column", false]], "column_index_truncate_length (datafusion.dataframe.parquetwriteroptions attribute)": [[2, "datafusion.dataframe.ParquetWriterOptions.column_index_truncate_length", false]], "column_index_truncate_length (datafusion.parquetwriteroptions attribute)": [[7, "datafusion.ParquetWriterOptions.column_index_truncate_length", false]], "column_name() (datafusion.expr method)": [[7, "datafusion.Expr.column_name", false]], "column_name() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.column_name", false]], "column_specific_options (datafusion.dataframe.parquetwriteroptions attribute)": [[2, "datafusion.dataframe.ParquetWriterOptions.column_specific_options", false]], "column_specific_options (datafusion.parquetwriteroptions attribute)": [[7, "datafusion.ParquetWriterOptions.column_specific_options", false]], "compression (class in datafusion.dataframe)": [[2, "datafusion.dataframe.Compression", false]], "compression (datafusion.dataframe.parquetcolumnoptions attribute)": [[2, "datafusion.dataframe.ParquetColumnOptions.compression", false]], "compression (datafusion.parquetcolumnoptions attribute)": [[7, "datafusion.ParquetColumnOptions.compression", 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"module-datafusion.dataframe", false]], "datafusion.dataframe_formatter": [[3, "module-datafusion.dataframe_formatter", false]], "datafusion.expr": [[4, "module-datafusion.expr", false]], "datafusion.functions": [[5, "module-datafusion.functions", false]], "datafusion.html_formatter": [[6, "module-datafusion.html_formatter", false]], "datafusion.input": [[9, "module-datafusion.input", false]], "datafusion.input.base": [[8, "module-datafusion.input.base", false]], "datafusion.input.location": [[10, "module-datafusion.input.location", false]], "datafusion.io": [[11, "module-datafusion.io", false]], "datafusion.object_store": [[12, "module-datafusion.object_store", false]], "datafusion.plan": [[13, "module-datafusion.plan", false]], "datafusion.record_batch": [[14, "module-datafusion.record_batch", false]], "datafusion.substrait": [[15, "module-datafusion.substrait", false]], "datafusion.unparser": [[16, "module-datafusion.unparser", false]], "datafusion.user_defined": [[17, 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datafusion.dataframe_formatter)": [[3, "datafusion.dataframe_formatter.DefaultStyleProvider", false]], "degrees() (datafusion.expr method)": [[7, "datafusion.Expr.degrees", false]], "degrees() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.degrees", false]], "degrees() (in module datafusion.functions)": [[5, "datafusion.functions.degrees", false]], "dense_rank() (in module datafusion.functions)": [[5, "datafusion.functions.dense_rank", false]], "deregister_schema() (datafusion.catalog method)": [[7, "datafusion.Catalog.deregister_schema", false]], "deregister_schema() (datafusion.catalog.catalog method)": [[0, "datafusion.catalog.Catalog.deregister_schema", false]], "deregister_schema() (datafusion.catalog.catalogprovider method)": [[0, "datafusion.catalog.CatalogProvider.deregister_schema", false]], "deregister_table() (datafusion.catalog.schema method)": [[0, "datafusion.catalog.Schema.deregister_table", false]], "deregister_table() (datafusion.catalog.schemaprovider method)": [[0, "datafusion.catalog.SchemaProvider.deregister_table", false]], "deregister_table() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.deregister_table", false]], "describe() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.describe", false]], "describetable (in module datafusion.expr)": [[4, "datafusion.expr.DescribeTable", false]], "deserialize() (datafusion.substrait.serde static method)": [[15, "datafusion.substrait.Serde.deserialize", false]], "deserialize_bytes() (datafusion.substrait.serde static method)": [[15, "datafusion.substrait.Serde.deserialize_bytes", false]], "df (datafusion.dataframe.dataframe attribute)": [[2, "datafusion.dataframe.DataFrame.df", false]], "dfschema (in module datafusion)": [[7, "datafusion.DFSchema", false]], "dialect (class in datafusion.unparser)": [[16, "datafusion.unparser.Dialect", false]], "dialect (datafusion.unparser.dialect attribute)": [[16, 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false], [15, "module-datafusion.substrait", false], [16, "module-datafusion.unparser", false], [17, "module-datafusion.user_defined", false]], "mysql() (datafusion.unparser.dialect static method)": [[16, "datafusion.unparser.Dialect.mysql", false]], "named_struct() (in module datafusion.functions)": [[5, "datafusion.functions.named_struct", false]], "names() (datafusion.catalog method)": [[7, "datafusion.Catalog.names", false]], "names() (datafusion.catalog.catalog method)": [[0, "datafusion.catalog.Catalog.names", false]], "names() (datafusion.catalog.schema method)": [[0, "datafusion.catalog.Schema.names", false]], "nanvl() (in module datafusion.functions)": [[5, "datafusion.functions.nanvl", false]], "negative (in module datafusion.expr)": [[4, "datafusion.expr.Negative", false]], "next() (datafusion.record_batch.recordbatchstream method)": [[14, "datafusion.record_batch.RecordBatchStream.next", false]], "next() (datafusion.recordbatchstream method)": [[7, "datafusion.RecordBatchStream.next", false]], "not (in module datafusion.expr)": [[4, "datafusion.expr.Not", false]], "now() (in module datafusion.functions)": [[5, "datafusion.functions.now", false]], "nth_value() (in module datafusion.functions)": [[5, "datafusion.functions.nth_value", false]], "ntile() (in module datafusion.functions)": [[5, "datafusion.functions.ntile", false]], "null_treatment() (datafusion.expr method)": [[7, "datafusion.Expr.null_treatment", false]], "null_treatment() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.null_treatment", false]], "nullif() (in module datafusion.functions)": [[5, "datafusion.functions.nullif", false]], "nulls_first() (datafusion.expr.sortexpr method)": [[4, "datafusion.expr.SortExpr.nulls_first", false]], "nvl() (in module datafusion.functions)": [[5, "datafusion.functions.nvl", false]], "octet_length() (datafusion.expr method)": [[7, "datafusion.Expr.octet_length", false]], "octet_length() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.octet_length", false]], "octet_length() (in module datafusion.functions)": [[5, "datafusion.functions.octet_length", false]], "operatefunctionarg (in module datafusion.expr)": [[4, "datafusion.expr.OperateFunctionArg", false]], "optimized_logical_plan() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.optimized_logical_plan", false]], "options_internal (datafusion.context.sqloptions attribute)": [[1, "datafusion.context.SQLOptions.options_internal", false]], "options_internal (datafusion.sqloptions attribute)": [[7, "datafusion.SQLOptions.options_internal", false]], "order_by() (datafusion.expr method)": [[7, "datafusion.Expr.order_by", false]], "order_by() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.order_by", false]], "order_by() (in module datafusion.functions)": [[5, "datafusion.functions.order_by", false]], "otherwise() (datafusion.expr.casebuilder method)": [[4, "datafusion.expr.CaseBuilder.otherwise", false]], "over() (datafusion.expr method)": [[7, "datafusion.Expr.over", false]], "over() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.over", false]], "overlay() (in module datafusion.functions)": [[5, "datafusion.functions.overlay", false]], "overwrite (datafusion.dataframe.insertop attribute)": [[2, "datafusion.dataframe.InsertOp.OVERWRITE", false]], "overwrite (datafusion.insertop attribute)": [[7, "datafusion.InsertOp.OVERWRITE", false]], "owner_name() (datafusion.catalog.schemaprovider method)": [[0, "datafusion.catalog.SchemaProvider.owner_name", false]], "parquetcolumnoptions (class in datafusion)": [[7, "datafusion.ParquetColumnOptions", false]], "parquetcolumnoptions (class in datafusion.dataframe)": [[2, "datafusion.dataframe.ParquetColumnOptions", false]], "parquetwriteroptions (class in datafusion)": [[7, "datafusion.ParquetWriterOptions", false]], "parquetwriteroptions (class in datafusion.dataframe)": [[2, "datafusion.dataframe.ParquetWriterOptions", false]], "parse_sql_expr() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.parse_sql_expr", false]], "partition_by() (datafusion.expr method)": [[7, "datafusion.Expr.partition_by", false]], "partition_by() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.partition_by", false]], "partition_count (datafusion.executionplan property)": [[7, "datafusion.ExecutionPlan.partition_count", false]], "partition_count (datafusion.plan.executionplan property)": [[13, "datafusion.plan.ExecutionPlan.partition_count", false]], "partitioning (in module datafusion.expr)": [[4, "datafusion.expr.Partitioning", false]], "percent_rank() (in module datafusion.functions)": [[5, "datafusion.functions.percent_rank", false]], "pi() (in module datafusion.functions)": [[5, "datafusion.functions.pi", false]], "placeholder (in module datafusion.expr)": [[4, "datafusion.expr.Placeholder", false]], "plan (class in datafusion.substrait)": [[15, "datafusion.substrait.Plan", false]], "plan_internal (datafusion.substrait.plan attribute)": [[15, "datafusion.substrait.Plan.plan_internal", false]], "plan_to_sql() (datafusion.unparser.unparser method)": [[16, "datafusion.unparser.Unparser.plan_to_sql", false]], "postgres() (datafusion.unparser.dialect static method)": [[16, "datafusion.unparser.Dialect.postgres", false]], "pow() (in module datafusion.functions)": [[5, "datafusion.functions.pow", false]], "power() (in module datafusion.functions)": [[5, "datafusion.functions.power", false]], "prepare (in module datafusion.expr)": [[4, "datafusion.expr.Prepare", false]], "producer (class in datafusion.substrait)": [[15, "datafusion.substrait.Producer", false]], "projection (in module datafusion.expr)": [[4, "datafusion.expr.Projection", false]], "python_value() (datafusion.expr method)": [[7, "datafusion.Expr.python_value", false]], "python_value() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.python_value", false]], "radians() (datafusion.expr 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"datafusion.read_avro", false]], "read_avro() (in module datafusion.io)": [[11, "datafusion.io.read_avro", false]], "read_csv() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.read_csv", false]], "read_csv() (in module datafusion)": [[7, "datafusion.read_csv", false]], "read_csv() (in module datafusion.io)": [[11, "datafusion.io.read_csv", false]], "read_json() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.read_json", false]], "read_json() (in module datafusion)": [[7, "datafusion.read_json", false]], "read_json() (in module datafusion.io)": [[11, "datafusion.io.read_json", false]], "read_parquet() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.read_parquet", false]], "read_parquet() (in module datafusion)": [[7, "datafusion.read_parquet", false]], "read_parquet() (in module datafusion.io)": [[11, "datafusion.io.read_parquet", false]], "read_table() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.read_table", false]], "record_batch (datafusion.record_batch.recordbatch attribute)": [[14, "datafusion.record_batch.RecordBatch.record_batch", false]], "record_batch (datafusion.recordbatch attribute)": [[7, "datafusion.RecordBatch.record_batch", false]], "recordbatch (class in datafusion)": [[7, "datafusion.RecordBatch", false]], "recordbatch (class in datafusion.record_batch)": [[14, "datafusion.record_batch.RecordBatch", false]], "recordbatchstream (class in datafusion)": [[7, "datafusion.RecordBatchStream", false]], "recordbatchstream (class in datafusion.record_batch)": [[14, "datafusion.record_batch.RecordBatchStream", false]], "recursivequery (in module datafusion.expr)": [[4, "datafusion.expr.RecursiveQuery", false]], "regexp_count() (in module datafusion.functions)": [[5, "datafusion.functions.regexp_count", false]], "regexp_like() (in module datafusion.functions)": [[5, "datafusion.functions.regexp_like", false]], "regexp_match() (in module datafusion.functions)": [[5, "datafusion.functions.regexp_match", false]], "regexp_replace() (in module datafusion.functions)": [[5, "datafusion.functions.regexp_replace", false]], "register_avro() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_avro", false]], "register_catalog_provider() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_catalog_provider", false]], "register_csv() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_csv", false]], "register_dataset() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_dataset", false]], "register_formatter() (datafusion.dataframe_formatter.dataframehtmlformatter method)": [[3, "datafusion.dataframe_formatter.DataFrameHtmlFormatter.register_formatter", false]], "register_json() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_json", false]], "register_listing_table() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_listing_table", false]], "register_object_store() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_object_store", false]], "register_parquet() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_parquet", false]], "register_record_batches() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_record_batches", false]], "register_schema() (datafusion.catalog method)": [[7, "datafusion.Catalog.register_schema", false]], "register_schema() (datafusion.catalog.catalog method)": [[0, "datafusion.catalog.Catalog.register_schema", false]], "register_schema() (datafusion.catalog.catalogprovider method)": [[0, "datafusion.catalog.CatalogProvider.register_schema", false]], "register_table() (datafusion.catalog.schema method)": [[0, "datafusion.catalog.Schema.register_table", false]], "register_table() (datafusion.catalog.schemaprovider method)": [[0, "datafusion.catalog.SchemaProvider.register_table", false]], "register_table() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_table", false]], "register_table_provider() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_table_provider", false]], "register_udaf() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_udaf", false]], "register_udf() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_udf", false]], "register_udtf() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_udtf", false]], "register_udwf() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_udwf", false]], "register_view() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_view", false]], "regr_avgx() (in module datafusion.functions)": [[5, "datafusion.functions.regr_avgx", false]], "regr_avgy() (in module datafusion.functions)": [[5, "datafusion.functions.regr_avgy", false]], "regr_count() (in module datafusion.functions)": [[5, "datafusion.functions.regr_count", false]], "regr_intercept() (in module datafusion.functions)": [[5, "datafusion.functions.regr_intercept", false]], "regr_r2() (in module datafusion.functions)": [[5, "datafusion.functions.regr_r2", false]], "regr_slope() (in module datafusion.functions)": [[5, "datafusion.functions.regr_slope", false]], "regr_sxx() (in module datafusion.functions)": [[5, "datafusion.functions.regr_sxx", false]], "regr_sxy() (in module datafusion.functions)": [[5, "datafusion.functions.regr_sxy", false]], "regr_syy() (in module datafusion.functions)": [[5, "datafusion.functions.regr_syy", false]], "repartition (in module datafusion.expr)": [[4, "datafusion.expr.Repartition", false]], "repartition() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.repartition", false]], "repartition_by_hash() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.repartition_by_hash", false]], "repeat() (in module datafusion.functions)": [[5, "datafusion.functions.repeat", false]], "replace (datafusion.dataframe.insertop attribute)": [[2, "datafusion.dataframe.InsertOp.REPLACE", false]], "replace (datafusion.insertop attribute)": [[7, "datafusion.InsertOp.REPLACE", false]], "replace() (in module datafusion.functions)": [[5, "datafusion.functions.replace", false]], "repr_rows (datafusion.dataframe_formatter.dataframehtmlformatter attribute)": [[3, "datafusion.dataframe_formatter.DataFrameHtmlFormatter.repr_rows", false]], "reset_formatter() (in module datafusion.dataframe_formatter)": [[3, "datafusion.dataframe_formatter.reset_formatter", false]], "reverse() (datafusion.expr method)": [[7, "datafusion.Expr.reverse", false]], "reverse() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.reverse", false]], "reverse() (in module datafusion.functions)": [[5, "datafusion.functions.reverse", false]], "rex_call_operands() (datafusion.expr method)": [[7, "datafusion.Expr.rex_call_operands", false]], "rex_call_operands() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.rex_call_operands", false]], "rex_call_operator() (datafusion.expr method)": [[7, "datafusion.Expr.rex_call_operator", false]], "rex_call_operator() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.rex_call_operator", false]], "rex_type() (datafusion.expr method)": [[7, "datafusion.Expr.rex_type", false]], "rex_type() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.rex_type", false]], "right() (in module datafusion.functions)": [[5, "datafusion.functions.right", false]], "round() (in module datafusion.functions)": [[5, "datafusion.functions.round", false]], "row_number() (in module datafusion.functions)": [[5, "datafusion.functions.row_number", false]], "rpad() (in module datafusion.functions)": [[5, "datafusion.functions.rpad", false]], "rtrim() (datafusion.expr method)": [[7, "datafusion.Expr.rtrim", false]], "rtrim() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.rtrim", false]], "rtrim() (in module datafusion.functions)": [[5, "datafusion.functions.rtrim", false]], "runtimeconfig (class in datafusion.context)": [[1, "datafusion.context.RuntimeConfig", false]], "runtimeenvbuilder (class in datafusion)": [[7, "datafusion.RuntimeEnvBuilder", false]], "runtimeenvbuilder (class in datafusion.context)": [[1, "datafusion.context.RuntimeEnvBuilder", false]], "scalarsubquery (in module datafusion.expr)": [[4, "datafusion.expr.ScalarSubquery", false]], "scalarudf (class in datafusion)": [[7, "datafusion.ScalarUDF", false]], "scalarudf (class in datafusion.user_defined)": [[17, "datafusion.user_defined.ScalarUDF", false]], "scalarudfexportable (class in datafusion.user_defined)": [[17, "datafusion.user_defined.ScalarUDFExportable", false]], "scalarvariable (in module datafusion.expr)": [[4, "datafusion.expr.ScalarVariable", false]], "schema (class in datafusion.catalog)": [[0, "datafusion.catalog.Schema", false]], "schema (datafusion.catalog.table property)": [[0, "datafusion.catalog.Table.schema", false]], "schema (datafusion.table property)": [[7, "datafusion.Table.schema", false]], "schema() (datafusion.catalog method)": [[7, "datafusion.Catalog.schema", false]], "schema() (datafusion.catalog.catalog method)": [[0, "datafusion.catalog.Catalog.schema", false]], "schema() (datafusion.catalog.catalogprovider method)": [[0, "datafusion.catalog.CatalogProvider.schema", false]], "schema() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.schema", false]], "schema_name() (datafusion.expr method)": [[7, "datafusion.Expr.schema_name", false]], "schema_name() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.schema_name", false]], "schema_names() (datafusion.catalog method)": [[7, "datafusion.Catalog.schema_names", false]], "schema_names() (datafusion.catalog.catalog method)": [[0, "datafusion.catalog.Catalog.schema_names", false]], "schema_names() (datafusion.catalog.catalogprovider method)": [[0, "datafusion.catalog.CatalogProvider.schema_names", false]], "schemaprovider (class in datafusion.catalog)": [[0, "datafusion.catalog.SchemaProvider", false]], "select() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.select", false]], "select_columns() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.select_columns", false]], "serde (class in datafusion.substrait)": [[15, "datafusion.substrait.Serde", false]], "serialize() (datafusion.substrait.serde static method)": [[15, "datafusion.substrait.Serde.serialize", false]], "serialize_bytes() (datafusion.substrait.serde static method)": [[15, "datafusion.substrait.Serde.serialize_bytes", false]], "serialize_to_plan() (datafusion.substrait.serde static method)": [[15, "datafusion.substrait.Serde.serialize_to_plan", false]], "session_id() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.session_id", false]], "sessionconfig (class in datafusion)": [[7, "datafusion.SessionConfig", false]], "sessionconfig (class in datafusion.context)": [[1, "datafusion.context.SessionConfig", false]], "sessioncontext (class in datafusion.context)": [[1, "datafusion.context.SessionContext", false]], "set() (datafusion.context.sessionconfig method)": [[1, "datafusion.context.SessionConfig.set", false]], "set() (datafusion.sessionconfig method)": [[7, "datafusion.SessionConfig.set", false]], "set_custom_cell_builder() (datafusion.dataframe_formatter.dataframehtmlformatter method)": [[3, "datafusion.dataframe_formatter.DataFrameHtmlFormatter.set_custom_cell_builder", false]], "set_custom_header_builder() (datafusion.dataframe_formatter.dataframehtmlformatter method)": [[3, "datafusion.dataframe_formatter.DataFrameHtmlFormatter.set_custom_header_builder", false]], "set_formatter() (datafusion.dataframe_formatter.formattermanager class method)": [[3, "datafusion.dataframe_formatter.FormatterManager.set_formatter", false]], "set_formatter() (in module datafusion.dataframe_formatter)": [[3, "datafusion.dataframe_formatter.set_formatter", false]], "setvariable (in module datafusion.expr)": [[4, "datafusion.expr.SetVariable", false]], "sha224() (datafusion.expr method)": [[7, "datafusion.Expr.sha224", false]], "sha224() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.sha224", false]], "sha224() (in module datafusion.functions)": 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      Distinct +----------+--------------------------------------------------+ | Type 1 | Type 2 List | +----------+--------------------------------------------------+ -| Bug | [Poison, , Grass, Flying] | -| Poison | [Ground, , Flying] | -| Electric | [Steel, Flying, ] | +| Bug | [Flying, Grass, , Poison] | +| Poison | [Flying, Ground, ] | +| Electric | [Steel, , Flying] | | Fairy | [] | | Normal | [, Flying, Fairy] | | Ice | [Psychic, Flying] | -| Grass | [, Psychic, Poison] | -| Fire | [, Flying, Dragon] | -| Water | [, Dark, Poison, Psychic, Flying, Ice, Fighting] | +| Grass | [Psychic, , Poison] | +| Fire | [, Dragon, Flying] | +| Water | [Dark, Psychic, Fighting, Ice, Poison, , Flying] | | Ground | [, Rock] | +----------+--------------------------------------------------+ Data truncated. @@ -634,15 +634,15 @@

      Distinct +----------+------------------------------------------------+ | Type 1 | Type 2 List | +----------+------------------------------------------------+ -| Bug | [Poison, Grass, Flying] | -| Poison | [Flying, Ground] | +| Bug | [Flying, Poison, Grass] | +| Poison | [Ground, Flying] | | Electric | [Flying, Steel] | -| Normal | [Flying, Fairy] | +| Normal | [Fairy, Flying] | | Ice | [Psychic, Flying] | -| Grass | [Poison, Psychic] | +| Grass | [Psychic, Poison] | | Fire | [Dragon, Flying] | -| Water | [Poison, Psychic, Flying, Fighting, Ice, Dark] | -| Rock | [Flying, Ground, Water] | +| Water | [Dark, Flying, Psychic, Ice, Fighting, Poison] | +| Rock | [Water, Ground, Flying] | | Ghost | [Poison] | +----------+------------------------------------------------+ Data truncated. @@ -653,15 +653,15 @@

      Distinct +----------+------------------------------------------------+ | Type 1 | Type 2 List | +----------+------------------------------------------------+ -| Bug | [Flying, Grass, Poison] | +| Bug | [Poison, Flying, Grass] | | Poison | [Flying, Ground] | | Electric | [Steel, Flying] | | Fairy | | | Normal | [Fairy, Flying] | | Ice | [Flying, Psychic] | -| Grass | [Psychic, Poison] | -| Fire | [Dragon, Flying] | -| Water | [Ice, Psychic, Fighting, Dark, Poison, Flying] | +| Grass | [Poison, Psychic] | +| Fire | [Flying, Dragon] | +| Water | [Psychic, Fighting, Dark, Poison, Flying, Ice] | | Ground | [Rock] | +----------+------------------------------------------------+ Data truncated. diff --git a/user-guide/common-operations/basic-info.html b/user-guide/common-operations/basic-info.html index 5f5186e73..f88289ea5 100644 --- a/user-guide/common-operations/basic-info.html +++ b/user-guide/common-operations/basic-info.html @@ -446,11 +446,11 @@

      Basic Operations+-----+---------+--------+--------+ | nrs | names | random | groups | +-----+---------+--------+--------+ -| 1 | python | 968 | A | -| 2 | ruby | 979 | A | -| 3 | java | 177 | B | -| 4 | haskell | 423 | C | -| 5 | go | 795 | B | +| 1 | python | 418 | A | +| 2 | ruby | 166 | A | +| 3 | java | 885 | B | +| 4 | haskell | 199 | C | +| 5 | go | 985 | B | +-----+---------+--------+--------+ @@ -461,8 +461,8 @@

      Basic Operations+-----+--------+--------+--------+ | nrs | names | random | groups | +-----+--------+--------+--------+ -| 1 | python | 968 | A | -| 2 | ruby | 979 | A | +| 1 | python | 418 | A | +| 2 | ruby | 166 | A | +-----+--------+--------+--------+ @@ -480,11 +480,11 @@

      Basic Operations
      In [8]: df.to_pandas()
 Out[8]: 
    nrs    names  random groups
-0    1   python     968      A
-1    2     ruby     979      A
-2    3     java     177      B
-3    4  haskell     423      C
-4    5       go     795      B
+0    1   python     418      A
+1    2     ruby     166      A
+2    3     java     885      B
+3    4  haskell     199      C
+4    5       go     985      B

      describe() shows a quick statistic summary of your data:

      @@ -496,11 +496,11 @@

      Basic Operations+------------+--------------------+-------+-------------------+--------+ | count | 5.0 | 5 | 5.0 | 5 | | null_count | 0.0 | 0 | 0.0 | 0 | -| mean | 3.0 | null | 668.4 | null | -| std | 1.5811388300841898 | null | 354.9490104226239 | null | -| min | 1.0 | go | 177.0 | A | -| max | 5.0 | ruby | 979.0 | C | -| median | 3.0 | null | 795.0 | null | +| mean | 3.0 | null | 530.6 | null | +| std | 1.5811388300841898 | null | 383.2914035039137 | null | +| min | 1.0 | go | 166.0 | A | +| max | 5.0 | ruby | 985.0 | C | +| median | 3.0 | null | 418.0 | null | +------------+--------------------+-------+-------------------+--------+ diff --git a/user-guide/common-operations/functions.html b/user-guide/common-operations/functions.html index cfc85464f..3211e8251 100644 --- a/user-guide/common-operations/functions.html +++ b/user-guide/common-operations/functions.html @@ -556,16 +556,16 @@

      Temporal +--------------------------------+ | now() | +--------------------------------+ -| 2025-09-17T19:32:40.245872298Z | -| 2025-09-17T19:32:40.245872298Z | -| 2025-09-17T19:32:40.245872298Z | -| 2025-09-17T19:32:40.245872298Z | -| 2025-09-17T19:32:40.245872298Z | -| 2025-09-17T19:32:40.245872298Z | -| 2025-09-17T19:32:40.245872298Z | -| 2025-09-17T19:32:40.245872298Z | -| 2025-09-17T19:32:40.245872298Z | -| 2025-09-17T19:32:40.245872298Z | +| 2025-10-16T17:13:48.336869762Z | +| 2025-10-16T17:13:48.336869762Z | +| 2025-10-16T17:13:48.336869762Z | +| 2025-10-16T17:13:48.336869762Z | +| 2025-10-16T17:13:48.336869762Z | +| 2025-10-16T17:13:48.336869762Z | +| 2025-10-16T17:13:48.336869762Z | +| 2025-10-16T17:13:48.336869762Z | +| 2025-10-16T17:13:48.336869762Z | +| 2025-10-16T17:13:48.336869762Z | +--------------------------------+ Data truncated. diff --git a/user-guide/data-sources.html b/user-guide/data-sources.html index a97fd0274..40625ae25 100644 --- a/user-guide/data-sources.html +++ b/user-guide/data-sources.html @@ -656,7 +656,7 @@

      Delta Lake
      from deltalake import DeltaTable
 
 delta_table = DeltaTable("path_to_table")
-ctx.register_table_provider("my_delta_table", delta_table)
+ctx.register_table("my_delta_table", delta_table)
 df = ctx.table("my_delta_table")
 df.show()
      diff --git a/user-guide/introduction.html b/user-guide/introduction.html index df9a43faf..cf5fd7719 100644 --- a/user-guide/introduction.html +++ b/user-guide/introduction.html @@ -447,7 +447,7 @@

      Installation
      In [1]: import datafusion
 
 In [2]: datafusion.__version__
-Out[2]: '50.0.0'
+Out[2]: '50.1.0'

      In this documentation we will also show some examples for how DataFusion integrates diff --git a/user-guide/io/table_provider.html b/user-guide/io/table_provider.html index 68208a0d4..ba7e1cbcb 100644 --- a/user-guide/io/table_provider.html +++ b/user-guide/io/table_provider.html @@ -438,23 +438,27 @@ &self, py: Python<'py>, ) -> PyResult<Bound<'py, PyCapsule>> { - let name = CString::new("datafusion_table_provider").unwrap(); + let name = cr"datafusion_table_provider".into(); - let provider = Arc::new(self.clone()) - .map_err(|e| PyRuntimeError::new_err(e.to_string()))?; - let provider = FFI_TableProvider::new(Arc::new(provider), false); + let provider = Arc::new(self.clone()); + let provider = FFI_TableProvider::new(provider, false, None); PyCapsule::new_bound(py, provider, Some(name.clone())) } } -

      Once you have this library available, in python you can register your table provider -to the SessionContext.

      -
      provider = MyTableProvider()
-ctx.register_table_provider("my_table", provider)
+
      Once you have this library available, you can construct a
+Table in Python and register it with the
+SessionContext.
      
+
      from datafusion import SessionContext, Table
 
-ctx.table("my_table").show()
+ctx = SessionContext()
+provider = MyTableProvider()
+
+ctx.register_table("capsule_table", provider)
+
+ctx.table("capsule_table").show()
 
      
 
      
 

From 79345e73fabb42f2dbd78c3c6dbda59ae68dd7de Mon Sep 17 00:00:00 2001
From: "github-actions[bot]" 
Date: Mon, 5 Jan 2026 16:07:08 +0000
Subject: [PATCH 31/36] Publish built docs triggered by
 fc5d46e9e307dba3778b5cfd7ecd465a5d63a797

---
 .../autoapi/datafusion/context/index.rst.txt  |  14 +-
 .../datafusion/dataframe/index.rst.txt        | 130 +++++++++++----
 .../dataframe_formatter/index.rst.txt         |  10 +-
 .../autoapi/datafusion/expr/index.rst.txt     |  22 +--
 .../datafusion/functions/index.rst.txt        | 102 ++++++------
 _sources/autoapi/datafusion/index.rst.txt     |  86 ++++++----
 .../datafusion/record_batch/index.rst.txt     |  25 ++-
 .../datafusion/user_defined/index.rst.txt     |  52 ++++--
 .../common-operations/joins.rst.txt           |  34 +++-
 _sources/user-guide/configuration.rst.txt     |   2 +
 _sources/user-guide/dataframe/index.rst.txt   | 116 ++++++++++++-
 _sources/user-guide/io/arrow.rst.txt          |  10 +-
 _sources/user-guide/sql.rst.txt               |  91 +++++++++-
 autoapi/datafusion/context/index.html         |  13 +-
 autoapi/datafusion/dataframe/index.html       | 155 +++++++++++++++---
 .../datafusion/dataframe_formatter/index.html |   8 +-
 autoapi/datafusion/expr/index.html            |   4 +-
 autoapi/datafusion/index.html                 |  84 +++++++---
 autoapi/datafusion/record_batch/index.html    |  36 +++-
 autoapi/datafusion/user_defined/index.html    |  72 ++++++--
 genindex.html                                 |  20 ++-
 objects.inv                                   | Bin 8766 -> 8815 bytes
 searchindex.js                                |   2 +-
 .../common-operations/aggregations.html       |  32 ++--
 user-guide/common-operations/basic-info.html  |  46 +++---
 user-guide/common-operations/functions.html   |  28 ++--
 user-guide/common-operations/index.html       |   1 +
 user-guide/common-operations/joins.html       |  51 ++++++
 user-guide/configuration.html                 |   2 +-
 user-guide/dataframe/index.html               | 113 ++++++++++++-
 user-guide/introduction.html                  |   2 +-
 user-guide/io/arrow.html                      |  18 +-
 user-guide/sql.html                           | 134 ++++++++++++++-
 33 files changed, 1191 insertions(+), 324 deletions(-)

diff --git a/_sources/autoapi/datafusion/context/index.rst.txt b/_sources/autoapi/datafusion/context/index.rst.txt
index 3641fe8e6..50c3a9d4e 100644
--- a/_sources/autoapi/datafusion/context/index.rst.txt
+++ b/_sources/autoapi/datafusion/context/index.rst.txt
@@ -866,10 +866,14 @@ Module Contents
 
 
 
-   .. py:method:: sql(query: str, options: SQLOptions | None = None) -> datafusion.dataframe.DataFrame
+   .. py:method:: sql(query: str, options: SQLOptions | None = None, param_values: dict[str, Any] | None = None, **named_params: Any) -> datafusion.dataframe.DataFrame
 
       Create a :py:class:`~datafusion.DataFrame` from SQL query text.
 
+      See the online documentation for a description of how to perform
+      parameterized substitution via either the ``param_values`` option
+      or passing in ``named_params``.
+
       Note: This API implements DDL statements such as ``CREATE TABLE`` and
       ``CREATE VIEW`` and DML statements such as ``INSERT INTO`` with in-memory
       default implementation.See
@@ -877,12 +881,15 @@ Module Contents
 
       :param query: SQL query text.
       :param options: If provided, the query will be validated against these options.
+      :param param_values: Provides substitution of scalar values in the query
+                           after parsing.
+      :param named_params: Provides string or DataFrame substitution in the query string.
 
       :returns: DataFrame representation of the SQL query.
 
 
 
-   .. py:method:: sql_with_options(query: str, options: SQLOptions) -> datafusion.dataframe.DataFrame
+   .. py:method:: sql_with_options(query: str, options: SQLOptions, param_values: dict[str, Any] | None = None, **named_params: Any) -> datafusion.dataframe.DataFrame
 
       Create a :py:class:`~datafusion.dataframe.DataFrame` from SQL query text.
 
@@ -891,6 +898,9 @@ Module Contents
 
       :param query: SQL query text.
       :param options: SQL options.
+      :param param_values: Provides substitution of scalar values in the query
+                           after parsing.
+      :param named_params: Provides string or DataFrame substitution in the query string.
 
       :returns: DataFrame representation of the SQL query.
 
diff --git a/_sources/autoapi/datafusion/dataframe/index.rst.txt b/_sources/autoapi/datafusion/dataframe/index.rst.txt
index 8898ceaf0..f4134a83d 100644
--- a/_sources/autoapi/datafusion/dataframe/index.rst.txt
+++ b/_sources/autoapi/datafusion/dataframe/index.rst.txt
@@ -49,7 +49,7 @@ Module Contents
 
 
 
-   .. py:method:: get_default_level() -> Optional[int]
+   .. py:method:: get_default_level() -> int | None
 
       Get the default compression level for the compression type.
 
@@ -96,6 +96,9 @@ Module Contents
 
    Two dimensional table representation of data.
 
+   DataFrame objects are iterable; iterating over a DataFrame yields
+   :class:`datafusion.RecordBatch` instances lazily.
+
    See :ref:`user_guide_concepts` in the online documentation for more information.
 
    This constructor is not to be used by the end user.
@@ -104,24 +107,52 @@ Module Contents
    create a :py:class:`DataFrame`.
 
 
+   .. py:method:: __aiter__() -> collections.abc.AsyncIterator[datafusion.record_batch.RecordBatch]
+
+      Return an async iterator over this DataFrame's record batches.
+
+      We're using __aiter__ because we support Python < 3.10 where aiter() is not
+      available.
+
+
+
    .. py:method:: __arrow_c_stream__(requested_schema: object | None = None) -> object
 
-      Export an Arrow PyCapsule Stream.
+      Export the DataFrame as an Arrow C Stream.
+
+      The DataFrame is executed using DataFusion's streaming APIs and exposed via
+      Arrow's C Stream interface. Record batches are produced incrementally, so the
+      full result set is never materialized in memory.
+
+      When ``requested_schema`` is provided, DataFusion applies only simple
+      projections such as selecting a subset of existing columns or reordering
+      them. Column renaming, computed expressions, or type coercion are not
+      supported through this interface.
 
-      This will execute and collect the DataFrame. We will attempt to respect the
-      requested schema, but only trivial transformations will be applied such as only
-      returning the fields listed in the requested schema if their data types match
-      those in the DataFrame.
+      :param requested_schema: Either a :py:class:`pyarrow.Schema` or an Arrow C
+                               Schema capsule (``PyCapsule``) produced by
+                               ``schema._export_to_c_capsule()``. The DataFrame will attempt to
+                               align its output with the fields and order specified by this schema.
 
-      :param requested_schema: Attempt to provide the DataFrame using this schema.
+      :returns: Arrow ``PyCapsule`` object representing an ``ArrowArrayStream``.
 
-      :returns: Arrow PyCapsule object.
+      For practical usage patterns, see the Apache Arrow streaming
+      documentation: https://arrow.apache.org/docs/python/ipc.html#streaming.
+
+      For details on DataFusion's Arrow integration and DataFrame streaming,
+      see the user guide (user-guide/io/arrow and user-guide/dataframe/index).
+
+      .. rubric:: Notes
+
+      The Arrow C Data Interface PyCapsule details are documented by Apache
+      Arrow and can be found at:
+      https://arrow.apache.org/docs/format/CDataInterface/PyCapsuleInterface.html
 
 
 
    .. py:method:: __getitem__(key: str | list[str]) -> DataFrame
 
-      Return a new :py:class`DataFrame` with the specified column or columns.
+      Return a new :py:class:`DataFrame` with the specified column or columns.
 
       :param key: Column name or list of column names to select.
 
@@ -129,6 +160,12 @@ Module Contents
 
 
 
+   .. py:method:: __iter__() -> collections.abc.Iterator[datafusion.record_batch.RecordBatch]
+
+      Return an iterator over this DataFrame's record batches.
+
+
+
    .. py:method:: __repr__() -> str
 
       Return a string representation of the DataFrame.
@@ -181,6 +218,12 @@ Module Contents
 
 
 
+   .. py:method:: collect_column(column_name: str) -> pyarrow.Array | pyarrow.ChunkedArray
+
+      Executes this :py:class:`DataFrame` for a single column.
+
+
+
    .. py:method:: collect_partitioned() -> list[list[pyarrow.RecordBatch]]
 
       Execute this DataFrame and collect all partitioned results.
@@ -328,24 +371,25 @@ Module Contents
 
 
 
-   .. py:method:: filter(*predicates: datafusion.expr.Expr) -> DataFrame
+   .. py:method:: filter(*predicates: datafusion.expr.Expr | str) -> DataFrame
 
       Return a DataFrame for which ``predicate`` evaluates to ``True``.
 
       Rows for which ``predicate`` evaluates to ``False`` or ``None`` are filtered
       out. If more than one predicate is provided, these predicates will be
-      combined as a logical AND. Each ``predicate`` must be an
+      combined as a logical AND. Each ``predicate`` can be an
       :class:`~datafusion.expr.Expr` created using helper functions such as
-      :func:`datafusion.col` or :func:`datafusion.lit`.
-      If more complex logic is required, see the logical operations in
-      :py:mod:`~datafusion.functions`.
+      :func:`datafusion.col` or :func:`datafusion.lit`, or a SQL expression string
+      that will be parsed against the DataFrame schema. If more complex logic is
+      required, see the logical operations in :py:mod:`~datafusion.functions`.
 
       Example::
 
           from datafusion import col, lit
           df.filter(col("a") > lit(1))
+          df.filter("a > 1")
 
-      :param predicates: Predicate expression(s) to filter the DataFrame.
+      :param predicates: Predicate expression(s) or SQL strings to filter the DataFrame.
 
       :returns: DataFrame after filtering.
 
@@ -373,7 +417,7 @@ Module Contents
 
 
 
-   .. py:method:: into_view() -> datafusion.catalog.Table
+   .. py:method:: into_view(temporary: bool = False) -> datafusion.catalog.Table
 
       Convert ``DataFrame`` into a :class:`~datafusion.Table`.
 
@@ -389,9 +433,9 @@ Module Contents
 
 
 
-   .. py:method:: join(right: DataFrame, on: str | collections.abc.Sequence[str], how: Literal['inner', 'left', 'right', 'full', 'semi', 'anti'] = 'inner', *, left_on: None = None, right_on: None = None, join_keys: None = None) -> DataFrame
-                  join(right: DataFrame, on: None = None, how: Literal['inner', 'left', 'right', 'full', 'semi', 'anti'] = 'inner', *, left_on: str | collections.abc.Sequence[str], right_on: str | collections.abc.Sequence[str], join_keys: tuple[list[str], list[str]] | None = None) -> DataFrame
-                  join(right: DataFrame, on: None = None, how: Literal['inner', 'left', 'right', 'full', 'semi', 'anti'] = 'inner', *, join_keys: tuple[list[str], list[str]], left_on: None = None, right_on: None = None) -> DataFrame
+   .. py:method:: join(right: DataFrame, on: str | collections.abc.Sequence[str], how: Literal['inner', 'left', 'right', 'full', 'semi', 'anti'] = 'inner', *, left_on: None = None, right_on: None = None, join_keys: None = None, coalesce_duplicate_keys: bool = True) -> DataFrame
+                  join(right: DataFrame, on: None = None, how: Literal['inner', 'left', 'right', 'full', 'semi', 'anti'] = 'inner', *, left_on: str | collections.abc.Sequence[str], right_on: str | collections.abc.Sequence[str], join_keys: tuple[list[str], list[str]] | None = None, coalesce_duplicate_keys: bool = True) -> DataFrame
+                  join(right: DataFrame, on: None = None, how: Literal['inner', 'left', 'right', 'full', 'semi', 'anti'] = 'inner', *, join_keys: tuple[list[str], list[str]], left_on: None = None, right_on: None = None, coalesce_duplicate_keys: bool = True) -> DataFrame
 
       Join this :py:class:`DataFrame` with another :py:class:`DataFrame`.
 
@@ -403,6 +447,9 @@ Module Contents
                   "right", "full", "semi", "anti".
       :param left_on: Join column of the left dataframe.
       :param right_on: Join column of the right dataframe.
+      :param coalesce_duplicate_keys: When True, coalesce the columns
+                                      from the right DataFrame and left DataFrame
+                                      that have identical names in the ``on`` fields.
       :param join_keys: Tuple of two lists of column names to join on. [Deprecated]
 
       :returns: DataFrame after join.
@@ -491,11 +538,12 @@ Module Contents
 
 
 
-   .. py:method:: repartition_by_hash(*exprs: datafusion.expr.Expr, num: int) -> DataFrame
+   .. py:method:: repartition_by_hash(*exprs: datafusion.expr.Expr | str, num: int) -> DataFrame
 
       Repartition a DataFrame using a hash partitioning scheme.
 
-      :param exprs: Expressions to evaluate and perform hashing on.
+      :param exprs: Expressions or a SQL expression string to evaluate
+                    and perform hashing on.
       :param num: Number of partitions to repartition the DataFrame into.
 
       :returns: Repartitioned DataFrame.
@@ -541,6 +589,17 @@ Module Contents
 
 
 
+   .. py:method:: select_exprs(*args: str) -> DataFrame
+
+      Project arbitrary list of expression strings into a new DataFrame.
+
+      This method will parse string expressions into logical plan expressions.
+      The output DataFrame has one column for each expression.
+
+      :returns: DataFrame only containing the specified columns.
+
+
+
    .. py:method:: show(num: int = 20) -> None
 
       Execute the DataFrame and print the result to the console.
@@ -615,7 +674,7 @@ Module Contents
 
 
 
-   .. py:method:: transform(func: Callable[Ellipsis, DataFrame], *args: Any) -> DataFrame
+   .. py:method:: transform(func: collections.abc.Callable[Ellipsis, DataFrame], *args: Any) -> DataFrame
 
       Apply a function to the current DataFrame which returns another DataFrame.
 
@@ -675,12 +734,13 @@ Module Contents
 
 
 
-   .. py:method:: with_column(name: str, expr: datafusion.expr.Expr) -> DataFrame
+   .. py:method:: with_column(name: str, expr: datafusion.expr.Expr | str) -> DataFrame
 
       Add an additional column to the DataFrame.
 
       The ``expr`` must be an :class:`~datafusion.expr.Expr` constructed with
-      :func:`datafusion.col` or :func:`datafusion.lit`.
+      :func:`datafusion.col` or :func:`datafusion.lit`, or a SQL expression
+      string that will be parsed against the DataFrame schema.
 
       Example::
 
@@ -710,13 +770,14 @@ Module Contents
 
 
 
-   .. py:method:: with_columns(*exprs: datafusion.expr.Expr | Iterable[datafusion.expr.Expr], **named_exprs: datafusion.expr.Expr) -> DataFrame
+   .. py:method:: with_columns(*exprs: datafusion.expr.Expr | str | collections.abc.Iterable[datafusion.expr.Expr | str], **named_exprs: datafusion.expr.Expr | str) -> DataFrame
 
       Add columns to the DataFrame.
 
-      By passing expressions, iterables of expressions, or named expressions.
+      By passing expressions, iterables of expressions, string SQL expressions,
+      or named expressions.
       All expressions must be :class:`~datafusion.expr.Expr` objects created via
-      :func:`datafusion.col` or :func:`datafusion.lit`.
+      :func:`datafusion.col` or :func:`datafusion.lit`, or SQL expression strings.
       To pass named expressions use the form ``name=Expr``.
 
       Example usage: The following will add 4 columns labeled ``a``, ``b``, ``c``,
@@ -729,7 +790,16 @@ Module Contents
               d=lit(3)
           )
 
-      :param exprs: Either a single expression or an iterable of expressions to add.
+          Equivalent example using just SQL strings:
+
+          df = df.with_columns(
+              "x as a",
+              ["1 as b", "y as c"],
+              d="3"
+          )
+
+      :param exprs: Either a single expression, an iterable of expressions to add or
+                    SQL expression strings.
       :param named_exprs: Named expressions in the form of ``name=expr``
 
       :returns: DataFrame with the new columns added.
@@ -849,7 +919,7 @@ Module Contents
       Replacement is typically based on a unique key or primary key.
 
 
-.. py:class:: ParquetColumnOptions(encoding: Optional[str] = None, dictionary_enabled: Optional[bool] = None, compression: Optional[str] = None, statistics_enabled: Optional[str] = None, bloom_filter_enabled: Optional[bool] = None, bloom_filter_fpp: Optional[float] = None, bloom_filter_ndv: Optional[int] = None)
+.. py:class:: ParquetColumnOptions(encoding: str | None = None, dictionary_enabled: bool | None = None, compression: str | None = None, statistics_enabled: str | None = None, bloom_filter_enabled: bool | None = None, bloom_filter_fpp: float | None = None, bloom_filter_ndv: int | None = None)
 
    Parquet options for individual columns.
 
@@ -916,7 +986,7 @@ Module Contents
 
 
 
-.. py:class:: ParquetWriterOptions(data_pagesize_limit: int = 1024 * 1024, write_batch_size: int = 1024, writer_version: str = '1.0', skip_arrow_metadata: bool = False, compression: Optional[str] = 'zstd(3)', compression_level: Optional[int] = None, dictionary_enabled: Optional[bool] = True, dictionary_page_size_limit: int = 1024 * 1024, statistics_enabled: Optional[str] = 'page', max_row_group_size: int = 1024 * 1024, created_by: str = 'datafusion-python', column_index_truncate_length: Optional[int] = 64, statistics_truncate_length: Optional[int] = None, data_page_row_count_limit: int = 20000, encoding: Optional[str] = None, bloom_filter_on_write: bool = False, bloom_filter_fpp: Optional[float] = None, bloom_filter_ndv: Optional[int] = None, allow_single_file_parallelism: bool = True, maximum_parallel_row_group_writers: int = 1, maximum_buffered_record_batches_per_stream: int = 2, column_specific_options: Optional[dict[str, ParquetColumnOptions]] = None)
+.. py:class:: ParquetWriterOptions(data_pagesize_limit: int = 1024 * 1024, write_batch_size: int = 1024, writer_version: str = '1.0', skip_arrow_metadata: bool = False, compression: str | None = 'zstd(3)', compression_level: int | None = None, dictionary_enabled: bool | None = True, dictionary_page_size_limit: int = 1024 * 1024, statistics_enabled: str | None = 'page', max_row_group_size: int = 1024 * 1024, created_by: str = 'datafusion-python', column_index_truncate_length: int | None = 64, statistics_truncate_length: int | None = None, data_page_row_count_limit: int = 20000, encoding: str | None = None, bloom_filter_on_write: bool = False, bloom_filter_fpp: float | None = None, bloom_filter_ndv: int | None = None, allow_single_file_parallelism: bool = True, maximum_parallel_row_group_writers: int = 1, maximum_buffered_record_batches_per_stream: int = 2, column_specific_options: dict[str, ParquetColumnOptions] | None = None)
 
    Advanced parquet writer options.
 
diff --git a/_sources/autoapi/datafusion/dataframe_formatter/index.rst.txt b/_sources/autoapi/datafusion/dataframe_formatter/index.rst.txt
index ad3e62b5d..7f5b3f530 100644
--- a/_sources/autoapi/datafusion/dataframe_formatter/index.rst.txt
+++ b/_sources/autoapi/datafusion/dataframe_formatter/index.rst.txt
@@ -52,7 +52,7 @@ Module Contents
 
 
 
-.. py:class:: DataFrameHtmlFormatter(max_cell_length: int = 25, max_width: int = 1000, max_height: int = 300, max_memory_bytes: int = 2 * 1024 * 1024, min_rows_display: int = 20, repr_rows: int = 10, enable_cell_expansion: bool = True, custom_css: Optional[str] = None, show_truncation_message: bool = True, style_provider: Optional[StyleProvider] = None, use_shared_styles: bool = True)
+.. py:class:: DataFrameHtmlFormatter(max_cell_length: int = 25, max_width: int = 1000, max_height: int = 300, max_memory_bytes: int = 2 * 1024 * 1024, min_rows_display: int = 20, repr_rows: int = 10, enable_cell_expansion: bool = True, custom_css: str | None = None, show_truncation_message: bool = True, style_provider: StyleProvider | None = None, use_shared_styles: bool = True)
 
    Configurable HTML formatter for DataFusion DataFrames.
 
@@ -237,7 +237,7 @@ Module Contents
 
 
 
-   .. py:method:: set_custom_cell_builder(builder: Callable[[Any, int, int, str], str]) -> None
+   .. py:method:: set_custom_cell_builder(builder: collections.abc.Callable[[Any, int, int, str], str]) -> None
 
       Set a custom cell builder function.
 
@@ -245,7 +245,7 @@ Module Contents
 
 
 
-   .. py:method:: set_custom_header_builder(builder: Callable[[Any], str]) -> None
+   .. py:method:: set_custom_header_builder(builder: collections.abc.Callable[[Any], str]) -> None
 
       Set a custom header builder function.
 
@@ -254,13 +254,13 @@ Module Contents
 
 
    .. py:attribute:: _custom_cell_builder
-      :type:  Optional[Callable[[Any, int, int, str], str]]
+      :type:  collections.abc.Callable[[Any, int, int, str], str] | None
       :value: None
 
 
 
    .. py:attribute:: _custom_header_builder
-      :type:  Optional[Callable[[Any], str]]
+      :type:  collections.abc.Callable[[Any], str] | None
       :value: None
 
 
diff --git a/_sources/autoapi/datafusion/expr/index.rst.txt b/_sources/autoapi/datafusion/expr/index.rst.txt
index 71f68f7e3..2bea04f40 100644
--- a/_sources/autoapi/datafusion/expr/index.rst.txt
+++ b/_sources/autoapi/datafusion/expr/index.rst.txt
@@ -339,7 +339,7 @@ Module Contents
 
 
 
-   .. py:method:: alias(name: str, metadata: Optional[dict[str, str]] = None) -> Expr
+   .. py:method:: alias(name: str, metadata: dict[str, str] | None = None) -> Expr
 
       Assign a name to the expression.
 
@@ -462,7 +462,7 @@ Module Contents
 
 
 
-   .. py:method:: cast(to: Union[pyarrow.DataType[Any], type]) -> Expr
+   .. py:method:: cast(to: pyarrow.DataType[Any] | type) -> Expr
 
       Cast to a new data type.
 
@@ -572,13 +572,13 @@ Module Contents
 
 
 
-   .. py:method:: fill_nan(value: Optional[Union[Any, Expr]] = None) -> Expr
+   .. py:method:: fill_nan(value: Any | Expr | None = None) -> Expr
 
       Fill NaN values with a provided value.
 
 
 
-   .. py:method:: fill_null(value: Optional[Union[Any, Expr]] = None) -> Expr
+   .. py:method:: fill_null(value: Any | Expr | None = None) -> Expr
 
       Fill NULL values with a provided value.
 
@@ -756,7 +756,7 @@ Module Contents
 
 
 
-   .. py:method:: order_by(*exprs: Union[Expr, SortExpr]) -> ExprFuncBuilder
+   .. py:method:: order_by(*exprs: Expr | SortExpr) -> ExprFuncBuilder
 
       Set the ordering for a window or aggregate function.
 
@@ -790,7 +790,7 @@ Module Contents
 
    .. py:method:: python_value() -> Any
 
-      Extracts the Expr value into a PyObject.
+      Extracts the Expr value into `Any`.
 
       This is only valid for literal expressions.
 
@@ -1048,7 +1048,7 @@ Module Contents
    .. py:attribute:: raw_sort
 
 
-.. py:class:: Window(partition_by: Optional[Union[list[Expr], Expr]] = None, window_frame: Optional[WindowFrame] = None, order_by: Optional[Union[list[Union[SortExpr, Expr, str]], Expr, SortExpr, str]] = None, null_treatment: Optional[datafusion.common.NullTreatment] = None)
+.. py:class:: Window(partition_by: list[Expr] | Expr | None = None, window_frame: WindowFrame | None = None, order_by: list[SortExpr | Expr | str] | Expr | SortExpr | str | None = None, null_treatment: datafusion.common.NullTreatment | None = None)
 
    Define reusable window parameters.
 
@@ -1080,7 +1080,7 @@ Module Contents
 
 
 
-.. py:class:: WindowFrame(units: str, start_bound: Optional[Any], end_bound: Optional[Any])
+.. py:class:: WindowFrame(units: str, start_bound: Any | None, end_bound: Any | None)
 
    Defines a window frame for performing window operations.
 
@@ -1131,7 +1131,7 @@ Module Contents
    Constructs a window frame bound.
 
 
-   .. py:method:: get_offset() -> Optional[int]
+   .. py:method:: get_offset() -> int | None
 
       Returns the offset of the window frame.
 
@@ -1164,7 +1164,7 @@ Module Contents
    .. py:attribute:: frame_bound
 
 
-.. py:function:: ensure_expr(value: Union[Expr, Any]) -> datafusion._internal.expr.Expr
+.. py:function:: ensure_expr(value: Expr | Any) -> datafusion._internal.expr.Expr
 
    Return the internal expression from ``Expr`` or raise ``TypeError``.
 
@@ -1179,7 +1179,7 @@ Module Contents
    :raises TypeError: If ``value`` is not an instance of :class:`Expr`.
 
 
-.. py:function:: ensure_expr_list(exprs: Iterable[Union[Expr, Iterable[Expr]]]) -> list[datafusion._internal.expr.Expr]
+.. py:function:: ensure_expr_list(exprs: collections.abc.Iterable[Expr | collections.abc.Iterable[Expr]]) -> list[datafusion._internal.expr.Expr]
 
    Flatten an iterable of expressions, validating each via ``ensure_expr``.
 
diff --git a/_sources/autoapi/datafusion/functions/index.rst.txt b/_sources/autoapi/datafusion/functions/index.rst.txt
index 6a2a049a1..10b7f1a01 100644
--- a/_sources/autoapi/datafusion/functions/index.rst.txt
+++ b/_sources/autoapi/datafusion/functions/index.rst.txt
@@ -285,7 +285,7 @@ Module Contents
    Returns inverse hyperbolic cosine.
 
 
-.. py:function:: alias(expr: datafusion.expr.Expr, name: str, metadata: Optional[dict[str, str]] = None) -> datafusion.expr.Expr
+.. py:function:: alias(expr: datafusion.expr.Expr, name: str, metadata: dict[str, str] | None = None) -> datafusion.expr.Expr
 
    Creates an alias expression with an optional metadata dictionary.
 
@@ -296,7 +296,7 @@ Module Contents
    :returns: An expression with the given alias
 
 
-.. py:function:: approx_distinct(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: approx_distinct(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Returns the approximate number of distinct values.
 
@@ -311,7 +311,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: approx_median(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: approx_median(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Returns the approximate median value.
 
@@ -325,7 +325,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: approx_percentile_cont(sort_expression: datafusion.expr.Expr | datafusion.expr.SortExpr, percentile: float, num_centroids: Optional[int] = None, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: approx_percentile_cont(sort_expression: datafusion.expr.Expr | datafusion.expr.SortExpr, percentile: float, num_centroids: int | None = None, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Returns the value that is approximately at a given percentile of ``expr``.
 
@@ -348,7 +348,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: approx_percentile_cont_with_weight(sort_expression: datafusion.expr.Expr | datafusion.expr.SortExpr, weight: datafusion.expr.Expr, percentile: float, num_centroids: Optional[int] = None, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: approx_percentile_cont_with_weight(sort_expression: datafusion.expr.Expr | datafusion.expr.SortExpr, weight: datafusion.expr.Expr, percentile: float, num_centroids: int | None = None, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Returns the value of the weighted approximate percentile.
 
@@ -372,7 +372,7 @@ Module Contents
    This is an alias for :py:func:`make_array`.
 
 
-.. py:function:: array_agg(expression: datafusion.expr.Expr, distinct: bool = False, filter: Optional[datafusion.expr.Expr] = None, order_by: Optional[list[datafusion.expr.SortKey] | datafusion.expr.SortKey] = None) -> datafusion.expr.Expr
+.. py:function:: array_agg(expression: datafusion.expr.Expr, distinct: bool = False, filter: datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None) -> datafusion.expr.Expr
 
    Aggregate values into an array.
 
@@ -643,7 +643,7 @@ Module Contents
    Returns inverse hyperbolic tangent.
 
 
-.. py:function:: avg(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: avg(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Returns the average value.
 
@@ -656,7 +656,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: bit_and(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: bit_and(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the bitwise AND of the argument.
 
@@ -674,7 +674,7 @@ Module Contents
    Returns the number of bits in the string argument.
 
 
-.. py:function:: bit_or(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: bit_or(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the bitwise OR of the argument.
 
@@ -687,7 +687,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: bit_xor(expression: datafusion.expr.Expr, distinct: bool = False, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: bit_xor(expression: datafusion.expr.Expr, distinct: bool = False, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the bitwise XOR of the argument.
 
@@ -701,7 +701,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: bool_and(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: bool_and(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the boolean AND of the argument.
 
@@ -715,7 +715,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: bool_or(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: bool_or(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the boolean OR of the argument.
 
@@ -797,7 +797,7 @@ Module Contents
    ``NULL`` arguments are ignored. ``separator`` should not be ``NULL``.
 
 
-.. py:function:: corr(value_y: datafusion.expr.Expr, value_x: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: corr(value_y: datafusion.expr.Expr, value_x: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Returns the correlation coefficient between ``value1`` and ``value2``.
 
@@ -826,7 +826,7 @@ Module Contents
    Returns the cotangent of the argument.
 
 
-.. py:function:: count(expressions: datafusion.expr.Expr | list[datafusion.expr.Expr] | None = None, distinct: bool = False, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: count(expressions: datafusion.expr.Expr | list[datafusion.expr.Expr] | None = None, distinct: bool = False, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Returns the number of rows that match the given arguments.
 
@@ -840,7 +840,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: count_star(filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: count_star(filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Create a COUNT(1) aggregate expression.
 
@@ -852,14 +852,14 @@ Module Contents
    :param filter: If provided, only count rows for which the filter is True
 
 
-.. py:function:: covar(value_y: datafusion.expr.Expr, value_x: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: covar(value_y: datafusion.expr.Expr, value_x: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the sample covariance.
 
    This is an alias for :py:func:`covar_samp`.
 
 
-.. py:function:: covar_pop(value_y: datafusion.expr.Expr, value_x: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: covar_pop(value_y: datafusion.expr.Expr, value_x: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the population covariance.
 
@@ -873,7 +873,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: covar_samp(value_y: datafusion.expr.Expr, value_x: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: covar_samp(value_y: datafusion.expr.Expr, value_x: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the sample covariance.
 
@@ -887,7 +887,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: cume_dist(partition_by: Optional[list[datafusion.expr.Expr] | datafusion.expr.Expr] = None, order_by: Optional[list[datafusion.expr.SortKey] | datafusion.expr.SortKey] = None) -> datafusion.expr.Expr
+.. py:function:: cume_dist(partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None) -> datafusion.expr.Expr
 
    Create a cumulative distribution window function.
 
@@ -963,7 +963,7 @@ Module Contents
    Converts the argument from radians to degrees.
 
 
-.. py:function:: dense_rank(partition_by: Optional[list[datafusion.expr.Expr] | datafusion.expr.Expr] = None, order_by: Optional[list[datafusion.expr.SortKey] | datafusion.expr.SortKey] = None) -> datafusion.expr.Expr
+.. py:function:: dense_rank(partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None) -> datafusion.expr.Expr
 
    Create a dense_rank window function.
 
@@ -1039,7 +1039,7 @@ Module Contents
    The string list is a string composed of substrings separated by ``,`` characters.
 
 
-.. py:function:: first_value(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None, order_by: Optional[list[datafusion.expr.SortKey] | datafusion.expr.SortKey] = None, null_treatment: datafusion.common.NullTreatment = NullTreatment.RESPECT_NULLS) -> datafusion.expr.Expr
+.. py:function:: first_value(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None, null_treatment: datafusion.common.NullTreatment = NullTreatment.RESPECT_NULLS) -> datafusion.expr.Expr
 
    Returns the first value in a group of values.
 
@@ -1102,7 +1102,7 @@ Module Contents
    Returns true if a given number is +0.0 or -0.0 otherwise returns false.
 
 
-.. py:function:: lag(arg: datafusion.expr.Expr, shift_offset: int = 1, default_value: Optional[Any] = None, partition_by: Optional[list[datafusion.expr.Expr] | datafusion.expr.Expr] = None, order_by: Optional[list[datafusion.expr.SortKey] | datafusion.expr.SortKey] = None) -> datafusion.expr.Expr
+.. py:function:: lag(arg: datafusion.expr.Expr, shift_offset: int = 1, default_value: Any | None = None, partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None) -> datafusion.expr.Expr
 
    Create a lag window function.
 
@@ -1135,7 +1135,7 @@ Module Contents
        lag(col("b"), order_by="ts")
 
 
-.. py:function:: last_value(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None, order_by: Optional[list[datafusion.expr.SortKey] | datafusion.expr.SortKey] = None, null_treatment: datafusion.common.NullTreatment = NullTreatment.RESPECT_NULLS) -> datafusion.expr.Expr
+.. py:function:: last_value(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None, null_treatment: datafusion.common.NullTreatment = NullTreatment.RESPECT_NULLS) -> datafusion.expr.Expr
 
    Returns the last value in a group of values.
 
@@ -1160,7 +1160,7 @@ Module Contents
    Returns the least common multiple.
 
 
-.. py:function:: lead(arg: datafusion.expr.Expr, shift_offset: int = 1, default_value: Optional[Any] = None, partition_by: Optional[list[datafusion.expr.Expr] | datafusion.expr.Expr] = None, order_by: Optional[list[datafusion.expr.SortKey] | datafusion.expr.SortKey] = None) -> datafusion.expr.Expr
+.. py:function:: lead(arg: datafusion.expr.Expr, shift_offset: int = 1, default_value: Any | None = None, partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None) -> datafusion.expr.Expr
 
    Create a lead window function.
 
@@ -1481,7 +1481,7 @@ Module Contents
    This is an alias for :py:func:`make_array`.
 
 
-.. py:function:: max(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: max(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Aggregate function that returns the maximum value of the argument.
 
@@ -1497,14 +1497,14 @@ Module Contents
    Computes an MD5 128-bit checksum for a string expression.
 
 
-.. py:function:: mean(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: mean(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Returns the average (mean) value of the argument.
 
    This is an alias for :py:func:`avg`.
 
 
-.. py:function:: median(expression: datafusion.expr.Expr, distinct: bool = False, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: median(expression: datafusion.expr.Expr, distinct: bool = False, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the median of a set of numbers.
 
@@ -1519,7 +1519,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: min(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: min(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Returns the minimum value of the argument.
 
@@ -1547,7 +1547,7 @@ Module Contents
    This will use the same value for all instances of now() in same statement.
 
 
-.. py:function:: nth_value(expression: datafusion.expr.Expr, n: int, filter: Optional[datafusion.expr.Expr] = None, order_by: Optional[list[datafusion.expr.SortKey] | datafusion.expr.SortKey] = None, null_treatment: datafusion.common.NullTreatment = NullTreatment.RESPECT_NULLS) -> datafusion.expr.Expr
+.. py:function:: nth_value(expression: datafusion.expr.Expr, n: int, filter: datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None, null_treatment: datafusion.common.NullTreatment = NullTreatment.RESPECT_NULLS) -> datafusion.expr.Expr
 
    Returns the n-th value in a group of values.
 
@@ -1568,7 +1568,7 @@ Module Contents
        df.select(nth_value(col("a"), 2, order_by="ts"))
 
 
-.. py:function:: ntile(groups: int, partition_by: Optional[list[datafusion.expr.Expr] | datafusion.expr.Expr] = None, order_by: Optional[list[datafusion.expr.SortKey] | datafusion.expr.SortKey] = None) -> datafusion.expr.Expr
+.. py:function:: ntile(groups: int, partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None) -> datafusion.expr.Expr
 
    Create a n-tile window function.
 
@@ -1628,7 +1628,7 @@ Module Contents
    extends for ``length`` characters with new substring.
 
 
-.. py:function:: percent_rank(partition_by: Optional[list[datafusion.expr.Expr] | datafusion.expr.Expr] = None, order_by: Optional[list[datafusion.expr.SortKey] | datafusion.expr.SortKey] = None) -> datafusion.expr.Expr
+.. py:function:: percent_rank(partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None) -> datafusion.expr.Expr
 
    Create a percent_rank window function.
 
@@ -1687,7 +1687,7 @@ Module Contents
    Create a list of values in the range between start and stop.
 
 
-.. py:function:: rank(partition_by: Optional[list[datafusion.expr.Expr] | datafusion.expr.Expr] = None, order_by: Optional[list[datafusion.expr.SortKey] | datafusion.expr.SortKey] = None) -> datafusion.expr.Expr
+.. py:function:: rank(partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None) -> datafusion.expr.Expr
 
    Create a rank window function.
 
@@ -1753,7 +1753,7 @@ Module Contents
    
 
 
-.. py:function:: regr_avgx(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: regr_avgx(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the average of the independent variable ``x``.
 
@@ -1768,7 +1768,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: regr_avgy(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: regr_avgy(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the average of the dependent variable ``y``.
 
@@ -1783,7 +1783,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: regr_count(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: regr_count(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Counts the number of rows in which both expressions are not null.
 
@@ -1798,7 +1798,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: regr_intercept(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: regr_intercept(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the intercept from the linear regression.
 
@@ -1813,7 +1813,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: regr_r2(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: regr_r2(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the R-squared value from linear regression.
 
@@ -1828,7 +1828,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: regr_slope(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: regr_slope(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the slope from linear regression.
 
@@ -1843,7 +1843,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: regr_sxx(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: regr_sxx(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the sum of squares of the independent variable ``x``.
 
@@ -1858,7 +1858,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: regr_sxy(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: regr_sxy(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the sum of products of pairs of numbers.
 
@@ -1873,7 +1873,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: regr_syy(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: regr_syy(y: datafusion.expr.Expr, x: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the sum of squares of the dependent variable ``y``.
 
@@ -1917,7 +1917,7 @@ Module Contents
    ``round(lit(125.2345), lit(-2))`` would yield a value of ``100.0``.
 
 
-.. py:function:: row_number(partition_by: Optional[list[datafusion.expr.Expr] | datafusion.expr.Expr] = None, order_by: Optional[list[datafusion.expr.SortKey] | datafusion.expr.SortKey] = None) -> datafusion.expr.Expr
+.. py:function:: row_number(partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None) -> datafusion.expr.Expr
 
    Create a row number window function.
 
@@ -2009,7 +2009,7 @@ Module Contents
    Returns true if string starts with prefix.
 
 
-.. py:function:: stddev(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: stddev(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the standard deviation of the argument.
 
@@ -2020,7 +2020,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: stddev_pop(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: stddev_pop(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the population standard deviation of the argument.
 
@@ -2031,14 +2031,14 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: stddev_samp(arg: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: stddev_samp(arg: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the sample standard deviation of the argument.
 
    This is an alias for :py:func:`stddev`.
 
 
-.. py:function:: string_agg(expression: datafusion.expr.Expr, delimiter: str, filter: Optional[datafusion.expr.Expr] = None, order_by: Optional[list[datafusion.expr.SortKey] | datafusion.expr.SortKey] = None) -> datafusion.expr.Expr
+.. py:function:: string_agg(expression: datafusion.expr.Expr, delimiter: str, filter: datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None) -> datafusion.expr.Expr
 
    Concatenates the input strings.
 
@@ -2088,7 +2088,7 @@ Module Contents
    Substring from the ``position`` with ``length`` characters.
 
 
-.. py:function:: sum(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: sum(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the sum of a set of numbers.
 
@@ -2183,14 +2183,14 @@ Module Contents
    Returns uuid v4 as a string value.
 
 
-.. py:function:: var(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: var(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the sample variance of the argument.
 
    This is an alias for :py:func:`var_samp`.
 
 
-.. py:function:: var_pop(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: var_pop(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the population variance of the argument.
 
@@ -2201,7 +2201,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: var_samp(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: var_samp(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the sample variance of the argument.
 
@@ -2212,7 +2212,7 @@ Module Contents
    :param filter: If provided, only compute against rows for which the filter is True
 
 
-.. py:function:: var_sample(expression: datafusion.expr.Expr, filter: Optional[datafusion.expr.Expr] = None) -> datafusion.expr.Expr
+.. py:function:: var_sample(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr
 
    Computes the sample variance of the argument.
 
diff --git a/_sources/autoapi/datafusion/index.rst.txt b/_sources/autoapi/datafusion/index.rst.txt
index e4208b05c..59e6d2915 100644
--- a/_sources/autoapi/datafusion/index.rst.txt
+++ b/_sources/autoapi/datafusion/index.rst.txt
@@ -131,7 +131,8 @@ Package Contents
 
 
 
-.. py:class:: AggregateUDF(name: str, accumulator: Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str)
+.. py:class:: AggregateUDF(name: str, accumulator: collections.abc.Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str)
+              AggregateUDF(name: str, accumulator: AggregateUDFExportable, input_types: None = ..., return_type: None = ..., state_type: None = ..., volatility: None = ...)
 
    Class for performing scalar user-defined functions (UDF).
 
@@ -159,7 +160,7 @@ Package Contents
 
 
 
-   .. py:method:: from_pycapsule(func: AggregateUDFExportable) -> AggregateUDF
+   .. py:method:: from_pycapsule(func: AggregateUDFExportable | _typeshed.CapsuleType) -> AggregateUDF
       :staticmethod:
 
 
@@ -170,8 +171,10 @@ Package Contents
 
 
 
-   .. py:method:: udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: Optional[str] = None) -> Callable[Ellipsis, AggregateUDF]
-                  udaf(accum: Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: Optional[str] = None) -> AggregateUDF
+   .. py:method:: udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[Ellipsis, AggregateUDF]
+                  udaf(accum: collections.abc.Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) -> AggregateUDF
+                  udaf(accum: AggregateUDFExportable) -> AggregateUDF
+                  udaf(accum: _typeshed.CapsuleType) -> AggregateUDF
       :staticmethod:
 
 
@@ -564,7 +567,7 @@ Package Contents
 
 
 
-   .. py:method:: alias(name: str, metadata: Optional[dict[str, str]] = None) -> Expr
+   .. py:method:: alias(name: str, metadata: dict[str, str] | None = None) -> Expr
 
       Assign a name to the expression.
 
@@ -687,7 +690,7 @@ Package Contents
 
 
 
-   .. py:method:: cast(to: Union[pyarrow.DataType[Any], type]) -> Expr
+   .. py:method:: cast(to: pyarrow.DataType[Any] | type) -> Expr
 
       Cast to a new data type.
 
@@ -797,13 +800,13 @@ Package Contents
 
 
 
-   .. py:method:: fill_nan(value: Optional[Union[Any, Expr]] = None) -> Expr
+   .. py:method:: fill_nan(value: Any | Expr | None = None) -> Expr
 
       Fill NaN values with a provided value.
 
 
 
-   .. py:method:: fill_null(value: Optional[Union[Any, Expr]] = None) -> Expr
+   .. py:method:: fill_null(value: Any | Expr | None = None) -> Expr
 
       Fill NULL values with a provided value.
 
@@ -981,7 +984,7 @@ Package Contents
 
 
 
-   .. py:method:: order_by(*exprs: Union[Expr, SortExpr]) -> ExprFuncBuilder
+   .. py:method:: order_by(*exprs: Expr | SortExpr) -> ExprFuncBuilder
 
       Set the ordering for a window or aggregate function.
 
@@ -1015,7 +1018,7 @@ Package Contents
 
    .. py:method:: python_value() -> Any
 
-      Extracts the Expr value into a PyObject.
+      Extracts the Expr value into `Any`.
 
       This is only valid for literal expressions.
 
@@ -1351,7 +1354,7 @@ Package Contents
    .. py:attribute:: _raw_plan
 
 
-.. py:class:: ParquetColumnOptions(encoding: Optional[str] = None, dictionary_enabled: Optional[bool] = None, compression: Optional[str] = None, statistics_enabled: Optional[str] = None, bloom_filter_enabled: Optional[bool] = None, bloom_filter_fpp: Optional[float] = None, bloom_filter_ndv: Optional[int] = None)
+.. py:class:: ParquetColumnOptions(encoding: str | None = None, dictionary_enabled: bool | None = None, compression: str | None = None, statistics_enabled: str | None = None, bloom_filter_enabled: bool | None = None, bloom_filter_fpp: float | None = None, bloom_filter_ndv: int | None = None)
 
    Parquet options for individual columns.
 
@@ -1418,7 +1421,7 @@ Package Contents
 
 
 
-.. py:class:: ParquetWriterOptions(data_pagesize_limit: int = 1024 * 1024, write_batch_size: int = 1024, writer_version: str = '1.0', skip_arrow_metadata: bool = False, compression: Optional[str] = 'zstd(3)', compression_level: Optional[int] = None, dictionary_enabled: Optional[bool] = True, dictionary_page_size_limit: int = 1024 * 1024, statistics_enabled: Optional[str] = 'page', max_row_group_size: int = 1024 * 1024, created_by: str = 'datafusion-python', column_index_truncate_length: Optional[int] = 64, statistics_truncate_length: Optional[int] = None, data_page_row_count_limit: int = 20000, encoding: Optional[str] = None, bloom_filter_on_write: bool = False, bloom_filter_fpp: Optional[float] = None, bloom_filter_ndv: Optional[int] = None, allow_single_file_parallelism: bool = True, maximum_parallel_row_group_writers: int = 1, maximum_buffered_record_batches_per_stream: int = 2, column_specific_options: Optional[dict[str, ParquetColumnOptions]] = None)
+.. py:class:: ParquetWriterOptions(data_pagesize_limit: int = 1024 * 1024, write_batch_size: int = 1024, writer_version: str = '1.0', skip_arrow_metadata: bool = False, compression: str | None = 'zstd(3)', compression_level: int | None = None, dictionary_enabled: bool | None = True, dictionary_page_size_limit: int = 1024 * 1024, statistics_enabled: str | None = 'page', max_row_group_size: int = 1024 * 1024, created_by: str = 'datafusion-python', column_index_truncate_length: int | None = 64, statistics_truncate_length: int | None = None, data_page_row_count_limit: int = 20000, encoding: str | None = None, bloom_filter_on_write: bool = False, bloom_filter_fpp: float | None = None, bloom_filter_ndv: int | None = None, allow_single_file_parallelism: bool = True, maximum_parallel_row_group_writers: int = 1, maximum_buffered_record_batches_per_stream: int = 2, column_specific_options: dict[str, ParquetColumnOptions] | None = None)
 
    Advanced parquet writer options.
 
@@ -1601,6 +1604,23 @@ Package Contents
    See the :py:class:`RecordBatchStream` iterator for generating this class.
 
 
+   .. py:method:: __arrow_c_array__(requested_schema: object | None = None) -> tuple[object, object]
+
+      Export the record batch via the Arrow C Data Interface.
+
+      This allows zero-copy interchange with libraries that support the
+      `Arrow PyCapsule interface `_.
+
+      :param requested_schema: Attempt to provide the record batch using this
+                               schema. Only straightforward projections such as column
+                               selection or reordering are applied.
+
+      :returns: Two Arrow PyCapsule objects representing the ``ArrowArray`` and
+                ``ArrowSchema``.
+
+
+
    .. py:method:: to_pyarrow() -> pyarrow.RecordBatch
 
       Convert to :py:class:`pa.RecordBatch`.
@@ -1622,7 +1642,7 @@ Package Contents
 
    .. py:method:: __aiter__() -> typing_extensions.Self
 
-      Async iterator function.
+      Return an asynchronous iterator over record batches.
 
 
 
@@ -1630,19 +1650,19 @@ Package Contents
       :async:
 
 
-      Async iterator function.
+      Return the next :py:class:`RecordBatch` in the stream asynchronously.
 
 
 
    .. py:method:: __iter__() -> typing_extensions.Self
 
-      Iterator function.
+      Return an iterator over record batches.
 
 
 
    .. py:method:: __next__() -> RecordBatch
 
-      Iterator function.
+      Return the next :py:class:`RecordBatch` in the stream.
 
 
 
@@ -1821,7 +1841,7 @@ Package Contents
    .. py:attribute:: options_internal
 
 
-.. py:class:: ScalarUDF(name: str, func: Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)
+.. py:class:: ScalarUDF(name: str, func: collections.abc.Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)
 
    Class for performing scalar user-defined functions (UDF).
 
@@ -1859,8 +1879,8 @@ Package Contents
 
 
 
-   .. py:method:: udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: Optional[str] = None) -> Callable[Ellipsis, ScalarUDF]
-                  udf(func: Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: Optional[str] = None) -> ScalarUDF
+   .. py:method:: udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[Ellipsis, ScalarUDF]
+                  udf(func: collections.abc.Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) -> ScalarUDF
                   udf(func: ScalarUDFExportable) -> ScalarUDF
       :staticmethod:
 
@@ -2120,7 +2140,7 @@ Package Contents
       Returns the schema associated with this table.
 
 
-.. py:class:: TableFunction(name: str, func: Callable[[], any])
+.. py:class:: TableFunction(name: str, func: collections.abc.Callable[[], any])
 
    Class for performing user-defined table functions (UDTF).
 
@@ -2145,7 +2165,7 @@ Package Contents
 
 
 
-   .. py:method:: _create_table_udf(func: Callable[Ellipsis, Any], name: str) -> TableFunction
+   .. py:method:: _create_table_udf(func: collections.abc.Callable[Ellipsis, Any], name: str) -> TableFunction
       :staticmethod:
 
 
@@ -2153,7 +2173,7 @@ Package Contents
 
 
 
-   .. py:method:: _create_table_udf_decorator(name: Optional[str] = None) -> Callable[[Callable[[], WindowEvaluator]], Callable[Ellipsis, datafusion.expr.Expr]]
+   .. py:method:: _create_table_udf_decorator(name: str | None = None) -> collections.abc.Callable[[collections.abc.Callable[[], WindowEvaluator]], collections.abc.Callable[Ellipsis, datafusion.expr.Expr]]
       :staticmethod:
 
 
@@ -2161,8 +2181,8 @@ Package Contents
 
 
 
-   .. py:method:: udtf(name: str) -> Callable[Ellipsis, Any]
-                  udtf(func: Callable[[], Any], name: str) -> TableFunction
+   .. py:method:: udtf(name: str) -> collections.abc.Callable[Ellipsis, Any]
+                  udtf(func: collections.abc.Callable[[], Any], name: str) -> TableFunction
       :staticmethod:
 
 
@@ -2173,7 +2193,7 @@ Package Contents
    .. py:attribute:: _udtf
 
 
-.. py:class:: WindowFrame(units: str, start_bound: Optional[Any], end_bound: Optional[Any])
+.. py:class:: WindowFrame(units: str, start_bound: Any | None, end_bound: Any | None)
 
    Defines a window frame for performing window operations.
 
@@ -2215,7 +2235,7 @@ Package Contents
    .. py:attribute:: window_frame
 
 
-.. py:class:: WindowUDF(name: str, func: Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str)
+.. py:class:: WindowUDF(name: str, func: collections.abc.Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str)
 
    Class for performing window user-defined functions (UDF).
 
@@ -2243,7 +2263,7 @@ Package Contents
 
 
 
-   .. py:method:: _create_window_udf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: Optional[str] = None) -> WindowUDF
+   .. py:method:: _create_window_udf(func: collections.abc.Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) -> WindowUDF
       :staticmethod:
 
 
@@ -2251,7 +2271,7 @@ Package Contents
 
 
 
-   .. py:method:: _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: Optional[str] = None) -> Callable[[Callable[[], WindowEvaluator]], Callable[Ellipsis, datafusion.expr.Expr]]
+   .. py:method:: _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[[collections.abc.Callable[[], WindowEvaluator]], collections.abc.Callable[Ellipsis, datafusion.expr.Expr]]
       :staticmethod:
 
 
@@ -2259,7 +2279,7 @@ Package Contents
 
 
 
-   .. py:method:: _get_default_name(func: Callable) -> str
+   .. py:method:: _get_default_name(func: collections.abc.Callable) -> str
       :staticmethod:
 
 
@@ -2286,8 +2306,8 @@ Package Contents
 
 
 
-   .. py:method:: udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: Optional[str] = None) -> Callable[Ellipsis, WindowUDF]
-                  udwf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: Optional[str] = None) -> WindowUDF
+   .. py:method:: udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[Ellipsis, WindowUDF]
+                  udwf(func: collections.abc.Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) -> WindowUDF
       :staticmethod:
 
 
@@ -2366,12 +2386,12 @@ Package Contents
    ... )
 
 
-.. py:function:: lit(value) -> expr.Expr
+.. py:function:: lit(value: Any) -> expr.Expr
 
    Create a literal expression.
 
 
-.. py:function:: literal(value) -> expr.Expr
+.. py:function:: literal(value: Any) -> expr.Expr
 
    Create a literal expression.
 
diff --git a/_sources/autoapi/datafusion/record_batch/index.rst.txt b/_sources/autoapi/datafusion/record_batch/index.rst.txt
index ae91b4c63..f51a7e667 100644
--- a/_sources/autoapi/datafusion/record_batch/index.rst.txt
+++ b/_sources/autoapi/datafusion/record_batch/index.rst.txt
@@ -33,6 +33,23 @@ Module Contents
    See the :py:class:`RecordBatchStream` iterator for generating this class.
 
 
+   .. py:method:: __arrow_c_array__(requested_schema: object | None = None) -> tuple[object, object]
+
+      Export the record batch via the Arrow C Data Interface.
+
+      This allows zero-copy interchange with libraries that support the
+      `Arrow PyCapsule interface `_.
+
+      :param requested_schema: Attempt to provide the record batch using this
+                               schema. Only straightforward projections such as column
+                               selection or reordering are applied.
+
+      :returns: Two Arrow PyCapsule objects representing the ``ArrowArray`` and
+                ``ArrowSchema``.
+
+
+
    .. py:method:: to_pyarrow() -> pyarrow.RecordBatch
 
       Convert to :py:class:`pa.RecordBatch`.
@@ -54,7 +71,7 @@ Module Contents
 
    .. py:method:: __aiter__() -> typing_extensions.Self
 
-      Async iterator function.
+      Return an asynchronous iterator over record batches.
 
 
 
@@ -62,19 +79,19 @@ Module Contents
       :async:
 
 
-      Async iterator function.
+      Return the next :py:class:`RecordBatch` in the stream asynchronously.
 
 
 
    .. py:method:: __iter__() -> typing_extensions.Self
 
-      Iterator function.
+      Return an iterator over record batches.
 
 
 
    .. py:method:: __next__() -> RecordBatch
 
-      Iterator function.
+      Return the next :py:class:`RecordBatch` in the stream.
 
 
 
diff --git a/_sources/autoapi/datafusion/user_defined/index.rst.txt b/_sources/autoapi/datafusion/user_defined/index.rst.txt
index 591d4cda9..784a39c75 100644
--- a/_sources/autoapi/datafusion/user_defined/index.rst.txt
+++ b/_sources/autoapi/datafusion/user_defined/index.rst.txt
@@ -38,6 +38,14 @@ Classes
    datafusion.user_defined.WindowUDFExportable
 
 
+Functions
+---------
+
+.. autoapisummary::
+
+   datafusion.user_defined._is_pycapsule
+
+
 Module Contents
 ---------------
 
@@ -78,7 +86,8 @@ Module Contents
 
 
 
-.. py:class:: AggregateUDF(name: str, accumulator: Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str)
+.. py:class:: AggregateUDF(name: str, accumulator: collections.abc.Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str)
+              AggregateUDF(name: str, accumulator: AggregateUDFExportable, input_types: None = ..., return_type: None = ..., state_type: None = ..., volatility: None = ...)
 
    Class for performing scalar user-defined functions (UDF).
 
@@ -106,7 +115,7 @@ Module Contents
 
 
 
-   .. py:method:: from_pycapsule(func: AggregateUDFExportable) -> AggregateUDF
+   .. py:method:: from_pycapsule(func: AggregateUDFExportable | _typeshed.CapsuleType) -> AggregateUDF
       :staticmethod:
 
 
@@ -117,8 +126,10 @@ Module Contents
 
 
 
-   .. py:method:: udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: Optional[str] = None) -> Callable[Ellipsis, AggregateUDF]
-                  udaf(accum: Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: Optional[str] = None) -> AggregateUDF
+   .. py:method:: udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[Ellipsis, AggregateUDF]
+                  udaf(accum: collections.abc.Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) -> AggregateUDF
+                  udaf(accum: AggregateUDFExportable) -> AggregateUDF
+                  udaf(accum: _typeshed.CapsuleType) -> AggregateUDF
       :staticmethod:
 
 
@@ -206,7 +217,7 @@ Module Contents
    .. py:method:: __datafusion_aggregate_udf__() -> object
 
 
-.. py:class:: ScalarUDF(name: str, func: Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)
+.. py:class:: ScalarUDF(name: str, func: collections.abc.Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)
 
    Class for performing scalar user-defined functions (UDF).
 
@@ -244,8 +255,8 @@ Module Contents
 
 
 
-   .. py:method:: udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: Optional[str] = None) -> Callable[Ellipsis, ScalarUDF]
-                  udf(func: Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: Optional[str] = None) -> ScalarUDF
+   .. py:method:: udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[Ellipsis, ScalarUDF]
+                  udf(func: collections.abc.Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) -> ScalarUDF
                   udf(func: ScalarUDFExportable) -> ScalarUDF
       :staticmethod:
 
@@ -308,7 +319,7 @@ Module Contents
    .. py:method:: __datafusion_scalar_udf__() -> object
 
 
-.. py:class:: TableFunction(name: str, func: Callable[[], any])
+.. py:class:: TableFunction(name: str, func: collections.abc.Callable[[], any])
 
    Class for performing user-defined table functions (UDTF).
 
@@ -333,7 +344,7 @@ Module Contents
 
 
 
-   .. py:method:: _create_table_udf(func: Callable[Ellipsis, Any], name: str) -> TableFunction
+   .. py:method:: _create_table_udf(func: collections.abc.Callable[Ellipsis, Any], name: str) -> TableFunction
       :staticmethod:
 
 
@@ -341,7 +352,7 @@ Module Contents
 
 
 
-   .. py:method:: _create_table_udf_decorator(name: Optional[str] = None) -> Callable[[Callable[[], WindowEvaluator]], Callable[Ellipsis, datafusion.expr.Expr]]
+   .. py:method:: _create_table_udf_decorator(name: str | None = None) -> collections.abc.Callable[[collections.abc.Callable[[], WindowEvaluator]], collections.abc.Callable[Ellipsis, datafusion.expr.Expr]]
       :staticmethod:
 
 
@@ -349,8 +360,8 @@ Module Contents
 
 
 
-   .. py:method:: udtf(name: str) -> Callable[Ellipsis, Any]
-                  udtf(func: Callable[[], Any], name: str) -> TableFunction
+   .. py:method:: udtf(name: str) -> collections.abc.Callable[Ellipsis, Any]
+                  udtf(func: collections.abc.Callable[[], Any], name: str) -> TableFunction
       :staticmethod:
 
 
@@ -589,7 +600,7 @@ Module Contents
 
 
 
-.. py:class:: WindowUDF(name: str, func: Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str)
+.. py:class:: WindowUDF(name: str, func: collections.abc.Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str)
 
    Class for performing window user-defined functions (UDF).
 
@@ -617,7 +628,7 @@ Module Contents
 
 
 
-   .. py:method:: _create_window_udf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: Optional[str] = None) -> WindowUDF
+   .. py:method:: _create_window_udf(func: collections.abc.Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) -> WindowUDF
       :staticmethod:
 
 
@@ -625,7 +636,7 @@ Module Contents
 
 
 
-   .. py:method:: _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: Optional[str] = None) -> Callable[[Callable[[], WindowEvaluator]], Callable[Ellipsis, datafusion.expr.Expr]]
+   .. py:method:: _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[[collections.abc.Callable[[], WindowEvaluator]], collections.abc.Callable[Ellipsis, datafusion.expr.Expr]]
       :staticmethod:
 
 
@@ -633,7 +644,7 @@ Module Contents
 
 
 
-   .. py:method:: _get_default_name(func: Callable) -> str
+   .. py:method:: _get_default_name(func: collections.abc.Callable) -> str
       :staticmethod:
 
 
@@ -660,8 +671,8 @@ Module Contents
 
 
 
-   .. py:method:: udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: Optional[str] = None) -> Callable[Ellipsis, WindowUDF]
-                  udwf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: Optional[str] = None) -> WindowUDF
+   .. py:method:: udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[Ellipsis, WindowUDF]
+                  udwf(func: collections.abc.Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) -> WindowUDF
       :staticmethod:
 
 
@@ -728,6 +739,11 @@ Module Contents
    .. py:method:: __datafusion_window_udf__() -> object
 
 
+.. py:function:: _is_pycapsule(value: object) -> TypeGuard[_typeshed.CapsuleType]
+
+   Return ``True`` when ``value`` is a CPython ``PyCapsule``.
+
+
 .. py:data:: _R
 
 .. py:data:: udaf
diff --git a/_sources/user-guide/common-operations/joins.rst.txt b/_sources/user-guide/common-operations/joins.rst.txt
index 40d922150..1d9d70385 100644
--- a/_sources/user-guide/common-operations/joins.rst.txt
+++ b/_sources/user-guide/common-operations/joins.rst.txt
@@ -101,4 +101,36 @@ the right table.
 
 .. ipython:: python
 
-    left.join(right, left_on="customer_id", right_on="id", how="anti")
\ No newline at end of file
+    left.join(right, left_on="customer_id", right_on="id", how="anti")
+
+Duplicate Keys
+--------------
+
+It is common to join two DataFrames on a common column name. Starting in
+version 51.0.0, ``datafusion-python``` will now coalesce on column with identical names by
+default. This reduces problems with ambiguous column selection after joins.
+You can disable this feature by setting the parameter ``coalesce_duplicate_keys``
+to ``False``.
+
+.. ipython:: python
+
+    left = ctx.from_pydict(
+        {
+            "id": [1, 2, 3],
+            "customer": ["Alice", "Bob", "Charlie"],
+        }
+    )
+
+    right = ctx.from_pylist([
+        {"id": 1, "name": "CityCabs"},
+        {"id": 2, "name": "MetroRide"},
+        {"id": 5, "name": "UrbanGo"},
+    ])
+
+    left.join(right, "id", how="inner")
+
+In contrast to the above example, if we wish to get both columns:
+
+.. ipython:: python
+
+    left.join(right, "id", how="inner", coalesce_duplicate_keys=False)
diff --git a/_sources/user-guide/configuration.rst.txt b/_sources/user-guide/configuration.rst.txt
index 5425a040d..f8e613cd4 100644
--- a/_sources/user-guide/configuration.rst.txt
+++ b/_sources/user-guide/configuration.rst.txt
@@ -15,6 +15,8 @@
 .. specific language governing permissions and limitations
 .. under the License.
 
+.. _configuration:
+
 Configuration
 =============
 
diff --git a/_sources/user-guide/dataframe/index.rst.txt b/_sources/user-guide/dataframe/index.rst.txt
index 1387db0bd..510bcbc68 100644
--- a/_sources/user-guide/dataframe/index.rst.txt
+++ b/_sources/user-guide/dataframe/index.rst.txt
@@ -95,8 +95,9 @@ DataFusion's DataFrame API offers a wide range of operations:
     # Select with expressions
     df = df.select(column("a") + column("b"), column("a") - column("b"))
     
-    # Filter rows
+    # Filter rows (expressions or SQL strings)
     df = df.filter(column("age") > literal(25))
+    df = df.filter("age > 25")
     
     # Add computed columns
     df = df.with_column("full_name", column("first_name") + literal(" ") + column("last_name"))
@@ -195,10 +196,121 @@ To materialize the results of your DataFrame operations:
     
     # Display results
     df.show()                         # Print tabular format to console
-    
+
     # Count rows
     count = df.count()
 
+    # Collect a single column of data as a PyArrow Array
+    arr = df.collect_column("age")
+
+Zero-copy streaming to Arrow-based Python libraries
+---------------------------------------------------
+
+DataFusion DataFrames implement the ``__arrow_c_stream__`` protocol, enabling
+zero-copy, lazy streaming into Arrow-based Python libraries. With the streaming
+protocol, batches are produced on demand.
+
+.. note::
+
+    The protocol is implementation-agnostic and works with any Python library
+    that understands the Arrow C streaming interface (for example, PyArrow
+    or other Arrow-compatible implementations). The sections below provide a
+    short PyArrow-specific example and general guidance for other
+    implementations.
+
+PyArrow
+-------
+
+.. code-block:: python
+
+    import pyarrow as pa
+
+    # Create a PyArrow RecordBatchReader without materializing all batches
+    reader = pa.RecordBatchReader.from_stream(df)
+    for batch in reader:
+        ...  # process each batch as it is produced
+
+DataFrames are also iterable, yielding :class:`datafusion.RecordBatch`
+objects lazily so you can loop over results directly without importing
+PyArrow:
+
+.. code-block:: python
+
+    for batch in df:
+        ...  # each batch is a ``datafusion.RecordBatch``
+
+Each batch exposes ``to_pyarrow()``, allowing conversion to a PyArrow
+table. ``pa.table(df)`` collects the entire DataFrame eagerly into a
+PyArrow table:
+
+.. code-block:: python
+
+    import pyarrow as pa
+    table = pa.table(df)
+
+Asynchronous iteration is supported as well, allowing integration with
+``asyncio`` event loops:
+
+.. code-block:: python
+
+    async for batch in df:
+        ...  # process each batch as it is produced
+
+To work with the stream directly, use ``execute_stream()``, which returns a
+:class:`~datafusion.RecordBatchStream`.
+
+.. code-block:: python
+
+    stream = df.execute_stream()
+    for batch in stream:
+        ...
+
+Execute as Stream
+^^^^^^^^^^^^^^^^^
+
+For finer control over streaming execution, use
+:py:meth:`~datafusion.DataFrame.execute_stream` to obtain a
+:py:class:`datafusion.RecordBatchStream`:
+
+.. code-block:: python
+
+    stream = df.execute_stream()
+    for batch in stream:
+        ...  # process each batch as it is produced
+
+.. tip::
+
+    To get a PyArrow reader instead, call
+
+    ``pa.RecordBatchReader.from_stream(df)``.
+    
+When partition boundaries are important,
+:py:meth:`~datafusion.DataFrame.execute_stream_partitioned`
+returns an iterable of :py:class:`datafusion.RecordBatchStream` objects, one per
+partition:
+
+.. code-block:: python
+
+    for stream in df.execute_stream_partitioned():
+        for batch in stream:
+            ...  # each stream yields RecordBatches
+
+To process partitions concurrently, first collect the streams into a list
+and then poll each one in a separate ``asyncio`` task:
+
+.. code-block:: python
+
+    import asyncio
+
+    async def consume(stream):
+        async for batch in stream:
+            ...
+
+    streams = list(df.execute_stream_partitioned())
+    await asyncio.gather(*(consume(s) for s in streams))
+
+See :doc:`../io/arrow` for additional details on the Arrow interface.
+
 HTML Rendering
 --------------
 
diff --git a/_sources/user-guide/io/arrow.rst.txt b/_sources/user-guide/io/arrow.rst.txt
index d571aa99c..9196fcea7 100644
--- a/_sources/user-guide/io/arrow.rst.txt
+++ b/_sources/user-guide/io/arrow.rst.txt
@@ -60,14 +60,16 @@ Exporting from DataFusion
 DataFusion DataFrames implement ``__arrow_c_stream__`` PyCapsule interface, so any
 Python library that accepts these can import a DataFusion DataFrame directly.
 
-.. warning::
-    It is important to note that this will cause the DataFrame execution to happen, which may be
-    a time consuming task. That is, you will cause a
-    :py:func:`datafusion.dataframe.DataFrame.collect` operation call to occur.
+Invoking ``__arrow_c_stream__`` triggers execution of the underlying query, but
+batches are yielded incrementally rather than materialized all at once in memory.
+Consumers can process the stream as it arrives. The stream executes lazily,
+letting downstream readers pull batches on demand.
 
 
 .. ipython:: python
 
+    from datafusion import col, lit
+
     df = df.select((col("a") * lit(1.5)).alias("c"), lit("df").alias("d"))
     pa.table(df)
 
diff --git a/_sources/user-guide/sql.rst.txt b/_sources/user-guide/sql.rst.txt
index 6fa7f0c6a..b4bfb9611 100644
--- a/_sources/user-guide/sql.rst.txt
+++ b/_sources/user-guide/sql.rst.txt
@@ -23,17 +23,100 @@ DataFusion also offers a SQL API, read the full reference `here `_,
+but allow passing named parameters into a SQL query. Consider this simple
+example.
+
+.. ipython:: python
+
+    def show_attacks(ctx: SessionContext, threshold: int) -> None:
+        ctx.sql(
+            'SELECT "Name", "Attack" FROM pokemon WHERE "Attack" > $val', val=threshold
+        ).show(num=5)
+    show_attacks(ctx, 75)
+
+When passing parameters like the example above we convert the Python objects
+into their string representation. We also have special case handling
+for :py:class:`~datafusion.dataframe.DataFrame` objects, since they cannot simply
+be turned into string representations for an SQL query. In these cases we
+will register a temporary view in the :py:class:`~datafusion.context.SessionContext`
+using a generated table name.
+
+The formatting for passing string replacement objects is to precede the
+variable name with a single ``$``. This works for all dialects in
+the SQL parser except ``hive`` and ``mysql``. Since these dialects do not
+support named placeholders, we are unable to do this type of replacement.
+We recommend either switching to another dialect or using Python
+f-string style replacement.
+
+.. warning::
+
+    To support DataFrame parameterized queries, your session must support
+    registration of temporary views. The default
+    :py:class:`~datafusion.catalog.CatalogProvider` and
+    :py:class:`~datafusion.catalog.SchemaProvider` do have this capability.
+    If you have implemented custom providers, it is important that temporary
+    views do not persist across :py:class:`~datafusion.context.SessionContext`
+    or you may get unintended consequences.
+
+The following example shows passing in both a :py:class:`~datafusion.dataframe.DataFrame`
+object as well as a Python object to be used in parameterized replacement.
+
+.. ipython:: python
+
+    def show_column(
+        ctx: SessionContext, column: str, df: DataFrame, threshold: int
+    ) -> None:
+        ctx.sql(
+            'SELECT "Name", $col FROM $df WHERE $col > $val',
+            col=column,
+            df=df,
+            val=threshold,
+        ).show(num=5)
+    df = ctx.table("pokemon")
+    show_column(ctx, '"Defense"', df, 75)
+
+The approach implemented for conversion of variables into a SQL query
+relies on string conversion. This has the potential for data loss,
+specifically for cases like floating point numbers. If you need to pass
+variables into a parameterized query and it is important to maintain the
+original value without conversion to a string, then you can use the
+optional parameter ``param_values`` to specify these. This parameter
+expects a dictionary mapping from the parameter name to a Python
+object. Those objects will be cast into a
+`PyArrow Scalar Value `_.
+
+Using ``param_values`` will rely on the SQL dialect you have configured
+for your session. This can be set using the :ref:`configuration options `
+of your :py:class:`~datafusion.context.SessionContext`. Similar to how
+`prepared statements `_
+work, these parameters are limited to places where you would pass in a
+scalar value, such as a comparison.
+
+.. ipython:: python
+
+    def param_attacks(ctx: SessionContext, threshold: int) -> None:
+        ctx.sql(
+            'SELECT "Name", "Attack" FROM pokemon WHERE "Attack" > $val',
+            param_values={"val": threshold},
+        ).show(num=5)
+    param_attacks(ctx, 75)
diff --git a/autoapi/datafusion/context/index.html b/autoapi/datafusion/context/index.html
index cfd76c86e..f8aefac95 100644
--- a/autoapi/datafusion/context/index.html
+++ b/autoapi/datafusion/context/index.html
@@ -2282,8 +2282,11 @@ 
      Module Contents
 
      
-sql(query: str, options: SQLOptions | None = None) → datafusion.dataframe.DataFrame
      
+sql(query: str, options: SQLOptions | None = None, param_values: dict[str, Any] | None = None, **named_params: Any) → datafusion.dataframe.DataFrame
 
      Create a DataFrame from SQL query text.
      
+
      See the online documentation for a description of how to perform
+parameterized substitution via either the param_values option
+or passing in named_params.
      
 
      Note: This API implements DDL statements such as CREATE TABLE and
 CREATE VIEW and DML statements such as INSERT INTO with in-memory
 default implementation.See
@@ -2293,6 +2296,9 @@ 
      Module Contents
        
 
      • query – SQL query text.
        • 
 
      • options – If provided, the query will be validated against these options.
        • 
+
      • param_values – Provides substitution of scalar values in the query
+after parsing.
        • 
+
      • named_params – Provides string or DataFrame substitution in the query string.
        • 
 
      
 
      
 
      Returns:
      
@@ -2303,7 +2309,7 @@ 
      Module Contents
 
      
-sql_with_options(query: str, options: SQLOptions) → datafusion.dataframe.DataFrame
      
+sql_with_options(query: str, options: SQLOptions, param_values: dict[str, Any] | None = None, **named_params: Any) → datafusion.dataframe.DataFrame
 
      Create a DataFrame from SQL query text.
      
 
      This function will first validate that the query is allowed by the
 provided options.
      
@@ -2312,6 +2318,9 @@ 
      Module Contents
        
 
      • query – SQL query text.
        • 
 
      • options – SQL options.
        • 
+
      • param_values – Provides substitution of scalar values in the query
+after parsing.
        • 
+
      • named_params – Provides string or DataFrame substitution in the query string.
        • 
 
      
 
      
 
      Returns:
      
diff --git a/autoapi/datafusion/dataframe/index.html b/autoapi/datafusion/dataframe/index.html
index b302fbec6..15d90ff7d 100644
--- a/autoapi/datafusion/dataframe/index.html
+++ b/autoapi/datafusion/dataframe/index.html
@@ -518,6 +518,15 @@
      
           
     
        
+     
      • 
+      
+       
+        
+         DataFrame.__aiter__()
+        
+       
+      
+     
        • 
      
      • 
       
        
@@ -536,6 +545,15 @@
        
       
      
        • 
+     
      • 
+      
+       
+        
+         DataFrame.__iter__()
+        
+       
+      
+     
        • 
      
      • 
       
        
@@ -590,6 +608,15 @@
        
       
      
        • 
+     
      • 
+      
+       
+        
+         DataFrame.collect_column()
+        
+       
+      
+     
        • 
      
      • 
       
        
@@ -833,6 +860,15 @@
        
       
      
        • 
+     
      • 
+      
+       
+        
+         DataFrame.select_exprs()
+        
+       
+      
+     
        • 
      
      • 
       
        
@@ -1475,32 +1511,56 @@ 
        Module Contents
 class datafusion.dataframe.DataFrame(df: datafusion._internal.DataFrame)
 
        Two dimensional table representation of data.
        
+
        DataFrame objects are iterable; iterating over a DataFrame yields
+datafusion.RecordBatch instances lazily.
        
 
        See Concepts in the online documentation for more information.
        
 
        This constructor is not to be used by the end user.
        
 
        See SessionContext for methods to
 create a DataFrame.
        
+
        
+
        
+__aiter__() → collections.abc.AsyncIterator[datafusion.record_batch.RecordBatch]
        
+
        Return an async iterator over this DataFrame’s record batches.
        
+
        We’re using __aiter__ because we support Python < 3.10 where aiter() is not
+available.
        
+
        
+
 
        
 
        
 __arrow_c_stream__(requested_schema: object | None = None) → object
        
-
        Export an Arrow PyCapsule Stream.
        
-
        This will execute and collect the DataFrame. We will attempt to respect the
-requested schema, but only trivial transformations will be applied such as only
-returning the fields listed in the requested schema if their data types match
-those in the DataFrame.
        
+
        Export the DataFrame as an Arrow C Stream.
        
+
        The DataFrame is executed using DataFusion’s streaming APIs and exposed via
+Arrow’s C Stream interface. Record batches are produced incrementally, so the
+full result set is never materialized in memory.
        
+
        When requested_schema is provided, DataFusion applies only simple
+projections such as selecting a subset of existing columns or reordering
+them. Column renaming, computed expressions, or type coercion are not
+supported through this interface.
        
 
        
 
        Parameters:
        
-
        requested_schema – Attempt to provide the DataFrame using this schema.
        
+
        requested_schema – Either a pyarrow.Schema or an Arrow C
+Schema capsule (PyCapsule) produced by
+schema._export_to_c_capsule(). The DataFrame will attempt to
+align its output with the fields and order specified by this schema.
        
 
        
 
        Returns:
        
-
        Arrow PyCapsule object.
        
+
        Arrow PyCapsule object representing an ArrowArrayStream.
        
 
        
 
        
+
        For practical usage patterns, see the Apache Arrow streaming
+documentation: https://arrow.apache.org/docs/python/ipc.html#streaming.
        
+
        For details on DataFusion’s Arrow integration and DataFrame streaming,
+see the user guide (user-guide/io/arrow and user-guide/dataframe/index).
        
+
        Notes
        
+
        The Arrow C Data Interface PyCapsule details are documented by Apache
+Arrow and can be found at:
+https://arrow.apache.org/docs/format/CDataInterface/PyCapsuleInterface.html
        
 
        
 
 
        
 
        
 __getitem__(key: str | list[str]) → DataFrame
        
-
        Return a new :py:class`DataFrame` with the specified column or columns.
        
+
        Return a new DataFrame with the specified column or columns.
        
 
        
 
        Parameters:
        
 
        key – Column name or list of column names to select.
        
@@ -1511,6 +1571,12 @@ 
        Module Contents
+
        
+__iter__() → collections.abc.Iterator[datafusion.record_batch.RecordBatch]
        
+
        Return an iterator over this DataFrame’s record batches.
        
+
        
+
 
        
 
        
 __repr__() → str
        
@@ -1583,6 +1649,12 @@ 
        Module Contents
+
        
+collect_column(column_name: str) → pyarrow.Array | pyarrow.ChunkedArray
        
+
        Executes this DataFrame for a single column.
        
+
        
+
 
        
 
        
 collect_partitioned() → list[list[pyarrow.RecordBatch]]
        
@@ -1763,23 +1835,24 @@ 
        Module Contents
 
        
-filter(*predicates: datafusion.expr.Expr) → DataFrame
        
+filter(*predicates: datafusion.expr.Expr | str) → DataFrame
 
        Return a DataFrame for which predicate evaluates to True.
        
 
        Rows for which predicate evaluates to False or None are filtered
 out. If more than one predicate is provided, these predicates will be
-combined as a logical AND. Each predicate must be an
+combined as a logical AND. Each predicate can be an
 Expr created using helper functions such as
-datafusion.col() or datafusion.lit().
-If more complex logic is required, see the logical operations in
-functions.
        
+datafusion.col() or datafusion.lit(), or a SQL expression string
+that will be parsed against the DataFrame schema. If more complex logic is
+required, see the logical operations in functions.
        
 
        Example:
        
 
        from datafusion import col, lit
 df.filter(col("a") > lit(1))
+df.filter("a > 1")
 
        
 
        
 
        
 
        Parameters:
        
-
        predicates – Predicate expression(s) to filter the DataFrame.
        
+
        predicates – Predicate expression(s) or SQL strings to filter the DataFrame.
        
 
        
 
        Returns:
        
 
        DataFrame after filtering.
        
@@ -1818,7 +1891,7 @@ 
        Module Contents
 
        
-into_view() → datafusion.catalog.Table
        
+into_view(temporary: bool = False) → datafusion.catalog.Table
 
        Convert DataFrame into a Table.
        
 
        Examples
        
 
        >>> from datafusion import SessionContext
@@ -1834,11 +1907,11 @@ 
        Module Contents
 
        
-join(right: DataFrame, on: str | collections.abc.Sequence[str], how: Literal['inner', 'left', 'right', 'full', 'semi', 'anti'] = 'inner', *, left_on: None = None, right_on: None = None, join_keys: None = None) → DataFrame
        
+join(right: DataFrame, on: str | collections.abc.Sequence[str], how: Literal['inner', 'left', 'right', 'full', 'semi', 'anti'] = 'inner', *, left_on: None = None, right_on: None = None, join_keys: None = None, coalesce_duplicate_keys: bool = True) → DataFrame
 
        
-join(right: DataFrame, on: None = None, how: Literal['inner', 'left', 'right', 'full', 'semi', 'anti'] = 'inner', *, left_on: str | collections.abc.Sequence[str], right_on: str | collections.abc.Sequence[str], join_keys: tuple[list[str], list[str]] | None = None) → DataFrame
        
+join(right: DataFrame, on: None = None, how: Literal['inner', 'left', 'right', 'full', 'semi', 'anti'] = 'inner', *, left_on: str | collections.abc.Sequence[str], right_on: str | collections.abc.Sequence[str], join_keys: tuple[list[str], list[str]] | None = None, coalesce_duplicate_keys: bool = True) → DataFrame
 
        
-join(right: DataFrame, on: None = None, how: Literal['inner', 'left', 'right', 'full', 'semi', 'anti'] = 'inner', *, join_keys: tuple[list[str], list[str]], left_on: None = None, right_on: None = None) → DataFrame
        
+join(right: DataFrame, on: None = None, how: Literal['inner', 'left', 'right', 'full', 'semi', 'anti'] = 'inner', *, join_keys: tuple[list[str], list[str]], left_on: None = None, right_on: None = None, coalesce_duplicate_keys: bool = True) → DataFrame
 
        Join this DataFrame with another DataFrame.
        
 
        on has to be provided or both left_on and right_on in conjunction.
        
 
        
@@ -1850,6 +1923,9 @@ 
        Module Contentson fields.
        • 
 
      • join_keys – Tuple of two lists of column names to join on. [Deprecated]
        • 
 
      
 
@@ -1966,12 +2042,13 @@ 
      Module Contents
 
      
-repartition_by_hash(*exprs: datafusion.expr.Expr, num: int) → DataFrame
      
+repartition_by_hash(*exprs: datafusion.expr.Expr | str, num: int) → DataFrame
 
      Repartition a DataFrame using a hash partitioning scheme.
      
 
      
 
      Parameters:
      
 
        
-
      • exprs – Expressions to evaluate and perform hashing on.
        • 
+
      • exprs – Expressions or a SQL expression string to evaluate
+and perform hashing on.
        • 
 
      • num – Number of partitions to repartition the DataFrame into.
        • 
 
      
 
      
@@ -2027,6 +2104,19 @@ 
      Module Contents
+
      
+select_exprs(*args: str) → DataFrame
      
+
      Project arbitrary list of expression strings into a new DataFrame.
      
+
      This method will parse string expressions into logical plan expressions.
+The output DataFrame has one column for each expression.
      
+
      
+
      Returns:
      
+
      DataFrame only containing the specified columns.
      
+
      
+
      
+
      
+
 
      
 
      
 show(num: int = 20) → None
      
@@ -2127,7 +2217,7 @@ 
      Module Contents
 
      
-transform(func: Callable[Ellipsis, DataFrame], *args: Any) → DataFrame
      
+transform(func: collections.abc.Callable[Ellipsis, DataFrame], *args: Any) → DataFrame
 
      Apply a function to the current DataFrame which returns another DataFrame.
      
 
      This is useful for chaining together multiple functions. For example:
      
 
      def add_3(df: DataFrame) -> DataFrame:
@@ -2209,10 +2299,11 @@ 
      Module Contents
 
      
-with_column(name: str, expr: datafusion.expr.Expr) → DataFrame
      
+with_column(name: str, expr: datafusion.expr.Expr | str) → DataFrame
 
      Add an additional column to the DataFrame.
      
 
      The expr must be an Expr constructed with
-datafusion.col() or datafusion.lit().
      
+datafusion.col() or datafusion.lit(), or a SQL expression
+string that will be parsed against the DataFrame schema.
      
 
      Example:
      
 
      from datafusion import col, lit
 df.with_column("b", col("a") + lit(1))
@@ -2253,11 +2344,12 @@ 
      Module Contents
 
      
-with_columns(*exprs: datafusion.expr.Expr | Iterable[datafusion.expr.Expr], **named_exprs: datafusion.expr.Expr) → DataFrame
      
+with_columns(*exprs: datafusion.expr.Expr | str | collections.abc.Iterable[datafusion.expr.Expr | str], **named_exprs: datafusion.expr.Expr | str) → DataFrame
 
      Add columns to the DataFrame.
      
-
      By passing expressions, iterables of expressions, or named expressions.
+
      By passing expressions, iterables of expressions, string SQL expressions,
+or named expressions.
 All expressions must be Expr objects created via
-datafusion.col() or datafusion.lit().
+datafusion.col() or datafusion.lit(), or SQL expression strings.
 To pass named expressions use the form name=Expr.
      
 
      Example usage: The following will add 4 columns labeled a, b, c,
 and d:
      
@@ -2267,12 +2359,21 @@ 
      Module Contents[lit(1).alias("b"), col("y").alias("c")],
     d=lit(3)
 )
+
+Equivalent example using just SQL strings:
+
+df = df.with_columns(
+    "x as a",
+    ["1 as b", "y as c"],
+    d="3"
+)
 
      
 
      
 
      
 
      Parameters:
      
 
        
-
      • exprs – Either a single expression or an iterable of expressions to add.
        • 
+
      • exprs – Either a single expression, an iterable of expressions to add or
+SQL expression strings.
        • 
 
      • named_exprs – Named expressions in the form of name=expr
        • 
 
      
 
      
diff --git a/autoapi/datafusion/dataframe_formatter/index.html b/autoapi/datafusion/dataframe_formatter/index.html
index 2fa77cd18..615c37da5 100644
--- a/autoapi/datafusion/dataframe_formatter/index.html
+++ b/autoapi/datafusion/dataframe_formatter/index.html
@@ -1181,7 +1181,7 @@ 
      Module Contents
 
      
-set_custom_cell_builder(builder: Callable[[Any, int, int, str], str]) → None
      
+set_custom_cell_builder(builder: collections.abc.Callable[[Any, int, int, str], str]) → None
 
      Set a custom cell builder function.
      
 
      
 
      Parameters:
      
@@ -1192,7 +1192,7 @@ 
      Module Contents
 
      
-set_custom_header_builder(builder: Callable[[Any], str]) → None
      
+set_custom_header_builder(builder: collections.abc.Callable[[Any], str]) → None
 
      Set a custom header builder function.
      
 
      
 
      Parameters:
      
@@ -1203,12 +1203,12 @@ 
      Module Contents
 
      
-_custom_cell_builder: Callable[[Any, int, int, str], str] | None = None
      
+_custom_cell_builder: collections.abc.Callable[[Any, int, int, str], str] | None = None
 
      
 
 
      
 
      
-_custom_header_builder: Callable[[Any], str] | None = None
      
+_custom_header_builder: collections.abc.Callable[[Any], str] | None = None
 
      
 
 
      
diff --git a/autoapi/datafusion/expr/index.html b/autoapi/datafusion/expr/index.html
index 692067365..e55ea8720 100644
--- a/autoapi/datafusion/expr/index.html
+++ b/autoapi/datafusion/expr/index.html
@@ -3518,7 +3518,7 @@ 
      Returns:
 
      
 python_value() → Any
      
-
      Extracts the Expr value into a PyObject.
      
+
      Extracts the Expr value into Any.
      
 
      This is only valid for literal expressions.
      
 
      
 
      Returns:
      
@@ -3948,7 +3948,7 @@ 
      Returns:
 
      
-datafusion.expr.ensure_expr_list(exprs: Iterable[Expr | Iterable[Expr]]) → list[datafusion._internal.expr.Expr]
      
+datafusion.expr.ensure_expr_list(exprs: collections.abc.Iterable[Expr | collections.abc.Iterable[Expr]]) → list[datafusion._internal.expr.Expr]
 
      Flatten an iterable of expressions, validating each via ensure_expr.
      
 
      
 
      Parameters:
      
diff --git a/autoapi/datafusion/index.html b/autoapi/datafusion/index.html
index fab8b5105..d306bc467 100644
--- a/autoapi/datafusion/index.html
+++ b/autoapi/datafusion/index.html
@@ -2252,6 +2252,15 @@
      
     
     
        
+     
      • 
+      
+       
+        
+         RecordBatch.__arrow_c_array__()
+        
+       
+      
+     
        • 
      
      • 
       
        
@@ -3274,7 +3283,9 @@ 
        Package Contents
 
        
-class datafusion.AggregateUDF(name: str, accumulator: Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str)
        
+class datafusion.AggregateUDF(name: str, accumulator: collections.abc.Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str)
+
        
+class datafusion.AggregateUDF(name: str, accumulator: AggregateUDFExportable, input_types: None = ..., return_type: None = ..., state_type: None = ..., volatility: None = ...)
        
 
        Class for performing scalar user-defined functions (UDF).
        
 
        Aggregate UDFs operate on a group of rows and return a single value. See
 also ScalarUDF for operating on a row by row basis.
        
@@ -3297,7 +3308,7 @@ 
        Package Contents
 
        
-static from_pycapsule(func: AggregateUDFExportable) → AggregateUDF
        
+static from_pycapsule(func: AggregateUDFExportable | _typeshed.CapsuleType) → AggregateUDF
 
        Create an Aggregate UDF from AggregateUDF PyCapsule object.
        
 
        This function will instantiate a Aggregate UDF that uses a DataFusion
 AggregateUDF that is exported via the FFI bindings.
        
@@ -3305,9 +3316,13 @@ 
        Package Contents
 
        
-static udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, AggregateUDF]
        
+static udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[Ellipsis, AggregateUDF]
+
        
+static udaf(accum: collections.abc.Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → AggregateUDF
        
+
        
+static udaf(accum: AggregateUDFExportable) → AggregateUDF
        
 
        
-static udaf(accum: Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → AggregateUDF
        
+static udaf(accum: _typeshed.CapsuleType) → AggregateUDF
 
        Create a new User-Defined Aggregate Function (UDAF).
        
 
        This class allows you to define an aggregate function that can be used in
 data aggregation or window function calls.
        
@@ -4143,7 +4158,7 @@ 
        Returns:
 
        
 python_value() → Any
        
-
        Extracts the Expr value into a PyObject.
        
+
        Extracts the Expr value into Any.
        
 
        This is only valid for literal expressions.
        
 
        
 
        Returns:
        
@@ -4749,6 +4764,25 @@ 
        Returns:
        This class is essentially a wrapper for pa.RecordBatch.
        
 
        This constructor is generally not called by the end user.
        
 
        See the RecordBatchStream iterator for generating this class.
        
+
        
+
        
+__arrow_c_array__(requested_schema: object | None = None) → tuple[object, object]
        
+
        Export the record batch via the Arrow C Data Interface.
        
+
        This allows zero-copy interchange with libraries that support the
+Arrow PyCapsule interface.
        
+
        
+
        Parameters:
        
+
        requested_schema – Attempt to provide the record batch using this
+schema. Only straightforward projections such as column
+selection or reordering are applied.
        
+
        
+
        Returns:
        
+
        Two Arrow PyCapsule objects representing the ArrowArray and
+ArrowSchema.
        
+
        
+
        
+
        
+
 
        
 
        
 to_pyarrow() → pyarrow.RecordBatch
        
@@ -4772,25 +4806,25 @@ 
        Returns:
 
        
 __aiter__() → typing_extensions.Self
        
-
        Async iterator function.
        
+
        Return an asynchronous iterator over record batches.
        
 
        
 
 
        
 
        
 async __anext__() → RecordBatch
        
-
        Async iterator function.
        
+
        Return the next RecordBatch in the stream asynchronously.
        
 
        
 
 
        
 
        
 __iter__() → typing_extensions.Self
        
-
        Iterator function.
        
+
        Return an iterator over record batches.
        
 
        
 
 
        
 
        
 __next__() → RecordBatch
        
-
        Iterator function.
        
+
        Return the next RecordBatch in the stream.
        
 
        
 
 
        
@@ -5013,7 +5047,7 @@ 
        Returns:
 
        
-class datafusion.ScalarUDF(name: str, func: Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)
        
+class datafusion.ScalarUDF(name: str, func: collections.abc.Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)
 
        Class for performing scalar user-defined functions (UDF).
        
 
        Scalar UDFs operate on a row by row basis. See also AggregateUDF for
 operating on a group of rows.
        
@@ -5043,9 +5077,9 @@ 
        Returns:
 
        
-static udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, ScalarUDF]
        
+static udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[Ellipsis, ScalarUDF]
 
        
-static udf(func: Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → ScalarUDF
        
+static udf(func: collections.abc.Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → ScalarUDF
 
        
 static udf(func: ScalarUDFExportable) → ScalarUDF
        
 
        Create a new User-Defined Function (UDF).
        
@@ -5361,7 +5395,7 @@ 
        Returns:
 
        
-class datafusion.TableFunction(name: str, func: Callable[[], any])
        
+class datafusion.TableFunction(name: str, func: collections.abc.Callable[[], any])
 
        Class for performing user-defined table functions (UDTF).
        
 
        Table functions generate new table providers based on the
 input expressions.
        
@@ -5382,21 +5416,21 @@ 
        Returns:
 
        
-static _create_table_udf(func: Callable[Ellipsis, Any], name: str) → TableFunction
        
+static _create_table_udf(func: collections.abc.Callable[Ellipsis, Any], name: str) → TableFunction
 
        Create a TableFunction instance from function arguments.
        
 
        
 
 
        
 
        
-static _create_table_udf_decorator(name: str | None = None) → Callable[[Callable[[], WindowEvaluator]], Callable[Ellipsis, datafusion.expr.Expr]]
        
+static _create_table_udf_decorator(name: str | None = None) → collections.abc.Callable[[collections.abc.Callable[[], WindowEvaluator]], collections.abc.Callable[Ellipsis, datafusion.expr.Expr]]
 
        Create a decorator for a WindowUDF.
        
 
        
 
 
        
 
        
-static udtf(name: str) → Callable[Ellipsis, Any]
        
+static udtf(name: str) → collections.abc.Callable[Ellipsis, Any]
 
        
-static udtf(func: Callable[[], Any], name: str) → TableFunction
        
+static udtf(func: collections.abc.Callable[[], Any], name: str) → TableFunction
 
        Create a new User-Defined Table Function (UDTF).
        
 
        
 
@@ -5458,7 +5492,7 @@ 
        Returns:
 
        
-class datafusion.WindowUDF(name: str, func: Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str)
        
+class datafusion.WindowUDF(name: str, func: collections.abc.Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str)
 
        Class for performing window user-defined functions (UDF).
        
 
        Window UDFs operate on a partition of rows. See
 also ScalarUDF for operating on a row by row basis.
        
@@ -5481,19 +5515,19 @@ 
        Returns:
 
        
-static _create_window_udf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
        
+static _create_window_udf(func: collections.abc.Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
 
        Create a WindowUDF instance from function arguments.
        
 
        
 
 
        
 
        
-static _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → Callable[[Callable[[], WindowEvaluator]], Callable[Ellipsis, datafusion.expr.Expr]]
        
+static _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[[collections.abc.Callable[[], WindowEvaluator]], collections.abc.Callable[Ellipsis, datafusion.expr.Expr]]
 
        Create a decorator for a WindowUDF.
        
 
        
 
 
        
 
        
-static _get_default_name(func: Callable) → str
        
+static _get_default_name(func: collections.abc.Callable) → str
 
        Get the default name for a function based on its attributes.
        
 
        
 
@@ -5513,9 +5547,9 @@ 
        Returns:
 
        
-static udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, WindowUDF]
        
+static udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[Ellipsis, WindowUDF]
 
        
-static udwf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
        
+static udwf(func: collections.abc.Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
 
        Create a new User-Defined Window Function (UDWF).
        
 
        This class can be used both as either a function or a decorator.
        
 
        
@@ -5607,13 +5641,13 @@ 
        Returns:
 
        
-datafusion.lit(value) → expr.Expr
        
+datafusion.lit(value: Any) → expr.Expr
 
        Create a literal expression.
        
 
        
 
 
        
 
        
-datafusion.literal(value) → expr.Expr
        
+datafusion.literal(value: Any) → expr.Expr
 
        Create a literal expression.
        
 
        
 
diff --git a/autoapi/datafusion/record_batch/index.html b/autoapi/datafusion/record_batch/index.html
index ec09d72c1..e36e3aa65 100644
--- a/autoapi/datafusion/record_batch/index.html
+++ b/autoapi/datafusion/record_batch/index.html
@@ -426,6 +426,15 @@
      
     
     
    
        • 
+   
      • 
+    
+     
+      
+       _is_pycapsule()
+      
+     
+    
+   
        • 
    
      • 
     
      
@@ -1066,6 +1080,16 @@ 
        Classes¶
 
 
 
+
        
+
        Functions
        
+
+
+
+
+
+
+
        _is_pycapsule(→ TypeGuard[_typeshed.CapsuleType])
        Return True when value is a CPython PyCapsule.
        
+
        
 
        
 
        Module Contents
        
 
        
@@ -1100,7 +1124,9 @@ 
        Module Contents
 
        
-class datafusion.user_defined.AggregateUDF(name: str, accumulator: Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str)
        
+class datafusion.user_defined.AggregateUDF(name: str, accumulator: collections.abc.Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str)
+
        
+class datafusion.user_defined.AggregateUDF(name: str, accumulator: AggregateUDFExportable, input_types: None = ..., return_type: None = ..., state_type: None = ..., volatility: None = ...)
        
 
        Class for performing scalar user-defined functions (UDF).
        
 
        Aggregate UDFs operate on a group of rows and return a single value. See
 also ScalarUDF for operating on a row by row basis.
        
@@ -1123,7 +1149,7 @@ 
        Module Contents
 
        
-static from_pycapsule(func: AggregateUDFExportable) → AggregateUDF
        
+static from_pycapsule(func: AggregateUDFExportable | _typeshed.CapsuleType) → AggregateUDF
 
        Create an Aggregate UDF from AggregateUDF PyCapsule object.
        
 
        This function will instantiate a Aggregate UDF that uses a DataFusion
 AggregateUDF that is exported via the FFI bindings.
        
@@ -1131,9 +1157,13 @@ 
        Module Contents
 
        
-static udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, AggregateUDF]
        
+static udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[Ellipsis, AggregateUDF]
+
        
+static udaf(accum: collections.abc.Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → AggregateUDF
        
+
        
+static udaf(accum: AggregateUDFExportable) → AggregateUDF
        
 
        
-static udaf(accum: Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → AggregateUDF
        
+static udaf(accum: _typeshed.CapsuleType) → AggregateUDF
 
        Create a new User-Defined Aggregate Function (UDAF).
        
 
        This class allows you to define an aggregate function that can be used in
 data aggregation or window function calls.
        
@@ -1231,7 +1261,7 @@ 
        Module Contents
 
        
-class datafusion.user_defined.ScalarUDF(name: str, func: Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)
        
+class datafusion.user_defined.ScalarUDF(name: str, func: collections.abc.Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)
 
        Class for performing scalar user-defined functions (UDF).
        
 
        Scalar UDFs operate on a row by row basis. See also AggregateUDF for
 operating on a group of rows.
        
@@ -1261,9 +1291,9 @@ 
        Module Contents
 
        
-static udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, ScalarUDF]
        
+static udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[Ellipsis, ScalarUDF]
 
        
-static udf(func: Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → ScalarUDF
        
+static udf(func: collections.abc.Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → ScalarUDF
 
        
 static udf(func: ScalarUDFExportable) → ScalarUDF
        
 
        Create a new User-Defined Function (UDF).
        
@@ -1333,7 +1363,7 @@ 
        Module Contents
 
        
-class datafusion.user_defined.TableFunction(name: str, func: Callable[[], any])
        
+class datafusion.user_defined.TableFunction(name: str, func: collections.abc.Callable[[], any])
 
        Class for performing user-defined table functions (UDTF).
        
 
        Table functions generate new table providers based on the
 input expressions.
        
@@ -1354,21 +1384,21 @@ 
        Module Contents
 
        
-static _create_table_udf(func: Callable[Ellipsis, Any], name: str) → TableFunction
        
+static _create_table_udf(func: collections.abc.Callable[Ellipsis, Any], name: str) → TableFunction
 
        Create a TableFunction instance from function arguments.
        
 
        
 
 
        
 
        
-static _create_table_udf_decorator(name: str | None = None) → Callable[[Callable[[], WindowEvaluator]], Callable[Ellipsis, datafusion.expr.Expr]]
        
+static _create_table_udf_decorator(name: str | None = None) → collections.abc.Callable[[collections.abc.Callable[[], WindowEvaluator]], collections.abc.Callable[Ellipsis, datafusion.expr.Expr]]
 
        Create a decorator for a WindowUDF.
        
 
        
 
 
        
 
        
-static udtf(name: str) → Callable[Ellipsis, Any]
        
+static udtf(name: str) → collections.abc.Callable[Ellipsis, Any]
 
        
-static udtf(func: Callable[[], Any], name: str) → TableFunction
        
+static udtf(func: collections.abc.Callable[[], Any], name: str) → TableFunction
 
        Create a new User-Defined Table Function (UDTF).
        
 
        
 
@@ -1606,7 +1636,7 @@ 
        Module Contents
 
        
-class datafusion.user_defined.WindowUDF(name: str, func: Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str)
        
+class datafusion.user_defined.WindowUDF(name: str, func: collections.abc.Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str)
 
        Class for performing window user-defined functions (UDF).
        
 
        Window UDFs operate on a partition of rows. See
 also ScalarUDF for operating on a row by row basis.
        
@@ -1629,19 +1659,19 @@ 
        Module Contents
 
        
-static _create_window_udf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
        
+static _create_window_udf(func: collections.abc.Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
 
        Create a WindowUDF instance from function arguments.
        
 
      
 
 
      
 
      
-static _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → Callable[[Callable[[], WindowEvaluator]], Callable[Ellipsis, datafusion.expr.Expr]]
      
+static _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[[collections.abc.Callable[[], WindowEvaluator]], collections.abc.Callable[Ellipsis, datafusion.expr.Expr]]
 
      Create a decorator for a WindowUDF.
      
 
      
 
 
      
 
      
-static _get_default_name(func: Callable) → str
      
+static _get_default_name(func: collections.abc.Callable) → str
 
      Get the default name for a function based on its attributes.
      
 
      
 
@@ -1661,9 +1691,9 @@ 
      Module Contents
 
      
-static udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → Callable[Ellipsis, WindowUDF]
      
+static udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[Ellipsis, WindowUDF]
 
      
-static udwf(func: Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
      
+static udwf(func: collections.abc.Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
 
      Create a new User-Defined Window Function (UDWF).
      
 
      This class can be used both as either a function or a decorator.
      
 
      
@@ -1738,6 +1768,12 @@ 
      Module Contents
+
      
+datafusion.user_defined._is_pycapsule(value: object) → TypeGuard[_typeshed.CapsuleType]
      
+
      Return True when value is a CPython PyCapsule.
      
+
      
+
 
      
 
      
 datafusion.user_defined._R
      
diff --git a/genindex.html b/genindex.html
index b07a6ea90..a36dc3da4 100644
--- a/genindex.html
+++ b/genindex.html
@@ -445,9 +445,11 @@ 
      _
      
         
    • (datafusion.expr.Expr method)
 
      •

    • -
  • __aiter__() (datafusion.record_batch.RecordBatchStream method) +
  • __aiter__() (datafusion.dataframe.DataFrame method)
    • @@ -464,7 +466,13 @@

    _

  • __arrow_c_array__() (datafusion.context.ArrowArrayExportable method) + +
  • __arrow_c_stream__() (datafusion.context.ArrowStreamExportable method)
    • -
  • __iter__() (datafusion.record_batch.RecordBatchStream method) +
  • __iter__() (datafusion.dataframe.DataFrame method)
    • @@ -769,6 +779,8 @@

    _

  • (datafusion.Table attribute)
    • +
  • _is_pycapsule() (in module datafusion.user_defined) +
  • _normalize_input_types() (datafusion.user_defined.WindowUDF static method)
  • Functions
      diff --git a/user-guide/common-operations/joins.html b/user-guide/common-operations/joins.html index 56ae4eaaa..20fb374e6 100644 --- a/user-guide/common-operations/joins.html +++ b/user-guide/common-operations/joins.html @@ -432,6 +432,11 @@ Left Anti Join +
    • + + Duplicate Keys + +
    @@ -571,6 +576,52 @@

    Left Anti Join +

    Duplicate Keys

    +

    It is common to join two DataFrames on a common column name. Starting in +version 51.0.0, datafusion-python` will now coalesce on column with identical names by +default. This reduces problems with ambiguous column selection after joins. +You can disable this feature by setting the parameter coalesce_duplicate_keys +to False.

    +
    In [10]: left = ctx.from_pydict(
+   ....:     {
+   ....:         "id": [1, 2, 3],
+   ....:         "customer": ["Alice", "Bob", "Charlie"],
+   ....:     }
+   ....: )
+   ....: 
+
+In [11]: right = ctx.from_pylist([
+   ....:     {"id": 1, "name": "CityCabs"},
+   ....:     {"id": 2, "name": "MetroRide"},
+   ....:     {"id": 5, "name": "UrbanGo"},
+   ....: ])
+   ....: 
+
+In [12]: left.join(right, "id", how="inner")
+Out[12]: 
+DataFrame()
++----+----------+-----------+
+| id | customer | name      |
++----+----------+-----------+
+| 1  | Alice    | CityCabs  |
+| 2  | Bob      | MetroRide |
++----+----------+-----------+
+
    +
    +

    In contrast to the above example, if we wish to get both columns:

    +
    In [13]: left.join(right, "id", how="inner", coalesce_duplicate_keys=False)
+Out[13]: 
+DataFrame()
++----+----------+----+-----------+
+| id | customer | id | name      |
++----+----------+----+-----------+
+| 1  | Alice    | 1  | CityCabs  |
+| 2  | Bob      | 2  | MetroRide |
++----+----------+----+-----------+
+
    +
    + diff --git a/user-guide/configuration.html b/user-guide/configuration.html index 87ebc3ee6..c26e0b53f 100644 --- a/user-guide/configuration.html +++ b/user-guide/configuration.html @@ -448,7 +448,7 @@
    -

    Configuration

    +

    Configuration

    Let’s look at how we can configure DataFusion. When creating a SessionContext, you can pass in a SessionConfig and RuntimeEnvBuilder object. These two cover a wide range of options.

    from datafusion import RuntimeEnvBuilder, SessionConfig, SessionContext
diff --git a/user-guide/dataframe/index.html b/user-guide/dataframe/index.html
index cf5c2acd0..69a344d86 100644
--- a/user-guide/dataframe/index.html
+++ b/user-guide/dataframe/index.html
@@ -432,6 +432,23 @@
    Terminal Operations

    • +
  • + + Zero-copy streaming to Arrow-based Python libraries + +
    • +
  • + + PyArrow + + +
  • HTML Rendering @@ -543,8 +560,9 @@

    Common DataFrame Operations# Select with expressions df = df.select(column("a") + column("b"), column("a") - column("b")) -# Filter rows +# Filter rows (expressions or SQL strings) df = df.filter(column("age") > literal(25)) +df = df.filter("age > 25") # Add computed columns df = df.with_column("full_name", column("first_name") + literal(" ") + column("last_name")) @@ -634,8 +652,101 @@

    Terminal Operations# Count rows count = df.count() + +# Collect a single column of data as a PyArrow Array +arr = df.collect_column("age") + + + +
    +

    Zero-copy streaming to Arrow-based Python libraries

    +

    DataFusion DataFrames implement the __arrow_c_stream__ protocol, enabling +zero-copy, lazy streaming into Arrow-based Python libraries. With the streaming +protocol, batches are produced on demand.

    +
    +

    Note

    +

    The protocol is implementation-agnostic and works with any Python library +that understands the Arrow C streaming interface (for example, PyArrow +or other Arrow-compatible implementations). The sections below provide a +short PyArrow-specific example and general guidance for other +implementations.

    +
    +
    +
    +

    PyArrow

    +
    import pyarrow as pa
+
+# Create a PyArrow RecordBatchReader without materializing all batches
+reader = pa.RecordBatchReader.from_stream(df)
+for batch in reader:
+    ...  # process each batch as it is produced
+
    +
    +

    DataFrames are also iterable, yielding datafusion.RecordBatch +objects lazily so you can loop over results directly without importing +PyArrow:

    +
    for batch in df:
+    ...  # each batch is a ``datafusion.RecordBatch``
    +

    Each batch exposes to_pyarrow(), allowing conversion to a PyArrow +table. pa.table(df) collects the entire DataFrame eagerly into a +PyArrow table:

    +
    import pyarrow as pa
+table = pa.table(df)
+
    +
    +

    Asynchronous iteration is supported as well, allowing integration with +asyncio event loops:

    +
    async for batch in df:
+    ...  # process each batch as it is produced
+
    +
    +

    To work with the stream directly, use execute_stream(), which returns a +RecordBatchStream.

    +
    stream = df.execute_stream()
+for batch in stream:
+    ...
+
    +
    +
    +

    Execute as Stream

    +

    For finer control over streaming execution, use +execute_stream() to obtain a +datafusion.RecordBatchStream:

    +
    stream = df.execute_stream()
+for batch in stream:
+    ...  # process each batch as it is produced
+
    +
    +
    +

    Tip

    +

    To get a PyArrow reader instead, call

    +

    pa.RecordBatchReader.from_stream(df).

    +
    +

    When partition boundaries are important, +execute_stream_partitioned() +returns an iterable of datafusion.RecordBatchStream objects, one per +partition:

    +
    for stream in df.execute_stream_partitioned():
+    for batch in stream:
+        ...  # each stream yields RecordBatches
+
    +
    +

    To process partitions concurrently, first collect the streams into a list +and then poll each one in a separate asyncio task:

    +
    import asyncio
+
+async def consume(stream):
+    async for batch in stream:
+        ...
+
+streams = list(df.execute_stream_partitioned())
+await asyncio.gather(*(consume(s) for s in streams))
+
    +
    +

    See Arrow for additional details on the Arrow interface.

    +

    HTML Rendering

    diff --git a/user-guide/introduction.html b/user-guide/introduction.html index cf5fd7719..9e1434734 100644 --- a/user-guide/introduction.html +++ b/user-guide/introduction.html @@ -447,7 +447,7 @@

    Installation
    In [1]: import datafusion
 
 In [2]: datafusion.__version__
-Out[2]: '50.1.0'
+Out[2]: '51.0.0'

    In this documentation we will also show some examples for how DataFusion integrates diff --git a/user-guide/io/arrow.html b/user-guide/io/arrow.html index a4786dfe2..046a0ade6 100644 --- a/user-guide/io/arrow.html +++ b/user-guide/io/arrow.html @@ -489,16 +489,16 @@

    Importing to DataFusionExporting from DataFusion

    DataFusion DataFrames implement __arrow_c_stream__ PyCapsule interface, so any Python library that accepts these can import a DataFusion DataFrame directly.

    -
    -

    Warning

    -

    It is important to note that this will cause the DataFrame execution to happen, which may be -a time consuming task. That is, you will cause a -datafusion.dataframe.DataFrame.collect() operation call to occur.

    -
    -
    In [8]: df = df.select((col("a") * lit(1.5)).alias("c"), lit("df").alias("d"))
+
    Invoking __arrow_c_stream__ triggers execution of the underlying query, but
+batches are yielded incrementally rather than materialized all at once in memory.
+Consumers can process the stream as it arrives. The stream executes lazily,
+letting downstream readers pull batches on demand.
    
+
    In [8]: from datafusion import col, lit
+
+In [9]: df = df.select((col("a") * lit(1.5)).alias("c"), lit("df").alias("d"))
 
-In [9]: pa.table(df)
-Out[9]: 
+In [10]: pa.table(df)
+Out[10]: 
 pyarrow.Table
 c: double
 d: string_view not null
diff --git a/user-guide/sql.html b/user-guide/sql.html
index 865fe2607..6dd6e0a48 100644
--- a/user-guide/sql.html
+++ b/user-guide/sql.html
@@ -401,9 +401,19 @@
               
               
    
                 
+
    
+     On this page
+
    
 
 
               
    
               
@@ -428,22 +438,20 @@ 
    SQL
    DataFusion also offers a SQL API, read the full reference here
    
 
    In [1]: import datafusion
 
-In [2]: from datafusion import col
-
-In [3]: import pyarrow
+In [2]: from datafusion import DataFrame, SessionContext
 
 # create a context
-In [4]: ctx = datafusion.SessionContext()
+In [3]: ctx = datafusion.SessionContext()
 
 # register a CSV
-In [5]: ctx.register_csv('pokemon', 'pokemon.csv')
+In [4]: ctx.register_csv("pokemon", "pokemon.csv")
 
 # create a new statement via SQL
-In [6]: df = ctx.sql('SELECT "Attack"+"Defense", "Attack"-"Defense" FROM pokemon')
+In [5]: df = ctx.sql('SELECT "Attack"+"Defense", "Attack"-"Defense" FROM pokemon')
 
 # collect and convert to pandas DataFrame
-In [7]: df.to_pandas()
-Out[7]: 
+In [6]: df.to_pandas()
+Out[6]: 
      pokemon.Attack + pokemon.Defense  pokemon.Attack - pokemon.Defense
 0                                  98                                 0
 1                                 125                                -1
@@ -460,6 +468,114 @@ 
    SQL
    [163 rows x 2 columns]
 
    
 
    
+
    
+
    Parameterized queries
    
+
    In DataFusion-Python 51.0.0 we introduced the ability to pass parameters
+in a SQL query. These are similar in concept to
+prepared statements,
+but allow passing named parameters into a SQL query. Consider this simple
+example.
    
+
    In [7]: def show_attacks(ctx: SessionContext, threshold: int) -> None:
+   ...:     ctx.sql(
+   ...:         'SELECT "Name", "Attack" FROM pokemon WHERE "Attack" > $val', val=threshold
+   ...:     ).show(num=5)
+   ...: show_attacks(ctx, 75)
+   ...: 
+DataFrame()
++---------------------------+--------+
+| Name                      | Attack |
++---------------------------+--------+
+| Venusaur                  | 82     |
+| VenusaurMega Venusaur     | 100    |
+| Charizard                 | 84     |
+| CharizardMega Charizard X | 130    |
+| CharizardMega Charizard Y | 104    |
++---------------------------+--------+
+
    
+
    
+
    When passing parameters like the example above we convert the Python objects
+into their string representation. We also have special case handling
+for DataFrame objects, since they cannot simply
+be turned into string representations for an SQL query. In these cases we
+will register a temporary view in the SessionContext
+using a generated table name.
    
+
    The formatting for passing string replacement objects is to precede the
+variable name with a single $. This works for all dialects in
+the SQL parser except hive and mysql. Since these dialects do not
+support named placeholders, we are unable to do this type of replacement.
+We recommend either switching to another dialect or using Python
+f-string style replacement.
    
+
    
+
    Warning
    
+
    To support DataFrame parameterized queries, your session must support
+registration of temporary views. The default
+CatalogProvider and
+SchemaProvider do have this capability.
+If you have implemented custom providers, it is important that temporary
+views do not persist across SessionContext
+or you may get unintended consequences.
    
+
    
+
    The following example shows passing in both a DataFrame
+object as well as a Python object to be used in parameterized replacement.
    
+
    In [8]: def show_column(
+   ...:     ctx: SessionContext, column: str, df: DataFrame, threshold: int
+   ...: ) -> None:
+   ...:     ctx.sql(
+   ...:         'SELECT "Name", $col FROM $df WHERE $col > $val',
+   ...:         col=column,
+   ...:         df=df,
+   ...:         val=threshold,
+   ...:     ).show(num=5)
+   ...: df = ctx.table("pokemon")
+   ...: show_column(ctx, '"Defense"', df, 75)
+   ...: 
+DataFrame()
++---------------------------+---------+
+| Name                      | Defense |
++---------------------------+---------+
+| Venusaur                  | 83      |
+| VenusaurMega Venusaur     | 123     |
+| Charizard                 | 78      |
+| CharizardMega Charizard X | 111     |
+| CharizardMega Charizard Y | 78      |
++---------------------------+---------+
+
    
+
    
+
    The approach implemented for conversion of variables into a SQL query
+relies on string conversion. This has the potential for data loss,
+specifically for cases like floating point numbers. If you need to pass
+variables into a parameterized query and it is important to maintain the
+original value without conversion to a string, then you can use the
+optional parameter param_values to specify these. This parameter
+expects a dictionary mapping from the parameter name to a Python
+object. Those objects will be cast into a
+PyArrow Scalar Value.
    
+
    Using param_values will rely on the SQL dialect you have configured
+for your session. This can be set using the configuration options
+of your SessionContext. Similar to how
+prepared statements
+work, these parameters are limited to places where you would pass in a
+scalar value, such as a comparison.
    
+
    In [9]: def param_attacks(ctx: SessionContext, threshold: int) -> None:
+   ...:     ctx.sql(
+   ...:         'SELECT "Name", "Attack" FROM pokemon WHERE "Attack" > $val',
+   ...:         param_values={"val": threshold},
+   ...:     ).show(num=5)
+   ...: param_attacks(ctx, 75)
+   ...: 
+DataFrame()
++---------------------------+--------+
+| Name                      | Attack |
++---------------------------+--------+
+| Venusaur                  | 82     |
+| VenusaurMega Venusaur     | 100    |
+| Charizard                 | 84     |
+| CharizardMega Charizard X | 130    |
+| CharizardMega Charizard Y | 104    |
++---------------------------+--------+
+
    
+
    
+

    From 1c410707bf4fdea4e1230c37ed990ac5f848ceff Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Mon, 9 Feb 2026 15:58:15 +0000 Subject: [PATCH 32/36] Publish built docs triggered by aa88d6540ca0b037347b959788ea32700509b98a --- .../autoapi/datafusion/catalog/index.rst.txt | 12 +- .../autoapi/datafusion/context/index.rst.txt | 33 +- .../dataframe_formatter/index.rst.txt | 94 +- _sources/autoapi/datafusion/index.rst.txt | 582 +++----- _sources/autoapi/datafusion/io/index.rst.txt | 4 +- .../autoapi/datafusion/options/index.rst.txt | 242 ++++ .../datafusion/user_defined/index.rst.txt | 40 +- _sources/contributor-guide/ffi.rst.txt | 2 + _sources/index.rst.txt | 1 + .../common-operations/udf-and-udfa.rst.txt | 11 + .../user-guide/dataframe/rendering.rst.txt | 8 +- _sources/user-guide/io/csv.rst.txt | 22 + _sources/user-guide/upgrade-guides.rst.txt | 96 ++ autoapi/datafusion/catalog/index.html | 31 +- autoapi/datafusion/context/index.html | 69 +- autoapi/datafusion/dataframe/index.html | 10 + .../datafusion/dataframe_formatter/index.html | 166 ++- autoapi/datafusion/expr/index.html | 10 + autoapi/datafusion/functions/index.html | 10 + autoapi/datafusion/html_formatter/index.html | 10 + autoapi/datafusion/index.html | 1277 +++++++---------- autoapi/datafusion/input/base/index.html | 10 + autoapi/datafusion/input/index.html | 10 + autoapi/datafusion/input/location/index.html | 10 + autoapi/datafusion/io/index.html | 14 +- autoapi/datafusion/object_store/index.html | 16 +- autoapi/datafusion/options/index.html | 1039 ++++++++++++++ autoapi/datafusion/plan/index.html | 16 +- autoapi/datafusion/record_batch/index.html | 10 + autoapi/datafusion/substrait/index.html | 10 + autoapi/datafusion/unparser/index.html | 10 + autoapi/datafusion/user_defined/index.html | 69 +- autoapi/index.html | 11 + contributor-guide/ffi.html | 12 +- contributor-guide/introduction.html | 16 +- genindex.html | 444 +++--- index.html | 10 + objects.inv | Bin 8815 -> 9168 bytes py-modindex.html | 15 + search.html | 10 + searchindex.js | 2 +- user-guide/basics.html | 10 + .../common-operations/aggregations.html | 48 +- user-guide/common-operations/basic-info.html | 56 +- user-guide/common-operations/expressions.html | 10 + user-guide/common-operations/functions.html | 50 +- user-guide/common-operations/index.html | 10 + user-guide/common-operations/joins.html | 10 + .../common-operations/select-and-filter.html | 10 + .../common-operations/udf-and-udfa.html | 19 + user-guide/common-operations/views.html | 10 + user-guide/common-operations/windows.html | 10 + user-guide/configuration.html | 10 + user-guide/data-sources.html | 10 + user-guide/dataframe/index.html | 10 + user-guide/dataframe/rendering.html | 18 +- user-guide/introduction.html | 10 + user-guide/io/arrow.html | 10 + user-guide/io/avro.html | 10 + user-guide/io/csv.html | 29 + user-guide/io/index.html | 10 + user-guide/io/json.html | 10 + user-guide/io/parquet.html | 10 + user-guide/io/table_provider.html | 10 + user-guide/sql.html | 16 +- user-guide/upgrade-guides.html | 571 ++++++++ 66 files changed, 3911 insertions(+), 1530 deletions(-) create mode 100644 _sources/autoapi/datafusion/options/index.rst.txt create mode 100644 _sources/user-guide/upgrade-guides.rst.txt create mode 100644 autoapi/datafusion/options/index.html create mode 100644 user-guide/upgrade-guides.html diff --git a/_sources/autoapi/datafusion/catalog/index.rst.txt b/_sources/autoapi/datafusion/catalog/index.rst.txt index 50fec8af3..aa511f3e0 100644 --- a/_sources/autoapi/datafusion/catalog/index.rst.txt +++ b/_sources/autoapi/datafusion/catalog/index.rst.txt @@ -49,7 +49,7 @@ Module Contents - .. py:method:: memory_catalog() -> Catalog + .. py:method:: memory_catalog(ctx: datafusion.SessionContext | None = None) -> Catalog :staticmethod: @@ -148,7 +148,7 @@ Module Contents - .. py:method:: memory_schema() -> Schema + .. py:method:: memory_schema(ctx: datafusion.SessionContext | None = None) -> Schema :staticmethod: @@ -174,6 +174,12 @@ Module Contents + .. py:method:: table_exist(name: str) -> bool + + Determines if a table exists in this schema. + + + .. py:method:: table_names() -> set[str] Returns the list of all tables in this schema. @@ -241,7 +247,7 @@ Module Contents -.. py:class:: Table(table: Table | datafusion.context.TableProviderExportable | datafusion.DataFrame | pyarrow.dataset.Dataset) +.. py:class:: Table(table: Table | datafusion.context.TableProviderExportable | datafusion.DataFrame | pyarrow.dataset.Dataset, ctx: datafusion.SessionContext | None = None) A DataFusion table. diff --git a/_sources/autoapi/datafusion/context/index.rst.txt b/_sources/autoapi/datafusion/context/index.rst.txt index 50c3a9d4e..3c2be3ae2 100644 --- a/_sources/autoapi/datafusion/context/index.rst.txt +++ b/_sources/autoapi/datafusion/context/index.rst.txt @@ -64,7 +64,7 @@ Module Contents https://docs.rs/datafusion/latest/datafusion/catalog/trait.CatalogProvider.html - .. py:method:: __datafusion_catalog_provider__() -> object + .. py:method:: __datafusion_catalog_provider__(session: Any) -> object .. py:class:: RuntimeConfig @@ -425,6 +425,18 @@ Module Contents df = ctx.read_csv("data.csv") + .. py:method:: __datafusion_logical_extension_codec__() -> Any + + Access the PyCapsule FFI_LogicalExtensionCodec. + + + + .. py:method:: __datafusion_task_context_provider__() -> Any + + Access the PyCapsule FFI_TaskContextProvider. + + + .. py:method:: __repr__() -> str Print a string representation of the Session Context. @@ -600,7 +612,7 @@ Module Contents - .. py:method:: read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None) -> datafusion.dataframe.DataFrame + .. py:method:: read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = DEFAULT_MAX_INFER_SCHEMA, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None, options: datafusion.options.CsvReadOptions | None = None) -> datafusion.dataframe.DataFrame Read a CSV data source. @@ -617,6 +629,8 @@ Module Contents selected for data input. :param table_partition_cols: Partition columns. :param file_compression_type: File compression type. + :param options: Set advanced options for CSV reading. This cannot be + combined with any of the other options in this method. :returns: DataFrame representation of the read CSV files @@ -690,7 +704,7 @@ Module Contents - .. py:method:: register_csv(name: str, path: str | pathlib.Path | list[str | pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', file_compression_type: str | None = None) -> None + .. py:method:: register_csv(name: str, path: str | pathlib.Path | list[str | pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = DEFAULT_MAX_INFER_SCHEMA, file_extension: str = '.csv', file_compression_type: str | None = None, options: datafusion.options.CsvReadOptions | None = None) -> None Register a CSV file as a table. @@ -709,6 +723,8 @@ Module Contents :param file_extension: File extension; only files with this extension are selected for data input. :param file_compression_type: File compression type. + :param options: Set advanced options for CSV reading. This cannot be + combined with any of the other options in this method. @@ -918,6 +934,15 @@ Module Contents + .. py:method:: with_logical_extension_codec(codec: Any) -> SessionContext + + Create a new session context with specified codec. + + This only supports codecs that have been implemented using the + FFI interface. + + + .. py:attribute:: ctx @@ -931,6 +956,6 @@ Module Contents https://datafusion.apache.org/python/user-guide/io/table_provider.html - .. py:method:: __datafusion_table_provider__() -> object + .. py:method:: __datafusion_table_provider__(session: Any) -> object diff --git a/_sources/autoapi/datafusion/dataframe_formatter/index.rst.txt b/_sources/autoapi/datafusion/dataframe_formatter/index.rst.txt index 7f5b3f530..243627a96 100644 --- a/_sources/autoapi/datafusion/dataframe_formatter/index.rst.txt +++ b/_sources/autoapi/datafusion/dataframe_formatter/index.rst.txt @@ -28,6 +28,7 @@ Functions datafusion.dataframe_formatter._refresh_formatter_reference datafusion.dataframe_formatter._validate_bool + datafusion.dataframe_formatter._validate_formatter_parameters datafusion.dataframe_formatter._validate_positive_int datafusion.dataframe_formatter.configure_formatter datafusion.dataframe_formatter.get_formatter @@ -52,7 +53,7 @@ Module Contents -.. py:class:: DataFrameHtmlFormatter(max_cell_length: int = 25, max_width: int = 1000, max_height: int = 300, max_memory_bytes: int = 2 * 1024 * 1024, min_rows_display: int = 20, repr_rows: int = 10, enable_cell_expansion: bool = True, custom_css: str | None = None, show_truncation_message: bool = True, style_provider: StyleProvider | None = None, use_shared_styles: bool = True) +.. py:class:: DataFrameHtmlFormatter(max_cell_length: int = 25, max_width: int = 1000, max_height: int = 300, max_memory_bytes: int = 2 * 1024 * 1024, min_rows: int = 10, max_rows: int | None = None, repr_rows: int | None = None, enable_cell_expansion: bool = True, custom_css: str | None = None, show_truncation_message: bool = True, style_provider: StyleProvider | None = None, use_shared_styles: bool = True) Configurable HTML formatter for DataFusion DataFrames. @@ -68,8 +69,9 @@ Module Contents :param max_width: Maximum width of the HTML table in pixels :param max_height: Maximum height of the HTML table in pixels :param max_memory_bytes: Maximum memory in bytes for rendered data (default: 2MB) - :param min_rows_display: Minimum number of rows to display - :param repr_rows: Default number of rows to display in repr output + :param min_rows: Minimum number of rows to display (must be <= max_rows) + :param max_rows: Maximum number of rows to display in repr output + :param repr_rows: Deprecated alias for max_rows :param enable_cell_expansion: Whether to add expand/collapse buttons for long cell values :param custom_css: Additional CSS to include in the HTML output @@ -81,36 +83,30 @@ Module Contents Initialize the HTML formatter. :param max_cell_length: Maximum length of cell content before truncation. - :type max_cell_length: int, default 25 :param max_width: Maximum width of the displayed table in pixels. - :type max_width: int, default 1000 :param max_height: Maximum height of the displayed table in pixels. - :type max_height: int, default 300 - :param max_memory_bytes: Maximum memory in bytes for rendered data. - :type max_memory_bytes: int, default 2097152 (2MB) - :param min_rows_display: Minimum number of rows to display. - :type min_rows_display: int, default 20 - :param repr_rows: Default number of rows to display in repr output. - :type repr_rows: int, default 10 + :param max_memory_bytes: Maximum memory in bytes for rendered data. Helps prevent performance + issues with large datasets. + :param min_rows: Minimum number of rows to display even if memory limit is reached. + Must not exceed ``max_rows``. + :param max_rows: Maximum number of rows to display. Takes precedence over memory limits + when fewer rows are requested. + :param repr_rows: Deprecated alias for ``max_rows``. Use ``max_rows`` instead. :param enable_cell_expansion: Whether to allow cells to expand when clicked. - :type enable_cell_expansion: bool, default True :param custom_css: Custom CSS to apply to the HTML table. - :type custom_css: str, optional :param show_truncation_message: Whether to show a message indicating that content has been truncated. - :type show_truncation_message: bool, default True :param style_provider: Provider of CSS styles for the HTML table. If None, DefaultStyleProvider is used. - :type style_provider: StyleProvider, optional - :param use_shared_styles: Whether to use shared styles across multiple tables. - :type use_shared_styles: bool, default True + :param use_shared_styles: Whether to use shared styles across multiple tables. This improves + performance when displaying many DataFrames in a single notebook. :param Raises: :param ------: :param ValueError: If max_cell_length, max_width, max_height, max_memory_bytes, - min_rows_display, or repr_rows is not a positive integer. + min_rows or max_rows is not a positive integer, or if min_rows + exceeds max_rows. :param TypeError: If enable_cell_expansion, show_truncation_message, or use_shared_styles is - not a boolean, - or if custom_css is provided but is not a string, - or if style_provider is provided but does not implement the StyleProvider + not a boolean, or if custom_css is provided but is not a string, or if + style_provider is provided but does not implement the StyleProvider protocol. @@ -265,6 +261,11 @@ Module Contents + .. py:attribute:: _max_rows + :value: None + + + .. py:attribute:: _type_formatters :type: dict[type, CellFormatter] @@ -294,19 +295,36 @@ Module Contents + .. py:property:: max_rows + :type: int + + + Get the maximum number of rows to display. + + :returns: The maximum number of rows to display in repr output + + .. py:attribute:: max_width :value: 1000 - .. py:attribute:: min_rows_display - :value: 20 + .. py:attribute:: min_rows + :value: 10 + + .. py:property:: repr_rows + :type: int - .. py:attribute:: repr_rows - :value: 10 + Get the maximum number of rows (deprecated name). + + .. deprecated:: + Use :attr:`max_rows` instead. This property is provided for + backward compatibility. + + :returns: The maximum number of rows to display .. py:attribute:: show_truncation_message @@ -410,6 +428,30 @@ Module Contents :raises TypeError: If the value is not a boolean +.. py:function:: _validate_formatter_parameters(max_cell_length: int, max_width: int, max_height: int, max_memory_bytes: int, min_rows: int, max_rows: int | None, repr_rows: int | None, enable_cell_expansion: bool, show_truncation_message: bool, use_shared_styles: bool, custom_css: str | None, style_provider: Any) -> int + + Validate all formatter parameters and return resolved max_rows value. + + :param max_cell_length: Maximum cell length value to validate + :param max_width: Maximum width value to validate + :param max_height: Maximum height value to validate + :param max_memory_bytes: Maximum memory bytes value to validate + :param min_rows: Minimum rows to display value to validate + :param max_rows: Maximum rows value to validate (None means use default) + :param repr_rows: Deprecated repr_rows value to validate + :param enable_cell_expansion: Boolean expansion flag to validate + :param show_truncation_message: Boolean message flag to validate + :param use_shared_styles: Boolean styles flag to validate + :param custom_css: Custom CSS string to validate + :param style_provider: Style provider object to validate + + :returns: The resolved max_rows value after handling repr_rows deprecation + + :raises ValueError: If any numeric parameter is invalid or constraints are violated + :raises TypeError: If any parameter has invalid type + :raises DeprecationWarning: If repr_rows parameter is used + + .. py:function:: _validate_positive_int(value: Any, param_name: str) -> None Validate that a parameter is a positive integer. diff --git a/_sources/autoapi/datafusion/index.rst.txt b/_sources/autoapi/datafusion/index.rst.txt index 59e6d2915..8afeae253 100644 --- a/_sources/autoapi/datafusion/index.rst.txt +++ b/_sources/autoapi/datafusion/index.rst.txt @@ -28,6 +28,7 @@ Submodules /autoapi/datafusion/input/index /autoapi/datafusion/io/index /autoapi/datafusion/object_store/index + /autoapi/datafusion/options/index /autoapi/datafusion/plan/index /autoapi/datafusion/record_batch/index /autoapi/datafusion/substrait/index @@ -43,10 +44,6 @@ Attributes datafusion.DFSchema datafusion.col datafusion.column - datafusion.udaf - datafusion.udf - datafusion.udtf - datafusion.udwf Classes @@ -54,9 +51,8 @@ Classes .. autoapisummary:: - datafusion.Accumulator - datafusion.AggregateUDF datafusion.Catalog + datafusion.CsvReadOptions datafusion.DataFrameWriteOptions datafusion.Database datafusion.ExecutionPlan @@ -69,12 +65,9 @@ Classes datafusion.RecordBatchStream datafusion.RuntimeEnvBuilder datafusion.SQLOptions - datafusion.ScalarUDF datafusion.SessionConfig datafusion.Table - datafusion.TableFunction datafusion.WindowFrame - datafusion.WindowUDF Functions @@ -94,221 +87,284 @@ Functions Package Contents ---------------- -.. py:class:: Accumulator +.. py:class:: Catalog(catalog: datafusion._internal.catalog.RawCatalog) - Defines how an :py:class:`AggregateUDF` accumulates values. + DataFusion data catalog. + This constructor is not typically called by the end user. - .. py:method:: evaluate() -> pyarrow.Scalar - :abstractmethod: + .. py:method:: __repr__() -> str - Return the resultant value. + Print a string representation of the catalog. - .. py:method:: merge(states: list[pyarrow.Array]) -> None - :abstractmethod: + .. py:method:: database(name: str = 'public') -> Schema + Returns the database with the given ``name`` from this catalog. - Merge a set of states. + .. py:method:: deregister_schema(name: str, cascade: bool = True) -> Schema | None - .. py:method:: state() -> list[pyarrow.Scalar] - :abstractmethod: + Deregister a schema from this catalog. - Return the current state. + .. py:method:: memory_catalog(ctx: datafusion.SessionContext | None = None) -> Catalog + :staticmethod: - .. py:method:: update(*values: pyarrow.Array) -> None - :abstractmethod: + Create an in-memory catalog provider. - Evaluate an array of values and update state. + .. py:method:: names() -> set[str] + This is an alias for `schema_names`. -.. py:class:: AggregateUDF(name: str, accumulator: collections.abc.Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str) - AggregateUDF(name: str, accumulator: AggregateUDFExportable, input_types: None = ..., return_type: None = ..., state_type: None = ..., volatility: None = ...) - Class for performing scalar user-defined functions (UDF). - Aggregate UDFs operate on a group of rows and return a single value. See - also :py:class:`ScalarUDF` for operating on a row by row basis. + .. py:method:: register_schema(name: str, schema: Schema | SchemaProvider | SchemaProviderExportable) -> Schema | None - Instantiate a user-defined aggregate function (UDAF). + Register a schema with this catalog. - See :py:func:`udaf` for a convenience function and argument - descriptions. - .. py:method:: __call__(*args: datafusion.expr.Expr) -> datafusion.expr.Expr + .. py:method:: schema(name: str = 'public') -> Schema - Execute the UDAF. + Returns the database with the given ``name`` from this catalog. - This function is not typically called by an end user. These calls will - occur during the evaluation of the dataframe. + .. py:method:: schema_names() -> set[str] - .. py:method:: __repr__() -> str + Returns the list of schemas in this catalog. - Print a string representation of the Aggregate UDF. + .. py:attribute:: catalog - .. py:method:: from_pycapsule(func: AggregateUDFExportable | _typeshed.CapsuleType) -> AggregateUDF - :staticmethod: +.. py:class:: CsvReadOptions(*, has_header: bool = True, delimiter: str = ',', quote: str = '"', terminator: str | None = None, escape: str | None = None, comment: str | None = None, newlines_in_values: bool = False, schema: pyarrow.Schema | None = None, schema_infer_max_records: int = DEFAULT_MAX_INFER_SCHEMA, file_extension: str = '.csv', table_partition_cols: list[tuple[str, pyarrow.DataType]] | None = None, file_compression_type: str = '', file_sort_order: list[list[datafusion.expr.SortExpr]] | None = None, null_regex: str | None = None, truncated_rows: bool = False) + + Options for reading CSV files. + + This class provides a builder pattern for configuring CSV reading options. + All methods starting with ``with_`` return ``self`` to allow method chaining. + + Initialize CsvReadOptions. + + :param has_header: Does the CSV file have a header row? If schema inference + is run on a file with no headers, default column names are created. + :param delimiter: Column delimiter character. Must be a single ASCII character. + :param quote: Quote character for fields containing delimiters or newlines. + Must be a single ASCII character. + :param terminator: Optional line terminator character. If ``None``, uses CRLF. + Must be a single ASCII character. + :param escape: Optional escape character for quotes. Must be a single ASCII + character. + :param comment: If specified, lines beginning with this character are ignored. + Must be a single ASCII character. + :param newlines_in_values: Whether newlines in quoted values are supported. + Parsing newlines in quoted values may be affected by execution + behavior such as parallel file scanning. Setting this to ``True`` + ensures that newlines in values are parsed successfully, which may + reduce performance. + :param schema: Optional PyArrow schema representing the CSV files. If ``None``, + the CSV reader will try to infer it based on data in the file. + :param schema_infer_max_records: Maximum number of rows to read from CSV files + for schema inference if needed. + :param file_extension: File extension; only files with this extension are + selected for data input. + :param table_partition_cols: Partition columns as a list of tuples of + (column_name, data_type). + :param file_compression_type: File compression type. Supported values are + ``"gzip"``, ``"bz2"``, ``"xz"``, ``"zstd"``, or empty string for + uncompressed. + :param file_sort_order: Optional sort order of the files as a list of sort + expressions per file. + :param null_regex: Optional regex pattern to match null values in the CSV. + :param truncated_rows: Whether to allow truncated rows when parsing. By default + this is ``False`` and will error if the CSV rows have different + lengths. When set to ``True``, it will allow records with less than + the expected number of columns and fill the missing columns with + nulls. If the record's schema is not nullable, it will still return + an error. - Create an Aggregate UDF from AggregateUDF PyCapsule object. - This function will instantiate a Aggregate UDF that uses a DataFusion - AggregateUDF that is exported via the FFI bindings. + .. py:method:: to_inner() -> datafusion._internal.options.CsvReadOptions + Convert this object into the underlying Rust structure. + This is intended for internal use only. - .. py:method:: udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[Ellipsis, AggregateUDF] - udaf(accum: collections.abc.Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) -> AggregateUDF - udaf(accum: AggregateUDFExportable) -> AggregateUDF - udaf(accum: _typeshed.CapsuleType) -> AggregateUDF - :staticmethod: - Create a new User-Defined Aggregate Function (UDAF). + .. py:method:: with_comment(comment: str | None) -> CsvReadOptions - This class allows you to define an aggregate function that can be used in - data aggregation or window function calls. + Configure the comment character. - Usage: - - As a function: ``udaf(accum, input_types, return_type, state_type, volatility, name)``. - - As a decorator: ``@udaf(input_types, return_type, state_type, volatility, name)``. - When using ``udaf`` as a decorator, do not pass ``accum`` explicitly. - Function example: - If your :py:class:`Accumulator` can be instantiated with no arguments, you - can simply pass it's type as `accum`. If you need to pass additional - arguments to it's constructor, you can define a lambda or a factory method. - During runtime the :py:class:`Accumulator` will be constructed for every - instance in which this UDAF is used. The following examples are all valid:: + .. py:method:: with_delimiter(delimiter: str) -> CsvReadOptions - import pyarrow as pa - import pyarrow.compute as pc + Configure the column delimiter. - class Summarize(Accumulator): - def __init__(self, bias: float = 0.0): - self._sum = pa.scalar(bias) - def state(self) -> list[pa.Scalar]: - return [self._sum] - def update(self, values: pa.Array) -> None: - self._sum = pa.scalar(self._sum.as_py() + pc.sum(values).as_py()) + .. py:method:: with_escape(escape: str | None) -> CsvReadOptions - def merge(self, states: list[pa.Array]) -> None: - self._sum = pa.scalar(self._sum.as_py() + pc.sum(states[0]).as_py()) + Configure the escape character. - def evaluate(self) -> pa.Scalar: - return self._sum - def sum_bias_10() -> Summarize: - return Summarize(10.0) - udaf1 = udaf(Summarize, pa.float64(), pa.float64(), [pa.float64()], - "immutable") - udaf2 = udaf(sum_bias_10, pa.float64(), pa.float64(), [pa.float64()], - "immutable") - udaf3 = udaf(lambda: Summarize(20.0), pa.float64(), pa.float64(), - [pa.float64()], "immutable") + .. py:method:: with_file_compression_type(file_compression_type: str) -> CsvReadOptions - Decorator example::: + Configure file compression type. - @udaf(pa.float64(), pa.float64(), [pa.float64()], "immutable") - def udf4() -> Summarize: - return Summarize(10.0) - :param accum: The accumulator python function. Only needed when calling as a - function. Skip this argument when using ``udaf`` as a decorator. - If you have a Rust backed AggregateUDF within a PyCapsule, you can - pass this parameter and ignore the rest. They will be determined - directly from the underlying function. See the online documentation - for more information. - :param input_types: The data types of the arguments to ``accum``. - :param return_type: The data type of the return value. - :param state_type: The data types of the intermediate accumulation. - :param volatility: See :py:class:`Volatility` for allowed values. - :param name: A descriptive name for the function. - :returns: A user-defined aggregate function, which can be used in either data - aggregation or window function calls. + .. py:method:: with_file_extension(file_extension: str) -> CsvReadOptions + Configure the file extension filter. - .. py:attribute:: _udaf + .. py:method:: with_file_sort_order(file_sort_order: list[list[datafusion.expr.SortExpr]]) -> CsvReadOptions -.. py:class:: Catalog(catalog: datafusion._internal.catalog.RawCatalog) + Configure file sort order. - DataFusion data catalog. - This constructor is not typically called by the end user. + .. py:method:: with_has_header(has_header: bool) -> CsvReadOptions - .. py:method:: __repr__() -> str + Configure whether the CSV has a header row. - Print a string representation of the catalog. + .. py:method:: with_newlines_in_values(newlines_in_values: bool) -> CsvReadOptions - .. py:method:: database(name: str = 'public') -> Schema + Configure whether newlines in values are supported. - Returns the database with the given ``name`` from this catalog. + .. py:method:: with_null_regex(null_regex: str | None) -> CsvReadOptions - .. py:method:: deregister_schema(name: str, cascade: bool = True) -> Schema | None + Configure null value regex pattern. - Deregister a schema from this catalog. + .. py:method:: with_quote(quote: str) -> CsvReadOptions - .. py:method:: memory_catalog() -> Catalog - :staticmethod: + Configure the quote character. - Create an in-memory catalog provider. + .. py:method:: with_schema(schema: pyarrow.Schema | None) -> CsvReadOptions + Configure the schema. - .. py:method:: names() -> set[str] - This is an alias for `schema_names`. + .. py:method:: with_schema_infer_max_records(schema_infer_max_records: int) -> CsvReadOptions + Configure maximum records for schema inference. - .. py:method:: register_schema(name: str, schema: Schema | SchemaProvider | SchemaProviderExportable) -> Schema | None - Register a schema with this catalog. + .. py:method:: with_table_partition_cols(table_partition_cols: list[tuple[str, pyarrow.DataType]]) -> CsvReadOptions + Configure table partition columns. - .. py:method:: schema(name: str = 'public') -> Schema - Returns the database with the given ``name`` from this catalog. + .. py:method:: with_terminator(terminator: str | None) -> CsvReadOptions + Configure the line terminator character. - .. py:method:: schema_names() -> set[str] - Returns the list of schemas in this catalog. + .. py:method:: with_truncated_rows(truncated_rows: bool) -> CsvReadOptions + Configure whether to allow truncated rows. + + + + .. py:attribute:: comment + :value: None + + + + .. py:attribute:: delimiter + :value: ',' + + + + .. py:attribute:: escape + :value: None + + + + .. py:attribute:: file_compression_type + :value: '' + + + + .. py:attribute:: file_extension + :value: '.csv' + + + + .. py:attribute:: file_sort_order + :value: [] + + + + .. py:attribute:: has_header + :value: True + + + + .. py:attribute:: newlines_in_values + :value: False + + + + .. py:attribute:: null_regex + :value: None + + + + .. py:attribute:: quote + :value: '"' + + + + .. py:attribute:: schema + :value: None + + + + .. py:attribute:: schema_infer_max_records + :value: 1000 + + + + .. py:attribute:: table_partition_cols + :value: [] + + + + .. py:attribute:: terminator + :value: None + + + + .. py:attribute:: truncated_rows + :value: False - .. py:attribute:: catalog .. py:class:: DataFrameWriteOptions(insert_operation: InsertOp | None = None, single_file_output: bool = False, partition_by: str | collections.abc.Sequence[str] | None = None, sort_by: datafusion.expr.Expr | datafusion.expr.SortExpr | collections.abc.Sequence[datafusion.expr.Expr] | collections.abc.Sequence[datafusion.expr.SortExpr] | None = None) @@ -1841,97 +1897,6 @@ Package Contents .. py:attribute:: options_internal -.. py:class:: ScalarUDF(name: str, func: collections.abc.Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str) - - Class for performing scalar user-defined functions (UDF). - - Scalar UDFs operate on a row by row basis. See also :py:class:`AggregateUDF` for - operating on a group of rows. - - Instantiate a scalar user-defined function (UDF). - - See helper method :py:func:`udf` for argument details. - - - .. py:method:: __call__(*args: datafusion.expr.Expr) -> datafusion.expr.Expr - - Execute the UDF. - - This function is not typically called by an end user. These calls will - occur during the evaluation of the dataframe. - - - - .. py:method:: __repr__() -> str - - Print a string representation of the Scalar UDF. - - - - .. py:method:: from_pycapsule(func: ScalarUDFExportable) -> ScalarUDF - :staticmethod: - - - Create a Scalar UDF from ScalarUDF PyCapsule object. - - This function will instantiate a Scalar UDF that uses a DataFusion - ScalarUDF that is exported via the FFI bindings. - - - - .. py:method:: udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[Ellipsis, ScalarUDF] - udf(func: collections.abc.Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) -> ScalarUDF - udf(func: ScalarUDFExportable) -> ScalarUDF - :staticmethod: - - - Create a new User-Defined Function (UDF). - - This class can be used both as either a function or a decorator. - - Usage: - - As a function: ``udf(func, input_types, return_type, volatility, name)``. - - As a decorator: ``@udf(input_types, return_type, volatility, name)``. - When used a decorator, do **not** pass ``func`` explicitly. - - :param func: Only needed when calling as a function. - Skip this argument when using `udf` as a decorator. If you have a Rust - backed ScalarUDF within a PyCapsule, you can pass this parameter - and ignore the rest. They will be determined directly from the - underlying function. See the online documentation for more information. - :type func: Callable, optional - :param input_types: The data types of the arguments - to ``func``. This list must be of the same length as the number of - arguments. - :type input_types: list[pa.DataType] - :param return_type: The data type of the return value from the function. - :type return_type: _R - :param volatility: See `Volatility` for allowed values. - :type volatility: Volatility | str - :param name: A descriptive name for the function. - :type name: Optional[str] - - :returns: A user-defined function that can be used in SQL expressions, - data aggregation, or window function calls. - - Example: Using ``udf`` as a function:: - - def double_func(x): - return x * 2 - double_udf = udf(double_func, [pa.int32()], pa.int32(), - "volatile", "double_it") - - Example: Using ``udf`` as a decorator:: - - @udf([pa.int32()], pa.int32(), "volatile", "double_it") - def double_udf(x): - return x * 2 - - - - .. py:attribute:: _udf - - .. py:class:: SessionConfig(config_options: dict[str, str] | None = None) Session configuration options. @@ -2088,7 +2053,7 @@ Package Contents .. py:attribute:: config_internal -.. py:class:: Table(table: Table | datafusion.context.TableProviderExportable | datafusion.DataFrame | pyarrow.dataset.Dataset) +.. py:class:: Table(table: Table | datafusion.context.TableProviderExportable | datafusion.DataFrame | pyarrow.dataset.Dataset, ctx: datafusion.SessionContext | None = None) A DataFusion table. @@ -2140,59 +2105,6 @@ Package Contents Returns the schema associated with this table. -.. py:class:: TableFunction(name: str, func: collections.abc.Callable[[], any]) - - Class for performing user-defined table functions (UDTF). - - Table functions generate new table providers based on the - input expressions. - - Instantiate a user-defined table function (UDTF). - - See :py:func:`udtf` for a convenience function and argument - descriptions. - - - .. py:method:: __call__(*args: datafusion.expr.Expr) -> Any - - Execute the UDTF and return a table provider. - - - - .. py:method:: __repr__() -> str - - User printable representation. - - - - .. py:method:: _create_table_udf(func: collections.abc.Callable[Ellipsis, Any], name: str) -> TableFunction - :staticmethod: - - - Create a TableFunction instance from function arguments. - - - - .. py:method:: _create_table_udf_decorator(name: str | None = None) -> collections.abc.Callable[[collections.abc.Callable[[], WindowEvaluator]], collections.abc.Callable[Ellipsis, datafusion.expr.Expr]] - :staticmethod: - - - Create a decorator for a WindowUDF. - - - - .. py:method:: udtf(name: str) -> collections.abc.Callable[Ellipsis, Any] - udtf(func: collections.abc.Callable[[], Any], name: str) -> TableFunction - :staticmethod: - - - Create a new User-Defined Table Function (UDTF). - - - - .. py:attribute:: _udtf - - .. py:class:: WindowFrame(units: str, start_bound: Any | None, end_bound: Any | None) Defines a window frame for performing window operations. @@ -2235,134 +2147,6 @@ Package Contents .. py:attribute:: window_frame -.. py:class:: WindowUDF(name: str, func: collections.abc.Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str) - - Class for performing window user-defined functions (UDF). - - Window UDFs operate on a partition of rows. See - also :py:class:`ScalarUDF` for operating on a row by row basis. - - Instantiate a user-defined window function (UDWF). - - See :py:func:`udwf` for a convenience function and argument - descriptions. - - - .. py:method:: __call__(*args: datafusion.expr.Expr) -> datafusion.expr.Expr - - Execute the UDWF. - - This function is not typically called by an end user. These calls will - occur during the evaluation of the dataframe. - - - - .. py:method:: __repr__() -> str - - Print a string representation of the Window UDF. - - - - .. py:method:: _create_window_udf(func: collections.abc.Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) -> WindowUDF - :staticmethod: - - - Create a WindowUDF instance from function arguments. - - - - .. py:method:: _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[[collections.abc.Callable[[], WindowEvaluator]], collections.abc.Callable[Ellipsis, datafusion.expr.Expr]] - :staticmethod: - - - Create a decorator for a WindowUDF. - - - - .. py:method:: _get_default_name(func: collections.abc.Callable) -> str - :staticmethod: - - - Get the default name for a function based on its attributes. - - - - .. py:method:: _normalize_input_types(input_types: pyarrow.DataType | list[pyarrow.DataType]) -> list[pyarrow.DataType] - :staticmethod: - - - Convert a single DataType to a list if needed. - - - - .. py:method:: from_pycapsule(func: WindowUDFExportable) -> WindowUDF - :staticmethod: - - - Create a Window UDF from WindowUDF PyCapsule object. - - This function will instantiate a Window UDF that uses a DataFusion - WindowUDF that is exported via the FFI bindings. - - - - .. py:method:: udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[Ellipsis, WindowUDF] - udwf(func: collections.abc.Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) -> WindowUDF - :staticmethod: - - - Create a new User-Defined Window Function (UDWF). - - This class can be used both as either a function or a decorator. - - Usage: - - As a function: ``udwf(func, input_types, return_type, volatility, name)``. - - As a decorator: ``@udwf(input_types, return_type, volatility, name)``. - When using ``udwf`` as a decorator, do not pass ``func`` explicitly. - - Function example:: - - import pyarrow as pa - - class BiasedNumbers(WindowEvaluator): - def __init__(self, start: int = 0) -> None: - self.start = start - - def evaluate_all(self, values: list[pa.Array], - num_rows: int) -> pa.Array: - return pa.array([self.start + i for i in range(num_rows)]) - - def bias_10() -> BiasedNumbers: - return BiasedNumbers(10) - - udwf1 = udwf(BiasedNumbers, pa.int64(), pa.int64(), "immutable") - udwf2 = udwf(bias_10, pa.int64(), pa.int64(), "immutable") - udwf3 = udwf(lambda: BiasedNumbers(20), pa.int64(), pa.int64(), "immutable") - - - Decorator example:: - - @udwf(pa.int64(), pa.int64(), "immutable") - def biased_numbers() -> BiasedNumbers: - return BiasedNumbers(10) - - :param func: Only needed when calling as a function. Skip this argument when - using ``udwf`` as a decorator. If you have a Rust backed WindowUDF - within a PyCapsule, you can pass this parameter and ignore the rest. - They will be determined directly from the underlying function. See - the online documentation for more information. - :param input_types: The data types of the arguments. - :param return_type: The data type of the return value. - :param volatility: See :py:class:`Volatility` for allowed values. - :param name: A descriptive name for the function. - - :returns: A user-defined window function that can be used in window function calls. - - - - .. py:attribute:: _udwf - - .. py:function:: configure_formatter(**kwargs: Any) -> None Configure the global DataFrame HTML formatter. @@ -2412,7 +2196,7 @@ Package Contents :returns: DataFrame representation of the read Avro file -.. py:function:: read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None) -> datafusion.dataframe.DataFrame +.. py:function:: read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None, options: datafusion.options.CsvReadOptions | None = None) -> datafusion.dataframe.DataFrame Read a CSV data source. @@ -2433,6 +2217,8 @@ Package Contents selected for data input. :param table_partition_cols: Partition columns. :param file_compression_type: File compression type. + :param options: Set advanced options for CSV reading. This cannot be + combined with any of the other options in this method. :returns: DataFrame representation of the read CSV files @@ -2490,11 +2276,3 @@ Package Contents .. py:data:: column :type: Col -.. py:data:: udaf - -.. py:data:: udf - -.. py:data:: udtf - -.. py:data:: udwf - diff --git a/_sources/autoapi/datafusion/io/index.rst.txt b/_sources/autoapi/datafusion/io/index.rst.txt index bb80c1cd3..453d6fa04 100644 --- a/_sources/autoapi/datafusion/io/index.rst.txt +++ b/_sources/autoapi/datafusion/io/index.rst.txt @@ -39,7 +39,7 @@ Module Contents :returns: DataFrame representation of the read Avro file -.. py:function:: read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None) -> datafusion.dataframe.DataFrame +.. py:function:: read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None, options: datafusion.options.CsvReadOptions | None = None) -> datafusion.dataframe.DataFrame Read a CSV data source. @@ -60,6 +60,8 @@ Module Contents selected for data input. :param table_partition_cols: Partition columns. :param file_compression_type: File compression type. + :param options: Set advanced options for CSV reading. This cannot be + combined with any of the other options in this method. :returns: DataFrame representation of the read CSV files diff --git a/_sources/autoapi/datafusion/options/index.rst.txt b/_sources/autoapi/datafusion/options/index.rst.txt new file mode 100644 index 000000000..25a6d6464 --- /dev/null +++ b/_sources/autoapi/datafusion/options/index.rst.txt @@ -0,0 +1,242 @@ +datafusion.options +================== + +.. py:module:: datafusion.options + +.. autoapi-nested-parse:: + + Options for reading various file formats. + + + +Classes +------- + +.. autoapisummary:: + + datafusion.options.CsvReadOptions + + +Module Contents +--------------- + +.. py:class:: CsvReadOptions(*, has_header: bool = True, delimiter: str = ',', quote: str = '"', terminator: str | None = None, escape: str | None = None, comment: str | None = None, newlines_in_values: bool = False, schema: pyarrow.Schema | None = None, schema_infer_max_records: int = DEFAULT_MAX_INFER_SCHEMA, file_extension: str = '.csv', table_partition_cols: list[tuple[str, pyarrow.DataType]] | None = None, file_compression_type: str = '', file_sort_order: list[list[datafusion.expr.SortExpr]] | None = None, null_regex: str | None = None, truncated_rows: bool = False) + + Options for reading CSV files. + + This class provides a builder pattern for configuring CSV reading options. + All methods starting with ``with_`` return ``self`` to allow method chaining. + + Initialize CsvReadOptions. + + :param has_header: Does the CSV file have a header row? If schema inference + is run on a file with no headers, default column names are created. + :param delimiter: Column delimiter character. Must be a single ASCII character. + :param quote: Quote character for fields containing delimiters or newlines. + Must be a single ASCII character. + :param terminator: Optional line terminator character. If ``None``, uses CRLF. + Must be a single ASCII character. + :param escape: Optional escape character for quotes. Must be a single ASCII + character. + :param comment: If specified, lines beginning with this character are ignored. + Must be a single ASCII character. + :param newlines_in_values: Whether newlines in quoted values are supported. + Parsing newlines in quoted values may be affected by execution + behavior such as parallel file scanning. Setting this to ``True`` + ensures that newlines in values are parsed successfully, which may + reduce performance. + :param schema: Optional PyArrow schema representing the CSV files. If ``None``, + the CSV reader will try to infer it based on data in the file. + :param schema_infer_max_records: Maximum number of rows to read from CSV files + for schema inference if needed. + :param file_extension: File extension; only files with this extension are + selected for data input. + :param table_partition_cols: Partition columns as a list of tuples of + (column_name, data_type). + :param file_compression_type: File compression type. Supported values are + ``"gzip"``, ``"bz2"``, ``"xz"``, ``"zstd"``, or empty string for + uncompressed. + :param file_sort_order: Optional sort order of the files as a list of sort + expressions per file. + :param null_regex: Optional regex pattern to match null values in the CSV. + :param truncated_rows: Whether to allow truncated rows when parsing. By default + this is ``False`` and will error if the CSV rows have different + lengths. When set to ``True``, it will allow records with less than + the expected number of columns and fill the missing columns with + nulls. If the record's schema is not nullable, it will still return + an error. + + + .. py:method:: to_inner() -> datafusion._internal.options.CsvReadOptions + + Convert this object into the underlying Rust structure. + + This is intended for internal use only. + + + + .. py:method:: with_comment(comment: str | None) -> CsvReadOptions + + Configure the comment character. + + + + .. py:method:: with_delimiter(delimiter: str) -> CsvReadOptions + + Configure the column delimiter. + + + + .. py:method:: with_escape(escape: str | None) -> CsvReadOptions + + Configure the escape character. + + + + .. py:method:: with_file_compression_type(file_compression_type: str) -> CsvReadOptions + + Configure file compression type. + + + + .. py:method:: with_file_extension(file_extension: str) -> CsvReadOptions + + Configure the file extension filter. + + + + .. py:method:: with_file_sort_order(file_sort_order: list[list[datafusion.expr.SortExpr]]) -> CsvReadOptions + + Configure file sort order. + + + + .. py:method:: with_has_header(has_header: bool) -> CsvReadOptions + + Configure whether the CSV has a header row. + + + + .. py:method:: with_newlines_in_values(newlines_in_values: bool) -> CsvReadOptions + + Configure whether newlines in values are supported. + + + + .. py:method:: with_null_regex(null_regex: str | None) -> CsvReadOptions + + Configure null value regex pattern. + + + + .. py:method:: with_quote(quote: str) -> CsvReadOptions + + Configure the quote character. + + + + .. py:method:: with_schema(schema: pyarrow.Schema | None) -> CsvReadOptions + + Configure the schema. + + + + .. py:method:: with_schema_infer_max_records(schema_infer_max_records: int) -> CsvReadOptions + + Configure maximum records for schema inference. + + + + .. py:method:: with_table_partition_cols(table_partition_cols: list[tuple[str, pyarrow.DataType]]) -> CsvReadOptions + + Configure table partition columns. + + + + .. py:method:: with_terminator(terminator: str | None) -> CsvReadOptions + + Configure the line terminator character. + + + + .. py:method:: with_truncated_rows(truncated_rows: bool) -> CsvReadOptions + + Configure whether to allow truncated rows. + + + + .. py:attribute:: comment + :value: None + + + + .. py:attribute:: delimiter + :value: ',' + + + + .. py:attribute:: escape + :value: None + + + + .. py:attribute:: file_compression_type + :value: '' + + + + .. py:attribute:: file_extension + :value: '.csv' + + + + .. py:attribute:: file_sort_order + :value: [] + + + + .. py:attribute:: has_header + :value: True + + + + .. py:attribute:: newlines_in_values + :value: False + + + + .. py:attribute:: null_regex + :value: None + + + + .. py:attribute:: quote + :value: '"' + + + + .. py:attribute:: schema + :value: None + + + + .. py:attribute:: schema_infer_max_records + :value: 1000 + + + + .. py:attribute:: table_partition_cols + :value: [] + + + + .. py:attribute:: terminator + :value: None + + + + .. py:attribute:: truncated_rows + :value: False + + + diff --git a/_sources/autoapi/datafusion/user_defined/index.rst.txt b/_sources/autoapi/datafusion/user_defined/index.rst.txt index 784a39c75..1a7a93d34 100644 --- a/_sources/autoapi/datafusion/user_defined/index.rst.txt +++ b/_sources/autoapi/datafusion/user_defined/index.rst.txt @@ -44,6 +44,8 @@ Functions .. autoapisummary:: datafusion.user_defined._is_pycapsule + datafusion.user_defined.data_type_or_field_to_field + datafusion.user_defined.data_types_or_fields_to_field_list Module Contents @@ -217,7 +219,7 @@ Module Contents .. py:method:: __datafusion_aggregate_udf__() -> object -.. py:class:: ScalarUDF(name: str, func: collections.abc.Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str) +.. py:class:: ScalarUDF(name: str, func: collections.abc.Callable[Ellipsis, _R], input_fields: list[pyarrow.Field], return_field: _R, volatility: Volatility | str) Class for performing scalar user-defined functions (UDF). @@ -255,8 +257,8 @@ Module Contents - .. py:method:: udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[Ellipsis, ScalarUDF] - udf(func: collections.abc.Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) -> ScalarUDF + .. py:method:: udf(input_fields: collections.abc.Sequence[pyarrow.DataType | pyarrow.Field] | pyarrow.DataType | pyarrow.Field, return_field: pyarrow.DataType | pyarrow.Field, volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[Ellipsis, ScalarUDF] + udf(func: collections.abc.Callable[Ellipsis, _R], input_fields: collections.abc.Sequence[pyarrow.DataType | pyarrow.Field] | pyarrow.DataType | pyarrow.Field, return_field: pyarrow.DataType | pyarrow.Field, volatility: Volatility | str, name: str | None = None) -> ScalarUDF udf(func: ScalarUDFExportable) -> ScalarUDF :staticmethod: @@ -266,22 +268,26 @@ Module Contents This class can be used both as either a function or a decorator. Usage: - - As a function: ``udf(func, input_types, return_type, volatility, name)``. - - As a decorator: ``@udf(input_types, return_type, volatility, name)``. + - As a function: ``udf(func, input_fields, return_field, volatility, name)``. + - As a decorator: ``@udf(input_fields, return_field, volatility, name)``. When used a decorator, do **not** pass ``func`` explicitly. + In lieu of passing a PyArrow Field, you can pass a DataType for simplicity. + When you do so, it will be assumed that the nullability of the inputs and + output are True and that they have no metadata. + :param func: Only needed when calling as a function. Skip this argument when using `udf` as a decorator. If you have a Rust backed ScalarUDF within a PyCapsule, you can pass this parameter and ignore the rest. They will be determined directly from the underlying function. See the online documentation for more information. :type func: Callable, optional - :param input_types: The data types of the arguments - to ``func``. This list must be of the same length as the number of - arguments. - :type input_types: list[pa.DataType] - :param return_type: The data type of the return value from the function. - :type return_type: _R + :param input_fields: The data types or Fields + of the arguments to ``func``. This list must be of the same length + as the number of arguments. + :type input_fields: list[pa.Field | pa.DataType] + :param return_field: The field of the return value from the function. + :type return_field: _R :param volatility: See `Volatility` for allowed values. :type volatility: Volatility | str :param name: A descriptive name for the function. @@ -319,7 +325,7 @@ Module Contents .. py:method:: __datafusion_scalar_udf__() -> object -.. py:class:: TableFunction(name: str, func: collections.abc.Callable[[], any]) +.. py:class:: TableFunction(name: str, func: collections.abc.Callable[[], any], ctx: datafusion.SessionContext | None = None) Class for performing user-defined table functions (UDTF). @@ -744,6 +750,16 @@ Module Contents Return ``True`` when ``value`` is a CPython ``PyCapsule``. +.. py:function:: data_type_or_field_to_field(value: pyarrow.DataType | pyarrow.Field, name: str) -> pyarrow.Field + + Helper function to return a Field from either a Field or DataType. + + +.. py:function:: data_types_or_fields_to_field_list(inputs: collections.abc.Sequence[pyarrow.Field | pyarrow.DataType] | pyarrow.Field | pyarrow.DataType) -> list[pyarrow.Field] + + Helper function to return a list of Fields. + + .. py:data:: _R .. py:data:: udaf diff --git a/_sources/contributor-guide/ffi.rst.txt b/_sources/contributor-guide/ffi.rst.txt index 64413866f..5006b0ca4 100644 --- a/_sources/contributor-guide/ffi.rst.txt +++ b/_sources/contributor-guide/ffi.rst.txt @@ -15,6 +15,8 @@ .. specific language governing permissions and limitations .. under the License. +.. _ffi: + Python Extensions ================= diff --git a/_sources/index.rst.txt b/_sources/index.rst.txt index adec60f48..134d41cb6 100644 --- a/_sources/index.rst.txt +++ b/_sources/index.rst.txt @@ -77,6 +77,7 @@ Example user-guide/io/index user-guide/configuration user-guide/sql + user-guide/upgrade-guides .. _toc.contributor_guide: diff --git a/_sources/user-guide/common-operations/udf-and-udfa.rst.txt b/_sources/user-guide/common-operations/udf-and-udfa.rst.txt index 0830fa81c..d554e1e25 100644 --- a/_sources/user-guide/common-operations/udf-and-udfa.rst.txt +++ b/_sources/user-guide/common-operations/udf-and-udfa.rst.txt @@ -90,6 +90,17 @@ converting to Python objects to do the evaluation. df.select(col("a"), is_null_arr(col("a")).alias("is_null")).show() +In this example we passed the PyArrow ``DataType`` when we defined the function +by calling ``udf()``. If you need additional control, such as specifying +metadata or nullability of the input or output, you can instead specify a +PyArrow ``Field``. + +If you need to write a custom function but do not want to incur the performance +cost of converting to Python objects and back, a more advanced approach is to +write Rust based UDFs and to expose them to Python. There is an example in the +`DataFusion blog `_ +describing how to do this. + Aggregate Functions ------------------- diff --git a/_sources/user-guide/dataframe/rendering.rst.txt b/_sources/user-guide/dataframe/rendering.rst.txt index 4c37c7471..9dea948bb 100644 --- a/_sources/user-guide/dataframe/rendering.rst.txt +++ b/_sources/user-guide/dataframe/rendering.rst.txt @@ -57,8 +57,8 @@ You can customize how DataFrames are rendered by configuring the formatter: max_width=1000, # Maximum width in pixels max_height=300, # Maximum height in pixels max_memory_bytes=2097152, # Maximum memory for rendering (2MB) - min_rows_display=20, # Minimum number of rows to display - repr_rows=10, # Number of rows to display in __repr__ + min_rows=10, # Minimum number of rows to display + max_rows=10, # Maximum rows to display in __repr__ enable_cell_expansion=True,# Allow expanding truncated cells custom_css=None, # Additional custom CSS show_truncation_message=True, # Show message when data is truncated @@ -190,8 +190,8 @@ You can control how much data is displayed and how much memory is used for rende configure_formatter( max_memory_bytes=4 * 1024 * 1024, # 4MB maximum memory for display - min_rows_display=50, # Always show at least 50 rows - repr_rows=20 # Show 20 rows in __repr__ output + min_rows=20, # Always show at least 20 rows + max_rows=50 # Show up to 50 rows in output ) These parameters help balance comprehensive data display against performance considerations. diff --git a/_sources/user-guide/io/csv.rst.txt b/_sources/user-guide/io/csv.rst.txt index 144b6615c..9c23c291b 100644 --- a/_sources/user-guide/io/csv.rst.txt +++ b/_sources/user-guide/io/csv.rst.txt @@ -36,3 +36,25 @@ An alternative is to use :py:func:`~datafusion.context.SessionContext.register_c ctx.register_csv("file", "file.csv") df = ctx.table("file") + +If you require additional control over how to read the CSV file, you can use +:py:class:`~datafusion.options.CsvReadOptions` to set a variety of options. + +.. code-block:: python + + from datafusion import CsvReadOptions + options = ( + CsvReadOptions() + .with_has_header(True) # File contains a header row + .with_delimiter(";") # Use ; as the delimiter instead of , + .with_comment("#") # Skip lines starting with # + .with_escape("\\") # Escape character + .with_null_regex(r"^(null|NULL|N/A)$") # Treat these as NULL + .with_truncated_rows(True) # Allow rows to have incomplete columns + .with_file_compression_type("gzip") # Read gzipped CSV + .with_file_extension(".gz") # File extension other than .csv + ) + df = ctx.read_csv("data.csv.gz", options=options) + +Details for all CSV reading options can be found on the +`DataFusion documentation site `_. diff --git a/_sources/user-guide/upgrade-guides.rst.txt b/_sources/user-guide/upgrade-guides.rst.txt new file mode 100644 index 000000000..a77f60776 --- /dev/null +++ b/_sources/user-guide/upgrade-guides.rst.txt @@ -0,0 +1,96 @@ +.. Licensed to the Apache Software Foundation (ASF) under one +.. or more contributor license agreements. See the NOTICE file +.. distributed with this work for additional information +.. regarding copyright ownership. The ASF licenses this file +.. to you under the Apache License, Version 2.0 (the +.. "License"); you may not use this file except in compliance +.. with the License. You may obtain a copy of the License at + +.. http://www.apache.org/licenses/LICENSE-2.0 + +.. Unless required by applicable law or agreed to in writing, +.. software distributed under the License is distributed on an +.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +.. KIND, either express or implied. See the License for the +.. specific language governing permissions and limitations +.. under the License. + +Upgrade Guides +============== + +DataFusion 52.0.0 +----------------- + +This version includes a major update to the :ref:`ffi` due to upgrades +to the `Foreign Function Interface `_. +Users who contribute their own ``CatalogProvider``, ``SchemaProvider``, +``TableProvider`` or ``TableFunction`` via FFI must now provide access to a +``LogicalExtensionCodec`` and a ``TaskContextProvider``. The function signatures +for the methods to get these ``PyCapsule`` objects now requires an additional +parameter, which is a Python object that can be used to extract the +``FFI_LogicalExtensionCodec`` that is necessary. + +A complete example can be found in the `FFI example `_. +Your methods need to be updated to take an additional parameter like in this +example. + +.. code-block:: rust + + #[pymethods] + impl MyCatalogProvider { + pub fn __datafusion_catalog_provider__<'py>( + &self, + py: Python<'py>, + session: Bound, + ) -> PyResult> { + let name = cr"datafusion_catalog_provider".into(); + + let provider = Arc::clone(&self.inner) as Arc; + + let codec = ffi_logical_codec_from_pycapsule(session)?; + let provider = FFI_CatalogProvider::new_with_ffi_codec(provider, None, codec); + + PyCapsule::new(py, provider, Some(name)) + } + } + +To extract the logical extension codec FFI object from the provided object you +can implement a helper method such as: + +.. code-block:: rust + + pub(crate) fn ffi_logical_codec_from_pycapsule( + obj: Bound, + ) -> PyResult { + let attr_name = "__datafusion_logical_extension_codec__"; + let capsule = if obj.hasattr(attr_name)? { + obj.getattr(attr_name)?.call0()? + } else { + obj + }; + + let capsule = capsule.downcast::()?; + validate_pycapsule(capsule, "datafusion_logical_extension_codec")?; + + let codec = unsafe { capsule.reference::() }; + + Ok(codec.clone()) + } + + +The DataFusion FFI interface updates no longer depend directly on the +``datafusion`` core crate. You can improve your build times and potentially +reduce your library binary size by removing this dependency and instead +using the specific datafusion project crates. + +For example, instead of including expressions like: + +.. code-block:: rust + + use datafusion::catalog::MemTable; + +Instead you can now write: + +.. code-block:: rust + + use datafusion_catalog::MemTable; diff --git a/autoapi/datafusion/catalog/index.html b/autoapi/datafusion/catalog/index.html index 862ded08f..e99ff9e4e 100644 --- a/autoapi/datafusion/catalog/index.html +++ b/autoapi/datafusion/catalog/index.html @@ -243,6 +243,11 @@ SQL

    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -619,6 +629,15 @@
    • +
  • + + + + Schema.table_exist() + + + +
  • @@ -844,7 +863,7 @@

    Module Contents
    -static memory_catalog() → Catalog
    +static memory_catalog(ctx: datafusion.SessionContext | None = None) → Catalog

    Create an in-memory catalog provider.

    @@ -941,7 +960,7 @@

    Module Contents
    -static memory_schema() → Schema
    +static memory_schema(ctx: datafusion.SessionContext | None = None) → Schema

    Create an in-memory schema provider.

    @@ -963,6 +982,12 @@

    Module Contentsname from this schema.

    +
    +
    +table_exist(name: str) → bool
    +

    Determines if a table exists in this schema.

    +
    +
    table_names() → set[str]
    @@ -1026,7 +1051,7 @@

    Module Contents
    -class datafusion.catalog.Table(table: Table | datafusion.context.TableProviderExportable | datafusion.DataFrame | pyarrow.dataset.Dataset)
    +class datafusion.catalog.Table(table: Table | datafusion.context.TableProviderExportable | datafusion.DataFrame | pyarrow.dataset.Dataset, ctx: datafusion.SessionContext | None = None)

    A DataFusion table.

    Internally we currently support the following types of tables:

      diff --git a/autoapi/datafusion/context/index.html b/autoapi/datafusion/context/index.html index f8aefac95..677e2937f 100644 --- a/autoapi/datafusion/context/index.html +++ b/autoapi/datafusion/context/index.html @@ -243,6 +243,11 @@ SQL +
    • + + Upgrade Guides + +

    @@ -354,6 +359,11 @@ datafusion.object_store

    • +
  • + + datafusion.options + +
  • datafusion.plan @@ -762,6 +772,24 @@

    @@ -354,6 +359,11 @@ datafusion.object_store

    • +
  • + + datafusion.options + +
  • datafusion.plan diff --git a/autoapi/datafusion/dataframe_formatter/index.html b/autoapi/datafusion/dataframe_formatter/index.html index 615c37da5..f611c472a 100644 --- a/autoapi/datafusion/dataframe_formatter/index.html +++ b/autoapi/datafusion/dataframe_formatter/index.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -613,6 +623,15 @@
    • +
  • + + + + DataFrameHtmlFormatter._max_rows + + + +
  • @@ -667,6 +686,15 @@
    • +
  • + + + + DataFrameHtmlFormatter.max_rows + + + +
  • @@ -677,10 +705,10 @@
  • - + - DataFrameHtmlFormatter.min_rows_display + DataFrameHtmlFormatter.min_rows @@ -837,6 +865,15 @@
    • +
  • + + + + _validate_formatter_parameters() + + + +
  • @@ -940,19 +977,22 @@

    Functions

    _validate_bool(→ None)

    Validate that a parameter is a boolean.

    -

    _validate_positive_int(→ None)

    +

    _validate_formatter_parameters(→ int)

    +

    Validate all formatter parameters and return resolved max_rows value.

    + +

    _validate_positive_int(→ None)

    Validate that a parameter is a positive integer.

    -

    configure_formatter(→ None)

    +

    configure_formatter(→ None)

    Configure the global DataFrame HTML formatter.

    -

    get_formatter(→ DataFrameHtmlFormatter)

    +

    get_formatter(→ DataFrameHtmlFormatter)

    Get the current global DataFrame HTML formatter.

    -

    reset_formatter(→ None)

    +

    reset_formatter(→ None)

    Reset the global DataFrame HTML formatter to default settings.

    -

    set_formatter(→ None)

    +

    set_formatter(→ None)

    Set the global DataFrame HTML formatter.

    @@ -975,7 +1015,7 @@

    Module Contents
    -class datafusion.dataframe_formatter.DataFrameHtmlFormatter(max_cell_length: int = 25, max_width: int = 1000, max_height: int = 300, max_memory_bytes: int = 2 * 1024 * 1024, min_rows_display: int = 20, repr_rows: int = 10, enable_cell_expansion: bool = True, custom_css: str | None = None, show_truncation_message: bool = True, style_provider: StyleProvider | None = None, use_shared_styles: bool = True)
    +class datafusion.dataframe_formatter.DataFrameHtmlFormatter(max_cell_length: int = 25, max_width: int = 1000, max_height: int = 300, max_memory_bytes: int = 2 * 1024 * 1024, min_rows: int = 10, max_rows: int | None = None, repr_rows: int | None = None, enable_cell_expansion: bool = True, custom_css: str | None = None, show_truncation_message: bool = True, style_provider: StyleProvider | None = None, use_shared_styles: bool = True)

    Configurable HTML formatter for DataFusion DataFrames.

    This class handles the HTML rendering of DataFrames for display in Jupyter notebooks and other rich display contexts.

    @@ -990,8 +1030,9 @@

    Module Contents
    Parameters:
    @@ -1211,6 +1257,11 @@

    Module Contents_custom_header_builder: collections.abc.Callable[[Any], str] | None = None
    +
    +
    +_max_rows = None
    +
    +
    _type_formatters: dict[type, CellFormatter]
    @@ -1241,20 +1292,41 @@

    Module Contentsmax_memory_bytes = 2097152

    +
    +
    +property max_rows: int
    +

    Get the maximum number of rows to display.

    +
    +
    Returns:
    +

    The maximum number of rows to display in repr output

    +
    +
    +
    +
    max_width = 1000
    -
    -min_rows_display = 20
    +
    +min_rows = 10
    -
    +
    -repr_rows = 10
    -
    +property repr_rows: int +

    Get the maximum number of rows (deprecated name).

    +
    +

    Deprecated since version Use: max_rows instead. This property is provided for +backward compatibility.

    +
    +
    +
    Returns:
    +

    The maximum number of rows to display

    +
    +
    +
    @@ -1378,6 +1450,40 @@

    Module Contents +
    +datafusion.dataframe_formatter._validate_formatter_parameters(max_cell_length: int, max_width: int, max_height: int, max_memory_bytes: int, min_rows: int, max_rows: int | None, repr_rows: int | None, enable_cell_expansion: bool, show_truncation_message: bool, use_shared_styles: bool, custom_css: str | None, style_provider: Any) → int
    +

    Validate all formatter parameters and return resolved max_rows value.

    +
    +
    Parameters:
    +
      +

    • max_cell_length – Maximum cell length value to validate

      • +

    • max_width – Maximum width value to validate

      • +

    • max_height – Maximum height value to validate

      • +

    • max_memory_bytes – Maximum memory bytes value to validate

      • +

    • min_rows – Minimum rows to display value to validate

      • +

    • max_rows – Maximum rows value to validate (None means use default)

      • +

    • repr_rows – Deprecated repr_rows value to validate

      • +

    • enable_cell_expansion – Boolean expansion flag to validate

      • +

    • show_truncation_message – Boolean message flag to validate

      • +

    • use_shared_styles – Boolean styles flag to validate

      • +

    • custom_css – Custom CSS string to validate

      • +

    • style_provider – Style provider object to validate

      • +
    +
    +
    Returns:
    +

    The resolved max_rows value after handling repr_rows deprecation

    +
    +
    Raises:
    +
      +

    • ValueError – If any numeric parameter is invalid or constraints are violated

      • +

    • TypeError – If any parameter has invalid type

      • +

    • DeprecationWarning – If repr_rows parameter is used

      • +
    +
    +
    +

    +
    datafusion.dataframe_formatter._validate_positive_int(value: Any, param_name: str) → None
    diff --git a/autoapi/datafusion/expr/index.html b/autoapi/datafusion/expr/index.html index e55ea8720..44cae0131 100644 --- a/autoapi/datafusion/expr/index.html +++ b/autoapi/datafusion/expr/index.html @@ -243,6 +243,11 @@ SQL

    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/autoapi/datafusion/functions/index.html b/autoapi/datafusion/functions/index.html index c50a7b543..bc1a0b1f8 100644 --- a/autoapi/datafusion/functions/index.html +++ b/autoapi/datafusion/functions/index.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/autoapi/datafusion/html_formatter/index.html b/autoapi/datafusion/html_formatter/index.html index 3bb3d0f09..d344fefca 100644 --- a/autoapi/datafusion/html_formatter/index.html +++ b/autoapi/datafusion/html_formatter/index.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/autoapi/datafusion/index.html b/autoapi/datafusion/index.html index d306bc467..21512f265 100644 --- a/autoapi/datafusion/index.html +++ b/autoapi/datafusion/index.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -433,102 +443,91 @@
  • - + - TableFunction + WindowFrame -
    • -
  • - - - - WindowFrame - - - -
    • -
  • - - - - WindowUDF - - - - -
  • @@ -3037,42 +3021,6 @@
    • -
  • - - - - udaf - - - -
    • -
  • - - - - udf - - - -
    • -
  • - - - - udtf - - - -
    • -
  • - - - - udwf - - - -
    • @@ -3115,6 +3063,7 @@

    Submodulesdatafusion.input
  • datafusion.io
  • datafusion.object_store
    • +
  • datafusion.options
  • datafusion.plan
  • datafusion.record_batch
  • datafusion.substrait
    • @@ -3136,18 +3085,6 @@

    Attributes

    column

    -

    udaf

    -

    - -

    udf

    -

    - -

    udtf

    -

    - -

    udwf

    -

    - @@ -3155,69 +3092,57 @@

    Attributes

    - - - - - - - + + + + - + - + - + - + - + - + - + - + - + - + - + - - - - - - - + - - -

    Accumulator

    Defines how an AggregateUDF accumulates values.

    AggregateUDF

    Class for performing scalar user-defined functions (UDF).

    Catalog

    DataFusion data catalog.

    DataFrameWriteOptions

    CsvReadOptions

    Options for reading CSV files.

    DataFrameWriteOptions

    Writer options for DataFrame.

    Database

    Database

    See Schema.

    ExecutionPlan

    ExecutionPlan

    Represent nodes in the DataFusion Physical Plan.

    Expr

    Expr

    Expression object.

    InsertOp

    InsertOp

    Insert operation mode.

    LogicalPlan

    LogicalPlan

    Logical Plan.

    ParquetColumnOptions

    ParquetColumnOptions

    Parquet options for individual columns.

    ParquetWriterOptions

    ParquetWriterOptions

    Advanced parquet writer options.

    RecordBatch

    RecordBatch

    This class is essentially a wrapper for pa.RecordBatch.

    RecordBatchStream

    RecordBatchStream

    This class represents a stream of record batches.

    RuntimeEnvBuilder

    RuntimeEnvBuilder

    Runtime configuration options.

    SQLOptions

    SQLOptions

    Options to be used when performing SQL queries.

    ScalarUDF

    Class for performing scalar user-defined functions (UDF).

    SessionConfig

    Session configuration options.

    Table

    A DataFusion table.

    TableFunction

    Class for performing user-defined table functions (UDTF).

    WindowFrame

    WindowFrame

    Defines a window frame for performing window operations.

    WindowUDF

    Class for performing window user-defined functions (UDF).
    @@ -3251,161 +3176,6 @@

    Functions

    Package Contents

    -
    -
    -class datafusion.Accumulator
    -

    Defines how an AggregateUDF accumulates values.

    -
    -
    -abstract evaluate() → pyarrow.Scalar
    -

    Return the resultant value.

    -
    - -
    -
    -abstract merge(states: list[pyarrow.Array]) → None
    -

    Merge a set of states.

    -
    - -
    -
    -abstract state() → list[pyarrow.Scalar]
    -

    Return the current state.

    -
    - -
    -
    -abstract update(*values: pyarrow.Array) → None
    -

    Evaluate an array of values and update state.

    -
    - -
    - -
    -
    -class datafusion.AggregateUDF(name: str, accumulator: collections.abc.Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str)
    -
    -class datafusion.AggregateUDF(name: str, accumulator: AggregateUDFExportable, input_types: None = ..., return_type: None = ..., state_type: None = ..., volatility: None = ...)
    -

    Class for performing scalar user-defined functions (UDF).

    -

    Aggregate UDFs operate on a group of rows and return a single value. See -also ScalarUDF for operating on a row by row basis.

    -

    Instantiate a user-defined aggregate function (UDAF).

    -

    See udaf() for a convenience function and argument -descriptions.

    -
    -
    -__call__(*args: datafusion.expr.Expr) → datafusion.expr.Expr
    -

    Execute the UDAF.

    -

    This function is not typically called by an end user. These calls will -occur during the evaluation of the dataframe.

    -
    - -
    -
    -__repr__() → str
    -

    Print a string representation of the Aggregate UDF.

    -
    - -
    -
    -static from_pycapsule(func: AggregateUDFExportable | _typeshed.CapsuleType) → AggregateUDF
    -

    Create an Aggregate UDF from AggregateUDF PyCapsule object.

    -

    This function will instantiate a Aggregate UDF that uses a DataFusion -AggregateUDF that is exported via the FFI bindings.

    -
    - -
    -
    -static udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[Ellipsis, AggregateUDF]
    -
    -static udaf(accum: collections.abc.Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → AggregateUDF
    -
    -static udaf(accum: AggregateUDFExportable) → AggregateUDF
    -
    -static udaf(accum: _typeshed.CapsuleType) → AggregateUDF
    -

    Create a new User-Defined Aggregate Function (UDAF).

    -

    This class allows you to define an aggregate function that can be used in -data aggregation or window function calls.

    -
    -
    Usage:
      -

    • As a function: udaf(accum, input_types, return_type, state_type, volatility, name).

      • -

    • As a decorator: @udaf(input_types, return_type, state_type, volatility, name). -When using udaf as a decorator, do not pass accum explicitly.

      • -
    -
    -
    -

    Function example:

    -

    If your Accumulator can be instantiated with no arguments, you -can simply pass it’s type as accum. If you need to pass additional -arguments to it’s constructor, you can define a lambda or a factory method. -During runtime the Accumulator will be constructed for every -instance in which this UDAF is used. The following examples are all valid:

    -
    import pyarrow as pa
-import pyarrow.compute as pc
-
-class Summarize(Accumulator):
-    def __init__(self, bias: float = 0.0):
-        self._sum = pa.scalar(bias)
-
-    def state(self) -> list[pa.Scalar]:
-        return [self._sum]
-
-    def update(self, values: pa.Array) -> None:
-        self._sum = pa.scalar(self._sum.as_py() + pc.sum(values).as_py())
-
-    def merge(self, states: list[pa.Array]) -> None:
-        self._sum = pa.scalar(self._sum.as_py() + pc.sum(states[0]).as_py())
-
-    def evaluate(self) -> pa.Scalar:
-        return self._sum
-
-def sum_bias_10() -> Summarize:
-    return Summarize(10.0)
-
-udaf1 = udaf(Summarize, pa.float64(), pa.float64(), [pa.float64()],
-    "immutable")
-udaf2 = udaf(sum_bias_10, pa.float64(), pa.float64(), [pa.float64()],
-    "immutable")
-udaf3 = udaf(lambda: Summarize(20.0), pa.float64(), pa.float64(),
-    [pa.float64()], "immutable")
-
    -
    -

    Decorator example::

    -
    @udaf(pa.float64(), pa.float64(), [pa.float64()], "immutable")
-def udf4() -> Summarize:
-    return Summarize(10.0)
-
    -
    -
    -
    Parameters:
    -
      -

    • accum – The accumulator python function. Only needed when calling as a -function. Skip this argument when using udaf as a decorator. -If you have a Rust backed AggregateUDF within a PyCapsule, you can -pass this parameter and ignore the rest. They will be determined -directly from the underlying function. See the online documentation -for more information.

      • -

    • input_types – The data types of the arguments to accum.

      • -

    • return_type – The data type of the return value.

      • -

    • state_type – The data types of the intermediate accumulation.

      • -

    • volatility – See Volatility for allowed values.

      • -

    • name – A descriptive name for the function.

      • -
    -
    -
    Returns:
    -

    A user-defined aggregate function, which can be used in either data -aggregation or window function calls.

    -
    -
    -
    - -
    -
    -_udaf
    -
    - -
    -
    class datafusion.Catalog(catalog: datafusion._internal.catalog.RawCatalog)
    @@ -3431,7 +3201,7 @@

    Package Contents
    -static memory_catalog() → Catalog
    +static memory_catalog(ctx: datafusion.SessionContext | None = None) → Catalog

    Create an in-memory catalog provider.

    @@ -3466,6 +3236,229 @@

    Package Contents +
    +class datafusion.CsvReadOptions(*, has_header: bool = True, delimiter: str = ',', quote: str = '"', terminator: str | None = None, escape: str | None = None, comment: str | None = None, newlines_in_values: bool = False, schema: pyarrow.Schema | None = None, schema_infer_max_records: int = DEFAULT_MAX_INFER_SCHEMA, file_extension: str = '.csv', table_partition_cols: list[tuple[str, pyarrow.DataType]] | None = None, file_compression_type: str = '', file_sort_order: list[list[datafusion.expr.SortExpr]] | None = None, null_regex: str | None = None, truncated_rows: bool = False)
    +

    Options for reading CSV files.

    +

    This class provides a builder pattern for configuring CSV reading options. +All methods starting with with_ return self to allow method chaining.

    +

    Initialize CsvReadOptions.

    +
    +
    Parameters:
    +
      +

    • has_header – Does the CSV file have a header row? If schema inference +is run on a file with no headers, default column names are created.

      • +

    • delimiter – Column delimiter character. Must be a single ASCII character.

      • +

    • quote – Quote character for fields containing delimiters or newlines. +Must be a single ASCII character.

      • +

    • terminator – Optional line terminator character. If None, uses CRLF. +Must be a single ASCII character.

      • +

    • escape – Optional escape character for quotes. Must be a single ASCII +character.

      • +

    • comment – If specified, lines beginning with this character are ignored. +Must be a single ASCII character.

      • +

    • newlines_in_values – Whether newlines in quoted values are supported. +Parsing newlines in quoted values may be affected by execution +behavior such as parallel file scanning. Setting this to True +ensures that newlines in values are parsed successfully, which may +reduce performance.

      • +

    • schema – Optional PyArrow schema representing the CSV files. If None, +the CSV reader will try to infer it based on data in the file.

      • +

    • schema_infer_max_records – Maximum number of rows to read from CSV files +for schema inference if needed.

      • +

    • file_extension – File extension; only files with this extension are +selected for data input.

      • +

    • table_partition_cols – Partition columns as a list of tuples of +(column_name, data_type).

      • +

    • file_compression_type – File compression type. Supported values are +"gzip", "bz2", "xz", "zstd", or empty string for +uncompressed.

      • +

    • file_sort_order – Optional sort order of the files as a list of sort +expressions per file.

      • +

    • null_regex – Optional regex pattern to match null values in the CSV.

      • +

    • truncated_rows – Whether to allow truncated rows when parsing. By default +this is False and will error if the CSV rows have different +lengths. When set to True, it will allow records with less than +the expected number of columns and fill the missing columns with +nulls. If the record’s schema is not nullable, it will still return +an error.

      • +
    +
    +
    +
    +
    +to_inner() → datafusion._internal.options.CsvReadOptions
    +

    Convert this object into the underlying Rust structure.

    +

    This is intended for internal use only.

    +
    + +
    +
    +with_comment(comment: str | None) → CsvReadOptions
    +

    Configure the comment character.

    +
    + +
    +
    +with_delimiter(delimiter: str) → CsvReadOptions
    +

    Configure the column delimiter.

    +
    + +
    +
    +with_escape(escape: str | None) → CsvReadOptions
    +

    Configure the escape character.

    +
    + +
    +
    +with_file_compression_type(file_compression_type: str) → CsvReadOptions
    +

    Configure file compression type.

    +
    + +
    +
    +with_file_extension(file_extension: str) → CsvReadOptions
    +

    Configure the file extension filter.

    +
    + +
    +
    +with_file_sort_order(file_sort_order: list[list[datafusion.expr.SortExpr]]) → CsvReadOptions
    +

    Configure file sort order.

    +
    + +
    +
    +with_has_header(has_header: bool) → CsvReadOptions
    +

    Configure whether the CSV has a header row.

    +
    + +
    +
    +with_newlines_in_values(newlines_in_values: bool) → CsvReadOptions
    +

    Configure whether newlines in values are supported.

    +
    + +
    +
    +with_null_regex(null_regex: str | None) → CsvReadOptions
    +

    Configure null value regex pattern.

    +
    + +
    +
    +with_quote(quote: str) → CsvReadOptions
    +

    Configure the quote character.

    +
    + +
    +
    +with_schema(schema: pyarrow.Schema | None) → CsvReadOptions
    +

    Configure the schema.

    +
    + +
    +
    +with_schema_infer_max_records(schema_infer_max_records: int) → CsvReadOptions
    +

    Configure maximum records for schema inference.

    +
    + +
    +
    +with_table_partition_cols(table_partition_cols: list[tuple[str, pyarrow.DataType]]) → CsvReadOptions
    +

    Configure table partition columns.

    +
    + +
    +
    +with_terminator(terminator: str | None) → CsvReadOptions
    +

    Configure the line terminator character.

    +
    + +
    +
    +with_truncated_rows(truncated_rows: bool) → CsvReadOptions
    +

    Configure whether to allow truncated rows.

    +
    + +
    +
    +comment = None
    +
    + +
    +
    +delimiter = ','
    +
    + +
    +
    +escape = None
    +
    + +
    +
    +file_compression_type = ''
    +
    + +
    +
    +file_extension = '.csv'
    +
    + +
    +
    +file_sort_order = []
    +
    + +
    +
    +has_header = True
    +
    + +
    +
    +newlines_in_values = False
    +
    + +
    +
    +null_regex = None
    +
    + +
    +
    +quote = '"'
    +
    + +
    +
    +schema = None
    +
    + +
    +
    +schema_infer_max_records = 1000
    +
    + +
    +
    +table_partition_cols = []
    +
    + +
    +
    +terminator = None
    +
    + +
    +
    +truncated_rows = False
    +
    + +
    +
    class datafusion.DataFrameWriteOptions(insert_operation: InsertOp | None = None, single_file_output: bool = False, partition_by: str | collections.abc.Sequence[str] | None = None, sort_by: datafusion.expr.Expr | datafusion.expr.SortExpr | collections.abc.Sequence[datafusion.expr.Expr] | collections.abc.Sequence[datafusion.expr.SortExpr] | None = None)
    @@ -5045,96 +5038,6 @@

    Returns:

    -
    -
    -class datafusion.ScalarUDF(name: str, func: collections.abc.Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)
    -

    Class for performing scalar user-defined functions (UDF).

    -

    Scalar UDFs operate on a row by row basis. See also AggregateUDF for -operating on a group of rows.

    -

    Instantiate a scalar user-defined function (UDF).

    -

    See helper method udf() for argument details.

    -
    -
    -__call__(*args: datafusion.expr.Expr) → datafusion.expr.Expr
    -

    Execute the UDF.

    -

    This function is not typically called by an end user. These calls will -occur during the evaluation of the dataframe.

    -
    - -
    -
    -__repr__() → str
    -

    Print a string representation of the Scalar UDF.

    -
    - -
    -
    -static from_pycapsule(func: ScalarUDFExportable) → ScalarUDF
    -

    Create a Scalar UDF from ScalarUDF PyCapsule object.

    -

    This function will instantiate a Scalar UDF that uses a DataFusion -ScalarUDF that is exported via the FFI bindings.

    -
    - -
    -
    -static udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[Ellipsis, ScalarUDF]
    -
    -static udf(func: collections.abc.Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → ScalarUDF
    -
    -static udf(func: ScalarUDFExportable) → ScalarUDF
    -

    Create a new User-Defined Function (UDF).

    -

    This class can be used both as either a function or a decorator.

    -
    -
    Usage:
      -

    • As a function: udf(func, input_types, return_type, volatility, name).

      • -

    • As a decorator: @udf(input_types, return_type, volatility, name). -When used a decorator, do not pass func explicitly.

      • -
    -
    -
    -
    -
    Parameters:
    -
      -

    • func (Callable, optional) – Only needed when calling as a function. -Skip this argument when using udf as a decorator. If you have a Rust -backed ScalarUDF within a PyCapsule, you can pass this parameter -and ignore the rest. They will be determined directly from the -underlying function. See the online documentation for more information.

      • -

    • input_types (list[pa.DataType]) – The data types of the arguments -to func. This list must be of the same length as the number of -arguments.

      • -

    • return_type (_R) – The data type of the return value from the function.

      • -

    • volatility (Volatility | str) – See Volatility for allowed values.

      • -

    • name (Optional[str]) – A descriptive name for the function.

      • -
    -
    -
    Returns:
    -

    A user-defined function that can be used in SQL expressions, -data aggregation, or window function calls.

    -
    -
    -

    Example: Using udf as a function:

    -
    def double_func(x):
-    return x * 2
-double_udf = udf(double_func, [pa.int32()], pa.int32(),
-"volatile", "double_it")
-
    -
    -

    Example: Using udf as a decorator:

    -
    @udf([pa.int32()], pa.int32(), "volatile", "double_it")
-def double_udf(x):
-    return x * 2
-
    -
    -
    - -
    -
    -_udf
    -
    - -
    -
    class datafusion.SessionConfig(config_options: dict[str, str] | None = None)
    @@ -5345,7 +5248,7 @@

    Returns:
    -class datafusion.Table(table: Table | datafusion.context.TableProviderExportable | datafusion.DataFrame | pyarrow.dataset.Dataset)
    +class datafusion.Table(table: Table | datafusion.context.TableProviderExportable | datafusion.DataFrame | pyarrow.dataset.Dataset, ctx: datafusion.SessionContext | None = None)

    A DataFusion table.

    Internally we currently support the following types of tables:

      @@ -5393,54 +5296,6 @@

      Returns:

    -
    -
    -class datafusion.TableFunction(name: str, func: collections.abc.Callable[[], any])
    -

    Class for performing user-defined table functions (UDTF).

    -

    Table functions generate new table providers based on the -input expressions.

    -

    Instantiate a user-defined table function (UDTF).

    -

    See udtf() for a convenience function and argument -descriptions.

    -
    -
    -__call__(*args: datafusion.expr.Expr) → Any
    -

    Execute the UDTF and return a table provider.

    -
    - -
    -
    -__repr__() → str
    -

    User printable representation.

    -
    - -
    -
    -static _create_table_udf(func: collections.abc.Callable[Ellipsis, Any], name: str) → TableFunction
    -

    Create a TableFunction instance from function arguments.

    -
    - -
    -
    -static _create_table_udf_decorator(name: str | None = None) → collections.abc.Callable[[collections.abc.Callable[[], WindowEvaluator]], collections.abc.Callable[Ellipsis, datafusion.expr.Expr]]
    -

    Create a decorator for a WindowUDF.

    -
    - -
    -
    -static udtf(name: str) → collections.abc.Callable[Ellipsis, Any]
    -
    -static udtf(func: collections.abc.Callable[[], Any], name: str) → TableFunction
    -

    Create a new User-Defined Table Function (UDTF).

    -
    - -
    -
    -_udtf
    -
    - -
    -
    class datafusion.WindowFrame(units: str, start_bound: Any | None, end_bound: Any | None)
    @@ -5490,128 +5345,6 @@

    Returns:

    -
    -
    -class datafusion.WindowUDF(name: str, func: collections.abc.Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str)
    -

    Class for performing window user-defined functions (UDF).

    -

    Window UDFs operate on a partition of rows. See -also ScalarUDF for operating on a row by row basis.

    -

    Instantiate a user-defined window function (UDWF).

    -

    See udwf() for a convenience function and argument -descriptions.

    -
    -
    -__call__(*args: datafusion.expr.Expr) → datafusion.expr.Expr
    -

    Execute the UDWF.

    -

    This function is not typically called by an end user. These calls will -occur during the evaluation of the dataframe.

    -
    - -
    -
    -__repr__() → str
    -

    Print a string representation of the Window UDF.

    -
    - -
    -
    -static _create_window_udf(func: collections.abc.Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
    -

    Create a WindowUDF instance from function arguments.

    -
    - -
    -
    -static _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[[collections.abc.Callable[[], WindowEvaluator]], collections.abc.Callable[Ellipsis, datafusion.expr.Expr]]
    -

    Create a decorator for a WindowUDF.

    -
    - -
    -
    -static _get_default_name(func: collections.abc.Callable) → str
    -

    Get the default name for a function based on its attributes.

    -
    - -
    -
    -static _normalize_input_types(input_types: pyarrow.DataType | list[pyarrow.DataType]) → list[pyarrow.DataType]
    -

    Convert a single DataType to a list if needed.

    -
    - -
    -
    -static from_pycapsule(func: WindowUDFExportable) → WindowUDF
    -

    Create a Window UDF from WindowUDF PyCapsule object.

    -

    This function will instantiate a Window UDF that uses a DataFusion -WindowUDF that is exported via the FFI bindings.

    -
    - -
    -
    -static udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[Ellipsis, WindowUDF]
    -
    -static udwf(func: collections.abc.Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
    -

    Create a new User-Defined Window Function (UDWF).

    -

    This class can be used both as either a function or a decorator.

    -
    -
    Usage:
      -

    • As a function: udwf(func, input_types, return_type, volatility, name).

      • -

    • As a decorator: @udwf(input_types, return_type, volatility, name). -When using udwf as a decorator, do not pass func explicitly.

      • -
    -
    -
    -

    Function example:

    -
    import pyarrow as pa
-
-class BiasedNumbers(WindowEvaluator):
-    def __init__(self, start: int = 0) -> None:
-        self.start = start
-
-    def evaluate_all(self, values: list[pa.Array],
-        num_rows: int) -> pa.Array:
-        return pa.array([self.start + i for i in range(num_rows)])
-
-def bias_10() -> BiasedNumbers:
-    return BiasedNumbers(10)
-
-udwf1 = udwf(BiasedNumbers, pa.int64(), pa.int64(), "immutable")
-udwf2 = udwf(bias_10, pa.int64(), pa.int64(), "immutable")
-udwf3 = udwf(lambda: BiasedNumbers(20), pa.int64(), pa.int64(), "immutable")
-
    -
    -

    Decorator example:

    -
    @udwf(pa.int64(), pa.int64(), "immutable")
-def biased_numbers() -> BiasedNumbers:
-    return BiasedNumbers(10)
-
    -
    -
    -
    Parameters:
    -
      -

    • func – Only needed when calling as a function. Skip this argument when -using udwf as a decorator. If you have a Rust backed WindowUDF -within a PyCapsule, you can pass this parameter and ignore the rest. -They will be determined directly from the underlying function. See -the online documentation for more information.

      • -

    • input_types – The data types of the arguments.

      • -

    • return_type – The data type of the return value.

      • -

    • volatility – See Volatility for allowed values.

      • -

    • name – A descriptive name for the function.

      • -
    -
    -
    Returns:
    -

    A user-defined window function that can be used in window function calls.

    -
    -
    -
    - -
    -
    -_udwf
    -
    - -
    -
    datafusion.configure_formatter(**kwargs: Any) → None
    @@ -5675,7 +5408,7 @@

    Returns:
    -datafusion.read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None) → datafusion.dataframe.DataFrame
    +datafusion.read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None, options: datafusion.options.CsvReadOptions | None = None) → datafusion.dataframe.DataFrame

    Read a CSV data source.

    This function will use the global context. Any functions or tables registered with another context may not be accessible when used with a DataFrame created @@ -5696,6 +5429,8 @@

    Returns:

  • table_partition_cols – Partition columns.

  • file_compression_type – File compression type.

    • +

  • options – Set advanced options for CSV reading. This cannot be +combined with any of the other options in this method.

    • Returns:
    @@ -5776,26 +5511,6 @@

    Returns:datafusion.column: Col

    -
    -
    -datafusion.udaf
    -
    - -
    -
    -datafusion.udf
    -
    - -
    -
    -datafusion.udtf
    -
    - -
    -
    -datafusion.udwf
    -
    - diff --git a/autoapi/datafusion/input/base/index.html b/autoapi/datafusion/input/base/index.html index c3af14fc7..0a4a58427 100644 --- a/autoapi/datafusion/input/base/index.html +++ b/autoapi/datafusion/input/base/index.html @@ -243,6 +243,11 @@ SQL +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/autoapi/datafusion/input/index.html b/autoapi/datafusion/input/index.html index 8be1dcc2b..ea03669e9 100644 --- a/autoapi/datafusion/input/index.html +++ b/autoapi/datafusion/input/index.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/autoapi/datafusion/input/location/index.html b/autoapi/datafusion/input/location/index.html index 65c4af52b..29dc97743 100644 --- a/autoapi/datafusion/input/location/index.html +++ b/autoapi/datafusion/input/location/index.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/autoapi/datafusion/io/index.html b/autoapi/datafusion/io/index.html index d2a42167e..ce57fb983 100644 --- a/autoapi/datafusion/io/index.html +++ b/autoapi/datafusion/io/index.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -524,7 +534,7 @@

    Module Contents
    -datafusion.io.read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None) → datafusion.dataframe.DataFrame
    +datafusion.io.read_csv(path: str | pathlib.Path | list[str] | list[pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = 1000, file_extension: str = '.csv', table_partition_cols: list[tuple[str, str | pyarrow.DataType]] | None = None, file_compression_type: str | None = None, options: datafusion.options.CsvReadOptions | None = None) → datafusion.dataframe.DataFrame

    Read a CSV data source.

    This function will use the global context. Any functions or tables registered with another context may not be accessible when used with a DataFrame created @@ -545,6 +555,8 @@

    Module ContentsReturns: diff --git a/autoapi/datafusion/object_store/index.html b/autoapi/datafusion/object_store/index.html index 9a4a9595e..8b1ad2c2d 100644 --- a/autoapi/datafusion/object_store/index.html +++ b/autoapi/datafusion/object_store/index.html @@ -34,7 +34,7 @@ - + @@ -243,6 +243,11 @@ SQL

    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -553,10 +563,10 @@

    Module Contentsdatafusion.io

     - +

    next

    -

    datafusion.plan

    +

    datafusion.options

     diff --git a/autoapi/datafusion/options/index.html b/autoapi/datafusion/options/index.html new file mode 100644 index 000000000..e436b87f5 --- /dev/null +++ b/autoapi/datafusion/options/index.html @@ -0,0 +1,1039 @@ + + + + + + + + datafusion.options — Apache Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + +
    +
    + + + + +
    + + +
    + + +
    +
    +
    +
    + + + + +
    + + +
    + +
    + On this page +
    + + +
    + +
    + +
    + + +
    + + + + + + +
    + +
    + +
    +

    datafusion.options

    +

    Options for reading various file formats.

    +
    +

    Classes

    + + + + + + +

    CsvReadOptions

    Options for reading CSV files.

    +
    +
    +

    Module Contents

    +
    +
    +class datafusion.options.CsvReadOptions(*, has_header: bool = True, delimiter: str = ',', quote: str = '"', terminator: str | None = None, escape: str | None = None, comment: str | None = None, newlines_in_values: bool = False, schema: pyarrow.Schema | None = None, schema_infer_max_records: int = DEFAULT_MAX_INFER_SCHEMA, file_extension: str = '.csv', table_partition_cols: list[tuple[str, pyarrow.DataType]] | None = None, file_compression_type: str = '', file_sort_order: list[list[datafusion.expr.SortExpr]] | None = None, null_regex: str | None = None, truncated_rows: bool = False)
    +

    Options for reading CSV files.

    +

    This class provides a builder pattern for configuring CSV reading options. +All methods starting with with_ return self to allow method chaining.

    +

    Initialize CsvReadOptions.

    +
    +
    Parameters:
    +
      +

    • has_header – Does the CSV file have a header row? If schema inference +is run on a file with no headers, default column names are created.

      • +

    • delimiter – Column delimiter character. Must be a single ASCII character.

      • +

    • quote – Quote character for fields containing delimiters or newlines. +Must be a single ASCII character.

      • +

    • terminator – Optional line terminator character. If None, uses CRLF. +Must be a single ASCII character.

      • +

    • escape – Optional escape character for quotes. Must be a single ASCII +character.

      • +

    • comment – If specified, lines beginning with this character are ignored. +Must be a single ASCII character.

      • +

    • newlines_in_values – Whether newlines in quoted values are supported. +Parsing newlines in quoted values may be affected by execution +behavior such as parallel file scanning. Setting this to True +ensures that newlines in values are parsed successfully, which may +reduce performance.

      • +

    • schema – Optional PyArrow schema representing the CSV files. If None, +the CSV reader will try to infer it based on data in the file.

      • +

    • schema_infer_max_records – Maximum number of rows to read from CSV files +for schema inference if needed.

      • +

    • file_extension – File extension; only files with this extension are +selected for data input.

      • +

    • table_partition_cols – Partition columns as a list of tuples of +(column_name, data_type).

      • +

    • file_compression_type – File compression type. Supported values are +"gzip", "bz2", "xz", "zstd", or empty string for +uncompressed.

      • +

    • file_sort_order – Optional sort order of the files as a list of sort +expressions per file.

      • +

    • null_regex – Optional regex pattern to match null values in the CSV.

      • +

    • truncated_rows – Whether to allow truncated rows when parsing. By default +this is False and will error if the CSV rows have different +lengths. When set to True, it will allow records with less than +the expected number of columns and fill the missing columns with +nulls. If the record’s schema is not nullable, it will still return +an error.

      • +
    +
    +
    +
    +
    +to_inner() → datafusion._internal.options.CsvReadOptions
    +

    Convert this object into the underlying Rust structure.

    +

    This is intended for internal use only.

    +
    + +
    +
    +with_comment(comment: str | None) → CsvReadOptions
    +

    Configure the comment character.

    +
    + +
    +
    +with_delimiter(delimiter: str) → CsvReadOptions
    +

    Configure the column delimiter.

    +
    + +
    +
    +with_escape(escape: str | None) → CsvReadOptions
    +

    Configure the escape character.

    +
    + +
    +
    +with_file_compression_type(file_compression_type: str) → CsvReadOptions
    +

    Configure file compression type.

    +
    + +
    +
    +with_file_extension(file_extension: str) → CsvReadOptions
    +

    Configure the file extension filter.

    +
    + +
    +
    +with_file_sort_order(file_sort_order: list[list[datafusion.expr.SortExpr]]) → CsvReadOptions
    +

    Configure file sort order.

    +
    + +
    +
    +with_has_header(has_header: bool) → CsvReadOptions
    +

    Configure whether the CSV has a header row.

    +
    + +
    +
    +with_newlines_in_values(newlines_in_values: bool) → CsvReadOptions
    +

    Configure whether newlines in values are supported.

    +
    + +
    +
    +with_null_regex(null_regex: str | None) → CsvReadOptions
    +

    Configure null value regex pattern.

    +
    + +
    +
    +with_quote(quote: str) → CsvReadOptions
    +

    Configure the quote character.

    +
    + +
    +
    +with_schema(schema: pyarrow.Schema | None) → CsvReadOptions
    +

    Configure the schema.

    +
    + +
    +
    +with_schema_infer_max_records(schema_infer_max_records: int) → CsvReadOptions
    +

    Configure maximum records for schema inference.

    +
    + +
    +
    +with_table_partition_cols(table_partition_cols: list[tuple[str, pyarrow.DataType]]) → CsvReadOptions
    +

    Configure table partition columns.

    +
    + +
    +
    +with_terminator(terminator: str | None) → CsvReadOptions
    +

    Configure the line terminator character.

    +
    + +
    +
    +with_truncated_rows(truncated_rows: bool) → CsvReadOptions
    +

    Configure whether to allow truncated rows.

    +
    + +
    +
    +comment = None
    +
    + +
    +
    +delimiter = ','
    +
    + +
    +
    +escape = None
    +
    + +
    +
    +file_compression_type = ''
    +
    + +
    +
    +file_extension = '.csv'
    +
    + +
    +
    +file_sort_order = []
    +
    + +
    +
    +has_header = True
    +
    + +
    +
    +newlines_in_values = False
    +
    + +
    +
    +null_regex = None
    +
    + +
    +
    +quote = '"'
    +
    + +
    +
    +schema = None
    +
    + +
    +
    +schema_infer_max_records = 1000
    +
    + +
    +
    +table_partition_cols = []
    +
    + +
    +
    +terminator = None
    +
    + +
    +
    +truncated_rows = False
    +
    + +
    + +
    +
    + + +
    + + + +
    + + +
    +

    previous

    +

    datafusion.object_store

    +
    +     + +
    +

    next

    +

    datafusion.plan

    +
    + +     +
    + +
    + + +
    +
    + + + + +
    +
    + +
    +

    + © Copyright 2019-2024, Apache Software Foundation.
    +

    +
    + +
    +

    +Created using Sphinx 8.1.3.
    +

    +
    + +
    +

    Apache Arrow DataFusion, Arrow DataFusion, Apache, the Apache feather logo, and the Apache Arrow DataFusion project logo

    +

    are either registered trademarks or trademarks of The Apache Software Foundation in the United States and other countries.

    +
    +
    +
    + + + + \ No newline at end of file diff --git a/autoapi/datafusion/plan/index.html b/autoapi/datafusion/plan/index.html index 53fa3a57d..da7b1c25d 100644 --- a/autoapi/datafusion/plan/index.html +++ b/autoapi/datafusion/plan/index.html @@ -35,7 +35,7 @@ - + @@ -243,6 +243,11 @@ SQL

    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -787,11 +797,11 @@

    Module Contents +

    previous

    -

    datafusion.object_store

    +

    datafusion.options

     diff --git a/autoapi/datafusion/record_batch/index.html b/autoapi/datafusion/record_batch/index.html index e36e3aa65..473630d11 100644 --- a/autoapi/datafusion/record_batch/index.html +++ b/autoapi/datafusion/record_batch/index.html @@ -243,6 +243,11 @@ SQL

    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/autoapi/datafusion/substrait/index.html b/autoapi/datafusion/substrait/index.html index a835be508..748f75d20 100644 --- a/autoapi/datafusion/substrait/index.html +++ b/autoapi/datafusion/substrait/index.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/autoapi/datafusion/unparser/index.html b/autoapi/datafusion/unparser/index.html index f6704c9d3..f88e76e22 100644 --- a/autoapi/datafusion/unparser/index.html +++ b/autoapi/datafusion/unparser/index.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/autoapi/datafusion/user_defined/index.html b/autoapi/datafusion/user_defined/index.html index df04d4b83..0686e59c0 100644 --- a/autoapi/datafusion/user_defined/index.html +++ b/autoapi/datafusion/user_defined/index.html @@ -242,6 +242,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -353,6 +358,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -950,6 +960,24 @@
    • +
  • + + + + data_type_or_field_to_field() + + + +
    • +
  • + + + + data_types_or_fields_to_field_list() + + + +
  • @@ -1087,6 +1115,12 @@

    Functions

    _is_pycapsule(→ TypeGuard[_typeshed.CapsuleType])

    Return True when value is a CPython PyCapsule.

    +

    data_type_or_field_to_field(→ pyarrow.Field)

    +

    Helper function to return a Field from either a Field or DataType.

    + +

    data_types_or_fields_to_field_list(→ list[pyarrow.Field])

    +

    Helper function to return a list of Fields.

    + @@ -1261,7 +1295,7 @@

    Module Contents
    -class datafusion.user_defined.ScalarUDF(name: str, func: collections.abc.Callable[Ellipsis, _R], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: _R, volatility: Volatility | str)
    +class datafusion.user_defined.ScalarUDF(name: str, func: collections.abc.Callable[Ellipsis, _R], input_fields: list[pyarrow.Field], return_field: _R, volatility: Volatility | str)

    Class for performing scalar user-defined functions (UDF).

    Scalar UDFs operate on a row by row basis. See also AggregateUDF for operating on a group of rows.

    @@ -1291,21 +1325,24 @@

    Module Contents
    -static udf(input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[Ellipsis, ScalarUDF]
    +static udf(input_fields: collections.abc.Sequence[pyarrow.DataType | pyarrow.Field] | pyarrow.DataType | pyarrow.Field, return_field: pyarrow.DataType | pyarrow.Field, volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[Ellipsis, ScalarUDF]
    -static udf(func: collections.abc.Callable[Ellipsis, _R], input_types: list[pyarrow.DataType], return_type: _R, volatility: Volatility | str, name: str | None = None) → ScalarUDF
    +static udf(func: collections.abc.Callable[Ellipsis, _R], input_fields: collections.abc.Sequence[pyarrow.DataType | pyarrow.Field] | pyarrow.DataType | pyarrow.Field, return_field: pyarrow.DataType | pyarrow.Field, volatility: Volatility | str, name: str | None = None) → ScalarUDF
    static udf(func: ScalarUDFExportable) → ScalarUDF

    Create a new User-Defined Function (UDF).

    This class can be used both as either a function or a decorator.

    Usage:
      -

    • As a function: udf(func, input_types, return_type, volatility, name).

      • -

    • As a decorator: @udf(input_types, return_type, volatility, name). +

    • As a function: udf(func, input_fields, return_field, volatility, name).

      • +

    • As a decorator: @udf(input_fields, return_field, volatility, name). When used a decorator, do not pass func explicitly.

    +

    In lieu of passing a PyArrow Field, you can pass a DataType for simplicity. +When you do so, it will be assumed that the nullability of the inputs and +output are True and that they have no metadata.

    Parameters:
    @@ -1363,7 +1400,7 @@

    Module Contents
    -class datafusion.user_defined.TableFunction(name: str, func: collections.abc.Callable[[], any])
    +class datafusion.user_defined.TableFunction(name: str, func: collections.abc.Callable[[], any], ctx: datafusion.SessionContext | None = None)

    Class for performing user-defined table functions (UDTF).

    Table functions generate new table providers based on the input expressions.

    @@ -1774,6 +1811,18 @@

    Module ContentsTrue when value is a CPython PyCapsule.

    +
    +
    +datafusion.user_defined.data_type_or_field_to_field(value: pyarrow.DataType | pyarrow.Field, name: str) → pyarrow.Field
    +

    Helper function to return a Field from either a Field or DataType.

    +
    + +
    +
    +datafusion.user_defined.data_types_or_fields_to_field_list(inputs: collections.abc.Sequence[pyarrow.Field | pyarrow.DataType] | pyarrow.Field | pyarrow.DataType) → list[pyarrow.Field]
    +

    Helper function to return a list of Fields.

    +
    +
    datafusion.user_defined._R
    diff --git a/autoapi/index.html b/autoapi/index.html index b79037d04..f209f86f6 100644 --- a/autoapi/index.html +++ b/autoapi/index.html @@ -243,6 +243,11 @@ SQL

    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -443,6 +453,7 @@

    API Referencedatafusion.io

  • datafusion.object_store
    • +
  • datafusion.options
  • datafusion.plan
  • datafusion.record_batch
  • datafusion.substrait
    • diff --git a/contributor-guide/ffi.html b/contributor-guide/ffi.html index 1c61dffea..e48533bb9 100644 --- a/contributor-guide/ffi.html +++ b/contributor-guide/ffi.html @@ -243,6 +243,11 @@ SQL +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -464,7 +474,7 @@
    -

    Python Extensions

    +

    Python Extensions

    The DataFusion in Python project is designed to allow users to extend its functionality in a few core areas. Ideally many users would like to package their extensions as a Python package and easily integrate that package with this project. This page serves to describe some of the challenges we face diff --git a/contributor-guide/introduction.html b/contributor-guide/introduction.html index 255f40973..d9cc00b36 100644 --- a/contributor-guide/introduction.html +++ b/contributor-guide/introduction.html @@ -35,7 +35,7 @@ - + @@ -243,6 +243,11 @@ SQL

    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -571,11 +581,11 @@

    Improving Build Speed
    - +

    previous

    -

    SQL

    +

    Upgrade Guides

     diff --git a/genindex.html b/genindex.html index a36dc3da4..7390ebec7 100644 --- a/genindex.html +++ b/genindex.html @@ -240,6 +240,11 @@ SQL

    • +
  • + + Upgrade Guides + +

    • @@ -351,6 +356,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -427,6 +437,7 @@

    Index

    |     N | O | P + | Q | R | S | T @@ -479,15 +490,9 @@

    _

  • (datafusion.dataframe.DataFrame method)
    • -
  • __call__() (datafusion.AggregateUDF method) +
  • __call__() (datafusion.dataframe_formatter.CellFormatter method)
  • __datafusion_aggregate_udf__() (datafusion.user_defined.AggregateUDFExportable method)
  • __datafusion_catalog_provider__() (datafusion.context.CatalogProviderExportable method) +
    • +
  • __datafusion_logical_extension_codec__() (datafusion.context.SessionContext method)
  • __datafusion_scalar_udf__() (datafusion.user_defined.ScalarUDFExportable method)
  • __datafusion_table_provider__() (datafusion.context.TableProviderExportable method) +
    • +
  • __datafusion_task_context_provider__() (datafusion.context.SessionContext method)
  • __datafusion_window_udf__() (datafusion.user_defined.WindowUDFExportable method)
    • @@ -603,11 +610,9 @@

    _

  • (datafusion.expr.Expr attribute)
    • -
  • __repr__() (datafusion.AggregateUDF method) +
  • __repr__() (datafusion.Catalog method)
    • @@ -729,30 +728,14 @@

    _

  • _convert_table_partition_cols() (datafusion.context.SessionContext static method)
    • -
  • _create_table_udf() (datafusion.TableFunction static method) - -
    • -
  • _create_table_udf_decorator() (datafusion.TableFunction static method) - -
  • _create_window_udf() (datafusion.user_defined.WindowUDF static method) - -
  • _create_window_udf_decorator() (datafusion.user_defined.WindowUDF static method) - -
  • _custom_cell_builder (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
  • _custom_header_builder (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute) @@ -766,11 +749,7 @@

    _

  • _get_default_css() (datafusion.dataframe_formatter.DataFrameHtmlFormatter method)
  • _get_default_name() (datafusion.user_defined.WindowUDF static method) - -
  • _get_javascript() (datafusion.dataframe_formatter.DataFrameHtmlFormatter method)
  • _inner (datafusion.catalog.Table attribute) @@ -780,13 +759,11 @@

    _

  • _is_pycapsule() (in module datafusion.user_defined) +
    • +
  • _max_rows (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
  • _normalize_input_types() (datafusion.user_defined.WindowUDF static method) - -
  • _null_treatment (datafusion.expr.Window attribute)
  • _order_by (datafusion.expr.Window attribute) @@ -825,31 +802,17 @@

    _

  • _type_formatters (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
    • -
  • _udaf (datafusion.AggregateUDF attribute) - -
    • -
  • _udf (datafusion.ScalarUDF attribute) - -
    • -
  • _udtf (datafusion.TableFunction attribute) - -
  • _udwf (datafusion.user_defined.WindowUDF attribute) - -
  • _validate_bool() (in module datafusion.dataframe_formatter) +
    • +
  • _validate_formatter_parameters() (in module datafusion.dataframe_formatter)
  • _validate_positive_int() (in module datafusion.dataframe_formatter)
    • @@ -869,12 +832,8 @@

    A

  • (in module datafusion.functions)
    • -
  • Accumulator (class in datafusion) - -
  • acos() (datafusion.Expr method) - + - +
    • +
  • data_type_or_field_to_field() (in module datafusion.user_defined) +
    • +
  • data_types_or_fields_to_field_list() (in module datafusion.user_defined) +
  • Database (class in datafusion)
  • database() (datafusion.Catalog method) @@ -1590,6 +1561,13 @@

    D

    • +
  • + datafusion.options + +
  • @@ -1636,11 +1614,11 @@

    D

  • datepart() (in module datafusion.functions)
  • datetrunc() (in module datafusion.functions) -
    • -
  • Deallocate (in module datafusion.expr)
    • +
  • delimiter (datafusion.CsvReadOptions attribute) + +
  • dense_rank() (in module datafusion.functions) @@ -1817,20 +1801,24 @@

    E

  • ensure_expr_list() (in module datafusion.expr)
    • -
  • evaluate() (datafusion.Accumulator method) +
  • escape (datafusion.CsvReadOptions attribute)
    • +
  • evaluate() (datafusion.user_defined.Accumulator method) + +
  • evaluate_all() (datafusion.user_defined.WindowEvaluator method) -
    • -
  • evaluate_all_with_rank() (datafusion.user_defined.WindowEvaluator method)
    • +
  • file_compression_type (datafusion.CsvReadOptions attribute) + +
    • +
  • file_extension (datafusion.CsvReadOptions attribute) + +
    • +
  • file_sort_order (datafusion.CsvReadOptions attribute) + +
  • FileType (in module datafusion.expr) @@ -1943,14 +1949,14 @@

    F

  • (in module datafusion.functions)
    • + + - -
  • from_pycapsule() (datafusion.AggregateUDF static method) +
  • from_pycapsule() (datafusion.user_defined.AggregateUDF static method)
  • from_pydict() (datafusion.context.SessionContext method) @@ -2073,10 +2073,16 @@

    G

    H

    @@ -2441,6 +2447,8 @@

    M

  • (datafusion.ParquetWriterOptions attribute)
    • +
  • max_rows (datafusion.dataframe_formatter.DataFrameHtmlFormatter property) +
  • max_width (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
  • maximum_buffered_record_batches_per_stream (datafusion.dataframe.ParquetWriterOptions attribute) @@ -2477,19 +2485,15 @@

    M

  • memory_schema() (datafusion.catalog.Schema static method)
    • -
  • merge() (datafusion.Accumulator method) - -
    • +

    Q

    + + +
    +

    R

    + - @@ -728,14 +748,30 @@

    _

  • _convert_table_partition_cols() (datafusion.context.SessionContext static method)
    • -
  • _create_table_udf() (datafusion.user_defined.TableFunction static method) +
  • _create_table_udf() (datafusion.TableFunction static method) + +
    • +
  • _create_table_udf_decorator() (datafusion.TableFunction static method) + +
  • _create_window_udf() (datafusion.user_defined.WindowUDF static method) + +
  • _create_window_udf_decorator() (datafusion.user_defined.WindowUDF static method) + +
  • _custom_cell_builder (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
  • _custom_header_builder (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute) @@ -749,7 +785,11 @@

    _

  • _get_default_css() (datafusion.dataframe_formatter.DataFrameHtmlFormatter method)
  • _get_default_name() (datafusion.user_defined.WindowUDF static method) + +
  • _get_javascript() (datafusion.dataframe_formatter.DataFrameHtmlFormatter method)
  • _inner (datafusion.catalog.Table attribute) @@ -763,7 +803,11 @@

    _

  • _max_rows (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
  • _normalize_input_types() (datafusion.user_defined.WindowUDF static method) + +
  • _null_treatment (datafusion.expr.Window attribute)
  • _order_by (datafusion.expr.Window attribute) @@ -802,14 +846,30 @@

    _

  • _type_formatters (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
    • -
  • _udaf (datafusion.user_defined.AggregateUDF attribute) +
  • _udaf (datafusion.AggregateUDF attribute) + +
    • +
  • _udf (datafusion.ScalarUDF attribute) + +
    • +
  • _udtf (datafusion.TableFunction attribute) + +
  • _udwf (datafusion.user_defined.WindowUDF attribute) + +
  • _validate_bool() (in module datafusion.dataframe_formatter)
  • _validate_formatter_parameters() (in module datafusion.dataframe_formatter) @@ -832,8 +892,12 @@

    A

  • (in module datafusion.functions)
    • -
  • Accumulator (class in datafusion.user_defined) +
  • Accumulator (class in datafusion) + +
  • acos() (datafusion.Expr method)
    • + - + - @@ -748,30 +732,14 @@

    _

  • _convert_table_partition_cols() (datafusion.context.SessionContext static method)
    • -
  • _create_table_udf() (datafusion.TableFunction static method) - -
    • -
  • _create_table_udf_decorator() (datafusion.TableFunction static method) - -
  • _create_window_udf() (datafusion.user_defined.WindowUDF static method) - -
  • _create_window_udf_decorator() (datafusion.user_defined.WindowUDF static method) - -
  • _custom_cell_builder (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
  • _custom_header_builder (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute) @@ -785,11 +753,7 @@

    _

  • _get_default_css() (datafusion.dataframe_formatter.DataFrameHtmlFormatter method)
  • _get_default_name() (datafusion.user_defined.WindowUDF static method) - -
  • _get_javascript() (datafusion.dataframe_formatter.DataFrameHtmlFormatter method)
  • _inner (datafusion.catalog.Table attribute) @@ -803,11 +767,7 @@

    _

  • _max_rows (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
  • _normalize_input_types() (datafusion.user_defined.WindowUDF static method) - -
  • _null_treatment (datafusion.expr.Window attribute)
  • _order_by (datafusion.expr.Window attribute) @@ -846,30 +806,14 @@

    _

  • _type_formatters (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
    • -
  • _udaf (datafusion.AggregateUDF attribute) - -
    • -
  • _udf (datafusion.ScalarUDF attribute) - -
    • -
  • _udtf (datafusion.TableFunction attribute) - -
  • _udwf (datafusion.user_defined.WindowUDF attribute) - -
  • _validate_bool() (in module datafusion.dataframe_formatter)
  • _validate_formatter_parameters() (in module datafusion.dataframe_formatter) @@ -892,12 +836,8 @@

    A

  • (in module datafusion.functions)
    • -
  • Accumulator (class in datafusion) - -
  • acos() (datafusion.Expr method) -
    • + - + @@ -732,14 +748,30 @@

    _

  • _convert_table_partition_cols() (datafusion.context.SessionContext static method)
    • -
  • _create_table_udf() (datafusion.user_defined.TableFunction static method) +
  • _create_table_udf() (datafusion.TableFunction static method) + +
    • +
  • _create_table_udf_decorator() (datafusion.TableFunction static method) + +
  • _create_window_udf() (datafusion.user_defined.WindowUDF static method) + +
  • _create_window_udf_decorator() (datafusion.user_defined.WindowUDF static method) + +
  • _custom_cell_builder (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
  • _custom_header_builder (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute) @@ -753,7 +785,11 @@

    _

  • _get_default_css() (datafusion.dataframe_formatter.DataFrameHtmlFormatter method)
  • _get_default_name() (datafusion.user_defined.WindowUDF static method) + +
  • _get_javascript() (datafusion.dataframe_formatter.DataFrameHtmlFormatter method)
  • _inner (datafusion.catalog.Table attribute) @@ -767,7 +803,11 @@

    _

  • _max_rows (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
  • _normalize_input_types() (datafusion.user_defined.WindowUDF static method) + +
  • _null_treatment (datafusion.expr.Window attribute)
  • _order_by (datafusion.expr.Window attribute) @@ -806,14 +846,30 @@

    _

  • _type_formatters (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
    • -
  • _udaf (datafusion.user_defined.AggregateUDF attribute) +
  • _udaf (datafusion.AggregateUDF attribute) + +
    • +
  • _udf (datafusion.ScalarUDF attribute) + +
    • +
  • _udtf (datafusion.TableFunction attribute) + +
  • _udwf (datafusion.user_defined.WindowUDF attribute) + +
  • _validate_bool() (in module datafusion.dataframe_formatter)
  • _validate_formatter_parameters() (in module datafusion.dataframe_formatter) @@ -836,8 +892,12 @@

    A

  • (in module datafusion.functions)
    • -
  • Accumulator (class in datafusion.user_defined) +
  • Accumulator (class in datafusion) + +
  • acos() (datafusion.Expr method)
    • + -
      @@ -2874,7 +2904,7 @@

      R

  • replace() (in module datafusion.functions)
    • -
  • repr_rows (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute) +
  • repr_rows (datafusion.dataframe_formatter.DataFrameHtmlFormatter property)
  • reset_formatter() (in module datafusion.dataframe_formatter)
    • @@ -2936,12 +2966,8 @@

    S

    		 +
  • schema_infer_max_records (datafusion.CsvReadOptions attribute) + +
  • schema_name() (datafusion.Expr method) @@ -3058,6 +3094,8 @@

    S

  • show_truncation_message (datafusion.dataframe_formatter.DataFrameHtmlFormatter attribute)
    • +     		-
  • TableFunction (class in datafusion) +
  • table_partition_cols (datafusion.CsvReadOptions attribute)
    • +
  • TableFunction (class in datafusion.user_defined) +
  • TableProviderExportable (class in datafusion.context)
  • TableScan (in module datafusion.expr) @@ -3250,6 +3286,12 @@

    T

  • (datafusion.expr.Expr method)
  • (in module datafusion.functions) +
    • + +
  • terminator (datafusion.CsvReadOptions attribute) + +
  • to_arrow_table() (datafusion.dataframe.DataFrame method) @@ -3260,6 +3302,12 @@

    T

  • (datafusion.expr.Expr method)
  • (in module datafusion.functions) +
    • + +
  • to_inner() (datafusion.CsvReadOptions method) + +
  • to_pandas() (datafusion.dataframe.DataFrame method) @@ -3336,6 +3384,12 @@

    T

  • trunc() (in module datafusion.functions)
    • +
  • truncated_rows (datafusion.CsvReadOptions attribute) + +
  • TryCast (in module datafusion.expr)
  • types() (datafusion.Expr method) @@ -3350,56 +3404,22 @@

    T

    U

    - + - + + + + - + + + + + + + @@ -898,6 +1016,54 @@

    Module Contents +
    +class datafusion.catalog.CatalogList(catalog_list: datafusion._internal.catalog.RawCatalogList)
    +

    DataFusion data catalog list.

    +

    This constructor is not typically called by the end user.

    +
    +
    +__repr__() → str
    +

    Print a string representation of the catalog list.

    +
    + +
    +
    +catalog(name: str = 'datafusion') → Catalog
    +

    Returns the catalog with the given name from this catalog.

    +
    + +
    +
    +catalog_names() → set[str]
    +

    Returns the list of schemas in this catalog.

    +
    + +
    +
    +static memory_catalog(ctx: datafusion.SessionContext | None = None) → CatalogList
    +

    Create an in-memory catalog provider list.

    +
    + +
    +
    +names() → set[str]
    +

    This is an alias for catalog_names.

    +
    + +
    +
    +register_catalog(name: str, catalog: Catalog | CatalogProvider | CatalogProviderExportable) → Catalog | None
    +

    Register a catalog with this catalog list.

    +
    + +
    +
    +catalog_list
    +
    + +
    +
    class datafusion.catalog.CatalogProvider
    @@ -941,6 +1107,33 @@

    Module Contents +
    +class datafusion.catalog.CatalogProviderList
    +

    Bases: abc.ABC

    +

    Abstract class for defining a Python based Catalog Provider List.

    +
    +
    +abstract catalog(name: str) → CatalogProviderExportable | CatalogProvider | Catalog | None
    +

    Retrieve a specific catalog from this catalog list.

    +
    + +
    +
    +abstract catalog_names() → set[str]
    +

    Set of the names of all catalogs in this catalog list.

    +
    + +
    +
    +register_catalog(name: str, catalog: CatalogProviderExportable | CatalogProvider | Catalog) → None
    +

    Add a catalog to this catalog list.

    +

    This method is optional. If your catalog provides a fixed list of catalogs, you +do not need to implement this method.

    +
    + +

    +
    class datafusion.catalog.Schema(schema: datafusion._internal.catalog.RawSchema)
    diff --git a/autoapi/datafusion/context/index.html b/autoapi/datafusion/context/index.html index 677e2937f..fba3608b3 100644 --- a/autoapi/datafusion/context/index.html +++ b/autoapi/datafusion/context/index.html @@ -467,26 +467,6 @@ -
  • - - - - CatalogProviderExportable - - - - -
  • @@ -1015,6 +995,15 @@
    • +
  • + + + + SessionContext.register_catalog_provider_list() + + + +
  • @@ -1262,25 +1251,22 @@

    Classes

    • - - - - + - + - + - + - + - + @@ -1314,19 +1300,6 @@

    Module Contents -
    -class datafusion.context.CatalogProviderExportable
    -

    Bases: Protocol

    -

    Type hint for object that has __datafusion_catalog_provider__ PyCapsule.

    -

    https://docs.rs/datafusion/latest/datafusion/catalog/trait.CatalogProvider.html

    -
    -
    -__datafusion_catalog_provider__(session: Any) → object
    -
    - -
    -
    class datafusion.context.RuntimeConfig
    @@ -2115,10 +2088,16 @@

    Module Contents
    -register_catalog_provider(name: str, provider: CatalogProviderExportable | datafusion.catalog.CatalogProvider | datafusion.catalog.Catalog) → None
    +register_catalog_provider(name: str, provider: datafusion.catalog.CatalogProviderExportable | datafusion.catalog.CatalogProvider | datafusion.catalog.Catalog) → None

    Register a catalog provider.

    +
    +
    +register_catalog_provider_list(provider: datafusion.catalog.CatalogProviderListExportable | datafusion.catalog.CatalogProviderList | datafusion.catalog.CatalogList) → None
    +

    Register a catalog provider list.

    +
    +
    register_csv(name: str, path: str | pathlib.Path | list[str | pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = DEFAULT_MAX_INFER_SCHEMA, file_extension: str = '.csv', file_compression_type: str | None = None, options: datafusion.options.CsvReadOptions | None = None) → None
    diff --git a/autoapi/datafusion/dataframe/index.html b/autoapi/datafusion/dataframe/index.html index c5697fafd..75b0c0c40 100644 --- a/autoapi/datafusion/dataframe/index.html +++ b/autoapi/datafusion/dataframe/index.html @@ -1449,7 +1449,7 @@

    Classes

    Module Contents

    -class datafusion.dataframe.Compression(*args, **kwds)
    +class datafusion.dataframe.Compression

    Bases: enum.Enum

    Enum representing the available compression types for Parquet files.

    @@ -2504,7 +2504,7 @@

    Module Contents
    -class datafusion.dataframe.InsertOp(*args, **kwds)
    +class datafusion.dataframe.InsertOp

    Bases: enum.Enum

    Insert operation mode.

    These modes are used by the table writing feature to define how record diff --git a/autoapi/datafusion/functions/index.html b/autoapi/datafusion/functions/index.html index bc1a0b1f8..3ca535bb4 100644 --- a/autoapi/datafusion/functions/index.html +++ b/autoapi/datafusion/functions/index.html @@ -2056,6 +2056,15 @@ +

  • + + + + regexp_instr() + + + +
  • @@ -3110,7 +3119,7 @@

    Functions

    • - + @@ -3169,184 +3178,187 @@

    Functions

     - + + + + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + @@ -3515,7 +3527,7 @@

    Returns:

    For example:

    -
    df.select(array_agg(col("a"), order_by="b"))
+
    df.aggregate([], array_agg(col("a"), order_by="b"))
 
    
 
    
 
@@ -4301,7 +4313,7 @@ 
    Returns:
 
 
    For example:
    
-
    df.select(first_value(col("a"), order_by="ts"))
+
    df.aggregate([], first_value(col("a"), order_by="ts"))
 
    
 
    
 
@@ -4413,7 +4425,7 @@ 
    Returns:
 
 
    For example:
    
-
    df.select(last_value(col("a"), order_by="ts"))
+
    df.aggregate([], last_value(col("a"), order_by="ts"))
 
    
 
    
 
@@ -4810,7 +4822,7 @@ 
    Returns:
 
    
 datafusion.functions.min(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) → datafusion.expr.Expr
    
-
    Returns the minimum value of the argument.
    
+
    Aggregate function that returns the minimum value of the argument.
    
 
    If using the builder functions described in ref:_aggregation this function ignores
 the options order_by, null_treatment, and distinct.
    
 
    
@@ -4862,7 +4874,7 @@ 
    Returns:
 
    
 
    For example:
    
-
    df.select(nth_value(col("a"), 2, order_by="ts"))
+
    df.aggregate([], nth_value(col("a"), 2, order_by="ts"))
 
    
 
    
 
    
@@ -5044,12 +5056,22 @@ 
    Returns:
 
    
-datafusion.functions.regexp_count(string: datafusion.expr.Expr, pattern: datafusion.expr.Expr, start: datafusion.expr.Expr, flags: datafusion.expr.Expr | None = None) → datafusion.expr.Expr
    
+datafusion.functions.regexp_count(string: datafusion.expr.Expr, pattern: datafusion.expr.Expr, start: datafusion.expr.Expr | None = None, flags: datafusion.expr.Expr | None = None) → datafusion.expr.Expr
 
    Returns the number of matches in a string.
    
 
    Optional start position (the first position is 1) to search for the regular
 expression.
    
 
    
 
+
    
+
    
+datafusion.functions.regexp_instr(values: datafusion.expr.Expr, regex: datafusion.expr.Expr, start: datafusion.expr.Expr | None = None, n: datafusion.expr.Expr | None = None, flags: datafusion.expr.Expr | None = None, sub_expr: datafusion.expr.Expr | None = None) → datafusion.expr.Expr
    
+
    Returns the position of a regular expression match in a string.
    
+
    Searches values for the n-th occurrence of regex, starting at position
+start (the first position is 1). Returns the starting or ending position based
+on end_position. Use flags to control regex behavior and sub_expr to
+return the position of a specific capture group instead of the entire match.
    
+
    
+
 
    
 
    
 datafusion.functions.regexp_like(string: datafusion.expr.Expr, regex: datafusion.expr.Expr, flags: datafusion.expr.Expr | None = None) → datafusion.expr.Expr
    
@@ -5447,7 +5469,7 @@ 
    Returns:
 
    
 
    For example:
    
-
    df.select(string_agg(col("a"), ",", order_by="b"))
+
    df.aggregate([], string_agg(col("a"), ",", order_by="b"))
 
    
 
    
 
diff --git a/autoapi/datafusion/index.html b/autoapi/datafusion/index.html
index 21512f265..49b2d73fe 100644
--- a/autoapi/datafusion/index.html
+++ b/autoapi/datafusion/index.html
@@ -442,6 +442,109 @@
    Package Contents
   
   
    
+   
  • 
+    
+     
+      
+       TableFunction
+      
+     
+    
+    
+   
    • 
    
  • 
     
      
@@ -2931,6 +3164,98 @@
      
    • 
     
    
+   
  • 
+    
+     
+      
+       WindowUDF
+      
+     
+    
+    
+   
    • 
    
  • 
     
      
@@ -3021,6 +3346,42 @@
      
     
    
    • 
+   
  • 
+    
+     
+      
+       udaf
+      
+     
+    
+   
    • 
+   
  • 
+    
+     
+      
+       udf
+      
+     
+    
+   
    • 
+   
  • 
+    
+     
+      
+       udtf
+      
+     
+    
+   
    • 
+   
  • 
+    
+     
+      
+       udwf
+      
+     
+    
+   
    • 
   
  
 
@@ -3085,6 +3446,18 @@ 
    Attributes

     + + + + + + + + + + + +
  • with_pretty() (datafusion.unparser.Unparser method)
    • +
  • with_quote() (datafusion.CsvReadOptions method) + +
  • with_repartition_aggregations() (datafusion.context.SessionConfig method)

    @@ -353,6 +358,11 @@ datafusion.object_store

    • +
  • + + datafusion.options + +
  • datafusion.plan diff --git a/objects.inv b/objects.inv index a9e3c5ffe2ce5adf3ffb34eccbc0c0e9e742b273..0f2e7e824db867e817d3d0061b4572e34918ea2b 100644 GIT binary patch delta 9111 zcmV;IBWT?3M9@c&hksjl+cvhx-}NcH)|^+X({wuPta(cur{hkVcM3ZHunBZ6C?jME7s+?Z^^@>zlkdpn7 zwLkyBct*GLwJ!3%_+Z!nb9Fu22bkZOKXb9NoHQp&UHv$KIe-5CJV_)iWsPbVxV ziA|>3JW!H-EVcQUnqKdFn0YFSf^r>KY5T~G=B!|*ARwVsrKF^g#3jpVVv=7bIo_iRJM{x&FllyVscnMl?CHO3(yLug~=7} zD=|cOJJ+(}=7UGGM2aWS40vLCopickkmx#SuOo)T?ti;tIOfUD7+9j$9Rsub9Wore z-zCFwk9W#|{9d;V$89@iIArul?}8&VQ;tGhMShlaxcnF=NWaa0iS_Z1|YLK%cslqDV?9w16UZyPL{K)bL9x^)3!< zhHcRiEoDT7E~Tl*B+KHev8Qkd3jGEESy2#(DRWvtkTd{<@r|i(0H7Qqb8?876au2g z6jcsD;SjkZBmhLV%`xI5P?I@XOoLdMUbu*4q=XC3Qj)uk#Aukz7&qNwbhnWb72A^1g^Wf}md7I2 zM8cG|C6UzbL<8YuEJ5T|!9gG(l`ncs05Bv-MQokR=t@!=o0MkF2OwX8h7=Hk3A!!g z2{L{JyEN@kNJe5ihb7Bxzso@|RSpoHsDEue56Mm5Mt>uhxe(DYu`84nXIssp8v)}? zrzE!aF_mzkA&Sb9ASm&bkE!oeMlP++LB43Y>8K!PQZ)yp*K;hm)NzpHnMNMnb=8!_ zZMqo_ahqh3%-Fh^i`9>Rjc2@yMm$A#qdCCXzQ}%#B)H9XEh*6jjh@;HGk67R41dlZ zB3ZG8MqfmETQK>(clZ`qW!2I?7{q2XhQELh<>*MdY4}Uz|eY%CgJ>1^Ee|-}NdoNaY zbvVkRtHS`;>(BEMBs-?(M*ShLY%u=yevra=5!UqZRH^v$B0&#=m}ERhv>wt-jZoE(6M zXDqdU5V^xE1j^9pkoJM53T~gv5}oTs^~E6F$`B-(!?A8Ma*Wq*ls(6O7DDc zzY7w{$F||e=AtLrymaN907lQ9lc8G;4aJBkd^{}?k|!5&o$iAfp0I-6^39uy<@JH% zX|?B&WQKEm$yR3YXn#tE`$cHDc-H6LnfjU(gquNwwEt*3?}_;vpb}%r7Q(MbzX-`# z5@zw%AgL502j^ScxNMiyzJgFBG%d^K1h{u1wkDV{?5%YRB z1k;{6T$ge`1FCCFQPWGOOMe0F@A_m#HBeH0KK6%( zU|2t`PBOYARjwOvVeVLL?4tD%wF}8Gz7(<`&Wr>BU;5#7QkqFYJu3xcOS-p!AuH28 zuSnY)p@_JixnLZ=YCTg?DM3ug7r_we)#EmK8pw8w45_)L0F}ePB-GiQS^jZfScKBKc40QZ@1bdzr zT#Lq&!yUtpXNNk9oj@MzICi|mI7hPM`9U66$79j+1%H>D;AG3a6dN|YW;B_5feP75 zT}Rq$YIB zhL5yQWTRv@c+cC%qF3-%NIY?CA`@UQJXzvGDY*b0r=A{Y0N2-$>HbI>!e?Xra=>VI z=<>i=@PC-)g0bwd<%6-*(B*^xuHT)R;sbW?AY z3L;u>yj4WB-c`>5Q|oh?XeOCBm&RMktN2%9uz+?axPB zZA?XvwBm@8iMHy9Qhy=Y@m3#EawDxkqO_)3g@B2UvJ!z+4YC>mlMJ#V0aFXIDgjdq zw0|;*(i?4cGDWSKcmscG+&_EMtlXbQ-d{+Sq#~m!OB(=T%?;U zV4k}RAx2)s6)!mD2ByiXp=|#*(H_Cv4z}iLwI~wy?=s^Z~;gl=au&cVn*0RA!~@7NNkOrJyndY zk%w%^P1RWCVqrS1x?e$&Fui4#kj=1@*f@n$ZEyv?D8X?R>M0to2yXjszaPj2UaK7L zD_lSkwVKr;p?j^-LdbQxR>_?+<<+ICo>+XLsZNv@@&ao3jkXr*yJ5iByHIJ>Gk=|n zHQ*{E%S)(SL_}Xi<>>+{8%FVlx2nGXn`L+s-*Qa0ceLK|R)ivi+vLX>m`&Ai*>qwV z3{KP;86jF#oZug>wskvBh*hxu(#aVsp*G;KolqNee$#iScP68b;zPLeHxC~_y}t`s zBAG7n%YX0gQ3c-r_ixzzU8(y`CPlUANS5A3+fUBW>`eD+S+pJzWAjv%+>=Ci5NM zhDMWU_M|D6KuXLU4G%s%fSSw}c}`Pod=hqdV5~~JeKu_KH(jdYXt~vN*?*=}a*YB{ zN2TV|hE`$yTp0BG*?|Y%)HRteMTy0x+mx2tTD##XxV@>4!%lpaOSC($Xs1CT`>oSe z44t9jgD-B35D2)@aVmXH30nC&+ewA^B{BjcXwhk^fVIrRWG4a*-?~Lcfse40n5tpd z$qM$JX2~VgOn0YD-}lWfIDg@Nq&t>z7m!F6yJSs7W|6POr*Ap4gnfe_=D$pVsaWo_`W z1S*c$Svz=wJ^QIRrwYBV^M^oC*91BeW-e_lQL_t3;pLd~zaL;U3mu~e6jBV;8lMB`q~R=0%T>&z3($jC=^6LmQG;^yLc6TFC!d;?epeQ|e_S@`Y@O zwG1s^utnF?8-Mkp6;jTg9~)H+mU62!@VO-IZ9%i`CUS4r5O8 zKu5v07FQ_aCtw&+SyQ%J>z9s2?J{<;(^S25T$--zyjyzIC_J(3g=+@mFW#lM=g#{R z?U!h??zqzn*9&EbKgY+bFOnyn_&gu4zD$hP)+ErcZ+}_CtAZ*;R`ez7u+qB&&lxWj zlgipZuZdj+c9FVJ)Ar-!N2?fkTM>@vyq!I`)L)>Eo{B`>SS}QewgUX-UF@T0{-NN! 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    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -486,6 +496,11 @@

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    		•     datafusion.object_store
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    • @@ -358,6 +363,11 @@ datafusion.object_store +

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false], [11, "module-datafusion.io", false], [12, "module-datafusion.object_store", false], [13, "module-datafusion.options", false], [14, "module-datafusion.plan", false], [15, "module-datafusion.record_batch", false], [16, "module-datafusion.substrait", false], [17, "module-datafusion.unparser", false], [18, "module-datafusion.user_defined", false]], "mysql() (datafusion.unparser.dialect static method)": [[17, "datafusion.unparser.Dialect.mysql", false]], "named_struct() (in module datafusion.functions)": [[5, "datafusion.functions.named_struct", false]], "names() (datafusion.catalog method)": [[7, "datafusion.Catalog.names", false]], "names() (datafusion.catalog.catalog method)": [[0, "datafusion.catalog.Catalog.names", false]], "names() (datafusion.catalog.schema method)": [[0, "datafusion.catalog.Schema.names", false]], "nanvl() (in module datafusion.functions)": [[5, "datafusion.functions.nanvl", false]], "negative (in module datafusion.expr)": [[4, "datafusion.expr.Negative", false]], "newlines_in_values (datafusion.csvreadoptions attribute)": [[7, "datafusion.CsvReadOptions.newlines_in_values", false]], "newlines_in_values (datafusion.options.csvreadoptions attribute)": [[13, "datafusion.options.CsvReadOptions.newlines_in_values", false]], "next() (datafusion.record_batch.recordbatchstream method)": [[15, "datafusion.record_batch.RecordBatchStream.next", false]], "next() (datafusion.recordbatchstream method)": [[7, "datafusion.RecordBatchStream.next", false]], "not (in module datafusion.expr)": [[4, "datafusion.expr.Not", false]], "now() (in module datafusion.functions)": [[5, "datafusion.functions.now", false]], "nth_value() (in module datafusion.functions)": [[5, "datafusion.functions.nth_value", false]], "ntile() (in module datafusion.functions)": [[5, "datafusion.functions.ntile", false]], "null_regex (datafusion.csvreadoptions attribute)": [[7, "datafusion.CsvReadOptions.null_regex", false]], "null_regex (datafusion.options.csvreadoptions attribute)": 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false]], "regexp_replace() (in module datafusion.functions)": [[5, "datafusion.functions.regexp_replace", false]], "register_avro() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_avro", false]], "register_catalog_provider() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_catalog_provider", false]], "register_csv() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_csv", false]], "register_dataset() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_dataset", false]], "register_formatter() (datafusion.dataframe_formatter.dataframehtmlformatter method)": [[3, "datafusion.dataframe_formatter.DataFrameHtmlFormatter.register_formatter", false]], "register_json() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_json", false]], "register_listing_table() 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false]], "register_table() (datafusion.catalog.schemaprovider method)": [[0, "datafusion.catalog.SchemaProvider.register_table", false]], "register_table() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_table", false]], "register_table_provider() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_table_provider", false]], "register_udaf() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_udaf", false]], "register_udf() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_udf", false]], "register_udtf() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_udtf", false]], "register_udwf() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_udwf", false]], "register_view() (datafusion.context.sessioncontext method)": [[1, 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[31, 35], "user_defin": 18, "valu": 27, "view": 32, "window": [31, 33], "work": 20, "zero": 36}}) \ No newline at end of file diff --git a/user-guide/basics.html b/user-guide/basics.html index c0247bdb3..98bef4d88 100644 --- a/user-guide/basics.html +++ b/user-guide/basics.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/common-operations/aggregations.html b/user-guide/common-operations/aggregations.html index 7c0269ad8..fe12b67a1 100644 --- a/user-guide/common-operations/aggregations.html +++ b/user-guide/common-operations/aggregations.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -610,15 +620,15 @@

    Distinct +----------+--------------------------------------------------+ | Type 1 | Type 2 List | +----------+--------------------------------------------------+ -| Bug | [Grass, Poison, Flying, ] | -| Poison | [Flying, , Ground] | -| Electric | [Steel, , Flying] | +| Bug | [Grass, , Flying, Poison] | +| Poison | [, Ground, Flying] | +| Electric | [Steel, Flying, ] | | Fairy | [] | | Normal | [Flying, , Fairy] | | Ice | [Flying, Psychic] | -| Grass | [Psychic, Poison, ] | -| Fire | [Flying, Dragon, ] | -| Water | [, Dark, Poison, Psychic, Fighting, Flying, Ice] | +| Grass | [Poison, , Psychic] | +| Fire | [Flying, , Dragon] | +| Water | [Psychic, Fighting, Poison, , Ice, Flying, Dark] | | Ground | [, Rock] | +----------+--------------------------------------------------+ Data truncated. @@ -635,14 +645,14 @@

    Distinct | Type 1 | Type 2 List | +----------+------------------------------------------------+ | Bug | [Poison, Grass, Flying] | -| Poison | [Ground, Flying] | -| Electric | [Steel, Flying] | -| Normal | [Fairy, Flying] | -| Ice | [Psychic, Flying] | +| Poison | [Flying, Ground] | +| Electric | [Flying, Steel] | +| Normal | [Flying, Fairy] | +| Ice | [Flying, Psychic] | | Grass | [Psychic, Poison] | -| Fire | [Flying, Dragon] | -| Water | [Poison, Flying, Ice, Fighting, Dark, Psychic] | -| Rock | [Ground, Water, Flying] | +| Fire | [Dragon, Flying] | +| Water | [Flying, Ice, Dark, Poison, Psychic, Fighting] | +| Rock | [Flying, Water, Ground] | | Ghost | [Poison] | +----------+------------------------------------------------+ Data truncated. @@ -653,15 +663,15 @@

    Distinct +----------+------------------------------------------------+ | Type 1 | Type 2 List | +----------+------------------------------------------------+ -| Bug | [Grass, Poison, Flying] | -| Poison | [Flying, Ground] | -| Electric | [Flying, Steel] | +| Bug | [Flying, Poison, Grass] | +| Poison | [Ground, Flying] | +| Electric | [Steel, Flying] | | Fairy | | | Normal | [Fairy, Flying] | | Ice | [Psychic, Flying] | -| Grass | [Poison, Psychic] | -| Fire | [Flying, Dragon] | -| Water | [Psychic, Poison, Ice, Flying, Fighting, Dark] | +| Grass | [Psychic, Poison] | +| Fire | [Dragon, Flying] | +| Water | [Ice, Dark, Flying, Psychic, Fighting, Poison] | | Ground | [Rock] | +----------+------------------------------------------------+ Data truncated. diff --git a/user-guide/common-operations/basic-info.html b/user-guide/common-operations/basic-info.html index 24cee81d8..cfcb45959 100644 --- a/user-guide/common-operations/basic-info.html +++ b/user-guide/common-operations/basic-info.html @@ -243,6 +243,11 @@ SQL

    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -446,11 +456,11 @@

    Basic Operations+-----+---------+--------+--------+ | nrs | names | random | groups | +-----+---------+--------+--------+ -| 1 | python | 730 | A | -| 2 | ruby | 479 | A | -| 3 | java | 280 | B | -| 4 | haskell | 944 | C | -| 5 | go | 44 | B | +| 1 | python | 465 | A | +| 2 | ruby | 390 | A | +| 3 | java | 725 | B | +| 4 | haskell | 8 | C | +| 5 | go | 9 | B | +-----+---------+--------+--------+ @@ -461,8 +471,8 @@

    Basic Operations+-----+--------+--------+--------+ | nrs | names | random | groups | +-----+--------+--------+--------+ -| 1 | python | 730 | A | -| 2 | ruby | 479 | A | +| 1 | python | 465 | A | +| 2 | ruby | 390 | A | +-----+--------+--------+--------+ @@ -480,28 +490,28 @@

    Basic Operations
    In [8]: df.to_pandas()
 Out[8]: 
    nrs    names  random groups
-0    1   python     730      A
-1    2     ruby     479      A
-2    3     java     280      B
-3    4  haskell     944      C
-4    5       go      44      B
+0    1   python     465      A
+1    2     ruby     390      A
+2    3     java     725      B
+3    4  haskell       8      C
+4    5       go       9      B

    describe() shows a quick statistic summary of your data:

    In [9]: df.describe()
 Out[9]: 
 DataFrame()
-+------------+--------------------+-------+------------------+--------+
-| describe   | nrs                | names | random           | groups |
-+------------+--------------------+-------+------------------+--------+
-| count      | 5.0                | 5     | 5.0              | 5      |
-| null_count | 0.0                | 0     | 0.0              | 0      |
-| mean       | 3.0                | null  | 495.4            | null   |
-| std        | 1.5811388300841898 | null  | 355.916844220669 | null   |
-| min        | 1.0                | go    | 44.0             | A      |
-| max        | 5.0                | ruby  | 944.0            | C      |
-| median     | 3.0                | null  | 479.0            | null   |
-+------------+--------------------+-------+------------------+--------+
++------------+--------------------+-------+--------------------+--------+
+| describe   | nrs                | names | random             | groups |
++------------+--------------------+-------+--------------------+--------+
+| count      | 5.0                | 5     | 5.0                | 5      |
+| null_count | 0.0                | 0     | 0.0                | 0      |
+| mean       | 3.0                | null  | 319.4              | null   |
+| std        | 1.5811388300841898 | null  | 309.84399300293046 | null   |
+| min        | 1.0                | go    | 8.0                | A      |
+| max        | 5.0                | ruby  | 725.0              | C      |
+| median     | 3.0                | null  | 390.0              | null   |
++------------+--------------------+-------+--------------------+--------+
    diff --git a/user-guide/common-operations/expressions.html b/user-guide/common-operations/expressions.html index f2358ca39..cbfda5390 100644 --- a/user-guide/common-operations/expressions.html +++ b/user-guide/common-operations/expressions.html @@ -243,6 +243,11 @@ SQL

    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/common-operations/functions.html b/user-guide/common-operations/functions.html index 867876c1d..d54ebd6f4 100644 --- a/user-guide/common-operations/functions.html +++ b/user-guide/common-operations/functions.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -507,16 +517,16 @@

    Mathematical+------------------------------------------------------------------+ | power(pokemon.Attack,Int64(2)) - power(pokemon.Defense,Int64(2)) | +------------------------------------------------------------------+ -| 0 | -| -125 | -| -165 | -| -5129 | -| 855 | -| 732 | -| 972 | -| 4579 | -| 4732 | -| -1921 | +| 0.0 | +| -125.0 | +| -165.0 | +| -5129.0 | +| 855.0 | +| 732.0 | +| 972.0 | +| 4579.0 | +| 4732.0 | +| -1921.0 | +------------------------------------------------------------------+ @@ -556,16 +566,16 @@

    Temporal +-------------------------------+ | now() | +-------------------------------+ -| 2026-01-05T16:06:57.764994749 | -| 2026-01-05T16:06:57.764994749 | -| 2026-01-05T16:06:57.764994749 | -| 2026-01-05T16:06:57.764994749 | -| 2026-01-05T16:06:57.764994749 | -| 2026-01-05T16:06:57.764994749 | -| 2026-01-05T16:06:57.764994749 | -| 2026-01-05T16:06:57.764994749 | -| 2026-01-05T16:06:57.764994749 | -| 2026-01-05T16:06:57.764994749 | +| 2026-02-09T15:58:03.744596391 | +| 2026-02-09T15:58:03.744596391 | +| 2026-02-09T15:58:03.744596391 | +| 2026-02-09T15:58:03.744596391 | +| 2026-02-09T15:58:03.744596391 | +| 2026-02-09T15:58:03.744596391 | +| 2026-02-09T15:58:03.744596391 | +| 2026-02-09T15:58:03.744596391 | +| 2026-02-09T15:58:03.744596391 | +| 2026-02-09T15:58:03.744596391 | +-------------------------------+ Data truncated. diff --git a/user-guide/common-operations/index.html b/user-guide/common-operations/index.html index 5bd5dc903..789adaf29 100644 --- a/user-guide/common-operations/index.html +++ b/user-guide/common-operations/index.html @@ -243,6 +243,11 @@ SQL

    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/common-operations/joins.html b/user-guide/common-operations/joins.html index 20fb374e6..de8c62fd0 100644 --- a/user-guide/common-operations/joins.html +++ b/user-guide/common-operations/joins.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/common-operations/select-and-filter.html b/user-guide/common-operations/select-and-filter.html index 180cd0c9f..90997c72f 100644 --- a/user-guide/common-operations/select-and-filter.html +++ b/user-guide/common-operations/select-and-filter.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/common-operations/udf-and-udfa.html b/user-guide/common-operations/udf-and-udfa.html index 45ac30e2d..07eb1060c 100644 --- a/user-guide/common-operations/udf-and-udfa.html +++ b/user-guide/common-operations/udf-and-udfa.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -546,6 +556,15 @@

    Scalar Functions+---+---------+ +

    In this example we passed the PyArrow DataType when we defined the function +by calling udf(). If you need additional control, such as specifying +metadata or nullability of the input or output, you can instead specify a +PyArrow Field.

    +

    If you need to write a custom function but do not want to incur the performance +cost of converting to Python objects and back, a more advanced approach is to +write Rust based UDFs and to expose them to Python. There is an example in the +DataFusion blog +describing how to do this.

    Aggregate Functions

    diff --git a/user-guide/common-operations/views.html b/user-guide/common-operations/views.html index 118a2ea93..31155df55 100644 --- a/user-guide/common-operations/views.html +++ b/user-guide/common-operations/views.html @@ -243,6 +243,11 @@ SQL

    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/common-operations/windows.html b/user-guide/common-operations/windows.html index ac2682ab1..2202f7eb1 100644 --- a/user-guide/common-operations/windows.html +++ b/user-guide/common-operations/windows.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/configuration.html b/user-guide/configuration.html index c26e0b53f..642d665b5 100644 --- a/user-guide/configuration.html +++ b/user-guide/configuration.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/data-sources.html b/user-guide/data-sources.html index 40625ae25..a2b1c80e5 100644 --- a/user-guide/data-sources.html +++ b/user-guide/data-sources.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/dataframe/index.html b/user-guide/dataframe/index.html index 69a344d86..80c598120 100644 --- a/user-guide/dataframe/index.html +++ b/user-guide/dataframe/index.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/dataframe/rendering.html b/user-guide/dataframe/rendering.html index 4779e0f58..91bac2c59 100644 --- a/user-guide/dataframe/rendering.html +++ b/user-guide/dataframe/rendering.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -517,8 +527,8 @@

    Configuring the HTML Formattermax_width=1000, # Maximum width in pixels max_height=300, # Maximum height in pixels max_memory_bytes=2097152, # Maximum memory for rendering (2MB) - min_rows_display=20, # Minimum number of rows to display - repr_rows=10, # Number of rows to display in __repr__ + min_rows=10, # Minimum number of rows to display + max_rows=10, # Maximum rows to display in __repr__ enable_cell_expansion=True,# Allow expanding truncated cells custom_css=None, # Additional custom CSS show_truncation_message=True, # Show message when data is truncated @@ -635,8 +645,8 @@

    Memory and Display Controls
    configure_formatter(
     max_memory_bytes=4 * 1024 * 1024,  # 4MB maximum memory for display
-    min_rows_display=50,               # Always show at least 50 rows
-    repr_rows=20                       # Show 20 rows in __repr__ output
+    min_rows=20,                       # Always show at least 20 rows
+    max_rows=50                        # Show up to 50 rows in output
 )
    diff --git a/user-guide/introduction.html b/user-guide/introduction.html index 9e1434734..ddbae16d0 100644 --- a/user-guide/introduction.html +++ b/user-guide/introduction.html @@ -243,6 +243,11 @@ SQL

    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/io/arrow.html b/user-guide/io/arrow.html index 046a0ade6..748fdbb54 100644 --- a/user-guide/io/arrow.html +++ b/user-guide/io/arrow.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/io/avro.html b/user-guide/io/avro.html index 68cd7cc12..bf41d6c8a 100644 --- a/user-guide/io/avro.html +++ b/user-guide/io/avro.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/io/csv.html b/user-guide/io/csv.html index 64b2ccfac..5b1933d99 100644 --- a/user-guide/io/csv.html +++ b/user-guide/io/csv.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -437,6 +447,25 @@ df = ctx.table("file") +

    If you require additional control over how to read the CSV file, you can use +CsvReadOptions to set a variety of options.

    +
    from datafusion import CsvReadOptions
+options = (
+    CsvReadOptions()
+    .with_has_header(True) # File contains a header row
+    .with_delimiter(";") # Use ; as the delimiter instead of ,
+    .with_comment("#")  # Skip lines starting with #
+    .with_escape("\\")  # Escape character
+    .with_null_regex(r"^(null|NULL|N/A)$")  # Treat these as NULL
+    .with_truncated_rows(True) # Allow rows to have incomplete columns
+    .with_file_compression_type("gzip")  # Read gzipped CSV
+    .with_file_extension(".gz") # File extension other than .csv
+)
+df = ctx.read_csv("data.csv.gz", options=options)
+
    +
    +

    Details for all CSV reading options can be found on the +DataFusion documentation site.

    diff --git a/user-guide/io/index.html b/user-guide/io/index.html index 183415639..5dd714ddf 100644 --- a/user-guide/io/index.html +++ b/user-guide/io/index.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/io/json.html b/user-guide/io/json.html index de0fc3b19..100317ffa 100644 --- a/user-guide/io/json.html +++ b/user-guide/io/json.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/io/parquet.html b/user-guide/io/parquet.html index 0d122763f..6039c851e 100644 --- a/user-guide/io/parquet.html +++ b/user-guide/io/parquet.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/io/table_provider.html b/user-guide/io/table_provider.html index ba7e1cbcb..875d160a8 100644 --- a/user-guide/io/table_provider.html +++ b/user-guide/io/table_provider.html @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan diff --git a/user-guide/sql.html b/user-guide/sql.html index 6dd6e0a48..0eeb3a249 100644 --- a/user-guide/sql.html +++ b/user-guide/sql.html @@ -34,7 +34,7 @@ - + @@ -243,6 +243,11 @@ SQL
    • +
  • + + Upgrade Guides + +

    • @@ -354,6 +359,11 @@ datafusion.object_store +

  • + + datafusion.options + +
  • datafusion.plan @@ -591,10 +601,10 @@

    Parameterized queriesConfiguration

     - +

    next

    -

    Introduction

    +

    Upgrade Guides

     diff --git a/user-guide/upgrade-guides.html b/user-guide/upgrade-guides.html new file mode 100644 index 000000000..97b92fc4a --- /dev/null +++ b/user-guide/upgrade-guides.html @@ -0,0 +1,571 @@ + + + + + + + + Upgrade Guides — Apache Arrow DataFusion documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + +
    +
    + + + + +
    + + +
    + + +
    +
    +
    +
    + + + + +
    + + +
    + +
    + On this page +
    + + +
    + +
    + +
    + + +
    + + + + + + +
    + +
    + +
    +

    Upgrade Guides

    +
    +

    DataFusion 52.0.0

    +

    This version includes a major update to the Python Extensions due to upgrades +to the Foreign Function Interface. +Users who contribute their own CatalogProvider, SchemaProvider, +TableProvider or TableFunction via FFI must now provide access to a +LogicalExtensionCodec and a TaskContextProvider. The function signatures +for the methods to get these PyCapsule objects now requires an additional +parameter, which is a Python object that can be used to extract the +FFI_LogicalExtensionCodec that is necessary.

    +

    A complete example can be found in the FFI example. +Your methods need to be updated to take an additional parameter like in this +example.

    +
    #[pymethods]
+impl MyCatalogProvider {
+    pub fn __datafusion_catalog_provider__<'py>(
+        &self,
+        py: Python<'py>,
+        session: Bound<PyAny>,
+    ) -> PyResult<Bound<'py, PyCapsule>> {
+        let name = cr"datafusion_catalog_provider".into();
+
+        let provider = Arc::clone(&self.inner) as Arc<dyn CatalogProvider + Send>;
+
+        let codec = ffi_logical_codec_from_pycapsule(session)?;
+        let provider = FFI_CatalogProvider::new_with_ffi_codec(provider, None, codec);
+
+        PyCapsule::new(py, provider, Some(name))
+    }
+}
+
    +
    +

    To extract the logical extension codec FFI object from the provided object you +can implement a helper method such as:

    +
    pub(crate) fn ffi_logical_codec_from_pycapsule(
+    obj: Bound<PyAny>,
+) -> PyResult<FFI_LogicalExtensionCodec> {
+    let attr_name = "__datafusion_logical_extension_codec__";
+    let capsule = if obj.hasattr(attr_name)? {
+        obj.getattr(attr_name)?.call0()?
+    } else {
+        obj
+    };
+
+    let capsule = capsule.downcast::<PyCapsule>()?;
+    validate_pycapsule(capsule, "datafusion_logical_extension_codec")?;
+
+    let codec = unsafe { capsule.reference::<FFI_LogicalExtensionCodec>() };
+
+    Ok(codec.clone())
+}
+
    +
    +

    The DataFusion FFI interface updates no longer depend directly on the +datafusion core crate. You can improve your build times and potentially +reduce your library binary size by removing this dependency and instead +using the specific datafusion project crates.

    +

    For example, instead of including expressions like:

    +
    use datafusion::catalog::MemTable;
+
    +
    +

    Instead you can now write:

    +
    use datafusion_catalog::MemTable;
+
    +
    +
    +
    + + +
    + + + +
    + + +
    +

    previous

    +

    SQL

    +
    +     + +
    +

    next

    +

    Introduction

    +
    + +     +
    + +
    + + +
    +
    + + + + +
    +
    + +
    +

    + © Copyright 2019-2024, Apache Software Foundation.
    +

    +
    + +
    +

    +Created using Sphinx 8.1.3.
    +

    +
    + +
    +

    Apache Arrow DataFusion, Arrow DataFusion, Apache, the Apache feather logo, and the Apache Arrow DataFusion project logo

    +

    are either registered trademarks or trademarks of The Apache Software Foundation in the United States and other countries.

    +
    +
    +
    + + + + \ No newline at end of file From 864566ab124d6df30b31a872ec39642d94dc064c Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Wed, 18 Feb 2026 20:25:20 +0000 Subject: [PATCH 33/36] Publish built docs triggered by 5affa06b17cdacd73b91808979309ce06312b2ae --- .../autoapi/datafusion/catalog/index.rst.txt | 83 ++ .../autoapi/datafusion/context/index.rst.txt | 22 +- .../datafusion/dataframe/index.rst.txt | 4 +- .../datafusion/functions/index.rst.txt | 25 +- _sources/autoapi/datafusion/index.rst.txt | 474 +++++++++- .../autoapi/datafusion/plan/index.rst.txt | 6 + .../datafusion/substrait/index.rst.txt | 20 + .../datafusion/user_defined/index.rst.txt | 18 +- .../common-operations/udf-and-udfa.rst.txt | 33 +- autoapi/datafusion/catalog/index.html | 195 +++- autoapi/datafusion/context/index.html | 65 +- autoapi/datafusion/dataframe/index.html | 4 +- autoapi/datafusion/functions/index.html | 158 ++-- autoapi/datafusion/index.html | 852 +++++++++++++++++- autoapi/datafusion/plan/index.html | 15 + autoapi/datafusion/substrait/index.html | 43 + autoapi/datafusion/user_defined/index.html | 16 +- genindex.html | 240 ++++- objects.inv | Bin 9168 -> 9481 bytes searchindex.js | 2 +- .../common-operations/aggregations.html | 32 +- user-guide/common-operations/basic-info.html | 34 +- user-guide/common-operations/functions.html | 20 +- .../common-operations/udf-and-udfa.html | 37 +- user-guide/introduction.html | 2 +- 25 files changed, 2160 insertions(+), 240 deletions(-) diff --git a/_sources/autoapi/datafusion/catalog/index.rst.txt b/_sources/autoapi/datafusion/catalog/index.rst.txt index aa511f3e0..f2c9776f3 100644 --- a/_sources/autoapi/datafusion/catalog/index.rst.txt +++ b/_sources/autoapi/datafusion/catalog/index.rst.txt @@ -15,7 +15,9 @@ Classes .. autoapisummary:: datafusion.catalog.Catalog + datafusion.catalog.CatalogList datafusion.catalog.CatalogProvider + datafusion.catalog.CatalogProviderList datafusion.catalog.Schema datafusion.catalog.SchemaProvider datafusion.catalog.Table @@ -84,6 +86,54 @@ Module Contents .. py:attribute:: catalog +.. py:class:: CatalogList(catalog_list: datafusion._internal.catalog.RawCatalogList) + + DataFusion data catalog list. + + This constructor is not typically called by the end user. + + + .. py:method:: __repr__() -> str + + Print a string representation of the catalog list. + + + + .. py:method:: catalog(name: str = 'datafusion') -> Catalog + + Returns the catalog with the given ``name`` from this catalog. + + + + .. py:method:: catalog_names() -> set[str] + + Returns the list of schemas in this catalog. + + + + .. py:method:: memory_catalog(ctx: datafusion.SessionContext | None = None) -> CatalogList + :staticmethod: + + + Create an in-memory catalog provider list. + + + + .. py:method:: names() -> set[str] + + This is an alias for `catalog_names`. + + + + .. py:method:: register_catalog(name: str, catalog: Catalog | CatalogProvider | CatalogProviderExportable) -> Catalog | None + + Register a catalog with this catalog list. + + + + .. py:attribute:: catalog_list + + .. py:class:: CatalogProvider Bases: :py:obj:`abc.ABC` @@ -129,6 +179,39 @@ Module Contents +.. py:class:: CatalogProviderList + + Bases: :py:obj:`abc.ABC` + + + Abstract class for defining a Python based Catalog Provider List. + + + .. py:method:: catalog(name: str) -> CatalogProviderExportable | CatalogProvider | Catalog | None + :abstractmethod: + + + Retrieve a specific catalog from this catalog list. + + + + .. py:method:: catalog_names() -> set[str] + :abstractmethod: + + + Set of the names of all catalogs in this catalog list. + + + + .. py:method:: register_catalog(name: str, catalog: CatalogProviderExportable | CatalogProvider | Catalog) -> None + + Add a catalog to this catalog list. + + This method is optional. If your catalog provides a fixed list of catalogs, you + do not need to implement this method. + + + .. py:class:: Schema(schema: datafusion._internal.catalog.RawSchema) DataFusion Schema. diff --git a/_sources/autoapi/datafusion/context/index.rst.txt b/_sources/autoapi/datafusion/context/index.rst.txt index 3c2be3ae2..f010a0103 100644 --- a/_sources/autoapi/datafusion/context/index.rst.txt +++ b/_sources/autoapi/datafusion/context/index.rst.txt @@ -16,7 +16,6 @@ Classes datafusion.context.ArrowArrayExportable datafusion.context.ArrowStreamExportable - datafusion.context.CatalogProviderExportable datafusion.context.RuntimeConfig datafusion.context.RuntimeEnvBuilder datafusion.context.SQLOptions @@ -54,19 +53,6 @@ Module Contents .. py:method:: __arrow_c_stream__(requested_schema: object | None = None) -> object -.. py:class:: CatalogProviderExportable - - Bases: :py:obj:`Protocol` - - - Type hint for object that has __datafusion_catalog_provider__ PyCapsule. - - https://docs.rs/datafusion/latest/datafusion/catalog/trait.CatalogProvider.html - - - .. py:method:: __datafusion_catalog_provider__(session: Any) -> object - - .. py:class:: RuntimeConfig Bases: :py:obj:`RuntimeEnvBuilder` @@ -698,12 +684,18 @@ Module Contents - .. py:method:: register_catalog_provider(name: str, provider: CatalogProviderExportable | datafusion.catalog.CatalogProvider | datafusion.catalog.Catalog) -> None + .. py:method:: register_catalog_provider(name: str, provider: datafusion.catalog.CatalogProviderExportable | datafusion.catalog.CatalogProvider | datafusion.catalog.Catalog) -> None Register a catalog provider. + .. py:method:: register_catalog_provider_list(provider: datafusion.catalog.CatalogProviderListExportable | datafusion.catalog.CatalogProviderList | datafusion.catalog.CatalogList) -> None + + Register a catalog provider list. + + + .. py:method:: register_csv(name: str, path: str | pathlib.Path | list[str | pathlib.Path], schema: pyarrow.Schema | None = None, has_header: bool = True, delimiter: str = ',', schema_infer_max_records: int = DEFAULT_MAX_INFER_SCHEMA, file_extension: str = '.csv', file_compression_type: str | None = None, options: datafusion.options.CsvReadOptions | None = None) -> None Register a CSV file as a table. diff --git a/_sources/autoapi/datafusion/dataframe/index.rst.txt b/_sources/autoapi/datafusion/dataframe/index.rst.txt index f4134a83d..0ac971060 100644 --- a/_sources/autoapi/datafusion/dataframe/index.rst.txt +++ b/_sources/autoapi/datafusion/dataframe/index.rst.txt @@ -27,7 +27,7 @@ Classes Module Contents --------------- -.. py:class:: Compression(*args, **kwds) +.. py:class:: Compression Bases: :py:obj:`enum.Enum` @@ -891,7 +891,7 @@ Module Contents .. py:attribute:: _raw_write_options -.. py:class:: InsertOp(*args, **kwds) +.. py:class:: InsertOp Bases: :py:obj:`enum.Enum` diff --git a/_sources/autoapi/datafusion/functions/index.rst.txt b/_sources/autoapi/datafusion/functions/index.rst.txt index 10b7f1a01..f1c509093 100644 --- a/_sources/autoapi/datafusion/functions/index.rst.txt +++ b/_sources/autoapi/datafusion/functions/index.rst.txt @@ -195,6 +195,7 @@ Functions datafusion.functions.range datafusion.functions.rank datafusion.functions.regexp_count + datafusion.functions.regexp_instr datafusion.functions.regexp_like datafusion.functions.regexp_match datafusion.functions.regexp_replace @@ -390,7 +391,7 @@ Module Contents For example:: - df.select(array_agg(col("a"), order_by="b")) + df.aggregate([], array_agg(col("a"), order_by="b")) .. py:function:: array_append(array: datafusion.expr.Expr, element: datafusion.expr.Expr) -> datafusion.expr.Expr @@ -1056,7 +1057,7 @@ Module Contents For example:: - df.select(first_value(col("a"), order_by="ts")) + df.aggregate([], first_value(col("a"), order_by="ts")) .. py:function:: flatten(array: datafusion.expr.Expr) -> datafusion.expr.Expr @@ -1152,7 +1153,7 @@ Module Contents For example:: - df.select(last_value(col("a"), order_by="ts")) + df.aggregate([], last_value(col("a"), order_by="ts")) .. py:function:: lcm(x: datafusion.expr.Expr, y: datafusion.expr.Expr) -> datafusion.expr.Expr @@ -1521,7 +1522,7 @@ Module Contents .. py:function:: min(expression: datafusion.expr.Expr, filter: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr - Returns the minimum value of the argument. + Aggregate function that returns the minimum value of the argument. If using the builder functions described in ref:`_aggregation` this function ignores the options ``order_by``, ``null_treatment``, and ``distinct``. @@ -1565,7 +1566,7 @@ Module Contents For example:: - df.select(nth_value(col("a"), 2, order_by="ts")) + df.aggregate([], nth_value(col("a"), 2, order_by="ts")) .. py:function:: ntile(groups: int, partition_by: list[datafusion.expr.Expr] | datafusion.expr.Expr | None = None, order_by: list[datafusion.expr.SortKey] | datafusion.expr.SortKey | None = None) -> datafusion.expr.Expr @@ -1718,7 +1719,7 @@ Module Contents rank(order_by="points") -.. py:function:: regexp_count(string: datafusion.expr.Expr, pattern: datafusion.expr.Expr, start: datafusion.expr.Expr, flags: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr +.. py:function:: regexp_count(string: datafusion.expr.Expr, pattern: datafusion.expr.Expr, start: datafusion.expr.Expr | None = None, flags: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr Returns the number of matches in a string. @@ -1726,6 +1727,16 @@ Module Contents expression. +.. py:function:: regexp_instr(values: datafusion.expr.Expr, regex: datafusion.expr.Expr, start: datafusion.expr.Expr | None = None, n: datafusion.expr.Expr | None = None, flags: datafusion.expr.Expr | None = None, sub_expr: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr + + Returns the position of a regular expression match in a string. + + Searches ``values`` for the ``n``-th occurrence of ``regex``, starting at position + ``start`` (the first position is 1). Returns the starting or ending position based + on ``end_position``. Use ``flags`` to control regex behavior and ``sub_expr`` to + return the position of a specific capture group instead of the entire match. + + .. py:function:: regexp_like(string: datafusion.expr.Expr, regex: datafusion.expr.Expr, flags: datafusion.expr.Expr | None = None) -> datafusion.expr.Expr Find if any regular expression (regex) matches exist. @@ -2057,7 +2068,7 @@ Module Contents For example:: - df.select(string_agg(col("a"), ",", order_by="b")) + df.aggregate([], string_agg(col("a"), ",", order_by="b")) .. py:function:: strpos(string: datafusion.expr.Expr, substring: datafusion.expr.Expr) -> datafusion.expr.Expr diff --git a/_sources/autoapi/datafusion/index.rst.txt b/_sources/autoapi/datafusion/index.rst.txt index 8afeae253..24fecff4f 100644 --- a/_sources/autoapi/datafusion/index.rst.txt +++ b/_sources/autoapi/datafusion/index.rst.txt @@ -44,6 +44,10 @@ Attributes datafusion.DFSchema datafusion.col datafusion.column + datafusion.udaf + datafusion.udf + datafusion.udtf + datafusion.udwf Classes @@ -51,6 +55,8 @@ Classes .. autoapisummary:: + datafusion.Accumulator + datafusion.AggregateUDF datafusion.Catalog datafusion.CsvReadOptions datafusion.DataFrameWriteOptions @@ -65,9 +71,12 @@ Classes datafusion.RecordBatchStream datafusion.RuntimeEnvBuilder datafusion.SQLOptions + datafusion.ScalarUDF datafusion.SessionConfig datafusion.Table + datafusion.TableFunction datafusion.WindowFrame + datafusion.WindowUDF Functions @@ -87,6 +96,179 @@ Functions Package Contents ---------------- +.. py:class:: Accumulator + + Defines how an :py:class:`AggregateUDF` accumulates values. + + + .. py:method:: evaluate() -> pyarrow.Scalar + :abstractmethod: + + + Return the resultant value. + + While this function template expects a PyArrow Scalar value return type, + you can return any value that can be converted into a Scalar. This + includes basic Python data types such as integers and strings. In + addition to primitive types, we currently support PyArrow, nanoarrow, + and arro3 objects in addition to primitive data types. Other objects + that support the Arrow FFI standard will be given a "best attempt" at + conversion to scalar objects. + + + + .. py:method:: merge(states: list[pyarrow.Array]) -> None + :abstractmethod: + + + Merge a set of states. + + + + .. py:method:: state() -> list[pyarrow.Scalar] + :abstractmethod: + + + Return the current state. + + While this function template expects PyArrow Scalar values return type, + you can return any value that can be converted into a Scalar. This + includes basic Python data types such as integers and strings. In + addition to primitive types, we currently support PyArrow, nanoarrow, + and arro3 objects in addition to primitive data types. Other objects + that support the Arrow FFI standard will be given a "best attempt" at + conversion to scalar objects. + + + + .. py:method:: update(*values: pyarrow.Array) -> None + :abstractmethod: + + + Evaluate an array of values and update state. + + + +.. py:class:: AggregateUDF(name: str, accumulator: collections.abc.Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str) + AggregateUDF(name: str, accumulator: AggregateUDFExportable, input_types: None = ..., return_type: None = ..., state_type: None = ..., volatility: None = ...) + + Class for performing scalar user-defined functions (UDF). + + Aggregate UDFs operate on a group of rows and return a single value. See + also :py:class:`ScalarUDF` for operating on a row by row basis. + + Instantiate a user-defined aggregate function (UDAF). + + See :py:func:`udaf` for a convenience function and argument + descriptions. + + + .. py:method:: __call__(*args: datafusion.expr.Expr) -> datafusion.expr.Expr + + Execute the UDAF. + + This function is not typically called by an end user. These calls will + occur during the evaluation of the dataframe. + + + + .. py:method:: __repr__() -> str + + Print a string representation of the Aggregate UDF. + + + + .. py:method:: from_pycapsule(func: AggregateUDFExportable | _typeshed.CapsuleType) -> AggregateUDF + :staticmethod: + + + Create an Aggregate UDF from AggregateUDF PyCapsule object. + + This function will instantiate a Aggregate UDF that uses a DataFusion + AggregateUDF that is exported via the FFI bindings. + + + + .. py:method:: udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[Ellipsis, AggregateUDF] + udaf(accum: collections.abc.Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) -> AggregateUDF + udaf(accum: AggregateUDFExportable) -> AggregateUDF + udaf(accum: _typeshed.CapsuleType) -> AggregateUDF + :staticmethod: + + + Create a new User-Defined Aggregate Function (UDAF). + + This class allows you to define an aggregate function that can be used in + data aggregation or window function calls. + + Usage: + - As a function: ``udaf(accum, input_types, return_type, state_type, volatility, name)``. + - As a decorator: ``@udaf(input_types, return_type, state_type, volatility, name)``. + When using ``udaf`` as a decorator, do not pass ``accum`` explicitly. + + Function example: + + If your :py:class:`Accumulator` can be instantiated with no arguments, you + can simply pass it's type as `accum`. If you need to pass additional + arguments to it's constructor, you can define a lambda or a factory method. + During runtime the :py:class:`Accumulator` will be constructed for every + instance in which this UDAF is used. The following examples are all valid:: + + import pyarrow as pa + import pyarrow.compute as pc + + class Summarize(Accumulator): + def __init__(self, bias: float = 0.0): + self._sum = pa.scalar(bias) + + def state(self) -> list[pa.Scalar]: + return [self._sum] + + def update(self, values: pa.Array) -> None: + self._sum = pa.scalar(self._sum.as_py() + pc.sum(values).as_py()) + + def merge(self, states: list[pa.Array]) -> None: + self._sum = pa.scalar(self._sum.as_py() + pc.sum(states[0]).as_py()) + + def evaluate(self) -> pa.Scalar: + return self._sum + + def sum_bias_10() -> Summarize: + return Summarize(10.0) + + udaf1 = udaf(Summarize, pa.float64(), pa.float64(), [pa.float64()], + "immutable") + udaf2 = udaf(sum_bias_10, pa.float64(), pa.float64(), [pa.float64()], + "immutable") + udaf3 = udaf(lambda: Summarize(20.0), pa.float64(), pa.float64(), + [pa.float64()], "immutable") + + Decorator example::: + + @udaf(pa.float64(), pa.float64(), [pa.float64()], "immutable") + def udf4() -> Summarize: + return Summarize(10.0) + + :param accum: The accumulator python function. Only needed when calling as a + function. Skip this argument when using ``udaf`` as a decorator. + If you have a Rust backed AggregateUDF within a PyCapsule, you can + pass this parameter and ignore the rest. They will be determined + directly from the underlying function. See the online documentation + for more information. + :param input_types: The data types of the arguments to ``accum``. + :param return_type: The data type of the return value. + :param state_type: The data types of the intermediate accumulation. + :param volatility: See :py:class:`Volatility` for allowed values. + :param name: A descriptive name for the function. + + :returns: A user-defined aggregate function, which can be used in either data + aggregation or window function calls. + + + + .. py:attribute:: _udaf + + .. py:class:: Catalog(catalog: datafusion._internal.catalog.RawCatalog) DataFusion data catalog. @@ -1298,7 +1480,7 @@ Package Contents .. py:attribute:: expr -.. py:class:: InsertOp(*args, **kwds) +.. py:class:: InsertOp Bases: :py:obj:`enum.Enum` @@ -1343,6 +1525,12 @@ Package Contents This constructor should not be called by the end user. + .. py:method:: __eq__(other: LogicalPlan) -> bool + + Test equality. + + + .. py:method:: __repr__() -> str Generate a printable representation of the plan. @@ -1897,6 +2085,101 @@ Package Contents .. py:attribute:: options_internal +.. py:class:: ScalarUDF(name: str, func: collections.abc.Callable[Ellipsis, _R], input_fields: list[pyarrow.Field], return_field: _R, volatility: Volatility | str) + + Class for performing scalar user-defined functions (UDF). + + Scalar UDFs operate on a row by row basis. See also :py:class:`AggregateUDF` for + operating on a group of rows. + + Instantiate a scalar user-defined function (UDF). + + See helper method :py:func:`udf` for argument details. + + + .. py:method:: __call__(*args: datafusion.expr.Expr) -> datafusion.expr.Expr + + Execute the UDF. + + This function is not typically called by an end user. These calls will + occur during the evaluation of the dataframe. + + + + .. py:method:: __repr__() -> str + + Print a string representation of the Scalar UDF. + + + + .. py:method:: from_pycapsule(func: ScalarUDFExportable) -> ScalarUDF + :staticmethod: + + + Create a Scalar UDF from ScalarUDF PyCapsule object. + + This function will instantiate a Scalar UDF that uses a DataFusion + ScalarUDF that is exported via the FFI bindings. + + + + .. py:method:: udf(input_fields: collections.abc.Sequence[pyarrow.DataType | pyarrow.Field] | pyarrow.DataType | pyarrow.Field, return_field: pyarrow.DataType | pyarrow.Field, volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[Ellipsis, ScalarUDF] + udf(func: collections.abc.Callable[Ellipsis, _R], input_fields: collections.abc.Sequence[pyarrow.DataType | pyarrow.Field] | pyarrow.DataType | pyarrow.Field, return_field: pyarrow.DataType | pyarrow.Field, volatility: Volatility | str, name: str | None = None) -> ScalarUDF + udf(func: ScalarUDFExportable) -> ScalarUDF + :staticmethod: + + + Create a new User-Defined Function (UDF). + + This class can be used both as either a function or a decorator. + + Usage: + - As a function: ``udf(func, input_fields, return_field, volatility, name)``. + - As a decorator: ``@udf(input_fields, return_field, volatility, name)``. + When used a decorator, do **not** pass ``func`` explicitly. + + In lieu of passing a PyArrow Field, you can pass a DataType for simplicity. + When you do so, it will be assumed that the nullability of the inputs and + output are True and that they have no metadata. + + :param func: Only needed when calling as a function. + Skip this argument when using `udf` as a decorator. If you have a Rust + backed ScalarUDF within a PyCapsule, you can pass this parameter + and ignore the rest. They will be determined directly from the + underlying function. See the online documentation for more information. + :type func: Callable, optional + :param input_fields: The data types or Fields + of the arguments to ``func``. This list must be of the same length + as the number of arguments. + :type input_fields: list[pa.Field | pa.DataType] + :param return_field: The field of the return value from the function. + :type return_field: _R + :param volatility: See `Volatility` for allowed values. + :type volatility: Volatility | str + :param name: A descriptive name for the function. + :type name: Optional[str] + + :returns: A user-defined function that can be used in SQL expressions, + data aggregation, or window function calls. + + Example: Using ``udf`` as a function:: + + def double_func(x): + return x * 2 + double_udf = udf(double_func, [pa.int32()], pa.int32(), + "volatile", "double_it") + + Example: Using ``udf`` as a decorator:: + + @udf([pa.int32()], pa.int32(), "volatile", "double_it") + def double_udf(x): + return x * 2 + + + + .. py:attribute:: _udf + + .. py:class:: SessionConfig(config_options: dict[str, str] | None = None) Session configuration options. @@ -2105,6 +2388,59 @@ Package Contents Returns the schema associated with this table. +.. py:class:: TableFunction(name: str, func: collections.abc.Callable[[], any], ctx: datafusion.SessionContext | None = None) + + Class for performing user-defined table functions (UDTF). + + Table functions generate new table providers based on the + input expressions. + + Instantiate a user-defined table function (UDTF). + + See :py:func:`udtf` for a convenience function and argument + descriptions. + + + .. py:method:: __call__(*args: datafusion.expr.Expr) -> Any + + Execute the UDTF and return a table provider. + + + + .. py:method:: __repr__() -> str + + User printable representation. + + + + .. py:method:: _create_table_udf(func: collections.abc.Callable[Ellipsis, Any], name: str) -> TableFunction + :staticmethod: + + + Create a TableFunction instance from function arguments. + + + + .. py:method:: _create_table_udf_decorator(name: str | None = None) -> collections.abc.Callable[[collections.abc.Callable[[], WindowEvaluator]], collections.abc.Callable[Ellipsis, datafusion.expr.Expr]] + :staticmethod: + + + Create a decorator for a WindowUDF. + + + + .. py:method:: udtf(name: str) -> collections.abc.Callable[Ellipsis, Any] + udtf(func: collections.abc.Callable[[], Any], name: str) -> TableFunction + :staticmethod: + + + Create a new User-Defined Table Function (UDTF). + + + + .. py:attribute:: _udtf + + .. py:class:: WindowFrame(units: str, start_bound: Any | None, end_bound: Any | None) Defines a window frame for performing window operations. @@ -2147,6 +2483,134 @@ Package Contents .. py:attribute:: window_frame +.. py:class:: WindowUDF(name: str, func: collections.abc.Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str) + + Class for performing window user-defined functions (UDF). + + Window UDFs operate on a partition of rows. See + also :py:class:`ScalarUDF` for operating on a row by row basis. + + Instantiate a user-defined window function (UDWF). + + See :py:func:`udwf` for a convenience function and argument + descriptions. + + + .. py:method:: __call__(*args: datafusion.expr.Expr) -> datafusion.expr.Expr + + Execute the UDWF. + + This function is not typically called by an end user. These calls will + occur during the evaluation of the dataframe. + + + + .. py:method:: __repr__() -> str + + Print a string representation of the Window UDF. + + + + .. py:method:: _create_window_udf(func: collections.abc.Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) -> WindowUDF + :staticmethod: + + + Create a WindowUDF instance from function arguments. + + + + .. py:method:: _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[[collections.abc.Callable[[], WindowEvaluator]], collections.abc.Callable[Ellipsis, datafusion.expr.Expr]] + :staticmethod: + + + Create a decorator for a WindowUDF. + + + + .. py:method:: _get_default_name(func: collections.abc.Callable) -> str + :staticmethod: + + + Get the default name for a function based on its attributes. + + + + .. py:method:: _normalize_input_types(input_types: pyarrow.DataType | list[pyarrow.DataType]) -> list[pyarrow.DataType] + :staticmethod: + + + Convert a single DataType to a list if needed. + + + + .. py:method:: from_pycapsule(func: WindowUDFExportable) -> WindowUDF + :staticmethod: + + + Create a Window UDF from WindowUDF PyCapsule object. + + This function will instantiate a Window UDF that uses a DataFusion + WindowUDF that is exported via the FFI bindings. + + + + .. py:method:: udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) -> collections.abc.Callable[Ellipsis, WindowUDF] + udwf(func: collections.abc.Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) -> WindowUDF + :staticmethod: + + + Create a new User-Defined Window Function (UDWF). + + This class can be used both as either a function or a decorator. + + Usage: + - As a function: ``udwf(func, input_types, return_type, volatility, name)``. + - As a decorator: ``@udwf(input_types, return_type, volatility, name)``. + When using ``udwf`` as a decorator, do not pass ``func`` explicitly. + + Function example:: + + import pyarrow as pa + + class BiasedNumbers(WindowEvaluator): + def __init__(self, start: int = 0) -> None: + self.start = start + + def evaluate_all(self, values: list[pa.Array], + num_rows: int) -> pa.Array: + return pa.array([self.start + i for i in range(num_rows)]) + + def bias_10() -> BiasedNumbers: + return BiasedNumbers(10) + + udwf1 = udwf(BiasedNumbers, pa.int64(), pa.int64(), "immutable") + udwf2 = udwf(bias_10, pa.int64(), pa.int64(), "immutable") + udwf3 = udwf(lambda: BiasedNumbers(20), pa.int64(), pa.int64(), "immutable") + + + Decorator example:: + + @udwf(pa.int64(), pa.int64(), "immutable") + def biased_numbers() -> BiasedNumbers: + return BiasedNumbers(10) + + :param func: Only needed when calling as a function. Skip this argument when + using ``udwf`` as a decorator. If you have a Rust backed WindowUDF + within a PyCapsule, you can pass this parameter and ignore the rest. + They will be determined directly from the underlying function. See + the online documentation for more information. + :param input_types: The data types of the arguments. + :param return_type: The data type of the return value. + :param volatility: See :py:class:`Volatility` for allowed values. + :param name: A descriptive name for the function. + + :returns: A user-defined window function that can be used in window function calls. + + + + .. py:attribute:: _udwf + + .. py:function:: configure_formatter(**kwargs: Any) -> None Configure the global DataFrame HTML formatter. @@ -2276,3 +2740,11 @@ Package Contents .. py:data:: column :type: Col +.. py:data:: udaf + +.. py:data:: udf + +.. py:data:: udtf + +.. py:data:: udwf + diff --git a/_sources/autoapi/datafusion/plan/index.rst.txt b/_sources/autoapi/datafusion/plan/index.rst.txt index c29dcdad1..93af06184 100644 --- a/_sources/autoapi/datafusion/plan/index.rst.txt +++ b/_sources/autoapi/datafusion/plan/index.rst.txt @@ -100,6 +100,12 @@ Module Contents This constructor should not be called by the end user. + .. py:method:: __eq__(other: LogicalPlan) -> bool + + Test equality. + + + .. py:method:: __repr__() -> str Generate a printable representation of the plan. diff --git a/_sources/autoapi/datafusion/substrait/index.rst.txt b/_sources/autoapi/datafusion/substrait/index.rst.txt index 38160a6ad..b9a1fd525 100644 --- a/_sources/autoapi/datafusion/substrait/index.rst.txt +++ b/_sources/autoapi/datafusion/substrait/index.rst.txt @@ -63,6 +63,26 @@ Module Contents + .. py:method:: from_json(json: str) -> Plan + :staticmethod: + + + Parse a plan from a JSON string representation. + + :param json: JSON representation of a Substrait plan. + + :returns: Plan object representing the Substrait plan. + + + + .. py:method:: to_json() -> str + + Get the JSON representation of the Substrait plan. + + :returns: A JSON representation of the Substrait plan. + + + .. py:attribute:: plan_internal diff --git a/_sources/autoapi/datafusion/user_defined/index.rst.txt b/_sources/autoapi/datafusion/user_defined/index.rst.txt index 1a7a93d34..21063829c 100644 --- a/_sources/autoapi/datafusion/user_defined/index.rst.txt +++ b/_sources/autoapi/datafusion/user_defined/index.rst.txt @@ -62,6 +62,14 @@ Module Contents Return the resultant value. + While this function template expects a PyArrow Scalar value return type, + you can return any value that can be converted into a Scalar. This + includes basic Python data types such as integers and strings. In + addition to primitive types, we currently support PyArrow, nanoarrow, + and arro3 objects in addition to primitive data types. Other objects + that support the Arrow FFI standard will be given a "best attempt" at + conversion to scalar objects. + .. py:method:: merge(states: list[pyarrow.Array]) -> None @@ -78,6 +86,14 @@ Module Contents Return the current state. + While this function template expects PyArrow Scalar values return type, + you can return any value that can be converted into a Scalar. This + includes basic Python data types such as integers and strings. In + addition to primitive types, we currently support PyArrow, nanoarrow, + and arro3 objects in addition to primitive data types. Other objects + that support the Arrow FFI standard will be given a "best attempt" at + conversion to scalar objects. + .. py:method:: update(*values: pyarrow.Array) -> None @@ -378,7 +394,7 @@ Module Contents .. py:attribute:: _udtf -.. py:class:: Volatility(*args, **kwds) +.. py:class:: Volatility Bases: :py:obj:`enum.Enum` diff --git a/_sources/user-guide/common-operations/udf-and-udfa.rst.txt b/_sources/user-guide/common-operations/udf-and-udfa.rst.txt index d554e1e25..f669721a3 100644 --- a/_sources/user-guide/common-operations/udf-and-udfa.rst.txt +++ b/_sources/user-guide/common-operations/udf-and-udfa.rst.txt @@ -123,7 +123,7 @@ also see how the inputs to ``update`` and ``merge`` differ. .. code-block:: python - import pyarrow + import pyarrow as pa import pyarrow.compute import datafusion from datafusion import col, udaf, Accumulator @@ -136,16 +136,16 @@ also see how the inputs to ``update`` and ``merge`` differ. def __init__(self): self._sum = 0.0 - def update(self, values_a: pyarrow.Array, values_b: pyarrow.Array) -> None: + def update(self, values_a: pa.Array, values_b: pa.Array) -> None: self._sum = self._sum + pyarrow.compute.sum(values_a).as_py() - pyarrow.compute.sum(values_b).as_py() - def merge(self, states: List[pyarrow.Array]) -> None: + def merge(self, states: list[pa.Array]) -> None: self._sum = self._sum + pyarrow.compute.sum(states[0]).as_py() - def state(self) -> pyarrow.Array: - return pyarrow.array([self._sum]) + def state(self) -> list[pa.Scalar]: + return [pyarrow.scalar(self._sum)] - def evaluate(self) -> pyarrow.Scalar: + def evaluate(self) -> pa.Scalar: return pyarrow.scalar(self._sum) ctx = datafusion.SessionContext() @@ -156,10 +156,29 @@ also see how the inputs to ``update`` and ``merge`` differ. } ) - my_udaf = udaf(MyAccumulator, [pyarrow.float64(), pyarrow.float64()], pyarrow.float64(), [pyarrow.float64()], 'stable') + my_udaf = udaf(MyAccumulator, [pa.float64(), pa.float64()], pa.float64(), [pa.float64()], 'stable') df.aggregate([], [my_udaf(col("a"), col("b")).alias("col_diff")]) +FAQ +^^^ + +**How do I return a list from a UDAF?** + +Both the ``evaluate`` and the ``state`` functions expect to return scalar values. +If you wish to return a list array as a scalar value, the best practice is to +wrap the values in a ``pyarrow.Scalar`` object. For example, you can return a +timestamp list with ``pa.scalar([...], type=pa.list_(pa.timestamp("ms")))`` and +register the appropriate return or state types as +``return_type=pa.list_(pa.timestamp("ms"))`` and +``state_type=[pa.list_(pa.timestamp("ms"))]``, respectively. + +As of DataFusion 52.0.0 , you can pass return any Python object, including a +PyArrow array, as the return value(s) for these functions and DataFusion will +attempt to create a scalar type from the value. DataFusion has been tested to +convert PyArrow, nanoarrow, and arro3 objects as well as primitive data types +like integers, strings, and so on. + Window Functions ---------------- diff --git a/autoapi/datafusion/catalog/index.html b/autoapi/datafusion/catalog/index.html index e99ff9e4e..2defa8e95 100644 --- a/autoapi/datafusion/catalog/index.html +++ b/autoapi/datafusion/catalog/index.html @@ -519,6 +519,80 @@

    • +
  • + + + + CatalogList + + + + +
  • @@ -566,6 +640,44 @@
    • +
  • + + + + CatalogProviderList + + + + +
  • @@ -821,9 +933,15 @@

    Classes

    • Catalog

    DataFusion data catalog.

    CatalogProvider

    CatalogList

    DataFusion data catalog list.

    CatalogProvider

    Abstract class for defining a Python based Catalog Provider.

    CatalogProviderList

    Abstract class for defining a Python based Catalog Provider List.

    Schema

    DataFusion Schema.

    ArrowStreamExportable

    Type hint for object exporting Arrow C Stream via Arrow PyCapsule Interface.

    CatalogProviderExportable

    Type hint for object that has __datafusion_catalog_provider__ PyCapsule.

    RuntimeConfig

    RuntimeConfig

    See RuntimeEnvBuilder.

    RuntimeEnvBuilder

    RuntimeEnvBuilder

    Runtime configuration options.

    SQLOptions

    SQLOptions

    Options to be used when performing SQL queries.

    SessionConfig

    SessionConfig

    Session configuration options.

    SessionContext

    SessionContext

    This is the main interface for executing queries and creating DataFrames.

    TableProviderExportable

    TableProviderExportable

    Type hint for object that has __datafusion_table_provider__ PyCapsule.

    min(→ datafusion.expr.Expr)

    Returns the minimum value of the argument.

    Aggregate function that returns the minimum value of the argument.

    named_struct(→ datafusion.expr.Expr)

    Returns a struct with the given names and arguments pairs.

    regexp_count(→ datafusion.expr.Expr)

    Returns the number of matches in a string.

    regexp_like(→ datafusion.expr.Expr)

    regexp_instr(→ datafusion.expr.Expr)

    Returns the position of a regular expression match in a string.

    regexp_like(→ datafusion.expr.Expr)

    Find if any regular expression (regex) matches exist.

    regexp_match(→ datafusion.expr.Expr)

    regexp_match(→ datafusion.expr.Expr)

    Perform regular expression (regex) matching.

    regexp_replace(→ datafusion.expr.Expr)

    regexp_replace(→ datafusion.expr.Expr)

    Replaces substring(s) matching a PCRE-like regular expression.

    regr_avgx(→ datafusion.expr.Expr)

    regr_avgx(→ datafusion.expr.Expr)

    Computes the average of the independent variable x.

    regr_avgy(→ datafusion.expr.Expr)

    regr_avgy(→ datafusion.expr.Expr)

    Computes the average of the dependent variable y.

    regr_count(→ datafusion.expr.Expr)

    regr_count(→ datafusion.expr.Expr)

    Counts the number of rows in which both expressions are not null.

    regr_intercept(→ datafusion.expr.Expr)

    regr_intercept(→ datafusion.expr.Expr)

    Computes the intercept from the linear regression.

    regr_r2(→ datafusion.expr.Expr)

    regr_r2(→ datafusion.expr.Expr)

    Computes the R-squared value from linear regression.

    regr_slope(→ datafusion.expr.Expr)

    regr_slope(→ datafusion.expr.Expr)

    Computes the slope from linear regression.

    regr_sxx(→ datafusion.expr.Expr)

    regr_sxx(→ datafusion.expr.Expr)

    Computes the sum of squares of the independent variable x.

    regr_sxy(→ datafusion.expr.Expr)

    regr_sxy(→ datafusion.expr.Expr)

    Computes the sum of products of pairs of numbers.

    regr_syy(→ datafusion.expr.Expr)

    regr_syy(→ datafusion.expr.Expr)

    Computes the sum of squares of the dependent variable y.

    repeat(→ datafusion.expr.Expr)

    repeat(→ datafusion.expr.Expr)

    Repeats the string to n times.

    replace(→ datafusion.expr.Expr)

    replace(→ datafusion.expr.Expr)

    Replaces all occurrences of from_val with to_val in the string.

    reverse(→ datafusion.expr.Expr)

    reverse(→ datafusion.expr.Expr)

    Reverse the string argument.

    right(→ datafusion.expr.Expr)

    right(→ datafusion.expr.Expr)

    Returns the last n characters in the string.

    round(→ datafusion.expr.Expr)

    round(→ datafusion.expr.Expr)

    Round the argument to the nearest integer.

    row_number(→ datafusion.expr.Expr)

    row_number(→ datafusion.expr.Expr)

    Create a row number window function.

    rpad(→ datafusion.expr.Expr)

    rpad(→ datafusion.expr.Expr)

    Add right padding to a string.

    rtrim(→ datafusion.expr.Expr)

    rtrim(→ datafusion.expr.Expr)

    Removes all characters, spaces by default, from the end of a string.

    sha224(→ datafusion.expr.Expr)

    sha224(→ datafusion.expr.Expr)

    Computes the SHA-224 hash of a binary string.

    sha256(→ datafusion.expr.Expr)

    sha256(→ datafusion.expr.Expr)

    Computes the SHA-256 hash of a binary string.

    sha384(→ datafusion.expr.Expr)

    sha384(→ datafusion.expr.Expr)

    Computes the SHA-384 hash of a binary string.

    sha512(→ datafusion.expr.Expr)

    sha512(→ datafusion.expr.Expr)

    Computes the SHA-512 hash of a binary string.

    signum(→ datafusion.expr.Expr)

    signum(→ datafusion.expr.Expr)

    Returns the sign of the argument (-1, 0, +1).

    sin(→ datafusion.expr.Expr)

    sin(→ datafusion.expr.Expr)

    Returns the sine of the argument.

    sinh(→ datafusion.expr.Expr)

    sinh(→ datafusion.expr.Expr)

    Returns the hyperbolic sine of the argument.

    split_part(→ datafusion.expr.Expr)

    split_part(→ datafusion.expr.Expr)

    Split a string and return one part.

    sqrt(→ datafusion.expr.Expr)

    sqrt(→ datafusion.expr.Expr)

    Returns the square root of the argument.

    starts_with(→ datafusion.expr.Expr)

    starts_with(→ datafusion.expr.Expr)

    Returns true if string starts with prefix.

    stddev(→ datafusion.expr.Expr)

    stddev(→ datafusion.expr.Expr)

    Computes the standard deviation of the argument.

    stddev_pop(→ datafusion.expr.Expr)

    stddev_pop(→ datafusion.expr.Expr)

    Computes the population standard deviation of the argument.

    stddev_samp(→ datafusion.expr.Expr)

    stddev_samp(→ datafusion.expr.Expr)

    Computes the sample standard deviation of the argument.

    string_agg(→ datafusion.expr.Expr)

    string_agg(→ datafusion.expr.Expr)

    Concatenates the input strings.

    strpos(→ datafusion.expr.Expr)

    strpos(→ datafusion.expr.Expr)

    Finds the position from where the substring matches the string.

    struct(→ datafusion.expr.Expr)

    struct(→ datafusion.expr.Expr)

    Returns a struct with the given arguments.

    substr(→ datafusion.expr.Expr)

    substr(→ datafusion.expr.Expr)

    Substring from the position to the end.

    substr_index(→ datafusion.expr.Expr)

    substr_index(→ datafusion.expr.Expr)

    Returns an indexed substring.

    substring(→ datafusion.expr.Expr)

    substring(→ datafusion.expr.Expr)

    Substring from the position with length characters.

    sum(→ datafusion.expr.Expr)

    sum(→ datafusion.expr.Expr)

    Computes the sum of a set of numbers.

    tan(→ datafusion.expr.Expr)

    tan(→ datafusion.expr.Expr)

    Returns the tangent of the argument.

    tanh(→ datafusion.expr.Expr)

    tanh(→ datafusion.expr.Expr)

    Returns the hyperbolic tangent of the argument.

    to_hex(→ datafusion.expr.Expr)

    to_hex(→ datafusion.expr.Expr)

    Converts an integer to a hexadecimal string.

    to_timestamp(→ datafusion.expr.Expr)

    to_timestamp(→ datafusion.expr.Expr)

    Converts a string and optional formats to a Timestamp in nanoseconds.

    to_timestamp_micros(→ datafusion.expr.Expr)

    to_timestamp_micros(→ datafusion.expr.Expr)

    Converts a string and optional formats to a Timestamp in microseconds.

    to_timestamp_millis(→ datafusion.expr.Expr)

    to_timestamp_millis(→ datafusion.expr.Expr)

    Converts a string and optional formats to a Timestamp in milliseconds.

    to_timestamp_nanos(→ datafusion.expr.Expr)

    to_timestamp_nanos(→ datafusion.expr.Expr)

    Converts a string and optional formats to a Timestamp in nanoseconds.

    to_timestamp_seconds(→ datafusion.expr.Expr)

    to_timestamp_seconds(→ datafusion.expr.Expr)

    Converts a string and optional formats to a Timestamp in seconds.

    to_unixtime(→ datafusion.expr.Expr)

    to_unixtime(→ datafusion.expr.Expr)

    Converts a string and optional formats to a Unixtime.

    translate(→ datafusion.expr.Expr)

    translate(→ datafusion.expr.Expr)

    Replaces the characters in from_val with the counterpart in to_val.

    trim(→ datafusion.expr.Expr)

    trim(→ datafusion.expr.Expr)

    Removes all characters, spaces by default, from both sides of a string.

    trunc(→ datafusion.expr.Expr)

    trunc(→ datafusion.expr.Expr)

    Truncate the number toward zero with optional precision.

    upper(→ datafusion.expr.Expr)

    upper(→ datafusion.expr.Expr)

    Converts a string to uppercase.

    uuid(→ datafusion.expr.Expr)

    uuid(→ datafusion.expr.Expr)

    Returns uuid v4 as a string value.

    var(→ datafusion.expr.Expr)

    var(→ datafusion.expr.Expr)

    Computes the sample variance of the argument.

    var_pop(→ datafusion.expr.Expr)

    var_pop(→ datafusion.expr.Expr)

    Computes the population variance of the argument.

    var_samp(→ datafusion.expr.Expr)

    var_samp(→ datafusion.expr.Expr)

    Computes the sample variance of the argument.

    var_sample(→ datafusion.expr.Expr)

    var_sample(→ datafusion.expr.Expr)

    Computes the sample variance of the argument.

    when(→ datafusion.expr.CaseBuilder)

    when(→ datafusion.expr.CaseBuilder)

    Create a case expression that has no base expression.

    window(→ datafusion.expr.Expr)

    window(→ datafusion.expr.Expr)

    Creates a new Window function expression.

    column

    udaf

    udf

    udtf

    udwf
    @@ -3092,6 +3465,12 @@

    Attributes

    + + + + + + @@ -3134,15 +3513,24 @@

    Classes

    - + + + + - + + + + + + +

    Accumulator

    Defines how an AggregateUDF accumulates values.

    AggregateUDF

    Class for performing scalar user-defined functions (UDF).

    Catalog

    DataFusion data catalog.

    SQLOptions

    Options to be used when performing SQL queries.

    SessionConfig

    ScalarUDF

    Class for performing scalar user-defined functions (UDF).

    SessionConfig

    Session configuration options.

    Table

    Table

    A DataFusion table.

    TableFunction

    Class for performing user-defined table functions (UDTF).

    WindowFrame

    Defines a window frame for performing window operations.

    WindowUDF

    Class for performing window user-defined functions (UDF).
    @@ -3176,6 +3564,175 @@

    Functions

    Package Contents

    +
    +
    +class datafusion.Accumulator
    +

    Defines how an AggregateUDF accumulates values.

    +
    +
    +abstract evaluate() → pyarrow.Scalar
    +

    Return the resultant value.

    +

    While this function template expects a PyArrow Scalar value return type, +you can return any value that can be converted into a Scalar. This +includes basic Python data types such as integers and strings. In +addition to primitive types, we currently support PyArrow, nanoarrow, +and arro3 objects in addition to primitive data types. Other objects +that support the Arrow FFI standard will be given a “best attempt” at +conversion to scalar objects.

    +
    + +
    +
    +abstract merge(states: list[pyarrow.Array]) → None
    +

    Merge a set of states.

    +
    + +
    +
    +abstract state() → list[pyarrow.Scalar]
    +

    Return the current state.

    +

    While this function template expects PyArrow Scalar values return type, +you can return any value that can be converted into a Scalar. This +includes basic Python data types such as integers and strings. In +addition to primitive types, we currently support PyArrow, nanoarrow, +and arro3 objects in addition to primitive data types. Other objects +that support the Arrow FFI standard will be given a “best attempt” at +conversion to scalar objects.

    +
    + +
    +
    +abstract update(*values: pyarrow.Array) → None
    +

    Evaluate an array of values and update state.

    +
    + +
    + +
    +
    +class datafusion.AggregateUDF(name: str, accumulator: collections.abc.Callable[[], Accumulator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str)
    +
    +class datafusion.AggregateUDF(name: str, accumulator: AggregateUDFExportable, input_types: None = ..., return_type: None = ..., state_type: None = ..., volatility: None = ...)
    +

    Class for performing scalar user-defined functions (UDF).

    +

    Aggregate UDFs operate on a group of rows and return a single value. See +also ScalarUDF for operating on a row by row basis.

    +

    Instantiate a user-defined aggregate function (UDAF).

    +

    See udaf() for a convenience function and argument +descriptions.

    +
    +
    +__call__(*args: datafusion.expr.Expr) → datafusion.expr.Expr
    +

    Execute the UDAF.

    +

    This function is not typically called by an end user. These calls will +occur during the evaluation of the dataframe.

    +
    + +
    +
    +__repr__() → str
    +

    Print a string representation of the Aggregate UDF.

    +
    + +
    +
    +static from_pycapsule(func: AggregateUDFExportable | _typeshed.CapsuleType) → AggregateUDF
    +

    Create an Aggregate UDF from AggregateUDF PyCapsule object.

    +

    This function will instantiate a Aggregate UDF that uses a DataFusion +AggregateUDF that is exported via the FFI bindings.

    +
    + +
    +
    +static udaf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[Ellipsis, AggregateUDF]
    +
    +static udaf(accum: collections.abc.Callable[[], Accumulator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, state_type: list[pyarrow.DataType], volatility: Volatility | str, name: str | None = None) → AggregateUDF
    +
    +static udaf(accum: AggregateUDFExportable) → AggregateUDF
    +
    +static udaf(accum: _typeshed.CapsuleType) → AggregateUDF
    +

    Create a new User-Defined Aggregate Function (UDAF).

    +

    This class allows you to define an aggregate function that can be used in +data aggregation or window function calls.

    +
    +
    Usage:
      +

    • As a function: udaf(accum, input_types, return_type, state_type, volatility, name).

      • +

    • As a decorator: @udaf(input_types, return_type, state_type, volatility, name). +When using udaf as a decorator, do not pass accum explicitly.

      • +
    +
    +
    +

    Function example:

    +

    If your Accumulator can be instantiated with no arguments, you +can simply pass it’s type as accum. If you need to pass additional +arguments to it’s constructor, you can define a lambda or a factory method. +During runtime the Accumulator will be constructed for every +instance in which this UDAF is used. The following examples are all valid:

    +
    import pyarrow as pa
+import pyarrow.compute as pc
+
+class Summarize(Accumulator):
+    def __init__(self, bias: float = 0.0):
+        self._sum = pa.scalar(bias)
+
+    def state(self) -> list[pa.Scalar]:
+        return [self._sum]
+
+    def update(self, values: pa.Array) -> None:
+        self._sum = pa.scalar(self._sum.as_py() + pc.sum(values).as_py())
+
+    def merge(self, states: list[pa.Array]) -> None:
+        self._sum = pa.scalar(self._sum.as_py() + pc.sum(states[0]).as_py())
+
+    def evaluate(self) -> pa.Scalar:
+        return self._sum
+
+def sum_bias_10() -> Summarize:
+    return Summarize(10.0)
+
+udaf1 = udaf(Summarize, pa.float64(), pa.float64(), [pa.float64()],
+    "immutable")
+udaf2 = udaf(sum_bias_10, pa.float64(), pa.float64(), [pa.float64()],
+    "immutable")
+udaf3 = udaf(lambda: Summarize(20.0), pa.float64(), pa.float64(),
+    [pa.float64()], "immutable")
+
    +
    +

    Decorator example::

    +
    @udaf(pa.float64(), pa.float64(), [pa.float64()], "immutable")
+def udf4() -> Summarize:
+    return Summarize(10.0)
+
    +
    +
    +
    Parameters:
    +
      +

    • accum – The accumulator python function. Only needed when calling as a +function. Skip this argument when using udaf as a decorator. +If you have a Rust backed AggregateUDF within a PyCapsule, you can +pass this parameter and ignore the rest. They will be determined +directly from the underlying function. See the online documentation +for more information.

      • +

    • input_types – The data types of the arguments to accum.

      • +

    • return_type – The data type of the return value.

      • +

    • state_type – The data types of the intermediate accumulation.

      • +

    • volatility – See Volatility for allowed values.

      • +

    • name – A descriptive name for the function.

      • +
    +
    +
    Returns:
    +

    A user-defined aggregate function, which can be used in either data +aggregation or window function calls.

    +
    +
    +
    + +
    +
    +_udaf
    +
    + +
    +
    class datafusion.Catalog(catalog: datafusion._internal.catalog.RawCatalog)
    @@ -4396,7 +4953,7 @@

    Returns:
    -class datafusion.InsertOp(*args, **kwds)
    +class datafusion.InsertOp

    Bases: enum.Enum

    Insert operation mode.

    These modes are used by the table writing feature to define how record @@ -4434,6 +4991,12 @@

    Returns:A LogicalPlan can be created by the SQL query planner, the DataFrame API, or programmatically (for example custom query languages).

    This constructor should not be called by the end user.

    +
    +
    +__eq__(other: LogicalPlan) → bool
    +

    Test equality.

    +
    +
    __repr__() → str
    @@ -5038,6 +5601,99 @@

    Returns:

    +
    +
    +class datafusion.ScalarUDF(name: str, func: collections.abc.Callable[Ellipsis, _R], input_fields: list[pyarrow.Field], return_field: _R, volatility: Volatility | str)
    +

    Class for performing scalar user-defined functions (UDF).

    +

    Scalar UDFs operate on a row by row basis. See also AggregateUDF for +operating on a group of rows.

    +

    Instantiate a scalar user-defined function (UDF).

    +

    See helper method udf() for argument details.

    +
    +
    +__call__(*args: datafusion.expr.Expr) → datafusion.expr.Expr
    +

    Execute the UDF.

    +

    This function is not typically called by an end user. These calls will +occur during the evaluation of the dataframe.

    +
    + +
    +
    +__repr__() → str
    +

    Print a string representation of the Scalar UDF.

    +
    + +
    +
    +static from_pycapsule(func: ScalarUDFExportable) → ScalarUDF
    +

    Create a Scalar UDF from ScalarUDF PyCapsule object.

    +

    This function will instantiate a Scalar UDF that uses a DataFusion +ScalarUDF that is exported via the FFI bindings.

    +
    + +
    +
    +static udf(input_fields: collections.abc.Sequence[pyarrow.DataType | pyarrow.Field] | pyarrow.DataType | pyarrow.Field, return_field: pyarrow.DataType | pyarrow.Field, volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[Ellipsis, ScalarUDF]
    +
    +static udf(func: collections.abc.Callable[Ellipsis, _R], input_fields: collections.abc.Sequence[pyarrow.DataType | pyarrow.Field] | pyarrow.DataType | pyarrow.Field, return_field: pyarrow.DataType | pyarrow.Field, volatility: Volatility | str, name: str | None = None) → ScalarUDF
    +
    +static udf(func: ScalarUDFExportable) → ScalarUDF
    +

    Create a new User-Defined Function (UDF).

    +

    This class can be used both as either a function or a decorator.

    +
    +
    Usage:
      +

    • As a function: udf(func, input_fields, return_field, volatility, name).

      • +

    • As a decorator: @udf(input_fields, return_field, volatility, name). +When used a decorator, do not pass func explicitly.

      • +
    +
    +
    +

    In lieu of passing a PyArrow Field, you can pass a DataType for simplicity. +When you do so, it will be assumed that the nullability of the inputs and +output are True and that they have no metadata.

    +
    +
    Parameters:
    +
      +

    • func (Callable, optional) – Only needed when calling as a function. +Skip this argument when using udf as a decorator. If you have a Rust +backed ScalarUDF within a PyCapsule, you can pass this parameter +and ignore the rest. They will be determined directly from the +underlying function. See the online documentation for more information.

      • +

    • input_fields (list[pa.Field | pa.DataType]) – The data types or Fields +of the arguments to func. This list must be of the same length +as the number of arguments.

      • +

    • return_field (_R) – The field of the return value from the function.

      • +

    • volatility (Volatility | str) – See Volatility for allowed values.

      • +

    • name (Optional[str]) – A descriptive name for the function.

      • +
    +
    +
    Returns:
    +

    A user-defined function that can be used in SQL expressions, +data aggregation, or window function calls.

    +
    +
    +

    Example: Using udf as a function:

    +
    def double_func(x):
+    return x * 2
+double_udf = udf(double_func, [pa.int32()], pa.int32(),
+"volatile", "double_it")
+
    +
    +

    Example: Using udf as a decorator:

    +
    @udf([pa.int32()], pa.int32(), "volatile", "double_it")
+def double_udf(x):
+    return x * 2
+
    +
    +
    + +
    +
    +_udf
    +
    + +
    +
    class datafusion.SessionConfig(config_options: dict[str, str] | None = None)
    @@ -5296,6 +5952,54 @@

    Returns:

    +
    +
    +class datafusion.TableFunction(name: str, func: collections.abc.Callable[[], any], ctx: datafusion.SessionContext | None = None)
    +

    Class for performing user-defined table functions (UDTF).

    +

    Table functions generate new table providers based on the +input expressions.

    +

    Instantiate a user-defined table function (UDTF).

    +

    See udtf() for a convenience function and argument +descriptions.

    +
    +
    +__call__(*args: datafusion.expr.Expr) → Any
    +

    Execute the UDTF and return a table provider.

    +
    + +
    +
    +__repr__() → str
    +

    User printable representation.

    +
    + +
    +
    +static _create_table_udf(func: collections.abc.Callable[Ellipsis, Any], name: str) → TableFunction
    +

    Create a TableFunction instance from function arguments.

    +
    + +
    +
    +static _create_table_udf_decorator(name: str | None = None) → collections.abc.Callable[[collections.abc.Callable[[], WindowEvaluator]], collections.abc.Callable[Ellipsis, datafusion.expr.Expr]]
    +

    Create a decorator for a WindowUDF.

    +
    + +
    +
    +static udtf(name: str) → collections.abc.Callable[Ellipsis, Any]
    +
    +static udtf(func: collections.abc.Callable[[], Any], name: str) → TableFunction
    +

    Create a new User-Defined Table Function (UDTF).

    +
    + +
    +
    +_udtf
    +
    + +
    +
    class datafusion.WindowFrame(units: str, start_bound: Any | None, end_bound: Any | None)
    @@ -5345,6 +6049,128 @@

    Returns:

    +
    +
    +class datafusion.WindowUDF(name: str, func: collections.abc.Callable[[], WindowEvaluator], input_types: list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str)
    +

    Class for performing window user-defined functions (UDF).

    +

    Window UDFs operate on a partition of rows. See +also ScalarUDF for operating on a row by row basis.

    +

    Instantiate a user-defined window function (UDWF).

    +

    See udwf() for a convenience function and argument +descriptions.

    +
    +
    +__call__(*args: datafusion.expr.Expr) → datafusion.expr.Expr
    +

    Execute the UDWF.

    +

    This function is not typically called by an end user. These calls will +occur during the evaluation of the dataframe.

    +
    + +
    +
    +__repr__() → str
    +

    Print a string representation of the Window UDF.

    +
    + +
    +
    +static _create_window_udf(func: collections.abc.Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
    +

    Create a WindowUDF instance from function arguments.

    +
    + +
    +
    +static _create_window_udf_decorator(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[[collections.abc.Callable[[], WindowEvaluator]], collections.abc.Callable[Ellipsis, datafusion.expr.Expr]]
    +

    Create a decorator for a WindowUDF.

    +
    + +
    +
    +static _get_default_name(func: collections.abc.Callable) → str
    +

    Get the default name for a function based on its attributes.

    +
    + +
    +
    +static _normalize_input_types(input_types: pyarrow.DataType | list[pyarrow.DataType]) → list[pyarrow.DataType]
    +

    Convert a single DataType to a list if needed.

    +
    + +
    +
    +static from_pycapsule(func: WindowUDFExportable) → WindowUDF
    +

    Create a Window UDF from WindowUDF PyCapsule object.

    +

    This function will instantiate a Window UDF that uses a DataFusion +WindowUDF that is exported via the FFI bindings.

    +
    + +
    +
    +static udwf(input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → collections.abc.Callable[Ellipsis, WindowUDF]
    +
    +static udwf(func: collections.abc.Callable[[], WindowEvaluator], input_types: pyarrow.DataType | list[pyarrow.DataType], return_type: pyarrow.DataType, volatility: Volatility | str, name: str | None = None) → WindowUDF
    +

    Create a new User-Defined Window Function (UDWF).

    +

    This class can be used both as either a function or a decorator.

    +
    +
    Usage:
      +

    • As a function: udwf(func, input_types, return_type, volatility, name).

      • +

    • As a decorator: @udwf(input_types, return_type, volatility, name). +When using udwf as a decorator, do not pass func explicitly.

      • +
    +
    +
    +

    Function example:

    +
    import pyarrow as pa
+
+class BiasedNumbers(WindowEvaluator):
+    def __init__(self, start: int = 0) -> None:
+        self.start = start
+
+    def evaluate_all(self, values: list[pa.Array],
+        num_rows: int) -> pa.Array:
+        return pa.array([self.start + i for i in range(num_rows)])
+
+def bias_10() -> BiasedNumbers:
+    return BiasedNumbers(10)
+
+udwf1 = udwf(BiasedNumbers, pa.int64(), pa.int64(), "immutable")
+udwf2 = udwf(bias_10, pa.int64(), pa.int64(), "immutable")
+udwf3 = udwf(lambda: BiasedNumbers(20), pa.int64(), pa.int64(), "immutable")
+
    +
    +

    Decorator example:

    +
    @udwf(pa.int64(), pa.int64(), "immutable")
+def biased_numbers() -> BiasedNumbers:
+    return BiasedNumbers(10)
+
    +
    +
    +
    Parameters:
    +
      +

    • func – Only needed when calling as a function. Skip this argument when +using udwf as a decorator. If you have a Rust backed WindowUDF +within a PyCapsule, you can pass this parameter and ignore the rest. +They will be determined directly from the underlying function. See +the online documentation for more information.

      • +

    • input_types – The data types of the arguments.

      • +

    • return_type – The data type of the return value.

      • +

    • volatility – See Volatility for allowed values.

      • +

    • name – A descriptive name for the function.

      • +
    +
    +
    Returns:
    +

    A user-defined window function that can be used in window function calls.

    +
    +
    +
    + +
    +
    +_udwf
    +
    + +
    +
    datafusion.configure_formatter(**kwargs: Any) → None
    @@ -5511,6 +6337,26 @@

    Returns:datafusion.column: Col

    +
    +
    +datafusion.udaf
    +
    + +
    +
    +datafusion.udf
    +
    + +
    +
    +datafusion.udtf
    +
    + +
    +
    +datafusion.udwf
    +
    + diff --git a/autoapi/datafusion/plan/index.html b/autoapi/datafusion/plan/index.html index da7b1c25d..07cc3fdf6 100644 --- a/autoapi/datafusion/plan/index.html +++ b/autoapi/datafusion/plan/index.html @@ -519,6 +519,15 @@

    +
    __repr__() → str
    diff --git a/autoapi/datafusion/substrait/index.html b/autoapi/datafusion/substrait/index.html index 748f75d20..52aeeca59 100644 --- a/autoapi/datafusion/substrait/index.html +++ b/autoapi/datafusion/substrait/index.html @@ -465,6 +465,24 @@

    • +
  • + + + + Plan.from_json() + + + +
    • +
  • + + + + Plan.to_json() + + + +
  • @@ -643,6 +661,31 @@

    Module Contents +
    +static from_json(json: str) → Plan
    +

    Parse a plan from a JSON string representation.

    +
    +
    Parameters:
    +

    json – JSON representation of a Substrait plan.

    +
    +
    Returns:
    +

    Plan object representing the Substrait plan.

    +
    +
    +
    + +
    +
    +to_json() → str
    +

    Get the JSON representation of the Substrait plan.

    +
    +
    Returns:
    +

    A JSON representation of the Substrait plan.

    +
    +
    +
    +
    plan_internal
    diff --git a/autoapi/datafusion/user_defined/index.html b/autoapi/datafusion/user_defined/index.html index 0686e59c0..4dbf00e96 100644 --- a/autoapi/datafusion/user_defined/index.html +++ b/autoapi/datafusion/user_defined/index.html @@ -1134,6 +1134,13 @@

    Module Contents abstract evaluate() → pyarrow.Scalar

    Return the resultant value.

    +

    While this function template expects a PyArrow Scalar value return type, +you can return any value that can be converted into a Scalar. This +includes basic Python data types such as integers and strings. In +addition to primitive types, we currently support PyArrow, nanoarrow, +and arro3 objects in addition to primitive data types. Other objects +that support the Arrow FFI standard will be given a “best attempt” at +conversion to scalar objects.

    @@ -1146,6 +1153,13 @@

    Module Contents abstract state() → list[pyarrow.Scalar]

    Return the current state.

    +

    While this function template expects PyArrow Scalar values return type, +you can return any value that can be converted into a Scalar. This +includes basic Python data types such as integers and strings. In +addition to primitive types, we currently support PyArrow, nanoarrow, +and arro3 objects in addition to primitive data types. Other objects +that support the Arrow FFI standard will be given a “best attempt” at +conversion to scalar objects.

    @@ -1448,7 +1462,7 @@

    Module Contents
    -class datafusion.user_defined.Volatility(*args, **kwds)
    +class datafusion.user_defined.Volatility

    Bases: enum.Enum

    Defines how stable or volatile a function is.

    When setting the volatility of a function, you can either pass this diff --git a/genindex.html b/genindex.html index 7390ebec7..277d439ea 100644 --- a/genindex.html +++ b/genindex.html @@ -490,9 +490,15 @@

    _

  • (datafusion.dataframe.DataFrame method)

    • -
  • __call__() (datafusion.dataframe_formatter.CellFormatter method) +
  • __call__() (datafusion.AggregateUDF method)
  • __datafusion_aggregate_udf__() (datafusion.user_defined.AggregateUDFExportable method) -
    • -
  • __datafusion_catalog_provider__() (datafusion.context.CatalogProviderExportable method)
  • __datafusion_logical_extension_codec__() (datafusion.context.SessionContext method)
    • @@ -520,6 +526,10 @@

    _

  • __ge__() (datafusion.Expr method) @@ -610,10 +620,14 @@

    _

  • (datafusion.expr.Expr attribute)
    • -
  • __repr__() (datafusion.Catalog method) +
  • __repr__() (datafusion.AggregateUDF method)
    		• + +
  • from_json() (datafusion.substrait.Plan static method) +
  • from_pandas() (datafusion.context.SessionContext method)
  • from_polars() (datafusion.context.SessionContext method) @@ -1983,12 +2071,18 @@

    F

  • (datafusion.plan.LogicalPlan static method)
    • -
  • from_pycapsule() (datafusion.user_defined.AggregateUDF static method) +
  • from_pycapsule() (datafusion.AggregateUDF static method)
  • from_pydict() (datafusion.context.SessionContext method) @@ -2481,14 +2575,20 @@

    M

  • memory_schema() (datafusion.catalog.Schema static method)
    		• +
  • to_json() (datafusion.substrait.Plan method) +
  • to_pandas() (datafusion.dataframe.DataFrame method)
  • to_polars() (datafusion.dataframe.DataFrame method)
    • +     		-
  • __repr__() (datafusion.AggregateUDF method) +
  • __repr__() (datafusion.Catalog method)
    		• -
  • from_pycapsule() (datafusion.AggregateUDF static method) +
  • from_pycapsule() (datafusion.user_defined.AggregateUDF static method)
  • from_pydict() (datafusion.context.SessionContext method) @@ -2583,12 +2511,8 @@

    M

    		•  -
  • __repr__() (datafusion.Catalog method) +
  • __repr__() (datafusion.AggregateUDF method)
    		• -
  • from_pycapsule() (datafusion.user_defined.AggregateUDF static method) +
  • from_pycapsule() (datafusion.AggregateUDF static method)
  • from_pydict() (datafusion.context.SessionContext method) @@ -2511,8 +2583,12 @@

    M

    		•
    • to_pyarrow() (datafusion.record_batch.RecordBatch method)
        @@ -3442,22 +3530,56 @@

        T

        U

        + -
        • Unnest (in module datafusion.expr)
        • unnest_columns() (datafusion.dataframe.DataFrame method) @@ -3478,8 +3598,12 @@

          U

        • unparser (datafusion.unparser.Unparser attribute)
          • -
        • update() (datafusion.user_defined.Accumulator method) +
        • update() (datafusion.Accumulator method) + +
        • upper() (datafusion.Expr method)
            @@ -3562,8 +3686,12 @@

            W

        • WindowFrameBound (class in datafusion.expr)
          • -
        • WindowUDF (class in datafusion.user_defined) +
        • WindowUDF (class in datafusion) + +
        • WindowUDFExportable (class in datafusion.user_defined)
        • with_allow_ddl() (datafusion.context.SQLOptions method) diff --git a/objects.inv b/objects.inv index 905cdeae27c2c43f318848526a690f53241e069e..c8c4788a3c3533285d2ef8d92a40ef86b9b56333 100644 GIT binary patch delta 9384 zcmV;ZBv;#^NQp|2hks3X+c>g@_x=?=XYSVO>GbrRduHc2PLF%siN{X5@63h=A|VM0 z2rvLCOZoK|A0$P}k_Zx2a&Hn@BA*uo@lgN@g^ZMBQE4W{WwHH7F0+c$%fDWds+6Q) zKVqP zjFu~z#n5u9mOv<7f~Be|vN+aqsp!%mKEHcEJ<~goS(2oL^CW>ulffxkC^%e|k%eWE zvQ%tdnY@d^EtJfYVw;je+j0++#wLl=P&eiym&?g7v%Vi7;~P@COVQ+9Z&>!LIngve zRT(uo&U8stqJPsB%}G2mr@2(yr1QLSJVA1*<1ygR3Cl@hA5*U%Dak$-rTI%wFZVsn zER}gqMHyFU`^b!PmNWArAfZ&7#)m=@7mU-yJbt05w!bIk7D0e+N-7$&0hFwzDif(P z*nD0Qovh5?uv9^xITKVTOeEG?@$~?VUYU;A)PA~wqaxcFhSa(PZkvw0b$& zm`q4bi2%)9(+`=#RuEM(`-Q179F|X2&O~DjgHff)72yjpL~}bURV7S^N3%r9XV46I zX5}jBG{Ydtb*0_Zwt5c)v-8;~s950r|aV8IIdF%y7tP zOYbQ2aDU?rr*f=$22|)Z(16?*E$TG(yZ2A++p}MfzTbR&uZ(T}hcaztta*KqHcJ$F zPM+;IiQEZH?m^ylMu(G9dAp%$Wz+G%iGZO145asXHqVMWeUr1Q&rDa0XNn4_G-gbj z6mEfWiM>9?80b^|KM@p)Fc5# 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false]], "plan_internal (datafusion.substrait.plan attribute)": [[16, "datafusion.substrait.Plan.plan_internal", false]], "plan_to_sql() (datafusion.unparser.unparser method)": [[17, "datafusion.unparser.Unparser.plan_to_sql", false]], "postgres() (datafusion.unparser.dialect static method)": [[17, "datafusion.unparser.Dialect.postgres", false]], "pow() (in module datafusion.functions)": [[5, "datafusion.functions.pow", false]], "power() (in module datafusion.functions)": [[5, "datafusion.functions.power", false]], "prepare (in module datafusion.expr)": [[4, "datafusion.expr.Prepare", false]], "producer (class in datafusion.substrait)": [[16, "datafusion.substrait.Producer", false]], "projection (in module datafusion.expr)": [[4, "datafusion.expr.Projection", false]], "python_value() (datafusion.expr method)": [[7, "datafusion.Expr.python_value", false]], "python_value() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.python_value", false]], "quote (datafusion.csvreadoptions 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"read_parquet() (in module datafusion)": [[7, "datafusion.read_parquet", false]], "read_parquet() (in module datafusion.io)": [[11, "datafusion.io.read_parquet", false]], "read_table() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.read_table", false]], "record_batch (datafusion.record_batch.recordbatch attribute)": [[15, "datafusion.record_batch.RecordBatch.record_batch", false]], "record_batch (datafusion.recordbatch attribute)": [[7, "datafusion.RecordBatch.record_batch", false]], "recordbatch (class in datafusion)": [[7, "datafusion.RecordBatch", false]], "recordbatch (class in datafusion.record_batch)": [[15, "datafusion.record_batch.RecordBatch", false]], "recordbatchstream (class in datafusion)": [[7, "datafusion.RecordBatchStream", false]], "recordbatchstream (class in datafusion.record_batch)": [[15, "datafusion.record_batch.RecordBatchStream", false]], "recursivequery (in module datafusion.expr)": [[4, "datafusion.expr.RecursiveQuery", false]], "regexp_count() (in module datafusion.functions)": [[5, "datafusion.functions.regexp_count", false]], "regexp_instr() (in module datafusion.functions)": [[5, "datafusion.functions.regexp_instr", false]], "regexp_like() (in module datafusion.functions)": [[5, "datafusion.functions.regexp_like", false]], "regexp_match() (in module datafusion.functions)": [[5, "datafusion.functions.regexp_match", false]], "regexp_replace() (in module datafusion.functions)": [[5, "datafusion.functions.regexp_replace", false]], "register_avro() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_avro", false]], "register_catalog() (datafusion.catalog.cataloglist method)": [[0, "datafusion.catalog.CatalogList.register_catalog", false]], "register_catalog() (datafusion.catalog.catalogproviderlist method)": [[0, "datafusion.catalog.CatalogProviderList.register_catalog", false]], "register_catalog_provider() (datafusion.context.sessioncontext method)": [[1, 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method)": [[1, "datafusion.context.SessionContext.register_object_store", false]], "register_parquet() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_parquet", false]], "register_record_batches() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.register_record_batches", false]], "register_schema() (datafusion.catalog method)": [[7, "datafusion.Catalog.register_schema", false]], "register_schema() (datafusion.catalog.catalog method)": [[0, "datafusion.catalog.Catalog.register_schema", false]], "register_schema() (datafusion.catalog.catalogprovider method)": [[0, "datafusion.catalog.CatalogProvider.register_schema", false]], "register_table() (datafusion.catalog.schema method)": [[0, "datafusion.catalog.Schema.register_table", false]], "register_table() (datafusion.catalog.schemaprovider method)": [[0, "datafusion.catalog.SchemaProvider.register_table", false]], "register_table() 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"datafusion.expr.ScalarVariable", false]], "schema (class in datafusion.catalog)": [[0, "datafusion.catalog.Schema", false]], "schema (datafusion.catalog.table property)": [[0, "datafusion.catalog.Table.schema", false]], "schema (datafusion.csvreadoptions attribute)": [[7, "datafusion.CsvReadOptions.schema", false]], "schema (datafusion.options.csvreadoptions attribute)": [[13, "datafusion.options.CsvReadOptions.schema", false]], "schema (datafusion.table property)": [[7, "datafusion.Table.schema", false]], "schema() (datafusion.catalog method)": [[7, "datafusion.Catalog.schema", false]], "schema() (datafusion.catalog.catalog method)": [[0, "datafusion.catalog.Catalog.schema", false]], "schema() (datafusion.catalog.catalogprovider method)": [[0, "datafusion.catalog.CatalogProvider.schema", false]], "schema() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.schema", false]], "schema_infer_max_records (datafusion.csvreadoptions attribute)": [[7, "datafusion.CsvReadOptions.schema_infer_max_records", false]], "schema_infer_max_records (datafusion.options.csvreadoptions attribute)": [[13, "datafusion.options.CsvReadOptions.schema_infer_max_records", false]], "schema_name() (datafusion.expr method)": [[7, "datafusion.Expr.schema_name", false]], "schema_name() (datafusion.expr.expr method)": [[4, "datafusion.expr.Expr.schema_name", false]], "schema_names() (datafusion.catalog method)": [[7, "datafusion.Catalog.schema_names", false]], "schema_names() (datafusion.catalog.catalog method)": [[0, "datafusion.catalog.Catalog.schema_names", false]], "schema_names() (datafusion.catalog.catalogprovider method)": [[0, "datafusion.catalog.CatalogProvider.schema_names", false]], "schemaprovider (class in datafusion.catalog)": [[0, "datafusion.catalog.SchemaProvider", false]], "select() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.select", false]], "select_columns() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.select_columns", false]], "select_exprs() (datafusion.dataframe.dataframe method)": [[2, "datafusion.dataframe.DataFrame.select_exprs", false]], "serde (class in datafusion.substrait)": [[16, "datafusion.substrait.Serde", false]], "serialize() (datafusion.substrait.serde static method)": [[16, "datafusion.substrait.Serde.serialize", false]], "serialize_bytes() (datafusion.substrait.serde static method)": [[16, "datafusion.substrait.Serde.serialize_bytes", false]], "serialize_to_plan() (datafusion.substrait.serde static method)": [[16, "datafusion.substrait.Serde.serialize_to_plan", false]], "session_id() (datafusion.context.sessioncontext method)": [[1, "datafusion.context.SessionContext.session_id", false]], "sessionconfig (class in datafusion)": [[7, "datafusion.SessionConfig", false]], "sessionconfig (class in datafusion.context)": [[1, "datafusion.context.SessionConfig", false]], "sessioncontext (class in datafusion.context)": [[1, 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b/user-guide/common-operations/aggregations.html @@ -620,15 +620,15 @@

          Distinct +----------+--------------------------------------------------+ | Type 1 | Type 2 List | +----------+--------------------------------------------------+ -| Bug | [, Grass, Flying, Poison] | -| Poison | [Ground, , Flying] | -| Electric | [, Flying, Steel] | +| Bug | [Flying, Poison, , Grass] | +| Poison | [Flying, , Ground] | +| Electric | [Flying, , Steel] | | Fairy | [] | -| Normal | [Flying, , Fairy] | +| Normal | [Fairy, , Flying] | | Ice | [Flying, Psychic] | -| Grass | [Psychic, , Poison] | -| Fire | [Dragon, , Flying] | -| Water | [Ice, Psychic, , Flying, Dark, Poison, Fighting] | +| Grass | [, Poison, Psychic] | +| Fire | [, Dragon, Flying] | +| Water | [Dark, Flying, Psychic, Poison, Ice, Fighting, ] | | Ground | [Rock, ] | +----------+--------------------------------------------------+ Data truncated. @@ -644,14 +644,14 @@

          Distinct +----------+------------------------------------------------+ | Type 1 | Type 2 List | +----------+------------------------------------------------+ -| Bug | [Poison, Flying, Grass] | -| Poison | [Ground, Flying] | -| Electric | [Flying, Steel] | -| Normal | [Fairy, Flying] | -| Ice | [Flying, Psychic] | +| Bug | [Flying, Grass, Poison] | +| Poison | [Flying, Ground] | +| Electric | [Steel, Flying] | +| Normal | [Flying, Fairy] | +| Ice | [Psychic, Flying] | | Grass | [Poison, Psychic] | -| Fire | [Dragon, Flying] | -| Water | [Fighting, Poison, Dark, Flying, Psychic, Ice] | +| Fire | [Flying, Dragon] | +| Water | [Psychic, Flying, Poison, Ice, Dark, Fighting] | | Rock | [Ground, Water, Flying] | | Ghost | [Poison] | +----------+------------------------------------------------+ @@ -663,15 +663,15 @@

          Distinct +----------+------------------------------------------------+ | Type 1 | Type 2 List | +----------+------------------------------------------------+ -| Bug | [Grass, Poison, Flying] | +| Bug | [Flying, Grass, Poison] | | Poison | [Ground, Flying] | -| Electric | [Flying, Steel] | +| Electric | [Steel, Flying] | | Fairy | | -| Normal | [Fairy, Flying] | +| Normal | [Flying, Fairy] | | Ice | [Flying, Psychic] | | Grass | [Poison, Psychic] | -| Fire | [Flying, Dragon] | -| Water | [Poison, Dark, Fighting, Ice, Psychic, Flying] | +| Fire | [Dragon, Flying] | +| Water | [Fighting, Psychic, Ice, Flying, Poison, Dark] | | Ground | [Rock] | +----------+------------------------------------------------+ Data truncated. diff --git a/user-guide/common-operations/basic-info.html b/user-guide/common-operations/basic-info.html index a8eb1c08b..7ae87351f 100644 --- a/user-guide/common-operations/basic-info.html +++ b/user-guide/common-operations/basic-info.html @@ -456,11 +456,11 @@

          Basic Operations+-----+---------+--------+--------+ | nrs | names | random | groups | +-----+---------+--------+--------+ -| 1 | python | 628 | A | -| 2 | ruby | 89 | A | -| 3 | java | 789 | B | -| 4 | haskell | 911 | C | -| 5 | go | 878 | B | +| 1 | python | 23 | A | +| 2 | ruby | 939 | A | +| 3 | java | 615 | B | +| 4 | haskell | 887 | C | +| 5 | go | 382 | B | +-----+---------+--------+--------+ @@ -471,8 +471,8 @@

          Basic Operations+-----+--------+--------+--------+ | nrs | names | random | groups | +-----+--------+--------+--------+ -| 1 | python | 628 | A | -| 2 | ruby | 89 | A | +| 1 | python | 23 | A | +| 2 | ruby | 939 | A | +-----+--------+--------+--------+ @@ -490,11 +490,11 @@

          Basic Operations
          In [8]: df.to_pandas()
 Out[8]: 
    nrs    names  random groups
-0    1   python     628      A
-1    2     ruby      89      A
-2    3     java     789      B
-3    4  haskell     911      C
-4    5       go     878      B
+0    1   python      23      A
+1    2     ruby     939      A
+2    3     java     615      B
+3    4  haskell     887      C
+4    5       go     382      B

          describe() shows a quick statistic summary of your data:

          @@ -506,11 +506,11 @@

          Basic Operations+------------+--------------------+-------+-------------------+--------+ | count | 5.0 | 5 | 5.0 | 5 | | null_count | 0.0 | 0 | 0.0 | 0 | -| mean | 3.0 | null | 659.0 | null | -| std | 1.5811388300841898 | null | 336.9814534955893 | null | -| min | 1.0 | go | 89.0 | A | -| max | 5.0 | ruby | 911.0 | C | -| median | 3.0 | null | 789.0 | null | +| mean | 3.0 | null | 569.2 | null | +| std | 1.5811388300841898 | null | 378.5580536720887 | null | +| min | 1.0 | go | 23.0 | A | +| max | 5.0 | ruby | 939.0 | C | +| median | 3.0 | null | 615.0 | null | +------------+--------------------+-------+-------------------+--------+ diff --git a/user-guide/common-operations/functions.html b/user-guide/common-operations/functions.html index b4e4a5c3a..1afdcb7ef 100644 --- a/user-guide/common-operations/functions.html +++ b/user-guide/common-operations/functions.html @@ -566,16 +566,16 @@

          Temporal +-------------------------------+ | now() | +-------------------------------+ -| 2026-02-23T12:53:06.752343449 | -| 2026-02-23T12:53:06.752343449 | -| 2026-02-23T12:53:06.752343449 | -| 2026-02-23T12:53:06.752343449 | -| 2026-02-23T12:53:06.752343449 | -| 2026-02-23T12:53:06.752343449 | -| 2026-02-23T12:53:06.752343449 | -| 2026-02-23T12:53:06.752343449 | -| 2026-02-23T12:53:06.752343449 | -| 2026-02-23T12:53:06.752343449 | +| 2026-03-12T09:56:53.757149654 | +| 2026-03-12T09:56:53.757149654 | +| 2026-03-12T09:56:53.757149654 | +| 2026-03-12T09:56:53.757149654 | +| 2026-03-12T09:56:53.757149654 | +| 2026-03-12T09:56:53.757149654 | +| 2026-03-12T09:56:53.757149654 | +| 2026-03-12T09:56:53.757149654 | +| 2026-03-12T09:56:53.757149654 | +| 2026-03-12T09:56:53.757149654 | +-------------------------------+ Data truncated. diff --git a/user-guide/introduction.html b/user-guide/introduction.html index 439c369f0..00a760dde 100644 --- a/user-guide/introduction.html +++ b/user-guide/introduction.html @@ -457,7 +457,7 @@

          Installation
          In [1]: import datafusion
 
 In [2]: datafusion.__version__
-Out[2]: '52.0.0'
+Out[2]: '52.3.0'

          In this documentation we will also show some examples for how DataFusion integrates