diff --git a/.buildinfo b/.buildinfo new file mode 100644 index 00000000..dd96f92d --- /dev/null +++ b/.buildinfo @@ -0,0 +1,4 @@ +# Sphinx build info version 1 +# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. +config: b68fb79aa115891308404ffb3376dfbf +tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/adis_tools/src/adis_tools/__init__.py b/.nojekyll similarity index 100% rename from adis_tools/src/adis_tools/__init__.py rename to .nojekyll diff --git a/README.html b/README.html new file mode 100644 index 00000000..8d509dc2 --- /dev/null +++ b/README.html @@ -0,0 +1,661 @@ + + + + + + + + + + + Python Workflow Definition — Python Workflow Definition + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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Python Workflow Definition

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+

Python Workflow Definition#

+

Pipeline +codecov +Binder +DOI

+
+

Definition#

+

In the Python Workflow Definition (PWD) each node represents a Python function, with the edges defining the connection +between input and output of the different Python functions.

+

Published in: J. Janssen, J. George, J. Geiger, M. Bercx, X. Wang, C. Ertural, J. Schaarschmidt, A.M. Ganose, G. Pizzi, T. Hickel and J. Neugebauer. A python workflow definition for computational materials design. Digital Discovery, 2025

+
+
+

Format#

+

Each workflow consists of three files, a Python module which defines the individual Pythons, a JSON file which defines +the connections between the different Python functions and a conda environment file to define the software dependencies. +The files are not intended to be human readable, but rather interact as a machine readable exchange format between the +different workflow engines to enable interoperability.

+
+
+

Installation#

+

The Python Workflow Definition can either be installed via pypi or via conda. For the pypi installation use:

+
pip install python-workflow-definition
+
+
+

For the conda installation via the conda-forge community channel use:

+
conda install conda-forge::python-workflow-definition
+
+
+
+
+

Examples#

+
+

Simple Example#

+

As a first example we define two Python functions which add multiple inputs:

+
def get_sum(x, y):
+    return x + y
+
+
+def get_prod_and_div(x: float, y: float) -> dict:
+    return {"prod": x * y, "div": x / y}
+
+
+

These two Python functions are combined in the following example workflow:

+
def combined_workflow(x=1, y=2):
+    tmp_dict = get_prod_and_div(x=x, y=y)
+    return get_sum(x=tmp_dict["prod"], y=tmp_dict["div"])
+
+
+

For the workflow representation of these Python functions the Python functions are stored in the example_workflows/arithmetic/workflow.py +Python module. The connection of the Python functions are stored in the example_workflows/arithmetic/workflow.json +JSON file:

+
{
+  "nodes": [
+    {"id": 0, "type": "function", "value": "workflow.get_prod_and_div"},
+    {"id": 1, "type": "function", "value": "workflow.get_sum"},
+    {"id": 2, "type": "input", "value": 1, "name": "x"},
+    {"id": 3, "type": "input", "value": 2, "name": "y"},
+    {"id": 4, "type": "output", "name": "result"}
+  ],
+  "edges": [
+    {"target": 0, "targetPort": "x", "source": 2, "sourcePort": null},
+    {"target": 0, "targetPort": "y", "source": 3, "sourcePort": null},
+    {"target": 1, "targetPort": "x", "source": 0, "sourcePort": "prod"},
+    {"target": 1, "targetPort": "y", "source": 0, "sourcePort": "div"},
+    {"target": 4, "targetPort": null, "source": 1, "sourcePort": null}
+  ]
+}
+
+
+

The abbreviations in the definition of the edges are:

+
    +

  • target - target node

    • +

  • targetPort - target port - for a node with multiple input parameters the target port specifies which input parameter to use.

    • +

  • source - source node

    • +

  • sourcePort - source port - for a node with multiple output parameters the source port specifies which output parameter to use.

    • +
+

As the workflow does not require any additional resources, as it is only using built-in functionality of the Python standard +library.

+

The corresponding Jupyter notebooks demonstrate this functionality:

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

Example

Explanation

example_workflows/arithmetic/aiida.ipynb

Define Workflow with aiida and execute it with jobflow and pyiron_base.

example_workflows/arithmetic/jobflow.ipynb

Define Workflow with jobflow and execute it with aiida and pyiron_base.

example_workflows/arithmetic/pyiron_base.ipynb

Define Workflow with pyiron_base and execute it with aiida and jobflow.

example_workflows/arithmetic/universal_workflow.ipynb

Execute workflow defined in the Python Workflow Definition with aiida, executorlib, jobflow, pyiron_base and pure Python.

+
+
+
+

Quantum Espresso Workflow#

+

The second workflow example is the calculation of an energy volume curve with Quantum Espresso. In the first step the +initial structure is relaxed, afterward it is strained and the total energy is calculated.

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

Example

Explanation

example_workflows/quantum_espresso/aiida.ipynb

Define Workflow with aiida and execute it with jobflow and pyiron_base.

example_workflows/quantum_espresso/jobflow.ipynb

Define Workflow with jobflow and execute it with aiida and pyiron_base.

example_workflows/quantum_espresso/pyiron_base.ipynb

Define Workflow with pyiron_base and execute it with aiida and jobflow.

example_workflows/quantum_espresso/universal_workflow.ipynb

Execute workflow defined in the Python Workflow Definition with aiida, executorlib, jobflow, pyiron_base and pure Python.

+
+
+
+

NFDI4Ing Scientific Workflow Requirements#

+

To demonstrate the compatibility of the Python Workflow Definition to file based workflows, the workflow benchmark developed as part of NFDI4Ing +is implemented for all three simulation codes based on a shared workflow definition.

+ +

Additional source files provided with the workflow benchmark:

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

Example

Explanation

example_workflows/nfdi/aiida.ipynb

Define Workflow with aiida and execute it with jobflow and pyiron_base.

example_workflows/nfdi/jobflow.ipynb

Define Workflow with jobflow and execute it with aiida and pyiron_base.

example_workflows/nfdi/pyiron_base.ipynb

Define Workflow with pyiron_base and execute it with aiida and jobflow.

example_workflows/nfdi/universal_workflow.ipynb

Execute workflow defined in the Python Workflow Definition with aiida, executorlib, jobflow, pyiron_base and pure Python.

+
+
+
+
+
+
+ + + + +
+ + + + + + + + +
+ + + + + + + +
+ + + +
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+
+ + + + + + + + \ No newline at end of file diff --git a/_downloads/074c18a527b229dcf1aceecb3ceb2862/workflow.json b/_downloads/074c18a527b229dcf1aceecb3ceb2862/workflow.json new file mode 100644 index 00000000..e653d594 --- /dev/null +++ b/_downloads/074c18a527b229dcf1aceecb3ceb2862/workflow.json @@ -0,0 +1,100 @@ +{ + "version": "0.1.0", + "nodes": [ + {"id": 0, "type": "function", "value": "workflow.get_bulk_structure"}, + {"id": 1, "type": "function", "value": "workflow.calculate_qe"}, + {"id": 2, "type": "function", "value": "workflow.generate_structures"}, + {"id": 3, "type": "function", "value": "workflow.calculate_qe"}, + {"id": 4, "type": "function", "value": "workflow.calculate_qe"}, + {"id": 5, "type": "function", "value": "workflow.calculate_qe"}, + {"id": 6, "type": "function", "value": "workflow.calculate_qe"}, + {"id": 7, "type": "function", "value": "workflow.calculate_qe"}, + {"id": 8, "type": "function", "value": "workflow.plot_energy_volume_curve"}, + {"id": 9, "type": "input", "value": "Al", "name": "element"}, + {"id": 10, "type": "input", "value": 4.05, "name": "a"}, + {"id": 11, "type": "input", "value": true, "name": "cubic"}, + {"id": 12, "type": "input", "value": "mini", "name": "working_directory_0"}, + {"id": 13, "type": "function", "value": "python_workflow_definition.shared.get_dict"}, + {"id": 14, "type": "input", "value": {"Al": "Al.pbe-n-kjpaw_psl.1.0.0.UPF"}, "name": "pseudopotentials"}, + {"id": 15, "type": "input", "value": [3, 3, 3], "name": "kpts"}, + {"id": 16, "type": "input", "value": "vc-relax", "name": "calculation_0"}, + {"id": 17, "type": "input", "value": 0.02, "name": "smearing"}, + {"id": 18, "type": "input", "value": [0.9, 0.95, 1.0, 1.05, 1.1], "name": "strain_lst"}, + {"id": 19, "type": "input", "value": "strain_0", "name": "working_directory_1"}, + {"id": 20, "type": "function", "value": "python_workflow_definition.shared.get_dict"}, + {"id": 21, "type": "input", "value": "scf", "name": "calculation_1"}, + {"id": 22, "type": "input", "value": "strain_1", "name": "working_directory_2"}, + {"id": 23, "type": "function", "value": "python_workflow_definition.shared.get_dict"}, + {"id": 24, "type": "input", "value": "strain_2", "name": "working_directory_3"}, + {"id": 25, "type": "function", "value": "python_workflow_definition.shared.get_dict"}, + {"id": 26, "type": "input", "value": "strain_3", "name": "working_directory_4"}, + {"id": 27, "type": "function", "value": "python_workflow_definition.shared.get_dict"}, + {"id": 28, "type": "input", "value": "strain_4", "name": "working_directory_5"}, + {"id": 29, "type": "function", "value": "python_workflow_definition.shared.get_dict"}, + {"id": 30, "type": "function", "value": "python_workflow_definition.shared.get_list"}, + {"id": 31, "type": "function", "value": "python_workflow_definition.shared.get_list"}, + {"id": 32, "type": "output", "name": "result"} + ], + "edges": [ + {"target": 0, "targetPort": "element", "source": 9, "sourcePort": null}, + {"target": 0, "targetPort": "a", "source": 10, "sourcePort": null}, + {"target": 0, "targetPort": "cubic", "source": 11, "sourcePort": null}, + {"target": 1, "targetPort": "working_directory", "source": 12, "sourcePort": null}, + {"target": 13, "targetPort": "structure", "source": 0, "sourcePort": null}, + {"target": 13, "targetPort": "pseudopotentials", "source": 14, "sourcePort": null}, + {"target": 13, "targetPort": "kpts", "source": 15, "sourcePort": null}, + {"target": 13, "targetPort": "calculation", "source": 16, "sourcePort": null}, + {"target": 13, "targetPort": "smearing", "source": 17, "sourcePort": null}, + {"target": 1, "targetPort": "input_dict", "source": 13, "sourcePort": null}, + {"target": 2, "targetPort": "structure", "source": 1, "sourcePort": "structure"}, + {"target": 2, "targetPort": "strain_lst", "source": 18, "sourcePort": null}, + {"target": 3, "targetPort": "working_directory", "source": 19, "sourcePort": null}, + {"target": 20, "targetPort": "structure", "source": 2, "sourcePort": "s_0"}, + {"target": 20, "targetPort": "pseudopotentials", "source": 14, "sourcePort": null}, + {"target": 20, "targetPort": "kpts", "source": 15, "sourcePort": null}, + {"target": 20, "targetPort": "calculation", "source": 21, "sourcePort": null}, + {"target": 20, "targetPort": "smearing", "source": 17, "sourcePort": null}, + {"target": 3, "targetPort": "input_dict", "source": 20, "sourcePort": null}, + {"target": 4, "targetPort": "working_directory", "source": 22, "sourcePort": null}, + {"target": 23, "targetPort": "structure", "source": 2, "sourcePort": "s_1"}, + {"target": 23, "targetPort": "pseudopotentials", "source": 14, "sourcePort": null}, + {"target": 23, "targetPort": "kpts", "source": 15, "sourcePort": null}, + {"target": 23, "targetPort": "calculation", "source": 21, "sourcePort": null}, + {"target": 23, "targetPort": "smearing", "source": 17, "sourcePort": null}, + {"target": 4, "targetPort": "input_dict", "source": 23, "sourcePort": null}, + {"target": 5, "targetPort": "working_directory", "source": 24, "sourcePort": null}, + {"target": 25, "targetPort": "structure", "source": 2, "sourcePort": "s_2"}, + {"target": 25, "targetPort": "pseudopotentials", "source": 14, "sourcePort": null}, + {"target": 25, "targetPort": "kpts", "source": 15, "sourcePort": null}, + {"target": 25, "targetPort": "calculation", "source": 21, "sourcePort": null}, + {"target": 25, "targetPort": "smearing", "source": 17, "sourcePort": null}, + {"target": 5, "targetPort": "input_dict", "source": 25, "sourcePort": null}, + {"target": 6, "targetPort": "working_directory", "source": 26, "sourcePort": null}, + {"target": 27, "targetPort": "structure", "source": 2, "sourcePort": "s_3"}, + {"target": 27, "targetPort": "pseudopotentials", "source": 14, "sourcePort": null}, + {"target": 27, "targetPort": "kpts", "source": 15, "sourcePort": null}, + {"target": 27, "targetPort": "calculation", "source": 21, "sourcePort": null}, + {"target": 27, "targetPort": "smearing", "source": 17, "sourcePort": null}, + {"target": 6, "targetPort": "input_dict", "source": 27, "sourcePort": null}, + {"target": 7, "targetPort": "working_directory", "source": 28, "sourcePort": null}, + {"target": 29, "targetPort": "structure", "source": 2, "sourcePort": "s_4"}, + {"target": 29, "targetPort": "pseudopotentials", "source": 14, "sourcePort": null}, + {"target": 29, "targetPort": "kpts", "source": 15, "sourcePort": null}, + {"target": 29, "targetPort": "calculation", "source": 21, "sourcePort": null}, + {"target": 29, "targetPort": "smearing", "source": 17, "sourcePort": null}, + {"target": 7, "targetPort": "input_dict", "source": 29, "sourcePort": null}, + {"target": 30, "targetPort": "0", "source": 3, "sourcePort": "volume"}, + {"target": 30, "targetPort": "1", "source": 4, "sourcePort": "volume"}, + {"target": 30, "targetPort": "2", "source": 5, "sourcePort": "volume"}, + {"target": 30, "targetPort": "3", "source": 6, "sourcePort": "volume"}, + {"target": 30, "targetPort": "4", "source": 7, "sourcePort": "volume"}, + {"target": 8, "targetPort": "volume_lst", "source": 30, "sourcePort": null}, + {"target": 31, "targetPort": "0", "source": 3, "sourcePort": "energy"}, + {"target": 31, "targetPort": "1", "source": 4, "sourcePort": "energy"}, + {"target": 31, "targetPort": "2", "source": 5, "sourcePort": "energy"}, + {"target": 31, "targetPort": "3", "source": 6, "sourcePort": "energy"}, + {"target": 31, "targetPort": "4", "source": 7, "sourcePort": "energy"}, + {"target": 8, "targetPort": "energy_lst", "source": 31, "sourcePort": null}, + {"target": 32, "targetPort": null, "source": 8, "sourcePort": null} + ] +} \ No newline at end of file diff --git a/quantum_espresso_workflow.py b/_downloads/0d09bdc32538ec374fdfcc8b206a84a1/workflow.py similarity index 63% rename from quantum_espresso_workflow.py rename to _downloads/0d09bdc32538ec374fdfcc8b206a84a1/workflow.py index f7c7359c..dcb6a1d4 100644 --- a/quantum_espresso_workflow.py +++ b/_downloads/0d09bdc32538ec374fdfcc8b206a84a1/workflow.py @@ -1,11 +1,13 @@ +import json import os import subprocess -from ase.atoms import Atoms from ase.build import bulk from ase.io import write -from adis_tools.parsers import parse_pw +from qe_xml_parser.parsers import parse_pw import matplotlib.pyplot as plt +from optimade.adapters.structures.ase import from_ase_atoms, get_ase_atoms +from optimade.models.structures import StructureResourceAttributes, StructureResource def write_input(input_dict, working_directory="."): @@ -13,7 +15,7 @@ def write_input(input_dict, working_directory="."): os.makedirs(working_directory, exist_ok=True) write( filename=filename, - images=Atoms(**input_dict["structure"]), + images=json_to_ase(atoms_json=input_dict["structure"]), Crystal=True, kpts=input_dict["kpts"], input_data={ @@ -30,7 +32,7 @@ def write_input(input_dict, working_directory="."): def collect_output(working_directory="."): output = parse_pw(os.path.join(working_directory, "pwscf.xml")) return { - "structure": output["ase_structure"].todict(), + "structure": ase_to_json(atoms=output["ase_structure"]), "energy": output["energy"], "volume": output["ase_structure"].get_volume(), } @@ -52,12 +54,12 @@ def calculate_qe(working_directory, input_dict): def generate_structures(structure, strain_lst): structure_lst = [] for strain in strain_lst: - structure_strain = Atoms(**structure) + structure_strain = json_to_ase(atoms_json=structure) structure_strain.set_cell( structure_strain.cell * strain ** (1 / 3), scale_atoms=True ) structure_lst.append(structure_strain) - return {str(i): s.todict() for i, s in enumerate(structure_lst)} + return {f"s_{i}": ase_to_json(atoms=s) for i, s in enumerate(structure_lst)} def plot_energy_volume_curve(volume_lst, energy_lst): @@ -67,9 +69,20 @@ def plot_energy_volume_curve(volume_lst, energy_lst): plt.savefig("evcurve.png") -def get_bulk_structure(name, a, cubic): - return bulk( - name=name, +def get_bulk_structure(element, a, cubic): + ase_atoms = bulk( + name=element, a=a, cubic=cubic, - ).todict() + ) + return ase_to_json(atoms=ase_atoms) + + +def ase_to_json(atoms): + struct_opt = from_ase_atoms(atoms=atoms) + return json.dumps(struct_opt.model_dump(mode="json")) + + +def json_to_ase(atoms_json): + structure_restore = StructureResourceAttributes.model_validate_json(atoms_json) + return get_ase_atoms(optimade_structure=StructureResource(id="ase", attributes=structure_restore)) diff --git a/_downloads/2b431daa5d8516cd4586feb00ce63187/preprocessing.yaml b/_downloads/2b431daa5d8516cd4586feb00ce63187/preprocessing.yaml new file mode 100644 index 00000000..d9a2660e --- /dev/null +++ b/_downloads/2b431daa5d8516cd4586feb00ce63187/preprocessing.yaml @@ -0,0 +1,5 @@ +channels: + - conda-forge +dependencies: + - gmsh=4.6.0=hd134328_0 + - meshio=5.0.5=pyhd8ed1ab_0 diff --git a/_downloads/331c5bde05983f9e76ce2cf65cfde073/paper.tex b/_downloads/331c5bde05983f9e76ce2cf65cfde073/paper.tex new file mode 100644 index 00000000..e8b0cfe3 --- /dev/null +++ b/_downloads/331c5bde05983f9e76ce2cf65cfde073/paper.tex @@ -0,0 +1,22 @@ +\documentclass[12pt]{article} +\usepackage{graphicx} +\usepackage{pgfplots} + +\input{macros} + +\title{An exemplary workflow} + +\begin{document} +\maketitle + +\begin{figure}[h] + \centering% + \begin{tikzpicture} + \begin{axis}[] + \addplot[color=red,smooth,thick] table[col sep=comma,header=true,x index=2,y index=0] {\plotDataPath}; + \end{axis} + \end{tikzpicture} + \caption{Solution of the poisson equation over the line $L = \{(x, y)\in\Omega = {(0, \domainSize{})}^2 | x = y\}$ using \numDofs{} DoFs in the finite element model.}% +\end{figure} + +\end{document} diff --git a/_downloads/4437283df7255c07a78686ad14ce4902/postprocessing.py b/_downloads/4437283df7255c07a78686ad14ce4902/postprocessing.py new file mode 100644 index 00000000..0ed43af1 --- /dev/null +++ b/_downloads/4437283df7255c07a78686ad14ce4902/postprocessing.py @@ -0,0 +1,54 @@ +""" +$ pvbatch postprocessing.py -h +""" + +import sys +import argparse +from paraview.simple import ( + PlotOverLine, + PVDReader, + SaveData, + UpdatePipeline, +) + + +def main(args): + pvd_file = args.pvd + source = PVDReader(registrationName="poisson.pvd", FileName=[pvd_file]) + source.PointArrays = [args.field] + UpdatePipeline() + + (xmin, xmax, ymin, ymax, zmin, zmax) = source.GetDataInformation().GetBounds() + # init the 'Line' selected for 'Source' + plotOverLine1 = PlotOverLine( + registrationName="PlotOverLine1", Input=source, Source="Line" + ) + plotOverLine1.Source.Point1 = [xmin, ymin, zmin] + plotOverLine1.Source.Point2 = [xmax, ymax, zmax] + UpdatePipeline() + + # save data + SaveData( + args.csv, + proxy=plotOverLine1, + ChooseArraysToWrite=1, + PointDataArrays=["arc_length", args.field, "vtkValidPointMask"], + ) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + prog=f"pvbatch {__file__}", + description="Plots the solution over a line and writes the data to file.", + usage="%(prog)s [options] pvd csv", + ) + parser.add_argument("pvd", type=str, help="The source pvd filepath.") + parser.add_argument("csv", type=str, help="The target csv filepath.") + parser.add_argument( + "--field", + type=str, + default="u", + help="Field variable to plot (default: u)", + ) + args = parser.parse_args(sys.argv[1:]) + main(args) diff --git a/_downloads/4fce43a14fb0221048f87bf1c5f7507a/workflow.json b/_downloads/4fce43a14fb0221048f87bf1c5f7507a/workflow.json new file mode 100644 index 00000000..b9135dce --- /dev/null +++ b/_downloads/4fce43a14fb0221048f87bf1c5f7507a/workflow.json @@ -0,0 +1,33 @@ +{ + "version": "0.1.0", + "nodes": [ + {"id": 0, "type": "function", "value": "workflow.generate_mesh"}, + {"id": 1, "type": "function", "value": "workflow.convert_to_xdmf"}, + {"id": 2, "type": "function", "value": "workflow.poisson"}, + {"id": 3, "type": "function", "value": "workflow.plot_over_line"}, + {"id": 4, "type": "function", "value": "workflow.substitute_macros"}, + {"id": 5, "type": "function", "value": "workflow.compile_paper"}, + {"id": 6, "type": "input", "value": 2.0, "name": "domain_size"}, + {"id": 7, "type": "input", "value": "source", "name": "source_directory"}, + {"id": 8, "type": "output", "name": "result"} + ], + "edges": [ + {"target": 0, "targetPort": "domain_size", "source": 6, "sourcePort": null}, + {"target": 0, "targetPort": "source_directory", "source": 7, "sourcePort": null}, + {"target": 1, "targetPort": "gmsh_output_file", "source": 0, "sourcePort": null}, + {"target": 2, "targetPort": "meshio_output_xdmf", "source": 1, "sourcePort": "xdmf_file"}, + {"target": 2, "targetPort": "meshio_output_h5", "source": 1, "sourcePort": "h5_file"}, + {"target": 2, "targetPort": "source_directory", "source": 7, "sourcePort": null}, + {"target": 3, "targetPort": "poisson_output_pvd_file", "source": 2, "sourcePort": "pvd_file"}, + {"target": 3, "targetPort": "poisson_output_vtu_file", "source": 2, "sourcePort": "vtu_file"}, + {"target": 3, "targetPort": "source_directory", "source": 7, "sourcePort": null}, + {"target": 4, "targetPort": "pvbatch_output_file", "source": 3, "sourcePort": null}, + {"target": 4, "targetPort": "ndofs", "source": 2, "sourcePort": "numdofs"}, + {"target": 4, "targetPort": "domain_size", "source": 6, "sourcePort": null}, + {"target": 4, "targetPort": "source_directory", "source": 7, "sourcePort": null}, + {"target": 5, "targetPort": "macros_tex", "source": 4, "sourcePort": null}, + {"target": 5, "targetPort": "plot_file", "source": 3, "sourcePort": null}, + {"target": 5, "targetPort": "source_directory", "source": 7, "sourcePort": null}, + {"target": 8, "targetPort": null, "source": 5, "sourcePort": null} + ] +} \ No newline at end of file diff --git a/_downloads/56e68093fdf308cb11075a58fe57fb60/poisson.py b/_downloads/56e68093fdf308cb11075a58fe57fb60/poisson.py new file mode 100644 index 00000000..d66939df --- /dev/null +++ b/_downloads/56e68093fdf308cb11075a58fe57fb60/poisson.py @@ -0,0 +1,108 @@ +""" +solution of the poisson equation on the unit square +""" + +from argparse import ArgumentParser +import dolfin as df + + +def boundary_expression(): + """Defines the function to be used for the boundary conditions""" + return "1.0 + x[0] * x[0] + 2.0 * x[1] * x[1]" + + +def solve_poisson( + meshfile: str, degree: int, bc_expression: str = boundary_expression() +): + """solves the poisson equation + + Parameters + ---------- + meshfile : str + FilePath to the mesh in xdmf format. + degree : int + Degree of the finite element space. + + Returns + ------- + solution : df.Function + """ + mesh = df.Mesh() + with df.XDMFFile(meshfile) as instream: + instream.read(mesh) + func_space = df.FunctionSpace(mesh, "CG", degree) + boundary_data = df.Expression(bc_expression, degree=2) + + def boundary(_, on_boundary): + return on_boundary + + boundary_conditions = df.DirichletBC(func_space, boundary_data, boundary) + trial_function = df.TrialFunction(func_space) + test_function = df.TestFunction(func_space) + source = df.Constant(-6.0) + lhs = df.dot(df.grad(trial_function), df.grad(test_function)) * df.dx + rhs = source * test_function * df.dx + + solution = df.Function(func_space) + df.solve(lhs == rhs, solution, boundary_conditions) + return solution + + +def solve_and_write_output( + mesh: str, degree: int, outputfile: str, numdofs=None, return_dofs=False +): + """solves the poisson equation and writes the solution + and the number of degrees of freedom to the given file + + Parameters + ---------- + meshfile : str + FilePath to the mesh in xdmf format. + degree : int + Degree of the finite element space. + outputfile : str + FilePath to the output file into which the solution is written. + numdofs : optional, str + FilePath to which the number of degrees of freedom is written. + return_dofs : optional, bool + If True, return number of degrees of freedom. + """ + discrete_solution = solve_poisson(mesh, degree) + discrete_solution.rename("u", discrete_solution.name()) + resultFile = df.File(outputfile) + resultFile << discrete_solution + + dofs = discrete_solution.function_space().dim() + print(f"Number of dofs used: {dofs}") + + if numdofs is not None: + with open(numdofs, "w") as handle: + handle.write("{}\n".format(dofs)) + if return_dofs: + return dofs + + +if __name__ == "__main__": + PARSER = ArgumentParser(description="run script for the poisson problem") + PARSER.add_argument("-m", "--mesh", required=True, help="mesh file to be used") + PARSER.add_argument( + "-d", "--degree", required=True, help="polynomial order to be used" + ) + PARSER.add_argument( + "-o", + "--outputfile", + required=True, + help="file name for the output to be written", + ) + PARSER.add_argument( + "-n", + "--num-dofs", + required=False, + default=None, + help="file name for the number of DoFs to be written", + ) + ARGS = vars(PARSER.parse_args()) + + solve_and_write_output( + ARGS["mesh"], int(ARGS["degree"]), ARGS["outputfile"], ARGS["num_dofs"] + ) diff --git a/_downloads/7849111caddeecc1f84b6e10d30bdd5e/workflow.py b/_downloads/7849111caddeecc1f84b6e10d30bdd5e/workflow.py new file mode 100644 index 00000000..03b16a7a --- /dev/null +++ b/_downloads/7849111caddeecc1f84b6e10d30bdd5e/workflow.py @@ -0,0 +1,135 @@ +import os +from conda_subprocess import check_output +import shutil + + +def generate_mesh(domain_size: float, source_directory: str) -> str: + stage_name = "preprocessing" + gmsh_output_file_name = "square.msh" + source_file_name ="unit_square.geo" + os.makedirs(stage_name, exist_ok=True) + _copy_file_from_source(stage_name=stage_name, source_file_name=source_file_name, source_directory=source_directory) + _ = check_output( + [ + "gmsh", "-2", "-setnumber", "domain_size", str(domain_size), + source_file_name, "-o", gmsh_output_file_name + ], + prefix_name=stage_name, + cwd=stage_name, + universal_newlines=True, + ).split("\n") + return os.path.abspath(os.path.join(stage_name, gmsh_output_file_name)) + + +def convert_to_xdmf(gmsh_output_file : str) -> dict: + stage_name = "preprocessing" + meshio_output_file_name = "square.xdmf" + os.makedirs(stage_name, exist_ok=True) + _copy_file(stage_name=stage_name, source_file=gmsh_output_file) + _ = check_output( + ["meshio", "convert", os.path.basename(gmsh_output_file), meshio_output_file_name], + prefix_name=stage_name, + cwd=stage_name, + universal_newlines=True, + ).split("\n") + return { + "xdmf_file": os.path.abspath(os.path.join(stage_name, meshio_output_file_name)), + "h5_file": os.path.join(os.path.abspath(stage_name), "square.h5"), + } + + +def poisson(meshio_output_xdmf: str, meshio_output_h5: str, source_directory: str) -> dict: + stage_name = "processing" + poisson_output_pvd_file_name = "poisson.pvd" + poisson_output_numdofs_file_name = "numdofs.txt" + source_file_name = "poisson.py" + os.makedirs(stage_name, exist_ok=True) + _copy_file_from_source(stage_name=stage_name, source_file_name=source_file_name, source_directory=source_directory) + _copy_file(stage_name=stage_name, source_file=meshio_output_xdmf) + _copy_file(stage_name=stage_name, source_file=meshio_output_h5) + _ = check_output( + [ + "python", "poisson.py", "--mesh", os.path.basename(meshio_output_xdmf), "--degree", "2", + "--outputfile", poisson_output_pvd_file_name, "--num-dofs", poisson_output_numdofs_file_name + ], + prefix_name=stage_name, + cwd=stage_name, + universal_newlines=True, + ).split("\n") + return { + "numdofs": _poisson_collect_output(numdofs_file=os.path.join(stage_name, poisson_output_numdofs_file_name)), + "pvd_file": os.path.abspath(os.path.join(stage_name, poisson_output_pvd_file_name)), + "vtu_file": os.path.abspath(os.path.join(stage_name, "poisson000000.vtu")), + } + + +def plot_over_line(poisson_output_pvd_file: str, poisson_output_vtu_file: str, source_directory: str) -> str: + stage_name = "postprocessing" + pvbatch_output_file_name = "plotoverline.csv" + source_file_name = "postprocessing.py" + os.makedirs(stage_name, exist_ok=True) + _copy_file_from_source(stage_name=stage_name, source_file_name=source_file_name, source_directory=source_directory) + _copy_file(stage_name=stage_name, source_file=poisson_output_pvd_file) + _copy_file(stage_name=stage_name, source_file=poisson_output_vtu_file) + _ = check_output( + ["pvbatch", source_file_name, os.path.basename(poisson_output_pvd_file), pvbatch_output_file_name], + prefix_name=stage_name, + cwd=stage_name, + universal_newlines=True, + ).split("\n") + return os.path.abspath(os.path.join("postprocessing", pvbatch_output_file_name)) + + +def substitute_macros(pvbatch_output_file: str, ndofs: int, domain_size: float, source_directory: str) -> str: + stage_name = "postprocessing" + source_file_name = "prepare_paper_macros.py" + template_file_name = "macros.tex.template" + macros_output_file_name = "macros.tex" + os.makedirs(stage_name, exist_ok=True) + _copy_file_from_source(stage_name=stage_name, source_file_name=source_file_name, source_directory=source_directory) + _copy_file_from_source(stage_name=stage_name, source_file_name=template_file_name, source_directory=source_directory) + _copy_file(stage_name=stage_name, source_file=pvbatch_output_file) + _ = check_output( + [ + "python", "prepare_paper_macros.py", "--macro-template-file", template_file_name, + "--plot-data-path", os.path.basename(pvbatch_output_file), "--domain-size", str(domain_size), + "--num-dofs", str(ndofs), "--output-macro-file", macros_output_file_name, + ], + prefix_name=stage_name, + cwd=stage_name, + universal_newlines=True, + ).split("\n") + return os.path.abspath(os.path.join(stage_name, macros_output_file_name)) + + +def compile_paper(macros_tex: str, plot_file: str, source_directory: str) -> str: + stage_name = "postprocessing" + paper_output = "paper.pdf" + source_file_name = "paper.tex" + os.makedirs(stage_name, exist_ok=True) + _copy_file_from_source(stage_name=stage_name, source_file_name=source_file_name, source_directory=source_directory) + _copy_file(stage_name=stage_name, source_file=macros_tex) + _copy_file(stage_name=stage_name, source_file=plot_file) + _ = check_output( + ["tectonic", source_file_name], + prefix_name=stage_name, + universal_newlines=True, + cwd=stage_name, + ).split("\n") + return os.path.abspath(os.path.join(stage_name, paper_output)) + + +def _poisson_collect_output(numdofs_file: str) -> int: + with open(os.path.join(numdofs_file), "r") as f: + return int(f.read()) + + +def _copy_file(stage_name: str, source_file: str): + input_file = os.path.join(os.path.abspath(stage_name), os.path.basename(source_file)) + if input_file != source_file: + shutil.copyfile(source_file, input_file) + + +def _copy_file_from_source(stage_name: str, source_file_name: str, source_directory: str): + source_file = os.path.join(source_directory, source_file_name) + shutil.copyfile(source_file, os.path.join(stage_name, source_file_name)) diff --git a/_downloads/b2eedcb0ddeefda5c51d1584979258ad/processing.yaml b/_downloads/b2eedcb0ddeefda5c51d1584979258ad/processing.yaml new file mode 100644 index 00000000..367874a7 --- /dev/null +++ b/_downloads/b2eedcb0ddeefda5c51d1584979258ad/processing.yaml @@ -0,0 +1,5 @@ +channels: + - conda-forge +dependencies: + - fenics=2019.1.0=py39hf3d152e_26 + - sympy=1.13.3 \ No newline at end of file diff --git a/_downloads/b85b54c725e4538522e7eabb629474c5/workflow.json b/_downloads/b85b54c725e4538522e7eabb629474c5/workflow.json new file mode 100644 index 00000000..9ffb9213 --- /dev/null +++ b/_downloads/b85b54c725e4538522e7eabb629474c5/workflow.json @@ -0,0 +1,19 @@ +{ + "version": "0.1.0", + "nodes": [ + {"id": 0, "type": "function", "value": "workflow.get_prod_and_div"}, + {"id": 1, "type": "function", "value": "workflow.get_sum"}, + {"id": 2, "type": "function", "value": "workflow.get_square"}, + {"id": 3, "type": "input", "value": 1, "name": "x"}, + {"id": 4, "type": "input", "value": 2, "name": "y"}, + {"id": 5, "type": "output", "name": "result"} + ], + "edges": [ + {"target": 0, "targetPort": "x", "source": 3, "sourcePort": null}, + {"target": 0, "targetPort": "y", "source": 4, "sourcePort": null}, + {"target": 1, "targetPort": "x", "source": 0, "sourcePort": "prod"}, + {"target": 1, "targetPort": "y", "source": 0, "sourcePort": "div"}, + {"target": 2, "targetPort": "x", "source": 1, "sourcePort": null}, + {"target": 5, "targetPort": null, "source": 2, "sourcePort": null} + ] +} diff --git a/_downloads/c16ba0969d10490ef2a46641272562b4/prepare_paper_macros.py b/_downloads/c16ba0969d10490ef2a46641272562b4/prepare_paper_macros.py new file mode 100644 index 00000000..663407d5 --- /dev/null +++ b/_downloads/c16ba0969d10490ef2a46641272562b4/prepare_paper_macros.py @@ -0,0 +1,43 @@ +""" +places the correct values into the paper macros template file +""" + +import string +import argparse + +PARSER = argparse.ArgumentParser( + description="Place computed values in the paper macros template file" +) +PARSER.add_argument( + "-f", "--macro-template-file", + required=False, default="macros.tex.template", + help="The macro template file" +) +PARSER.add_argument( + "-o", "--output-macro-file", + required=False, default="macros.tex", + help="The macro file to be written" +) +PARSER.add_argument( + "-s", "--domain-size", + required=True, help="The computed domain size", +) +PARSER.add_argument( + "-n", "--num-dofs", + required=True, help="The computed number of dofs", +) +PARSER.add_argument( + "-p", "--plot-data-path", + required=True, help="The path to the data for the plot over line" +) +ARGS = vars(PARSER.parse_args()) + + +with open(ARGS["output_macro_file"], "w") as out_file: + with open(ARGS["macro_template_file"], "r") as in_file: + raw = string.Template(in_file.read()) + out_file.write(raw.substitute({ + "DOMAINSIZE": ARGS["domain_size"], + "NUMDOFS": ARGS["num_dofs"], + "PLOTDATAPATH": ARGS["plot_data_path"] + })) diff --git a/_downloads/cdcd3d8b8608feb76c8d22665a4ae8ae/unit_square.geo b/_downloads/cdcd3d8b8608feb76c8d22665a4ae8ae/unit_square.geo new file mode 100644 index 00000000..b8f55b7a --- /dev/null +++ b/_downloads/cdcd3d8b8608feb76c8d22665a4ae8ae/unit_square.geo @@ -0,0 +1,9 @@ +DefineConstant[ domain_size = 1.0 ]; +DefineConstant[ mesh_size = domain_size/4.0 ]; + +SetFactory("OpenCASCADE"); +Rectangle(1) = {0, 0, 0, domain_size, domain_size, 0}; +Physical Surface(1) = {1}; + +Printf("Used domain size: %f", domain_size); +Printf("Used mesh size: %f", mesh_size); diff --git a/_downloads/cdf93d425e6df529ed97c8b502821274/postprocessing.yaml b/_downloads/cdf93d425e6df529ed97c8b502821274/postprocessing.yaml new file mode 100644 index 00000000..acd99eda --- /dev/null +++ b/_downloads/cdf93d425e6df529ed97c8b502821274/postprocessing.yaml @@ -0,0 +1,5 @@ +channels: + - conda-forge +dependencies: + - paraview=5.9.1=hfc1cbd4_3_egl + - tectonic=0.8.0=ha1fef3e_1 diff --git a/_downloads/d4b6ab1210e71ac0cfa700589f3eda0c/workflow.py b/_downloads/d4b6ab1210e71ac0cfa700589f3eda0c/workflow.py new file mode 100644 index 00000000..1a2e4c3f --- /dev/null +++ b/_downloads/d4b6ab1210e71ac0cfa700589f3eda0c/workflow.py @@ -0,0 +1,10 @@ +def get_prod_and_div(x, y): + return {"prod": x * y, "div": x / y} + + +def get_sum(x, y): + return x + y + + +def get_square(x): + return x ** 2 diff --git a/_downloads/d87a46985e2e587030c68d49ffa4528b/environment.yml b/_downloads/d87a46985e2e587030c68d49ffa4528b/environment.yml new file mode 100644 index 00000000..7ebaa8fe --- /dev/null +++ b/_downloads/d87a46985e2e587030c68d49ffa4528b/environment.yml @@ -0,0 +1,9 @@ +channels: +- conda-forge +dependencies: +- ase=3.29.0 +- matplotlib=3.11.1 +- xmlschema=4.3.2 +- optimade=1.5.0 +- qe=7.5 +- qe-tools=2.0.0 diff --git a/_downloads/f2b741fba3a65a1b1eecdff88867e31c/macros.tex.template b/_downloads/f2b741fba3a65a1b1eecdff88867e31c/macros.tex.template 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b/_images/f7106aeb5d9e4e6445043145533fde9386717f0d5e039ef0f6516b5f871e8414.svg @@ -0,0 +1,161 @@ + + + + + +0 + +workflow.generate_mesh + + + +1 + +workflow.convert_to_xdmf + + + +0->1 + + +gmsh_output_file + + + +2 + +workflow.poisson + + + +1->2 + + + + + +3 + +workflow.plot_over_line + + + +2->3 + + + + + +4 + +workflow.substitute_macros + + + +2->4 + + +ndofs=result[numdofs] + + + +3->4 + + +pvbatch_output_file + + + +5 + +workflow.compile_paper + + + +3->5 + + +plot_file + + + +4->5 + + +macros_tex + + + +8 + +result + + + +5->8 + + + + + +6 + +2.0 + + + +6->0 + + +domain_size + + + +6->4 + + +domain_size + + + +7 + +/home/jovyan/example_workflows/nfdi/source + + + +7->0 + + +source_directory + + + +7->2 + + +source_directory + + + +7->3 + + +source_directory + + + +7->4 + + +source_directory + + + +7->5 + + +source_directory + + + \ No newline at end of file diff --git a/_sources/README.md b/_sources/README.md new file mode 100644 index 00000000..b5fc82d4 --- /dev/null +++ b/_sources/README.md @@ -0,0 +1,121 @@ +# Python Workflow Definition +[![Pipeline](https://github.com/pythonworkflow/python-workflow-definition/actions/workflows/pipeline.yml/badge.svg)](https://github.com/pythonworkflow/python-workflow-definition/actions/workflows/pipeline.yml) +[![codecov](https://codecov.io/github/pythonworkflow/python-workflow-definition/graph/badge.svg?token=3JXD1GN8LG)](https://codecov.io/github/pythonworkflow/python-workflow-definition) +[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/pythonworkflow/python-workflow-definition/HEAD) +[![DOI](https://zenodo.org/badge/945869529.svg)](https://doi.org/10.5281/zenodo.15516179) + +## Definition +In the Python Workflow Definition (PWD) each node represents a Python function, with the edges defining the connection +between input and output of the different Python functions. + +Published in: [J. Janssen, J. George, J. Geiger, M. Bercx, X. Wang, C. Ertural, J. Schaarschmidt, A.M. Ganose, G. Pizzi, T. Hickel and J. Neugebauer. A python workflow definition for computational materials design. Digital Discovery, 2025](https://doi.org/10.1039/D5DD00231A) + +## Format +Each workflow consists of three files, a Python module which defines the individual Pythons, a JSON file which defines +the connections between the different Python functions and a conda environment file to define the software dependencies. +The files are not intended to be human readable, but rather interact as a machine readable exchange format between the +different workflow engines to enable interoperability. + +## Installation +The Python Workflow Definition can either be installed via pypi or via conda. For the [pypi installation](https://pypi.org/project/python-workflow-definition/) use: +``` +pip install python-workflow-definition +``` +For the conda installation via the [conda-forge community channel](https://anaconda.org/conda-forge/python-workflow-definition) use: +``` +conda install conda-forge::python-workflow-definition +``` + +## Examples +### Simple Example +As a first example we define two Python functions which add multiple inputs: +```python +def get_sum(x, y): + return x + y + + +def get_prod_and_div(x: float, y: float) -> dict: + return {"prod": x * y, "div": x / y} +``` +These two Python functions are combined in the following example workflow: +```python +def combined_workflow(x=1, y=2): + tmp_dict = get_prod_and_div(x=x, y=y) + return get_sum(x=tmp_dict["prod"], y=tmp_dict["div"]) +``` +For the workflow representation of these Python functions the Python functions are stored in the [example_workflows/arithmetic/workflow.py](example_workflows/arithmetic/workflow.py) +Python module. The connection of the Python functions are stored in the [example_workflows/arithmetic/workflow.json](example_workflows/arithmetic/workflow.json) +JSON file: +```JSON +{ + "nodes": [ + {"id": 0, "type": "function", "value": "workflow.get_prod_and_div"}, + {"id": 1, "type": "function", "value": "workflow.get_sum"}, + {"id": 2, "type": "input", "value": 1, "name": "x"}, + {"id": 3, "type": "input", "value": 2, "name": "y"}, + {"id": 4, "type": "output", "name": "result"} + ], + "edges": [ + {"target": 0, "targetPort": "x", "source": 2, "sourcePort": null}, + {"target": 0, "targetPort": "y", "source": 3, "sourcePort": null}, + {"target": 1, "targetPort": "x", "source": 0, "sourcePort": "prod"}, + {"target": 1, "targetPort": "y", "source": 0, "sourcePort": "div"}, + {"target": 4, "targetPort": null, "source": 1, "sourcePort": null} + ] +} +``` +The abbreviations in the definition of the edges are: +* `target` - target node +* `targetPort` - target port - for a node with multiple input parameters the target port specifies which input parameter to use. +* `source` - source node +* `sourcePort` - source port - for a node with multiple output parameters the source port specifies which output parameter to use. + +As the workflow does not require any additional resources, as it is only using built-in functionality of the Python standard +library. + +The corresponding Jupyter notebooks demonstrate this functionality: + +| Example | Explanation | +|----------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------| +| [example_workflows/arithmetic/aiida.ipynb](example_workflows/arithmetic/aiida.ipynb) | Define Workflow with aiida and execute it with jobflow and pyiron_base. | +| [example_workflows/arithmetic/jobflow.ipynb](example_workflows/arithmetic/jobflow.ipynb) | Define Workflow with jobflow and execute it with aiida and pyiron_base. | +| [example_workflows/arithmetic/pyiron_base.ipynb](example_workflows/arithmetic/pyiron_base.ipynb) | Define Workflow with pyiron_base and execute it with aiida and jobflow. | +| [example_workflows/arithmetic/universal_workflow.ipynb](example_workflows/arithmetic/universal_workflow.ipynb) | Execute workflow defined in the Python Workflow Definition with aiida, executorlib, jobflow, pyiron_base and pure Python. | + +### Quantum Espresso Workflow +The second workflow example is the calculation of an energy volume curve with Quantum Espresso. In the first step the +initial structure is relaxed, afterward it is strained and the total energy is calculated. +* [example_workflows/quantum_espresso/workflow.py](example_workflows/quantum_espresso/workflow.py) Python functions +* [example_workflows/quantum_espresso/workflow.json](example_workflows/quantum_espresso/workflow.json) Workflow definition in the Python Workflow Definition. +* [example_workflows/quantum_espresso/environment.yml](example_workflows/quantum_espresso/environment.yml) Conda environment + +| Example | Explanation | +|----------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------| +| [example_workflows/quantum_espresso/aiida.ipynb](example_workflows/quantum_espresso/aiida.ipynb) | Define Workflow with aiida and execute it with jobflow and pyiron_base. | +| [example_workflows/quantum_espresso/jobflow.ipynb](example_workflows/quantum_espresso/jobflow.ipynb) | Define Workflow with jobflow and execute it with aiida and pyiron_base. | +| [example_workflows/quantum_espresso/pyiron_base.ipynb](example_workflows/quantum_espresso/pyiron_base.ipynb) | Define Workflow with pyiron_base and execute it with aiida and jobflow. | +| [example_workflows/quantum_espresso/universal_workflow.ipynb](example_workflows/quantum_espresso/universal_workflow.ipynb) | Execute workflow defined in the Python Workflow Definition with aiida, executorlib, jobflow, pyiron_base and pure Python. | + +### NFDI4Ing Scientific Workflow Requirements +To demonstrate the compatibility of the Python Workflow Definition to file based workflows, the workflow benchmark developed as part of [NFDI4Ing](https://github.com/BAMresearch/NFDI4IngScientificWorkflowRequirements) +is implemented for all three simulation codes based on a shared workflow definition. +* [example_workflows/nfdi/workflow.py](example_workflows/nfdi/workflow.py) Python functions +* [example_workflows/nfdi/workflow.json](example_workflows/nfdi/workflow.json) Workflow definition in the Python Workflow Definition. + +Additional source files provided with the workflow benchmark: +* [example_workflows/nfdi/source/envs/preprocessing.yaml](example_workflows/nfdi/source/envs/preprocessing.yaml) Conda environment for preprocessing +* [example_workflows/nfdi/source/envs/processing.yaml](example_workflows/nfdi/source/envs/processing.yaml) Conda environment for processing +* [example_workflows/nfdi/source/envs/postprocessing.yaml](example_workflows/nfdi/source/envs/postprocessing.yaml) Conda environment for postprocessing +* [example_workflows/nfdi/source/macros.tex.template](example_workflows/nfdi/source/macros.tex.template) LaTeX module template +* [example_workflows/nfdi/source/paper.tex](example_workflows/nfdi/source/paper.tex) LaTeX paper template +* [example_workflows/nfdi/source/poisson.py](example_workflows/nfdi/source/poisson.py) Poisson Python script +* [example_workflows/nfdi/source/postprocessing.py](example_workflows/nfdi/source/postprocessing.py) Postprocessing Python script +* [example_workflows/nfdi/source/prepare_paper_macros.py](example_workflows/nfdi/source/prepare_paper_macros.py) LaTeX preprocessing Python script +* [example_workflows/nfdi/source/unit_square.geo](example_workflows/nfdi/source/unit_square.geo) Input structure + +| Example | Explanation | +|----------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------| +| [example_workflows/nfdi/aiida.ipynb](example_workflows/nfdi/aiida.ipynb) | Define Workflow with aiida and execute it with jobflow and pyiron_base. | +| [example_workflows/nfdi/jobflow.ipynb](example_workflows/nfdi/jobflow.ipynb) | Define Workflow with jobflow and execute it with aiida and pyiron_base. | +| [example_workflows/nfdi/pyiron_base.ipynb](example_workflows/nfdi/pyiron_base.ipynb) | Define Workflow with pyiron_base and execute it with aiida and jobflow. | +| [example_workflows/nfdi/universal_workflow.ipynb](example_workflows/nfdi/universal_workflow.ipynb) | Execute workflow defined in the Python Workflow Definition with aiida, executorlib, jobflow, pyiron_base and pure Python. | diff --git a/_sources/arithmetic.md b/_sources/arithmetic.md new file mode 100644 index 00000000..72ecb6d1 --- /dev/null +++ b/_sources/arithmetic.md @@ -0,0 +1,44 @@ +# Arithmetic Workflow +As a first example we define two Python functions which add multiple inputs: +```python +def get_sum(x, y): + return x + y + +def get_prod_and_div(x: float, y: float) -> dict: + return {"prod": x * y, "div": x / y} +``` +These two Python functions are combined in the following example workflow: +```python +def combined_workflow(x=1, y=2): + tmp_dict = get_prod_and_div(x=x, y=y) + return get_sum(x=tmp_dict["prod"], y=tmp_dict["div"]) +``` +For the workflow representation of these Python functions the Python functions are stored in the [workflow.py](example_workflows/arithmetic/workflow.py) +Python module. The connection of the Python functions are stored in the [workflow.json](example_workflows/arithmetic/workflow.json) +JSON file: +``` +{ + "nodes": [ + {"id": 0, "type": "function", "value": "workflow.get_prod_and_div"}, + {"id": 1, "type": "function", "value": "workflow.get_sum"}, + {"id": 2, "type": "input", "value": 1, "name": "x"}, + {"id": 3, "type": "input", "value": 2, "name": "y"}, + {"id": 4, "type": "output", "name": "result"} + ], + "edges": [ + {"target": 0, "targetPort": "x", "source": 2, "sourcePort": null}, + {"target": 0, "targetPort": "y", "source": 3, "sourcePort": null}, + {"target": 1, "targetPort": "x", "source": 0, "sourcePort": "prod"}, + {"target": 1, "targetPort": "y", "source": 0, "sourcePort": "div"}, + {"target": 4, "targetPort": null, "source": 1, "sourcePort": null} + ] +} +``` +The abbreviations in the definition of the edges are: +* `target` - target node +* `targetPort` - target port - for a node with multiple input parameters the target port specifies which input parameter to use. +* `source` - source node +* `sourcePort` - source port - for a node with multiple output parameters the source port specifies which output parameter to use. + +As the workflow does not require any additional resources, as it is only using built-in functionality of the Python standard +library. diff --git a/_sources/conclusion.md b/_sources/conclusion.md new file mode 100644 index 00000000..5afbcb49 --- /dev/null +++ b/_sources/conclusion.md @@ -0,0 +1,17 @@ +# Conclusion +Based on the Python Workflow Definition three rather different workflows were implemented in rather different workflow +engines: a simple arithmetic example coupling two Python functions, a Quantum Espresso energy volume curve calculation +with fan-out parallelism, and a file based, multi-tool NFDI4Ing benchmark. In each case the same `workflow.json` was +written by one workflow engine and successfully loaded and executed by the others, without any change to the underlying +Python functions in `workflow.py`. This demonstrates the interoperability achieved with the Python Workflow Definition, +and shows that it scales from small, in-memory Python workflows to larger, file based, multi-environment scientific +workflows. + +## Where to go next +* Browse the [example_workflows](https://github.com/pythonworkflow/python-workflow-definition/tree/main/example_workflows) + directory for the full set of notebooks, including engines not covered in this book such as `pyiron_workflow`, + `executorlib` and CWL. +* See the [README](https://github.com/pythonworkflow/python-workflow-definition) for installation instructions via + `pip` or `conda`. +* Read the accompanying publication: [J. Janssen et al., A python workflow definition for computational materials + design, Digital Discovery, 2025](https://doi.org/10.1039/D5DD00231A). \ No newline at end of file diff --git a/_sources/documentation/arithmetic.md b/_sources/documentation/arithmetic.md new file mode 100644 index 00000000..72ecb6d1 --- /dev/null +++ b/_sources/documentation/arithmetic.md @@ -0,0 +1,44 @@ +# Arithmetic Workflow +As a first example we define two Python functions which add multiple inputs: +```python +def get_sum(x, y): + return x + y + +def get_prod_and_div(x: float, y: float) -> dict: + return {"prod": x * y, "div": x / y} +``` +These two Python functions are combined in the following example workflow: +```python +def combined_workflow(x=1, y=2): + tmp_dict = get_prod_and_div(x=x, y=y) + return get_sum(x=tmp_dict["prod"], y=tmp_dict["div"]) +``` +For the workflow representation of these Python functions the Python functions are stored in the [workflow.py](example_workflows/arithmetic/workflow.py) +Python module. The connection of the Python functions are stored in the [workflow.json](example_workflows/arithmetic/workflow.json) +JSON file: +``` +{ + "nodes": [ + {"id": 0, "type": "function", "value": "workflow.get_prod_and_div"}, + {"id": 1, "type": "function", "value": "workflow.get_sum"}, + {"id": 2, "type": "input", "value": 1, "name": "x"}, + {"id": 3, "type": "input", "value": 2, "name": "y"}, + {"id": 4, "type": "output", "name": "result"} + ], + "edges": [ + {"target": 0, "targetPort": "x", "source": 2, "sourcePort": null}, + {"target": 0, "targetPort": "y", "source": 3, "sourcePort": null}, + {"target": 1, "targetPort": "x", "source": 0, "sourcePort": "prod"}, + {"target": 1, "targetPort": "y", "source": 0, "sourcePort": "div"}, + {"target": 4, "targetPort": null, "source": 1, "sourcePort": null} + ] +} +``` +The abbreviations in the definition of the edges are: +* `target` - target node +* `targetPort` - target port - for a node with multiple input parameters the target port specifies which input parameter to use. +* `source` - source node +* `sourcePort` - source port - for a node with multiple output parameters the source port specifies which output parameter to use. + +As the workflow does not require any additional resources, as it is only using built-in functionality of the Python standard +library. diff --git a/_sources/documentation/conclusion.md b/_sources/documentation/conclusion.md new file mode 100644 index 00000000..5afbcb49 --- /dev/null +++ b/_sources/documentation/conclusion.md @@ -0,0 +1,17 @@ +# Conclusion +Based on the Python Workflow Definition three rather different workflows were implemented in rather different workflow +engines: a simple arithmetic example coupling two Python functions, a Quantum Espresso energy volume curve calculation +with fan-out parallelism, and a file based, multi-tool NFDI4Ing benchmark. In each case the same `workflow.json` was +written by one workflow engine and successfully loaded and executed by the others, without any change to the underlying +Python functions in `workflow.py`. This demonstrates the interoperability achieved with the Python Workflow Definition, +and shows that it scales from small, in-memory Python workflows to larger, file based, multi-environment scientific +workflows. + +## Where to go next +* Browse the [example_workflows](https://github.com/pythonworkflow/python-workflow-definition/tree/main/example_workflows) + directory for the full set of notebooks, including engines not covered in this book such as `pyiron_workflow`, + `executorlib` and CWL. +* See the [README](https://github.com/pythonworkflow/python-workflow-definition) for installation instructions via + `pip` or `conda`. +* Read the accompanying publication: [J. Janssen et al., A python workflow definition for computational materials + design, Digital Discovery, 2025](https://doi.org/10.1039/D5DD00231A). \ No newline at end of file diff --git a/_sources/documentation/evcurve.md b/_sources/documentation/evcurve.md new file mode 100644 index 00000000..536eec6f --- /dev/null +++ b/_sources/documentation/evcurve.md @@ -0,0 +1,67 @@ +# Energy Volume Curve +Based on [previous work](https://materialdigital.github.io/ADIS2023/README.html) from the [ADIS 2023 workshop](https://www.mpie.de/4902385/adis2023) +the calculation of an energy volume curve with the [quantum espresso](https://www.quantum-espresso.org) density +functional theory (DFT) simulation code is implemented in the Python Workflow Definition. + +## Workflow +An energy-volume curve is computed by relaxing a bulk crystal structure, straining it to a series of volumes and +computing the total energy at each volume with a self-consistent-field (SCF) calculation. The pipeline is implemented +as five Python functions in [workflow.py](example_workflows/quantum_espresso/workflow.py): +```python +def get_bulk_structure(element, a, cubic): + # build an ASE bulk crystal structure, e.g. Al + +def calculate_qe(working_directory, input_dict): + # write a pw.x input file, run "pw.x -in input.pwi > output.pwo" and parse the pwscf.xml output; + # input_dict["calculation"] selects "vc-relax" (cell + geometry relaxation) or "scf" (single-point energy) + +def generate_structures(structure, strain_lst): + # apply each volumetric strain in strain_lst to a structure, returning one structure per strain + +def plot_energy_volume_curve(volume_lst, energy_lst): + # plot energy against volume and save it as evcurve.png +``` +`write_input`/`collect_output` handle the file-based `pw.x` input/output (`.pwi`/`.pwo`/`.xml` files), and +`ase_to_json`/`json_to_ase` (de)serialize ASE `Atoms` objects to/from OPTIMADE-JSON strings, so structures can be +passed between functions as plain JSON data instead of Python objects. + +The workflow combines these functions as: `get_bulk_structure` -> `calculate_qe` (`vc-relax`, once) -> +`generate_structures` -> `calculate_qe` (`scf`, once per strained structure) -> `plot_energy_volume_curve`. With five +strains this means one relaxation followed by five independent SCF calculations that fan out from +`generate_structures` and feed back into a single plot. + +## workflow.json +[workflow.json](example_workflows/quantum_espresso/workflow.json) encodes this fan-out as five separate +`workflow.calculate_qe` function nodes, each connected to its own strained structure and its own `working_directory` +input, all reading the same shared inputs (`pseudopotentials`, `kpts`, `calculation`, `smearing`) via +`python_workflow_definition.shared.get_dict`. An excerpt showing the pattern for two of the five strained +calculations: +``` +{ + "nodes": [ + {"id": 2, "type": "function", "value": "workflow.generate_structures"}, + {"id": 3, "type": "function", "value": "workflow.calculate_qe"}, + {"id": 4, "type": "function", "value": "workflow.calculate_qe"}, + {"id": 19, "type": "input", "value": "strain_0", "name": "working_directory_1"}, + {"id": 20, "type": "function", "value": "python_workflow_definition.shared.get_dict"}, + {"id": 22, "type": "input", "value": "strain_1", "name": "working_directory_2"}, + {"id": 23, "type": "function", "value": "python_workflow_definition.shared.get_dict"} + ], + "edges": [ + {"target": 3, "targetPort": "working_directory", "source": 19, "sourcePort": null}, + {"target": 20, "targetPort": "structure", "source": 2, "sourcePort": "s_0"}, + {"target": 3, "targetPort": "input_dict", "source": 20, "sourcePort": null}, + {"target": 4, "targetPort": "working_directory", "source": 22, "sourcePort": null}, + {"target": 23, "targetPort": "structure", "source": 2, "sourcePort": "s_1"}, + {"target": 4, "targetPort": "input_dict", "source": 23, "sourcePort": null} + ] +} +``` +Node 2 (`generate_structures`) exposes one output port per strain (`s_0`, `s_1`, ...); each port is wired into its +own `get_dict`/`calculate_qe` pair. The energy and volume outputs of all five `calculate_qe` nodes are collected back +into lists with `python_workflow_definition.shared.get_list` before being passed to `plot_energy_volume_curve`. + +## Requirements +Running this workflow (rather than just loading/inspecting the JSON) requires the Quantum Espresso `pw.x` binary, +matching pseudopotential files (see [espresso/pseudo](example_workflows/quantum_espresso/espresso/pseudo)) and the +Python dependencies listed in [environment.yml](example_workflows/quantum_espresso/environment.yml). \ No newline at end of file diff --git a/_sources/documentation/intro.md b/_sources/documentation/intro.md new file mode 100644 index 00000000..4ad92284 --- /dev/null +++ b/_sources/documentation/intro.md @@ -0,0 +1,24 @@ +# Definition +In the Python Workflow Definition (PWD) each node represents a Python function, with the edges defining the connection +between input and output of the different Python functions. + +## Format +Each workflow consists of three files, a Python module which defines the individual Pythons, a JSON file which defines +the connections between the different Python functions and a conda environment file to define the software dependencies. +The files are not intended to be human readable, but rather interact as a machine readable exchange format between the +different workflow engines to enable interoperability. + +## Workflow Engines +Currently supported workflow engines: +* [aiida-workgraph](https://github.com/aiidateam/aiida-workgraph) +* [jobflow](https://github.com/materialsproject/jobflow) +* [pyiron_base](https://github.com/pyiron/pyiron_base) +* [pyiron_workflow](https://github.com/pyiron/pyiron_workflow) +* [executorlib](https://github.com/pyiron/executorlib) +* [CWL](https://www.commonwl.org/) via [cwltool](https://github.com/common-workflow-language/cwltool) + +## Example Workflows +Three workflows are implemented: +* Simple workflow coupling two python functions +* Calculation of an [energy volume curve with quantum espresso](https://materialdigital.github.io/ADIS2023/) +* File based workflow benchmark from [NFDI4Ing](https://www.inggrid.org/article/id/3726/) diff --git a/_sources/documentation/nfdi.md b/_sources/documentation/nfdi.md new file mode 100644 index 00000000..1fa6a863 --- /dev/null +++ b/_sources/documentation/nfdi.md @@ -0,0 +1,61 @@ +# NFDI4Ing Benchmark +To demonstrate the compatibility of the Python Workflow Definition to file based workflows, the workflow benchmark +developed as part of [NFDI4Ing](https://www.inggrid.org/article/id/3726/) is implemented for all workflow engines +based on the Python Workflow Definition. + +## Workflow +Unlike the [arithmetic](arithmetic.md) and energy-volume-curve examples, which pass Python objects between functions, +this benchmark chains together external command line tools that each require their own conda environment (defined in +`source/envs/*.yaml`) and communicate through files rather than in-memory values. The +pipeline is defined by six Python functions in [workflow.py](example_workflows/nfdi/workflow.py), each of which +copies its inputs into a stage-specific subdirectory (`preprocessing`, `processing` or `postprocessing`) and calls +its external tool with `conda_subprocess.check_output`: +```python +def generate_mesh(domain_size: float, source_directory: str) -> str: ... +def convert_to_xdmf(gmsh_output_file: str) -> dict: ... +def poisson(meshio_output_xdmf: str, meshio_output_h5: str, source_directory: str) -> dict: ... +def plot_over_line(poisson_output_pvd_file: str, poisson_output_vtu_file: str, source_directory: str) -> str: ... +def substitute_macros(pvbatch_output_file: str, ndofs: int, domain_size: float, source_directory: str) -> str: ... +def compile_paper(macros_tex: str, plot_file: str, source_directory: str) -> str: ... +``` +* `generate_mesh` runs [`gmsh`](https://gmsh.info) on `unit_square.geo` to mesh a 2D square whose side length is set + by the `domain_size` parameter, producing a `.msh` file. +* `convert_to_xdmf` runs `meshio convert` to turn the gmsh mesh into an XDMF/H5 file pair that the FEM solver can read. +* `poisson` runs a [FEniCS](https://fenicsproject.org)-based `poisson.py` script that solves the Poisson equation on + the mesh, returning the number of degrees of freedom (`numdofs`) alongside the `.pvd`/`.vtu` result files. +* `plot_over_line` runs ParaView's `pvbatch` with `postprocessing.py` to sample the FEM solution along a line and + write it out as a CSV file. +* `substitute_macros` runs `prepare_paper_macros.py` to fill a LaTeX macro template with the plot data path, the + domain size and the number of degrees of freedom. +* `compile_paper` runs [`tectonic`](https://tectonic-typesetting.github.io) to compile `paper.tex`, which references + those macros and the plot, into `paper.pdf`. + +The connection of these Python functions is stored in the [workflow.json](example_workflows/nfdi/workflow.json) +JSON file, following the same `nodes`/`edges` structure as the other examples. Each function is a `function` node, +`domain_size` and `source_directory` are `input` nodes, and edges connect a function's input port either to another +function's output port or directly to an input node: +``` +{ + "version": "0.1.0", + "nodes": [ + {"id": 0, "type": "function", "value": "workflow.generate_mesh"}, + {"id": 1, "type": "function", "value": "workflow.convert_to_xdmf"}, + {"id": 6, "type": "input", "value": 2.0, "name": "domain_size"}, + {"id": 7, "type": "input", "value": "source", "name": "source_directory"}, + {"id": 8, "type": "output", "name": "result"} + ], + "edges": [ + {"target": 0, "targetPort": "domain_size", "source": 6, "sourcePort": null}, + {"target": 0, "targetPort": "source_directory", "source": 7, "sourcePort": null}, + {"target": 1, "targetPort": "gmsh_output_file", "source": 0, "sourcePort": null} + ] +} +``` +Since `convert_to_xdmf` and `poisson` return a `dict` instead of a single value, the edges that read their output +set `sourcePort` to the specific dictionary key (e.g. `"xdmf_file"` or `"numdofs"`) rather than `null`. + +Because every stage shells out to a different external tool in a different conda environment and passes file paths +along the graph, this benchmark exercises a different part of the Python Workflow Definition than the arithmetic and +energy-volume-curve examples: it shows that the same `workflow.json` produced by one engine can be handed to another +engine, an execution manager like [CWL](https://www.commonwl.org)/`cwltool`, or plain Python, and still reproduce the +same chain of `gmsh`, `meshio`, FEniCS, `pvbatch` and `tectonic` calls end to end. diff --git a/_sources/evcurve.md b/_sources/evcurve.md new file mode 100644 index 00000000..536eec6f --- /dev/null +++ b/_sources/evcurve.md @@ -0,0 +1,67 @@ +# Energy Volume Curve +Based on [previous work](https://materialdigital.github.io/ADIS2023/README.html) from the [ADIS 2023 workshop](https://www.mpie.de/4902385/adis2023) +the calculation of an energy volume curve with the [quantum espresso](https://www.quantum-espresso.org) density +functional theory (DFT) simulation code is implemented in the Python Workflow Definition. + +## Workflow +An energy-volume curve is computed by relaxing a bulk crystal structure, straining it to a series of volumes and +computing the total energy at each volume with a self-consistent-field (SCF) calculation. The pipeline is implemented +as five Python functions in [workflow.py](example_workflows/quantum_espresso/workflow.py): +```python +def get_bulk_structure(element, a, cubic): + # build an ASE bulk crystal structure, e.g. Al + +def calculate_qe(working_directory, input_dict): + # write a pw.x input file, run "pw.x -in input.pwi > output.pwo" and parse the pwscf.xml output; + # input_dict["calculation"] selects "vc-relax" (cell + geometry relaxation) or "scf" (single-point energy) + +def generate_structures(structure, strain_lst): + # apply each volumetric strain in strain_lst to a structure, returning one structure per strain + +def plot_energy_volume_curve(volume_lst, energy_lst): + # plot energy against volume and save it as evcurve.png +``` +`write_input`/`collect_output` handle the file-based `pw.x` input/output (`.pwi`/`.pwo`/`.xml` files), and +`ase_to_json`/`json_to_ase` (de)serialize ASE `Atoms` objects to/from OPTIMADE-JSON strings, so structures can be +passed between functions as plain JSON data instead of Python objects. + +The workflow combines these functions as: `get_bulk_structure` -> `calculate_qe` (`vc-relax`, once) -> +`generate_structures` -> `calculate_qe` (`scf`, once per strained structure) -> `plot_energy_volume_curve`. With five +strains this means one relaxation followed by five independent SCF calculations that fan out from +`generate_structures` and feed back into a single plot. + +## workflow.json +[workflow.json](example_workflows/quantum_espresso/workflow.json) encodes this fan-out as five separate +`workflow.calculate_qe` function nodes, each connected to its own strained structure and its own `working_directory` +input, all reading the same shared inputs (`pseudopotentials`, `kpts`, `calculation`, `smearing`) via +`python_workflow_definition.shared.get_dict`. An excerpt showing the pattern for two of the five strained +calculations: +``` +{ + "nodes": [ + {"id": 2, "type": "function", "value": "workflow.generate_structures"}, + {"id": 3, "type": "function", "value": "workflow.calculate_qe"}, + {"id": 4, "type": "function", "value": "workflow.calculate_qe"}, + {"id": 19, "type": "input", "value": "strain_0", "name": "working_directory_1"}, + {"id": 20, "type": "function", "value": "python_workflow_definition.shared.get_dict"}, + {"id": 22, "type": "input", "value": "strain_1", "name": "working_directory_2"}, + {"id": 23, "type": "function", "value": "python_workflow_definition.shared.get_dict"} + ], + "edges": [ + {"target": 3, "targetPort": "working_directory", "source": 19, "sourcePort": null}, + {"target": 20, "targetPort": "structure", "source": 2, "sourcePort": "s_0"}, + {"target": 3, "targetPort": "input_dict", "source": 20, "sourcePort": null}, + {"target": 4, "targetPort": "working_directory", "source": 22, "sourcePort": null}, + {"target": 23, "targetPort": "structure", "source": 2, "sourcePort": "s_1"}, + {"target": 4, "targetPort": "input_dict", "source": 23, "sourcePort": null} + ] +} +``` +Node 2 (`generate_structures`) exposes one output port per strain (`s_0`, `s_1`, ...); each port is wired into its +own `get_dict`/`calculate_qe` pair. The energy and volume outputs of all five `calculate_qe` nodes are collected back +into lists with `python_workflow_definition.shared.get_list` before being passed to `plot_energy_volume_curve`. + +## Requirements +Running this workflow (rather than just loading/inspecting the JSON) requires the Quantum Espresso `pw.x` binary, +matching pseudopotential files (see [espresso/pseudo](example_workflows/quantum_espresso/espresso/pseudo)) and the +Python dependencies listed in [environment.yml](example_workflows/quantum_espresso/environment.yml). \ No newline at end of file diff --git a/_sources/example_workflows/arithmetic/aiida.ipynb b/_sources/example_workflows/arithmetic/aiida.ipynb new file mode 100644 index 00000000..bd067d85 --- /dev/null +++ b/_sources/example_workflows/arithmetic/aiida.ipynb @@ -0,0 +1,280 @@ +{ + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.8" + } + }, + "nbformat_minor": 4, + "nbformat": 4, + "cells": [ + { + "cell_type": "markdown", + "source": "# Aiida\n\nThis notebook defines the arithmetic workflow with [`aiida-workgraph`](https://github.com/aiidateam/aiida-workgraph) and then loads the resulting `workflow.json` into `jobflow`, `pyiron_base` and `pyiron_workflow`, to demonstrate that the same workflow definition can be executed by several different engines.", + "metadata": {} + }, + { + "cell_type": "markdown", + "source": "## Define workflow with aiida\n\n`aiida-workgraph` represents a workflow as a `WorkGraph` of `Task`s. Tasks are executed and stored by the AiiDA engine, so we first need to connect to an AiiDA profile with `load_profile()` before any task can run.", + "metadata": {} + }, + { + "cell_type": "code", + "source": [ + "from python_workflow_definition.aiida import write_workflow_json\n", + "\n", + "from aiida_workgraph import WorkGraph, task\n", + "from aiida import orm, load_profile\n", + "load_profile()\n", + "\n", + "workflow_json_filename = \"aiida_simple.json\"" + ], + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 1 + }, + { + "cell_type": "code", + "source": [ + "from workflow import (\n", + " get_sum as _get_sum,\n", + " get_prod_and_div as _get_prod_and_div,\n", + " get_square as _get_square,\n", + ")" + ], + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 2 + }, + { + "cell_type": "markdown", + "source": "The arithmetic functions are imported under a leading underscore because they are still plain Python functions at this point; `wg.add_task` below turns each one into an AiiDA `Task` that can be linked to other tasks' inputs and outputs. `get_prod_and_div` returns a dictionary, so it is wrapped with `task(outputs=['prod', 'div'])` to expose `prod` and `div` as separate output sockets.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "wg = WorkGraph(\"arithmetic\")", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 3 + }, + { + "cell_type": "code", + "source": "get_prod_and_div_task = wg.add_task(\n task(outputs=['prod', 'div'])(_get_prod_and_div),\n x=orm.Float(1),\n y=orm.Float(2),\n)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 4 + }, + { + "cell_type": "code", + "source": "get_sum_task = wg.add_task(\n _get_sum,\n x=get_prod_and_div_task.outputs.prod,\n y=get_prod_and_div_task.outputs.div,\n)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 5 + }, + { + "cell_type": "code", + "source": "get_square_task = wg.add_task(\n _get_square,\n x=get_sum_task.outputs.result,\n)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 6 + }, + { + "cell_type": "markdown", + "source": "With all tasks connected, `write_workflow_json` walks the `WorkGraph`'s tasks and links and serializes them into the PWD `workflow.json` format: each task becomes a `function` node and each link becomes an edge between an input and an output port.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "write_workflow_json(wg=wg, file_name=workflow_json_filename)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 7 + }, + { + "cell_type": "code", + "source": "!cat {workflow_json_filename}", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "{\n \"version\": \"0.1.0\",\n \"nodes\": [\n {\n \"id\": 0,\n \"type\": \"function\",\n \"value\": \"workflow.get_prod_and_div\"\n },\n {\n \"id\": 1,\n \"type\": \"function\",\n \"value\": \"workflow.get_sum\"\n },\n {\n \"id\": 2,\n \"type\": \"function\",\n \"value\": \"workflow.get_square\"\n },\n {\n \"id\": 3,\n \"type\": \"input\",\n \"name\": \"x\",\n \"value\": 1.0\n },\n {\n \"id\": 4,\n \"type\": \"input\",\n \"name\": \"y\",\n \"value\": 2.0\n },\n {\n \"id\": 5,\n \"type\": \"output\",\n \"name\": \"result\"\n }\n ],\n \"edges\": [\n {\n \"target\": 1,\n \"targetPort\": \"x\",\n \"source\": 0,\n \"sourcePort\": \"prod\"\n },\n {\n \"target\": 1,\n \"targetPort\": \"y\",\n \"source\": 0,\n \"sourcePort\": \"div\"\n },\n {\n \"target\": 2,\n \"targetPort\": \"x\",\n \"source\": 1,\n \"sourcePort\": null\n },\n {\n \"target\": 0,\n \"targetPort\": \"x\",\n \"source\": 3,\n \"sourcePort\": null\n },\n {\n \"target\": 0,\n \"targetPort\": \"y\",\n \"source\": 4,\n \"sourcePort\": null\n },\n {\n \"target\": 5,\n \"targetPort\": null,\n \"source\": 2,\n \"sourcePort\": null\n }\n ]\n}" + } + ], + "execution_count": 8 + }, + { + "cell_type": "markdown", + "source": "## Load Workflow with jobflow\n\nThe same `workflow.json` can now be loaded by a different engine. `python_workflow_definition.jobflow.load_workflow_json` reconstructs a jobflow `Flow` from the JSON, which is then executed locally with `run_locally`.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.jobflow import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 9 + }, + { + "cell_type": "code", + "source": "from jobflow.managers.local import run_locally", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 10 + }, + { + "cell_type": "code", + "source": "flow = load_workflow_json(file_name=workflow_json_filename)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 11 + }, + { + "cell_type": "code", + "source": "result = run_locally(flow)\nresult", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "2025-05-24 05:37:36,950 INFO Started executing jobs locally\n2025-05-24 05:37:37,216 INFO Starting job - get_prod_and_div (3ea26df7-3e4f-4541-a399-52684f0d763e)\n2025-05-24 05:37:37,218 INFO Finished job - get_prod_and_div (3ea26df7-3e4f-4541-a399-52684f0d763e)\n2025-05-24 05:37:37,219 INFO Starting job - get_sum (8d0957e4-21b1-433e-8e9a-b2af7b2d9b6d)\n2025-05-24 05:37:37,220 INFO Finished job - get_sum (8d0957e4-21b1-433e-8e9a-b2af7b2d9b6d)\n2025-05-24 05:37:37,221 INFO Starting job - get_square (af8ae958-4ce4-4b1f-a5df-eb7768a9aa86)\n2025-05-24 05:37:37,223 INFO Finished job - get_square (af8ae958-4ce4-4b1f-a5df-eb7768a9aa86)\n2025-05-24 05:37:37,223 INFO Finished executing jobs locally\n" + }, + { + "execution_count": 12, + "output_type": "execute_result", + "data": { + "text/plain": "{'3ea26df7-3e4f-4541-a399-52684f0d763e': {1: Response(output={'prod': 2.0, 'div': 0.5}, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/arithmetic'))},\n '8d0957e4-21b1-433e-8e9a-b2af7b2d9b6d': {1: Response(output=2.5, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/arithmetic'))},\n 'af8ae958-4ce4-4b1f-a5df-eb7768a9aa86': {1: Response(output=6.25, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/arithmetic'))}}" + }, + "metadata": {} + } + ], + "execution_count": 12 + }, + { + "cell_type": "markdown", + "source": "## Load Workflow with pyiron_base\n\nThe same JSON file is loaded into `pyiron_base`, producing a list of delayed jobs. `.draw()` visualizes the dependency graph and `.pull()` triggers delayed execution, running each job in turn and returning the final result.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.pyiron_base import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 13 + }, + { + "cell_type": "code", + "source": "delayed_object_lst = load_workflow_json(file_name=workflow_json_filename)\ndelayed_object_lst[-1].draw()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "", + "image/svg+xml": "\n\n\n\n\ncreate_function_job_9e748c1c8cdef9464869503612dbb8dd\n\ncreate_function_job=<pyiron_base.project.delayed.DelayedObject object at 0x7960e32575c0>\n\n\n\nx_a067a96e1de754e11581b419c5c1d4dd\n\nx=<pyiron_base.project.delayed.DelayedObject object at 0x7960e3257350>\n\n\n\nx_a067a96e1de754e11581b419c5c1d4dd->create_function_job_9e748c1c8cdef9464869503612dbb8dd\n\n\n\n\n\nx_e71e72d9c42ba1008579078b6c079655\n\nx=<pyiron_base.project.delayed.DelayedObject object at 0x7960ec8cc9b0>\n\n\n\nx_e71e72d9c42ba1008579078b6c079655->x_a067a96e1de754e11581b419c5c1d4dd\n\n\n\n\n\nx_974924ff998969b91bfc8b2db5f854a1\n\nx=1.0\n\n\n\nx_974924ff998969b91bfc8b2db5f854a1->x_e71e72d9c42ba1008579078b6c079655\n\n\n\n\n\ny_49c159de63f318f02b04278442feee05\n\ny=<pyiron_base.project.delayed.DelayedObject object at 0x7960e3257020>\n\n\n\nx_974924ff998969b91bfc8b2db5f854a1->y_49c159de63f318f02b04278442feee05\n\n\n\n\n\ny_49c159de63f318f02b04278442feee05->x_a067a96e1de754e11581b419c5c1d4dd\n\n\n\n\n\ny_f12a7f1986b9dd058dfc666dbe230b20\n\ny=2.0\n\n\n\ny_f12a7f1986b9dd058dfc666dbe230b20->x_e71e72d9c42ba1008579078b6c079655\n\n\n\n\n\ny_f12a7f1986b9dd058dfc666dbe230b20->y_49c159de63f318f02b04278442feee05\n\n\n\n\n" + }, + "metadata": {} + } + ], + "execution_count": 14 + }, + { + "cell_type": "code", + "source": "delayed_object_lst[-1].pull()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "The job get_prod_and_div_4729edf2c689ca4cf512acd163c98b28 was saved and received the ID: 1\nThe job get_sum_25f72a559657d0b1549593792391953e was saved and received the ID: 2\nThe job get_square_9cc2f0545498916d7720c59c1120a66d was saved and received the ID: 3\n" + }, + { + "execution_count": 15, + "output_type": "execute_result", + "data": { + "text/plain": "6.25" + }, + "metadata": {} + } + ], + "execution_count": 15 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## Load Workflow with pyiron_workflow\n\nFinally, the workflow is loaded into `pyiron_workflow`, producing a `Workflow` object whose node graph can be visualized with `.draw()` and executed with `.run()`." + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "from python_workflow_definition.pyiron_workflow import load_workflow_json" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf = load_workflow_json(file_name=workflow_json_filename)" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.draw(size=(10,10))" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.run()" + } + ] +} \ No newline at end of file diff --git a/_sources/example_workflows/arithmetic/cwl.ipynb b/_sources/example_workflows/arithmetic/cwl.ipynb new file mode 100644 index 00000000..b0c0f40e --- /dev/null +++ b/_sources/example_workflows/arithmetic/cwl.ipynb @@ -0,0 +1,121 @@ +{ + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.12.8", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + } + }, + "nbformat_minor": 5, + "nbformat": 4, + "cells": [ + { + "cell_type": "markdown", + "id": "7a93c81a", + "source": "# CWL\n\n[`cwltool`](https://github.com/common-workflow-language/cwltool) is the reference implementation of the [Common Workflow Language (CWL)](https://www.commonwl.org/), a standard for describing command-line based workflows. Unlike the other engines in this repository, CWL has no Python API: workflows are described in YAML/JSON documents and executed by the external `cwltool` command. This notebook converts the arithmetic `workflow.json` into an equivalent set of CWL files and executes them with `cwltool`.", + "metadata": {} + }, + { + "id": "377fef56-484d-491c-b19e-1be6931e44eb", + "cell_type": "code", + "source": "import pickle", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 1 + }, + { + "id": "92e3921b-2bb8-4333-8cfe-4bd27f785d24", + "cell_type": "code", + "source": "from python_workflow_definition.cwl import write_workflow", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 2 + }, + { + "cell_type": "markdown", + "id": "55b1a180", + "source": "`write_workflow` reads the existing `workflow.json` and generates the corresponding CWL description: one `CommandLineTool` `.cwl` file per function node, a `workflow.cwl` file that wires the steps together, and a `workflow.yml` file listing the input values (each serialized to its own pickle file). Every generated tool invokes `python -m python_workflow_definition.cwl`, which loads the target function from `workflow.py` and calls it with the pickled inputs.", + "metadata": {} + }, + { + "id": "5303c059-8ae4-4557-858e-b4bd64eac711", + "cell_type": "code", + "source": "write_workflow(file_name=\"workflow.json\")", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 3 + }, + { + "cell_type": "markdown", + "id": "0581c24f", + "source": "Running `cwltool workflow.cwl workflow.yml` executes the steps in dependency order, passing intermediate results between steps as pickle files, and prints the location of the final output file.", + "metadata": {} + }, + { + "id": "df302bd2-e9b6-4595-979c-67c46414d986", + "cell_type": "code", + "source": "! cwltool workflow.cwl workflow.yml", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "/srv/conda/envs/notebook/bin/cwltool:11: DeprecationWarning: Nesting argument groups is deprecated.\n sys.exit(run())\n\u001b[1;30mINFO\u001b[0m /srv/conda/envs/notebook/bin/cwltool 3.1.20250110105449\n\u001b[1;30mINFO\u001b[0m Resolved 'workflow.cwl' to 'file:///home/jovyan/example_workflows/arithmetic/workflow.cwl'\n\u001b[1;30mINFO\u001b[0m [workflow ] start\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step get_prod_and_div_0\n\u001b[1;30mINFO\u001b[0m [step get_prod_and_div_0] start\n\u001b[1;30mINFO\u001b[0m [job get_prod_and_div_0] /tmp/_1apt559$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/dyuxg6ka/stgf337bac5-2f8e-4489-bd51-83491b1d5f0e/workflow.py \\\n --function=workflow.get_prod_and_div \\\n --arg_x=/tmp/dyuxg6ka/stgd87c2fe4-ca8e-4031-9af0-751d6944cbe7/x.pickle \\\n --arg_y=/tmp/dyuxg6ka/stg7bcb8ced-0e5b-442e-a0e0-2b3117afe2d8/y.pickle\n\u001b[1;30mINFO\u001b[0m [job get_prod_and_div_0] completed success\n\u001b[1;30mINFO\u001b[0m [step get_prod_and_div_0] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step get_sum_1\n\u001b[1;30mINFO\u001b[0m [step get_sum_1] start\n\u001b[1;30mINFO\u001b[0m [job get_sum_1] /tmp/ysau_yra$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/rm6c9qek/stgfef68b90-5d69-4da9-a952-b9c2f2a1eb76/workflow.py \\\n --function=workflow.get_sum \\\n --arg_x=/tmp/rm6c9qek/stg35728be7-5a6d-487b-bd02-345581007663/prod.pickle \\\n --arg_y=/tmp/rm6c9qek/stgc0992786-237e-4308-9d9e-814ebbfb0319/div.pickle\n\u001b[1;30mINFO\u001b[0m [job get_sum_1] completed success\n\u001b[1;30mINFO\u001b[0m [step get_sum_1] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step get_square_2\n\u001b[1;30mINFO\u001b[0m [step get_square_2] start\n\u001b[1;30mINFO\u001b[0m [job get_square_2] /tmp/o3gzya8t$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/6a3sltnz/stg58ccf048-a5c3-4ba3-a24f-c64adfff84cd/workflow.py \\\n --function=workflow.get_square \\\n --arg_x=/tmp/6a3sltnz/stg70203cec-cbd4-4fea-a3de-70e9373d9c9d/result.pickle\n\u001b[1;30mINFO\u001b[0m [job get_square_2] completed success\n\u001b[1;30mINFO\u001b[0m [step get_square_2] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] completed success\n{\n \"result_file\": {\n \"location\": \"file:///home/jovyan/example_workflows/arithmetic/result.pickle\",\n \"basename\": \"result.pickle\",\n \"class\": \"File\",\n \"checksum\": \"sha1$1fd8f217331336b1226b84e351c56fb9a8d93685\",\n \"size\": 21,\n \"path\": \"/home/jovyan/example_workflows/arithmetic/result.pickle\"\n }\n}\u001b[1;30mINFO\u001b[0m Final process status is success\n" + } + ], + "execution_count": 4 + }, + { + "cell_type": "markdown", + "id": "c483a640", + "source": "The workflow's final output is written to `result.pickle`; unpickling it gives the same numeric result produced by the other engines.", + "metadata": {} + }, + { + "id": "2942dbba-ea0a-4d20-be5c-ed9992d09ff8", + "cell_type": "code", + "source": "with open(\"result.pickle\", \"rb\") as f:\n print(pickle.load(f))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "6.25\n" + } + ], + "execution_count": 5 + }, + { + "id": "60e909ee-d0d0-4bd1-81c8-dd5274ae5834", + "cell_type": "code", + "source": "", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": null + } + ] +} \ No newline at end of file diff --git a/_sources/example_workflows/arithmetic/executorlib.ipynb b/_sources/example_workflows/arithmetic/executorlib.ipynb new file mode 100644 index 00000000..612c6152 --- /dev/null +++ b/_sources/example_workflows/arithmetic/executorlib.ipynb @@ -0,0 +1,1125 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "c39b76fb-259f-4e16-a44d-02a295c82386", + "metadata": {}, + "source": "# executorlib\n\nThis notebook defines the arithmetic workflow with [`executorlib`](https://github.com/pyiron/executorlib), a lightweight `concurrent.futures`-style executor for up-scaling Python functions to HPC resources, and then loads the resulting `workflow.json` into `aiida-workgraph`, `jobflow`, `pyiron_base` and `pyiron_workflow`." + }, + { + "cell_type": "markdown", + "id": "3638419b-a0cb-49e2-b157-7fbb1acde90f", + "metadata": {}, + "source": "## Define workflow with executorlib\n\n`executorlib`'s `SingleNodeExecutor` implements the standard `Executor` interface: `.submit()` schedules a function call and immediately returns a `Future`. Passing `export_workflow_filename` to the executor records every submitted call and its dependencies as a side effect and writes them out as a PWD `workflow.json` once the `with` block exits." + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "b4a78447-e87c-4fb4-8d17-d9a280eb7254", + "metadata": {}, + "outputs": [], + "source": [ + "from executorlib import SingleNodeExecutor, get_item_from_future" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "6d859dfff0c2df5c", + "metadata": {}, + "outputs": [], + "source": [ + "from workflow import get_sum, get_prod_and_div, get_square" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "77135b0c61898507", + "metadata": {}, + "outputs": [], + "source": [ + "workflow_json_filename = \"executorlib_arithmetic.json\"" + ] + }, + { + "cell_type": "markdown", + "id": "a6c2ee50", + "source": "`get_prod_and_div` returns a dictionary, so `get_item_from_future` is used to extract the `prod` and `div` keys from its future's result before they can be passed on as separate arguments to `get_sum`.", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "07598344-0f75-433b-8902-bea21a42088c", + "metadata": {}, + "outputs": [], + "source": [ + "with SingleNodeExecutor(export_workflow_filename=workflow_json_filename) as exe:\n", + " future_prod_and_div = exe.submit(get_prod_and_div, x=1, y=2)\n", + " future_prod = get_item_from_future(future_prod_and_div, key=\"prod\")\n", + " future_div = get_item_from_future(future_prod_and_div, key=\"div\")\n", + " future_sum = exe.submit(get_sum, x=future_prod, y=future_div)\n", + " future_result = exe.submit(get_square, x=future_sum)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "bca646b2-0a9a-4271-966a-e5903a8c9031", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"version\": \"0.1.0\",\n", + " \"nodes\": [\n", + " {\n", + " \"id\": 0,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.get_prod_and_div\"\n", + " },\n", + " {\n", + " \"id\": 1,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.get_sum\"\n", + " },\n", + " {\n", + " \"id\": 2,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.get_square\"\n", + " },\n", + " {\n", + " \"id\": 3,\n", + " \"type\": \"input\",\n", + " \"value\": 1,\n", + " \"name\": \"x\"\n", + " },\n", + " {\n", + " \"id\": 4,\n", + " \"type\": \"input\",\n", + " \"value\": 2,\n", + " \"name\": \"y\"\n", + " },\n", + " {\n", + " \"id\": 5,\n", + " \"type\": \"output\",\n", + " \"name\": \"result\"\n", + " }\n", + " ],\n", + " \"edges\": [\n", + " {\n", + " \"target\": 0,\n", + " \"targetPort\": \"x\",\n", + " \"source\": 3,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 0,\n", + " \"targetPort\": \"y\",\n", + " \"source\": 4,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 1,\n", + " \"targetPort\": \"x\",\n", + " \"source\": 0,\n", + " \"sourcePort\": \"prod\"\n", + " },\n", + " {\n", + " \"target\": 1,\n", + " \"targetPort\": \"y\",\n", + " \"source\": 0,\n", + " \"sourcePort\": \"div\"\n", + " },\n", + " {\n", + " \"target\": 2,\n", + " \"targetPort\": \"x\",\n", + " \"source\": 1,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 5,\n", + " \"targetPort\": null,\n", + " \"source\": 2,\n", + " \"sourcePort\": null\n", + " }\n", + " ]\n", + "}" + ] + } + ], + "source": [ + "!cat {workflow_json_filename}" + ] + }, + { + "cell_type": "markdown", + "id": "a4c0faaf-e30d-4ded-8e9f-57f97f51b14c", + "metadata": {}, + "source": "## Load Workflow with aiida\n\nThe exported `workflow.json` is loaded into `aiida-workgraph`. As with the other notebooks, an AiiDA profile must be connected via `load_profile()` before the resulting `WorkGraph` can be run." + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "2ecc229f-daa1-49b9-9279-a6b5ae1aa4f2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Profile" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from aiida import load_profile\n", + "\n", + "load_profile()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "68a56b32-9f99-43d7-aaee-0c1cd9522681", + "metadata": {}, + "outputs": [], + "source": [ + "from python_workflow_definition.aiida import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "8f2a621d-b533-4ddd-8bcd-c22db2f922ec", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "d1e4dac30bd3409f8000d40062e2ae1b", + "version_major": 2, + "version_minor": 1 + }, + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wg = load_workflow_json(file_name=workflow_json_filename)\n", + "wg" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "cf80267d-c2b0-4236-bf1d-a57596985fc1", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "01/16/2026 08:08:17 AM <39822> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1573|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_prod_and_div\n", + "01/16/2026 08:08:17 AM <39822> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1573|WorkGraphEngine|update_task_state]: Task: get_prod_and_div, type: PYFUNCTION, finished.\n", + "01/16/2026 08:08:17 AM <39822> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1573|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_sum\n", + "01/16/2026 08:08:18 AM <39822> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1573|WorkGraphEngine|update_task_state]: Task: get_sum, type: PYFUNCTION, finished.\n", + "01/16/2026 08:08:18 AM <39822> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1573|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_square\n", + "01/16/2026 08:08:18 AM <39822> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1573|WorkGraphEngine|update_task_state]: Task: get_square, type: PYFUNCTION, finished.\n", + "01/16/2026 08:08:18 AM <39822> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1573|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n", + "01/16/2026 08:08:18 AM <39822> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1573|WorkGraphEngine|finalize]: Finalize workgraph.\n" + ] + }, + { + "data": { + "text/plain": [ + "{}" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wg.run()" + ] + }, + { + "cell_type": "markdown", + "id": "0c3503e1-0a32-40e1-845d-3fd9ec3c4c19", + "metadata": {}, + "source": "## Load Workflow with jobflow\n\nThe same JSON is loaded into a jobflow `Flow` and executed locally with `run_locally`." + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "4abb0481-8e38-479d-ae61-6c46d091653e", + "metadata": {}, + "outputs": [], + "source": [ + "from python_workflow_definition.jobflow import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "8253dd7c283bf3f7", + "metadata": {}, + "outputs": [], + "source": [ + "from jobflow.managers.local import run_locally" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "4b45e83b-945f-48c5-8e20-9df0ce0a14a1", + "metadata": {}, + "outputs": [], + "source": [ + "flow = load_workflow_json(file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "8665c39c-220c-4982-b738-c31f6460530f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2026-01-16 08:08:27,788 INFO Started executing jobs locally\n", + "2026-01-16 08:08:28,329 INFO Starting job - get_prod_and_div (548e497c-81af-44a2-a626-cd9466984398)\n", + "2026-01-16 08:08:28,332 INFO Finished job - get_prod_and_div (548e497c-81af-44a2-a626-cd9466984398)\n", + "2026-01-16 08:08:28,333 INFO Starting job - get_sum (c4ce346f-059c-4cb1-8e98-c7f4f0df837e)\n", + "2026-01-16 08:08:28,335 INFO Finished job - get_sum (c4ce346f-059c-4cb1-8e98-c7f4f0df837e)\n", + "2026-01-16 08:08:28,336 INFO Starting job - get_square (e94efcd4-8074-48b1-865c-0e614fc9c846)\n", + "2026-01-16 08:08:28,339 INFO Finished job - get_square (e94efcd4-8074-48b1-865c-0e614fc9c846)\n", + "2026-01-16 08:08:28,340 INFO Finished executing jobs locally\n" + ] + }, + { + "data": { + "text/plain": [ + "{'548e497c-81af-44a2-a626-cd9466984398': {1: Response(output={'prod': 2, 'div': 0.5}, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/arithmetic'))},\n", + " 'c4ce346f-059c-4cb1-8e98-c7f4f0df837e': {1: Response(output=2.5, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/arithmetic'))},\n", + " 'e94efcd4-8074-48b1-865c-0e614fc9c846': {1: Response(output=6.25, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/arithmetic'))}}" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result = run_locally(flow)\n", + "result" + ] + }, + { + "cell_type": "markdown", + "id": "406fd07dd4bd8006", + "metadata": {}, + "source": "## Load Workflow with pyiron_base\n\nLoading the workflow into `pyiron_base` produces a list of delayed jobs; `.draw()` visualizes the dependency graph and `.pull()` triggers delayed execution of the whole chain." + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "cf76f305-24de-45a7-be8e-cfe45cd6458e", + "metadata": { + "ExecuteTime": { + "end_time": "2025-05-24T08:25:33.797570Z", + "start_time": "2025-05-24T08:25:33.771214Z" + } + }, + "outputs": [], + "source": [ + "from python_workflow_definition.pyiron_base import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "5b442611457aa5a8", + "metadata": {}, + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "create_function_job_90a5b42c58fdc46b3ef919df41d06f68\n", + "\n", + "create_function_job=<pyiron_base.project.delayed.DelayedObject object at 0x7f9f60f8bb90>\n", + "\n", + "\n", + "\n", + "x_ac1d6fed32a5172c23c7d80f1257d4cf\n", + "\n", + "x=<pyiron_base.project.delayed.DelayedObject object at 0x7f9f60f8ba40>\n", + "\n", + "\n", + "\n", + "x_ac1d6fed32a5172c23c7d80f1257d4cf->create_function_job_90a5b42c58fdc46b3ef919df41d06f68\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "x_19fc443a8a97273a376990b43ca208fc\n", + "\n", + "x=<pyiron_base.project.delayed.DelayedObject object at 0x7f9f60f8b770>\n", + "\n", + "\n", + "\n", + "x_19fc443a8a97273a376990b43ca208fc->x_ac1d6fed32a5172c23c7d80f1257d4cf\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "x_1d847da32ecaabf6731c38f798c3d4ce\n", + "\n", + "x=1\n", + "\n", + "\n", + "\n", + "x_1d847da32ecaabf6731c38f798c3d4ce->x_19fc443a8a97273a376990b43ca208fc\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "y_8b6d8b56733d62ed930105017913a62e\n", + "\n", + "y=<pyiron_base.project.delayed.DelayedObject object at 0x7f9f60f8b740>\n", + "\n", + "\n", + "\n", + "x_1d847da32ecaabf6731c38f798c3d4ce->y_8b6d8b56733d62ed930105017913a62e\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "y_8b6d8b56733d62ed930105017913a62e->x_ac1d6fed32a5172c23c7d80f1257d4cf\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "y_a9ec4f5f33f0d64e74ed5d9900bceac6\n", + "\n", + "y=2\n", + "\n", + "\n", + "\n", + "y_a9ec4f5f33f0d64e74ed5d9900bceac6->x_19fc443a8a97273a376990b43ca208fc\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "y_a9ec4f5f33f0d64e74ed5d9900bceac6->y_8b6d8b56733d62ed930105017913a62e\n", + "\n", + "\n", + "\n", + "\n", + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "delayed_object_lst = load_workflow_json(file_name=workflow_json_filename)\n", + "delayed_object_lst[-1].draw()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "2ca33c8590a54866", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job get_prod_and_div_00cf2c787390eacfbc4a51e9a0c38ec7 was saved and received the ID: 31\n", + "The job get_sum_4b5b9d16b259a13b6a32798ce2779af8 was saved and received the ID: 32\n", + "The job get_square_9cc2f0545498916d7720c59c1120a66d was saved and received the ID: 33\n" + ] + }, + { + "data": { + "text/plain": [ + "6.25" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "delayed_object_lst[-1].pull()" + ] + }, + { + "cell_type": "markdown", + "id": "406d62d0-76eb-411f-a7fb-f866d5cec9c1", + "metadata": {}, + "source": "## Load Workflow with pyiron_workflow\n\nFinally, the workflow is loaded into a `pyiron_workflow` `Workflow` object, drawn with `.draw()` and executed with `.run()`." + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "c8c95d7f-7a3b-4ff4-890e-3f9b0434b436", + "metadata": {}, + "outputs": [], + "source": [ + "from python_workflow_definition.pyiron_workflow import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "5c759f6d-d82d-44f8-8120-e7732988fe71", + "metadata": {}, + "outputs": [], + "source": [ + 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"execution_count": 20, + "id": "3c4971a2-b66f-4fda-b438-1039b41d8f8e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'get_square__get_square': 6.25}" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wf.run()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "094c79c9-81e7-4613-b4e5-b029ce30b102", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} \ No newline at end of file diff --git a/_sources/example_workflows/arithmetic/jobflow.ipynb b/_sources/example_workflows/arithmetic/jobflow.ipynb new file mode 100644 index 00000000..3ff3b1ce --- /dev/null +++ b/_sources/example_workflows/arithmetic/jobflow.ipynb @@ -0,0 +1,410 @@ +{ + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.8" + } + }, + "nbformat_minor": 5, + "nbformat": 4, + "cells": [ + { + "id": "982a4fbe-7cf9-45dd-84ae-9854149db0b9", + "cell_type": "markdown", + "source": "# jobflow", + "metadata": {} + }, + { + "id": "e6180712-d081-45c7-ba41-fc5191f10427", + "cell_type": "markdown", + "source": "## Define workflow with jobflow\n\nThis tutorial will demonstrate how to use the PWD with `jobflow` and load the workflow with `aiida` and `pyiron`.\n\n[`jobflow`](https://joss.theoj.org/papers/10.21105/joss.05995) was developed to simplify the development of high-throughput workflows. It uses a decorator-based approach to define the “Job“s that can be connected to form complex workflows (“Flow“s). `jobflow` is the workflow language of the workflow library [`atomate2`](https://chemrxiv.org/engage/chemrxiv/article-details/678e76a16dde43c9085c75e9), designed to replace [atomate](https://www.sciencedirect.com/science/article/pii/S0927025617303919), which was central to the development of the [Materials Project](https://pubs.aip.org/aip/apm/article/1/1/011002/119685/Commentary-The-Materials-Project-A-materials) database.", + "metadata": {} + }, + { + "id": "69bedfb9ec12c092", + "cell_type": "markdown", + "source": "First, we start by importing the job decorator and the Flow class from jobflow, as welll as the necessary modules from the python workflow definition and the example arithmetic workflow.", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + } + }, + { + "id": "000bbd4a-f53c-4eea-9d85-76f0aa2ca10b", + "cell_type": "code", + "source": "from jobflow import job, Flow", + "metadata": { + "ExecuteTime": { + "end_time": "2025-04-24T12:51:34.747117656Z", + "start_time": "2025-04-24T12:51:33.203979325Z" + }, + "trusted": true + }, + "outputs": [], + "execution_count": 1 + }, + { + "id": "06c2bd9e-b2ac-4b88-9158-fa37331c3418", + "cell_type": "code", + "source": "from python_workflow_definition.jobflow import write_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 2 + }, + { + "id": "f9217ce7b093b5fc", + "cell_type": "code", + "source": "from workflow import (\n get_sum as _get_sum,\n get_prod_and_div as _get_prod_and_div,\n get_square as _get_square,\n)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 3 + }, + { + "id": "2639deadfae9c591", + "cell_type": "markdown", + "source": "Using the job object decorator, the imported functions from the arithmetic workflow are transformed into jobflow “Job”s. These “Job”s can delay the execution of Python functions and can be chained into workflows (“Flow”s). A “Job” can return serializable outputs (e.g., a number, a dictionary, or a Pydantic model) or a so-called “Response” object, which enables the execution of dynamic workflows where the number of nodes is not known prior to the workflow’s execution. ", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + } + }, + { + "id": "1feba0898ee4e361", + "cell_type": "code", + "source": "workflow_json_filename = \"jobflow_simple.json\"", + "metadata": { + "ExecuteTime": { + "end_time": "2025-04-24T10:30:04.751088Z", + "start_time": "2025-04-24T10:30:04.748941Z" + }, + "trusted": true + }, + "outputs": [], + "execution_count": 4 + }, + { + "id": "07598344-0f75-433b-8902-bea21a42088c", + "cell_type": "code", + "source": "get_sum = job(_get_sum)\n# Note: one could also transfer the outputs to the datastore as well: get_prod_and_div = job(_get_prod_and_div, data=[\"prod\", \"div\"])\n# On the way from the general definition to the jobflow definition, we do this automatically to avoid overflow databases.\nget_prod_and_div = job(_get_prod_and_div)\nget_square = job(_get_square)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 5 + }, + { + "id": "ecef1ed5-a8d3-48c3-9e01-4a40e55c1153", + "cell_type": "code", + "source": "prod_and_div = get_prod_and_div(x=1, y=2)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 6 + }, + { + "id": "2b88a30a-e26b-4802-89b7-79ca08cc0af9", + "cell_type": "code", + "source": "tmp_sum = get_sum(x=prod_and_div.output.prod, y=prod_and_div.output.div)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 7 + }, + { + "id": "8d95c3aa", + "cell_type": "code", + "source": "result = get_square(x=tmp_sum.output)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 8 + }, + { + "id": "a5e5ca63-2906-47c9-bac6-adebf8643cba", + "cell_type": "code", + "source": "flow = Flow([prod_and_div, tmp_sum, result])", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 9 + }, + { + "id": "27688edd256f1420", + "cell_type": "markdown", + "source": "As jobflow itself is only a workflow language, the workflows are typically executed on high-performance computers with a workflow manager such as [Fireworks](https://onlinelibrary.wiley.com/doi/full/10.1002/cpe.3505) or [jobflow-remote](https://github.com/Matgenix/jobflow-remote). For smaller and test workflows, simple linear, non-parallel execution of the workflow graph can be performed with jobflow itself. All outputs of individual jobs are saved in a database. For high-throughput applications typically, a MongoDB database is used. For testing and smaller workflows, a memory database can be used instead.", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + } + }, + { + "id": "e464da97-16a1-4772-9a07-0a47f152781d", + "cell_type": "code", + "source": "write_workflow_json(flow=flow, file_name=workflow_json_filename)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 10 + }, + { + "id": "bca646b2-0a9a-4271-966a-e5903a8c9031", + "cell_type": "code", + "source": "!cat {workflow_json_filename}", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "{\n \"version\": \"0.1.0\",\n \"nodes\": [\n {\n \"id\": 0,\n \"type\": \"function\",\n \"value\": \"workflow.get_prod_and_div\"\n },\n {\n \"id\": 1,\n \"type\": \"function\",\n \"value\": \"workflow.get_sum\"\n },\n {\n \"id\": 2,\n \"type\": \"function\",\n \"value\": \"workflow.get_square\"\n },\n {\n \"id\": 3,\n \"type\": \"input\",\n \"name\": \"x\",\n \"value\": 1\n },\n {\n \"id\": 4,\n \"type\": \"input\",\n \"name\": \"y\",\n \"value\": 2\n },\n {\n \"id\": 5,\n \"type\": \"output\",\n \"name\": \"result\"\n }\n ],\n \"edges\": [\n {\n \"target\": 0,\n \"targetPort\": \"x\",\n \"source\": 3,\n \"sourcePort\": null\n },\n {\n \"target\": 0,\n \"targetPort\": \"y\",\n \"source\": 4,\n \"sourcePort\": null\n },\n {\n \"target\": 1,\n \"targetPort\": \"x\",\n \"source\": 0,\n \"sourcePort\": \"prod\"\n },\n {\n \"target\": 1,\n \"targetPort\": \"y\",\n \"source\": 0,\n \"sourcePort\": \"div\"\n },\n {\n \"target\": 2,\n \"targetPort\": \"x\",\n \"source\": 1,\n \"sourcePort\": null\n },\n {\n \"target\": 5,\n \"targetPort\": null,\n \"source\": 2,\n \"sourcePort\": null\n }\n ]\n}" + } + ], + "execution_count": 11 + }, + { + "id": "65389ef27c38fdec", + "cell_type": "markdown", + "source": "Finally, you can write the workflow data into a JSON file to be imported later.", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + } + }, + { + "id": "87a27540-c390-4d34-ae75-4739bfc4c1b7", + "cell_type": "markdown", + "source": "## Load Workflow with aiida\n\nIn this part, we will demonstrate how to import the `jobflow` workflow into `aiida` via the PWD.", + "metadata": {} + }, + { + "id": "66a1b3a6-3d3b-4caa-b58f-d8bc089b1074", + "cell_type": "code", + "source": "from aiida import load_profile\n\nload_profile()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 12, + "output_type": "execute_result", + "data": { + "text/plain": "Profile" + }, + "metadata": {} + } + ], + "execution_count": 12 + }, + { + "id": "4679693b-039b-45cf-8c67-5b2b3d705a83", + "cell_type": "code", + "source": "from python_workflow_definition.aiida import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 13 + }, + { + "id": "cc7127193d31d8ef", + "cell_type": "markdown", + "source": "We import the necessary modules from `aiida` and the PWD, as well as the workflow JSON file.", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + } + }, + { + "id": "68c41a61-d185-47e8-ba31-eeff71d8b2c6", + "cell_type": "code", + "source": "wg = load_workflow_json(file_name=workflow_json_filename)\nwg", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 14, + "output_type": "execute_result", + "data": { + "text/plain": "NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'WorkGra…", + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 1, + "model_id": "9f822f7ac5ca4cb9960374af471f79cf" + } + }, + "metadata": {} + } + ], + "execution_count": 14 + }, + { + "id": "4816325767559bbe", + "cell_type": "markdown", + "source": "Finally, we are now able to run the workflow with `aiida`.", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + } + }, + { + "id": "05228ece-643c-420c-8df8-4ce3df379515", + "cell_type": "code", + "source": "wg.run()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "05/24/2025 05:38:40 AM <306> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_prod_and_div1\n05/24/2025 05:38:41 AM <306> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|update_task_state]: Task: get_prod_and_div1, type: PyFunction, finished.\n05/24/2025 05:38:41 AM <306> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_sum2\n05/24/2025 05:38:41 AM <306> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|update_task_state]: Task: get_sum2, type: PyFunction, finished.\n05/24/2025 05:38:41 AM <306> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_square3\n05/24/2025 05:38:42 AM <306> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|update_task_state]: Task: get_square3, type: PyFunction, finished.\n05/24/2025 05:38:42 AM <306> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n05/24/2025 05:38:42 AM <306> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|finalize]: Finalize workgraph.\n" + } + ], + "execution_count": 15 + }, + { + "id": "2c942094-61b4-4e94-859a-64f87b5bec64", + "cell_type": "markdown", + "source": "## Load Workflow with pyiron_base\n\nIn this part, we will demonstrate how to import the `jobflow` workflow into `pyiron` via the PWD.", + "metadata": {} + }, + { + "id": "ea102341-84f7-4156-a7d1-c3ab1ea613a5", + "cell_type": "code", + "source": "from python_workflow_definition.pyiron_base import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 16 + }, + { + "id": "8f2a621d-b533-4ddd-8bcd-c22db2f922ec", + "cell_type": "code", + "source": "delayed_object_lst = load_workflow_json(file_name=workflow_json_filename)\ndelayed_object_lst[-1].draw()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "", + "image/svg+xml": "\n\n\n\n\ncreate_function_job_25906340bd0c28c44fd73d69e7a3d8bc\n\ncreate_function_job=<pyiron_base.project.delayed.DelayedObject object at 0x733f400d1310>\n\n\n\nx_1a7fff02f6473a13e5e8742988186611\n\nx=<pyiron_base.project.delayed.DelayedObject object at 0x733f40ddb0e0>\n\n\n\nx_1a7fff02f6473a13e5e8742988186611->create_function_job_25906340bd0c28c44fd73d69e7a3d8bc\n\n\n\n\n\nx_e4655695917c433de56d1c64232473f9\n\nx=<pyiron_base.project.delayed.DelayedObject object at 0x733f4db8caa0>\n\n\n\nx_e4655695917c433de56d1c64232473f9->x_1a7fff02f6473a13e5e8742988186611\n\n\n\n\n\nx_1d847da32ecaabf6731c38f798c3d4ce\n\nx=1\n\n\n\nx_1d847da32ecaabf6731c38f798c3d4ce->x_e4655695917c433de56d1c64232473f9\n\n\n\n\n\ny_3b83397feef07a74d9a046a1b7f57749\n\ny=<pyiron_base.project.delayed.DelayedObject object at 0x733f4ed91130>\n\n\n\nx_1d847da32ecaabf6731c38f798c3d4ce->y_3b83397feef07a74d9a046a1b7f57749\n\n\n\n\n\ny_3b83397feef07a74d9a046a1b7f57749->x_1a7fff02f6473a13e5e8742988186611\n\n\n\n\n\ny_a9ec4f5f33f0d64e74ed5d9900bceac6\n\ny=2\n\n\n\ny_a9ec4f5f33f0d64e74ed5d9900bceac6->x_e4655695917c433de56d1c64232473f9\n\n\n\n\n\ny_a9ec4f5f33f0d64e74ed5d9900bceac6->y_3b83397feef07a74d9a046a1b7f57749\n\n\n\n\n" + }, + "metadata": {} + } + ], + "execution_count": 17 + }, + { + "id": "cf80267d-c2b0-4236-bf1d-a57596985fc1", + "cell_type": "code", + "source": "delayed_object_lst[-1].pull()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "The job get_prod_and_div_00cf2c787390eacfbc4a51e9a0c38ec7 was saved and received the ID: 1\nThe job get_sum_4b5b9d16b259a13b6a32798ce2779af8 was saved and received the ID: 2\nThe job get_square_9cc2f0545498916d7720c59c1120a66d was saved and received the ID: 3\n" + }, + { + "execution_count": 18, + "output_type": "execute_result", + "data": { + "text/plain": "6.25" + }, + "metadata": {} + } + ], + "execution_count": 18 + }, + { + "id": "9414680d1cbc3b2e", + "cell_type": "markdown", + "source": "Here, the procedure is the same as before: Import the necessary `pyiron_base` module from the PWD, import the workflow JSON file and run the workflow with pyiron.", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + } + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## Load Workflow with pyiron_workflow", + "id": "7da4733bfeffee63" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "from python_workflow_definition.pyiron_workflow import load_workflow_json", + "id": "6c87661996ff840b" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf = load_workflow_json(file_name=workflow_json_filename)", + "id": "33b1e9408924f9c0" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.draw(size=(10,10))", + "id": "df63b2963a0d90a5" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.run()", + "id": "bf110395454bd694" + } + ] +} diff --git a/_sources/example_workflows/arithmetic/pyiron_base.ipynb b/_sources/example_workflows/arithmetic/pyiron_base.ipynb new file mode 100644 index 00000000..eaba0a52 --- /dev/null +++ b/_sources/example_workflows/arithmetic/pyiron_base.ipynb @@ -0,0 +1,328 @@ +{ + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.8" + } + }, + "nbformat_minor": 5, + "nbformat": 4, + "cells": [ + { + "id": "c39b76fb-259f-4e16-a44d-02a295c82386", + "cell_type": "markdown", + "source": "# pyiron\n\nThis notebook defines the arithmetic workflow with [`pyiron_base`](https://github.com/pyiron/pyiron_base) and then loads the resulting `workflow.json` into `aiida-workgraph`, `jobflow` and `pyiron_workflow`.", + "metadata": {} + }, + { + "id": "3638419b-a0cb-49e2-b157-7fbb1acde90f", + "cell_type": "markdown", + "source": "## Define workflow with pyiron_base\n\nThe `job` decorator from `pyiron_base` turns a plain Python function into a pyiron job: calling the decorated function no longer executes it immediately, but returns a delayed object that can be chained with other jobs. For functions such as `get_prod_and_div` that return a dictionary, `output_key_lst` declares the dictionary keys so that individual entries (`prod`, `div`) can be wired as separate outputs to downstream jobs.", + "metadata": {} + }, + { + "id": "b4a78447-e87c-4fb4-8d17-d9a280eb7254", + "cell_type": "code", + "source": "from pyiron_base import job", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 1 + }, + { + "id": "06c2bd9e-b2ac-4b88-9158-fa37331c3418", + "cell_type": "code", + "source": "from python_workflow_definition.pyiron_base import write_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 2 + }, + { + "id": "6d859dfff0c2df5c", + "cell_type": "code", + "source": "from workflow import (\n get_sum as _get_sum,\n get_prod_and_div as _get_prod_and_div,\n get_square as _get_square,\n)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 3 + }, + { + "id": "77135b0c61898507", + "cell_type": "code", + "source": "workflow_json_filename = \"pyiron_arithmetic.json\"", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 4 + }, + { + "id": "07598344-0f75-433b-8902-bea21a42088c", + "cell_type": "code", + "source": "get_sum = job(_get_sum)\nget_prod_and_div = job(_get_prod_and_div, output_key_lst=[\"prod\", \"div\"])\nget_square = job(_get_square)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 5 + }, + { + "id": "2b88a30a-e26b-4802-89b7-79ca08cc0af9", + "cell_type": "code", + "source": "prod_and_div = get_prod_and_div(x=1, y=2)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 6 + }, + { + "id": "a5e5ca63-2906-47c9-bac6-adebf8643cba", + "cell_type": "code", + "source": "tmp_sum = get_sum(x=prod_and_div.output.prod, y=prod_and_div.output.div)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 7 + }, + { + "id": "eae321f1", + "cell_type": "code", + "source": "result = get_square(x=tmp_sum)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 8 + }, + { + "cell_type": "markdown", + "id": "9cecf662", + "source": "None of these calls run yet, they only build up a graph of delayed jobs. `write_workflow_json` walks that graph starting from the final `result` job and serializes it into the PWD `workflow.json` format.", + "metadata": {} + }, + { + "id": "e464da97-16a1-4772-9a07-0a47f152781d", + "cell_type": "code", + "source": "write_workflow_json(delayed_object=result, file_name=workflow_json_filename)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 9 + }, + { + "id": "bca646b2-0a9a-4271-966a-e5903a8c9031", + "cell_type": "code", + "source": "!cat {workflow_json_filename}", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "{\n \"version\": \"0.1.0\",\n \"nodes\": [\n {\n \"id\": 0,\n \"type\": \"function\",\n \"value\": \"workflow.get_square\"\n },\n {\n \"id\": 1,\n \"type\": \"function\",\n \"value\": \"workflow.get_sum\"\n },\n {\n \"id\": 2,\n \"type\": \"function\",\n \"value\": \"workflow.get_prod_and_div\"\n },\n {\n \"id\": 3,\n \"type\": \"input\",\n \"name\": \"x\",\n \"value\": 1\n },\n {\n \"id\": 4,\n \"type\": \"input\",\n \"name\": \"y\",\n \"value\": 2\n },\n {\n \"id\": 5,\n \"type\": \"output\",\n \"name\": \"result\"\n }\n ],\n \"edges\": [\n {\n \"target\": 0,\n \"targetPort\": \"x\",\n \"source\": 1,\n \"sourcePort\": null\n },\n {\n \"target\": 1,\n \"targetPort\": \"x\",\n \"source\": 2,\n \"sourcePort\": \"prod\"\n },\n {\n \"target\": 2,\n \"targetPort\": \"x\",\n \"source\": 3,\n \"sourcePort\": null\n },\n {\n \"target\": 2,\n \"targetPort\": \"y\",\n \"source\": 4,\n \"sourcePort\": null\n },\n {\n \"target\": 1,\n \"targetPort\": \"y\",\n \"source\": 2,\n \"sourcePort\": \"div\"\n },\n {\n \"target\": 5,\n \"targetPort\": null,\n \"source\": 0,\n \"sourcePort\": null\n }\n ]\n}" + } + ], + "execution_count": 10 + }, + { + "id": "a4c0faaf-e30d-4ded-8e9f-57f97f51b14c", + "cell_type": "markdown", + "source": "## Load Workflow with aiida\n\nThe exported `workflow.json` is loaded into `aiida-workgraph`. An AiiDA profile must be connected via `load_profile()` before the resulting `WorkGraph` can be run.", + "metadata": {} + }, + { + "id": "2ecc229f-daa1-49b9-9279-a6b5ae1aa4f2", + "cell_type": "code", + "source": "from aiida import load_profile\n\nload_profile()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 11, + "output_type": "execute_result", + "data": { + "text/plain": "Profile" + }, + "metadata": {} + } + ], + "execution_count": 11 + }, + { + "id": "68a56b32-9f99-43d7-aaee-0c1cd9522681", + "cell_type": "code", + "source": "from python_workflow_definition.aiida import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 12 + }, + { + "id": "8f2a621d-b533-4ddd-8bcd-c22db2f922ec", + "cell_type": "code", + "source": "wg = load_workflow_json(file_name=workflow_json_filename)\nwg", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 13, + "output_type": "execute_result", + "data": { + "text/plain": "NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'WorkGra…", + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 1, + "model_id": "f52e57854d6e4d07b6a2c11a75873efe" + } + }, + "metadata": {} + } + ], + "execution_count": 13 + }, + { + "id": "cf80267d-c2b0-4236-bf1d-a57596985fc1", + "cell_type": "code", + "source": "\nwg.run()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "05/24/2025 05:39:21 AM <524> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [19|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_prod_and_div3\n05/24/2025 05:39:21 AM <524> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [19|WorkGraphEngine|update_task_state]: Task: get_prod_and_div3, type: PyFunction, finished.\n05/24/2025 05:39:21 AM <524> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [19|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_sum2\n05/24/2025 05:39:21 AM <524> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [19|WorkGraphEngine|update_task_state]: Task: get_sum2, type: PyFunction, finished.\n05/24/2025 05:39:21 AM <524> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [19|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_square1\n05/24/2025 05:39:22 AM <524> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [19|WorkGraphEngine|update_task_state]: Task: get_square1, type: PyFunction, finished.\n05/24/2025 05:39:22 AM <524> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [19|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n05/24/2025 05:39:22 AM <524> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [19|WorkGraphEngine|finalize]: Finalize workgraph.\n" + } + ], + "execution_count": 14 + }, + { + "id": "0c3503e1-0a32-40e1-845d-3fd9ec3c4c19", + "cell_type": "markdown", + "source": "## Load Workflow with jobflow\n\nThe same JSON is loaded into a jobflow `Flow` and executed locally with `run_locally`.", + "metadata": {} + }, + { + "id": "4abb0481-8e38-479d-ae61-6c46d091653e", + "cell_type": "code", + "source": "from python_workflow_definition.jobflow import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 15 + }, + { + "id": "8253dd7c283bf3f7", + "cell_type": "code", + "source": "from jobflow.managers.local import run_locally", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 16 + }, + { + "id": "4b45e83b-945f-48c5-8e20-9df0ce0a14a1", + "cell_type": "code", + "source": "flow = load_workflow_json(file_name=workflow_json_filename)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 17 + }, + { + "id": "8665c39c-220c-4982-b738-c31f6460530f", + "cell_type": "code", + "source": "result = run_locally(flow)\nresult", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "2025-05-24 05:39:22,893 INFO Started executing jobs locally\n2025-05-24 05:39:23,184 INFO Starting job - get_prod_and_div (82cb13d7-d7c8-4bd1-84d1-c301d4ee2422)\n2025-05-24 05:39:23,187 INFO Finished job - get_prod_and_div (82cb13d7-d7c8-4bd1-84d1-c301d4ee2422)\n2025-05-24 05:39:23,187 INFO Starting job - get_sum (19c0830c-e918-44d2-82f1-b9418463c057)\n2025-05-24 05:39:23,189 INFO Finished job - get_sum (19c0830c-e918-44d2-82f1-b9418463c057)\n2025-05-24 05:39:23,189 INFO Starting job - get_square (78fc4e6e-2a99-490e-b829-fae9704296c2)\n2025-05-24 05:39:23,190 INFO Finished job - get_square (78fc4e6e-2a99-490e-b829-fae9704296c2)\n2025-05-24 05:39:23,191 INFO Finished executing jobs locally\n" + }, + { + "execution_count": 18, + "output_type": "execute_result", + "data": { + "text/plain": "{'82cb13d7-d7c8-4bd1-84d1-c301d4ee2422': {1: Response(output={'prod': 2, 'div': 0.5}, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/arithmetic'))},\n '19c0830c-e918-44d2-82f1-b9418463c057': {1: Response(output=2.5, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/arithmetic'))},\n '78fc4e6e-2a99-490e-b829-fae9704296c2': {1: Response(output=6.25, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/arithmetic'))}}" + }, + "metadata": {} + } + ], + "execution_count": 18 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## Load Workflow with pyiron_workflow\n\nFinally, the workflow is loaded into a `pyiron_workflow` `Workflow` object, drawn with `.draw()` and executed with `.run()`.", + "id": "406fd07dd4bd8006" + }, + { + "id": "cf76f305-24de-45a7-be8e-cfe45cd6458e", + "cell_type": "code", + "source": "from python_workflow_definition.pyiron_workflow import load_workflow_json", + "metadata": { + "trusted": true, + "ExecuteTime": { + "end_time": "2025-05-24T08:25:33.797570Z", + "start_time": "2025-05-24T08:25:33.771214Z" + } + }, + "outputs": [], + "execution_count": null + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf = load_workflow_json(file_name=workflow_json_filename)", + "id": "5b442611457aa5a8" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.draw(size=(10,10))", + "id": "2ca33c8590a54866" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.run()", + "id": "d36522a1c315b7f5" + } + ] +} \ No newline at end of file diff --git a/_sources/example_workflows/arithmetic/pyiron_workflow.ipynb b/_sources/example_workflows/arithmetic/pyiron_workflow.ipynb new file mode 100644 index 00000000..491322eb --- /dev/null +++ b/_sources/example_workflows/arithmetic/pyiron_workflow.ipynb @@ -0,0 +1,916 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "9db99131-e5ef-49a9-93f6-13c44782c119", + "metadata": {}, + "source": "# pyiron_workflow\n\nThis notebook defines the arithmetic workflow with [`pyiron_workflow`](https://github.com/pyiron/pyiron_workflow) and then loads the resulting `workflow.json` into `aiida-workgraph`, `jobflow` and `pyiron_base`." + }, + { + "cell_type": "markdown", + "id": "d16df60e-1359-4d4c-bb95-2b994860d04a", + "metadata": {}, + "source": "## Define workflow in pyiron_workflow\n\n`to_function_node` wraps a plain Python function into a `pyiron_workflow` node that can be added to a `Workflow` graph. Nodes are assembled into a graph with attribute access: assigning `wf. = node(...)` both registers the node under that name and connects its inputs to the outputs of other nodes already on the graph." + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "e19826e4-3540-4ea0-ba83-566e818ab6e3", + "metadata": {}, + "outputs": [], + "source": [ + "from python_workflow_definition.pyiron_workflow import write_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "f0d54cc1-3603-4c6e-a715-852a8ef1545f", + "metadata": {}, + "outputs": [], + "source": [ + "from pyiron_workflow._legacy import Workflow, to_function_node" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "9fa01739-812c-4188-b7af-320b4890c963", + "metadata": {}, + "outputs": [], + "source": [ + "from workflow import (\n", + " get_prod_and_div as _get_prod_and_div, \n", + " get_sum as _get_sum,\n", + " get_square as _get_square,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b8b236cc-d0ff-4a53-b01a-ecbb74f68b0f", + "metadata": {}, + "outputs": [], + "source": [ + "workflow_json_filename = \"pyiron_workflow_arithmetic.json\"" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "99037759-4d9e-43b2-8b04-341f2698bbe7", + "metadata": {}, + "outputs": [], + "source": [ + "get_prod_and_div = to_function_node(\"get_prod_and_div\", _get_prod_and_div, \"get_prod_and_div\")\n", + "get_sum = to_function_node(\"get_sum\", _get_sum, \"get_sum\")\n", + "get_square = to_function_node(\"get_square\", _get_square, \"get_square\")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "523a3561-315a-4345-a356-bd46774cc7dc", + "metadata": {}, + "outputs": [], + "source": [ + "wf = Workflow(\"my_workflow\")" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "92a67ce5-9c73-4018-8e70-ed95789a592e", + "metadata": {}, + "outputs": [], + "source": [ + "wf.x = 1\n", + "wf.y = 2\n", + "wf.prod_and_div = get_prod_and_div(x=wf.x, y=wf.y)\n", + "wf.tmp_sum = get_sum(x=wf.prod_and_div[\"prod\"], y=wf.prod_and_div[\"div\"])\n", + "wf.square_result = get_square(x=wf.tmp_sum)" + ] + }, + { + "cell_type": "markdown", + "id": "7d2460f1", + "source": "`wf.draw()` renders the resulting node graph, and `write_workflow_json` serializes `wf.graph_as_dict` into the PWD `workflow.json` format.", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "bafebfbe-72de-407c-b376-6fce6cbb665e", + "metadata": {}, + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "clustermy_workflow\n", + "\n", + "my_workflow: Workflow\n", + "\n", + "clustermy_workflowInputs\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "Inputs\n", + "\n", + "\n", + "clustermy_workflowOutputsWithInjection\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "OutputsWithInjection\n", + "\n", + "\n", + "clustermy_workflowprod_and_div\n", + 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+ "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wf.draw(size=(10,10))" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "f140ec87-085c-4433-93cb-379226781bd3", + "metadata": {}, + "outputs": [], + "source": [ + "write_workflow_json(graph_as_dict=wf.graph_as_dict, file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "c61b9a68-d1cd-4949-97b6-00451ba850b7", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"version\": \"0.1.0\",\n", + " \"nodes\": [\n", + " {\n", + " \"id\": 0,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.get_prod_and_div\"\n", + " },\n", + " {\n", + " \"id\": 1,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.get_sum\"\n", + " },\n", + " {\n", + " \"id\": 2,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.get_square\"\n", + " },\n", + " {\n", + " \"id\": 3,\n", + " \"type\": \"input\",\n", + " \"name\": \"x\",\n", + " \"value\": 1\n", + " },\n", + " {\n", + " \"id\": 4,\n", + " \"type\": \"input\",\n", + " \"name\": \"y\",\n", + " \"value\": 2\n", + " },\n", + " {\n", + " \"id\": 5,\n", + " \"type\": \"output\",\n", + " \"name\": \"result\"\n", + " }\n", + " ],\n", + " \"edges\": [\n", + " {\n", + " \"target\": 1,\n", + " \"targetPort\": \"y\",\n", + " \"source\": 0,\n", + " \"sourcePort\": \"div\"\n", + " },\n", + " {\n", + " \"target\": 1,\n", + " \"targetPort\": \"x\",\n", + " \"source\": 0,\n", + " \"sourcePort\": \"prod\"\n", + " },\n", + " {\n", + " \"target\": 2,\n", + " \"targetPort\": \"x\",\n", + " \"source\": 1,\n", + " \"sourcePort\": \"get_sum\"\n", + " },\n", + " {\n", + " \"target\": 0,\n", + " \"targetPort\": \"x\",\n", + " \"source\": 3,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 0,\n", + " \"targetPort\": \"y\",\n", + " \"source\": 4,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 5,\n", + " \"targetPort\": null,\n", + " \"source\": 2,\n", + " \"sourcePort\": null\n", + " }\n", + " ]\n", + "}" + ] + } + ], + "source": [ + "!cat workflow.json" + ] + }, + { + "cell_type": "markdown", + "id": "1681d449-0266-4da4-8d87-40a055cf3149", + "metadata": {}, + "source": "## Load Workflow with aiida\n\nThe exported `workflow.json` is loaded into `aiida-workgraph`. An AiiDA profile must be connected via `load_profile()` before the resulting `WorkGraph` can be run." + }, + { + "cell_type": "code", + "execution_count": null, + "id": "41b41ac3-7880-48dd-824e-7176187b8734", + "metadata": {}, + "outputs": [], + "source": [ + "from aiida import load_profile\n", + "\n", + "load_profile()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f6112a23-cdde-4346-88af-295f463940c5", + "metadata": {}, + "outputs": [], + "source": [ + "from python_workflow_definition.aiida import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "db6d30b6-2b42-4c07-b319-b6700e3c319b", + "metadata": {}, + "outputs": [], + "source": [ + "wg = load_workflow_json(file_name=workflow_json_filename)\n", + "wg" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "022066b4-21b3-41c6-b0ab-f40661fcf957", + "metadata": {}, + "outputs": [], + "source": [ + "wg.run()" + ] + }, + { + "cell_type": "markdown", + "id": "bac61097-e666-443b-9446-4ebb9a3e6b5f", + "metadata": {}, + "source": "## Load Workflow with jobflow\n\nThe same JSON is loaded into a jobflow `Flow` and executed locally with `run_locally`." + }, + { + "cell_type": "code", + "execution_count": null, + "id": "63df1efd-9417-4146-a88e-cde161962b9e", + "metadata": {}, + "outputs": [], + "source": [ + "from python_workflow_definition.jobflow import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6506e6cc-842c-4899-8382-696466d63a1b", + "metadata": {}, + "outputs": [], + "source": [ + "from jobflow.managers.local import run_locally" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "eed9ca1c-ad8d-440a-97f8-97b9d3d45eb0", + "metadata": {}, + "outputs": [], + "source": [ + "flow = load_workflow_json(file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "21c2303c-1118-4d50-9d99-6ec71653be02", + "metadata": {}, + "outputs": [], + "source": [ + "result = run_locally(flow)\n", + "result" + ] + }, + { + "cell_type": "markdown", + "id": "f26c9650-649f-436d-8d19-b2cd75cf6488", + "metadata": {}, + "source": "## Load Workflow with pyiron_base\n\nFinally, the workflow is loaded into `pyiron_base`, producing a list of delayed jobs. `.draw()` visualizes the dependency graph and `.pull()` triggers delayed execution of the whole chain." + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0ada4861-0e5a-4baf-9e16-42b7c238558b", + "metadata": {}, + "outputs": [], + "source": [ + "from python_workflow_definition.pyiron_base import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7ac2fd45-e88a-4d12-b4e3-b23212729730", + "metadata": {}, + "outputs": [], + "source": [ + "delayed_object_lst = load_workflow_json(file_name=workflow_json_filename)\n", + "delayed_object_lst[-1].draw()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e8811199-2c2d-4613-be74-cc00508d97c4", + "metadata": {}, + "outputs": [], + "source": [ + "delayed_object_lst[-1].pull()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/_sources/example_workflows/arithmetic/universal_workflow.ipynb b/_sources/example_workflows/arithmetic/universal_workflow.ipynb new file mode 100644 index 00000000..a100ed2d --- /dev/null +++ b/_sources/example_workflows/arithmetic/universal_workflow.ipynb @@ -0,0 +1,357 @@ +{ + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.12.8", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + } + }, + "nbformat_minor": 4, + "nbformat": 4, + "cells": [ + { + "cell_type": "markdown", + "source": "# Load Simple Workflow\n\nThis notebook loads a single, pre-existing `workflow.json` with several different engines in turn. Since the JSON only describes function nodes, inputs, outputs and the edges between them, it does not matter which engine originally wrote it — any of the engines below can load and execute it.", + "metadata": {} + }, + { + "cell_type": "markdown", + "source": "## Plot\n\nBefore running the workflow with any engine, `python_workflow_definition.plot.plot` renders `workflow.json` directly as a graph of function, input and output nodes — independent of any particular workflow engine.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.plot import plot", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 1 + }, + { + "cell_type": "code", + "source": "plot(file_name='workflow.json')", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "", + "image/svg+xml": "\n\n\n\n\n0\n\nworkflow.get_prod_and_div\n\n\n\n1\n\nworkflow.get_sum\n\n\n\n0->1\n\n\n\n\n\n2\n\nworkflow.get_square\n\n\n\n1->2\n\n\nx\n\n\n\n5\n\nresult\n\n\n\n2->5\n\n\n\n\n\n3\n\n1\n\n\n\n3->0\n\n\nx\n\n\n\n4\n\n2\n\n\n\n4->0\n\n\ny\n\n\n" + }, + "metadata": {} + } + ], + "execution_count": 2 + }, + { + "cell_type": "markdown", + "source": "## Aiida\n\nLoading the JSON into `aiida-workgraph` requires connecting to an AiiDA profile first via `load_profile()`; the workflow is then reconstructed as a `WorkGraph` and executed with `.run()`.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.aiida import load_workflow_json\n\nfrom aiida import load_profile\nload_profile()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 3, + "output_type": "execute_result", + "data": { + "text/plain": "Profile" + }, + "metadata": {} + } + ], + "execution_count": 3 + }, + { + "cell_type": "code", + "source": "workgraph = load_workflow_json(file_name='workflow.json')", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 4 + }, + { + "cell_type": "code", + "source": "# TODO: Create inputs rather than tasks out of data nodes\nworkgraph", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 5, + "output_type": "execute_result", + "data": { + "text/plain": "NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'WorkGra…", + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 1, + "model_id": "fc63f59e75a74fbcab9e44a06ecb6d18" + } + }, + "metadata": {} + } + ], + "execution_count": 5 + }, + { + "cell_type": "code", + "source": "\nworkgraph.run()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "05/24/2025 05:39:46 AM <644> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [35|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_prod_and_div1\n05/24/2025 05:39:46 AM <644> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [35|WorkGraphEngine|update_task_state]: Task: get_prod_and_div1, type: PyFunction, finished.\n05/24/2025 05:39:46 AM <644> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [35|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_sum2\n05/24/2025 05:39:47 AM <644> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [35|WorkGraphEngine|update_task_state]: Task: get_sum2, type: PyFunction, finished.\n05/24/2025 05:39:47 AM <644> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [35|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_square3\n05/24/2025 05:39:47 AM <644> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [35|WorkGraphEngine|update_task_state]: Task: get_square3, type: PyFunction, finished.\n05/24/2025 05:39:47 AM <644> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [35|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n05/24/2025 05:39:47 AM <644> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [35|WorkGraphEngine|finalize]: Finalize workgraph.\n" + } + ], + "execution_count": 6 + }, + { + "cell_type": "markdown", + "source": "## executorlib\n\n`python_workflow_definition.executorlib.load_workflow_json` submits each function node to the given `Executor` and returns the `Future` of the final node; calling `.result()` blocks until the whole chain has completed.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from executorlib import SingleNodeExecutor", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 7 + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.executorlib import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 8 + }, + { + "cell_type": "code", + "source": "with SingleNodeExecutor(max_workers=1) as exe:\n result = load_workflow_json(file_name=\"workflow.json\", exe=exe).result()", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 9 + }, + { + "cell_type": "code", + "source": "result", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 10, + "output_type": "execute_result", + "data": { + "text/plain": "6.25" + }, + "metadata": {} + } + ], + "execution_count": 10 + }, + { + "cell_type": "markdown", + "source": "## Jobflow\n\nThe JSON is reconstructed as a jobflow `Flow` and executed locally with `run_locally`.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from jobflow.managers.local import run_locally", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 11 + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.jobflow import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 12 + }, + { + "cell_type": "code", + "source": "flow = load_workflow_json(file_name=\"workflow.json\")", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 13 + }, + { + "cell_type": "code", + "source": "result = run_locally(flow)\nresult", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "2025-05-24 05:39:49,427 INFO Started executing jobs locally\n2025-05-24 05:39:49,510 INFO Starting job - get_prod_and_div (f82f13df-44cc-4bce-8712-ab5a1408c551)\n2025-05-24 05:39:49,512 INFO Finished job - get_prod_and_div (f82f13df-44cc-4bce-8712-ab5a1408c551)\n2025-05-24 05:39:49,513 INFO Starting job - get_sum (bb1c3b6d-986a-4e5d-b2f4-6611940ba4c6)\n2025-05-24 05:39:49,514 INFO Finished job - get_sum (bb1c3b6d-986a-4e5d-b2f4-6611940ba4c6)\n2025-05-24 05:39:49,515 INFO Starting job - get_square (5c60ac07-39fd-4511-93d8-3bd65c6bd7ca)\n2025-05-24 05:39:49,516 INFO Finished job - get_square (5c60ac07-39fd-4511-93d8-3bd65c6bd7ca)\n2025-05-24 05:39:49,516 INFO Finished executing jobs locally\n" + }, + { + "execution_count": 14, + "output_type": "execute_result", + "data": { + "text/plain": "{'f82f13df-44cc-4bce-8712-ab5a1408c551': {1: Response(output={'prod': 2, 'div': 0.5}, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/arithmetic'))},\n 'bb1c3b6d-986a-4e5d-b2f4-6611940ba4c6': {1: Response(output=2.5, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/arithmetic'))},\n '5c60ac07-39fd-4511-93d8-3bd65c6bd7ca': {1: Response(output=6.25, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/arithmetic'))}}" + }, + "metadata": {} + } + ], + "execution_count": 14 + }, + { + "cell_type": "markdown", + "source": "## pyiron\n\nLoading the JSON into `pyiron_base` produces a list of delayed jobs; `.draw()` visualizes the dependency graph and `.pull()` triggers execution of the whole chain.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.pyiron_base import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 15 + }, + { + "cell_type": "code", + "source": "delayed_object_lst = load_workflow_json(file_name=\"workflow.json\")\ndelayed_object_lst[-1].draw()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "", + "image/svg+xml": "\n\n\n\n\ncreate_function_job_25906340bd0c28c44fd73d69e7a3d8bc\n\ncreate_function_job=<pyiron_base.project.delayed.DelayedObject object at 0x749611736a50>\n\n\n\nx_1a7fff02f6473a13e5e8742988186611\n\nx=<pyiron_base.project.delayed.DelayedObject object at 0x7496117367e0>\n\n\n\nx_1a7fff02f6473a13e5e8742988186611->create_function_job_25906340bd0c28c44fd73d69e7a3d8bc\n\n\n\n\n\nx_e4655695917c433de56d1c64232473f9\n\nx=<pyiron_base.project.delayed.DelayedObject object at 0x74961213ea50>\n\n\n\nx_e4655695917c433de56d1c64232473f9->x_1a7fff02f6473a13e5e8742988186611\n\n\n\n\n\nx_1d847da32ecaabf6731c38f798c3d4ce\n\nx=1\n\n\n\nx_1d847da32ecaabf6731c38f798c3d4ce->x_e4655695917c433de56d1c64232473f9\n\n\n\n\n\ny_3b83397feef07a74d9a046a1b7f57749\n\ny=<pyiron_base.project.delayed.DelayedObject object at 0x74961eca0a10>\n\n\n\nx_1d847da32ecaabf6731c38f798c3d4ce->y_3b83397feef07a74d9a046a1b7f57749\n\n\n\n\n\ny_3b83397feef07a74d9a046a1b7f57749->x_1a7fff02f6473a13e5e8742988186611\n\n\n\n\n\ny_a9ec4f5f33f0d64e74ed5d9900bceac6\n\ny=2\n\n\n\ny_a9ec4f5f33f0d64e74ed5d9900bceac6->x_e4655695917c433de56d1c64232473f9\n\n\n\n\n\ny_a9ec4f5f33f0d64e74ed5d9900bceac6->y_3b83397feef07a74d9a046a1b7f57749\n\n\n\n\n" + }, + "metadata": {} + } + ], + "execution_count": 16 + }, + { + "cell_type": "code", + "source": "delayed_object_lst[-1].pull()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "The job get_prod_and_div_00cf2c787390eacfbc4a51e9a0c38ec7 was saved and received the ID: 1\nThe job get_sum_4b5b9d16b259a13b6a32798ce2779af8 was saved and received the ID: 2\nThe job get_square_9cc2f0545498916d7720c59c1120a66d was saved and received the ID: 3\n" + }, + { + "execution_count": 17, + "output_type": "execute_result", + "data": { + "text/plain": "6.25" + }, + "metadata": {} + } + ], + "execution_count": 17 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## pyiron_workflow\n\nFinally, the workflow is loaded into a `pyiron_workflow` `Workflow` object, drawn with `.draw()` and executed with `.run()`." + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "from python_workflow_definition.pyiron_workflow import load_workflow_json" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf = load_workflow_json(file_name=\"workflow.json\")" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.draw(size=(10,10))" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.run()" + }, + { + "cell_type": "markdown", + "source": "## Python\n\nAs a baseline, `python_workflow_definition.purepython.load_workflow_json` interprets the JSON directly in plain Python, with no workflow engine involved: it evaluates each function node in dependency order and returns the final result.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.purepython import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 18 + }, + { + "cell_type": "code", + "source": "load_workflow_json(file_name=\"workflow.json\")", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 19, + "output_type": "execute_result", + "data": { + "text/plain": "6.25" + }, + "metadata": {} + } + ], + "execution_count": 19 + } + ] +} \ No newline at end of file diff --git a/_sources/example_workflows/nfdi/aiida.ipynb b/_sources/example_workflows/nfdi/aiida.ipynb new file mode 100644 index 00000000..ef72f1bf --- /dev/null +++ b/_sources/example_workflows/nfdi/aiida.ipynb @@ -0,0 +1,416 @@ +{ + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.12.8", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + } + }, + "nbformat_minor": 5, + "nbformat": 4, + "cells": [ + { + "id": "106ded66-d202-46ac-82b0-2755ca309bdd", + "cell_type": "markdown", + "source": "# Aiida\n\nhttps://github.com/BAMresearch/NFDI4IngScientificWorkflowRequirements\n\nThis notebook defines the NFDI4Ing file-based workflow benchmark with [`aiida-workgraph`](https://github.com/aiidateam/aiida-workgraph) and then loads the resulting `workflow.json` into `jobflow`, `pyiron_base` and `pyiron_workflow` to show that the same JSON file can be executed by different engines. Every stage of the workflow calls an external command-line tool (`gmsh`, `meshio`, a FEniCS-based Poisson solver, ParaView's `pvbatch`, `tectonic`) in its own conda environment and passes file paths between stages rather than in-memory Python objects — see [`workflow.py`](workflow.py) for the six pipeline functions.", + "metadata": {} + }, + { + "id": "11e09b78-cb72-465f-9c8b-5b77f0aa729c", + "cell_type": "markdown", + "source": "## Define workflow with aiida\n\n`aiida-workgraph` represents a workflow as a `WorkGraph` of `Task`s. `load_profile()` connects to the local AiiDA profile/database that stores provenance and results for every task. `generate_mesh`, `plot_over_line`, `substitute_macros` and `compile_paper` each return a single value and can be added to the graph unchanged, but `convert_to_xdmf` and `poisson` return a `dict`, so they are wrapped with `task(outputs=[...])` to expose each dictionary key as its own output socket that later tasks can connect to.", + "metadata": {} + }, + { + "id": "17173d54-dc76-4052-ab39-d44771ac903d", + "cell_type": "code", + "source": "import os", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 1 + }, + { + "id": "89c02460-b543-442c-a27e-f1757dc2262e", + "cell_type": "code", + "source": "from python_workflow_definition.aiida import write_workflow_json\n\nfrom aiida_workgraph import WorkGraph, task\nfrom aiida import orm, load_profile\nload_profile()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 2, + "output_type": "execute_result", + "data": { + "text/plain": "Profile" + }, + "metadata": {} + } + ], + "execution_count": 2 + }, + { + "id": "6dac225a1ce86b25", + "cell_type": "code", + "source": "from workflow import (\n generate_mesh,\n convert_to_xdmf as _convert_to_xdmf,\n poisson as _poisson,\n plot_over_line,\n substitute_macros,\n compile_paper,\n)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 3 + }, + { + "id": "c47205d289499756", + "cell_type": "code", + "source": "convert_to_xdmf = task(outputs=[\"xdmf_file\", \"h5_file\"])(_convert_to_xdmf)\npoisson = task(outputs=[\"numdofs\", \"pvd_file\", \"vtu_file\"])(_poisson)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 4 + }, + { + "cell_type": "markdown", + "id": "e16e7b61", + "source": "AiiDA tracks every input as a typed, storable node, so the shared `domain_size` and `source_directory` values are wrapped as `orm.Float` and `orm.Str` before being connected to any task.", + "metadata": {} + }, + { + "id": "37c9d988-1755-446c-9f7b-c32f99e280d4", + "cell_type": "code", + "source": "source_directory = orm.Str(os.path.abspath(os.path.join(os.curdir, \"source\")))", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 5 + }, + { + "id": "8d911f98-3b80-457f-a0f4-3cb37ebf1691", + "cell_type": "code", + "source": "domain_size = orm.Float(2.0)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 6 + }, + { + "id": "1e7e14ba-c4a7-485f-9bd8-44625830cca0", + "cell_type": "code", + "source": "wg = WorkGraph(\"wg-nfdi\")", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 7 + }, + { + "cell_type": "markdown", + "id": "2e764162", + "source": "Each `wg.add_task` call below adds one stage of the pipeline: mesh generation, XDMF conversion, the Poisson solve, line-plot postprocessing, LaTeX macro substitution and paper compilation. Outputs are wired to the next task's inputs with `.outputs.`; since the underlying functions communicate through files on disk, these connections are really file paths handed from one task to the next, not shared Python objects.", + "metadata": {} + }, + { + "id": "71d411b6-cbec-489e-99e3-ba71680bcb5b", + "cell_type": "code", + "source": "gmsh_output_file = wg.add_task(\n generate_mesh,\n domain_size=domain_size,\n source_directory=source_directory,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 8 + }, + { + "id": "1d0d9804-f250-48b3-a5d0-a546d520f79b", + "cell_type": "code", + "source": "meshio_output_dict = wg.add_task(\n convert_to_xdmf,\n gmsh_output_file=gmsh_output_file.outputs.result,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 9 + }, + { + "id": "7b69bcff-e2b1-4d4a-b62c-6a1c86eeb590", + "cell_type": "code", + "source": "poisson_dict = wg.add_task(\n poisson,\n meshio_output_xdmf=meshio_output_dict.outputs.xdmf_file, \n meshio_output_h5=meshio_output_dict.outputs.h5_file,\n source_directory=source_directory,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 10 + }, + { + "id": "3c4a29b0-eb1e-490a-8be0-e03cfff15e0a", + "cell_type": "code", + "source": "pvbatch_output_file = wg.add_task(\n plot_over_line,\n poisson_output_pvd_file=poisson_dict.outputs.pvd_file, \n poisson_output_vtu_file=poisson_dict.outputs.vtu_file,\n source_directory=source_directory,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 11 + }, + { + "id": "a0a4c233-322d-4723-9627-62ca2487bfa9", + "cell_type": "code", + "source": "macros_tex_file = wg.add_task(\n substitute_macros,\n pvbatch_output_file=pvbatch_output_file.outputs.result, \n ndofs=poisson_dict.outputs.numdofs, \n domain_size=domain_size,\n source_directory=source_directory,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 12 + }, + { + "id": "c281408f-e63d-4380-a7e6-c595d49fbb8f", + "cell_type": "code", + "source": "paper_output = wg.add_task(\n compile_paper,\n macros_tex=macros_tex_file.outputs.result, \n plot_file=pvbatch_output_file.outputs.result,\n source_directory=source_directory,\n)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 13 + }, + { + "id": "a384d70a-8ef5-4fdd-880c-56ac7eaf87b9", + "cell_type": "code", + "source": "wg", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 14, + "output_type": "execute_result", + "data": { + "text/plain": "NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'wg-nfdi…", + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 1, + "model_id": "17520c019e5c413fb7a119ecc997c3ea" + } + }, + "metadata": {} + } + ], + "execution_count": 14 + }, + { + "cell_type": "markdown", + "id": "a7bd7df7", + "source": "The `wg` widget above renders the assembled task graph. Once satisfied, `write_workflow_json` serializes it into the PWD `workflow.json` format — one `function` node per task, `input` nodes for `domain_size`/`source_directory`, and edges recording which task output feeds which task's input port, as shown by the `cat` output below.", + "metadata": {} + }, + { + "id": "fb23ad9c-76fd-4c0b-b546-e305d6c49796", + "cell_type": "code", + "source": "workflow_json_filename = \"aiida_nfdi.json\"", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 15 + }, + { + "id": "4139547a-9717-4708-b1a5-8202a0382d77", + "cell_type": "code", + "source": "write_workflow_json(wg=wg, file_name=workflow_json_filename)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 16 + }, + { + "id": "490df6a3-e402-4620-acf2-dbcfa0c5d537", + "cell_type": "code", + "source": "!cat {workflow_json_filename}", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "{\n \"version\": \"0.1.0\",\n \"nodes\": [\n {\n \"id\": 0,\n \"type\": \"function\",\n \"value\": \"workflow.generate_mesh\"\n },\n {\n \"id\": 1,\n \"type\": \"function\",\n \"value\": \"workflow.convert_to_xdmf\"\n },\n {\n \"id\": 2,\n \"type\": \"function\",\n \"value\": \"workflow.poisson\"\n },\n {\n \"id\": 3,\n \"type\": \"function\",\n \"value\": \"workflow.plot_over_line\"\n },\n {\n \"id\": 4,\n \"type\": \"function\",\n \"value\": \"workflow.substitute_macros\"\n },\n {\n \"id\": 5,\n \"type\": \"function\",\n \"value\": \"workflow.compile_paper\"\n },\n {\n \"id\": 6,\n \"type\": \"input\",\n \"name\": \"domain_size\",\n \"value\": 2.0\n },\n {\n \"id\": 7,\n \"type\": \"input\",\n \"name\": \"source_directory\",\n \"value\": \"/home/jovyan/example_workflows/nfdi/source\"\n },\n {\n \"id\": 8,\n \"type\": \"output\",\n \"name\": \"result\"\n }\n ],\n \"edges\": [\n {\n \"target\": 1,\n \"targetPort\": \"gmsh_output_file\",\n \"source\": 0,\n \"sourcePort\": null\n },\n {\n \"target\": 2,\n \"targetPort\": \"meshio_output_xdmf\",\n \"source\": 1,\n \"sourcePort\": \"xdmf_file\"\n },\n {\n \"target\": 2,\n \"targetPort\": \"meshio_output_h5\",\n \"source\": 1,\n \"sourcePort\": \"h5_file\"\n },\n {\n \"target\": 3,\n \"targetPort\": \"poisson_output_pvd_file\",\n \"source\": 2,\n \"sourcePort\": \"pvd_file\"\n },\n {\n \"target\": 3,\n \"targetPort\": \"poisson_output_vtu_file\",\n \"source\": 2,\n \"sourcePort\": \"vtu_file\"\n },\n {\n \"target\": 4,\n \"targetPort\": \"pvbatch_output_file\",\n \"source\": 3,\n \"sourcePort\": null\n },\n {\n \"target\": 4,\n \"targetPort\": \"ndofs\",\n \"source\": 2,\n \"sourcePort\": \"numdofs\"\n },\n {\n \"target\": 5,\n \"targetPort\": \"macros_tex\",\n \"source\": 4,\n \"sourcePort\": null\n },\n {\n \"target\": 5,\n \"targetPort\": \"plot_file\",\n \"source\": 3,\n \"sourcePort\": null\n },\n {\n \"target\": 0,\n \"targetPort\": \"domain_size\",\n \"source\": 6,\n \"sourcePort\": null\n },\n {\n \"target\": 0,\n \"targetPort\": \"source_directory\",\n \"source\": 7,\n \"sourcePort\": null\n },\n {\n \"target\": 2,\n \"targetPort\": \"source_directory\",\n \"source\": 7,\n \"sourcePort\": null\n },\n {\n \"target\": 3,\n \"targetPort\": \"source_directory\",\n \"source\": 7,\n \"sourcePort\": null\n },\n {\n \"target\": 4,\n \"targetPort\": \"domain_size\",\n \"source\": 6,\n \"sourcePort\": null\n },\n {\n \"target\": 4,\n \"targetPort\": \"source_directory\",\n \"source\": 7,\n \"sourcePort\": null\n },\n {\n \"target\": 5,\n \"targetPort\": \"source_directory\",\n \"source\": 7,\n \"sourcePort\": null\n },\n {\n \"target\": 8,\n \"targetPort\": null,\n \"source\": 5,\n \"sourcePort\": null\n }\n ]\n}" + } + ], + "execution_count": 17 + }, + { + "id": "11a829e2-face-469f-b343-2c95763b1f13", + "cell_type": "markdown", + "source": "## Load Workflow with jobflow\n\n`python_workflow_definition.jobflow.load_workflow_json` reconstructs the same six-stage pipeline as a jobflow `Flow`, purely from `aiida_nfdi.json` — no reference to the `aiida-workgraph` objects defined above. `run_locally` then executes the jobs in dependency order, re-running `gmsh`, `meshio`, the Poisson solver, `pvbatch` and `tectonic` exactly as before.", + "metadata": {} + }, + { + "id": "4f3acabe-55df-479a-af4d-a23a80c4660d", + "cell_type": "code", + "source": "from python_workflow_definition.jobflow import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 18 + }, + { + "id": "b6ba9444-a2c8-451b-b74c-19b0f69ba369", + "cell_type": "code", + "source": "from jobflow.managers.local import run_locally", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 19 + }, + { + "id": "c3528d55-6bf7-47ed-a110-65c47446ba92", + "cell_type": "code", + "source": "flow = load_workflow_json(file_name=workflow_json_filename)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 20 + }, + { + "id": "5ef48778-4209-425f-8c6b-85a4cd2f92ec", + "cell_type": "code", + "source": "result = run_locally(flow)\nresult", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "2025-05-24 05:41:02,340 INFO Started executing jobs locally\n2025-05-24 05:41:02,615 INFO Starting job - generate_mesh (1c3eab15-7639-4f4e-9ca7-7523ba640ca5)\n2025-05-24 05:41:03,800 INFO Finished job - generate_mesh (1c3eab15-7639-4f4e-9ca7-7523ba640ca5)\n2025-05-24 05:41:03,801 INFO Starting job - convert_to_xdmf (07acbed1-2abb-4141-896d-170b58aba7c2)\n2025-05-24 05:41:05,099 INFO Finished job - convert_to_xdmf (07acbed1-2abb-4141-896d-170b58aba7c2)\n2025-05-24 05:41:05,100 INFO Starting job - poisson (b212b743-f36d-4f7b-a64a-79060469f34b)\n2025-05-24 05:41:12,945 INFO Finished job - poisson (b212b743-f36d-4f7b-a64a-79060469f34b)\n2025-05-24 05:41:12,946 INFO Starting job - plot_over_line (af5a3a54-b7fa-45f8-a70f-7f95d23c32c4)\n2025-05-24 05:41:14,360 INFO Finished job - plot_over_line (af5a3a54-b7fa-45f8-a70f-7f95d23c32c4)\n2025-05-24 05:41:14,360 INFO Starting job - substitute_macros (ec55c04a-a5cb-4d8f-9981-961f7297532e)\n2025-05-24 05:41:15,171 INFO Finished job - substitute_macros (ec55c04a-a5cb-4d8f-9981-961f7297532e)\n2025-05-24 05:41:15,172 INFO Starting job - compile_paper (629539b7-2541-4ba7-9546-b7adb0cc312e)\n2025-05-24 05:42:14,698 INFO Finished job - compile_paper (629539b7-2541-4ba7-9546-b7adb0cc312e)\n2025-05-24 05:42:14,699 INFO Finished executing jobs locally\n" + }, + { + "execution_count": 21, + "output_type": "execute_result", + "data": { + "text/plain": "{'1c3eab15-7639-4f4e-9ca7-7523ba640ca5': {1: Response(output='/home/jovyan/example_workflows/nfdi/preprocessing/square.msh', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n '07acbed1-2abb-4141-896d-170b58aba7c2': {1: Response(output={'xdmf_file': '/home/jovyan/example_workflows/nfdi/preprocessing/square.xdmf', 'h5_file': '/home/jovyan/example_workflows/nfdi/preprocessing/square.h5'}, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n 'b212b743-f36d-4f7b-a64a-79060469f34b': {1: Response(output={'numdofs': 357, 'pvd_file': '/home/jovyan/example_workflows/nfdi/processing/poisson.pvd', 'vtu_file': '/home/jovyan/example_workflows/nfdi/processing/poisson000000.vtu'}, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n 'af5a3a54-b7fa-45f8-a70f-7f95d23c32c4': {1: Response(output='/home/jovyan/example_workflows/nfdi/postprocessing/plotoverline.csv', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n 'ec55c04a-a5cb-4d8f-9981-961f7297532e': {1: Response(output='/home/jovyan/example_workflows/nfdi/postprocessing/macros.tex', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n '629539b7-2541-4ba7-9546-b7adb0cc312e': {1: Response(output='/home/jovyan/example_workflows/nfdi/postprocessing/paper.pdf', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))}}" + }, + "metadata": {} + } + ], + "execution_count": 21 + }, + { + "id": "397b16a2-e1ec-4eec-8562-1c84f585c347", + "cell_type": "markdown", + "source": "## Load Workflow with pyiron_base\n\n`python_workflow_definition.pyiron_base.load_workflow_json` turns the JSON graph into a list of delayed pyiron jobs; `.draw()` visualizes their dependencies and `.pull()` triggers execution, running each job in turn and returning the final `paper.pdf` path.", + "metadata": {} + }, + { + "id": "be4d5d93-e9f6-4072-a6be-0ee5dc93590f", + "cell_type": "code", + "source": "from python_workflow_definition.pyiron_base import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 22 + }, + { + "id": "4452a648-d4c3-4f5f-8678-ffb54bef17dc", + "cell_type": "code", + "source": "delayed_object_lst = load_workflow_json(file_name=workflow_json_filename)\ndelayed_object_lst[-1].draw()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "", + "image/svg+xml": "\n\n\n\n\ncreate_function_job_724cfd00ffeb70f8b463a938195e0447\n\ncreate_function_job=<pyiron_base.project.delayed.DelayedObject object at 0x74ee3cf38aa0>\n\n\n\nmacros_tex_b52804e5fa845b3657fa99b738e02cf7\n\nmacros_tex=<pyiron_base.project.delayed.DelayedObject object at 0x74ee3cf38830>\n\n\n\nmacros_tex_b52804e5fa845b3657fa99b738e02cf7->create_function_job_724cfd00ffeb70f8b463a938195e0447\n\n\n\n\n\npvbatch_output_file_554a54a50a86b23416c0daf6ab0938df\n\npvbatch_output_file=<pyiron_base.project.delayed.DelayedObject object at 0x74ee3cf38500>\n\n\n\npvbatch_output_file_554a54a50a86b23416c0daf6ab0938df->macros_tex_b52804e5fa845b3657fa99b738e02cf7\n\n\n\n\n\npoisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9\n\npoisson_output_pvd_file=<pyiron_base.project.delayed.DelayedObject object at 0x74ee3cf07a10>\n\n\n\npoisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9->pvbatch_output_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\nplot_file_554a54a50a86b23416c0daf6ab0938df\n\nplot_file=<pyiron_base.project.delayed.DelayedObject object at 0x74ee3cf38500>\n\n\n\npoisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9->plot_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\nplot_file_554a54a50a86b23416c0daf6ab0938df->create_function_job_724cfd00ffeb70f8b463a938195e0447\n\n\n\n\n\nmeshio_output_xdmf_52103bbf2f92608bdb3c6bedb045e0e1\n\nmeshio_output_xdmf=<pyiron_base.project.delayed.DelayedObject object at 0x74ee3cf07da0>\n\n\n\nmeshio_output_xdmf_52103bbf2f92608bdb3c6bedb045e0e1->poisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9\n\n\n\n\n\npoisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810\n\npoisson_output_vtu_file=<pyiron_base.project.delayed.DelayedObject object at 0x74ee3cf381a0>\n\n\n\nmeshio_output_xdmf_52103bbf2f92608bdb3c6bedb045e0e1->poisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810\n\n\n\n\n\nndofs_e826761b60042b070e0c0a24b472ee26\n\nndofs=<pyiron_base.project.delayed.DelayedObject object at 0x74ee3cf38590>\n\n\n\nmeshio_output_xdmf_52103bbf2f92608bdb3c6bedb045e0e1->ndofs_e826761b60042b070e0c0a24b472ee26\n\n\n\n\n\npoisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810->pvbatch_output_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\npoisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810->plot_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\nndofs_e826761b60042b070e0c0a24b472ee26->macros_tex_b52804e5fa845b3657fa99b738e02cf7\n\n\n\n\n\ngmsh_output_file_553a0d07e32ca83a3640e955a7b868a4\n\ngmsh_output_file=<pyiron_base.project.delayed.DelayedObject object at 0x74ee3cf07b00>\n\n\n\ngmsh_output_file_553a0d07e32ca83a3640e955a7b868a4->meshio_output_xdmf_52103bbf2f92608bdb3c6bedb045e0e1\n\n\n\n\n\nmeshio_output_h5_0e11ecf3d5834e399bb91f99309bf3fe\n\nmeshio_output_h5=<pyiron_base.project.delayed.DelayedObject object at 0x74ee3cf07d70>\n\n\n\ngmsh_output_file_553a0d07e32ca83a3640e955a7b868a4->meshio_output_h5_0e11ecf3d5834e399bb91f99309bf3fe\n\n\n\n\n\nmeshio_output_h5_0e11ecf3d5834e399bb91f99309bf3fe->poisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9\n\n\n\n\n\nmeshio_output_h5_0e11ecf3d5834e399bb91f99309bf3fe->poisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810\n\n\n\n\n\nmeshio_output_h5_0e11ecf3d5834e399bb91f99309bf3fe->ndofs_e826761b60042b070e0c0a24b472ee26\n\n\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20\n\ndomain_size=2.0\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20->macros_tex_b52804e5fa845b3657fa99b738e02cf7\n\n\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20->gmsh_output_file_553a0d07e32ca83a3640e955a7b868a4\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696\n\nsource_directory=/home/jovyan/example_workflows/nfdi/source\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->create_function_job_724cfd00ffeb70f8b463a938195e0447\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->macros_tex_b52804e5fa845b3657fa99b738e02cf7\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->pvbatch_output_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->poisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->plot_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->poisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->ndofs_e826761b60042b070e0c0a24b472ee26\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->gmsh_output_file_553a0d07e32ca83a3640e955a7b868a4\n\n\n\n\n" + }, + "metadata": {} + } + ], + "execution_count": 23 + }, + { + "id": "1c2760b6-96b4-4f44-ac49-a229d4a0cf67", + "cell_type": "code", + "source": "delayed_object_lst[-1].pull()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "The job generate_mesh_47725c16637f799ac042e47468005db3 was saved and received the ID: 1\nThe job convert_to_xdmf_d6a46eb9a4ec352aa996e783ec3c785f was saved and received the ID: 2\nThe job poisson_3c147fc86db87cf0c0f94bda333f8cd8 was saved and received the ID: 3\nThe job plot_over_line_ef50933291910dadcc8311924971e127 was saved and received the ID: 4\nThe job substitute_macros_63766eafd6b1980c7832dd8c9a97c96e was saved and received the ID: 5\nThe job compile_paper_128d1d58374953c00e95b8de62cbb10b was saved and received the ID: 6\n" + }, + { + "execution_count": 24, + "output_type": "execute_result", + "data": { + "text/plain": "'/home/jovyan/example_workflows/nfdi/postprocessing/paper.pdf'" + }, + "metadata": {} + } + ], + "execution_count": 24 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## Load Workflow with pyiron_workflow\n\nFinally, the same JSON is loaded into a `pyiron_workflow` `Workflow` object. `.draw()` shows the node graph and `.run()` executes it end to end, again shelling out to each external tool in turn.", + "id": "afaf2bc0b3a491ca" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "from python_workflow_definition.pyiron_workflow import load_workflow_json", + "id": "6172b410eb776fc4" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf = load_workflow_json(file_name=workflow_json_filename)", + "id": "668fe64b18b4d604" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.draw(size=(10,10))", + "id": "8c4fd72394841ffa" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.run()", + "id": "c1427e3ce0716f64" + } + ] +} \ No newline at end of file diff --git a/_sources/example_workflows/nfdi/cwl.ipynb b/_sources/example_workflows/nfdi/cwl.ipynb new file mode 100644 index 00000000..5fc2d266 --- /dev/null +++ b/_sources/example_workflows/nfdi/cwl.ipynb @@ -0,0 +1,171 @@ +{ + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.12.8", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + } + }, + "nbformat_minor": 5, + "nbformat": 4, + "cells": [ + { + "cell_type": "markdown", + "id": "e88c3a45", + "source": "# CWL\n\nThis notebook executes the NFDI4Ing file-based workflow benchmark's `workflow.json` with the [Common Workflow Language](https://www.commonwl.org/) via [`cwltool`](https://github.com/common-workflow-language/cwltool), instead of generating the JSON from a Python workflow engine like the other notebooks in this directory. `python_workflow_definition.cwl.write_workflow` translates the PWD graph into a CWL `workflow.cwl` plus one `CommandLineTool` wrapper per pipeline function; CWL then passes data between steps as pickled files on disk rather than in-memory Python objects, which matches this benchmark's file-based nature.", + "metadata": {} + }, + { + "id": "377fef56-484d-491c-b19e-1be6931e44eb", + "cell_type": "code", + "source": "import pickle", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 1 + }, + { + "id": "2033dda1-dc7a-4f96-b1bd-90505b0ec555", + "cell_type": "code", + "source": "import json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 2 + }, + { + "id": "60cb8ace-acb0-47b4-b0bc-bb54d00d19dd", + "cell_type": "code", + "source": "import os", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 3 + }, + { + "id": "92e3921b-2bb8-4333-8cfe-4bd27f785d24", + "cell_type": "code", + "source": "from python_workflow_definition.cwl import write_workflow", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 4 + }, + { + "id": "b0cf73b9-ea21-4437-8d2a-c51b65bbfa86", + "cell_type": "markdown", + "source": "## Overwrite source directory with absolute path\n\n`workflow.json` stores `source_directory` as the relative path `\"source\"`. Because `cwltool` stages each step's inputs into its own temporary working directory, a relative path would no longer resolve once execution starts, so it is rewritten to an absolute path before export.", + "metadata": {} + }, + { + "id": "bca61d32-89dd-4df7-92da-fee1a157df5a", + "cell_type": "code", + "source": "with open(\"workflow.json\") as f:\n content = json.load(f)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 5 + }, + { + "id": "8392fa04-4fb3-496e-9387-0106c872fb98", + "cell_type": "code", + "source": "node_lst = []\nfor n in content[\"nodes\"]:\n if 'name' in n and n['name'] == 'source_directory':\n n[\"value\"] = os.path.abspath(n[\"value\"])\n node_lst.append(n)\n\ncontent[\"nodes\"] = node_lst", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 6 + }, + { + "id": "e53c7769-28bb-4d8e-b3a4-02298818a001", + "cell_type": "code", + "source": "with open(\"workflow.json\", \"w\") as f:\n json.dump(content, f)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 7 + }, + { + "id": "a9540ba7-f15a-4d04-86aa-0cf2ad4ac185", + "cell_type": "markdown", + "source": "## Execute workflow\n\n`write_workflow` reads `workflow.json` and writes out `workflow.cwl` (the CWL `Workflow` definition), one `_.cwl` `CommandLineTool` per pipeline step, and `workflow.yml` with the input values pickled to disk. `cwltool` then runs the six steps in dependency order, invoking `gmsh`, `meshio`, the Poisson solver, `pvbatch` and `tectonic` in turn, and writes the workflow's single output — the path to the compiled `paper.pdf` — to `result.pickle`.", + "metadata": {} + }, + { + "id": "5303c059-8ae4-4557-858e-b4bd64eac711", + "cell_type": "code", + "source": "write_workflow(file_name=\"workflow.json\")", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 8 + }, + { + "id": "df302bd2-e9b6-4595-979c-67c46414d986", + "cell_type": "code", + "source": "! cwltool --preserve-environment=CONDA_EXE workflow.cwl workflow.yml", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "/srv/conda/envs/notebook/bin/cwltool:11: DeprecationWarning: Nesting argument groups is deprecated.\n sys.exit(run())\n\u001b[1;30mINFO\u001b[0m /srv/conda/envs/notebook/bin/cwltool 3.1.20250110105449\n\u001b[1;30mINFO\u001b[0m Resolved 'workflow.cwl' to 'file:///home/jovyan/example_workflows/nfdi/workflow.cwl'\n\u001b[1;30mINFO\u001b[0m [workflow ] start\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step generate_mesh_0\n\u001b[1;30mINFO\u001b[0m [step generate_mesh_0] start\n\u001b[1;30mINFO\u001b[0m [job generate_mesh_0] /tmp/xjzxjjxg$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/lint8hha/stgaa9fa1cf-dae6-4402-aa25-3da9289e3937/workflow.py \\\n --function=workflow.generate_mesh \\\n --arg_domain_size=/tmp/lint8hha/stg94834a09-0454-4ad4-bc93-b8f3a1dc72f4/domain_size.pickle \\\n --arg_source_directory=/tmp/lint8hha/stg03fa6508-a0ea-4379-97b1-e3815dfe7395/source_directory.pickle\n\u001b[1;30mINFO\u001b[0m [job generate_mesh_0] Max memory used: 60MiB\n\u001b[1;30mINFO\u001b[0m [job generate_mesh_0] completed success\n\u001b[1;30mINFO\u001b[0m [step generate_mesh_0] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step convert_to_xdmf_1\n\u001b[1;30mINFO\u001b[0m [step convert_to_xdmf_1] start\n\u001b[1;30mINFO\u001b[0m [job convert_to_xdmf_1] /tmp/q47niux0$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/pd0inpeh/stg928009b1-efc5-45d7-9746-e1af8d96f0c5/workflow.py \\\n --function=workflow.convert_to_xdmf \\\n --arg_gmsh_output_file=/tmp/pd0inpeh/stg03750262-f7c4-4bb9-b558-0b7ea0a54cf3/result.pickle\n\u001b[1;30mINFO\u001b[0m [job convert_to_xdmf_1] Max memory used: 69MiB\n\u001b[1;30mINFO\u001b[0m [job convert_to_xdmf_1] completed success\n\u001b[1;30mINFO\u001b[0m [step convert_to_xdmf_1] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step poisson_2\n\u001b[1;30mINFO\u001b[0m [step poisson_2] start\n\u001b[1;30mINFO\u001b[0m [job poisson_2] /tmp/e045_wvq$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/rsa0i3o4/stgfd3d067f-0d0e-46b6-8b1c-e63a936cca99/workflow.py \\\n --function=workflow.poisson \\\n --arg_meshio_output_xdmf=/tmp/rsa0i3o4/stgebd53ba4-dbbc-4769-b359-f1f95611d02d/xdmf_file.pickle \\\n --arg_meshio_output_h5=/tmp/rsa0i3o4/stga4bcfd98-5bf0-4da3-b1e6-a4d55a00cc30/h5_file.pickle \\\n --arg_source_directory=/tmp/rsa0i3o4/stg003e0d81-81e0-4138-9e97-103a910c925e/source_directory.pickle\n\u001b[1;30mINFO\u001b[0m [job poisson_2] Max memory used: 81MiB\n\u001b[1;30mINFO\u001b[0m [job poisson_2] completed success\n\u001b[1;30mINFO\u001b[0m [step poisson_2] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step plot_over_line_3\n\u001b[1;30mINFO\u001b[0m [step plot_over_line_3] start\n\u001b[1;30mINFO\u001b[0m [job plot_over_line_3] /tmp/0tov09ih$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/z9a5oiuc/stgcde66eb7-274f-4ae3-833b-c8d99fe3bbb1/workflow.py \\\n --function=workflow.plot_over_line \\\n --arg_poisson_output_vtu_file=/tmp/z9a5oiuc/stg144f313e-e286-4800-a3d2-86a6cae36a98/vtu_file.pickle \\\n --arg_source_directory=/tmp/z9a5oiuc/stg224c0c40-7cb8-4f1c-921c-013809fb5cbf/source_directory.pickle \\\n --arg_poisson_output_pvd_file=/tmp/z9a5oiuc/stgc4c75ca6-aab0-40be-bfbd-f432d3523d2b/pvd_file.pickle\n\u001b[1;30mINFO\u001b[0m [job plot_over_line_3] Max memory used: 68MiB\n\u001b[1;30mINFO\u001b[0m [job plot_over_line_3] completed success\n\u001b[1;30mINFO\u001b[0m [step plot_over_line_3] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step substitute_macros_4\n\u001b[1;30mINFO\u001b[0m [step substitute_macros_4] start\n\u001b[1;30mINFO\u001b[0m [job substitute_macros_4] /tmp/08mfe8f0$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/5valbs4a/stg15353150-ebc3-49de-93a8-564a25f33270/workflow.py \\\n --function=workflow.substitute_macros \\\n --arg_domain_size=/tmp/5valbs4a/stg0734ab21-1efd-480b-ba2b-cea9ed24012e/domain_size.pickle \\\n --arg_source_directory=/tmp/5valbs4a/stg0c79cde6-159f-4b82-bdb9-aabef8678f9f/source_directory.pickle \\\n --arg_ndofs=/tmp/5valbs4a/stg770f9cb7-d2c3-4ce5-bc00-7a9cdb11d64d/numdofs.pickle \\\n --arg_pvbatch_output_file=/tmp/5valbs4a/stgdd978452-6c84-4308-abf6-7ae2609fc91d/result.pickle\n\u001b[1;30mINFO\u001b[0m [job substitute_macros_4] Max memory used: 60MiB\n\u001b[1;30mINFO\u001b[0m [job substitute_macros_4] completed success\n\u001b[1;30mINFO\u001b[0m [step substitute_macros_4] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step compile_paper_5\n\u001b[1;30mINFO\u001b[0m [step compile_paper_5] start\n\u001b[1;30mINFO\u001b[0m [job compile_paper_5] /tmp/hjjeng16$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/3bq2mxdl/stg34a5d902-97c3-43f1-95eb-5e14d0c68386/workflow.py \\\n --function=workflow.compile_paper \\\n --arg_macros_tex=/tmp/3bq2mxdl/stg184e0acf-5138-4b37-97f0-ba406ed71433/result.pickle \\\n --arg_plot_file=/tmp/3bq2mxdl/stg2360c6e9-26ec-43f5-99a2-26c05668b2fa/result.pickle \\\n --arg_source_directory=/tmp/3bq2mxdl/stg7194b36e-38db-4ef7-af5d-368e9575f15f/source_directory.pickle\n\u001b[1;30mINFO\u001b[0m [job compile_paper_5] Max memory used: 265MiB\n\u001b[1;30mINFO\u001b[0m [job compile_paper_5] completed success\n\u001b[1;30mINFO\u001b[0m [step compile_paper_5] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] completed success\n{\n \"result_file\": {\n \"location\": \"file:///home/jovyan/example_workflows/nfdi/result.pickle\",\n \"basename\": \"result.pickle\",\n \"class\": \"File\",\n \"checksum\": \"sha1$a23617d3f4b4e6970b7f4fb9eb4d2148f9888e58\",\n \"size\": 53,\n \"path\": \"/home/jovyan/example_workflows/nfdi/result.pickle\"\n }\n}\u001b[1;30mINFO\u001b[0m Final process status is success\n" + } + ], + "execution_count": 9 + }, + { + "cell_type": "markdown", + "id": "c55f089b", + "source": "The result is unpickled below to confirm it is the expected `paper.pdf` path.", + "metadata": {} + }, + { + "id": "2942dbba-ea0a-4d20-be5c-ed9992d09ff8", + "cell_type": "code", + "source": "with open(\"result.pickle\", \"rb\") as f:\n print(pickle.load(f))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "/tmp/hjjeng16/postprocessing/paper.pdf\n" + } + ], + "execution_count": 10 + }, + { + "id": "60e909ee-d0d0-4bd1-81c8-dd5274ae5834", + "cell_type": "code", + "source": "", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": null + } + ] +} \ No newline at end of file diff --git a/_sources/example_workflows/nfdi/executorlib.ipynb b/_sources/example_workflows/nfdi/executorlib.ipynb new file mode 100644 index 00000000..8a2e0bac --- /dev/null +++ b/_sources/example_workflows/nfdi/executorlib.ipynb @@ -0,0 +1,2121 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "106ded66-d202-46ac-82b0-2755ca309bdd", + "metadata": {}, + "source": "# executorlib\n\nhttps://github.com/BAMresearch/NFDI4IngScientificWorkflowRequirements\n\nThis notebook defines the NFDI4Ing file-based workflow benchmark with [`executorlib`](https://github.com/pyiron/executorlib) and then loads the resulting `workflow.json` into `aiida`, `jobflow`, `pyiron_base` and `pyiron_workflow`. Every stage of the pipeline shells out to an external command-line tool (`gmsh`, `meshio`, a FEniCS-based Poisson solver, ParaView's `pvbatch`, `tectonic`) in its own conda environment and passes file paths between stages rather than in-memory Python objects — see [`workflow.py`](workflow.py)." + }, + { + "cell_type": "markdown", + "id": "91dd48ea-aa7e-4937-a68e-59fc5017eb1e", + "metadata": {}, + "source": "## Define workflow with executorlib\n\n`executorlib` provides a `concurrent.futures`-compatible `SingleNodeExecutor`: each `exe.submit(func, ...)` call schedules a function call and immediately returns a `Future`. Since `convert_to_xdmf` and `poisson` return a `dict`, `get_item_from_future` is used to pick a single key (e.g. `\"xdmf_file\"`) out of a future's eventual result before passing it on as an input to the next stage." + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "2c9622f5-ab7e-460e-b8e4-8d21413eda77", + "metadata": {}, + "outputs": [], + "source": [ + "import os" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "d265bb5aa6af79d6", + "metadata": {}, + "outputs": [], + "source": [ + "from workflow import generate_mesh, convert_to_xdmf, poisson, plot_over_line, substitute_macros, compile_paper " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "2dced28725813fc1", + "metadata": {}, + "outputs": [], + "source": [ + "from executorlib import SingleNodeExecutor, get_item_from_future" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "8d911f98-3b80-457f-a0f4-3cb37ebf1691", + "metadata": {}, + "outputs": [], + "source": [ + "domain_size = 2.0" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "c6ea980b-6761-4191-8407-7b1f78a4c3ea", + "metadata": {}, + "outputs": [], + "source": [ + "source_directory = os.path.abspath(os.path.join(os.curdir, \"source\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "ef1a63b7-2c04-43ac-9f33-333c5f7d93cd", + "metadata": {}, + "outputs": [], + "source": [ + "workflow_json_filename = \"executorlib_nfdi.json\"" + ] + }, + { + "cell_type": "markdown", + "id": "57d670cb", + "source": "Passing `export_workflow_filename` to `SingleNodeExecutor` makes it record every `submit` call as a side effect and write them out as a PWD `workflow.json` once the `with` block exits — no separate `write_workflow_json` call is needed. The six `submit` calls below mirror the six pipeline stages: mesh generation, XDMF conversion, the Poisson solve, line-plot postprocessing, LaTeX macro substitution and paper compilation.", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "71d411b6-cbec-489e-99e3-ba71680bcb5b", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "with SingleNodeExecutor(export_workflow_filename=workflow_json_filename) as exe:\n", + " gmsh_output_file = exe.submit(\n", + " generate_mesh,\n", + " domain_size=domain_size,\n", + " source_directory=source_directory,\n", + " )\n", + " meshio_output_dict = exe.submit(\n", + " convert_to_xdmf,\n", + " gmsh_output_file=gmsh_output_file,\n", + " )\n", + " poisson_dict = exe.submit(\n", + " poisson,\n", + " meshio_output_xdmf=get_item_from_future(meshio_output_dict, key=\"xdmf_file\"), \n", + " meshio_output_h5=get_item_from_future(meshio_output_dict, key=\"h5_file\"),\n", + " source_directory=source_directory,\n", + " )\n", + " pvbatch_output_file = exe.submit(\n", + " plot_over_line,\n", + " poisson_output_pvd_file=get_item_from_future(poisson_dict, key=\"pvd_file\"), \n", + " poisson_output_vtu_file=get_item_from_future(poisson_dict, key=\"vtu_file\"),\n", + " source_directory=source_directory,\n", + " )\n", + " macros_tex_file = exe.submit(\n", + " substitute_macros,\n", + " pvbatch_output_file=pvbatch_output_file, \n", + " ndofs=get_item_from_future(poisson_dict, key=\"numdofs\"), \n", + " domain_size=domain_size,\n", + " source_directory=source_directory,\n", + " )\n", + " paper_output = exe.submit(\n", + " compile_paper,\n", + " macros_tex=macros_tex_file, \n", + " plot_file=pvbatch_output_file,\n", + " source_directory=source_directory,\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "0a42a34e-ebe2-478c-bea6-e6c5c8506883", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"version\": \"0.1.0\",\n", + " \"nodes\": [\n", + " {\n", + " \"id\": 0,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.generate_mesh\"\n", + " },\n", + " {\n", + " \"id\": 1,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.convert_to_xdmf\"\n", + " },\n", + " {\n", + " \"id\": 2,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.poisson\"\n", + " },\n", + " {\n", + " \"id\": 3,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.plot_over_line\"\n", + " },\n", + " {\n", + " \"id\": 4,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.substitute_macros\"\n", + " },\n", + " {\n", + " \"id\": 5,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.compile_paper\"\n", + " },\n", + " {\n", + " \"id\": 6,\n", + " \"type\": \"input\",\n", + " \"value\": 2.0,\n", + " \"name\": \"domain_size\"\n", + " },\n", + " {\n", + " \"id\": 7,\n", + " \"type\": \"input\",\n", + " \"value\": \"/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi/source\",\n", + " \"name\": \"source_directory\"\n", + " },\n", + " {\n", + " \"id\": 8,\n", + " \"type\": \"output\",\n", + " \"name\": \"result\"\n", + " }\n", + " ],\n", + " \"edges\": [\n", + " {\n", + " \"target\": 0,\n", + " \"targetPort\": \"domain_size\",\n", + " \"source\": 6,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 0,\n", + " \"targetPort\": \"source_directory\",\n", + " \"source\": 7,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 1,\n", + " \"targetPort\": \"gmsh_output_file\",\n", + " \"source\": 0,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 2,\n", + " \"targetPort\": \"meshio_output_xdmf\",\n", + " \"source\": 1,\n", + " \"sourcePort\": \"xdmf_file\"\n", + " },\n", + " {\n", + " \"target\": 2,\n", + " \"targetPort\": \"meshio_output_h5\",\n", + " \"source\": 1,\n", + " \"sourcePort\": \"h5_file\"\n", + " },\n", + " {\n", + " \"target\": 2,\n", + " \"targetPort\": \"source_directory\",\n", + " \"source\": 7,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 3,\n", + " \"targetPort\": \"poisson_output_pvd_file\",\n", + " \"source\": 2,\n", + " \"sourcePort\": \"pvd_file\"\n", + " },\n", + " {\n", + " \"target\": 3,\n", + " \"targetPort\": \"poisson_output_vtu_file\",\n", + " \"source\": 2,\n", + " \"sourcePort\": \"vtu_file\"\n", + " },\n", + " {\n", + " \"target\": 3,\n", + " \"targetPort\": \"source_directory\",\n", + " \"source\": 7,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 4,\n", + " \"targetPort\": \"pvbatch_output_file\",\n", + " \"source\": 3,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 4,\n", + " \"targetPort\": \"ndofs\",\n", + " \"source\": 2,\n", + " \"sourcePort\": \"numdofs\"\n", + " },\n", + " {\n", + " \"target\": 4,\n", + " \"targetPort\": \"domain_size\",\n", + " \"source\": 6,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 4,\n", + " \"targetPort\": \"source_directory\",\n", + " \"source\": 7,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 5,\n", + " \"targetPort\": \"macros_tex\",\n", + " \"source\": 4,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 5,\n", + " \"targetPort\": \"plot_file\",\n", + " \"source\": 3,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 5,\n", + " \"targetPort\": \"source_directory\",\n", + " \"source\": 7,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 8,\n", + " \"targetPort\": null,\n", + " \"source\": 5,\n", + " \"sourcePort\": null\n", + " }\n", + " ]\n", + "}" + ] + } + ], + "source": [ + "!cat {workflow_json_filename}" + ] + }, + { + "cell_type": "markdown", + "id": "d789971e-8f41-45fa-832a-11fd72dea96e", + "metadata": {}, + "source": "## Load Workflow with aiida\n\nThe JSON produced by `executorlib` is loaded into an `aiida-workgraph` `WorkGraph` via `load_workflow_json`, after connecting to a local AiiDA profile with `load_profile()`. `wg.run()` then re-executes the whole pipeline under `aiida`." + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "a6e85e89-5d7a-40eb-809c-ac44974e3fd7", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Profile" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from aiida import load_profile\n", + "\n", + "load_profile()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "3de84fb7-b01b-4541-868a-92e881eb6e77", + "metadata": {}, + "outputs": [], + "source": [ + "from python_workflow_definition.aiida import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "b33f5528-10cd-47c8-8723-622902978859", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "d1895b0b32c4451c8847cc76ded8f82e", + "version_major": 2, + "version_minor": 1 + }, + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wg = load_workflow_json(file_name=workflow_json_filename)\n", + "wg" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "15282ca1-d339-40e7-ad68-8a7613ed08da", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "01/16/2026 08:09:53 AM <39943> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1584|WorkGraphEngine|continue_workgraph]: tasks ready to run: generate_mesh\n", + "01/16/2026 08:09:56 AM <39943> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1584|WorkGraphEngine|update_task_state]: Task: generate_mesh, type: PYFUNCTION, finished.\n", + "01/16/2026 08:09:56 AM <39943> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1584|WorkGraphEngine|continue_workgraph]: tasks ready to run: convert_to_xdmf\n", + "01/16/2026 08:10:00 AM <39943> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1584|WorkGraphEngine|update_task_state]: Task: convert_to_xdmf, type: PYFUNCTION, finished.\n", + "01/16/2026 08:10:00 AM <39943> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1584|WorkGraphEngine|continue_workgraph]: tasks ready to run: poisson\n", + "/home/jan/miniforge3/envs/processing/lib/python3.9/site-packages/ufl/__init__.py:250: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n", + " import pkg_resources\n", + "01/16/2026 08:10:04 AM <39943> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1584|WorkGraphEngine|update_task_state]: Task: poisson, type: PYFUNCTION, finished.\n", + "01/16/2026 08:10:05 AM <39943> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1584|WorkGraphEngine|continue_workgraph]: tasks ready to run: plot_over_line\n", + "01/16/2026 08:10:09 AM <39943> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1584|WorkGraphEngine|update_task_state]: Task: plot_over_line, type: PYFUNCTION, finished.\n", + "01/16/2026 08:10:09 AM <39943> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1584|WorkGraphEngine|continue_workgraph]: tasks ready to run: substitute_macros\n", + "01/16/2026 08:10:11 AM <39943> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1584|WorkGraphEngine|update_task_state]: Task: substitute_macros, type: PYFUNCTION, finished.\n", + "01/16/2026 08:10:11 AM <39943> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1584|WorkGraphEngine|continue_workgraph]: tasks ready to run: compile_paper\n", + "01/16/2026 08:10:16 AM <39943> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1584|WorkGraphEngine|update_task_state]: Task: compile_paper, type: PYFUNCTION, finished.\n", + "01/16/2026 08:10:16 AM <39943> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1584|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n", + "01/16/2026 08:10:16 AM <39943> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1584|WorkGraphEngine|finalize]: Finalize workgraph.\n" + ] + }, + { + "data": { + "text/plain": [ + "{}" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wg.run()" + ] + }, + { + "cell_type": "markdown", + "id": "55dc8d12-dfe6-4465-a368-b7e590ae6800", + "metadata": {}, + "source": "## Load Workflow with jobflow\n\nThe same `workflow.json` is reconstructed as a jobflow `Flow` and executed locally with `run_locally`, independently of the `executorlib` objects used to define it." + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "dff46eb8-e0e7-49bb-8c40-0db2df133124", + "metadata": {}, + "outputs": [], + "source": [ + "from python_workflow_definition.jobflow import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "6a189459-84e4-4738-ada1-37ee8c65b2ab", + "metadata": {}, + "outputs": [], + "source": [ + "from jobflow.managers.local import run_locally" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "6e7f3614-c971-4e2d-83f0-96f0d0fc04de", + "metadata": {}, + "outputs": [], + "source": [ + "flow = load_workflow_json(file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "2d87ed45-f5d9-403f-a03a-26be4a47a3ef", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2026-01-16 08:10:22,433 INFO Started executing jobs locally\n", + "2026-01-16 08:10:22,747 INFO Starting job - generate_mesh (fca356ed-0f12-49aa-90c5-3161982fb757)\n", + "2026-01-16 08:10:24,797 INFO Finished job - generate_mesh (fca356ed-0f12-49aa-90c5-3161982fb757)\n", + "2026-01-16 08:10:24,797 INFO Starting job - convert_to_xdmf (2be5b5a6-4ba9-4962-b09c-c7565e4655a8)\n", + "2026-01-16 08:10:27,186 INFO Finished job - convert_to_xdmf (2be5b5a6-4ba9-4962-b09c-c7565e4655a8)\n", + "2026-01-16 08:10:27,186 INFO Starting job - poisson (e539fd0a-4e53-42b4-b79d-9d07a2f602d7)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/jan/miniforge3/envs/processing/lib/python3.9/site-packages/ufl/__init__.py:250: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n", + " import pkg_resources\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2026-01-16 08:10:30,319 INFO Finished job - poisson (e539fd0a-4e53-42b4-b79d-9d07a2f602d7)\n", + "2026-01-16 08:10:30,320 INFO Starting job - plot_over_line (e71edb93-5784-4a14-9cb8-29180644c4e1)\n", + "2026-01-16 08:10:33,201 INFO Finished job - plot_over_line (e71edb93-5784-4a14-9cb8-29180644c4e1)\n", + "2026-01-16 08:10:33,202 INFO Starting job - substitute_macros (ca231d17-16ce-409c-a4cc-9a3988b7524a)\n", + "2026-01-16 08:10:35,251 INFO Finished job - substitute_macros (ca231d17-16ce-409c-a4cc-9a3988b7524a)\n", + "2026-01-16 08:10:35,252 INFO Starting job - compile_paper (43798414-e406-411e-9daa-bf1bf3d20c25)\n", + "2026-01-16 08:10:39,264 INFO Finished job - compile_paper (43798414-e406-411e-9daa-bf1bf3d20c25)\n", + "2026-01-16 08:10:39,265 INFO Finished executing jobs locally\n" + ] + }, + { + "data": { + "text/plain": [ + "{'fca356ed-0f12-49aa-90c5-3161982fb757': {1: Response(output='/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi/preprocessing/square.msh', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi'))},\n", + " '2be5b5a6-4ba9-4962-b09c-c7565e4655a8': {1: Response(output={'xdmf_file': '/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi/preprocessing/square.xdmf', 'h5_file': '/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi/preprocessing/square.h5'}, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi'))},\n", + " 'e539fd0a-4e53-42b4-b79d-9d07a2f602d7': {1: Response(output={'numdofs': 357, 'pvd_file': '/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi/processing/poisson.pvd', 'vtu_file': '/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi/processing/poisson000000.vtu'}, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi'))},\n", + " 'e71edb93-5784-4a14-9cb8-29180644c4e1': {1: Response(output='/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi/postprocessing/plotoverline.csv', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi'))},\n", + " 'ca231d17-16ce-409c-a4cc-9a3988b7524a': {1: Response(output='/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi/postprocessing/macros.tex', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi'))},\n", + " '43798414-e406-411e-9daa-bf1bf3d20c25': {1: Response(output='/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi/postprocessing/paper.pdf', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi'))}}" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result = run_locally(flow)\n", + "result" + ] + }, + { + "cell_type": "markdown", + "id": "7ecc0861-6fc8-4788-b05b-fa5ae06b96e3", + "metadata": {}, + "source": "## Load Workflow with pyiron_base\n\n`load_workflow_json` turns the graph into a list of delayed pyiron jobs; `.draw()` visualizes the dependency chain and `.pull()` triggers execution, returning the path to the final `paper.pdf`." + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "78bf8ce1-518c-4a14-9375-9557db125fd0", + "metadata": {}, + "outputs": [], + "source": [ + "from python_workflow_definition.pyiron_base import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "3c9a66a4-81e1-40e7-bf33-b0c661b6c8df", + "metadata": {}, + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "create_function_job_d98d5639807a3be4999a1365311f70f7\n", + "\n", + "create_function_job=<pyiron_base.project.delayed.DelayedObject object at 0x7f752e211850>\n", + "\n", + "\n", + "\n", + "macros_tex_2966c3cce2a45e8cba702c524f55c461\n", + "\n", + "macros_tex=<pyiron_base.project.delayed.DelayedObject object at 0x7f752e2115e0>\n", + "\n", + "\n", + "\n", + "macros_tex_2966c3cce2a45e8cba702c524f55c461->create_function_job_d98d5639807a3be4999a1365311f70f7\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "pvbatch_output_file_2e9051e35dd84c5e1f106937c8c783f5\n", + "\n", + "pvbatch_output_file=<pyiron_base.project.delayed.DelayedObject object at 0x7f752e2112b0>\n", + "\n", + "\n", + "\n", + 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convert_to_xdmf_eb9b45572042c1ef8c618184cde64b0d was saved and received the ID: 35\n", + "The job poisson_2fd5008b2250fed255cc4f58e009fe7e was saved and received the ID: 36\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/jan/miniforge3/envs/processing/lib/python3.9/site-packages/ufl/__init__.py:250: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n", + " import pkg_resources\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job plot_over_line_e59dd6066e3aaeb378917024209e71cf was saved and received the ID: 37\n", + "The job substitute_macros_317cac7b98bf8b6278cdf40a45350ccb was saved and received the ID: 38\n", + "The job compile_paper_32a7807be3644bd018cad61f46ebfb35 was saved and received the ID: 39\n" + ] + }, + { + "data": { + "text/plain": [ + "'/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi/postprocessing/paper.pdf'" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "delayed_object_lst[-1].pull()" + ] + }, + { + "cell_type": "markdown", + "id": "385acbf585763632", + "metadata": {}, + "source": "## Load Workflow with pyiron_workflow\n\nFinally, the graph is loaded into a `pyiron_workflow` `Workflow`. `.draw()` shows the node graph and `.run()` executes it end to end." + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "927d0118cc4edfba", + "metadata": {}, + "outputs": [], + "source": [ + "from python_workflow_definition.pyiron_workflow import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "50055483ca2c9909", + "metadata": {}, + "outputs": [], + "source": [ + "wf = load_workflow_json(file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "7d25a578c431e0f5", + "metadata": {}, + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "clusterexecutorlib_nfdi\n", + "\n", + "executorlib_nfdi: Workflow\n", + "\n", + "clusterexecutorlib_nfdiInputs\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "Inputs\n", + "\n", + "\n", + "clusterexecutorlib_nfdiOutputsWithInjection\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "OutputsWithInjection\n", + "\n", + "\n", + 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"clusterexecutorlib_nfdiinjected_GetItem_288724780737349182OutputsWithInjectiongetitem->clusterexecutorlib_nfdiplot_over_lineInputspoisson_output_vtu_file\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "clusterexecutorlib_nfdiinjected_GetItem_8657121023782977951Inputsrun\n", + "\n", + "run\n", + "\n", + "\n", + "\n", + "clusterexecutorlib_nfdiinjected_GetItem_8657121023782977951OutputsWithInjectionran\n", + "\n", + "ran\n", + "\n", + "\n", + "\n", + "\n", + "clusterexecutorlib_nfdiinjected_GetItem_8657121023782977951Inputsaccumulate_and_run\n", + "\n", + "accumulate_and_run\n", + "\n", + "\n", + "\n", + "clusterexecutorlib_nfdiinjected_GetItem_8657121023782977951OutputsWithInjectionfailed\n", + "\n", + "failed\n", + "\n", + "\n", + "\n", + "clusterexecutorlib_nfdiinjected_GetItem_8657121023782977951OutputsWithInjectiongetitem\n", + "\n", + "getitem\n", + "\n", + "\n", + "\n", + "clusterexecutorlib_nfdiinjected_GetItem_8657121023782977951OutputsWithInjectiongetitem->clusterexecutorlib_nfdisubstitute_macrosInputsndofs\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wf.draw(size=(10,10))" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "fff9513c4a127a96", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/jan/miniforge3/envs/processing/lib/python3.9/site-packages/ufl/__init__.py:250: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n", + " import pkg_resources\n" + ] + }, + { + "data": { + "text/plain": [ + "{'compile_paper__compile_paper': '/home/jan/notebooks/2026/2026-01-16-executorlib-pwd/nfdi/postprocessing/paper.pdf'}" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wf.run()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "47a4de7a-d149-4cd2-9b92-1901ce0ceb9d", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} \ No newline at end of file diff --git a/_sources/example_workflows/nfdi/jobflow.ipynb b/_sources/example_workflows/nfdi/jobflow.ipynb new file mode 100644 index 00000000..77c50414 --- /dev/null +++ b/_sources/example_workflows/nfdi/jobflow.ipynb @@ -0,0 +1,382 @@ +{ + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.12.8", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + } + }, + "nbformat_minor": 5, + "nbformat": 4, + "cells": [ + { + "id": "048b53d1-db08-44ff-84cc-a4ff50032944", + "cell_type": "markdown", + "source": "# jobflow", + "metadata": {} + }, + { + "id": "106ded66-d202-46ac-82b0-2755ca309bdd", + "cell_type": "markdown", + "source": "https://github.com/BAMresearch/NFDI4IngScientificWorkflowRequirements\n\nThis notebook defines the NFDI4Ing file-based workflow benchmark with [`jobflow`](https://github.com/materialsproject/jobflow) and then loads the resulting `workflow.json` into `aiida`, `pyiron_base` and `pyiron_workflow`. Every stage of the pipeline shells out to an external command-line tool (`gmsh`, `meshio`, a FEniCS-based Poisson solver, ParaView's `pvbatch`, `tectonic`) in its own conda environment and passes file paths between stages rather than in-memory Python objects — see [`workflow.py`](workflow.py).", + "metadata": {} + }, + { + "id": "856b2ba2-93d5-4516-93e1-a1eac49c48f2", + "cell_type": "markdown", + "source": "## Define workflow with jobflow\n\nThe `job` decorator turns each of the six pipeline functions into a jobflow `Job` that delays execution until the `Flow` is run. Because `convert_to_xdmf` and `poisson` return a `dict`, their outputs are accessed downstream as `.output.` (e.g. `meshio_output_dict.output.xdmf_file`) to wire a single dictionary entry into the next job's input.", + "metadata": {} + }, + { + "id": "43d5c810-a701-4971-8534-56dcbd112716", + "cell_type": "code", + "source": "import os", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 1 + }, + { + "id": "89c02460-b543-442c-a27e-f1757dc2262e", + "cell_type": "code", + "source": "from jobflow import job, Flow\n\nfrom python_workflow_definition.jobflow import write_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 2 + }, + { + "id": "864f048d78ea3f08", + "cell_type": "code", + "source": "from workflow import (\n generate_mesh as _generate_mesh, \n convert_to_xdmf as _convert_to_xdmf,\n poisson as _poisson,\n plot_over_line as _plot_over_line,\n substitute_macros as _substitute_macros,\n compile_paper as _compile_paper,\n)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 3 + }, + { + "id": "147b81b7b494ceda", + "cell_type": "code", + "source": "generate_mesh = job(_generate_mesh)\nconvert_to_xdmf = job(_convert_to_xdmf)\npoisson = job(_poisson)\nplot_over_line = job(_plot_over_line)\nsubstitute_macros = job(_substitute_macros)\ncompile_paper = job(_compile_paper)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 4 + }, + { + "id": "981e548b-a3b4-49a3-9653-85e90f05c60e", + "cell_type": "code", + "source": "source_directory = os.path.abspath(os.path.join(os.curdir, \"source\"))", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 5 + }, + { + "cell_type": "markdown", + "id": "1cd3d59e", + "source": "With `source_directory` and `domain_size` fixed, the calls below chain the six jobs together: mesh generation, XDMF conversion, the Poisson solve, line-plot postprocessing, LaTeX macro substitution and paper compilation. Each job runs in its own subdirectory and conda environment (see `source/envs/`), so what actually flows from one job to the next are file paths, not in-memory results.", + "metadata": {} + }, + { + "id": "8d911f98-3b80-457f-a0f4-3cb37ebf1691", + "cell_type": "code", + "source": "domain_size = 2.0", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 6 + }, + { + "id": "71d411b6-cbec-489e-99e3-ba71680bcb5b", + "cell_type": "code", + "source": "gmsh_output_file = generate_mesh(\n domain_size=domain_size,\n source_directory=source_directory,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 7 + }, + { + "id": "1d0d9804-f250-48b3-a5d0-a546d520f79b", + "cell_type": "code", + "source": "meshio_output_dict = convert_to_xdmf(\n gmsh_output_file=gmsh_output_file.output,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 8 + }, + { + "id": "7b69bcff-e2b1-4d4a-b62c-6a1c86eeb590", + "cell_type": "code", + "source": "poisson_dict = poisson(\n meshio_output_xdmf=meshio_output_dict.output.xdmf_file, \n meshio_output_h5=meshio_output_dict.output.h5_file,\n source_directory=source_directory,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 9 + }, + { + "id": "3c4a29b0-eb1e-490a-8be0-e03cfff15e0a", + "cell_type": "code", + "source": "pvbatch_output_file = plot_over_line(\n poisson_output_pvd_file=poisson_dict.output.pvd_file, \n poisson_output_vtu_file=poisson_dict.output.vtu_file,\n source_directory=source_directory,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 10 + }, + { + "id": "a0a4c233-322d-4723-9627-62ca2487bfa9", + "cell_type": "code", + "source": "macros_tex_file = substitute_macros( \n pvbatch_output_file=pvbatch_output_file.output, \n ndofs=poisson_dict.output.numdofs, \n domain_size=domain_size,\n source_directory=source_directory,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 11 + }, + { + "id": "c281408f-e63d-4380-a7e6-c595d49fbb8f", + "cell_type": "code", + "source": "paper_output = compile_paper(\n macros_tex=macros_tex_file.output, \n plot_file=pvbatch_output_file.output,\n source_directory=source_directory,\n)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 12 + }, + { + "id": "a384d70a-8ef5-4fdd-880c-56ac7eaf87b9", + "cell_type": "code", + "source": "flow = Flow([gmsh_output_file, meshio_output_dict, poisson_dict, pvbatch_output_file, macros_tex_file, paper_output])", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 13 + }, + { + "cell_type": "markdown", + "id": "71c4ff70", + "source": "The six jobs are collected into a `Flow`, which `write_workflow_json` then serializes to the PWD `workflow.json` format for the other engines to load.", + "metadata": {} + }, + { + "id": "fb23ad9c-76fd-4c0b-b546-e305d6c49796", + "cell_type": "code", + "source": "workflow_json_filename = \"jobflow_nfdi.json\"", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 14 + }, + { + "id": "4139547a-9717-4708-b1a5-8202a0382d77", + "cell_type": "code", + "source": "write_workflow_json(flow=flow, file_name=workflow_json_filename)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 15 + }, + { + "id": "11a829e2-face-469f-b343-2c95763b1f13", + "cell_type": "markdown", + "source": "## Load Workflow with aiida\n\n`load_workflow_json` rebuilds the pipeline as an `aiida-workgraph` `WorkGraph` from `jobflow_nfdi.json`, after connecting to a local AiiDA profile with `load_profile()`. `wg.run()` re-executes the whole pipeline under `aiida`.", + "metadata": {} + }, + { + "id": "4f3acabe-55df-479a-af4d-a23a80c4660d", + "cell_type": "code", + "source": "from aiida import load_profile\n\nload_profile()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 16, + "output_type": "execute_result", + "data": { + "text/plain": "Profile" + }, + "metadata": {} + } + ], + "execution_count": 16 + }, + { + "id": "b6ba9444-a2c8-451b-b74c-19b0f69ba369", + "cell_type": "code", + "source": "from python_workflow_definition.aiida import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 17 + }, + { + "id": "c3528d55-6bf7-47ed-a110-65c47446ba92", + "cell_type": "code", + "source": "wg = load_workflow_json(file_name=workflow_json_filename)\nwg", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 18, + "output_type": "execute_result", + "data": { + "text/plain": "NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'WorkGra…", + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 1, + "model_id": "47a0a80d777f424aa98a551c4cbe7e1e" + } + }, + "metadata": {} + } + ], + "execution_count": 18 + }, + { + "id": "5ef48778-4209-425f-8c6b-85a4cd2f92ec", + "cell_type": "code", + "source": "wg.run()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "05/24/2025 05:44:19 AM <3034> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [51|WorkGraphEngine|continue_workgraph]: tasks ready to run: generate_mesh1\n05/24/2025 05:44:21 AM <3034> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [51|WorkGraphEngine|update_task_state]: Task: generate_mesh1, type: PyFunction, finished.\n05/24/2025 05:44:21 AM <3034> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [51|WorkGraphEngine|continue_workgraph]: tasks ready to run: convert_to_xdmf2\n05/24/2025 05:44:22 AM <3034> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [51|WorkGraphEngine|update_task_state]: Task: convert_to_xdmf2, type: PyFunction, finished.\n05/24/2025 05:44:22 AM <3034> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [51|WorkGraphEngine|continue_workgraph]: tasks ready to run: poisson3\n05/24/2025 05:44:25 AM <3034> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [51|WorkGraphEngine|update_task_state]: Task: poisson3, type: PyFunction, finished.\n05/24/2025 05:44:25 AM <3034> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [51|WorkGraphEngine|continue_workgraph]: tasks ready to run: plot_over_line4\n05/24/2025 05:44:27 AM <3034> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [51|WorkGraphEngine|update_task_state]: Task: plot_over_line4, type: PyFunction, finished.\n05/24/2025 05:44:27 AM <3034> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [51|WorkGraphEngine|continue_workgraph]: tasks ready to run: substitute_macros5\n05/24/2025 05:44:29 AM <3034> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [51|WorkGraphEngine|update_task_state]: Task: substitute_macros5, type: PyFunction, finished.\n05/24/2025 05:44:29 AM <3034> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [51|WorkGraphEngine|continue_workgraph]: tasks ready to run: compile_paper6\n05/24/2025 05:44:31 AM <3034> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [51|WorkGraphEngine|update_task_state]: Task: compile_paper6, type: PyFunction, finished.\n05/24/2025 05:44:31 AM <3034> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [51|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n05/24/2025 05:44:31 AM <3034> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [51|WorkGraphEngine|finalize]: Finalize workgraph.\n" + } + ], + "execution_count": 19 + }, + { + "id": "397b16a2-e1ec-4eec-8562-1c84f585c347", + "cell_type": "markdown", + "source": "## Load Workflow with pyiron_base\n\nThe same JSON is loaded into a list of delayed pyiron jobs; `.draw()` visualizes their dependencies and `.pull()` triggers execution, returning the final `paper.pdf` path.", + "metadata": {} + }, + { + "id": "be4d5d93-e9f6-4072-a6be-0ee5dc93590f", + "cell_type": "code", + "source": "from python_workflow_definition.pyiron_base import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 20 + }, + { + "id": "4452a648-d4c3-4f5f-8678-ffb54bef17dc", + "cell_type": "code", + "source": "delayed_object_lst = load_workflow_json(file_name=workflow_json_filename)\ndelayed_object_lst[-1].draw()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "", + "image/svg+xml": "\n\n\n\n\ncreate_function_job_724cfd00ffeb70f8b463a938195e0447\n\ncreate_function_job=<pyiron_base.project.delayed.DelayedObject object at 0x7da7483b9b80>\n\n\n\nmacros_tex_b52804e5fa845b3657fa99b738e02cf7\n\nmacros_tex=<pyiron_base.project.delayed.DelayedObject object at 0x7da7483b9910>\n\n\n\nmacros_tex_b52804e5fa845b3657fa99b738e02cf7->create_function_job_724cfd00ffeb70f8b463a938195e0447\n\n\n\n\n\npvbatch_output_file_554a54a50a86b23416c0daf6ab0938df\n\npvbatch_output_file=<pyiron_base.project.delayed.DelayedObject object at 0x7da7483b95e0>\n\n\n\npvbatch_output_file_554a54a50a86b23416c0daf6ab0938df->macros_tex_b52804e5fa845b3657fa99b738e02cf7\n\n\n\n\n\npoisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9\n\npoisson_output_pvd_file=<pyiron_base.project.delayed.DelayedObject object at 0x7da7483b9280>\n\n\n\npoisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9->pvbatch_output_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\nplot_file_554a54a50a86b23416c0daf6ab0938df\n\nplot_file=<pyiron_base.project.delayed.DelayedObject object at 0x7da7483b95e0>\n\n\n\npoisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9->plot_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\nplot_file_554a54a50a86b23416c0daf6ab0938df->create_function_job_724cfd00ffeb70f8b463a938195e0447\n\n\n\n\n\nmeshio_output_xdmf_52103bbf2f92608bdb3c6bedb045e0e1\n\nmeshio_output_xdmf=<pyiron_base.project.delayed.DelayedObject object at 0x7da7483b8e90>\n\n\n\nmeshio_output_xdmf_52103bbf2f92608bdb3c6bedb045e0e1->poisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9\n\n\n\n\n\npoisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810\n\npoisson_output_vtu_file=<pyiron_base.project.delayed.DelayedObject object at 0x7da7483b9250>\n\n\n\nmeshio_output_xdmf_52103bbf2f92608bdb3c6bedb045e0e1->poisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810\n\n\n\n\n\nndofs_e826761b60042b070e0c0a24b472ee26\n\nndofs=<pyiron_base.project.delayed.DelayedObject object at 0x7da7483b9670>\n\n\n\nmeshio_output_xdmf_52103bbf2f92608bdb3c6bedb045e0e1->ndofs_e826761b60042b070e0c0a24b472ee26\n\n\n\n\n\npoisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810->pvbatch_output_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\npoisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810->plot_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\nndofs_e826761b60042b070e0c0a24b472ee26->macros_tex_b52804e5fa845b3657fa99b738e02cf7\n\n\n\n\n\ngmsh_output_file_553a0d07e32ca83a3640e955a7b868a4\n\ngmsh_output_file=<pyiron_base.project.delayed.DelayedObject object at 0x7da7483b8b90>\n\n\n\ngmsh_output_file_553a0d07e32ca83a3640e955a7b868a4->meshio_output_xdmf_52103bbf2f92608bdb3c6bedb045e0e1\n\n\n\n\n\nmeshio_output_h5_0e11ecf3d5834e399bb91f99309bf3fe\n\nmeshio_output_h5=<pyiron_base.project.delayed.DelayedObject object at 0x7da7483b8e60>\n\n\n\ngmsh_output_file_553a0d07e32ca83a3640e955a7b868a4->meshio_output_h5_0e11ecf3d5834e399bb91f99309bf3fe\n\n\n\n\n\nmeshio_output_h5_0e11ecf3d5834e399bb91f99309bf3fe->poisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9\n\n\n\n\n\nmeshio_output_h5_0e11ecf3d5834e399bb91f99309bf3fe->poisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810\n\n\n\n\n\nmeshio_output_h5_0e11ecf3d5834e399bb91f99309bf3fe->ndofs_e826761b60042b070e0c0a24b472ee26\n\n\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20\n\ndomain_size=2.0\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20->macros_tex_b52804e5fa845b3657fa99b738e02cf7\n\n\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20->gmsh_output_file_553a0d07e32ca83a3640e955a7b868a4\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696\n\nsource_directory=/home/jovyan/example_workflows/nfdi/source\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->create_function_job_724cfd00ffeb70f8b463a938195e0447\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->macros_tex_b52804e5fa845b3657fa99b738e02cf7\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->pvbatch_output_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->poisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->plot_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->poisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->ndofs_e826761b60042b070e0c0a24b472ee26\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->gmsh_output_file_553a0d07e32ca83a3640e955a7b868a4\n\n\n\n\n" + }, + "metadata": {} + } + ], + "execution_count": 21 + }, + { + "id": "1c2760b6-96b4-4f44-ac49-a229d4a0cf67", + "cell_type": "code", + "source": "delayed_object_lst[-1].pull()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "The job generate_mesh_47725c16637f799ac042e47468005db3 was saved and received the ID: 1\nThe job convert_to_xdmf_d6a46eb9a4ec352aa996e783ec3c785f was saved and received the ID: 2\nThe job poisson_3c147fc86db87cf0c0f94bda333f8cd8 was saved and received the ID: 3\nThe job plot_over_line_ef50933291910dadcc8311924971e127 was saved and received the ID: 4\nThe job substitute_macros_63766eafd6b1980c7832dd8c9a97c96e was saved and received the ID: 5\nThe job compile_paper_128d1d58374953c00e95b8de62cbb10b was saved and received the ID: 6\n" + }, + { + "execution_count": 22, + "output_type": "execute_result", + "data": { + "text/plain": "'/home/jovyan/example_workflows/nfdi/postprocessing/paper.pdf'" + }, + "metadata": {} + } + ], + "execution_count": 22 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## Load Workflow with pyiron_workflow\n\nFinally, the graph is loaded into a `pyiron_workflow` `Workflow`. `.draw()` shows the node graph and `.run()` executes it end to end.", + "id": "8e73fa07cebd7b72" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "from python_workflow_definition.pyiron_workflow import load_workflow_json", + "id": "aa99fbd94b03a869" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf = load_workflow_json(file_name=workflow_json_filename)", + "id": "728b8684fee475b5" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.draw(size=(10,10))", + "id": "7b814f0f74f0b15a" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.run()", + "id": "447506cdca5080e6" + } + ] +} \ No newline at end of file diff --git a/_sources/example_workflows/nfdi/pyiron_base.ipynb b/_sources/example_workflows/nfdi/pyiron_base.ipynb new file mode 100644 index 00000000..164b5af8 --- /dev/null +++ b/_sources/example_workflows/nfdi/pyiron_base.ipynb @@ -0,0 +1,367 @@ +{ + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.12.8", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + } + }, + "nbformat_minor": 5, + "nbformat": 4, + "cells": [ + { + "id": "106ded66-d202-46ac-82b0-2755ca309bdd", + "cell_type": "markdown", + "source": "# pyiron\n\nhttps://github.com/BAMresearch/NFDI4IngScientificWorkflowRequirements\n\nThis notebook defines the NFDI4Ing file-based workflow benchmark with [`pyiron_base`](https://github.com/pyiron/pyiron_base) and then loads the resulting `workflow.json` into `aiida`, `jobflow` and `pyiron_workflow`. Every stage of the pipeline shells out to an external command-line tool (`gmsh`, `meshio`, a FEniCS-based Poisson solver, ParaView's `pvbatch`, `tectonic`) in its own conda environment and passes file paths between stages rather than in-memory Python objects — see [`workflow.py`](workflow.py).", + "metadata": {} + }, + { + "id": "91dd48ea-aa7e-4937-a68e-59fc5017eb1e", + "cell_type": "markdown", + "source": "## Define workflow with pyiron_base\n\nThe `job` decorator turns a plain Python function into a delayed pyiron job. Since `convert_to_xdmf` and `poisson` return a `dict`, they are decorated with `output_key_lst=[...]` so each dictionary key becomes a separately addressable output (e.g. `meshio_output_dict.output.xdmf_file`) that can be wired into the next job's input.", + "metadata": {} + }, + { + "id": "2c9622f5-ab7e-460e-b8e4-8d21413eda77", + "cell_type": "code", + "source": "import os", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 1 + }, + { + "id": "d265bb5aa6af79d6", + "cell_type": "code", + "source": "from workflow import (\n generate_mesh as _generate_mesh, \n convert_to_xdmf as _convert_to_xdmf,\n poisson as _poisson,\n plot_over_line as _plot_over_line,\n substitute_macros as _substitute_macros,\n compile_paper as _compile_paper,\n)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 2 + }, + { + "id": "2dced28725813fc1", + "cell_type": "code", + "source": "from pyiron_base import job\n\nfrom python_workflow_definition.pyiron_base import write_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 3 + }, + { + "id": "549ecf27-88ef-4e77-8bd4-b616cfdda2e4", + "cell_type": "code", + "source": "generate_mesh = job(_generate_mesh)\nconvert_to_xdmf = job(_convert_to_xdmf, output_key_lst=[\"xdmf_file\", \"h5_file\"])\npoisson = job(_poisson, output_key_lst=[\"numdofs\", \"pvd_file\", \"vtu_file\"])\nplot_over_line = job(_plot_over_line)\nsubstitute_macros = job(_substitute_macros)\ncompile_paper = job(_compile_paper)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 4 + }, + { + "id": "8d911f98-3b80-457f-a0f4-3cb37ebf1691", + "cell_type": "code", + "source": "domain_size = 2.0", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 5 + }, + { + "id": "c6ea980b-6761-4191-8407-7b1f78a4c3ea", + "cell_type": "code", + "source": "source_directory = os.path.abspath(os.path.join(os.curdir, \"source\"))", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 6 + }, + { + "cell_type": "markdown", + "id": "b80c6588", + "source": "The calls below chain the six jobs together: mesh generation, XDMF conversion, the Poisson solve, line-plot postprocessing, LaTeX macro substitution and paper compilation. Since each stage runs an external tool in its own conda environment (see `source/envs/`), what is actually passed between jobs are file paths, not in-memory Python values.", + "metadata": {} + }, + { + "id": "71d411b6-cbec-489e-99e3-ba71680bcb5b", + "cell_type": "code", + "source": "gmsh_output_file = generate_mesh(\n domain_size=domain_size,\n source_directory=source_directory,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 7 + }, + { + "id": "1d0d9804-f250-48b3-a5d0-a546d520f79b", + "cell_type": "code", + "source": "meshio_output_dict = convert_to_xdmf(\n gmsh_output_file=gmsh_output_file,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 8 + }, + { + "id": "7b69bcff-e2b1-4d4a-b62c-6a1c86eeb590", + "cell_type": "code", + "source": "poisson_dict = poisson(\n meshio_output_xdmf=meshio_output_dict.output.xdmf_file, \n meshio_output_h5=meshio_output_dict.output.h5_file,\n source_directory=source_directory,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 9 + }, + { + "id": "3c4a29b0-eb1e-490a-8be0-e03cfff15e0a", + "cell_type": "code", + "source": "pvbatch_output_file = plot_over_line(\n poisson_output_pvd_file=poisson_dict.output.pvd_file, \n poisson_output_vtu_file=poisson_dict.output.vtu_file,\n source_directory=source_directory,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 10 + }, + { + "id": "a0a4c233-322d-4723-9627-62ca2487bfa9", + "cell_type": "code", + "source": "macros_tex_file = substitute_macros( \n pvbatch_output_file=pvbatch_output_file, \n ndofs=poisson_dict.output.numdofs, \n domain_size=domain_size,\n source_directory=source_directory,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 11 + }, + { + "id": "c281408f-e63d-4380-a7e6-c595d49fbb8f", + "cell_type": "code", + "source": "paper_output = compile_paper(\n macros_tex=macros_tex_file, \n plot_file=pvbatch_output_file,\n source_directory=source_directory,\n)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 12 + }, + { + "cell_type": "markdown", + "id": "4d1ce825", + "source": "Because pyiron builds a delayed call graph rather than an explicit `Flow`/`WorkGraph` object, `write_workflow_json` only needs the final delayed object (`paper_output`) — it walks the graph backwards to discover every upstream job.", + "metadata": {} + }, + { + "id": "63f29646-3846-4a97-a033-20e9df0ac214", + "cell_type": "code", + "source": "workflow_json_filename = \"pyiron_base_nfdi.json\"", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 13 + }, + { + "id": "f62111ba-9271-4987-9c7e-3b1c9f9eae7a", + "cell_type": "code", + "source": "write_workflow_json(delayed_object=paper_output, file_name=workflow_json_filename)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 14 + }, + { + "id": "d789971e-8f41-45fa-832a-11fd72dea96e", + "cell_type": "markdown", + "source": "## Load Workflow with aiida\n\n`load_workflow_json` rebuilds the pipeline as an `aiida-workgraph` `WorkGraph` from `pyiron_base_nfdi.json`, after connecting to a local AiiDA profile with `load_profile()`. `wg.run()` re-executes the whole pipeline under `aiida`.", + "metadata": {} + }, + { + "id": "a6e85e89-5d7a-40eb-809c-ac44974e3fd7", + "cell_type": "code", + "source": "from aiida import load_profile\n\nload_profile()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 15, + "output_type": "execute_result", + "data": { + "text/plain": "Profile" + }, + "metadata": {} + } + ], + "execution_count": 15 + }, + { + "id": "3de84fb7-b01b-4541-868a-92e881eb6e77", + "cell_type": "code", + "source": "from python_workflow_definition.aiida import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 16 + }, + { + "id": "b33f5528-10cd-47c8-8723-622902978859", + "cell_type": "code", + "source": "wg = load_workflow_json(file_name=workflow_json_filename)\nwg", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 17, + "output_type": "execute_result", + "data": { + "text/plain": "NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'WorkGra…", + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 1, + "model_id": "ecd2de75aecb4dc7b8db86590fff92bb" + } + }, + "metadata": {} + } + ], + "execution_count": 17 + }, + { + "id": "15282ca1-d339-40e7-ad68-8a7613ed08da", + "cell_type": "code", + "source": "wg.run()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "05/24/2025 05:45:10 AM <4326> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [81|WorkGraphEngine|continue_workgraph]: tasks ready to run: generate_mesh6\n05/24/2025 05:45:12 AM <4326> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [81|WorkGraphEngine|update_task_state]: Task: generate_mesh6, type: PyFunction, finished.\n05/24/2025 05:45:12 AM <4326> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [81|WorkGraphEngine|continue_workgraph]: tasks ready to run: convert_to_xdmf5\n05/24/2025 05:45:13 AM <4326> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [81|WorkGraphEngine|update_task_state]: Task: convert_to_xdmf5, type: PyFunction, finished.\n05/24/2025 05:45:13 AM <4326> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [81|WorkGraphEngine|continue_workgraph]: tasks ready to run: poisson4\n05/24/2025 05:45:16 AM <4326> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [81|WorkGraphEngine|update_task_state]: Task: poisson4, type: PyFunction, finished.\n05/24/2025 05:45:16 AM <4326> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [81|WorkGraphEngine|continue_workgraph]: tasks ready to run: plot_over_line3\n05/24/2025 05:45:18 AM <4326> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [81|WorkGraphEngine|update_task_state]: Task: plot_over_line3, type: PyFunction, finished.\n05/24/2025 05:45:18 AM <4326> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [81|WorkGraphEngine|continue_workgraph]: tasks ready to run: substitute_macros2\n05/24/2025 05:45:20 AM <4326> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [81|WorkGraphEngine|update_task_state]: Task: substitute_macros2, type: PyFunction, finished.\n05/24/2025 05:45:20 AM <4326> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [81|WorkGraphEngine|continue_workgraph]: tasks ready to run: compile_paper1\n05/24/2025 05:45:22 AM <4326> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [81|WorkGraphEngine|update_task_state]: Task: compile_paper1, type: PyFunction, finished.\n05/24/2025 05:45:22 AM <4326> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [81|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n05/24/2025 05:45:22 AM <4326> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [81|WorkGraphEngine|finalize]: Finalize workgraph.\n" + } + ], + "execution_count": 18 + }, + { + "id": "55dc8d12-dfe6-4465-a368-b7e590ae6800", + "cell_type": "markdown", + "source": "## Load Workflow with jobflow\n\nThe same JSON is reconstructed as a jobflow `Flow` and executed locally with `run_locally`, independently of the `pyiron_base` objects used to define it.", + "metadata": {} + }, + { + "id": "dff46eb8-e0e7-49bb-8c40-0db2df133124", + "cell_type": "code", + "source": "from python_workflow_definition.jobflow import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 19 + }, + { + "id": "6a189459-84e4-4738-ada1-37ee8c65b2ab", + "cell_type": "code", + "source": "from jobflow.managers.local import run_locally", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 20 + }, + { + "id": "6e7f3614-c971-4e2d-83f0-96f0d0fc04de", + "cell_type": "code", + "source": "flow = load_workflow_json(file_name=workflow_json_filename)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 21 + }, + { + "id": "2d87ed45-f5d9-403f-a03a-26be4a47a3ef", + "cell_type": "code", + "source": "result = run_locally(flow)\nresult", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "2025-05-24 05:45:23,211 INFO Started executing jobs locally\n2025-05-24 05:45:23,487 INFO Starting job - generate_mesh (afd8b83e-2283-40e8-9a75-4553a7ca72d0)\n2025-05-24 05:45:24,604 INFO Finished job - generate_mesh (afd8b83e-2283-40e8-9a75-4553a7ca72d0)\n2025-05-24 05:45:24,605 INFO Starting job - convert_to_xdmf (6723daca-18b6-4f38-8b3e-a92c2a227dc3)\n2025-05-24 05:45:26,001 INFO Finished job - convert_to_xdmf (6723daca-18b6-4f38-8b3e-a92c2a227dc3)\n2025-05-24 05:45:26,002 INFO Starting job - poisson (db43f907-45eb-4596-ac6b-ab5978cc5e17)\n2025-05-24 05:45:28,507 INFO Finished job - poisson (db43f907-45eb-4596-ac6b-ab5978cc5e17)\n2025-05-24 05:45:28,509 INFO Starting job - plot_over_line (b6493a73-f134-4067-ba0d-d6e2cd246afe)\n2025-05-24 05:45:29,933 INFO Finished job - plot_over_line (b6493a73-f134-4067-ba0d-d6e2cd246afe)\n2025-05-24 05:45:29,934 INFO Starting job - substitute_macros (65c3db44-dcc1-44ca-a1bb-374e8f5c771e)\n2025-05-24 05:45:30,774 INFO Finished job - substitute_macros (65c3db44-dcc1-44ca-a1bb-374e8f5c771e)\n2025-05-24 05:45:30,775 INFO Starting job - compile_paper (84277487-0e26-444b-92dc-4516ae8a4eba)\n2025-05-24 05:45:32,790 INFO Finished job - compile_paper (84277487-0e26-444b-92dc-4516ae8a4eba)\n2025-05-24 05:45:32,791 INFO Finished executing jobs locally\n" + }, + { + "execution_count": 22, + "output_type": "execute_result", + "data": { + "text/plain": "{'afd8b83e-2283-40e8-9a75-4553a7ca72d0': {1: Response(output='/home/jovyan/example_workflows/nfdi/preprocessing/square.msh', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n '6723daca-18b6-4f38-8b3e-a92c2a227dc3': {1: Response(output={'xdmf_file': '/home/jovyan/example_workflows/nfdi/preprocessing/square.xdmf', 'h5_file': '/home/jovyan/example_workflows/nfdi/preprocessing/square.h5'}, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n 'db43f907-45eb-4596-ac6b-ab5978cc5e17': {1: Response(output={'numdofs': 357, 'pvd_file': '/home/jovyan/example_workflows/nfdi/processing/poisson.pvd', 'vtu_file': '/home/jovyan/example_workflows/nfdi/processing/poisson000000.vtu'}, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n 'b6493a73-f134-4067-ba0d-d6e2cd246afe': {1: Response(output='/home/jovyan/example_workflows/nfdi/postprocessing/plotoverline.csv', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n '65c3db44-dcc1-44ca-a1bb-374e8f5c771e': {1: Response(output='/home/jovyan/example_workflows/nfdi/postprocessing/macros.tex', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n '84277487-0e26-444b-92dc-4516ae8a4eba': {1: Response(output='/home/jovyan/example_workflows/nfdi/postprocessing/paper.pdf', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))}}" + }, + "metadata": {} + } + ], + "execution_count": 22 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## Load Workflow with pyiron_workflow\n\nFinally, the graph is loaded into a `pyiron_workflow` `Workflow`. `.draw()` shows the node graph and `.run()` executes it end to end.", + "id": "385acbf585763632" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "from python_workflow_definition.pyiron_workflow import load_workflow_json", + "id": "927d0118cc4edfba" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf = load_workflow_json(file_name=workflow_json_filename)", + "id": "50055483ca2c9909" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.draw(size=(10,10))", + "id": "7d25a578c431e0f5" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.run()", + "id": "fff9513c4a127a96" + } + ] +} \ No newline at end of file diff --git a/_sources/example_workflows/nfdi/pyiron_workflow.ipynb b/_sources/example_workflows/nfdi/pyiron_workflow.ipynb new file mode 100644 index 00000000..2bc76e3a --- /dev/null +++ b/_sources/example_workflows/nfdi/pyiron_workflow.ipynb @@ -0,0 +1,428 @@ +{ + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.12.8", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + } + }, + "nbformat_minor": 5, + "nbformat": 4, + "cells": [ + { + "id": "106ded66-d202-46ac-82b0-2755ca309bdd", + "cell_type": "markdown", + "source": "# pyiron\n\nhttps://github.com/BAMresearch/NFDI4IngScientificWorkflowRequirements\n\nThis notebook defines the NFDI4Ing file-based workflow benchmark with [`pyiron_workflow`](https://github.com/pyiron/pyiron_workflow) and then loads the resulting `workflow.json` into `aiida`, `jobflow` and `pyiron_base`. Every stage of the pipeline shells out to an external command-line tool (`gmsh`, `meshio`, a FEniCS-based Poisson solver, ParaView's `pvbatch`, `tectonic`) in its own conda environment and passes file paths between stages rather than in-memory Python objects — see [`workflow.py`](workflow.py).", + "metadata": {} + }, + { + "id": "91dd48ea-aa7e-4937-a68e-59fc5017eb1e", + "cell_type": "markdown", + "source": "## Define workflow with pyiron_workflow\n\n`to_function_node` wraps each plain Python function into a `pyiron_workflow` node; the three arguments are the node's registered class name, the function itself, and the name of its (single, unlabeled) output. Nodes are assembled into a graph by assigning them as attributes of a `Workflow` object (`wf. = node(...)`), and dictionary outputs such as `convert_to_xdmf`'s are indexed with `wf.meshio_output_dict[\"xdmf_file\"]` when wiring the next node's input.", + "metadata": {} + }, + { + "id": "2c9622f5-ab7e-460e-b8e4-8d21413eda77", + "cell_type": "code", + "source": "import os", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 1 + }, + { + "id": "d265bb5aa6af79d6", + "cell_type": "code", + "source": "from workflow import (\n generate_mesh as _generate_mesh, \n convert_to_xdmf as _convert_to_xdmf,\n poisson as _poisson,\n plot_over_line as _plot_over_line,\n substitute_macros as _substitute_macros,\n compile_paper as _compile_paper,\n)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 2 + }, + { + "id": "2dced28725813fc1", + "cell_type": "code", + "source": "from pyiron_workflow._legacy import Workflow, to_function_node\n\nfrom python_workflow_definition.pyiron_workflow import write_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 3 + }, + { + "id": "549ecf27-88ef-4e77-8bd4-b616cfdda2e4", + "cell_type": "code", + "source": "generate_mesh = to_function_node(\"generate_mesh\", _generate_mesh, \"generate_mesh\")\nconvert_to_xdmf = to_function_node(\"convert_to_xdmf\", _convert_to_xdmf, \"convert_to_xdmf\")\npoisson = to_function_node(\"poisson\", _poisson, \"poisson\")\nplot_over_line = to_function_node(\"plot_over_line\", _plot_over_line, \"plot_over_line\")\nsubstitute_macros = to_function_node(\"substitute_macros\", _substitute_macros, \"substitute_macros\")\ncompile_paper = to_function_node(\"compile_paper\", _compile_paper, \"compile_paper\")", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 4 + }, + { + "id": "3a75428e-18c7-49cf-8256-23cff58b9d6e", + "cell_type": "code", + "source": "wf = Workflow(\"my_workflow\")", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 5 + }, + { + "id": "8d911f98-3b80-457f-a0f4-3cb37ebf1691", + "cell_type": "code", + "source": "wf.domain_size = 2.0", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 6 + }, + { + "id": "c6ea980b-6761-4191-8407-7b1f78a4c3ea", + "cell_type": "code", + "source": "wf.source_directory = os.path.abspath(os.path.join(os.curdir, \"source\"))", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 7 + }, + { + "cell_type": "markdown", + "id": "7c642a24", + "source": "The assignments below build the six-stage pipeline as attributes of `wf`: mesh generation, XDMF conversion, the Poisson solve, line-plot postprocessing, LaTeX macro substitution and paper compilation. Each stage runs an external tool in its own conda environment (see `source/envs/`), so the values connecting them are file paths on disk rather than shared Python objects.", + "metadata": {} + }, + { + "id": "71d411b6-cbec-489e-99e3-ba71680bcb5b", + "cell_type": "code", + "source": "wf.gmsh_output_file = generate_mesh(\n domain_size=wf.domain_size,\n source_directory=wf.source_directory,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 8 + }, + { + "id": "1d0d9804-f250-48b3-a5d0-a546d520f79b", + "cell_type": "code", + "source": "wf.meshio_output_dict = convert_to_xdmf(\n gmsh_output_file=wf.gmsh_output_file,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 9 + }, + { + "id": "7b69bcff-e2b1-4d4a-b62c-6a1c86eeb590", + "cell_type": "code", + "source": "wf.poisson_dict = poisson(\n meshio_output_xdmf=wf.meshio_output_dict[\"xdmf_file\"], \n meshio_output_h5=wf.meshio_output_dict[\"h5_file\"],\n source_directory=wf.source_directory,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 10 + }, + { + "id": "3c4a29b0-eb1e-490a-8be0-e03cfff15e0a", + "cell_type": "code", + "source": "wf.pvbatch_output_file = plot_over_line(\n poisson_output_pvd_file=wf.poisson_dict[\"pvd_file\"], \n poisson_output_vtu_file=wf.poisson_dict[\"vtu_file\"],\n source_directory=wf.source_directory,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 11 + }, + { + "id": "a0a4c233-322d-4723-9627-62ca2487bfa9", + "cell_type": "code", + "source": "wf.macros_tex_file = substitute_macros( \n pvbatch_output_file=wf.pvbatch_output_file, \n ndofs=wf.poisson_dict[\"numdofs\"], \n domain_size=wf.domain_size,\n source_directory=wf.source_directory,\n)", + "metadata": { + "tags": [], + "trusted": true + }, + "outputs": [], + "execution_count": 12 + }, + { + "id": "c281408f-e63d-4380-a7e6-c595d49fbb8f", + "cell_type": "code", + "source": "wf.paper_output = compile_paper(\n macros_tex=wf.macros_tex_file, \n plot_file=wf.pvbatch_output_file,\n source_directory=wf.source_directory,\n)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 13 + }, + { + "cell_type": "markdown", + "id": "cb9a923d", + "source": "`wf.draw()` renders the assembled node graph; `wf.graph_as_dict` is then handed to `write_workflow_json`, which serializes it into the PWD `workflow.json` format for the other engines to load.", + "metadata": {} + }, + { + "id": "db4f1e15-3710-4e24-abc2-0fef417043e8", + "cell_type": "code", + "source": "wf.draw(size=(10,10))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 14, + "output_type": "execute_result", + "data": { + "image/svg+xml": "\n\n\n\n\n\nclustermy_workflow\n\nmy_workflow: Workflow\n\nclustermy_workflowInputs\n\n\n\n\n\n\n\nInputs\n\n\nclustermy_workflowOutputsWithInjection\n\n\n\n\n\n\n\nOutputsWithInjection\n\n\nclustermy_workflowgmsh_output_file\n\n\n\n\n\n\n\ngmsh_output_file: generate_mesh\n\n\nclustermy_workflowgmsh_output_fileInputs\n\n\n\n\n\n\n\nInputs\n\n\nclustermy_workflowgmsh_output_fileOutputsWithInjection\n\n\n\n\n\n\n\nOutputsWithInjection\n\n\nclustermy_workflowmeshio_output_dict\n\n\n\n\n\n\n\nmeshio_output_dict: convert_to_xdmf\n\n\nclustermy_workflowmeshio_output_dictInputs\n\n\n\n\n\n\n\nInputs\n\n\nclustermy_workflowmeshio_output_dictOutputsWithInjection\n\n\n\n\n\n\n\nOutputsWithInjection\n\n\nclustermy_workflowinjected_GetItem_m7197572853956972366\n\n\n\n\n\n\n\ninjected_GetItem_m7197572853956972366: GetItem\n\n\nclustermy_workflowinjected_GetItem_m7197572853956972366Inputs\n\n\n\n\n\n\n\nInputs\n\n\nclustermy_workflowinjected_GetItem_m7197572853956972366OutputsWithInjection\n\n\n\n\n\n\n\nOutputsWithInjection\n\n\nclustermy_workflowinjected_GetItem_5401042856615209092\n\n\n\n\n\n\n\ninjected_GetItem_5401042856615209092: GetItem\n\n\nclustermy_workflowinjected_GetItem_5401042856615209092Inputs\n\n\n\n\n\n\n\nInputs\n\n\nclustermy_workflowinjected_GetItem_5401042856615209092OutputsWithInjection\n\n\n\n\n\n\n\nOutputsWithInjection\n\n\nclustermy_workflowpoisson_dict\n\n\n\n\n\n\n\npoisson_dict: poisson\n\n\nclustermy_workflowpoisson_dictInputs\n\n\n\n\n\n\n\nInputs\n\n\nclustermy_workflowpoisson_dictOutputsWithInjection\n\n\n\n\n\n\n\nOutputsWithInjection\n\n\nclustermy_workflowinjected_GetItem_5839915180513303609\n\n\n\n\n\n\n\ninjected_GetItem_5839915180513303609: GetItem\n\n\nclustermy_workflowinjected_GetItem_5839915180513303609Inputs\n\n\n\n\n\n\n\nInputs\n\n\nclustermy_workflowinjected_GetItem_5839915180513303609OutputsWithInjection\n\n\n\n\n\n\n\nOutputsWithInjection\n\n\nclustermy_workflowinjected_GetItem_m3497348724979863100\n\n\n\n\n\n\n\ninjected_GetItem_m3497348724979863100: GetItem\n\n\nclustermy_workflowinjected_GetItem_m3497348724979863100Inputs\n\n\n\n\n\n\n\nInputs\n\n\nclustermy_workflowinjected_GetItem_m3497348724979863100OutputsWithInjection\n\n\n\n\n\n\n\nOutputsWithInjection\n\n\nclustermy_workflowpvbatch_output_file\n\n\n\n\n\n\n\npvbatch_output_file: plot_over_line\n\n\nclustermy_workflowpvbatch_output_fileInputs\n\n\n\n\n\n\n\nInputs\n\n\nclustermy_workflowpvbatch_output_fileOutputsWithInjection\n\n\n\n\n\n\n\nOutputsWithInjection\n\n\nclustermy_workflowinjected_GetItem_m6105838930489235458\n\n\n\n\n\n\n\ninjected_GetItem_m6105838930489235458: GetItem\n\n\nclustermy_workflowinjected_GetItem_m6105838930489235458Inputs\n\n\n\n\n\n\n\nInputs\n\n\nclustermy_workflowinjected_GetItem_m6105838930489235458OutputsWithInjection\n\n\n\n\n\n\n\nOutputsWithInjection\n\n\nclustermy_workflowmacros_tex_file\n\n\n\n\n\n\n\nmacros_tex_file: substitute_macros\n\n\nclustermy_workflowmacros_tex_fileInputs\n\n\n\n\n\n\n\nInputs\n\n\nclustermy_workflowmacros_tex_fileOutputsWithInjection\n\n\n\n\n\n\n\nOutputsWithInjection\n\n\nclustermy_workflowpaper_output\n\n\n\n\n\n\n\npaper_output: compile_paper\n\n\nclustermy_workflowpaper_outputInputs\n\n\n\n\n\n\n\nInputs\n\n\nclustermy_workflowpaper_outputOutputsWithInjection\n\n\n\n\n\n\n\nOutputsWithInjection\n\n\n\nclustermy_workflowInputsrun\n\nrun\n\n\n\nclustermy_workflowOutputsWithInjectionran\n\nran\n\n\n\n\nclustermy_workflowInputsaccumulate_and_run\n\naccumulate_and_run\n\n\n\nclustermy_workflowInputsgmsh_output_file__domain_size\n\ngmsh_output_file__domain_size: float\n\n\n\nclustermy_workflowgmsh_output_fileInputsdomain_size\n\ndomain_size: float\n\n\n\nclustermy_workflowInputsgmsh_output_file__domain_size->clustermy_workflowgmsh_output_fileInputsdomain_size\n\n\n\n\n\n\nclustermy_workflowInputsgmsh_output_file__source_directory\n\ngmsh_output_file__source_directory: str\n\n\n\nclustermy_workflowgmsh_output_fileInputssource_directory\n\nsource_directory: str\n\n\n\nclustermy_workflowInputsgmsh_output_file__source_directory->clustermy_workflowgmsh_output_fileInputssource_directory\n\n\n\n\n\n\nclustermy_workflowInputsinjected_GetItem_m7197572853956972366__item\n\ninjected_GetItem_m7197572853956972366__item\n\n\n\nclustermy_workflowinjected_GetItem_m7197572853956972366Inputsitem\n\nitem\n\n\n\nclustermy_workflowInputsinjected_GetItem_m7197572853956972366__item->clustermy_workflowinjected_GetItem_m7197572853956972366Inputsitem\n\n\n\n\n\n\nclustermy_workflowInputsinjected_GetItem_5401042856615209092__item\n\ninjected_GetItem_5401042856615209092__item\n\n\n\nclustermy_workflowinjected_GetItem_5401042856615209092Inputsitem\n\nitem\n\n\n\nclustermy_workflowInputsinjected_GetItem_5401042856615209092__item->clustermy_workflowinjected_GetItem_5401042856615209092Inputsitem\n\n\n\n\n\n\nclustermy_workflowInputspoisson_dict__source_directory\n\npoisson_dict__source_directory: str\n\n\n\nclustermy_workflowpoisson_dictInputssource_directory\n\nsource_directory: str\n\n\n\nclustermy_workflowInputspoisson_dict__source_directory->clustermy_workflowpoisson_dictInputssource_directory\n\n\n\n\n\n\nclustermy_workflowInputsinjected_GetItem_5839915180513303609__item\n\ninjected_GetItem_5839915180513303609__item\n\n\n\nclustermy_workflowinjected_GetItem_5839915180513303609Inputsitem\n\nitem\n\n\n\nclustermy_workflowInputsinjected_GetItem_5839915180513303609__item->clustermy_workflowinjected_GetItem_5839915180513303609Inputsitem\n\n\n\n\n\n\nclustermy_workflowInputsinjected_GetItem_m3497348724979863100__item\n\ninjected_GetItem_m3497348724979863100__item\n\n\n\nclustermy_workflowinjected_GetItem_m3497348724979863100Inputsitem\n\nitem\n\n\n\nclustermy_workflowInputsinjected_GetItem_m3497348724979863100__item->clustermy_workflowinjected_GetItem_m3497348724979863100Inputsitem\n\n\n\n\n\n\nclustermy_workflowInputspvbatch_output_file__source_directory\n\npvbatch_output_file__source_directory: str\n\n\n\nclustermy_workflowpvbatch_output_fileInputssource_directory\n\nsource_directory: str\n\n\n\nclustermy_workflowInputspvbatch_output_file__source_directory->clustermy_workflowpvbatch_output_fileInputssource_directory\n\n\n\n\n\n\nclustermy_workflowInputsinjected_GetItem_m6105838930489235458__item\n\ninjected_GetItem_m6105838930489235458__item\n\n\n\nclustermy_workflowinjected_GetItem_m6105838930489235458Inputsitem\n\nitem\n\n\n\nclustermy_workflowInputsinjected_GetItem_m6105838930489235458__item->clustermy_workflowinjected_GetItem_m6105838930489235458Inputsitem\n\n\n\n\n\n\nclustermy_workflowInputsmacros_tex_file__domain_size\n\nmacros_tex_file__domain_size: float\n\n\n\nclustermy_workflowmacros_tex_fileInputsdomain_size\n\ndomain_size: float\n\n\n\nclustermy_workflowInputsmacros_tex_file__domain_size->clustermy_workflowmacros_tex_fileInputsdomain_size\n\n\n\n\n\n\nclustermy_workflowInputsmacros_tex_file__source_directory\n\nmacros_tex_file__source_directory: str\n\n\n\nclustermy_workflowmacros_tex_fileInputssource_directory\n\nsource_directory: str\n\n\n\nclustermy_workflowInputsmacros_tex_file__source_directory->clustermy_workflowmacros_tex_fileInputssource_directory\n\n\n\n\n\n\nclustermy_workflowInputspaper_output__source_directory\n\npaper_output__source_directory: str\n\n\n\nclustermy_workflowpaper_outputInputssource_directory\n\nsource_directory: str\n\n\n\nclustermy_workflowInputspaper_output__source_directory->clustermy_workflowpaper_outputInputssource_directory\n\n\n\n\n\n\nclustermy_workflowOutputsWithInjectionfailed\n\nfailed\n\n\n\nclustermy_workflowOutputsWithInjectionpaper_output__compile_paper\n\npaper_output__compile_paper: str\n\n\n\nclustermy_workflowgmsh_output_fileInputsrun\n\nrun\n\n\n\nclustermy_workflowgmsh_output_fileOutputsWithInjectionran\n\nran\n\n\n\n\nclustermy_workflowgmsh_output_fileInputsaccumulate_and_run\n\naccumulate_and_run\n\n\n\nclustermy_workflowgmsh_output_fileOutputsWithInjectionfailed\n\nfailed\n\n\n\nclustermy_workflowgmsh_output_fileOutputsWithInjectiongenerate_mesh\n\ngenerate_mesh: str\n\n\n\nclustermy_workflowmeshio_output_dictInputsgmsh_output_file\n\ngmsh_output_file: str\n\n\n\nclustermy_workflowgmsh_output_fileOutputsWithInjectiongenerate_mesh->clustermy_workflowmeshio_output_dictInputsgmsh_output_file\n\n\n\n\n\n\nclustermy_workflowmeshio_output_dictInputsrun\n\nrun\n\n\n\nclustermy_workflowmeshio_output_dictOutputsWithInjectionran\n\nran\n\n\n\n\nclustermy_workflowmeshio_output_dictInputsaccumulate_and_run\n\naccumulate_and_run\n\n\n\nclustermy_workflowmeshio_output_dictOutputsWithInjectionfailed\n\nfailed\n\n\n\nclustermy_workflowmeshio_output_dictOutputsWithInjectionconvert_to_xdmf\n\nconvert_to_xdmf: dict\n\n\n\nclustermy_workflowinjected_GetItem_m7197572853956972366Inputsobj\n\nobj\n\n\n\nclustermy_workflowmeshio_output_dictOutputsWithInjectionconvert_to_xdmf->clustermy_workflowinjected_GetItem_m7197572853956972366Inputsobj\n\n\n\n\n\n\nclustermy_workflowinjected_GetItem_5401042856615209092Inputsobj\n\nobj\n\n\n\nclustermy_workflowmeshio_output_dictOutputsWithInjectionconvert_to_xdmf->clustermy_workflowinjected_GetItem_5401042856615209092Inputsobj\n\n\n\n\n\n\nclustermy_workflowinjected_GetItem_m7197572853956972366Inputsrun\n\nrun\n\n\n\nclustermy_workflowinjected_GetItem_m7197572853956972366OutputsWithInjectionran\n\nran\n\n\n\n\nclustermy_workflowinjected_GetItem_m7197572853956972366Inputsaccumulate_and_run\n\naccumulate_and_run\n\n\n\nclustermy_workflowinjected_GetItem_m7197572853956972366OutputsWithInjectionfailed\n\nfailed\n\n\n\nclustermy_workflowinjected_GetItem_m7197572853956972366OutputsWithInjectiongetitem\n\ngetitem\n\n\n\nclustermy_workflowpoisson_dictInputsmeshio_output_xdmf\n\nmeshio_output_xdmf: str\n\n\n\nclustermy_workflowinjected_GetItem_m7197572853956972366OutputsWithInjectiongetitem->clustermy_workflowpoisson_dictInputsmeshio_output_xdmf\n\n\n\n\n\n\nclustermy_workflowinjected_GetItem_5401042856615209092Inputsrun\n\nrun\n\n\n\nclustermy_workflowinjected_GetItem_5401042856615209092OutputsWithInjectionran\n\nran\n\n\n\n\nclustermy_workflowinjected_GetItem_5401042856615209092Inputsaccumulate_and_run\n\naccumulate_and_run\n\n\n\nclustermy_workflowinjected_GetItem_5401042856615209092OutputsWithInjectionfailed\n\nfailed\n\n\n\nclustermy_workflowinjected_GetItem_5401042856615209092OutputsWithInjectiongetitem\n\ngetitem\n\n\n\nclustermy_workflowpoisson_dictInputsmeshio_output_h5\n\nmeshio_output_h5: str\n\n\n\nclustermy_workflowinjected_GetItem_5401042856615209092OutputsWithInjectiongetitem->clustermy_workflowpoisson_dictInputsmeshio_output_h5\n\n\n\n\n\n\nclustermy_workflowpoisson_dictInputsrun\n\nrun\n\n\n\nclustermy_workflowpoisson_dictOutputsWithInjectionran\n\nran\n\n\n\n\nclustermy_workflowpoisson_dictInputsaccumulate_and_run\n\naccumulate_and_run\n\n\n\nclustermy_workflowpoisson_dictOutputsWithInjectionfailed\n\nfailed\n\n\n\nclustermy_workflowpoisson_dictOutputsWithInjectionpoisson\n\npoisson: dict\n\n\n\nclustermy_workflowinjected_GetItem_5839915180513303609Inputsobj\n\nobj\n\n\n\nclustermy_workflowpoisson_dictOutputsWithInjectionpoisson->clustermy_workflowinjected_GetItem_5839915180513303609Inputsobj\n\n\n\n\n\n\nclustermy_workflowinjected_GetItem_m3497348724979863100Inputsobj\n\nobj\n\n\n\nclustermy_workflowpoisson_dictOutputsWithInjectionpoisson->clustermy_workflowinjected_GetItem_m3497348724979863100Inputsobj\n\n\n\n\n\n\nclustermy_workflowinjected_GetItem_m6105838930489235458Inputsobj\n\nobj\n\n\n\nclustermy_workflowpoisson_dictOutputsWithInjectionpoisson->clustermy_workflowinjected_GetItem_m6105838930489235458Inputsobj\n\n\n\n\n\n\nclustermy_workflowinjected_GetItem_5839915180513303609Inputsrun\n\nrun\n\n\n\nclustermy_workflowinjected_GetItem_5839915180513303609OutputsWithInjectionran\n\nran\n\n\n\n\nclustermy_workflowinjected_GetItem_5839915180513303609Inputsaccumulate_and_run\n\naccumulate_and_run\n\n\n\nclustermy_workflowinjected_GetItem_5839915180513303609OutputsWithInjectionfailed\n\nfailed\n\n\n\nclustermy_workflowinjected_GetItem_5839915180513303609OutputsWithInjectiongetitem\n\ngetitem\n\n\n\nclustermy_workflowpvbatch_output_fileInputspoisson_output_pvd_file\n\npoisson_output_pvd_file: str\n\n\n\nclustermy_workflowinjected_GetItem_5839915180513303609OutputsWithInjectiongetitem->clustermy_workflowpvbatch_output_fileInputspoisson_output_pvd_file\n\n\n\n\n\n\nclustermy_workflowinjected_GetItem_m3497348724979863100Inputsrun\n\nrun\n\n\n\nclustermy_workflowinjected_GetItem_m3497348724979863100OutputsWithInjectionran\n\nran\n\n\n\n\nclustermy_workflowinjected_GetItem_m3497348724979863100Inputsaccumulate_and_run\n\naccumulate_and_run\n\n\n\nclustermy_workflowinjected_GetItem_m3497348724979863100OutputsWithInjectionfailed\n\nfailed\n\n\n\nclustermy_workflowinjected_GetItem_m3497348724979863100OutputsWithInjectiongetitem\n\ngetitem\n\n\n\nclustermy_workflowpvbatch_output_fileInputspoisson_output_vtu_file\n\npoisson_output_vtu_file: str\n\n\n\nclustermy_workflowinjected_GetItem_m3497348724979863100OutputsWithInjectiongetitem->clustermy_workflowpvbatch_output_fileInputspoisson_output_vtu_file\n\n\n\n\n\n\nclustermy_workflowpvbatch_output_fileInputsrun\n\nrun\n\n\n\nclustermy_workflowpvbatch_output_fileOutputsWithInjectionran\n\nran\n\n\n\n\nclustermy_workflowpvbatch_output_fileInputsaccumulate_and_run\n\naccumulate_and_run\n\n\n\nclustermy_workflowpvbatch_output_fileOutputsWithInjectionfailed\n\nfailed\n\n\n\nclustermy_workflowpvbatch_output_fileOutputsWithInjectionplot_over_line\n\nplot_over_line: str\n\n\n\nclustermy_workflowmacros_tex_fileInputspvbatch_output_file\n\npvbatch_output_file: str\n\n\n\nclustermy_workflowpvbatch_output_fileOutputsWithInjectionplot_over_line->clustermy_workflowmacros_tex_fileInputspvbatch_output_file\n\n\n\n\n\n\nclustermy_workflowpaper_outputInputsplot_file\n\nplot_file: str\n\n\n\nclustermy_workflowpvbatch_output_fileOutputsWithInjectionplot_over_line->clustermy_workflowpaper_outputInputsplot_file\n\n\n\n\n\n\nclustermy_workflowinjected_GetItem_m6105838930489235458Inputsrun\n\nrun\n\n\n\nclustermy_workflowinjected_GetItem_m6105838930489235458OutputsWithInjectionran\n\nran\n\n\n\n\nclustermy_workflowinjected_GetItem_m6105838930489235458Inputsaccumulate_and_run\n\naccumulate_and_run\n\n\n\nclustermy_workflowinjected_GetItem_m6105838930489235458OutputsWithInjectionfailed\n\nfailed\n\n\n\nclustermy_workflowinjected_GetItem_m6105838930489235458OutputsWithInjectiongetitem\n\ngetitem\n\n\n\nclustermy_workflowmacros_tex_fileInputsndofs\n\nndofs: int\n\n\n\nclustermy_workflowinjected_GetItem_m6105838930489235458OutputsWithInjectiongetitem->clustermy_workflowmacros_tex_fileInputsndofs\n\n\n\n\n\n\nclustermy_workflowmacros_tex_fileInputsrun\n\nrun\n\n\n\nclustermy_workflowmacros_tex_fileOutputsWithInjectionran\n\nran\n\n\n\n\nclustermy_workflowmacros_tex_fileInputsaccumulate_and_run\n\naccumulate_and_run\n\n\n\nclustermy_workflowmacros_tex_fileOutputsWithInjectionfailed\n\nfailed\n\n\n\nclustermy_workflowmacros_tex_fileOutputsWithInjectionsubstitute_macros\n\nsubstitute_macros: str\n\n\n\nclustermy_workflowpaper_outputInputsmacros_tex\n\nmacros_tex: str\n\n\n\nclustermy_workflowmacros_tex_fileOutputsWithInjectionsubstitute_macros->clustermy_workflowpaper_outputInputsmacros_tex\n\n\n\n\n\n\nclustermy_workflowpaper_outputInputsrun\n\nrun\n\n\n\nclustermy_workflowpaper_outputOutputsWithInjectionran\n\nran\n\n\n\n\nclustermy_workflowpaper_outputInputsaccumulate_and_run\n\naccumulate_and_run\n\n\n\nclustermy_workflowpaper_outputOutputsWithInjectionfailed\n\nfailed\n\n\n\nclustermy_workflowpaper_outputOutputsWithInjectioncompile_paper\n\ncompile_paper: str\n\n\n\nclustermy_workflowpaper_outputOutputsWithInjectioncompile_paper->clustermy_workflowOutputsWithInjectionpaper_output__compile_paper\n\n\n\n\n\n\n", + "text/plain": "" + }, + "metadata": {} + } + ], + "execution_count": 14 + }, + { + "id": "63f29646-3846-4a97-a033-20e9df0ac214", + "cell_type": "code", + "source": "workflow_json_filename = \"pyiron_workflow_nfdi.json\"", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 15 + }, + { + "id": "f62111ba-9271-4987-9c7e-3b1c9f9eae7a", + "cell_type": "code", + "source": "write_workflow_json(graph_as_dict=wf.graph_as_dict, file_name=workflow_json_filename)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 16 + }, + { + "id": "d789971e-8f41-45fa-832a-11fd72dea96e", + "cell_type": "markdown", + "source": "## Load Workflow with aiida\n\n`load_workflow_json` rebuilds the pipeline as an `aiida-workgraph` `WorkGraph` from `pyiron_workflow_nfdi.json`, after connecting to a local AiiDA profile with `load_profile()`. `wg.run()` re-executes the whole pipeline under `aiida`.", + "metadata": {} + }, + { + "id": "a6e85e89-5d7a-40eb-809c-ac44974e3fd7", + "cell_type": "code", + "source": "from aiida import load_profile\n\nload_profile()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 17, + "output_type": "execute_result", + "data": { + "text/plain": "Profile" + }, + "metadata": {} + } + ], + "execution_count": 17 + }, + { + "id": "3de84fb7-b01b-4541-868a-92e881eb6e77", + "cell_type": "code", + "source": "from python_workflow_definition.aiida import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 18 + }, + { + "id": "b33f5528-10cd-47c8-8723-622902978859", + "cell_type": "code", + "source": "wg = load_workflow_json(file_name=workflow_json_filename)\nwg", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 19, + "output_type": "execute_result", + "data": { + "text/plain": "NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'WorkGra…", + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 1, + "model_id": "6641ced7603742b8b28900587d764b7c" + } + }, + "metadata": {} + } + ], + "execution_count": 19 + }, + { + "id": "15282ca1-d339-40e7-ad68-8a7613ed08da", + "cell_type": "code", + "source": "wg.run()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "05/24/2025 09:30:18 AM <282> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: generate_mesh1\n05/24/2025 09:30:20 AM <282> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|update_task_state]: Task: generate_mesh1, type: PyFunction, finished.\n05/24/2025 09:30:20 AM <282> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: convert_to_xdmf2\n05/24/2025 09:30:22 AM <282> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|update_task_state]: Task: convert_to_xdmf2, type: PyFunction, finished.\n05/24/2025 09:30:22 AM <282> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: poisson3\n05/24/2025 09:30:30 AM <282> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|update_task_state]: Task: poisson3, type: PyFunction, finished.\n05/24/2025 09:30:30 AM <282> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: plot_over_line4\n05/24/2025 09:30:33 AM <282> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|update_task_state]: Task: plot_over_line4, type: PyFunction, finished.\n05/24/2025 09:30:33 AM <282> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: substitute_macros5\n05/24/2025 09:30:34 AM <282> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|update_task_state]: Task: substitute_macros5, type: PyFunction, finished.\n05/24/2025 09:30:34 AM <282> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: compile_paper6\n05/24/2025 09:30:50 AM <282> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|update_task_state]: Task: compile_paper6, type: PyFunction, finished.\n05/24/2025 09:30:50 AM <282> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n05/24/2025 09:30:50 AM <282> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [3|WorkGraphEngine|finalize]: Finalize workgraph.\n" + } + ], + "execution_count": 20 + }, + { + "id": "55dc8d12-dfe6-4465-a368-b7e590ae6800", + "cell_type": "markdown", + "source": "## Load Workflow with jobflow\n\nThe same JSON is reconstructed as a jobflow `Flow` and executed locally with `run_locally`, independently of the `pyiron_workflow` objects used to define it.", + "metadata": {} + }, + { + "id": "dff46eb8-e0e7-49bb-8c40-0db2df133124", + "cell_type": "code", + "source": "from python_workflow_definition.jobflow import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 21 + }, + { + "id": "6a189459-84e4-4738-ada1-37ee8c65b2ab", + "cell_type": "code", + "source": "from jobflow.managers.local import run_locally", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 22 + }, + { + "id": "6e7f3614-c971-4e2d-83f0-96f0d0fc04de", + "cell_type": "code", + "source": "flow = load_workflow_json(file_name=workflow_json_filename)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 23 + }, + { + "id": "2d87ed45-f5d9-403f-a03a-26be4a47a3ef", + "cell_type": "code", + "source": "result = run_locally(flow)\nresult", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "2025-05-24 09:31:15,165 INFO Started executing jobs locally\n2025-05-24 09:31:15,364 INFO Starting job - generate_mesh (4cc4e3d9-39aa-4c20-a047-a029b6812d61)\n2025-05-24 09:31:16,480 INFO Finished job - generate_mesh (4cc4e3d9-39aa-4c20-a047-a029b6812d61)\n2025-05-24 09:31:16,481 INFO Starting job - convert_to_xdmf (8527c563-c0b1-4ae5-a6c3-00ae25ad2508)\n2025-05-24 09:31:17,834 INFO Finished job - convert_to_xdmf (8527c563-c0b1-4ae5-a6c3-00ae25ad2508)\n2025-05-24 09:31:17,836 INFO Starting job - poisson (58b31d24-51f9-4b9a-ac3e-88a7f01a09ad)\n2025-05-24 09:31:20,318 INFO Finished job - poisson (58b31d24-51f9-4b9a-ac3e-88a7f01a09ad)\n2025-05-24 09:31:20,318 INFO Starting job - plot_over_line (b095dc38-f858-4c34-876c-df8f8b851a5f)\n2025-05-24 09:31:21,717 INFO Finished job - plot_over_line (b095dc38-f858-4c34-876c-df8f8b851a5f)\n2025-05-24 09:31:21,718 INFO Starting job - substitute_macros (656e820d-20d5-4665-bb8a-43807ed6b2e9)\n2025-05-24 09:31:22,542 INFO Finished job - substitute_macros (656e820d-20d5-4665-bb8a-43807ed6b2e9)\n2025-05-24 09:31:22,543 INFO Starting job - compile_paper (52de4e6d-7574-401b-bcdb-ae6c298cc6b9)\n2025-05-24 09:31:24,556 INFO Finished job - compile_paper (52de4e6d-7574-401b-bcdb-ae6c298cc6b9)\n2025-05-24 09:31:24,557 INFO Finished executing jobs locally\n" + }, + { + "execution_count": 24, + "output_type": "execute_result", + "data": { + "text/plain": "{'4cc4e3d9-39aa-4c20-a047-a029b6812d61': {1: Response(output='/home/jovyan/example_workflows/nfdi/preprocessing/square.msh', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n '8527c563-c0b1-4ae5-a6c3-00ae25ad2508': {1: Response(output={'xdmf_file': '/home/jovyan/example_workflows/nfdi/preprocessing/square.xdmf', 'h5_file': '/home/jovyan/example_workflows/nfdi/preprocessing/square.h5'}, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n '58b31d24-51f9-4b9a-ac3e-88a7f01a09ad': {1: Response(output={'numdofs': 357, 'pvd_file': '/home/jovyan/example_workflows/nfdi/processing/poisson.pvd', 'vtu_file': '/home/jovyan/example_workflows/nfdi/processing/poisson000000.vtu'}, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n 'b095dc38-f858-4c34-876c-df8f8b851a5f': {1: Response(output='/home/jovyan/example_workflows/nfdi/postprocessing/plotoverline.csv', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n '656e820d-20d5-4665-bb8a-43807ed6b2e9': {1: Response(output='/home/jovyan/example_workflows/nfdi/postprocessing/macros.tex', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n '52de4e6d-7574-401b-bcdb-ae6c298cc6b9': {1: Response(output='/home/jovyan/example_workflows/nfdi/postprocessing/paper.pdf', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))}}" + }, + "metadata": {} + } + ], + "execution_count": 24 + }, + { + "id": "ebd3248b-ff75-40bf-a488-b5e338342671", + "cell_type": "markdown", + "source": "## Load Workflow with pyiron_base\n\nFinally, the graph is loaded into a list of delayed `pyiron_base` jobs. `.draw()` visualizes the dependency chain and `.pull()` triggers execution, returning the final `paper.pdf` path.", + "metadata": {} + }, + { + "id": "c7e1047f-0d42-4777-911d-ab405396401a", + "cell_type": "code", + "source": "from python_workflow_definition.pyiron_base import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 25 + }, + { + "id": "6aeba274-10d3-4e79-8ee4-4d870f163939", + "cell_type": "code", + "source": "delayed_object_lst = load_workflow_json(file_name=workflow_json_filename)\ndelayed_object_lst[-1].draw()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "", + "image/svg+xml": "\n\n\n\n\ncreate_function_job_ba0bf2668d8f7b42ff717c2cb79b5920\n\ncreate_function_job=<pyiron_base.project.delayed.DelayedObject object at 0x76dba30d9280>\n\n\n\nplot_file_5007b1d67345934b2ffcdeaaad6ea2ab\n\nplot_file=<pyiron_base.project.delayed.DelayedObject object at 0x76dba30d8da0>\n\n\n\nplot_file_5007b1d67345934b2ffcdeaaad6ea2ab->create_function_job_ba0bf2668d8f7b42ff717c2cb79b5920\n\n\n\n\n\npoisson_output_vtu_file_51141ca0ec0a07922807865d8a067793\n\npoisson_output_vtu_file=<pyiron_base.project.delayed.DelayedObject object at 0x76dba30d8a40>\n\n\n\npoisson_output_vtu_file_51141ca0ec0a07922807865d8a067793->plot_file_5007b1d67345934b2ffcdeaaad6ea2ab\n\n\n\n\n\npvbatch_output_file_5007b1d67345934b2ffcdeaaad6ea2ab\n\npvbatch_output_file=<pyiron_base.project.delayed.DelayedObject object at 0x76dba30d8da0>\n\n\n\npoisson_output_vtu_file_51141ca0ec0a07922807865d8a067793->pvbatch_output_file_5007b1d67345934b2ffcdeaaad6ea2ab\n\n\n\n\n\nmacros_tex_02d82cedf90ad323f7eef57ddf383160\n\nmacros_tex=<pyiron_base.project.delayed.DelayedObject object at 0x76dba30d9070>\n\n\n\npvbatch_output_file_5007b1d67345934b2ffcdeaaad6ea2ab->macros_tex_02d82cedf90ad323f7eef57ddf383160\n\n\n\n\n\nmeshio_output_h5_0af06cb14e9ddc7585647c44e4d4ef88\n\nmeshio_output_h5=<pyiron_base.project.delayed.DelayedObject object at 0x76dba3cb2600>\n\n\n\nmeshio_output_h5_0af06cb14e9ddc7585647c44e4d4ef88->poisson_output_vtu_file_51141ca0ec0a07922807865d8a067793\n\n\n\n\n\npoisson_output_pvd_file_0440a581658dfd1533b4c5d08eaf8513\n\npoisson_output_pvd_file=<pyiron_base.project.delayed.DelayedObject object at 0x76dba30d8a10>\n\n\n\nmeshio_output_h5_0af06cb14e9ddc7585647c44e4d4ef88->poisson_output_pvd_file_0440a581658dfd1533b4c5d08eaf8513\n\n\n\n\n\nndofs_ac7427db28c0527371c0e9b27a57024b\n\nndofs=<pyiron_base.project.delayed.DelayedObject object at 0x76dba30d8e30>\n\n\n\nmeshio_output_h5_0af06cb14e9ddc7585647c44e4d4ef88->ndofs_ac7427db28c0527371c0e9b27a57024b\n\n\n\n\n\npoisson_output_pvd_file_0440a581658dfd1533b4c5d08eaf8513->plot_file_5007b1d67345934b2ffcdeaaad6ea2ab\n\n\n\n\n\npoisson_output_pvd_file_0440a581658dfd1533b4c5d08eaf8513->pvbatch_output_file_5007b1d67345934b2ffcdeaaad6ea2ab\n\n\n\n\n\nndofs_ac7427db28c0527371c0e9b27a57024b->macros_tex_02d82cedf90ad323f7eef57ddf383160\n\n\n\n\n\ngmsh_output_file_6ef41eb684984daa8337ee65c2aa9f18\n\ngmsh_output_file=<pyiron_base.project.delayed.DelayedObject object at 0x76dba89319d0>\n\n\n\ngmsh_output_file_6ef41eb684984daa8337ee65c2aa9f18->meshio_output_h5_0af06cb14e9ddc7585647c44e4d4ef88\n\n\n\n\n\nmeshio_output_xdmf_c383e7d9f83d7cdc8ae04ebf9c264173\n\nmeshio_output_xdmf=<pyiron_base.project.delayed.DelayedObject object at 0x76dba30d8710>\n\n\n\ngmsh_output_file_6ef41eb684984daa8337ee65c2aa9f18->meshio_output_xdmf_c383e7d9f83d7cdc8ae04ebf9c264173\n\n\n\n\n\nmeshio_output_xdmf_c383e7d9f83d7cdc8ae04ebf9c264173->poisson_output_vtu_file_51141ca0ec0a07922807865d8a067793\n\n\n\n\n\nmeshio_output_xdmf_c383e7d9f83d7cdc8ae04ebf9c264173->poisson_output_pvd_file_0440a581658dfd1533b4c5d08eaf8513\n\n\n\n\n\nmeshio_output_xdmf_c383e7d9f83d7cdc8ae04ebf9c264173->ndofs_ac7427db28c0527371c0e9b27a57024b\n\n\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20\n\ndomain_size=2.0\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20->gmsh_output_file_6ef41eb684984daa8337ee65c2aa9f18\n\n\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20->macros_tex_02d82cedf90ad323f7eef57ddf383160\n\n\n\n\n\nmacros_tex_02d82cedf90ad323f7eef57ddf383160->create_function_job_ba0bf2668d8f7b42ff717c2cb79b5920\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696\n\nsource_directory=/home/jovyan/example_workflows/nfdi/source\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->create_function_job_ba0bf2668d8f7b42ff717c2cb79b5920\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->plot_file_5007b1d67345934b2ffcdeaaad6ea2ab\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->poisson_output_vtu_file_51141ca0ec0a07922807865d8a067793\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->pvbatch_output_file_5007b1d67345934b2ffcdeaaad6ea2ab\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->poisson_output_pvd_file_0440a581658dfd1533b4c5d08eaf8513\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->ndofs_ac7427db28c0527371c0e9b27a57024b\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->gmsh_output_file_6ef41eb684984daa8337ee65c2aa9f18\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->macros_tex_02d82cedf90ad323f7eef57ddf383160\n\n\n\n\n" + }, + "metadata": {} + } + ], + "execution_count": 26 + }, + { + "id": "ea92c7ad-afef-423c-b8fa-9d24c1267c73", + "cell_type": "code", + "source": "delayed_object_lst[-1].pull()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "The job generate_mesh_47725c16637f799ac042e47468005db3 was saved and received the ID: 1\nThe job convert_to_xdmf_d6a46eb9a4ec352aa996e783ec3c785f was saved and received the ID: 2\nThe job poisson_3c147fc86db87cf0c0f94bda333f8cd8 was saved and received the ID: 3\nThe job plot_over_line_ef50933291910dadcc8311924971e127 was saved and received the ID: 4\nThe job substitute_macros_63766eafd6b1980c7832dd8c9a97c96e was saved and received the ID: 5\nThe job compile_paper_128d1d58374953c00e95b8de62cbb10b was saved and received the ID: 6\n" + }, + { + "execution_count": 27, + "output_type": "execute_result", + "data": { + "text/plain": "'/home/jovyan/example_workflows/nfdi/postprocessing/paper.pdf'" + }, + "metadata": {} + } + ], + "execution_count": 27 + }, + { + "id": "32287743-e59a-467c-92fe-8586f199e36e", + "cell_type": "code", + "source": "", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": null + } + ] +} diff --git a/_sources/example_workflows/nfdi/universal_workflow.ipynb b/_sources/example_workflows/nfdi/universal_workflow.ipynb new file mode 100644 index 00000000..8ceeaad3 --- /dev/null +++ b/_sources/example_workflows/nfdi/universal_workflow.ipynb @@ -0,0 +1,357 @@ +{ + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.12.8", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + } + }, + "nbformat_minor": 4, + "nbformat": 4, + "cells": [ + { + "cell_type": "markdown", + "source": "# Load Simple Workflow\n\nThis notebook loads the single, pre-existing NFDI4Ing `workflow.json` — the file-based benchmark from [`workflow.py`](workflow.py) that runs `gmsh`, `meshio`, a FEniCS-based Poisson solver, ParaView's `pvbatch` and `tectonic` in turn — with several different engines. Since the JSON only describes function nodes, inputs, outputs and the edges between them, it does not matter which engine originally wrote it; any of the engines below can load and execute it, each re-running the same chain of external tools.", + "metadata": {} + }, + { + "cell_type": "markdown", + "source": "## Plot\n\nBefore running the workflow with any engine, `python_workflow_definition.plot.plot` renders `workflow.json` directly as a graph of function, input and output nodes — independent of any particular workflow engine.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.plot import plot", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 1 + }, + { + "cell_type": "code", + "source": "plot(file_name='workflow.json')", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "", + "image/svg+xml": "\n\n\n\n\n0\n\nworkflow.generate_mesh\n\n\n\n1\n\nworkflow.convert_to_xdmf\n\n\n\n0->1\n\n\ngmsh_output_file\n\n\n\n2\n\nworkflow.poisson\n\n\n\n1->2\n\n\n\n\n\n3\n\nworkflow.plot_over_line\n\n\n\n2->3\n\n\n\n\n\n4\n\nworkflow.substitute_macros\n\n\n\n2->4\n\n\nndofs=result[numdofs]\n\n\n\n3->4\n\n\npvbatch_output_file\n\n\n\n5\n\nworkflow.compile_paper\n\n\n\n3->5\n\n\nplot_file\n\n\n\n4->5\n\n\nmacros_tex\n\n\n\n8\n\nresult\n\n\n\n5->8\n\n\n\n\n\n6\n\n2.0\n\n\n\n6->0\n\n\ndomain_size\n\n\n\n6->4\n\n\ndomain_size\n\n\n\n7\n\n/home/jovyan/example_workflows/nfdi/source\n\n\n\n7->0\n\n\nsource_directory\n\n\n\n7->2\n\n\nsource_directory\n\n\n\n7->3\n\n\nsource_directory\n\n\n\n7->4\n\n\nsource_directory\n\n\n\n7->5\n\n\nsource_directory\n\n\n" + }, + "metadata": {} + } + ], + "execution_count": 2 + }, + { + "cell_type": "markdown", + "source": "## Aiida\n\nLoading the JSON into `aiida-workgraph` requires connecting to an AiiDA profile first via `load_profile()`; the workflow is then reconstructed as a `WorkGraph` and executed with `.run()`, which re-runs `generate_mesh`, `convert_to_xdmf`, `poisson`, `plot_over_line`, `substitute_macros` and `compile_paper` in order.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.aiida import load_workflow_json\n\nfrom aiida import load_profile\nload_profile()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 3, + "output_type": "execute_result", + "data": { + "text/plain": "Profile" + }, + "metadata": {} + } + ], + "execution_count": 3 + }, + { + "cell_type": "code", + "source": "workgraph = load_workflow_json(file_name='workflow.json')", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 4 + }, + { + "cell_type": "code", + "source": "# TODO: Create inputs rather than tasks out of data nodes\nworkgraph", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 5, + "output_type": "execute_result", + "data": { + "text/plain": "NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'WorkGra…", + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 1, + "model_id": "b9f711f3af4b4f9c9f6260d595667b1d" + } + }, + "metadata": {} + } + ], + "execution_count": 5 + }, + { + "cell_type": "code", + "source": "\nworkgraph.run()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "05/24/2025 05:45:59 AM <5606> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: generate_mesh1\n05/24/2025 05:46:01 AM <5606> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: generate_mesh1, type: PyFunction, finished.\n05/24/2025 05:46:01 AM <5606> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: convert_to_xdmf2\n05/24/2025 05:46:03 AM <5606> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: convert_to_xdmf2, type: PyFunction, finished.\n05/24/2025 05:46:03 AM <5606> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: poisson3\n05/24/2025 05:46:06 AM <5606> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: poisson3, type: PyFunction, finished.\n05/24/2025 05:46:06 AM <5606> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: plot_over_line4\n05/24/2025 05:46:08 AM <5606> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: plot_over_line4, type: PyFunction, finished.\n05/24/2025 05:46:08 AM <5606> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: substitute_macros5\n05/24/2025 05:46:09 AM <5606> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: substitute_macros5, type: PyFunction, finished.\n05/24/2025 05:46:09 AM <5606> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: compile_paper6\n05/24/2025 05:46:12 AM <5606> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: compile_paper6, type: PyFunction, finished.\n05/24/2025 05:46:12 AM <5606> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n05/24/2025 05:46:12 AM <5606> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|finalize]: Finalize workgraph.\n" + } + ], + "execution_count": 6 + }, + { + "cell_type": "markdown", + "source": "## executorlib\n\n`python_workflow_definition.executorlib.load_workflow_json` submits each function node to the given `Executor` and returns the `Future` of the final node (the compiled `paper.pdf` path); calling `.result()` blocks until the whole chain of external tools has completed.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from executorlib import SingleNodeExecutor", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 7 + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.executorlib import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 8 + }, + { + "cell_type": "code", + "source": "with SingleNodeExecutor(max_workers=1) as exe:\n result = load_workflow_json(file_name=\"workflow.json\", exe=exe).result()", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 9 + }, + { + "cell_type": "code", + "source": "result", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 10, + "output_type": "execute_result", + "data": { + "text/plain": "'/home/jovyan/example_workflows/nfdi/postprocessing/paper.pdf'" + }, + "metadata": {} + } + ], + "execution_count": 10 + }, + { + "cell_type": "markdown", + "source": "## Jobflow\n\nThe JSON is reconstructed as a jobflow `Flow` and executed locally with `run_locally`.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from jobflow.managers.local import run_locally", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 11 + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.jobflow import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 12 + }, + { + "cell_type": "code", + "source": "flow = load_workflow_json(file_name=\"workflow.json\")", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 13 + }, + { + "cell_type": "code", + "source": "result = run_locally(flow)\nresult", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "2025-05-24 05:46:27,374 INFO Started executing jobs locally\n2025-05-24 05:46:27,453 INFO Starting job - generate_mesh (e65df967-702e-4def-9172-6be0b3b95604)\n2025-05-24 05:46:28,600 INFO Finished job - generate_mesh (e65df967-702e-4def-9172-6be0b3b95604)\n2025-05-24 05:46:28,601 INFO Starting job - convert_to_xdmf (173b17f6-c6d6-4002-81f3-fdc267be7837)\n2025-05-24 05:46:29,943 INFO Finished job - convert_to_xdmf (173b17f6-c6d6-4002-81f3-fdc267be7837)\n2025-05-24 05:46:29,944 INFO Starting job - poisson (91e67802-de2e-462d-a076-536c2e874b0b)\n2025-05-24 05:46:32,711 INFO Finished job - poisson (91e67802-de2e-462d-a076-536c2e874b0b)\n2025-05-24 05:46:32,712 INFO Starting job - plot_over_line (5094148b-2ae8-4f88-bbf3-73b68fe02fb1)\n2025-05-24 05:46:34,138 INFO Finished job - plot_over_line (5094148b-2ae8-4f88-bbf3-73b68fe02fb1)\n2025-05-24 05:46:34,139 INFO Starting job - substitute_macros (8badd91e-4495-491e-b978-0b1abac4c680)\n2025-05-24 05:46:34,939 INFO Finished job - substitute_macros (8badd91e-4495-491e-b978-0b1abac4c680)\n2025-05-24 05:46:34,940 INFO Starting job - compile_paper (ae640287-0fda-4682-8bd9-da3251f2cd30)\n2025-05-24 05:46:37,022 INFO Finished job - compile_paper (ae640287-0fda-4682-8bd9-da3251f2cd30)\n2025-05-24 05:46:37,024 INFO Finished executing jobs locally\n" + }, + { + "execution_count": 14, + "output_type": "execute_result", + "data": { + "text/plain": "{'e65df967-702e-4def-9172-6be0b3b95604': {1: Response(output='/home/jovyan/example_workflows/nfdi/preprocessing/square.msh', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n '173b17f6-c6d6-4002-81f3-fdc267be7837': {1: Response(output={'xdmf_file': '/home/jovyan/example_workflows/nfdi/preprocessing/square.xdmf', 'h5_file': '/home/jovyan/example_workflows/nfdi/preprocessing/square.h5'}, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n '91e67802-de2e-462d-a076-536c2e874b0b': {1: Response(output={'numdofs': 357, 'pvd_file': '/home/jovyan/example_workflows/nfdi/processing/poisson.pvd', 'vtu_file': '/home/jovyan/example_workflows/nfdi/processing/poisson000000.vtu'}, detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n '5094148b-2ae8-4f88-bbf3-73b68fe02fb1': {1: Response(output='/home/jovyan/example_workflows/nfdi/postprocessing/plotoverline.csv', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n '8badd91e-4495-491e-b978-0b1abac4c680': {1: Response(output='/home/jovyan/example_workflows/nfdi/postprocessing/macros.tex', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))},\n 'ae640287-0fda-4682-8bd9-da3251f2cd30': {1: Response(output='/home/jovyan/example_workflows/nfdi/postprocessing/paper.pdf', detour=None, addition=None, replace=None, stored_data=None, stop_children=False, stop_jobflow=False, job_dir=PosixPath('/home/jovyan/example_workflows/nfdi'))}}" + }, + "metadata": {} + } + ], + "execution_count": 14 + }, + { + "cell_type": "markdown", + "source": "## pyiron\n\nLoading the JSON into `pyiron_base` produces a list of delayed jobs; `.draw()` visualizes the dependency graph and `.pull()` triggers execution of the whole chain, again writing intermediate files to `preprocessing/`, `processing/` and `postprocessing/`.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.pyiron_base import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 15 + }, + { + "cell_type": "code", + "source": "delayed_object_lst = load_workflow_json(file_name=\"workflow.json\")\ndelayed_object_lst[-1].draw()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "", + "image/svg+xml": "\n\n\n\n\ncreate_function_job_724cfd00ffeb70f8b463a938195e0447\n\ncreate_function_job=<pyiron_base.project.delayed.DelayedObject object at 0x7cace97128d0>\n\n\n\nmacros_tex_b52804e5fa845b3657fa99b738e02cf7\n\nmacros_tex=<pyiron_base.project.delayed.DelayedObject object at 0x7cace9712660>\n\n\n\nmacros_tex_b52804e5fa845b3657fa99b738e02cf7->create_function_job_724cfd00ffeb70f8b463a938195e0447\n\n\n\n\n\npvbatch_output_file_554a54a50a86b23416c0daf6ab0938df\n\npvbatch_output_file=<pyiron_base.project.delayed.DelayedObject object at 0x7cace9712330>\n\n\n\npvbatch_output_file_554a54a50a86b23416c0daf6ab0938df->macros_tex_b52804e5fa845b3657fa99b738e02cf7\n\n\n\n\n\npoisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9\n\npoisson_output_pvd_file=<pyiron_base.project.delayed.DelayedObject object at 0x7cace9711fd0>\n\n\n\npoisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9->pvbatch_output_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\nplot_file_554a54a50a86b23416c0daf6ab0938df\n\nplot_file=<pyiron_base.project.delayed.DelayedObject object at 0x7cace9712330>\n\n\n\npoisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9->plot_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\nplot_file_554a54a50a86b23416c0daf6ab0938df->create_function_job_724cfd00ffeb70f8b463a938195e0447\n\n\n\n\n\nmeshio_output_xdmf_52103bbf2f92608bdb3c6bedb045e0e1\n\nmeshio_output_xdmf=<pyiron_base.project.delayed.DelayedObject object at 0x7cace9711d60>\n\n\n\nmeshio_output_xdmf_52103bbf2f92608bdb3c6bedb045e0e1->poisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9\n\n\n\n\n\npoisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810\n\npoisson_output_vtu_file=<pyiron_base.project.delayed.DelayedObject object at 0x7cace9711fa0>\n\n\n\nmeshio_output_xdmf_52103bbf2f92608bdb3c6bedb045e0e1->poisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810\n\n\n\n\n\nndofs_e826761b60042b070e0c0a24b472ee26\n\nndofs=<pyiron_base.project.delayed.DelayedObject object at 0x7cace97123c0>\n\n\n\nmeshio_output_xdmf_52103bbf2f92608bdb3c6bedb045e0e1->ndofs_e826761b60042b070e0c0a24b472ee26\n\n\n\n\n\npoisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810->pvbatch_output_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\npoisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810->plot_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\nndofs_e826761b60042b070e0c0a24b472ee26->macros_tex_b52804e5fa845b3657fa99b738e02cf7\n\n\n\n\n\ngmsh_output_file_553a0d07e32ca83a3640e955a7b868a4\n\ngmsh_output_file=<pyiron_base.project.delayed.DelayedObject object at 0x7cace97119a0>\n\n\n\ngmsh_output_file_553a0d07e32ca83a3640e955a7b868a4->meshio_output_xdmf_52103bbf2f92608bdb3c6bedb045e0e1\n\n\n\n\n\nmeshio_output_h5_0e11ecf3d5834e399bb91f99309bf3fe\n\nmeshio_output_h5=<pyiron_base.project.delayed.DelayedObject object at 0x7cace9711d30>\n\n\n\ngmsh_output_file_553a0d07e32ca83a3640e955a7b868a4->meshio_output_h5_0e11ecf3d5834e399bb91f99309bf3fe\n\n\n\n\n\nmeshio_output_h5_0e11ecf3d5834e399bb91f99309bf3fe->poisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9\n\n\n\n\n\nmeshio_output_h5_0e11ecf3d5834e399bb91f99309bf3fe->poisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810\n\n\n\n\n\nmeshio_output_h5_0e11ecf3d5834e399bb91f99309bf3fe->ndofs_e826761b60042b070e0c0a24b472ee26\n\n\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20\n\ndomain_size=2.0\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20->macros_tex_b52804e5fa845b3657fa99b738e02cf7\n\n\n\n\n\ndomain_size_f12a7f1986b9dd058dfc666dbe230b20->gmsh_output_file_553a0d07e32ca83a3640e955a7b868a4\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696\n\nsource_directory=/home/jovyan/example_workflows/nfdi/source\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->create_function_job_724cfd00ffeb70f8b463a938195e0447\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->macros_tex_b52804e5fa845b3657fa99b738e02cf7\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->pvbatch_output_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->poisson_output_pvd_file_50ce5e5ed091c2b7a77b69e1c1750ad9\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->plot_file_554a54a50a86b23416c0daf6ab0938df\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->poisson_output_vtu_file_fdcc35c5e09c1b2a481c5350749d9810\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->ndofs_e826761b60042b070e0c0a24b472ee26\n\n\n\n\n\nsource_directory_053958014e7cd4a4df22cfa51c9fc696->gmsh_output_file_553a0d07e32ca83a3640e955a7b868a4\n\n\n\n\n" + }, + "metadata": {} + } + ], + "execution_count": 16 + }, + { + "cell_type": "code", + "source": "delayed_object_lst[-1].pull()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "The job generate_mesh_47725c16637f799ac042e47468005db3 was saved and received the ID: 1\nThe job convert_to_xdmf_d6a46eb9a4ec352aa996e783ec3c785f was saved and received the ID: 2\nThe job poisson_3c147fc86db87cf0c0f94bda333f8cd8 was saved and received the ID: 3\nThe job plot_over_line_ef50933291910dadcc8311924971e127 was saved and received the ID: 4\nThe job substitute_macros_63766eafd6b1980c7832dd8c9a97c96e was saved and received the ID: 5\nThe job compile_paper_128d1d58374953c00e95b8de62cbb10b was saved and received the ID: 6\n" + }, + { + "execution_count": 17, + "output_type": "execute_result", + "data": { + "text/plain": "'/home/jovyan/example_workflows/nfdi/postprocessing/paper.pdf'" + }, + "metadata": {} + } + ], + "execution_count": 17 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## Load Workflow with pyiron_workflow\n\nFinally, the workflow is loaded into a `pyiron_workflow` `Workflow` object, drawn with `.draw()` and executed with `.run()`." + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "from python_workflow_definition.pyiron_workflow import load_workflow_json" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf = load_workflow_json(file_name=\"workflow.json\")" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.draw(size=(10,10))" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.run()" + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## Python\n\nAs a baseline, `python_workflow_definition.purepython.load_workflow_json` interprets the JSON directly in plain Python, with no workflow engine involved: it evaluates each function node in dependency order — invoking `gmsh`, `meshio`, the Poisson solver, `pvbatch` and `tectonic` via `conda_subprocess` exactly as `workflow.py` defines — and returns the final result." + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.purepython import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 18 + }, + { + "cell_type": "code", + "source": "load_workflow_json(file_name=\"workflow.json\")", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 19, + "output_type": "execute_result", + "data": { + "text/plain": "'/home/jovyan/example_workflows/nfdi/postprocessing/paper.pdf'" + }, + "metadata": {} + } + ], + "execution_count": 19 + } + ] +} \ No newline at end of file diff --git a/_sources/example_workflows/quantum_espresso/aiida.ipynb b/_sources/example_workflows/quantum_espresso/aiida.ipynb new file mode 100644 index 00000000..8b297f21 --- /dev/null +++ b/_sources/example_workflows/quantum_espresso/aiida.ipynb @@ -0,0 +1,5800 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": "# aiida-workgraph\n\nThis notebook builds the Quantum Espresso energy-volume-curve workflow directly with [`aiida-workgraph`](https://github.com/aiidateam/aiida-workgraph) and exports it as a PWD `workflow.json`. The second half of the notebook loads that same JSON file with `jobflow`, `pyiron_base` and `pyiron_workflow` to show that a graph built with one engine can be executed by another." + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "## Define workflow with aiida\n\n`aiida-workgraph` represents a workflow as a `WorkGraph` built from `task`s, each wrapping a Python function; connecting a task's output to another task's input builds up the graph. `load_profile()` connects to the local AiiDA profile/database, which is required before any AiiDA node can be created, since every task and its result are stored there for provenance." + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from python_workflow_definition.aiida import write_workflow_json\n", + "from python_workflow_definition.shared import get_dict, get_list\n", + "\n", + "from aiida import load_profile, orm\n", + "\n", + "load_profile()\n", + "\n", + "workflow_json_filename = \"aiida_qe.json\"" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from aiida_workgraph import task, WorkGraph" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from workflow import (\n", + " generate_structures,\n", + " get_bulk_structure,\n", + " calculate_qe as _calculate_qe,\n", + " plot_energy_volume_curve,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "source": "`calculate_qe` (defined in [`workflow.py`](workflow.py)) returns a dict with `energy`, `volume` and `structure` keys. Wrapping it with `task(outputs=[...])` tells `aiida-workgraph` to expose these as separate output sockets (`.outputs.energy`, `.outputs.volume`, `.outputs.structure`) instead of a single opaque result, so downstream tasks can connect to individual keys.", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "calculate_qe = task(outputs=[\"energy\", \"volume\", \"structure\"])(_calculate_qe)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wg = WorkGraph(\"wg-qe\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "### Prepare the inputs\n\nScalar inputs are wrapped as AiiDA data types (`orm.Str`, `orm.Float`, `orm.Bool`, `orm.Dict`, `orm.List`) so AiiDA can track their provenance. `strain_lst` are the five volumetric strains (0.9-1.1) that will later be applied to the relaxed structure to sample the energy-volume curve." + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "element = orm.Str(\"Al\")\n", + "a = orm.Float(4.04)\n", + "cubic = orm.Bool(True)\n", + "relax_workdir = orm.Str(\"mini\")\n", + "pseudopotentials = orm.Dict({\"Al\": \"Al.pbe-n-kjpaw_psl.1.0.0.UPF\"})\n", + "kpts = orm.List([3, 3, 3])\n", + "calc_type_relax = orm.Str(\"vc-relax\")\n", + "calc_type_scf = orm.Str(\"scf\")\n", + "smearing = orm.Float(0.02)\n", + "strain_lst = orm.List([0.9, 0.95, 1.0, 1.05, 1.1])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "### Build the task graph\n\nThe pipeline is: `get_bulk_structure` builds the initial Al structure, `calculate_qe` relaxes it (`vc-relax`), `generate_structures` applies the strains, and one `calculate_qe` (`scf`) task per strained structure computes its energy and volume. `get_dict` bundles the structure, calculation type, k-points, pseudopotentials and smearing into the `input_dict` argument `calculate_qe` expects." + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "get_bulk_structure_task = wg.add_task(\n", + " get_bulk_structure,\n", + " element=element,\n", + " a=a,\n", + " cubic=cubic,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "relax_prepare_input_dict_task = wg.add_task(\n", + " get_dict,\n", + " structure=get_bulk_structure_task.outputs.result,\n", + " calculation=calc_type_relax,\n", + " kpts=kpts,\n", + " pseudopotentials=pseudopotentials,\n", + " smearing=smearing,\n", + ")\n", + "\n", + "relax_task = wg.add_task(\n", + " calculate_qe,\n", + " input_dict=relax_prepare_input_dict_task.outputs.result,\n", + " working_directory=relax_workdir,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "source": "`generate_structures` applies each of the five strains to the relaxed structure, producing five strained structures (`s_0` ... `s_4`). This is the fan-out point of the workflow: the loop below adds one independent `scf` `calculate_qe` task per strained structure, and their `energy`/`volume` outputs are collected into two lists (via `get_list` tasks) for the final plot.", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "generate_structures_task = wg.add_task(\n", + " generate_structures,\n", + " structure=relax_task.outputs.structure,\n", + " strain_lst=strain_lst,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "get_volumes_task = wg.add_task(get_list)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "get_energies_task = wg.add_task(get_list)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "strain_dir_tasks, scf_qe_tasks, scf_get_dict_tasks = [], [], []\n", + "\n", + "for i, strain in enumerate(strain_lst):\n", + "\n", + " structure_key = f\"s_{i}\"\n", + " strain_dir = orm.Str(f\"strain_{i}\")\n", + " generate_structures_task.add_output(\"workgraph.any\", structure_key)\n", + "\n", + " scf_prepare_input_dict_task = wg.add_task(\n", + " get_dict,\n", + " structure=generate_structures_task.outputs[structure_key],\n", + " calculation=calc_type_scf,\n", + " kpts=kpts,\n", + " pseudopotentials=pseudopotentials,\n", + " smearing=smearing,\n", + " )\n", + "\n", + " scf_qe_task = wg.add_task(\n", + " calculate_qe,\n", + " input_dict=scf_prepare_input_dict_task.outputs.result,\n", + " working_directory=strain_dir,\n", + " )\n", + "\n", + " # collect energy and volume\n", + " get_energies_task.set_inputs({f\"{i}\": scf_qe_task.outputs.energy})\n", + " get_volumes_task.set_inputs({f\"{i}\": scf_qe_task.outputs.volume})" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "plot_energy_volume_curve_task = wg.add_task(\n", + " plot_energy_volume_curve,\n", + " volume_lst=get_volumes_task.outputs.result,\n", + " energy_lst=get_energies_task.outputs.result,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "source": "Displaying `wg` renders an interactive `NodeGraphWidget` of the task graph, which is useful to check the wiring before running it. `write_workflow_json` then serializes the `WorkGraph` into the PWD `workflow.json` format (nodes = functions/inputs/outputs, edges = data connections) so it can be loaded by another engine.", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "8cde6dcdf8224a4a9c002550a0165c73", + "version_major": 2, + "version_minor": 1 + }, + "text/plain": [ + "NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'wg-qe',…" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wg" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "_ = write_workflow_json(wg=wg, file_name=workflow_json_filename)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"version\": \"0.1.0\",\n", + " \"nodes\": [\n", + " {\n", + " \"id\": 0,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.get_bulk_structure\"\n", + " },\n", + " {\n", + " \"id\": 1,\n", + " \"type\": \"function\",\n", + " \"value\": \"python_workflow_definition.shared.get_dict\"\n", + " },\n", + " {\n", + " \"id\": 2,\n", + " \"type\": \"function\",\n", + " 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null\n", + " },\n", + " {\n", + " \"target\": 1,\n", + " \"targetPort\": \"calculation\",\n", + " \"source\": 20,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 1,\n", + " \"targetPort\": \"kpts\",\n", + " \"source\": 21,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 1,\n", + " \"targetPort\": \"pseudopotentials\",\n", + " \"source\": 22,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 1,\n", + " \"targetPort\": \"smearing\",\n", + " \"source\": 23,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 2,\n", + " \"targetPort\": \"working_directory\",\n", + " \"source\": 24,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 3,\n", + " \"targetPort\": \"strain_lst\",\n", + " \"source\": 25,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 6,\n", + " \"targetPort\": \"calculation\",\n", + " \"source\": 26,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 6,\n", + " \"targetPort\": \"kpts\",\n", + " \"source\": 21,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 6,\n", + " \"targetPort\": \"pseudopotentials\",\n", + " \"source\": 22,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 6,\n", + " \"targetPort\": \"smearing\",\n", + " \"source\": 23,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 7,\n", + " \"targetPort\": \"working_directory\",\n", + " \"source\": 27,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 8,\n", + " \"targetPort\": \"calculation\",\n", + " \"source\": 26,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 8,\n", + " \"targetPort\": \"kpts\",\n", + " \"source\": 21,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 8,\n", + " \"targetPort\": \"pseudopotentials\",\n", + " \"source\": 22,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 8,\n", + " \"targetPort\": \"smearing\",\n", + " \"source\": 23,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 9,\n", + " \"targetPort\": \"working_directory\",\n", + " \"source\": 28,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 10,\n", + " \"targetPort\": \"calculation\",\n", + " \"source\": 26,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 10,\n", + " \"targetPort\": \"kpts\",\n", + " \"source\": 21,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 10,\n", + " \"targetPort\": \"pseudopotentials\",\n", + " \"source\": 22,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 10,\n", + " \"targetPort\": \"smearing\",\n", + " \"source\": 23,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 11,\n", + " \"targetPort\": \"working_directory\",\n", + " \"source\": 29,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 12,\n", + " \"targetPort\": \"calculation\",\n", + " \"source\": 26,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 12,\n", + " \"targetPort\": \"kpts\",\n", + " \"source\": 21,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 12,\n", + " \"targetPort\": \"pseudopotentials\",\n", + " \"source\": 22,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 12,\n", + " \"targetPort\": \"smearing\",\n", + " \"source\": 23,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 13,\n", + " \"targetPort\": \"working_directory\",\n", + " \"source\": 30,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 14,\n", + " \"targetPort\": \"calculation\",\n", + " \"source\": 26,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 14,\n", + " \"targetPort\": \"kpts\",\n", + " \"source\": 21,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 14,\n", + " \"targetPort\": \"pseudopotentials\",\n", + " \"source\": 22,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 14,\n", + " \"targetPort\": \"smearing\",\n", + " \"source\": 23,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 15,\n", + " \"targetPort\": \"working_directory\",\n", + " \"source\": 31,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 32,\n", + " \"targetPort\": null,\n", + " \"source\": 16,\n", + " \"sourcePort\": null\n", + " }\n", + " ]\n", + "}" + ] + } + ], + "source": [ + "!cat {workflow_json_filename}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "## Load Workflow with jobflow\n\n`load_workflow_json` reconstructs the same graph as a `jobflow` `Flow` of `Job`s. To show that the loaded graph behaves like a native `jobflow` object, the lattice constant `a` of the first job is overridden (4.04 -> 4.05) before the flow is executed locally with `run_locally`." + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from python_workflow_definition.jobflow import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from jobflow.managers.local import run_locally" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "flow = load_workflow_json(file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "flow[0].function_kwargs[\"a\"] = 4.05" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 04:52:50,581 INFO Started executing jobs locally\n", + "2025-05-26 04:52:50,675 INFO Starting job - get_bulk_structure (3ac8790d-eb22-4532-be62-de8fbef1b1d6)\n", + "2025-05-26 04:52:50,678 INFO Finished job - get_bulk_structure (3ac8790d-eb22-4532-be62-de8fbef1b1d6)\n", + "2025-05-26 04:52:50,678 INFO Starting job - get_dict (c4961244-74bf-450f-8d51-1185a6fa636e)\n", + "2025-05-26 04:52:50,679 INFO Finished job - get_dict (c4961244-74bf-450f-8d51-1185a6fa636e)\n", + "2025-05-26 04:52:50,680 INFO Starting job - calculate_qe (1c454eb0-0ad4-4b71-9d98-9d767f2eeb26)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---218119f8:02130] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 04:53:41,492 INFO Finished job - calculate_qe (1c454eb0-0ad4-4b71-9d98-9d767f2eeb26)\n", + "2025-05-26 04:53:41,493 INFO Starting job - generate_structures (4b55ebda-5c1f-4778-96b0-04b01637fd55)\n", + "2025-05-26 04:53:41,497 INFO Finished job - generate_structures (4b55ebda-5c1f-4778-96b0-04b01637fd55)\n", + "2025-05-26 04:53:41,498 INFO Starting job - get_dict (b565cdc4-4ce6-4a26-80aa-df13d5c66c6a)\n", + "2025-05-26 04:53:41,501 INFO Finished job - get_dict (b565cdc4-4ce6-4a26-80aa-df13d5c66c6a)\n", + "2025-05-26 04:53:41,502 INFO Starting job - get_dict (b77d779a-5ef4-444f-be7e-386f16f7ec4a)\n", + "2025-05-26 04:53:41,505 INFO Finished job - get_dict (b77d779a-5ef4-444f-be7e-386f16f7ec4a)\n", + "2025-05-26 04:53:41,506 INFO Starting job - get_dict (bd7706a1-7c30-4c5c-9319-a082dc3950ad)\n", + "2025-05-26 04:53:41,509 INFO Finished job - get_dict (bd7706a1-7c30-4c5c-9319-a082dc3950ad)\n", + "2025-05-26 04:53:41,510 INFO Starting job - get_dict (05f7faac-40ed-495e-b0dc-26ba16f805c8)\n", + "2025-05-26 04:53:41,513 INFO Finished job - get_dict (05f7faac-40ed-495e-b0dc-26ba16f805c8)\n", + "2025-05-26 04:53:41,516 INFO Starting job - get_dict (378217fd-e39a-45a3-ba59-435de2062c71)\n", + "2025-05-26 04:53:41,531 INFO Finished job - get_dict (378217fd-e39a-45a3-ba59-435de2062c71)\n", + "2025-05-26 04:53:41,532 INFO Starting job - calculate_qe (45551771-435e-4dc6-913f-07091732e0a3)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---218119f8:02145] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 04:53:51,562 INFO Finished job - calculate_qe (45551771-435e-4dc6-913f-07091732e0a3)\n", + "2025-05-26 04:53:51,563 INFO Starting job - calculate_qe (548d3d66-855c-45f6-803d-894aaf90fd6b)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02155] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 04:54:02,977 INFO Finished job - calculate_qe (548d3d66-855c-45f6-803d-894aaf90fd6b)\n", + "2025-05-26 04:54:02,978 INFO Starting job - calculate_qe (d309162b-9af7-4270-bfd5-fc0c893ba9f0)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02165] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 04:54:14,530 INFO Finished job - calculate_qe (d309162b-9af7-4270-bfd5-fc0c893ba9f0)\n", + "2025-05-26 04:54:14,531 INFO Starting job - calculate_qe (67abe614-2777-4184-92e6-f5443def6503)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02175] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 04:54:27,806 INFO Finished job - calculate_qe (67abe614-2777-4184-92e6-f5443def6503)\n", + "2025-05-26 04:54:27,807 INFO Starting job - calculate_qe (35826c86-14ca-4341-90f0-894b9be0d16d)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02185] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 04:54:41,828 INFO Finished job - calculate_qe (35826c86-14ca-4341-90f0-894b9be0d16d)\n", + "2025-05-26 04:54:41,829 INFO Starting job - get_list (87cd2e29-15fc-4e35-845f-47211f6a1090)\n", + "2025-05-26 04:54:41,835 INFO Finished job - get_list (87cd2e29-15fc-4e35-845f-47211f6a1090)\n", + "2025-05-26 04:54:41,836 INFO Starting job - get_list (3b0846af-d37d-4199-897b-16f124a5516a)\n", + "2025-05-26 04:54:41,839 INFO Finished job - get_list (3b0846af-d37d-4199-897b-16f124a5516a)\n", + "2025-05-26 04:54:41,840 INFO Starting job - plot_energy_volume_curve (88a18290-ffeb-40b6-b0e8-fca1ee6fade4)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 04:54:41,900 INFO Finished job - plot_energy_volume_curve (88a18290-ffeb-40b6-b0e8-fca1ee6fade4)\n", + "2025-05-26 04:54:41,901 INFO Finished executing jobs locally\n" + ] + }, + { + "data": { + "text/plain": [ + "{'3ac8790d-eb22-4532-be62-de8fbef1b1d6': {1: Response(output='{\"immutable_id\": null, \"last_modified\": null, \"elements\": [\"Al\"], \"nelements\": 1, \"elements_ratios\": [1.0], \"chemical_formula_descriptive\": \"Al4\", \"chemical_formula_reduced\": \"Al\", \"chemical_formula_hill\": null, \"chemical_formula_anonymous\": \"A\", 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job_dir=PosixPath('/home/jovyan/example_workflows/quantum_espresso'))}}" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "result = run_locally(flow)\n", + "result" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "## Load Workflow with pyiron_base\n\n`pyiron_base`'s `load_workflow_json` turns each node into a delayed pyiron job. `.draw()` renders the dependency graph, and `.pull()` triggers execution of the whole chain, saving every intermediate job (relax + 5 strained SCF calculations) to the pyiron project." + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from python_workflow_definition.pyiron_base import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "create_function_job_2dd37919a07881ec35b48b79261ff390\n", + "\n", + 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signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job generate_structures_4ebba2fa25817e4d72c841e3b2e8b6f0 was saved and received the ID: 4\n", + "The job get_dict_869b937d7880c2f0aa7d1ff12e5658fe was saved and received the ID: 5\n", + "The job calculate_qe_1e1d1a32203e271ae2255924d3e9b14f was saved and received the ID: 6\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---218119f8:02247] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job get_dict_afe14b210783e4e61e6d468d63799bad was saved and received the ID: 7\n", + "The job calculate_qe_0c07010ebc24b938a57832c41fcd74af was saved and received the ID: 8\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---218119f8:02261] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job get_dict_c42b900d2b5d0c900d1158c58ab1a259 was saved and received the ID: 9\n", + "The job calculate_qe_808bdd6630f3c0da564a58075a232427 was saved and received the ID: 10\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---218119f8:02271] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job get_dict_db89bfa1573064c1e658fee65739f0d7 was saved and received the ID: 11\n", + "The job calculate_qe_91a59b931c007125c72d9a407632de03 was saved and received the ID: 12\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---218119f8:02281] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job get_dict_8e6eb778e855d484b1763a645b753abf was saved and received the ID: 13\n", + "The job calculate_qe_80b6905597629098e2dca3067098d3e9 was saved and received the ID: 14\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---218119f8:02295] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job get_list_befc04228af2690aa933355368b2374b was saved and received the ID: 15\n", + "The job get_list_de1f227902310f2b34d080eff15204c9 was saved and received the ID: 16\n", + "The job plot_energy_volume_curve_a817e1974411e9ad4e1c06ce96b8a65d was saved and received the ID: 17\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "delayed_object_lst[-1].pull()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "## Load Workflow with pyiron_workflow\n\nFinally, the same JSON is loaded into a `pyiron_workflow` `Workflow` object. Nodes become graph nodes reachable via attribute access (e.g. `wf.get_bulk_structure`), and `.run()` executes them in dependency order." + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from python_workflow_definition.pyiron_workflow import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wf = load_workflow_json(file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wf.get_bulk_structure.inputs.a.value = 4.05" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "clusteraiida_qe\n", + "\n", + "aiida_qe: Workflow\n", + "\n", + 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"clusteraiida_qeget_dict_0OutputsWithInjection\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "OutputsWithInjection\n", + "\n", + "\n", + "clusteraiida_qecalculate_qe_0\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "calculate_qe_0: calculate_qe\n", + "\n", + "\n", + "clusteraiida_qecalculate_qe_0Inputs\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "Inputs\n", + "\n", + "\n", + "clusteraiida_qecalculate_qe_0OutputsWithInjection\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "OutputsWithInjection\n", + "\n", + "\n", + "clusteraiida_qegenerate_structures\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "generate_structures: generate_structures\n", + "\n", + "\n", + "clusteraiida_qegenerate_structuresInputs\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "Inputs\n", + "\n", + "\n", + "clusteraiida_qegenerate_structuresOutputsWithInjection\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "OutputsWithInjection\n", + "\n", + "\n", + "clusteraiida_qeget_list_0\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "get_list_0: get_list\n", + "\n", + "\n", + "clusteraiida_qeget_list_0Inputs\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "Inputs\n", + "\n", + "\n", + "clusteraiida_qeget_list_0OutputsWithInjection\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "OutputsWithInjection\n", + "\n", + "\n", + "clusteraiida_qeget_list_1\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "get_list_1: get_list\n", + "\n", + "\n", + "clusteraiida_qeget_list_1Inputs\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "Inputs\n", + "\n", + "\n", + "clusteraiida_qeget_list_1OutputsWithInjection\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "OutputsWithInjection\n", + "\n", + "\n", + "clusteraiida_qeget_dict_1\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "get_dict_1: get_dict\n", + "\n", + "\n", + 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mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02404] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02421] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02443] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02459] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02470] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "data": { + "text/plain": [ + "{'plot_energy_volume_curve__plot_energy_volume_curve': None}" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "wf.run()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.8" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} \ No newline at end of file diff --git a/_sources/example_workflows/quantum_espresso/cwl.ipynb b/_sources/example_workflows/quantum_espresso/cwl.ipynb new file mode 100644 index 00000000..4c477564 --- /dev/null +++ b/_sources/example_workflows/quantum_espresso/cwl.ipynb @@ -0,0 +1,147 @@ +{ + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.12.8", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + } + }, + "nbformat_minor": 5, + "nbformat": 4, + "cells": [ + { + "cell_type": "markdown", + "id": "f9fecca7", + "source": "# CWL\n\nThis notebook executes the Quantum Espresso energy-volume-curve `workflow.json` (produced by one of the other notebooks in this directory, e.g. `aiida.ipynb`) with the [Common Workflow Language](https://www.commonwl.org) via [`cwltool`](https://github.com/common-workflow-language/cwltool). Unlike the other engines, PWD does not build a CWL graph directly in Python - instead it translates an existing `workflow.json` into native CWL files, which `cwltool` then executes as a separate command line process.", + "metadata": {} + }, + { + "id": "4eca79ef-1053-4f69-89ad-2bee8411068e", + "cell_type": "code", + "source": "import os", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 1 + }, + { + "id": "377fef56-484d-491c-b19e-1be6931e44eb", + "cell_type": "code", + "source": "import pickle", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 2 + }, + { + "cell_type": "markdown", + "id": "8da8470b", + "source": "## Translate workflow.json to CWL\n\n`write_workflow` reads the existing `workflow.json` and generates: one `.cwl` `CommandLineTool` per PWD function node (each one invokes `python -m python_workflow_definition.cwl --function=...` to call the matching function in `workflow.py`), a top-level `workflow.cwl` that chains these steps together following the `workflow.json` edges, and a `workflow.yml` job file listing one input file per PWD input node. Since CWL only passes files between steps, every input and every function output is exchanged as a pickle file.", + "metadata": {} + }, + { + "id": "92e3921b-2bb8-4333-8cfe-4bd27f785d24", + "cell_type": "code", + "source": "from python_workflow_definition.cwl import write_workflow", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 3 + }, + { + "id": "5303c059-8ae4-4557-858e-b4bd64eac711", + "cell_type": "code", + "source": "write_workflow(file_name=\"workflow.json\")", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 4 + }, + { + "cell_type": "markdown", + "id": "21fc2973", + "source": "## Run the workflow with cwltool\n\nASE's Quantum Espresso writer resolves the pseudopotential directory from the `ESPRESSO_PSEUDO` environment variable when no explicit path is given. Because `cwltool` runs every step in its own isolated temporary directory, the environment variable has to be forwarded explicitly with `--preserve-environment=ESPRESSO_PSEUDO`, so that `pw.x` can find the pseudopotential file shipped in [`espresso/pseudo`](espresso/pseudo) from any step.", + "metadata": {} + }, + { + "id": "0192ca74-3971-464b-9435-c156e0b6e623", + "cell_type": "code", + "source": "os.environ[\"ESPRESSO_PSEUDO\"] = os.path.abspath(os.path.join(\"../../espresso/pseudo\"))", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 5 + }, + { + "id": "df302bd2-e9b6-4595-979c-67c46414d986", + "cell_type": "code", + "source": "! cwltool --preserve-environment=ESPRESSO_PSEUDO workflow.cwl workflow.yml", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "/srv/conda/envs/notebook/bin/cwltool:11: DeprecationWarning: Nesting argument groups is deprecated.\n sys.exit(run())\n\u001b[1;30mINFO\u001b[0m /srv/conda/envs/notebook/bin/cwltool 3.1.20250110105449\n\u001b[1;30mINFO\u001b[0m Resolved 'workflow.cwl' to 'file:///home/jovyan/example_workflows/quantum_espresso/workflow.cwl'\n\u001b[1;30mINFO\u001b[0m [workflow ] start\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step get_bulk_structure_0\n\u001b[1;30mINFO\u001b[0m [step get_bulk_structure_0] start\n\u001b[1;30mINFO\u001b[0m [job get_bulk_structure_0] /tmp/9sant4h9$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/va137af6/stga19aac01-d6f9-48d3-ba6b-d8a6e460f525/workflow.py \\\n --function=workflow.get_bulk_structure \\\n --arg_cubic=/tmp/va137af6/stgd2861bb7-939d-449d-9600-71f380ee058d/cubic.pickle \\\n --arg_element=/tmp/va137af6/stg93f5775e-477a-4b2e-87ac-822ff4097346/element.pickle \\\n --arg_a=/tmp/va137af6/stgcfd0bd7b-a186-4b46-80a6-663aeb5d0fa9/a.pickle\n\u001b[1;30mINFO\u001b[0m [job get_bulk_structure_0] Max memory used: 110MiB\n\u001b[1;30mINFO\u001b[0m [job get_bulk_structure_0] completed success\n\u001b[1;30mINFO\u001b[0m [step get_bulk_structure_0] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step get_dict_13\n\u001b[1;30mINFO\u001b[0m [step get_dict_13] start\n\u001b[1;30mINFO\u001b[0m [job get_dict_13] /tmp/_o8rxcyc$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --function=python_workflow_definition.shared.get_dict \\\n --arg_smearing=/tmp/1h2uwpt9/stg17e865b8-f1f4-406f-a9c7-b8deddc5695d/smearing.pickle \\\n --arg_calculation=/tmp/1h2uwpt9/stgf1d25320-f3de-48f7-8087-5cdb5531765c/calculation_0.pickle \\\n --arg_kpts=/tmp/1h2uwpt9/stgc9e37196-83cf-49d9-88e1-b5acb7c53e7f/kpts.pickle \\\n --arg_pseudopotentials=/tmp/1h2uwpt9/stgcfb6bfd1-3ae7-4600-b07d-ca107c1a275c/pseudopotentials.pickle \\\n --arg_structure=/tmp/1h2uwpt9/stg0da627e7-f19e-4948-b23e-4552aa692862/result.pickle\n\u001b[1;30mINFO\u001b[0m [job get_dict_13] completed success\n\u001b[1;30mINFO\u001b[0m [step get_dict_13] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step calculate_qe_1\n\u001b[1;30mINFO\u001b[0m [step calculate_qe_1] start\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_1] /tmp/q56p65x4$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/5hwlsb8q/stga00637b3-d27a-4b67-b4b2-5857ffc8f94a/workflow.py \\\n --function=workflow.calculate_qe \\\n --arg_input_dict=/tmp/5hwlsb8q/stgea0d773c-cef9-49b7-9895-09c22db6f52d/result.pickle \\\n --arg_working_directory=/tmp/5hwlsb8q/stg541840e1-d4a6-4a2c-a220-ab09e72c869d/working_directory_0.pickle\n[jupyter-pythonworkflow-fl--x---d7231032:09273] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_1] Max memory used: 273MiB\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_1] completed success\n\u001b[1;30mINFO\u001b[0m [step calculate_qe_1] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step generate_structures_2\n\u001b[1;30mINFO\u001b[0m [step generate_structures_2] start\n\u001b[1;30mINFO\u001b[0m [job generate_structures_2] /tmp/81vwps2h$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/0d6xih7u/stg8da9bfd1-34a7-4282-8446-97a728d4747b/workflow.py \\\n --function=workflow.generate_structures \\\n --arg_structure=/tmp/0d6xih7u/stg89eb15f9-014d-4c20-8197-87c6c7345ffe/structure.pickle \\\n --arg_strain_lst=/tmp/0d6xih7u/stg80ec088c-9b6a-45bd-8565-e68fd3c76210/strain_lst.pickle\n\u001b[1;30mINFO\u001b[0m [job generate_structures_2] Max memory used: 96MiB\n\u001b[1;30mINFO\u001b[0m [job generate_structures_2] completed success\n\u001b[1;30mINFO\u001b[0m [step generate_structures_2] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step get_dict_25\n\u001b[1;30mINFO\u001b[0m [step get_dict_25] start\n\u001b[1;30mINFO\u001b[0m [job get_dict_25] /tmp/hj3teyvh$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --function=python_workflow_definition.shared.get_dict \\\n --arg_smearing=/tmp/ky497mud/stgf2ab029c-fd78-4490-a4aa-2ee352fa40a2/smearing.pickle \\\n --arg_calculation=/tmp/ky497mud/stg12f82711-28cb-42e6-80c5-59e7fa946ea8/calculation_1.pickle \\\n --arg_kpts=/tmp/ky497mud/stgd35fecc6-83e5-493e-85ad-caf6acd301cb/kpts.pickle \\\n --arg_pseudopotentials=/tmp/ky497mud/stg9b98aba6-11a6-4718-bd3a-23f160518077/pseudopotentials.pickle \\\n --arg_structure=/tmp/ky497mud/stg00376f4a-a991-469a-b494-27c160e6c15d/s_2.pickle\n\u001b[1;30mINFO\u001b[0m [job get_dict_25] completed success\n\u001b[1;30mINFO\u001b[0m [step get_dict_25] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step get_dict_20\n\u001b[1;30mINFO\u001b[0m [step get_dict_20] start\n\u001b[1;30mINFO\u001b[0m [job get_dict_20] /tmp/y9drdoe7$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --function=python_workflow_definition.shared.get_dict \\\n --arg_smearing=/tmp/dsu142t1/stgcba59359-36e1-4bf9-9e6f-e7cf99a23077/smearing.pickle \\\n --arg_calculation=/tmp/dsu142t1/stg56a2646f-2057-4670-bb4e-f55af62c5858/calculation_1.pickle \\\n --arg_kpts=/tmp/dsu142t1/stgc443e9a8-c9b6-4c5e-8321-6a70d347706b/kpts.pickle \\\n --arg_pseudopotentials=/tmp/dsu142t1/stg47b4b44d-c69c-4629-aaed-0e15bf14426e/pseudopotentials.pickle \\\n --arg_structure=/tmp/dsu142t1/stg0e5b3c6e-a315-4eaf-9a66-dbf5669eaada/s_0.pickle\n\u001b[1;30mINFO\u001b[0m [job get_dict_20] completed success\n\u001b[1;30mINFO\u001b[0m [step get_dict_20] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step get_dict_23\n\u001b[1;30mINFO\u001b[0m [step get_dict_23] start\n\u001b[1;30mINFO\u001b[0m [job get_dict_23] /tmp/9v59c4vd$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --function=python_workflow_definition.shared.get_dict \\\n --arg_smearing=/tmp/2mc_byfs/stgace4b178-c0ff-406e-95ac-754318766886/smearing.pickle \\\n --arg_calculation=/tmp/2mc_byfs/stg793df1d8-8f8d-4bb3-9c7c-243a48dc494b/calculation_1.pickle \\\n --arg_kpts=/tmp/2mc_byfs/stga852e76a-885f-4e39-8ab4-ecebf95c656f/kpts.pickle \\\n --arg_pseudopotentials=/tmp/2mc_byfs/stgd06acdff-6e0c-476c-be57-1f21b2d03711/pseudopotentials.pickle \\\n --arg_structure=/tmp/2mc_byfs/stg02210df5-d3e2-42b8-a75e-47e2f2c9f274/s_1.pickle\n\u001b[1;30mINFO\u001b[0m [job get_dict_23] completed success\n\u001b[1;30mINFO\u001b[0m [step get_dict_23] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step get_dict_29\n\u001b[1;30mINFO\u001b[0m [step get_dict_29] start\n\u001b[1;30mINFO\u001b[0m [job get_dict_29] /tmp/q_svsf9g$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --function=python_workflow_definition.shared.get_dict \\\n --arg_smearing=/tmp/8u8e7db4/stgbba611dc-3b23-4653-a293-f71d492a42af/smearing.pickle \\\n --arg_calculation=/tmp/8u8e7db4/stge9a32972-6649-4eb5-abd7-9db61d929d2d/calculation_1.pickle \\\n --arg_kpts=/tmp/8u8e7db4/stg02098ea5-7487-4a66-bb77-99a6336d7b71/kpts.pickle \\\n --arg_pseudopotentials=/tmp/8u8e7db4/stg571b6259-4599-4c39-8cb2-79a70feb78b8/pseudopotentials.pickle \\\n --arg_structure=/tmp/8u8e7db4/stg64c55a4d-8af6-40bf-abfd-3ec8a690b90b/s_4.pickle\n\u001b[1;30mINFO\u001b[0m [job get_dict_29] completed success\n\u001b[1;30mINFO\u001b[0m [step get_dict_29] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step get_dict_27\n\u001b[1;30mINFO\u001b[0m [step get_dict_27] start\n\u001b[1;30mINFO\u001b[0m [job get_dict_27] /tmp/vgcwzb84$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --function=python_workflow_definition.shared.get_dict \\\n --arg_smearing=/tmp/xf32x1ld/stg3cbb6408-2383-49d0-9476-ef3fbee7c165/smearing.pickle \\\n --arg_calculation=/tmp/xf32x1ld/stgeb36ed3b-b442-43ea-b14d-1397875e8839/calculation_1.pickle \\\n --arg_kpts=/tmp/xf32x1ld/stge8854d32-32f3-4a90-8e66-8ce7b1160d8d/kpts.pickle \\\n --arg_pseudopotentials=/tmp/xf32x1ld/stg0dba3c44-e6af-46a9-9f00-c08969392ede/pseudopotentials.pickle \\\n --arg_structure=/tmp/xf32x1ld/stg4223a500-1f85-4651-9130-bd1629008770/s_3.pickle\n\u001b[1;30mINFO\u001b[0m [job get_dict_27] completed success\n\u001b[1;30mINFO\u001b[0m [step get_dict_27] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step calculate_qe_3\n\u001b[1;30mINFO\u001b[0m [step calculate_qe_3] start\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_3] /tmp/v2e_84tz$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/n81xp6_a/stgf98a9803-3329-400e-a03c-02b51d3f3c97/workflow.py \\\n --function=workflow.calculate_qe \\\n --arg_input_dict=/tmp/n81xp6_a/stgd93a737b-2598-4fb8-bdcb-bb1d2048116f/result.pickle \\\n --arg_working_directory=/tmp/n81xp6_a/stg5ad2a52b-2844-45e4-b227-3d835efa01f6/working_directory_1.pickle\n[jupyter-pythonworkflow-fl--x---d7231032:09459] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_3] Max memory used: 240MiB\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_3] completed success\n\u001b[1;30mINFO\u001b[0m [step calculate_qe_3] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step calculate_qe_4\n\u001b[1;30mINFO\u001b[0m [step calculate_qe_4] start\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_4] /tmp/tgwdkhxx$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/l5mihx97/stgf73a20aa-bd97-46af-a923-b8d776da2b98/workflow.py \\\n --function=workflow.calculate_qe \\\n --arg_input_dict=/tmp/l5mihx97/stgb8c3fcbe-9277-46c4-b8a2-a1171a292580/result.pickle \\\n --arg_working_directory=/tmp/l5mihx97/stg3ae0b93a-2e0b-4f1b-b079-985ea6bbaa72/working_directory_2.pickle\n[jupyter-pythonworkflow-fl--x---d7231032:09533] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_4] Max memory used: 213MiB\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_4] completed success\n\u001b[1;30mINFO\u001b[0m [step calculate_qe_4] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step calculate_qe_5\n\u001b[1;30mINFO\u001b[0m [step calculate_qe_5] start\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_5] /tmp/d36x49f6$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/nvm7fsf5/stg384bab04-833c-43f2-bd00-f4b5a5c93eec/workflow.py \\\n --function=workflow.calculate_qe \\\n --arg_input_dict=/tmp/nvm7fsf5/stg9aa51e21-01b0-4157-b73f-a3feee8a917a/result.pickle \\\n --arg_working_directory=/tmp/nvm7fsf5/stg02ef6345-c598-4127-95c7-e92d0a977c40/working_directory_3.pickle\n[jupyter-pythonworkflow-fl--x---d7231032:09611] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_5] Max memory used: 243MiB\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_5] completed success\n\u001b[1;30mINFO\u001b[0m [step calculate_qe_5] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step calculate_qe_6\n\u001b[1;30mINFO\u001b[0m [step calculate_qe_6] start\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_6] /tmp/eiyg8it6$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/708xmf3f/stg791b1717-cfb1-4569-ba75-d648a84e0a72/workflow.py \\\n --function=workflow.calculate_qe \\\n --arg_input_dict=/tmp/708xmf3f/stg9ebf7054-080c-4173-a8b9-2247d01a0068/result.pickle \\\n --arg_working_directory=/tmp/708xmf3f/stg1afccee5-d9b6-46ed-bc2c-fa36bdb8013d/working_directory_4.pickle\n[jupyter-pythonworkflow-fl--x---d7231032:09688] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_6] Max memory used: 245MiB\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_6] completed success\n\u001b[1;30mINFO\u001b[0m [step calculate_qe_6] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step calculate_qe_7\n\u001b[1;30mINFO\u001b[0m [step calculate_qe_7] start\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_7] /tmp/qjgxwxnd$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/g3sp392q/stg0a51a8da-c7a7-4d90-a49c-1817002a62a6/workflow.py \\\n --function=workflow.calculate_qe \\\n --arg_input_dict=/tmp/g3sp392q/stg67e73a60-3cc6-46dd-b009-cfc0034aec2c/result.pickle \\\n --arg_working_directory=/tmp/g3sp392q/stgf3d265db-820b-4af3-8975-0a6faa0d7a67/working_directory_5.pickle\n[jupyter-pythonworkflow-fl--x---d7231032:09770] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_7] Max memory used: 244MiB\n\u001b[1;30mINFO\u001b[0m [job calculate_qe_7] completed success\n\u001b[1;30mINFO\u001b[0m [step calculate_qe_7] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step get_list_31\n\u001b[1;30mINFO\u001b[0m [step get_list_31] start\n\u001b[1;30mINFO\u001b[0m [job get_list_31] /tmp/mnovytq_$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --function=python_workflow_definition.shared.get_list \\\n --arg_0=/tmp/bz0ntajx/stgdab2f59b-b118-44c4-96ef-b4639edaee4e/energy.pickle \\\n --arg_2=/tmp/bz0ntajx/stg2e9bec4d-1824-4152-b003-aab0eac204cd/energy.pickle \\\n --arg_1=/tmp/bz0ntajx/stg9511563e-9784-48a9-8d81-74ade3a084c1/energy.pickle \\\n --arg_4=/tmp/bz0ntajx/stg17845efd-e335-421e-9891-6e627254edb4/energy.pickle \\\n --arg_3=/tmp/bz0ntajx/stg051fa3bc-832a-4d70-b9fb-b9948f51904d/energy.pickle\n\u001b[1;30mINFO\u001b[0m [job get_list_31] completed success\n\u001b[1;30mINFO\u001b[0m [step get_list_31] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step get_list_30\n\u001b[1;30mINFO\u001b[0m [step get_list_30] start\n\u001b[1;30mINFO\u001b[0m [job get_list_30] /tmp/vc0dzppy$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --function=python_workflow_definition.shared.get_list \\\n --arg_0=/tmp/mejux8b1/stg71e3a6a9-c56b-4be8-8720-0ca90ac40513/volume.pickle \\\n --arg_2=/tmp/mejux8b1/stg429d498d-cf56-4561-a653-8048c1213851/volume.pickle \\\n --arg_1=/tmp/mejux8b1/stgee1a0001-20f2-45de-ac4e-77b0d0c59957/volume.pickle \\\n --arg_4=/tmp/mejux8b1/stg0de2a6dc-57cd-4a0c-9637-ef2e63e96fce/volume.pickle \\\n --arg_3=/tmp/mejux8b1/stga4551f25-d5f6-47c6-92ea-452cf694a286/volume.pickle\n\u001b[1;30mINFO\u001b[0m [job get_list_30] completed success\n\u001b[1;30mINFO\u001b[0m [step get_list_30] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] starting step plot_energy_volume_curve_8\n\u001b[1;30mINFO\u001b[0m [step plot_energy_volume_curve_8] start\n\u001b[1;30mINFO\u001b[0m [job plot_energy_volume_curve_8] /tmp/j4v3j3mt$ python \\\n -m \\\n python_workflow_definition.cwl \\\n --workflowfile=/tmp/_67k4bu3/stg5be48d76-8a92-4b02-b3d6-7bdb4c35c9ce/workflow.py \\\n --function=workflow.plot_energy_volume_curve \\\n --arg_volume_lst=/tmp/_67k4bu3/stgd43e71b0-d16b-4eb2-8d14-83924dafd7d6/result.pickle \\\n --arg_energy_lst=/tmp/_67k4bu3/stg43eeacdd-5042-4f2d-8efc-d8e0d5fe1c14/result.pickle\n\u001b[1;30mINFO\u001b[0m [job plot_energy_volume_curve_8] Max memory used: 112MiB\n\u001b[1;30mINFO\u001b[0m [job plot_energy_volume_curve_8] completed success\n\u001b[1;30mINFO\u001b[0m [step plot_energy_volume_curve_8] completed success\n\u001b[1;30mINFO\u001b[0m [workflow ] completed success\n{\n \"result_file\": {\n \"location\": \"file:///home/jovyan/example_workflows/quantum_espresso/result.pickle\",\n \"basename\": \"result.pickle\",\n \"class\": \"File\",\n \"checksum\": \"sha1$dbc1aaddc8b7343d6d33b34edcf608b8f8801918\",\n \"size\": 4,\n \"path\": \"/home/jovyan/example_workflows/quantum_espresso/result.pickle\"\n }\n}\u001b[1;30mINFO\u001b[0m Final process status is success\n" + } + ], + "execution_count": 6 + }, + { + "cell_type": "markdown", + "id": "7ddd08ec", + "source": "`cwltool` runs one step per PWD function node - `get_bulk_structure`, the `vc-relax` `calculate_qe`, `generate_structures`, the five strained `scf` `calculate_qe` steps and finally `plot_energy_volume_curve` - each reading its input pickles and writing its output pickle(s), exactly mirroring the fan-out of one relax followed by five parallel SCF calculations seen in the other notebooks. The workflow's final output is declared as `result_file`, the pickle produced by the last step.", + "metadata": {} + }, + { + "id": "2942dbba-ea0a-4d20-be5c-ed9992d09ff8", + "cell_type": "code", + "source": "with open(\"result.pickle\", \"rb\") as f:\n print(pickle.load(f))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "None\n" + } + ], + "execution_count": 7 + }, + { + "cell_type": "markdown", + "id": "e9ec76ee", + "source": "`plot_energy_volume_curve` has no return value, so `result_file` unpickles to `None` here - that is expected. The actual output of this workflow is the `evcurve.png` plot, written as a side effect into the working directory of the last CWL step.", + "metadata": {} + }, + { + "id": "60e909ee-d0d0-4bd1-81c8-dd5274ae5834", + "cell_type": "code", + "source": "", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": null + } + ] +} \ No newline at end of file diff --git a/_sources/example_workflows/quantum_espresso/executorlib.ipynb b/_sources/example_workflows/quantum_espresso/executorlib.ipynb new file mode 100644 index 00000000..e4ebd6f0 --- /dev/null +++ b/_sources/example_workflows/quantum_espresso/executorlib.ipynb @@ -0,0 +1,5558 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "be2d61b0-0d47-4349-b4b0-1b767c961644", + "metadata": {}, + "source": "# executorlib\n\nThis notebook builds the Quantum Espresso energy-volume-curve workflow with [`executorlib`](https://github.com/pyiron/executorlib), a lightweight `concurrent.futures`-style executor. Tasks are submitted individually with `.submit()`, and the resulting graph is exported as a PWD `workflow.json` as a side effect. The second half of the notebook loads that same JSON with `aiida-workgraph`, `jobflow` and `pyiron_base`/`pyiron_workflow`." + }, + { + "cell_type": "markdown", + "id": "0bad2a57-1bd2-4837-94fe-f8c60e211fae", + "metadata": {}, + "source": "## Define workflow with executorlib\n\n`SingleNodeExecutor` runs submitted functions in local worker processes. Passing `export_workflow_filename` makes it record every `.submit()` call and its dependencies and write them out as `workflow_json_filename` once the `with` block exits - no separate `write_workflow_json` call is needed, unlike the other engines." + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "a2ed2608-9e1b-4a81-81cb-5079573ea2d1", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "from executorlib import SingleNodeExecutor, get_item_from_future" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "ea65c6275f956bdb", + "metadata": {}, + "outputs": [], + "source": [ + "from workflow import calculate_qe, generate_structures, get_bulk_structure, plot_energy_volume_curve" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "686a6a5f54a0cef5", + "metadata": {}, + "outputs": [], + "source": [ + "workflow_json_filename = \"executorlib_qe.json\"" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "5071d3a0-7c1f-44c5-85e0-dede1566c10c", + "metadata": {}, + "outputs": [], + "source": [ + "pseudopotentials = {\"Al\": \"Al.pbe-n-kjpaw_psl.1.0.0.UPF\"}" + ] + }, + { + "cell_type": "markdown", + "id": "9ce84a62", + "source": "Each `exe.submit()` call schedules one function call and returns a `Future`. Since `calculate_qe` returns a dict, `get_item_from_future` extracts a single key (e.g. `\"structure\"`, `\"energy\"`, `\"volume\"`) from a future's eventual result so it can be passed as an argument to the next `submit()` call. The relaxed structure is strained into `number_of_strains` (5) structures by `generate_structures`, and each strained structure is submitted as its own independent `scf` `calculate_qe` call - the fan-out that produces the 5 points of the energy-volume curve.", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "1f1cb12f-4001-478d-8ea0-b369f4f2981a", + "metadata": {}, + "outputs": [], + "source": [ + "with SingleNodeExecutor(export_workflow_filename=workflow_json_filename) as exe:\n", + " structure_future = exe.submit(\n", + " get_bulk_structure,\n", + " element=\"Al\",\n", + " a=4.04,\n", + " cubic=True,\n", + " )\n", + " calc_mini_future = exe.submit(\n", + " calculate_qe,\n", + " working_directory=\"mini\",\n", + " input_dict={\n", + " \"structure\": structure_future,\n", + " \"pseudopotentials\": pseudopotentials,\n", + " \"kpts\": (3, 3, 3),\n", + " \"calculation\": \"vc-relax\",\n", + " \"smearing\": 0.02,\n", + " },\n", + " )\n", + " number_of_strains = 5\n", + " structure_lst_future = exe.submit(\n", + " generate_structures,\n", + " structure=get_item_from_future(calc_mini_future, key=\"structure\"),\n", + " strain_lst=np.linspace(0.9, 1.1, number_of_strains),\n", + " )\n", + " calc_future_lst = []\n", + " for i, structure_strain in [[i, get_item_from_future(structure_lst_future, key=\"s_\" + str(i))] for i in range(number_of_strains)]:\n", + " calc_future_lst.append(exe.submit(\n", + " calculate_qe,\n", + " working_directory=\"strain_\" + str(i),\n", + " input_dict={\n", + " \"structure\": structure_strain,\n", + " \"pseudopotentials\": pseudopotentials,\n", + " \"kpts\": (3, 3, 3),\n", + " \"calculation\": \"scf\",\n", + " \"smearing\": 0.02,\n", + " },\n", + " ))\n", + " plot_future = exe.submit(\n", + " plot_energy_volume_curve,\n", + " volume_lst=[get_item_from_future(future=f, key=\"volume\") for f in calc_future_lst],\n", + " energy_lst=[get_item_from_future(future=f, key=\"energy\") for f in calc_future_lst],\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "72c8e6e6-8e60-4a4f-81f3-968b4b5f36ee", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"version\": \"0.1.0\",\n", + " \"nodes\": [\n", + " {\n", + " \"id\": 0,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.get_bulk_structure\"\n", + " },\n", + " {\n", + " \"id\": 1,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.calculate_qe\"\n", + " },\n", + " {\n", + " \"id\": 2,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.generate_structures\"\n", + " },\n", + " {\n", + " \"id\": 3,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.calculate_qe\"\n", + " },\n", + " {\n", + " \"id\": 4,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.calculate_qe\"\n", + " },\n", + " {\n", + " \"id\": 5,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.calculate_qe\"\n", + 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\"source\": 6,\n", + " \"sourcePort\": \"volume\"\n", + " },\n", + " {\n", + " \"target\": 30,\n", + " \"targetPort\": \"4\",\n", + " \"source\": 7,\n", + " \"sourcePort\": \"volume\"\n", + " },\n", + " {\n", + " \"target\": 8,\n", + " \"targetPort\": \"energy_lst\",\n", + " \"source\": 31,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 31,\n", + " \"targetPort\": \"0\",\n", + " \"source\": 3,\n", + " \"sourcePort\": \"energy\"\n", + " },\n", + " {\n", + " \"target\": 31,\n", + " \"targetPort\": \"1\",\n", + " \"source\": 4,\n", + " \"sourcePort\": \"energy\"\n", + " },\n", + " {\n", + " \"target\": 31,\n", + " \"targetPort\": \"2\",\n", + " \"source\": 5,\n", + " \"sourcePort\": \"energy\"\n", + " },\n", + " {\n", + " \"target\": 31,\n", + " \"targetPort\": \"3\",\n", + " \"source\": 6,\n", + " \"sourcePort\": \"energy\"\n", + " },\n", + " {\n", + " \"target\": 31,\n", + " \"targetPort\": \"4\",\n", + " \"source\": 7,\n", + " \"sourcePort\": \"energy\"\n", + " },\n", + " {\n", + " \"target\": 32,\n", + " \"targetPort\": null,\n", + " \"source\": 31,\n", + " \"sourcePort\": null\n", + " }\n", + " ]\n", + "}" + ] + } + ], + "source": [ + "!cat {workflow_json_filename}" + ] + }, + { + "cell_type": "markdown", + "id": "7d75a2f6-6fad-49c8-bd29-37cca1b84441", + "metadata": {}, + "source": "## Load Workflow with aiida\n\n`load_workflow_json` reconstructs the graph as an `aiida-workgraph` `WorkGraph`. To demonstrate that the loaded graph can still be edited like one built natively with `aiida-workgraph`, the lattice constant `a` is overridden (4.04 -> 4.05) before running it with `wg.run()`." + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "28760464-2a2c-40c2-9451-20713da2ba2c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Profile" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from aiida import orm, load_profile\n", + "\n", + "load_profile()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "a442fe46-057c-469b-a5e0-173ed4829dfb", + "metadata": {}, + "outputs": [], + "source": [ + "from python_workflow_definition.aiida import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "32fcd4b2-4f0a-442d-b098-827672823796", + "metadata": {}, + "outputs": [], + "source": [ + "wg = load_workflow_json(file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d81a4fb5-a674-41a9-ac19-24c56f952468", + "metadata": {}, + "outputs": [], + "source": [ + "wg.tasks.get_bulk_structure.inputs.a.value = orm.Float(4.05)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "a80b59bd-fe30-49c6-92ca-35ef2d77a6fb", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "01/16/2026 08:27:06 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_bulk_structure\n", + "01/16/2026 08:27:06 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: get_bulk_structure, type: PYFUNCTION, finished.\n", + "01/16/2026 08:27:06 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict\n", + "01/16/2026 08:27:07 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: get_dict, type: PYFUNCTION, finished.\n", + "01/16/2026 08:27:07 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe\n", + "01/16/2026 08:28:16 AM <71653> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: ['energy', 'volume']\n", + "01/16/2026 08:28:17 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: calculate_qe, type: PYFUNCTION, finished.\n", + "01/16/2026 08:28:17 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: generate_structures\n", + "01/16/2026 08:28:18 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: generate_structures, type: PYFUNCTION, finished.\n", + "01/16/2026 08:28:18 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict1,get_dict2,get_dict3,get_dict4,get_dict5\n", + "01/16/2026 08:28:18 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: get_dict1, type: PYFUNCTION, finished.\n", + "01/16/2026 08:28:18 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe1,get_dict2,get_dict3,get_dict4,get_dict5\n", + "01/16/2026 08:28:34 AM <71653> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: ['structure']\n", + "01/16/2026 08:28:34 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: calculate_qe1, type: PYFUNCTION, finished.\n", + "01/16/2026 08:28:34 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict2,get_dict3,get_dict4,get_dict5\n", + "01/16/2026 08:28:35 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: get_dict2, type: PYFUNCTION, finished.\n", + "01/16/2026 08:28:35 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe2,get_dict3,get_dict4,get_dict5\n", + "01/16/2026 08:28:51 AM <71653> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: ['structure']\n", + "01/16/2026 08:28:51 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: calculate_qe2, type: PYFUNCTION, finished.\n", + "01/16/2026 08:28:51 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict3,get_dict4,get_dict5\n", + "01/16/2026 08:28:51 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: get_dict3, type: PYFUNCTION, finished.\n", + "01/16/2026 08:28:52 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe3,get_dict4,get_dict5\n", + "01/16/2026 08:29:11 AM <71653> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: ['structure']\n", + "01/16/2026 08:29:12 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: calculate_qe3, type: PYFUNCTION, finished.\n", + "01/16/2026 08:29:12 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict4,get_dict5\n", + "01/16/2026 08:29:12 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: get_dict4, type: PYFUNCTION, finished.\n", + "01/16/2026 08:29:13 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe4,get_dict5\n", + "01/16/2026 08:29:34 AM <71653> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: ['structure']\n", + "01/16/2026 08:29:35 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: calculate_qe4, type: PYFUNCTION, finished.\n", + "01/16/2026 08:29:35 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict5\n", + "01/16/2026 08:29:36 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: get_dict5, type: PYFUNCTION, finished.\n", + "01/16/2026 08:29:36 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe5\n", + "01/16/2026 08:29:58 AM <71653> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: ['structure']\n", + "01/16/2026 08:29:59 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: calculate_qe5, type: PYFUNCTION, finished.\n", + "01/16/2026 08:29:59 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_list,get_list1\n", + "01/16/2026 08:29:59 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: get_list, type: PYFUNCTION, finished.\n", + "01/16/2026 08:29:59 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_list1\n", + "01/16/2026 08:30:00 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: get_list1, type: PYFUNCTION, finished.\n", + "01/16/2026 08:30:00 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: plot_energy_volume_curve\n", + "01/16/2026 08:30:00 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|update_task_state]: Task: plot_energy_volume_curve, type: PYFUNCTION, finished.\n", + "01/16/2026 08:30:00 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n", + "01/16/2026 08:30:01 AM <71653> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [1663|WorkGraphEngine|finalize]: Finalize workgraph.\n" + ] + }, + { + "data": { + "text/plain": [ + "{}" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "wg.run()" + ] + }, + { + "cell_type": "markdown", + "id": "c4f5c047-c6da-4b54-9007-415faca7a448", + "metadata": {}, + "source": "## Load Workflow with jobflow\n\nThe same JSON is loaded as a `jobflow` `Flow` and executed locally with `run_locally`, again after overriding the lattice constant `a`." + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "b8e3c2ca-2672-4e9d-aada-63344842dbcf", + "metadata": {}, + "outputs": [], + "source": [ + "from python_workflow_definition.jobflow import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "54a24ff6c569094e", + "metadata": {}, + "outputs": [], + "source": [ + "from jobflow.managers.local import run_locally" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "48a27146-7372-40ab-8b02-e2a9283d4748", + "metadata": {}, + "outputs": [], + "source": [ + "flow = load_workflow_json(file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "bf84ef10-e1af-475f-a457-d2703c7276a0", + "metadata": {}, + "outputs": [], + "source": [ + "flow[0].function_kwargs[\"a\"] = 4.05" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "98fa5694-2cc6-44e9-a6e7-2cc71b4f48ce", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2026-01-16 08:31:28,452 INFO Started executing jobs locally\n", + "2026-01-16 08:31:28,816 INFO Starting job - get_bulk_structure (9a8ea16b-3d54-40ab-ba1c-ed56a2f6c7a3)\n", + "2026-01-16 08:31:28,821 INFO Finished job - get_bulk_structure (9a8ea16b-3d54-40ab-ba1c-ed56a2f6c7a3)\n", + "2026-01-16 08:31:28,821 INFO Starting job - get_dict (0dbdd8f7-8a2f-4160-be09-0620e7fa3bea)\n", + "2026-01-16 08:31:28,825 INFO Finished job - get_dict (0dbdd8f7-8a2f-4160-be09-0620e7fa3bea)\n", + "2026-01-16 08:31:28,826 INFO Starting job - calculate_qe (583839c2-ffac-4ef2-8ca4-64c2a7701745)\n", + "2026-01-16 08:32:37,487 INFO Finished job - calculate_qe (583839c2-ffac-4ef2-8ca4-64c2a7701745)\n", + "2026-01-16 08:32:37,489 INFO Starting job - generate_structures (c8cf3dd8-ddfc-4f28-9d19-6da0ab99346f)\n", + "2026-01-16 08:32:37,497 INFO Finished job - generate_structures (c8cf3dd8-ddfc-4f28-9d19-6da0ab99346f)\n", + "2026-01-16 08:32:37,498 INFO Starting job - get_dict (f50678d3-6d30-4941-822d-e9e46a0d42aa)\n", + "2026-01-16 08:32:37,501 INFO Finished job - get_dict (f50678d3-6d30-4941-822d-e9e46a0d42aa)\n", + "2026-01-16 08:32:37,503 INFO Starting job - get_dict (115aa31e-629e-4371-8c88-9e12e5fc0c4e)\n", + "2026-01-16 08:32:37,508 INFO Finished job - get_dict (115aa31e-629e-4371-8c88-9e12e5fc0c4e)\n", + "2026-01-16 08:32:37,510 INFO Starting job - get_dict (7e22fea0-9529-44ce-8ce0-5dc47cf9a558)\n", + "2026-01-16 08:32:37,517 INFO Finished job - get_dict (7e22fea0-9529-44ce-8ce0-5dc47cf9a558)\n", + "2026-01-16 08:32:37,518 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "result = run_locally(flow)\n", + "result" + ] + }, + { + "cell_type": "markdown", + "id": "9a956c9e", + "metadata": {}, + "source": "## Load Workflow with pyiron_base\n\n`pyiron_base`'s loader turns the graph into a list of delayed jobs. `.draw()` visualizes the dependency graph and `.pull()` executes the whole chain (relax + 5 strained SCF calculations), after the lattice constant override." + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "60e3a47c", + "metadata": {}, + "outputs": [], + "source": [ + "from python_workflow_definition.pyiron_base import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "2b5f8ac0", + "metadata": {}, + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "create_function_job_5b061420d63d9ec78dec4ea199d17802\n", + "\n", + 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"working_directory_72bba39b22d2b7ce154d37c7e8c658b7->4_f1a7b8e82b6bf6190263e6e6d63b9ebf\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "working_directory_72bba39b22d2b7ce154d37c7e8c658b7->4_b415c675207adb05d16e428662ace723\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "4_b415c675207adb05d16e428662ace723->energy_lst_66d2789b6d3a5694711b89056d28c94e\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "energy_lst_66d2789b6d3a5694711b89056d28c94e->create_function_job_5b061420d63d9ec78dec4ea199d17802\n", + "\n", + "\n", + "\n", + "\n", + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "delayed_object_lst = load_workflow_json(file_name=workflow_json_filename)\n", + "delayed_object_lst[-1].draw()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "6a5b0297", + "metadata": {}, + "outputs": [], + "source": [ + "delayed_object_lst[0].input['a'] = 4.05" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "5a1666ae", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job get_bulk_structure_2ca4aeae204ceaa28593c93054b07908 was saved and received the ID: 40\n", + "The job get_dict_1e47509b88d63a21fd421686554c8f4a was saved and received the ID: 41\n", + "The job calculate_qe_411e578f2700d09ba2df9a4c682b4582 was saved and received the ID: 42\n", + "The job generate_structures_7f140b9836b0bba16af81baf1b246241 was saved and received the ID: 43\n", + "The job get_dict_c58ae4a3f59bfb45975f3785a2ea7f39 was saved and received the ID: 44\n", + "The job calculate_qe_fe50ef8ac8518002303cd38ac9d6815a was saved and received the ID: 45\n", + "The job get_dict_15fbde13a9aabf52685fc04f66093040 was saved and received the ID: 46\n", + "The job calculate_qe_80b9c98a7807cac136aa34a89dde5b3c was saved and received the ID: 47\n", + "The job get_dict_63901158944acf473876b0bcffdfc90c was saved and received the ID: 48\n", + "The job calculate_qe_d20ea0f0eb2b5331fdae70cdb74b5b47 was saved and received the ID: 49\n", + "The job get_dict_0426b545b339ef96773c978a8d508c0b was saved and received the ID: 50\n", + "The job calculate_qe_0e46fbe7e87a5b5a8cadd21dad9584fc was saved and received the ID: 51\n", + "The job get_dict_cfd40a0a40679f9c358ca371dcf2f5c2 was saved and received the ID: 52\n", + "The job calculate_qe_ad9c11a3767907eb1b0532258092495c was saved and received the ID: 53\n", + "The job get_list_58b9234b924f260fdd0ca16332ed9a67 was saved and received the ID: 54\n", + "The job get_list_093dd62325e29744484ef602b97e825f was saved and received the ID: 55\n", + "The job plot_energy_volume_curve_9e2db727fd8ef415e376c937e44a8213 was saved and received the ID: 56\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "delayed_object_lst[-1].pull()" + ] + }, + { + "cell_type": "markdown", + "id": "406b0429e65b9760", + "metadata": {}, + "source": "## Load Workflow with pyiron_workflow\n\nFinally, the graph is loaded into a `pyiron_workflow` `Workflow`, its lattice constant overridden, drawn with `.draw()`, and executed with `.run()`." + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "1b45a453f593202f", + "metadata": {}, + "outputs": [], + "source": [ + "from python_workflow_definition.pyiron_workflow import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "97ef39ae859855ab", + "metadata": {}, + "outputs": [], + "source": [ + "wf = load_workflow_json(file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "4368c6921b71e396", + "metadata": {}, + "outputs": [], + "source": [ + "wf.get_bulk_structure.inputs.a.value = 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "wf.run()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5022eb03-b714-409d-b82b-cada385b351d", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} \ No newline at end of file diff --git a/_sources/example_workflows/quantum_espresso/jobflow.ipynb b/_sources/example_workflows/quantum_espresso/jobflow.ipynb new file mode 100644 index 00000000..d8b1e1fa --- /dev/null +++ b/_sources/example_workflows/quantum_espresso/jobflow.ipynb @@ -0,0 +1,5739 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# jobflow" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, + "source": [ + "[`jobflow`](https://materialsproject.github.io/jobflow/index.html) and [`atomate2`](https://materialsproject.github.io/atomate2/index.html) are key packages of the [Materials Project](https://materialsproject.org/) . `jobflow` was especially designed to simplify the execution of dynamic workflows -- when the actual number of jobs is dynamically determined upon runtime instead of being statically fixed before running the workflow(s). `jobflow`'s overall flexibility allows for building workflows that go beyond the usage in materials science. `jobflow` serves as the basis of `atomate2`, which implements data generation workflows in the context of materials science and will be used for data generation in the Materials Project in the future." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Define workflow with jobflow\n", + "\n", + "We start by importing the job decorator and Flow class from `jobflow` and the respective PWD tools." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from jobflow import job, Flow" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from python_workflow_definition.jobflow import write_workflow_json" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, + "source": [ + "## Quantum Espresso Workflow\n", + "We will use the knowledge from the previous arithmetic workflow example to create the Quantum Espresso-related tasks for calculating an \"Energy vs. Volume\" curve. It’s important to note that this is only a basic implementation, and further extensions towards data validation or for a simplified user experience can be added. For example, one can typically configure run commands for quantum-chemical programs via configuration files in atomate2." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from workflow import (\n", + " calculate_qe as _calculate_qe, \n", + " generate_structures as _generate_structures, \n", + " get_bulk_structure as _get_bulk_structure, \n", + " plot_energy_volume_curve as _plot_energy_volume_curve,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "workflow_json_filename = \"jobflow_qe.json\"" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "calculate_qe = job(_calculate_qe)\n", + "generate_structures = job(_generate_structures)\n", + "plot_energy_volume_curve = job(_plot_energy_volume_curve)\n", + "get_bulk_structure = job(_get_bulk_structure)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, + "source": [ + "We need to specify the typical QE input like pseudopotential(s) and structure model." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "pseudopotentials = {\"Al\": \"Al.pbe-n-kjpaw_psl.1.0.0.UPF\"}" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "structure = get_bulk_structure(\n", + " element=\"Al\",\n", + " a=4.04,\n", + " cubic=True,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "calc_mini = calculate_qe(\n", + " working_directory=\"mini\",\n", + " input_dict={\n", + " \"structure\": structure.output,\n", + " \"pseudopotentials\": pseudopotentials,\n", + " \"kpts\": (3, 3, 3),\n", + " \"calculation\": \"vc-relax\",\n", + " \"smearing\": 0.02,\n", + " },\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, + "source": "Next, for the \"Energy vs. Volume\" curve, we need to specify the number of strained structures and save them into a list object. This is the fan-out point of the workflow: for each of the `number_of_strains` (5) strained structures, an independent `scf` QE calculation is carried out below." + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "number_of_strains = 5\n", + "structure_lst = generate_structures(\n", + " structure=calc_mini.output.structure,\n", + " strain_lst=np.linspace(0.9, 1.1, number_of_strains),\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "job_strain_lst = []\n", + "for i in range(number_of_strains):\n", + " calc_strain = calculate_qe(\n", + " working_directory=\"strain_\" + str(i),\n", + " input_dict={\n", + " \"structure\": getattr(structure_lst.output, f\"s_{i}\"),\n", + " \"pseudopotentials\": pseudopotentials,\n", + " \"kpts\": (3, 3, 3),\n", + " \"calculation\": \"scf\",\n", + " \"smearing\": 0.02,\n", + " },\n", + " )\n", + " job_strain_lst.append(calc_strain)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, + "source": [ + "Finally, we specify a plotter for the \"Energy vs. Volume\" curve and can export the workflow." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "plot = plot_energy_volume_curve(\n", + " volume_lst=[job.output.volume for job in job_strain_lst],\n", + " energy_lst=[job.output.energy for job in job_strain_lst],\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "flow = Flow([structure, calc_mini, structure_lst] + job_strain_lst + [plot])" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "write_workflow_json(flow=flow, file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"version\": \"0.1.0\",\n", + " \"nodes\": [\n", + " {\n", + " \"id\": 0,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.get_bulk_structure\"\n", + " },\n", + " {\n", + " \"id\": 1,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.calculate_qe\"\n", + " },\n", + " {\n", + " \"id\": 2,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.generate_structures\"\n", + " },\n", + " {\n", + " \"id\": 3,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.calculate_qe\"\n", + " },\n", + " {\n", + " \"id\": 4,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.calculate_qe\"\n", + " },\n", + " {\n", + " \"id\": 5,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.calculate_qe\"\n", + " },\n", + " {\n", 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},\n", + " {\n", + " \"target\": 8,\n", + " \"targetPort\": \"volume_lst\",\n", + " \"source\": 30,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 31,\n", + " \"targetPort\": \"0\",\n", + " \"source\": 3,\n", + " \"sourcePort\": \"energy\"\n", + " },\n", + " {\n", + " \"target\": 31,\n", + " \"targetPort\": \"1\",\n", + " \"source\": 4,\n", + " \"sourcePort\": \"energy\"\n", + " },\n", + " {\n", + " \"target\": 31,\n", + " \"targetPort\": \"2\",\n", + " \"source\": 5,\n", + " \"sourcePort\": \"energy\"\n", + " },\n", + " {\n", + " \"target\": 31,\n", + " \"targetPort\": \"3\",\n", + " \"source\": 6,\n", + " \"sourcePort\": \"energy\"\n", + " },\n", + " {\n", + " \"target\": 31,\n", + " \"targetPort\": \"4\",\n", + " \"source\": 7,\n", + " \"sourcePort\": \"energy\"\n", + " },\n", + " {\n", + " \"target\": 8,\n", + " \"targetPort\": \"energy_lst\",\n", + " \"source\": 31,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 32,\n", + " \"targetPort\": null,\n", + " \"source\": 8,\n", + " \"sourcePort\": null\n", + " }\n", + " ]\n", + "}" + ] + } + ], + "source": [ + "!cat {workflow_json_filename}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Load Workflow with aiida\n", + "\n", + "Now, we can import the workflow, run it with `aiida` and plot the \"Energy vs. Volume\" curve." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Profile" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from aiida import orm, load_profile\n", + "\n", + "load_profile()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from python_workflow_definition.aiida import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wg = load_workflow_json(workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true, + "trusted": true + }, + "outputs": [], + "source": [ + "wg.tasks.get_bulk_structure.inputs.a.value = orm.Float(4.05)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "e9bb01de73ff4284a7578d7064ae369f", + "version_major": 2, + "version_minor": 1 + }, + "text/plain": [ + "NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'WorkGra…" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wg" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "05/26/2025 04:59:05 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_bulk_structure1\n", + "05/26/2025 04:59:05 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: get_bulk_structure1, type: PyFunction, finished.\n", + "05/26/2025 04:59:05 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict10\n", + "05/26/2025 04:59:06 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: get_dict10, type: PyFunction, finished.\n", + "05/26/2025 04:59:06 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe2\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02569] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 04:59:56 AM <2497> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['energy', 'volume'])\n", + "05/26/2025 04:59:57 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: calculate_qe2, type: PyFunction, finished.\n", + "05/26/2025 04:59:57 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: generate_structures3\n", + "05/26/2025 04:59:58 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: generate_structures3, type: PyFunction, finished.\n", + "05/26/2025 04:59:58 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict11,get_dict12,get_dict13,get_dict14,get_dict15\n", + "05/26/2025 04:59:58 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: get_dict11, type: PyFunction, finished.\n", + "05/26/2025 04:59:58 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe4,get_dict12,get_dict13,get_dict14,get_dict15\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02586] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 05:00:10 AM <2497> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n", + "05/26/2025 05:00:10 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: calculate_qe4, type: PyFunction, finished.\n", + "05/26/2025 05:00:10 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict12,get_dict13,get_dict14,get_dict15\n", + "05/26/2025 05:00:11 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: get_dict12, type: PyFunction, finished.\n", + "05/26/2025 05:00:11 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe5,get_dict13,get_dict14,get_dict15\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02596] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 05:00:22 AM <2497> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n", + "05/26/2025 05:00:22 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: calculate_qe5, type: PyFunction, finished.\n", + "05/26/2025 05:00:22 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict13,get_dict14,get_dict15\n", + "05/26/2025 05:00:23 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: get_dict13, type: PyFunction, finished.\n", + "05/26/2025 05:00:23 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe6,get_dict14,get_dict15\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02606] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 05:00:35 AM <2497> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n", + "05/26/2025 05:00:35 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: calculate_qe6, type: PyFunction, finished.\n", + "05/26/2025 05:00:35 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict14,get_dict15\n", + "05/26/2025 05:00:35 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: get_dict14, type: PyFunction, finished.\n", + "05/26/2025 05:00:36 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe7,get_dict15\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02616] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 05:00:50 AM <2497> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n", + "05/26/2025 05:00:51 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: calculate_qe7, type: PyFunction, finished.\n", + "05/26/2025 05:00:51 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict15\n", + "05/26/2025 05:00:51 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: get_dict15, type: PyFunction, finished.\n", + "05/26/2025 05:00:51 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe8\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02626] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 05:01:05 AM <2497> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n", + "05/26/2025 05:01:05 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: calculate_qe8, type: PyFunction, finished.\n", + "05/26/2025 05:01:06 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_list16,get_list17\n", + "05/26/2025 05:01:06 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: get_list16, type: PyFunction, finished.\n", + "05/26/2025 05:01:07 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_list17\n", + "05/26/2025 05:01:07 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: get_list17, type: PyFunction, finished.\n", + "05/26/2025 05:01:07 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: plot_energy_volume_curve9\n", + "05/26/2025 05:01:08 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|update_task_state]: Task: plot_energy_volume_curve9, type: PyFunction, finished.\n", + "05/26/2025 05:01:08 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n", + "05/26/2025 05:01:08 AM <2497> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [111|WorkGraphEngine|finalize]: Finalize workgraph.\n" + ] + }, + { + "data": { + "image/png": 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directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job get_dict_7079cab3db71ad163cfc2e39fcf98688 was saved and received the ID: 9\n", + "The job calculate_qe_3c1dbc8b42e651e328ae99033a426980 was saved and received the ID: 10\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---218119f8:02690] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job get_dict_0e89a9ec0ef1fd918240aa8d2dc44178 was saved and received the ID: 11\n", + "The job calculate_qe_2550d6d1ccd7ab3d68c384d3887a3fe3 was saved and received the ID: 12\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---218119f8:02700] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job get_dict_2ac7f25535cfa6c6850c0f9af197b541 was saved and received the ID: 13\n", + "The job calculate_qe_10d82eb36a247279f62c63b70e1a55d2 was saved and received the ID: 14\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---218119f8:02710] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job get_list_e21c87f95f3795055e7214eec6d7c927 was saved and received the ID: 15\n", + "The job get_list_61df540ee8a34a06782249cbe8834865 was saved and received the ID: 16\n", + "The job plot_energy_volume_curve_bbe171c30a8de804ba8d4227e65e62bf was saved and received the ID: 17\n" + ] + }, + { + "data": { + "image/png": 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GDBjAtGnTWLFiBfv27WPu3Ll88sknjB07Fiid2ps2bRpvvvkmCxYsYPfu3Tz55JPs2rWLO++805T3ak9lJ3p/tyWVIzkF5oYRERGpo0wdWboQn3/+Offddx9DhgwBYPTo0cyePbvCNgkJCWRlZZV/PW/ePKZPn86tt97K8ePHCQ0N5fnnn+eee+4p3+aBBx4gPz+fqVOncvz4cbp27cqSJUu45JL6f0l991ZN6RbiQ9zBTL5Ye4D7B7UzO5KIiEid4xDrLNV1jrTO0p99G5fC/fPi8GvizqpHr8LNxSEGG0VERC5avVpnSWrP8E4t8G/izpGcAn7clmZ2HBERkTpHZamBc3NxIrpvKFC6jIAGGkVERCpSWRJu6dMKNxcnthzKYtOBTLPjiIiI1CkqS0Lzxu6M7hoEaJFKERGRP1NZEuB/ywj8tD2dtKxT5oYRERGpQ1SWBICOQVZ6t25Gic3gs9j9ZscRERGpM1SWpNwdp0eXvlh7gPyiEnPDiIiI1BEqS1JuUEQALX0acSKviG/jUsyOIyIiUieoLEk5F2cnJkSVLSOQrGUEREREUFmSP7np0lY0cnVmV3oOsXuPmx1HRETEdCpLUoHV05XrerQEtIyAiIgIqCxJJSb2CwNgaXwGB4/nmRtGRETEZCpLcoZ2AU24vJ0vNgM+WZNsdhwRERFTqSxJpcoWqZy3/iC5BcXmhhERETGRypJUamB7f8Kae5KTX8zCTYfMjiMiImIalSWplJOThdtPn7s0d3UyNpuWERARkYZJZUnO6oaewTR2d2HPkVx+333U7DgiIiKmUFmSs2ri4cq4XsGAlhEQEZGGS2VJqnR7VBgWC6xIOMKeIyfNjiMiImJ3KktSpTBfL67q4A/AJ6uTzQ0jIiJiApUlOadJl7UGYMHGQ2TnF5mcRkRExL5UluScLmvbnHb+jcktLOE/6w+aHUdERMSuVJbknCwWCxNPL1L58ZpkSrSMgIiINCAqS3JerusejLWRKwePn2LZrsNmxxEREbEblSU5L43cnLmpdwigZQRERKRhUVmS8zYhKgwnC6zec4xd6dlmxxEREbELlSU5by19GjG0YyAAc1clmxtGRETETlSW5IKULSOwaHMKJ3ILTU4jIiJS+1SW5IJcGtaUjkHeFBTb+HL9AbPjiIiI1DqVJbkgFoulfHTp0zX7KSqxmZxIRESkdqksyQUb2aUFzb3cSMvK5+cd6WbHERERqVUqS3LBPFydubVPK0AneouISP2nsiTVclvfUFydLWzYf4Jth7LMjiMiIlJrVJakWvy9PRjRuQWgRSpFRKR+U1mSapt4+kTv77amcjgn3+Q0IiIitUNlSaqtW4gP3Vv5UFRi8MVaLSMgIiL1k8qSXJSyZQQ+iz1AQXGJyWlERERqnsqSXJThnQIJ8Hbn6MkCftiaZnYcERGRGqeyJBfF1dmJ6L6hAMxZlYxhGCYnEhERqVkqS3LRbu7dCjcXJ7alZLHpwAmz44iIiNQolSW5aM0buzOmWxAAH2mRShERqWdUlqRGTOxXeqJ3zPZ0UjNPmZxGRESk5qgsSY2IDPKmT+tmlNgMPovdb3YcERGRGqOyJDWmbBmBL9cdIL9IywiIiMjFO3g8jzmr9mGzmXcBkcqS1JjBkQEEN23EibwivtmcYnYcERFxcDabwbQFW/jHdzt54cd403KoLEmNcXaycHtUGKBlBERE5OJ9tnY/sXuP08jVmeioUNNyqCxJjbqxVwiNXJ1JyMhhzd5jZscREREHdeBYHjN/3AXAY8PDCW3uZVoWlSWpUVZPV67v2RIoHV0SERG5UDabwcMLtnCqqIS+bZqVL35sFpUlqXFlywgsjc/gwLE8k9OIiIij+WRNMuv2HcfTzZmXru+Kk5PF1DwqS1Lj2vo35or2fhgGfLwm2ew4IiLiQJKP5jIrpnT6bfrwcFo19zQ5kcqS1JJJ/cIA+M/6g+QWFJsbRkREHILNZvDIgq3kF9mIatOcW/uYO/1WRmVJasWA9n608fUip6CYrzcdMjuOiIg4gLmrk1mXfBwvN2deuqGL6dNvZVSWpFY4OVm4/fTo0txVyaYuJiYiInXfvqO5vPTz6em3ayIIaWb+9FsZlSWpNdf3DKaJuwt7j+byW9IRs+OIiEgdVWIzmDZ/C/lFNvq39eXWPq3MjlSBypLUmsbuLozrFQKUji6JiIhUZs6qfWzYf4LG7i7Mur4zFkvdmH4ro7IktWpivzAsFvgt8Qi7D580O46IiNQxe46c5OWfEwB4/JoIgpvWnem3MipLUqtaNffk6vAAAD5enWxuGBERqVPKpt8Kim1c3s6Xm3uHmB2pUipLUusmXRYGwNebDpF1qsjcMCIiUmd8tHIfmw5knp5+61Lnpt/KqCxJret3SXM6BDQhr7CE+RsOmh1HRETqgN2HT/LyL6XTb0+MiKClTyOTE52dypLUOovFwsTTo0tzVydTomUEREQatBKbwcPzt1BYbOOK9n6Mv7RuTr+VUVkSuxjTrSU+nq4cOnGKpfEZZscRERETffD7XuIOZtLE3YUX6+DVb3+msiR20cjNmZsuLV03Q8sIiIg0XLsP5/DakkQAnhwVSQtr3Z1+K6OyJHYzISoUZycLa/YeIz4t2+w4IiJiZ8UlNh6av5XCYhtXdvBjXM9gsyOdF4cpSydOnCA6Ohqr1YrVaiU6OprMzMwq9zl58iRTpkwhODiYRo0aERERwbvvvlthm/T0dKKjowkMDMTLy4sePXqwYMGCWnwnDVeQTyOGdQwENLokItIQ/ev3vWw5mEkTDxdmXld3r377M4cpS7fccgtxcXHExMQQExNDXFwc0dHRVe4zdepUYmJi+Oyzz4iPj2fq1Knce++9fPvtt+XbREdHk5CQwOLFi9m2bRvXXXcd48ePZ/PmzbX9lhqksmUEvolL4XhuoblhRETEbhIzcnhjSRIAT4/qSKDVw+RE588hylJ8fDwxMTH8+9//JioqiqioKD744AO+//57EhISzrrfmjVruP322xk4cCBhYWH85S9/oWvXrmzYsKHCNvfeey+9e/emTZs2PPHEE/j4+LBp0yZ7vLUGp2doUzq19Kag2MaX6w6YHUdEROyguMRWevVbiY2rwv25vkdLsyNdEIcoS2vWrMFqtdKnT5/y5/r27YvVamX16tVn3a9///4sXryYlJQUDMNg+fLlJCYmMnTo0ArbfPXVVxw/fhybzca8efMoKChg4MCBtfmWGiyLxcKkfq0B+HTNfopKbCYnEhGR2vb+f/ey9VAW3h4uzLyu7l/99mcOUZbS09Px9/c/43l/f3/S09PPut+bb75JZGQkwcHBuLm5MWzYMN555x369+9fvs1XX31FcXExzZs3x93dnbvvvptFixZxySWXnPV1CwoKyM7OrvCQ8zeyawt8G7uTnp1PzPaz//cTERHHtys9mzeWll79NmN0RwK8HWf6rYypZWnGjBlYLJYqH2VTZpW1UMMwqmynb775JrGxsSxevJiNGzfy6quv8re//Y2lS5eWb/PEE09w4sQJli5dyoYNG3jwwQcZN24c27ZtO+vrzpw5s/xEc6vVSkhI3V5Mq65xd3Hm1j6lywjMWbXP5DQiIlJbik5PvxWVGAyK8Gdsd8eafitjMQzDtOWUjx49ytGjR6vcJiwsjC+++IIHH3zwjKvffHx8eP3115k0adIZ+506dQqr1cqiRYsYMWJE+fN33XUXhw4dIiYmhj179tC2bVu2b99Ox44dy7cZNGgQbdu25b333qs0U0FBAQUFBeVfZ2dnExISQlZWFt7e3ufz1hu8wzn5XDZrGUUlBt/+/TK6hviYHUlERGrYW78m8eqSRKyNXFky9Qr869ioUnZ2Nlar9Zx/v13smOkMvr6++Pr6nnO7qKgosrKyWLduHb179wZg7dq1ZGVl0a9fv0r3KSoqoqioCCenioNnzs7O2Gyl58nk5eUBVLlNZdzd3XF3dz9nbjk7/yYejOwSxKLNKcxdnczr47uZHUlERGpQfFo2by4rvfrtH6M71rmidCEc4pyliIgIhg0bxuTJk4mNjSU2NpbJkyczcuRIOnToUL5deHg4ixYtAsDb25sBAwYwbdo0VqxYwb59+5g7dy6ffPIJY8eOLd++bdu23H333axbt449e/bw6quvsmTJEsaMGWPGW21QypYR+H5rKoez880NIyIiNeaP02+DIwO4tluQ2ZEuikOUJYDPP/+czp07M2TIEIYMGUKXLl349NNPK2yTkJBAVlZW+dfz5s3j0ksv5dZbbyUyMpJZs2bx/PPPc8899wDg6urKjz/+iJ+fH6NGjaJLly588sknfPzxx1xzzTV2fX8NUZdgH3qGNqWoxOCztVpGQESkvnhn+R52pGbj4+nK82M7OdzVb39m6jlL9cX5znnKmb7bksq9X27Gt7Ebqx67CncXZ7MjiYjIRdiRmsW1s1dRbDP4503duLZb3T2p+3z/fjvMyJLUT8M6BRLo7cHRk4V8vyXN7DgiInIRCottPDx/K8U2g6EdAxjd1bGn38qoLImpXJ2diI4KBWDO6n1ooFNExHG9vXw38WnZNPV05bkxjrf45NmoLInpbu7dCncXJ7anZLNh/wmz44iISDVsT8ni7eW7AXjm2k74Nak/V42rLInpmnm5Meb0nPbcVcnmhhERkQtWOv22hWKbwfBOgYzs0sLsSDVKZUnqhEn9wwCI2ZFOauYpc8OIiMgFmb0siV3pOTTzcuPZMY5/9dufqSxJnRAe6E1Um+aU2Aw+WbPf7DgiInKeth3K4u0VewB49tpO+DauP9NvZVSWpM4oW6Tyy3UHOFVYYm4YERE5p4LiEh6ev4USm8GILi0YUc+m38qoLEmdcXVEACHNGpF1qohv4lLMjiMiIufw1q+7ScjIobmXG8+M7njuHRyUypLUGc5OFm6PCgNgziotIyAiUpdtPZTJu7+VTr89N6YTzevh9FsZlSWpU8b1CsHTzZnEjJOs3nPM7DgiIlKJP06/jeoaxPDO9XP6rYzKktQp1kau3NAzGIA5WkZARKRO+ufSJBIzTuLb2I1/1OPptzIqS1Ln3N4vDIBfd2Ww/1iuuWFERKSCuIOZvFc+/daZZl5uJieqfSpLUudc4teYAe39MAz4eLWWERARqSvyi0qn32wGXNstiGGdAs2OZBfVKku5ufrXvtSusmUE5m84yMmCYnPDiIgIAK8vTWT34ZP4NnZnxqj6P/1WplplKSAggDvuuIOVK1fWdB4RAK5o50cbXy9yCor5euMhs+OIiDR4mw6c4IP/7gXghbGdaNoApt/KVKssffnll2RlZXH11VfTvn17Zs2aRWpqak1nkwbMycnCxNOjS3NXJ2OzaRkBERGz5BeVMO309NvY7i0Z0rFhTL+VqVZZGjVqFF9//TWpqan89a9/5csvvyQ0NJSRI0eycOFCios1bSIX7/oewTTxcGHf0Vx+SzxidhwRkQbrtSWJ7DmSi18Td54eFWl2HLu7qBO8mzdvztSpU9myZQuvvfYaS5cu5YYbbiAoKIinnnqKvLy8msopDZCXuwvje4UA8NGqfSanERFpmDbuP8EHv5dOv80c2xkfz4Yz/VbmospSeno6L730EhERETz22GPccMMN/Prrr7z++ussWrSIMWPG1FBMaagmRIVhscDvSUfZfTjH7DgiIg1K2fSbYcB1PVoyKDLA7EimcKnOTgsXLmTOnDn8/PPPREZG8ve//53bbrsNHx+f8m26detG9+7dayqnNFCtmnsyKCKAJTszmLs6mefGdDY7kohIg/HKzwnsPZpLgLc7T49sOFe//Vm1RpYmTZpEUFAQq1atIi4ujilTplQoSgBt2rTh//7v/2oiozRwZcsIfL0xhay8InPDiIg0EBuSj/Ph6VMgZl7XGaunq8mJzFOtkaW0tDQ8PT2r3KZRo0Y8/fTT1Qol8kdRbZoTHtiEXek5fLXhAH+54hKzI4mI1GunCksXnzQMuKFnMFeFN8zptzLVGlkqLi4mOzv7jEdOTg6FhYU1nVEaOIvFwsTTt0D5ePV+SrSMgIhIrXr55wSSj+UR6O3BkyMb3tVvf1atsuTj40PTpk3PePj4+NCoUSNCQ0N5+umnsdlsNZ1XGqgx3VvS1NOVlMxTLNmZYXYcEZF6a92+48xZfXr67frOWBs13Om3MtUqS3PnziUoKIjHH3+cb775hkWLFvH444/TsmVL3n33Xf7yl7/w5ptvMmvWrJrOKw2Uh6szN/duBcAcLSMgIlIr8gqLmbagdPrtxl7BXNnB3+xIdUK1zln6+OOPefXVV7nxxhvLnxs9ejSdO3fm/fff59dff6VVq1Y8//zzPP744zUWVhq26KhQ3v/vXtbuO86O1Cw6BlnNjiQiUq+8FJPA/mN5tLB68ISm38pVa2RpzZo1lS4L0L17d9asWQNA//79OXDgwMWlE/mDFtZG5Xe4/nh1srlhRETqmdi9x5h7+rN11vVd8PbQ9FuZapWl4OBgPvzwwzOe//DDDwkJKV1x+dixYzRt2vTi0on8yR2nlxH4Ji6VYycLzA0jIlJP5BUW88iCrQDcdGkIA9r7mZyobqnWNNwrr7zCuHHj+Omnn7j00kuxWCysX7+eXbt2sWDBAgDWr1/P+PHjazSsSI9WTekSbGXroSy+XHeAKVe1MzuSiIjDe/GnXRw4nkeQ1YP/GxFhdpw6x2IYRrWuw96/fz/vvfceCQkJGIZBeHg4d999N2FhYTUcse7Lzs7GarWSlZWFt7e32XHqvUWbDzH1qy0EeLuz8tGrcHW+qLv2iIg0aKv3HOWWD9YC8Omdvbm8XcMZVTrfv98XPLJUVFTEkCFDeP/995k5c+ZFhRSpjms6t+D5H3aRkV3AT9vTGd01yOxIIiIOKbfgf9Nvt/Rp1aCK0oW44H+Su7q6sn37diwWS23kETkndxdnbuurZQRERC7WrJ92cejEKVr6NOLxazT9djbVmr+YMGFCpSd4i9jLrX1CcXN2YvOBTOIOZpodR0TE4azefZRPY/cD8NINXWjsXq3TmBuEah2ZwsJC/v3vf7NkyRJ69eqFl5dXhe+/9tprNRJO5Gz8mrgzsmsLFm5KYe6qfbxx05lLWYiISOVOFhQz7fT02219W3FZW1+TE9Vt1SpL27dvp0ePHgAkJiZW+J6m58ReJvVrzcJNKfywLY3Hr4nA39vD7EgiIg5h5o/xpGSeIrhpI6YP1/TbuVSrLC1fvrymc4hcsM7BVnqFNmXD/hN8FrufB4d0MDuSiEidtzLpKJ+vLV00+qUbuuCl6bdzuqhrrnfv3s3PP//MqVOnAKjmKgQi1TbpstYAfL72APlFJSanERGp23Lyi3j069LptwlRofS7RNNv56NaZenYsWNcffXVtG/fnmuuuYa0tDQA7rrrLh566KEaDShSlaEdA2hh9eBYbiHfb00zO46ISJ32wunpt5BmjXh0WLjZcRxGtcrS1KlTcXV15cCBA3h6epY/P378eGJiYmosnMi5uDg7ER0VCpQuI6DRTRGRyv038QhfrjsIwMs3dNX02wWoVln65ZdfePHFFwkODq7wfLt27di/f3+NBBM5Xzdf2goPVyd2pGazPvmE2XFEROqc7PwiHjs9/TaxXxh92zQ3OZFjqVZZys3NrTCiVObo0aO4u7tfdCiRC9HUy42x3VsCWqRSRKQyz38fT2pWPqHNPXlkmC6GuVDVKktXXHEFn3zySfnXFosFm83Gyy+/zJVXXllj4UTO18R+pSd6/7wjnZTMUyanERGpO1YkHOarDQexWEqn3zzdNP12oap1xF5++WUGDhzIhg0bKCws5JFHHmHHjh0cP36cVatW1XRGkXPqENiEfpc0Z/WeY3yyJlnrhoiIAFmninjs621A6fRb79bNTE7kmKo1shQZGcnWrVvp3bs3gwcPJjc3l+uuu47NmzdzySWX1HRGkfNStozAvHUHySssNjmNiIj5nvt+J+nZ+YQ19+SRobr6rbqqPRYXGBjIP/7xj5rMInJRrgr3p1UzTw4cz2PR5hRu7RNqdiQREdMs33WY+RsPlU6/jetKIzdnsyM5rGqXpczMTNatW8fhw4ex2WwVvjdhwoSLDiZyoZydLEyICuW5H+KZuyqZW3q30u13RKRBysor4rGFpVe/3XFZay4N0/TbxahWWfruu++49dZbyc3NpUmTJhX+IFksFpUlMc2Nl4bw+pJEkg6fZNXuY/Rvp9VpRaTheeb7nWRkF9Da14uHdSuoi1atc5Yeeugh7rjjDnJycsjMzOTEiRPlj+PHj9d0RpHz5u3hyg09S9f/0jICItIQ/RqfwdebSqffXhnXRdNvNaBaZSklJYX77ruv0rWWRMx2e78wAJYlHCb5aK65YURE7Cgrr4jpC0uvfrurf2t6hmr6rSZUqywNHTqUDRs21HQWkRrRxq8xAzv4YRjw8Zpks+OIiNjNP77bweGcAtr4efGQpt9qTLXOWRoxYgTTpk1j586ddO7cGVdX1wrfHz16dI2EE6muSZe1ZkXCEeZvOMSDg9vTxMP13DuJiDiwJTszWLg5BScLvDKuKx6umn6rKdUqS5MnTwbgmWeeOeN7FouFkpKSi0slcpGuaOfLJX5e7DmSy4KNh8rXYBIRqY8y8wp5fFHp9Nvky9vQo1VTkxPVL9WahrPZbGd9qChJXWCxWJh4uiB9vDoZm80wOZGISO2ZsXgHR3IKuMTPi6mD25sdp965oLJ0zTXXkJWVVf71888/T2ZmZvnXx44dIzIyssbCiVyM67q3pImHC8nH8liReNjsOCIiteLnHel8E5eKkwVevbGbpt9qwQWVpZ9//pmCgoLyr1988cUKSwUUFxeTkJBQc+lELoKXuws3XRoCwJxVyeaGERGpBSdyC/m/RdsB+MsVl9AtxMfcQPXUBZUlwzCq/FqkrpkQFYaTBX5POkpSRo7ZcUREatTTi3dw9GQB7fwb88CgdmbHqbeqdc6SiKMIaebJ4MgAAOauTjY3jIhIDYrZnsbiLak4O1l09Vstu6CyZLFYzrjXlu69JXXdxH6lJ3ov3JRCVl6RyWlERC7e8dxCnvimdPrtngFt6Krpt1p1QUsHGIbBxIkTcXd3ByA/P5977rkHLy8vgArnM4nUFX3bNCM8sAm70nOYt/4Adw+4xOxIIiIX5alvt3P0ZCEdAppw39WafqttFzSydPvtt+Pv74/VasVqtXLbbbcRFBRU/rW/v79uoit1jsVi4Y7Tywh8smY/xSU2kxOJiFTfj9vS+H5rWvn0m7uLpt9q2wWNLM2ZM6e2cojUqtHdgpgVs4uUzFMsjc9gWKcWZkcSEblgx04W8OTp6be/DbyEzsFWkxM1DDrBWxoED1dnbu5duozAR1pGQEQc1FPf7uBYbiHhgU249ypNv9mLypI0GNF9w3BxsrBu33F2pGadewcRkTrk+62p/LDtf9Nvbi76E24vDnOkT5w4QXR0dPn5UdHR0RVWD69MRkYGEydOJCgoCE9PT4YNG0ZSUlKFbQoKCrj33nvx9fXFy8uL0aNHc+jQoVp8J2KWQKsHwzuXTr9pkUoRcSRHcv43/fb3K9vSqaWm3+zJYcrSLbfcQlxcHDExMcTExBAXF0d0dPRZtzcMgzFjxrB3716+/fZbNm/eTGhoKIMGDSI3N7d8uwceeIBFixYxb948Vq5cycmTJxk5cqTucVdPTbosDIDFcakcPamrN0Wk7jMMgye/2c6JvCIiWngz5cq2ZkdqcCyGAyzDHR8fT2RkJLGxsfTp0weA2NhYoqKi2LVrFx06dDhjn8TERDp06MD27dvp2LEjACUlJfj7+/Piiy9y1113kZWVhZ+fH59++injx48HIDU1lZCQEH788UeGDh16Xvmys7OxWq1kZWXh7e1dQ+9aaoNhGIx5exVbDmXx0OD23KtLbkWkjlu8JZX7vtyMi5OFb6dcRscgjSrVlPP9++0QI0tr1qzBarWWFyWAvn37YrVaWb16daX7lK355OHhUf6cs7Mzbm5urFy5EoCNGzdSVFTEkCFDyrcJCgqiU6dOZ31dcWwWi4VJp5cR+DR2P4XFWkZAROquwzn5PPVt6fTblKvaqiiZxCHKUnp6Ov7+/mc87+/vT3p6eqX7hIeHExoayvTp0zlx4gSFhYXMmjWL9PR00tLSyl/Xzc2Npk2bVtg3ICDgrK8LpUUsOzu7wkMcxzWdW+DfxJ3DOQX8tD3N7DgiIpUyDIMnFm0nM6+IyBbe/F3Tb6YxtSzNmDGj/BYqZ3ts2LABqPy2KoZhnPV2K66urnz99dckJibSrFkzPD09WbFiBcOHD8fZueoFvKp6XYCZM2eWn2hutVoJCQm5gHctZnNzceK2vqGATvQWkbpr8ZZUftmZgatz6dVvrs4OMb5RL13QopQ1bcqUKdx0001VbhMWFsbWrVvJyMg443tHjhwhICDgrPv27NmTuLg4srKyKCwsxM/Pjz59+tCrVy8AAgMDKSws5MSJExVGlw4fPky/fv3O+rrTp0/nwQcfLP86OztbhcnB3Ny7FbOX7SbuYCabD5yge6um595JRMRODmfn89S3OwC496p2RAbpfFgzmVqWfH198fX1Ped2UVFRZGVlsW7dOnr37g3A2rVrycrKqrLUlLFaS+d4k5KS2LBhA88++yxQWqZcXV1ZsmQJN954IwBpaWls376dl1566ayv5+7uXn5/PHFMfk3cGdU1iK83HWLOqmSVJRGpMwzD4PFF28k6VUSnlt78daDuZ2k2hxjTi4iIYNiwYUyePJnY2FhiY2OZPHkyI0eOrHAlXHh4OIsWLSr/ev78+axYsaJ8+YDBgwczZsyY8hO6rVYrd955Jw899BC//vormzdv5rbbbqNz584MGjTI7u9T7KtsGYEft6WRnpVvbhgRkdO+iUthabym3+oSh/kv8Pnnn9O5c2eGDBnCkCFD6NKlC59++mmFbRISEsjK+t/KzGlpaURHRxMeHs59991HdHQ0X375ZYV9Xn/9dcaMGcONN97IZZddhqenJ9999905z2sSx9eppZXeYc0othl8vna/2XFERMjIzmfG4p0A3H91O8IDNf1WFzjEOkt1ndZZclw/bkvjb59vormXG6seuwoPV5VkETGHYRjc9fEGft11mM4trSz6Wz9cNKpUq+rVOksitWVIZAAtfRpxLLeQxVtSzY4jIg3Ywk0p/LrrMG7OTrx6Y1cVpTpE/yWkQXNxdiI66n/LCGigVUTMkJ6Vz4zvSq9+u39QO9oHNDE5kfyRypI0eDddGoKHqxPxadms23fc7Dgi0sAYhsH0hVvJyS+ma7CVu69oY3Yk+ROVJWnwfDzdGNs9GNAilSJifws2HmJ5whHcnJ14ZZym3+oi/RcR4X/LCPyyM52Dx/PMDSMiDUZa1ime+a706repg9vTTtNvdZLKkgjQPqAJ/dv6YjNKb7ArIlLbDMPgsa+3kVNQTLcQHyZf3trsSHIWKksip03sFwbAvHUHyCssNjeMiNR78zcc4rfEI7i5aPqtrtN/GZHTrgr3J7S5J9n5xSzclGJ2HBGpx1IzT/Hs96XTbw8Nbk9b/8YmJ5KqqCyJnObkZOH2qDAA5q7WMgIiUjsMw+DRr7eSU1BM91Y+3HW5rn6r61SWRP5gXK9gvNyc2X34JCt3HzU7jojUQ/PWH+T3pKO4n55+c3aymB1JzkFlSeQPmni4Mq5XCKBlBESk5qVknuL5H+IBmDa0A5f4afrNEagsifzJ7f3CsFhg2a7D7Duaa3YcEaknDMPg0QVbOVlQTK/Qpky6TFe/OQqVJZE/ae3rxZUd/AH4eHWyuWFEpN74Yt0BVu4unX576YYumn5zICpLIpUoW6Ry/oaD5OQXmRtGRBzeweN5vHB6+u2RYeG00fSbQ1FZEqlE/7a+tPVvTG5hCfM3HDI7jog4MJut9Oq33MISLg1ryqTTa7qJ41BZEqmExWIpX6Ty4zXJlNi0jICIVM/n6w6wes8xPFydePmGrjhp+s3hqCyJnMV1PVri7eHC/mN5LN912Ow4IuKADh7PY+aPpdNvjw4LJ8zXy+REUh0qSyJn4enmws29WwGli1SKiFwIm81g2oIt5BWW0Lt1s/JFb8XxqCyJVCE6KhQnC6zcfZTEjByz44iIA/ls7X5i9x6nkaszL9/QRdNvDkxlSaQKwU09GRIZCGiRShE5fweO5THzx10APDY8nNDmmn5zZCpLIudQtozAos2HyMwrNDeMiNR5NpvBwwu2cKqohL5tmhHdN9TsSHKRVJZEzqF362ZEtvAmv8jGvPUHzY4jInXcJ2uSWbfvOJ5uzrx0va5+qw9UlkTOwWKxMPH06NInq5MpLrGZG0hE6qzko7m8GJMAwPTh4bRq7mlyIqkJKksi52F01yCae7mRmpXPLzszzI4jInWQzWbwyIKtnCoqIapNc27to+m3+kJlSeQ8eLg6c0uf0mUE5qzaZ3IaEamL5q5OZl3ycbzcnHlJV7/VKypLIufptr6huDhZWJ98gu0pWWbHEZE6ZN/RXF76ufTqt+nXRBDSTNNv9YnKksh5CvD24JrOLQAtIyAi/1NiM5g2fwv5RTb6t/Xl1tOj0FJ/qCyJXICyZQS+25LKkZwCc8OISJ0wZ9U+Nuw/QWN3F2Zd3xmLRdNv9Y3KksgF6N6qKd1CfCgssfHF2gNmxxERk+05cpKXfy69+u3xayIIbqrpt/pIZUnkApWNLn22dj+FxVpGQKShKpt+Kyi2cXk7X27uHWJ2JKklKksiF2h4pxb4N3HnSE4BP25LMzuOiJjko5X72HQg8/T0WxdNv9VjKksiF8jNxan89gVzVu3DMAyTE4mIve0+fJKXfymdfntiRAQtfRqZnEhqk8qSSDXc0qcVbi5ObDmUxeaDmWbHERE7KrEZTFuwhcJiG1e092P8pZp+q+9UlkSqoXljd67tGgRoGQGRhubfv+9l84FMmri78KKufmsQVJZEqqnsfnE/bUsjPSvf3DAiYhe7D+fw6pJEAJ4cFUkLq6bfGgKVJZFq6hhkpXfrZhTbDD6NTTY7jojUsuISGw/N30phsY0rO/gxrmew2ZHETlSWRC7CHadHl75Ye4D8ohJzw4hIrfrX73vZcjCTJh4uzLxOV781JCpLIhdhUEQALX0acSKviMVxqWbHEZFakpiRwxtLkgB4elRHAq0eJicSe1JZErkILs5OTIgqXUbgIy0jIFIvFZfYeHj+FgpLbFwV7s/1PVqaHUnsTGVJ5CLddGkrGrk6sys9h9i9x82OIyI17P3/7mXroSy8PVyYeZ2ufmuIVJZELpLV05XrTv9Lc+7qfSanEZGalJCewxtLS69+mzG6IwHemn5riFSWRGrAxH5hACzZmcHB43nmhhGRGlF0evqtqMRgUIQ/Y7tr+q2hUlkSqQHtAppweTtfbAZ8sibZ7DgiUgPeW7GHbSlZWBu58sJYTb81ZCpLIjVk0ullBOatP0huQbG5YUTkosSnZfPmstKr3/4xuiP+mn5r0FSWRGrIwPb+hDX3JCe/mIWbU8yOIyLV9Mfpt8GRAVzbLcjsSGIylSWRGuLkZOH20+cuzV21D5tNywiIOKJ3lu9hR2o2Pp6uPD+2k6bfRGVJpCbd0DOYxu4u7DmSy++7j5odR0Qu0I7ULN764/RbE02/icqSSI1q4uHKuF6l94uas0rLCIg4ksJiGw/P30qxzWBoxwBGd9X0m5RSWRKpYbdHhWGxwIqEI+w9ctLsOCJynt5evpv4tGyaerry3Bhd/Sb/o7IkUsPCfL24qoM/AB+vTjY3jIicl+0pWby9fDcAz1zbCb8m7iYnkrpEZUmkFky6rDUACzYeIju/yOQ0IlKV0um3LRTbDIZ3CmRklxZmR5I6RmVJpBZc1rY57QMak1tYwn/WHzQ7johUYfayJHal59DMy41nx+jqNzmTypJILbBYLEzsVzq69PGaZPKLSkxOJCKV2Z6Sxdsr9gDw7LWd8G2s6Tc5k8qSSC0Z270lPp6uHDx+ilFvrWTLwUyzI4nIHxQUl/DQf7ZQYjMY0aUFIzT9JmehsiRSSxq5OTP75h74NnYn6fBJrnt3NS/F7KKgWKNMInXBW7/uJiEjh+ZebjwzuqPZcaQOU1kSqUX92/myZOoVjO4aRInN4J0Vexj11kq2Hso0O5pIg7b1UCbv/lY6/fbcmE401/SbVEFlSaSWNfVy482bu/PebT3wbexGYsZJxr6zmld+TtAok4gJCopLeHh+6fTbqK5BDO+s6TepmsqSiJ0M69SCX6YOYGSXFpTYDGYv383ot1axPSXL7GgiDco/lyaRmHES38Zu/EPTb3IeVJZE7KiZlxuzb+nBu7f2oLmXGwkZOVz79ipe+yWBwmKb2fFE6r24g5m8Vz791plmXm4mJxJHoLIkYoLhnVvwy9QrGNG5dJTpzWW7GT17pUaZRGpRflHp9JvNgGu7BTGsU6DZkcRBqCyJmKR5Y3fevrUHb9/Sg2ZebuxKz2HM26t4bUmiRplEasEbS5PYffgkvo3dmTFK029y/lSWREw2okvpKNPwToEU2wze/DWJa99exc7UbLOjidQbmw6c4F//LZ1+e2FsJ5pq+k0ugMqSSB3g29idd27twVs3d6eppyvxadmMnr2SN5YmUlSiUSaRi5FfVMK009NvY7u3ZEhHTb/JhXGYsnTixAmio6OxWq1YrVaio6PJzMyscp+MjAwmTpxIUFAQnp6eDBs2jKSkpPLvHz9+nHvvvZcOHTrg6elJq1atuO+++8jK0nkjYn8Wi4VRXYP4ZeoAhnUsHWV6Y2kSY95eRXyaRplEquu1JYnsOZKLXxN3nh4VaXYccUAOU5ZuueUW4uLiiImJISYmhri4OKKjo8+6vWEYjBkzhr179/Ltt9+yefNmQkNDGTRoELm5uQCkpqaSmprKK6+8wrZt25g7dy4xMTHceeed9npbImfwa+LOu7f14M2bu+Pj6cqO1NJRpjd/TdIok8gFKCy28e/f9/Lv3/cCMHNsZ3w8Nf0mF85iGIZhdohziY+PJzIyktjYWPr06QNAbGwsUVFR7Nq1iw4dOpyxT2JiIh06dGD79u107Fh6Il9JSQn+/v68+OKL3HXXXZX+rPnz53PbbbeRm5uLi4vLeeXLzs7GarWSlZWFt7d3Nd+lyJkO5+TzxKLt/LIzA4BOLb15ZVxXwgP1eyZyNoZhsGRnBjN/2sW+o6X/OL6xVzAv3dDV5GRS15zv32+HGFlas2YNVqu1vCgB9O3bF6vVyurVqyvdp6CgAAAPD4/y55ydnXFzc2PlypVn/VllB+x8i5JIbfJv4sH70T35503dsDZyZXtKNqPeWsnsZUkUa5RJ5Aw7UrO45YO1/OXTjew7motvY3dmXdeZmdd1MTuaODCHaATp6en4+/uf8by/vz/p6emV7hMeHk5oaCjTp0/n/fffx8vLi9dee4309HTS0tIq3efYsWM8++yz3H333VXmKSgoKC9jUNpMRWqLxWLh2m4tiWrTnMcXbWdpfAav/JLIzzsyeGVcVzoENjE7oojpDmfn8+ovifxn40EMA9xcnLirf2v+dmVbGrs7xJ86qcNMHVmaMWMGFoulyseGDRuA0j8Yf2YYRqXPA7i6uvL111+TmJhIs2bN8PT0ZMWKFQwfPhxnZ+czts/OzmbEiBFERkby9NNPV5l75syZ5SeaW61WQkJCqvHuRS6Mv7cHH0zoyevju2Jt5Mq2lCxGvbWSt5fv1iiTNFj5RSXMXpbEwFdW8NWG0qI0sksLfn1wAI8MC1dRkhph6jlLR48e5ejRo1VuExYWxhdffMGDDz54xtVvPj4+vP7660yaNKnK18jKyqKwsBA/Pz/69OlDr169ePvtt8u/n5OTw9ChQ/H09OT777+vMHVXmcpGlkJCQnTOktjN4ex8Hl+0jaXxhwHoGmzllXFdaRegUSZpGAzDYPGWVF6KSSAl8xQAXUN8eGpkBD1Dm5mcThzF+Z6z5FAneK9du5bevXsDsHbtWvr27XvWE7wrk5SURHh4OD/99BNDhgwBSg/U0KFDcXd358cff8TT0/OC8+kEbzGDYRgs3JTCP77bQXZ+MW7OTkwd3J7Jl7fGxdkhTkcUqZZNB07w7Pc72XwgE4AgqwePDg9nVJcgnJwqn20QqUy9KksAw4cPJzU1lffffx+Av/zlL4SGhvLdd9+VbxMeHs7MmTMZO3YsUHplm5+fH61atWLbtm3cf//99OzZk6+//hooHVEaPHgweXl5LFq0CC8vr/LX8vPzq3S6rjIqS2Km9KzSUaZlu06PMoX48Oq4LrT11yiT1C8pmad48addLN6SCoCnmzN/HXAJd13ehkZu5/d5LfJH5/v322Emcz///HPuu+++8hGh0aNHM3v27ArbJCQkVFhQMi0tjQcffJCMjAxatGjBhAkTePLJJ8u/v3HjRtauXQtA27ZtK7zWvn37CAsLq6V3I1JzAq0efHh7LxZsPMQz3+9ky8FMrnlzJQ8Obs/ky9vgrH9pi4PLLSjm3RV7+OD3vRQU27BY4IYewTw8tAMB3lWfNiFSExxmZKku08iS1BXpWfk8tnArKxKOANC9lQ8v39CVtv6NTU4mcuFKbAYLNh7klV8SOZJTep5on9bNeHJkJJ1aWk1OJ/VBvZuGq8tUlqQuMQyD+RsO8ez3O8kpKMbNxYmHh7Tnzv4aZRLHsXrPUZ77Pp6dp2/1E9rck8eviWBIZMBZr4IWuVAqS3aksiR1UWrmKR5buI3/JpaOMvVo5cPL47pyiZ9GmaTu2nc0lxd+jGfJ6VXrm3i4cP/V7ZgQFYabiy5ckJqlsmRHKktSVxmGwX82HOTZ7+M5WVCMu4sT04Z2YNJlrTXKJHVKVl4Rby5L4pM1yRSVGDg7Wbi1TyseGNSeZl66n5vUDpUlO1JZkrouJfMUj329ld+TStc16xXalJdu6EIbjTKJyYpKbHweu583fk0iM68IgIEd/Pi/ayK0bpjUOpUlO1JZEkdgGAbz1h/k+R80yiTmMwyD5QmHef6HePYcKb3ZbTv/xjwxMpIB7f1MTicNhcqSHaksiSNJyTzFowu2snJ36SjTpWFNefmGroT5ep1jT5GakZCew3M/7Cwf6Wzm5caDg9tz06UhWlBV7EplyY5UlsTRGIbBF+sO8MIP8eQWluDh6sQjQ8OZ2C9MKyBLrTl6soDXliQyb90BbAa4OTsx6bIw/n5VW7w9XM2OJw2QypIdqSyJozp4PI/HFm5l1e5jAPRu3YyXb+hCaHONMknNKSguYc6qZN5etpucgmIAhncK5LHh4fpdE1OpLNmRypI4MsMw+HztAV74MZ68whIauTrz6LAOTIjSKJNcHMMw+Gl7OjN/iufg8dKb3XZuaeWJERH0adPc5HQiKkt2pbIk9cHB43k8smAra/aWjjL1ad2Ml2/oSqvmF35zaZGthzJ59vudrE8+AUCAtzvThoZzXfeWKuFSZ6gs2ZHKktQXNpvB52v388KPuzhVVIKnmzOPDQ/ntj6h+gMn5yUt6xQvxySwcHMKAB6uTvzliku4Z0AbPN0c5nak0kCoLNmRypLUNweO5TFtwRbW7jsOQN82paNMIc00yiSVyyss5v3f9vL+f/eQX2QD4LruLZk2rAMtrI1MTidSOZUlO1JZkvrIZjP4NHY/s3763yjT9GsiuLV3K40ySTmbzWDR5hRe/jmB9Ox8oHTR0ydHRtI1xMfccCLnoLJkRypLUp/tP5bLtPlbWZdcOsrU75LmvHh9F40yCev2Hee5H3ay9VAWAMFNGzF9eATXdA7UzW7FIags2ZHKktR3NpvBx2uSeTFmF/lFNrzcnHl8RAS39G6lP4oN0IFjecyKiefHbekANHZ34e9XtmXSZWF4uDqbnE7k/Kks2ZHKkjQUyUdzmbZgS/kVTv3b+jLr+s4EN9UoU0OQnV/E28t2M2dVMoUlNpwscFPvVjw4uD2+jd3NjidywVSW7EhlSRoSm81gzupkXv65dJSpsbsLj18Twc29QzTKVE8Vl9iYt/4gry9J5FhuIQCXt/Pl/0ZEEB6ozzxxXCpLdqSyJA3RvqO5TJu/hQ37S0eZLm/ny6zru9DSR1c+1Sf/TTzCcz/sJDHjJABt/Lx4YkQEV3bwVzkWh6eyZEcqS9JQldgM5qzax8s/J1BQXDrK9MSICMZfqlEmR7f7cA7P/xDP8oQjAPh4uvLA1e24tW8orrrZrdQTKkt2pLIkDd2eIyeZNn8Lmw5kAnBFez9mXdeZII0yOZzjuYW8sTSRz9ceoMRm4OJkYUJUGPdf3Q6rp252K/WLypIdqSyJlI4yfbhyL6/8kkhhsY0m7i48OTKScb2CNcrkAAqLbXyyJpk3f00iO7/0ZreDIwOYPjycNn6NTU4nUjtUluxIZUnkf3YfPsm0BVvYfHqUaWAHP2Ze11mrONdRhmHwy84MZv4YT/KxPAAiWnjz5IgI+rX1NTmdSO1SWbIjlSWRikpsBv/+fS+vLjk9yuRxepSpp0aZ6pIdqVk8+/1OYveWLjjq29idaUPbc0PPEJy1Srs0ACpLdqSyJFK53YdzeGj+VrYczATgyg5+zLyuC4FWD3ODNXCHs/N55ZcE5m88hGGAm4sTky9vzV8HtqWxu252Kw2HypIdqSyJnF1xiY0Pft/H60sSKSyx4e3hwlOjOnJ9j5YaZbKz/KIS/v37Xt5ZsYe8whIARnUN4tFhHbSwqDRIKkt2pLIkcm5JGTk8PH8LW07fR+zqcH9euK4zAd4aZapthmGweEsqL/60i9Ss0pvddgvx4cmRkfQMbWpyOhHzqCzZkcqSyPkpLrHx/n/38s+lSeWjTDNGd2Rsd40y1ZaN+0/w7Pc7iTs9FRpk9eDR4eGM7hqkYy4NnsqSHaksiVyYhPTSUaZtKaWjTIMiAnhhbCf8NcpUYw6dyOPFmAS+25IKgKebM38beAl3Xd5GN7sVOU1lyY5UlkQuXNko0xtLEykqMbA2cuUfoztybTeNeFyMkwXFvLtiN//+fR8FxTYsFhjXM5iHh3RQGRX5E5UlO1JZEqm+XenZPDx/C9tTsoHShRCfH9sJ/yb6w34hSmwG8zcc5JVfEjl6sgCAvm2a8cSISDq1tJqcTqRuUlmyI5UlkYtTVGLjvRV7eHNZEkUlBj6epaNMOq/m/KzefZRnf4gnPq20cIY19+TxayIYHBmg4ydSBZUlO1JZEqkZ8WnZPPSfLew8/Ud/aMcAnhvTGb8m7iYnq5v2HjnJCz/uYml8BgDeHi7cd3U7JkSF4eaim92KnIvKkh2pLInUnKISG+8s38Nby5Iothk09XTlH9d2YlSXFholOS0rr4h//prEJ2uSKbYZODtZuK1PK+4f1J5mXm5mxxNxGCpLdqSyJFLzdqaWnstUNso0vFMgz47phG/jhjvKVFRi4/PY/bzxaxKZeUVA6aro/zcigrb+TUxOJ+J4VJbsSGVJpHYUFtt4e/lu3l6+m2KbQTMvN565tiMjuwSZHc2uDMNgecJhnv8hnj1HcgFoH9CYJ0ZEckV7P5PTiTgulSU7UlkSqV3bU7J4eP4WdqXnAHBN50CevbYTzRvAKNOu9Gye+z6elbuPAtDcy40Hh7RnfK8QXJx1XpLIxVBZsiOVJZHaV1hsY/ayJN5esYcSm0FzLzeeHdOJazq3MDtarTh6soBXf0nkq/UHsBng5uzEpP5h/P3Ktnh7uJodT6ReUFmyI5UlEfv58yjTiC4tePbaTvXmxOb8ohLmrErm7eW7OVlQDJSOpD02LIJWzXWzW5GapLJkRypLIvZVUFzCW7/u5t3f/jfK9NyYTgx34FEmwzD4cVs6M3+K59CJUwB0CbbyxIhIerduZnI6kfpJZcmOVJZEzLH1UCYPz99CYsZJAEZ1DeKZ0R1p6mCjTFsOZvLcDztZn3wCgEBvDx4Z1oEx3Vri5KTlEkRqi8qSHaksiZinoLiEN39N4t0Ve7AZ4NvYjefGdGZYp0Czo51TWtYpXo5JYOHmFAAauTpz94A2/OWKNni6uZicTqT+U1myI5UlEfNtOVg6ypR0uHSU6dpuQcwYVTdHmfIKi3nvt7386797yC+yAXBdj5Y8MjScQKvuiSdiLypLdqSyJFI35BeV8M9fk3j/t7JRJndeGNuJIR3rxiiTzWawcHMKL/+8i4zs0pvdXhrWlCdHRtIl2MfccCINkMqSHaksidQtcQczeeg/ceULOI7t3pKnR0Xi42neKNO6fcd59vudbEvJAiCkWSOmD49geKdA3cZFxCQqS3aksiRS9+QXlfD60kQ++O9ebAb4NXFn5tjODIoMsGuOA8fymPlTPD9tTwegibsLU65qy+39wvBwdbZrFhGpSGXJjlSWROquTQdOMG3+lvJRpuu6t+TpUR2xetbuwo7Z+UXMXrabuauSKSyx4WSBm3u3Yurg9g36/nYidYnKkh2pLInUbflFJby+JJF//b4Xw4AAb3dmXteZq8JrfpSpuMTGl+sP8vqSRI7nFgJweTtfnhgRSYdA3exWpC5RWbIjlSURx7Bxf+ko096jpaNM1/cI5qlRkVgb1cwo02+JR3j+h53l6z5d4ufFEyMiGdjBT+clidRBKkt2pLIk4jjyi0p49ZcE/r1yX/ko06zrunBluH+1X3P34Rye+yGeFQlHAPDxdGXqoPbc0qcVrrrZrUidpbJkRypLIo5nQ/Jxpi3Yyr7To0zjegbzxMgLG2U6nlvIG0sT+XztAUpsBq7OFiZEhXHfVe1q/ZwoEbl4Kkt2pLIk4phOFZbwyi8JfLSqdJQp0NuDWdd3ZmCHqkeZCottfLImmX/+mkROfunNbodEBjD9mgha+3rZI7qI1ACVJTtSWRJxbOuTjzNt/haSj+UBML5XCP83MgJvj4qjQ4Zh8POODGb+FM/+09tGtvDmiZER9LvE1+65ReTiqCzZkcqSiOM7VVjCSz/vYu7qZAwDWlg9ePH6LlzR3g+A7SlZPPfDTmL3HgdK122aNqQD1/cMxlk3uxVxSCpLdqSyJFJ/rN17jGkLtnLgeOnI0U2XhlBiM1iw6RCGAe4uTky+vA33DLyExu662a2II1NZsiOVJZH6Ja+wmJdiEpi7OrnC89d2C+KRYeG09GlkTjARqVHn+/db/ywSEfkTTzcXZozuyLBOgTz97Q6snq48NjycHq2amh1NREygkaUaoJElERERx3O+f7+1WpqIiIhIFVSWRERERKqgsiQiIiJSBZUlERERkSqoLImIiIhUQWVJREREpAoOU5ZOnDhBdHQ0VqsVq9VKdHQ0mZmZVe6TkZHBxIkTCQoKwtPTk2HDhpGUlFTptoZhMHz4cCwWC998803NvwERERFxSA5Tlm655Rbi4uKIiYkhJiaGuLg4oqOjz7q9YRiMGTOGvXv38u2337J582ZCQ0MZNGgQubm5Z2z/xhtvYLHo/k4iIiJSkUOs4B0fH09MTAyxsbH06dMHgA8++ICoqCgSEhLo0KHDGfskJSURGxvL9u3b6dixIwDvvPMO/v7+fPnll9x1113l227ZsoXXXnuN9evX06JFC/u8KREREXEIDjGytGbNGqxWa3lRAujbty9Wq5XVq1dXuk9BQQEAHh4e5c85Ozvj5ubGypUry5/Ly8vj5ptvZvbs2QQGBtbSOxARERFH5RBlKT09HX9//zOe9/f3Jz09vdJ9wsPDCQ0NZfr06Zw4cYLCwkJmzZpFeno6aWlp5dtNnTqVfv36ce211553noKCArKzsys8REREpH4ytSzNmDEDi8VS5WPDhg0AlZ5PZBjGWc8zcnV15euvvyYxMZFmzZrh6enJihUrGD58OM7OzgAsXryYZcuW8cYbb1xQ7pkzZ5afaG61WgkJCbmwNy4iIiIOw9RzlqZMmcJNN91U5TZhYWFs3bqVjIyMM7535MgRAgICzrpvz549iYuLIysri8LCQvz8/OjTpw+9evUCYNmyZezZswcfH58K+11//fVcfvnlrFixotLXnT59Og8++GD519nZ2SpMIiIi9ZTFMAzD7BDnEh8fT2RkJGvXrqV3794ArF27lr59+7Jr165KT/CuTFJSEuHh4fz0008MGTKE9PR0jh49WmGbzp07889//pNRo0bRunXr83rd871rsYiIiNQd5/v32yGuhouIiGDYsGFMnjyZ999/H4C//OUvjBw5skJRCg8PZ+bMmYwdOxaA+fPn4+fnR6tWrdi2bRv3338/Y8aMYciQIQAEBgZWelJ3q1atzrsoQel0IKBzl0RERBxI2d/tc40bOURZAvj888+57777yovO6NGjmT17doVtEhISyMrKKv86LS2NBx98kIyMDFq0aMGECRN48sknazxbTk4OgKbiREREHFBOTg5Wq/Ws33eIabi6zmazkZqaSpMmTerEwpZl51AdPHhQ04LoePyZjseZdEwq0vGoSMejovp0PAzDICcnh6CgIJyczn7Nm8OMLNVlTk5OBAcHmx3jDN7e3g7/i1yTdDwq0vE4k45JRToeFel4VFRfjkdVI0plHGKdJRERERGzqCyJiIiIVEFlqR5yd3fn6aefxt3d3ewodYKOR0U6HmfSMalIx6MiHY+KGuLx0AneIiIiIlXQyJKIiIhIFVSWRERERKqgsiQiIiJSBZUlB5aSksJtt91G8+bN8fT0pFu3bmzcuLH8+4ZhMGPGDIKCgmjUqBEDBw5kx44dJiauXVUdj6KiIh599FE6d+6Ml5cXQUFBTJgwgdTUVJNT165z/Y780d13343FYuGNN96wb0g7Op/jER8fz+jRo7FarTRp0oS+ffty4MABkxLXrnMdj5MnTzJlyhSCg4Np1KgRERERvPvuuyYmrj1hYWFYLJYzHn//+9+Bhvd5WtXxaIifpypLDurEiRNcdtlluLq68tNPP7Fz505effVVfHx8yrd56aWXeO2115g9ezbr168nMDCQwYMHl9+epT451/HIy8tj06ZNPPnkk2zatImFCxeSmJjI6NGjzQ1ei87nd6TMN998w9q1awkKCrJ/UDs5n+OxZ88e+vfvT3h4OCtWrGDLli08+eSTeHh4mBe8lpzP8Zg6dSoxMTF89tlnxMfHM3XqVO69916+/fZb84LXkvXr15OWllb+WLJkCQDjxo0DGtbnKVR9PBri5ymGOKRHH33U6N+//1m/b7PZjMDAQGPWrFnlz+Xn5xtWq9V477337BHRrs51PCqzbt06AzD2799fS6nMdb7H5NChQ0bLli2N7du3G6Ghocbrr79e++FMcD7HY/z48cZtt91mp0TmOp/j0bFjR+OZZ56p8FyPHj2MJ554ojaj1Qn333+/cckllxg2m63BfZ5W5o/HozL1/fNUI0sOavHixfTq1Ytx48bh7+9P9+7d+eCDD8q/v2/fPtLT08tvPAyla2MMGDCA1atXmxG5Vp3reFQmKysLi8VS6UhLfXA+x8RmsxEdHc20adPo2LGjSUnt41zHw2az8cMPP9C+fXuGDh2Kv78/ffr04ZtvvjEvdC06n9+P/v37s3jxYlJSUjAMg+XLl5OYmMjQoUNNSm0fhYWFfPbZZ9xxxx1YLJYG93n6Z38+HpWp75+nGllyUO7u7oa7u7sxffp0Y9OmTcZ7771neHh4GB9//LFhGIaxatUqAzBSUlIq7Dd58mRjyJAhZkSuVec6Hn926tQpo2fPnsatt95q56T2cz7H5IUXXjAGDx5c/q/F+jyydK7jkZaWZgCGp6en8dprrxmbN282Zs6caVgsFmPFihUmp6955/P7UVBQYEyYMMEADBcXF8PNzc345JNPTExtH1999ZXh7Oxc/vnZ0D5P/+zPx+PPGsLnqcqSg3J1dTWioqIqPHfvvfcaffv2NQzjf//jTk1NrbDNXXfdZQwdOtRuOe3lXMfjjwoLC41rr73W6N69u5GVlWWviHZ3rmOyYcMGIyAgoMIHYH0uS+c6HikpKQZg3HzzzRW2GTVqlHHTTTfZLae9nM//Zl5++WWjffv2xuLFi40tW7YYb731ltG4cWNjyZIl9o5rV0OGDDFGjhxZ/nVD+zz9sz8fjz9qKJ+nmoZzUC1atCAyMrLCcxEREeVX7QQGBgKQnp5eYZvDhw8TEBBgn5B2dK7jUaaoqIgbb7yRffv2sWTJknpxx+yzOdcx+f333zl8+DCtWrXCxcUFFxcX9u/fz0MPPURYWJgJiWvXuY6Hr68vLi4u5/V7VB+c63icOnWKxx9/nNdee41Ro0bRpUsXpkyZwvjx43nllVfMiGwX+/fvZ+nSpdx1113lzzW0z9M/qux4lGlIn6cqSw7qsssuIyEhocJziYmJhIaGAtC6dWsCAwPLr2CA0nnn3377jX79+tk1qz2c63jA//6HnZSUxNKlS2nevLm9Y9rVuY5JdHQ0W7duJS4urvwRFBTEtGnT+Pnnn82IXKvOdTzc3Ny49NJLz/l7VF+c63gUFRVRVFSEk1PFPxPOzs7YbDa75bS3OXPm4O/vz4gRI8qfa2ifp39U2fGAhvd5qmk4B7Vu3TrDxcXFeP75542kpCTj888/Nzw9PY3PPvusfJtZs2YZVqvVWLhwobFt2zbj5ptvNlq0aGFkZ2ebmLx2nOt4FBUVGaNHjzaCg4ONuLg4Iy0trfxRUFBgcvracT6/I39Wn6fhzud4LFy40HB1dTX+9a9/GUlJScZbb71lODs7G7///ruJyWvH+RyPAQMGGB07djSWL19u7N2715gzZ47h4eFhvPPOOyYmrz0lJSVGq1atjEcfffSM7zWkz9MyZzseDfHzVGXJgX333XdGp06dDHd3dyM8PNz417/+VeH7NpvNePrpp43AwEDD3d3duOKKK4xt27aZlLb2VXU89u3bZwCVPpYvX25e6Fp2rt+RP6vPZckwzu94fPjhh0bbtm0NDw8Po2vXrsY333xjQlL7ONfxSEtLMyZOnGgEBQUZHh4eRocOHYxXX331rJePO7qff/7ZAIyEhIQzvtfQPk8N4+zHoyF+nloMwzDMGNESERERcQQ6Z0lERESkCipLIiIiIlVQWRIRERGpgsqSiIiISBVUlkRERESqoLIkIiIiUgWVJREREZEqqCyJiIiIVEFlSUQatLCwMN544w2zY4hIHaayJCIOa9SoUQwaNKjS761ZswaLxcKmTZvsnEpE6huVJRFxWHfeeSfLli1j//79Z3zvo48+olu3bvTo0cOEZCJSn6gsiYjDGjlyJP7+/sydO7fC83l5eXz11VfceeedfP3113Ts2BF3d3fCwsJ49dVXz/p6ycnJWCwW4uLiyp/LzMzEYrGwYsUKAFasWIHFYuHnn3+me/fuNGrUiKuuuorDhw/z008/ERERgbe3NzfffDN5eXnlr2MYBi+99BJt2rShUaNGdO3alQULFtTk4RCRWqKyJCIOy8XFhQkTJjB37lz+eE/w+fPnU1hYSFRUFDfeeCM33XQT27ZtY8aMGTz55JNnlKvqmDFjBrNnz2b16tUcPHiQG2+8kTfeeIMvvviCH374gSVLlvDWW2+Vb//EE08wZ84c3n33XXbs2MHUqVO57bbb+O233y46i4jULovxx08YEREHs2vXLiIiIli2bBlXXnklAAMGDKBly5ZYLBaOHDnCL7/8Ur79I488wg8//MCOHTuA0hO8H3jgAR544AGSk5Np3bo1mzdvplu3bkDpyFLTpk1Zvnw5AwcOZMWKFVx55ZUsXbqUq6++GoBZs2Yxffp09uzZQ5s2bQC45557SE5OJiYmhtzcXHx9fVm2bBlRUVHlWe666y7y8vL44osv7HGoRKSaNLIkIg4tPDycfv368dFHHwGwZ88efv/9d+644w7i4+O57LLLKmx/2WWXkZSURElJyUX93C5dupT//wEBAXh6epYXpbLnDh8+DMDOnTvJz89n8ODBNG7cuPzxySefsGfPnovKISK1z8XsACIiF+vOO+9kypQpvP3228yZM4fQ0FCuvvpqDMPAYrFU2LaqwXQnJ6cztikqKqp0W1dX1/L/32KxVPi67DmbzQZQ/n9/+OEHWrZsWWE7d3f3c709ETGZRpZExOHdeOONODs788UXX/Dxxx8zadIkLBYLkZGRrFy5ssK2q1evpn379jg7O5/xOn5+fgCkpaWVP/fHk72rKzIyEnd3dw4cOEDbtm0rPEJCQi769UWkdmlkSUQcXuPGjRk/fjyPP/44WVlZTJw4EYCHHnqISy+9lGeffZbx48ezZs0aZs+ezTvvvFPp6zRq1Ii+ffsya9YswsLCOHr0KE888cRF52vSpAkPP/wwU6dOxWaz0b9/f7Kzs1m9ejWNGzfm9ttvv+ifISK1RyNLIlIv3HnnnZw4cYJBgwbRqlUrAHr06MF//vMf5s2bR6dOnXjqqad45plnystUZT766COKioro1asX999/P88991yN5Hv22Wd56qmnmDlzJhEREQwdOpTvvvuO1q1b18jri0jt0dVwIiIiIlXQyJKIiIhIFVSWRERERKqgsiQiIiJSBZUlERERkSqoLImIiIhUQWVJREREpAoqSyIiIiJVUFkSERERqYLKkoiIiEgVVJZEREREqqCyJCIiIlIFlSURERGRKvw/FsCLm/9axZsAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "delayed_object_lst[-1].pull()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": "## Load Workflow with pyiron_workflow\n\nFinally, the same JSON is loaded into a `pyiron_workflow` `Workflow`; nodes become graph nodes reachable via attribute access (e.g. `wf.get_bulk_structure`). The lattice constant `a` is overridden again before drawing the graph with `.draw()` and executing it with `.run()`." + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from python_workflow_definition.pyiron_workflow import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wf = load_workflow_json(file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wf.get_bulk_structure.inputs.a.value = 4.05" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "clusterjobflow_qe\n", + "\n", + "jobflow_qe: Workflow\n", + "\n", + "clusterjobflow_qeInputs\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "Inputs\n", + "\n", + "\n", + "clusterjobflow_qeOutputsWithInjection\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "OutputsWithInjection\n", + "\n", + "\n", + "clusterjobflow_qeget_bulk_structure\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "get_bulk_structure: get_bulk_structure\n", + "\n", + "\n", + "clusterjobflow_qeget_bulk_structureInputs\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "Inputs\n", + "\n", + "\n", + "clusterjobflow_qeget_bulk_structureOutputsWithInjection\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "OutputsWithInjection\n", + "\n", + "\n", + "clusterjobflow_qecalculate_qe_0\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "calculate_qe_0: calculate_qe\n", + "\n", + "\n", + "clusterjobflow_qecalculate_qe_0Inputs\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "Inputs\n", + "\n", + "\n", + "clusterjobflow_qecalculate_qe_0OutputsWithInjection\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "OutputsWithInjection\n", + "\n", + "\n", + "clusterjobflow_qegenerate_structures\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "generate_structures: generate_structures\n", + "\n", + "\n", + "clusterjobflow_qegenerate_structuresInputs\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "Inputs\n", + "\n", + "\n", + "clusterjobflow_qegenerate_structuresOutputsWithInjection\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "OutputsWithInjection\n", + "\n", + "\n", + "clusterjobflow_qecalculate_qe_1\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "calculate_qe_1: calculate_qe\n", + "\n", + "\n", + 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mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02738] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02748] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02758] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02768] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02778] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "data": { + "text/plain": [ + "{'plot_energy_volume_curve__plot_energy_volume_curve': None}" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "wf.run()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.8" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} \ No newline at end of file diff --git a/_sources/example_workflows/quantum_espresso/pyiron_base.ipynb b/_sources/example_workflows/quantum_espresso/pyiron_base.ipynb new file mode 100644 index 00000000..1369193c --- /dev/null +++ b/_sources/example_workflows/quantum_espresso/pyiron_base.ipynb @@ -0,0 +1,5001 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "be2d61b0-0d47-4349-b4b0-1b767c961644", + "metadata": {}, + "source": "# pyiron\n\nThis notebook builds the Quantum Espresso energy-volume-curve workflow with [`pyiron_base`](https://github.com/pyiron/pyiron_base). The `job` decorator turns plain functions into delayed pyiron jobs that are only executed once `.pull()` is called on the final result, and the whole chain of jobs is exported as a PWD `workflow.json`. The second half of the notebook loads that same JSON with `aiida-workgraph`, `jobflow` and `pyiron_workflow`." + }, + { + "cell_type": "markdown", + "id": "0bad2a57-1bd2-4837-94fe-f8c60e211fae", + "metadata": {}, + "source": "## Define workflow with pyiron_base\n\nWe import the `job` decorator from `pyiron_base` and the PWD writer for `pyiron_base`, together with the Quantum Espresso functions from `workflow.py`." + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "a2ed2608-9e1b-4a81-81cb-5079573ea2d1", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "from pyiron_base import job\n", + "from python_workflow_definition.pyiron_base import write_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "ea65c6275f956bdb", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from workflow import (\n", + " calculate_qe as _calculate_qe, \n", + " generate_structures as _generate_structures, \n", + " get_bulk_structure as _get_bulk_structure, \n", + " plot_energy_volume_curve as _plot_energy_volume_curve,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "686a6a5f54a0cef5", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "workflow_json_filename = \"pyiron_base_qe.json\"" + ] + }, + { + "cell_type": "markdown", + "id": "d73d32d1", + "source": "`calculate_qe` returns a dict with `energy`, `volume` and `structure` keys. `job(..., output_key_lst=[...])` tells `pyiron_base` which keys to expose as separate delayed outputs (e.g. `calc_mini.output.structure`), so a single downstream job can depend on just one of them instead of the whole dict.", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "208ddfb8-dfda-4227-aa1f-3dc29e34ea82", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "calculate_qe = job(_calculate_qe, output_key_lst=[\"energy\", \"volume\", \"structure\"])\n", + "generate_structures = job(_generate_structures)\n", + "plot_energy_volume_curve = job(_plot_energy_volume_curve)\n", + "get_bulk_structure = job(_get_bulk_structure)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "5071d3a0-7c1f-44c5-85e0-dede1566c10c", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "pseudopotentials = {\"Al\": \"Al.pbe-n-kjpaw_psl.1.0.0.UPF\"}" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "1f1cb12f-4001-478d-8ea0-b369f4f2981a", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "structure = get_bulk_structure(\n", + " element=\"Al\",\n", + " a=4.04,\n", + " cubic=True,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "4140f07b-af54-41ef-be22-df6b5b53bf95", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "calc_mini = calculate_qe(\n", + " working_directory=\"mini\",\n", + " input_dict={\n", + " \"structure\": structure,\n", + " \"pseudopotentials\": pseudopotentials,\n", + " \"kpts\": (3, 3, 3),\n", + " \"calculation\": \"vc-relax\",\n", + " \"smearing\": 0.02,\n", + " },\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "1e0aace0", + "source": "`generate_structures` fans out the relaxed structure into `number_of_strains` (5) strained structures. Since `pyiron_base` builds the graph lazily, it cannot know how many items a delayed dict result will contain, so `list_length` is passed explicitly - this lets `structure_lst` be iterated with `enumerate()` below to create one independent `scf` `calculate_qe` job per strained structure, before anything has actually run.", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "3c4dae11-8750-42d5-807c-cd19f2b65706", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "number_of_strains = 5\n", + "structure_lst = generate_structures( # the generate_structures() function is not available in the workflow graph\n", + " structure=calc_mini.output.structure,\n", + " strain_lst=np.linspace(0.9, 1.1, number_of_strains),\n", + " list_length=number_of_strains,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "fdf3b62d-6cce-4312-8a5b-057224e36aca", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "job_strain_lst = []\n", + "for i, structure_strain in enumerate(structure_lst):\n", + " calc_strain = calculate_qe(\n", + " working_directory=\"strain_\" + str(i),\n", + " input_dict={\n", + " \"structure\": structure_strain,\n", + " \"pseudopotentials\": pseudopotentials,\n", + " \"kpts\": (3, 3, 3),\n", + " \"calculation\": \"scf\",\n", + " \"smearing\": 0.02,\n", + " },\n", + " )\n", + " job_strain_lst.append(calc_strain)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "b2823306-0a8a-4ae6-bb1f-104e90e2fe41", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "plot = plot_energy_volume_curve(\n", + " volume_lst=[job.output.volume for job in job_strain_lst],\n", + " energy_lst=[job.output.energy for job in job_strain_lst],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "e7e789dd", + "source": "`write_workflow_json` only needs the single terminal delayed object (`plot`, the plotting job) - `pyiron_base` walks its dependency chain backwards to discover the full graph, unlike `jobflow`'s `Flow` which needs an explicit list of jobs.", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "52646121-335f-48e6-bd5e-a1d69d00e8bc", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "write_workflow_json(delayed_object=plot, file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "72c8e6e6-8e60-4a4f-81f3-968b4b5f36ee", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\n", + " \"version\": \"0.1.0\",\n", + " \"nodes\": [\n", + " {\n", + " \"id\": 0,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.plot_energy_volume_curve\"\n", + " },\n", + " {\n", + " \"id\": 1,\n", + " \"type\": \"function\",\n", + " \"value\": \"python_workflow_definition.shared.get_list\"\n", + " },\n", + " {\n", + " \"id\": 2,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.calculate_qe\"\n", + " },\n", + " {\n", + " \"id\": 3,\n", + " \"type\": \"function\",\n", + " \"value\": \"python_workflow_definition.shared.get_dict\"\n", + " },\n", + " {\n", + " \"id\": 4,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.generate_structures\"\n", + " },\n", + " {\n", + " \"id\": 5,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.calculate_qe\"\n", + " },\n", + " {\n", + " \"id\": 6,\n", + " \"type\": \"function\",\n", + " \"value\": \"python_workflow_definition.shared.get_dict\"\n", + " },\n", + " {\n", + " \"id\": 7,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.get_bulk_structure\"\n", + " },\n", + " {\n", + " \"id\": 8,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.calculate_qe\"\n", + " },\n", + " {\n", + " \"id\": 9,\n", + " \"type\": \"function\",\n", + " \"value\": \"python_workflow_definition.shared.get_dict\"\n", + " },\n", + " {\n", + " \"id\": 10,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.calculate_qe\"\n", + " },\n", + " {\n", + " \"id\": 11,\n", + " \"type\": \"function\",\n", + " \"value\": \"python_workflow_definition.shared.get_dict\"\n", + " },\n", + " {\n", + " \"id\": 12,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.calculate_qe\"\n", + " },\n", + " {\n", + " \"id\": 13,\n", + " \"type\": \"function\",\n", + " \"value\": \"python_workflow_definition.shared.get_dict\"\n", + " },\n", + " {\n", + " \"id\": 14,\n", + " \"type\": \"function\",\n", + " \"value\": \"workflow.calculate_qe\"\n", + " },\n", + " {\n", + " \"id\": 15,\n", + " \"type\": \"function\",\n", + " \"value\": \"python_workflow_definition.shared.get_dict\"\n", + " },\n", + " {\n", + " \"id\": 16,\n", + " \"type\": \"function\",\n", + " \"value\": \"python_workflow_definition.shared.get_list\"\n", + " },\n", + " {\n", + " \"id\": 17,\n", + " \"type\": \"input\",\n", + " \"name\": \"working_directory_0\",\n", + " \"value\": \"strain_0\"\n", + " },\n", + " {\n", + " \"id\": 18,\n", + " \"type\": \"input\",\n", + " \"name\": \"working_directory_1\",\n", + " \"value\": \"mini\"\n", + " },\n", + " {\n", + " \"id\": 19,\n", + " \"type\": \"input\",\n", + " \"name\": \"element\",\n", + " \"value\": \"Al\"\n", + " },\n", + " {\n", + " \"id\": 20,\n", + " \"type\": \"input\",\n", + " \"name\": \"a\",\n", + " \"value\": 4.04\n", + " },\n", + " {\n", + " \"id\": 21,\n", + " \"type\": \"input\",\n", + " \"name\": \"cubic\",\n", + " \"value\": true\n", + " },\n", + " {\n", + " \"id\": 22,\n", + " \"type\": \"input\",\n", + " \"name\": \"pseudopotentials\",\n", + " \"value\": {\n", + " \"Al\": \"Al.pbe-n-kjpaw_psl.1.0.0.UPF\"\n", + " }\n", + " },\n", + " {\n", + " \"id\": 23,\n", + " \"type\": \"input\",\n", + " \"name\": \"kpts\",\n", + " \"value\": [\n", + " 3,\n", + " 3,\n", + " 3\n", + " ]\n", + " },\n", + " {\n", + " \"id\": 24,\n", + " \"type\": \"input\",\n", + " \"name\": \"calculation_0\",\n", + " \"value\": \"vc-relax\"\n", + " },\n", + " {\n", + " \"id\": 25,\n", + " \"type\": \"input\",\n", + " \"name\": \"smearing\",\n", + " \"value\": 0.02\n", + " },\n", + " {\n", + " \"id\": 26,\n", + " \"type\": \"input\",\n", + " \"name\": \"strain_lst\",\n", + " \"value\": [\n", + " 0.9,\n", + " 0.9500000000000001,\n", + " 1.0,\n", + " 1.05,\n", + " 1.1\n", + " ]\n", + " },\n", + " {\n", + " \"id\": 27,\n", + " \"type\": \"input\",\n", + " \"name\": \"calculation_1\",\n", + " \"value\": \"scf\"\n", + " },\n", + " {\n", + " \"id\": 28,\n", + " \"type\": \"input\",\n", + " \"name\": \"working_directory_2\",\n", + " \"value\": \"strain_1\"\n", + " },\n", + " {\n", + " \"id\": 29,\n", + " \"type\": \"input\",\n", + " \"name\": \"working_directory_3\",\n", + " \"value\": \"strain_2\"\n", + " },\n", + " {\n", + " \"id\": 30,\n", + " \"type\": \"input\",\n", + " \"name\": \"working_directory_4\",\n", + " \"value\": \"strain_3\"\n", + " },\n", + " {\n", + " \"id\": 31,\n", + " \"type\": \"input\",\n", + " \"name\": \"working_directory_5\",\n", + " \"value\": \"strain_4\"\n", + " },\n", + " {\n", + " \"id\": 32,\n", + " \"type\": \"output\",\n", + " \"name\": \"result\"\n", + " }\n", + " ],\n", + " \"edges\": [\n", + " {\n", + " \"target\": 0,\n", + " \"targetPort\": \"volume_lst\",\n", + " \"source\": 1,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 1,\n", + " \"targetPort\": \"0\",\n", + " \"source\": 2,\n", + " \"sourcePort\": \"volume\"\n", + " },\n", + " {\n", + " \"target\": 2,\n", + " \"targetPort\": \"working_directory\",\n", + " \"source\": 17,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 2,\n", + " \"targetPort\": \"input_dict\",\n", + " \"source\": 3,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 3,\n", + " \"targetPort\": \"structure\",\n", + " \"source\": 4,\n", + " \"sourcePort\": \"s_0\"\n", + " },\n", + " {\n", + " \"target\": 4,\n", + " \"targetPort\": \"structure\",\n", + " \"source\": 5,\n", + " \"sourcePort\": \"structure\"\n", + " },\n", + " {\n", + " \"target\": 5,\n", + " \"targetPort\": \"working_directory\",\n", + " \"source\": 18,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 5,\n", + " \"targetPort\": \"input_dict\",\n", + " \"source\": 6,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 6,\n", + " \"targetPort\": \"structure\",\n", + " \"source\": 7,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 7,\n", + " \"targetPort\": \"element\",\n", + " \"source\": 19,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 7,\n", + " \"targetPort\": \"a\",\n", + " \"source\": 20,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 7,\n", + " \"targetPort\": \"cubic\",\n", + " \"source\": 21,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 6,\n", + " \"targetPort\": \"pseudopotentials\",\n", + " \"source\": 22,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 6,\n", + " \"targetPort\": \"kpts\",\n", + " \"source\": 23,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 6,\n", + " \"targetPort\": \"calculation\",\n", + " \"source\": 24,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 6,\n", + " \"targetPort\": \"smearing\",\n", + " \"source\": 25,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 4,\n", + " \"targetPort\": \"strain_lst\",\n", + " \"source\": 26,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 3,\n", + " \"targetPort\": \"pseudopotentials\",\n", + " \"source\": 22,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 3,\n", + " \"targetPort\": \"kpts\",\n", + " \"source\": 23,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 3,\n", + " \"targetPort\": \"calculation\",\n", + " \"source\": 27,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 3,\n", + " \"targetPort\": \"smearing\",\n", + " \"source\": 25,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 1,\n", + " \"targetPort\": \"1\",\n", + " \"source\": 8,\n", + " \"sourcePort\": \"volume\"\n", + " },\n", + " {\n", + " \"target\": 8,\n", + " \"targetPort\": \"working_directory\",\n", + " \"source\": 28,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 8,\n", + " \"targetPort\": \"input_dict\",\n", + " \"source\": 9,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 9,\n", + " \"targetPort\": \"structure\",\n", + " \"source\": 4,\n", + " \"sourcePort\": \"s_1\"\n", + " },\n", + " {\n", + " \"target\": 9,\n", + " \"targetPort\": \"pseudopotentials\",\n", + " \"source\": 22,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 9,\n", + " \"targetPort\": \"kpts\",\n", + " \"source\": 23,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 9,\n", + " \"targetPort\": \"calculation\",\n", + " \"source\": 27,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 9,\n", + " \"targetPort\": \"smearing\",\n", + " \"source\": 25,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 1,\n", + " \"targetPort\": \"2\",\n", + " \"source\": 10,\n", + " \"sourcePort\": \"volume\"\n", + " },\n", + " {\n", + " \"target\": 10,\n", + " \"targetPort\": \"working_directory\",\n", + " \"source\": 29,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 10,\n", + " \"targetPort\": \"input_dict\",\n", + " \"source\": 11,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 11,\n", + " \"targetPort\": \"structure\",\n", + " \"source\": 4,\n", + " \"sourcePort\": \"s_2\"\n", + " },\n", + " {\n", + " \"target\": 11,\n", + " \"targetPort\": \"pseudopotentials\",\n", + " \"source\": 22,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 11,\n", + " \"targetPort\": \"kpts\",\n", + " \"source\": 23,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 11,\n", + " \"targetPort\": \"calculation\",\n", + " \"source\": 27,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 11,\n", + " \"targetPort\": \"smearing\",\n", + " \"source\": 25,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 1,\n", + " \"targetPort\": \"3\",\n", + " \"source\": 12,\n", + " \"sourcePort\": \"volume\"\n", + " },\n", + " {\n", + " \"target\": 12,\n", + " \"targetPort\": \"working_directory\",\n", + " \"source\": 30,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 12,\n", + " \"targetPort\": \"input_dict\",\n", + " \"source\": 13,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 13,\n", + " \"targetPort\": \"structure\",\n", + " \"source\": 4,\n", + " \"sourcePort\": \"s_3\"\n", + " },\n", + " {\n", + " \"target\": 13,\n", + " \"targetPort\": \"pseudopotentials\",\n", + " \"source\": 22,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 13,\n", + " \"targetPort\": \"kpts\",\n", + " \"source\": 23,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 13,\n", + " \"targetPort\": \"calculation\",\n", + " \"source\": 27,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 13,\n", + " \"targetPort\": \"smearing\",\n", + " \"source\": 25,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 1,\n", + " \"targetPort\": \"4\",\n", + " \"source\": 14,\n", + " \"sourcePort\": \"volume\"\n", + " },\n", + " {\n", + " \"target\": 14,\n", + " \"targetPort\": \"working_directory\",\n", + " \"source\": 31,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 14,\n", + " \"targetPort\": \"input_dict\",\n", + " \"source\": 15,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 15,\n", + " \"targetPort\": \"structure\",\n", + " \"source\": 4,\n", + " \"sourcePort\": \"s_4\"\n", + " },\n", + " {\n", + " \"target\": 15,\n", + " \"targetPort\": \"pseudopotentials\",\n", + " \"source\": 22,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 15,\n", + " \"targetPort\": \"kpts\",\n", + " \"source\": 23,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 15,\n", + " \"targetPort\": \"calculation\",\n", + " \"source\": 27,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 15,\n", + " \"targetPort\": \"smearing\",\n", + " \"source\": 25,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 0,\n", + " \"targetPort\": \"energy_lst\",\n", + " \"source\": 16,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 16,\n", + " \"targetPort\": \"0\",\n", + " \"source\": 2,\n", + " \"sourcePort\": \"energy\"\n", + " },\n", + " {\n", + " \"target\": 16,\n", + " \"targetPort\": \"1\",\n", + " \"source\": 8,\n", + " \"sourcePort\": \"energy\"\n", + " },\n", + " {\n", + " \"target\": 16,\n", + " \"targetPort\": \"2\",\n", + " \"source\": 10,\n", + " \"sourcePort\": \"energy\"\n", + " },\n", + " {\n", + " \"target\": 16,\n", + " \"targetPort\": \"3\",\n", + " \"source\": 12,\n", + " \"sourcePort\": \"energy\"\n", + " },\n", + " {\n", + " \"target\": 16,\n", + " \"targetPort\": \"4\",\n", + " \"source\": 14,\n", + " \"sourcePort\": \"energy\"\n", + " },\n", + " {\n", + " \"target\": 32,\n", + " \"targetPort\": null,\n", + " \"source\": 0,\n", + " \"sourcePort\": null\n", + " }\n", + " ]\n", + "}" + ] + } + ], + "source": [ + "!cat {workflow_json_filename}" + ] + }, + { + "cell_type": "markdown", + "id": "7d75a2f6-6fad-49c8-bd29-37cca1b84441", + "metadata": {}, + "source": "## Load Workflow with aiida\n\n`load_workflow_json` reconstructs the graph as an `aiida-workgraph` `WorkGraph`. The lattice constant `a` is overridden (4.04 -> 4.05) to show the loaded graph can still be edited like one built natively with `aiida-workgraph`, before running it with `wg.run()`." + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "28760464-2a2c-40c2-9451-20713da2ba2c", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Profile" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from aiida import orm, load_profile\n", + "\n", + "load_profile()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "a442fe46-057c-469b-a5e0-173ed4829dfb", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from python_workflow_definition.aiida import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "32fcd4b2-4f0a-442d-b098-827672823796", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wg = load_workflow_json(file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d81a4fb5-a674-41a9-ac19-24c56f952468", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wg.tasks.get_bulk_structure.inputs.a.value = orm.Float(4.05)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "a80b59bd-fe30-49c6-92ca-35ef2d77a6fb", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "05/26/2025 04:46:41 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_bulk_structure8\n", + "05/26/2025 04:46:41 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_bulk_structure8, type: PyFunction, finished.\n", + "05/26/2025 04:46:41 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict7\n", + "05/26/2025 04:46:42 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_dict7, type: PyFunction, finished.\n", + "05/26/2025 04:46:42 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe6\n", + "[jupyter-pythonworkflow-fl--x---218119f8:01776] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 04:47:34 AM <1688> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['energy', 'volume'])\n", + "05/26/2025 04:47:34 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: calculate_qe6, type: PyFunction, finished.\n", + "05/26/2025 04:47:34 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: generate_structures5\n", + "05/26/2025 04:47:35 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: generate_structures5, type: PyFunction, finished.\n", + "05/26/2025 04:47:35 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict4,get_dict10,get_dict12,get_dict14,get_dict16\n", + "05/26/2025 04:47:36 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_dict4, type: PyFunction, finished.\n", + "05/26/2025 04:47:36 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe3,get_dict10,get_dict12,get_dict14,get_dict16\n", + "[jupyter-pythonworkflow-fl--x---218119f8:01828] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 04:47:47 AM <1688> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n", + "05/26/2025 04:47:47 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: calculate_qe3, type: PyFunction, finished.\n", + "05/26/2025 04:47:47 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict10,get_dict12,get_dict14,get_dict16\n", + "05/26/2025 04:47:48 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_dict10, type: PyFunction, finished.\n", + "05/26/2025 04:47:48 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe9,get_dict12,get_dict14,get_dict16\n", + "[jupyter-pythonworkflow-fl--x---218119f8:01860] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 04:47:59 AM <1688> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n", + "05/26/2025 04:48:00 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: calculate_qe9, type: PyFunction, finished.\n", + "05/26/2025 04:48:00 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict12,get_dict14,get_dict16\n", + "05/26/2025 04:48:00 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_dict12, type: PyFunction, finished.\n", + "05/26/2025 04:48:00 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe11,get_dict14,get_dict16\n", + "[jupyter-pythonworkflow-fl--x---218119f8:01874] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 04:48:13 AM <1688> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n", + "05/26/2025 04:48:13 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: calculate_qe11, type: PyFunction, finished.\n", + "05/26/2025 04:48:13 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict14,get_dict16\n", + "05/26/2025 04:48:14 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_dict14, type: PyFunction, finished.\n", + "05/26/2025 04:48:14 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe13,get_dict16\n", + "[jupyter-pythonworkflow-fl--x---218119f8:01885] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 04:48:29 AM <1688> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n", + "05/26/2025 04:48:29 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: calculate_qe13, type: PyFunction, finished.\n", + "05/26/2025 04:48:29 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict16\n", + "05/26/2025 04:48:29 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_dict16, type: PyFunction, finished.\n", + "05/26/2025 04:48:29 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe15\n", + "[jupyter-pythonworkflow-fl--x---218119f8:01895] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 04:48:44 AM <1688> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n", + "05/26/2025 04:48:44 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: calculate_qe15, type: PyFunction, finished.\n", + "05/26/2025 04:48:44 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_list2,get_list17\n", + "05/26/2025 04:48:44 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_list2, type: PyFunction, finished.\n", + "05/26/2025 04:48:44 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_list17\n", + "05/26/2025 04:48:45 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_list17, type: PyFunction, finished.\n", + "05/26/2025 04:48:45 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: plot_energy_volume_curve1\n", + "05/26/2025 04:48:45 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: plot_energy_volume_curve1, type: PyFunction, finished.\n", + "05/26/2025 04:48:46 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n", + "05/26/2025 04:48:46 AM <1688> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|finalize]: Finalize workgraph.\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "wg.run()" + ] + }, + { + "cell_type": "markdown", + "id": "c4f5c047-c6da-4b54-9007-415faca7a448", + "metadata": {}, + "source": "## Load Workflow with jobflow\n\nThe same JSON is loaded as a `jobflow` `Flow` and executed locally with `run_locally`, again after overriding the lattice constant `a`." + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "b8e3c2ca-2672-4e9d-aada-63344842dbcf", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from python_workflow_definition.jobflow import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "54a24ff6c569094e", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from jobflow.managers.local import run_locally" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "48a27146-7372-40ab-8b02-e2a9283d4748", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "flow = load_workflow_json(file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "bf84ef10-e1af-475f-a457-d2703c7276a0", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "flow[0].function_kwargs[\"a\"] = 4.05" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "98fa5694-2cc6-44e9-a6e7-2cc71b4f48ce", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 04:48:47,564 INFO Started executing jobs locally\n", + "2025-05-26 04:48:47,751 INFO Starting job - get_bulk_structure (f386f375-fcc9-4700-a077-b8c7b4ed29d4)\n", + "2025-05-26 04:48:47,754 INFO Finished job - get_bulk_structure (f386f375-fcc9-4700-a077-b8c7b4ed29d4)\n", + "2025-05-26 04:48:47,755 INFO Starting job - get_dict (6c1c9b0f-5c14-4ae9-be98-984400228394)\n", + "2025-05-26 04:48:47,757 INFO Finished job - get_dict (6c1c9b0f-5c14-4ae9-be98-984400228394)\n", + "2025-05-26 04:48:47,757 INFO Starting job - calculate_qe (f511b680-fa97-420f-904d-2ae232dbe75b)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---218119f8:01905] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 04:49:37,980 INFO Finished job - calculate_qe (f511b680-fa97-420f-904d-2ae232dbe75b)\n", + "2025-05-26 04:49:37,981 INFO Starting job - generate_structures (d5fc7015-e7fe-4111-bf16-23bdc6755f93)\n", + "2025-05-26 04:49:37,985 INFO Finished job - generate_structures (d5fc7015-e7fe-4111-bf16-23bdc6755f93)\n", + "2025-05-26 04:49:37,986 INFO Starting job - get_dict (49b7b2e8-78ca-4d63-bfa6-f3b47ca3378f)\n", + "2025-05-26 04:49:37,988 INFO Finished job - get_dict (49b7b2e8-78ca-4d63-bfa6-f3b47ca3378f)\n", + "2025-05-26 04:49:37,988 INFO Starting job - get_dict (a45e0be5-c229-4817-8dc8-e2f54c46205f)\n", + "2025-05-26 04:49:37,990 INFO Finished job - get_dict (a45e0be5-c229-4817-8dc8-e2f54c46205f)\n", + "2025-05-26 04:49:37,990 INFO Starting job - get_dict (30bf90f1-57c2-474b-8bd2-d8a18061d85c)\n", + "2025-05-26 04:49:37,992 INFO Finished job - get_dict (30bf90f1-57c2-474b-8bd2-d8a18061d85c)\n", + "2025-05-26 04:49:37,993 INFO Starting job - get_dict (d4b595f2-93a9-42d7-a547-f64be9b4ca80)\n", + "2025-05-26 04:49:37,995 INFO Finished job - get_dict (d4b595f2-93a9-42d7-a547-f64be9b4ca80)\n", + "2025-05-26 04:49:37,996 INFO Starting job - get_dict (8c32a293-38d8-4c3a-82fc-78edd324d64d)\n", + "2025-05-26 04:49:37,998 INFO Finished job - get_dict (8c32a293-38d8-4c3a-82fc-78edd324d64d)\n", + "2025-05-26 04:49:37,998 INFO Starting job - calculate_qe (e747fb6a-e704-44ff-906e-664be75da6fc)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---218119f8:01923] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 04:49:48,629 INFO Finished job - calculate_qe (e747fb6a-e704-44ff-906e-664be75da6fc)\n", + "2025-05-26 04:49:48,630 INFO Starting job - calculate_qe (579fbf80-e6e7-464c-a808-f5cecd9ef430)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:01934] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 04:50:00,439 INFO Finished job - calculate_qe (579fbf80-e6e7-464c-a808-f5cecd9ef430)\n", + "2025-05-26 04:50:00,439 INFO Starting job - calculate_qe (ceb70e3f-c90a-4aa3-a670-23ecf40fa11b)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:01945] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 04:50:13,181 INFO Finished job - calculate_qe (ceb70e3f-c90a-4aa3-a670-23ecf40fa11b)\n", + "2025-05-26 04:50:13,182 INFO Starting job - calculate_qe (290a2a1d-9a74-40b1-af28-e4f61b357694)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:01955] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 04:50:27,249 INFO Finished job - calculate_qe (290a2a1d-9a74-40b1-af28-e4f61b357694)\n", + "2025-05-26 04:50:27,250 INFO Starting job - calculate_qe (a9f810e8-c291-46b9-ab8f-4c59765bf3b9)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:01965] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 04:50:37,525 INFO Finished job - calculate_qe (a9f810e8-c291-46b9-ab8f-4c59765bf3b9)\n", + "2025-05-26 04:50:37,526 INFO Starting job - get_list (20122c29-0e2d-4a9c-8506-d371390f8042)\n", + "2025-05-26 04:50:37,528 INFO Finished job - get_list (20122c29-0e2d-4a9c-8506-d371390f8042)\n", + "2025-05-26 04:50:37,529 INFO Starting job - get_list (9842e2f0-3ca3-4a23-b82b-a3644a0294a8)\n", + "2025-05-26 04:50:37,531 INFO Finished job - get_list (9842e2f0-3ca3-4a23-b82b-a3644a0294a8)\n", + "2025-05-26 04:50:37,532 INFO Starting job - plot_energy_volume_curve (a1614162-0427-4cd2-a2c4-01837c5ae505)\n", + "2025-05-26 04:50:37,581 INFO Finished job - plot_energy_volume_curve (a1614162-0427-4cd2-a2c4-01837c5ae505)\n", + "2025-05-26 04:50:37,582 INFO Finished executing jobs locally\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "data": { + "text/plain": [ + 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "result = run_locally(flow)\n", + "result" + ] + }, + { + "cell_type": "markdown", + "id": "406b0429e65b9760", + "metadata": {}, + "source": "## Load Workflow with pyiron_workflow\n\nFinally, the graph is loaded into a `pyiron_workflow` `Workflow`, its lattice constant overridden, drawn with `.draw()`, and executed with `.run()`." + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "1b45a453f593202f", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from python_workflow_definition.pyiron_workflow import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "97ef39ae859855ab", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wf = load_workflow_json(file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "907dcc6d-97a6-4b6a-8214-4ba96ce26769", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "4368c6921b71e396", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wf.get_bulk_structure.inputs.a.value = 4.05" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "659ccc92-a4d9-4876-a63a-be5dac50e295", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "clusterpyiron_base_qe\n", + "\n", + "pyiron_base_qe: Workflow\n", + "\n", + "clusterpyiron_base_qeInputs\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "Inputs\n", + "\n", + "\n", + "clusterpyiron_base_qeOutputsWithInjection\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "OutputsWithInjection\n", + "\n", + "\n", + "clusterpyiron_base_qeplot_energy_volume_curve\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "plot_energy_volume_curve: plot_energy_volume_curve\n", + "\n", + "\n", + "clusterpyiron_base_qeplot_energy_volume_curveInputs\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "Inputs\n", + "\n", + "\n", + "clusterpyiron_base_qeplot_energy_volume_curveOutputsWithInjection\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "OutputsWithInjection\n", + "\n", + "\n", + "clusterpyiron_base_qeget_list_0\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "get_list_0: get_list\n", + "\n", + "\n", + "clusterpyiron_base_qeget_list_0Inputs\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "Inputs\n", + "\n", + "\n", + "clusterpyiron_base_qeget_list_0OutputsWithInjection\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "OutputsWithInjection\n", + "\n", + "\n", + "clusterpyiron_base_qecalculate_qe_0\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "calculate_qe_0: calculate_qe\n", + "\n", + "\n", + "clusterpyiron_base_qecalculate_qe_0Inputs\n", + "\n", 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exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:01993] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02008] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02018] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02028] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---218119f8:02039] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "data": { + "text/plain": [ + "{'plot_energy_volume_curve__plot_energy_volume_curve': None}" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "wf.run()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5022eb03-b714-409d-b82b-cada385b351d", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.8" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} \ No newline at end of file diff --git a/_sources/example_workflows/quantum_espresso/pyiron_workflow.ipynb b/_sources/example_workflows/quantum_espresso/pyiron_workflow.ipynb new file mode 100644 index 00000000..88d94a23 --- /dev/null +++ b/_sources/example_workflows/quantum_espresso/pyiron_workflow.ipynb @@ -0,0 +1,6042 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "760acc89-8c02-4bc9-a8f6-2572506b7085", + "metadata": {}, + "source": "# pyiron_workflow\n## Define workflow with pyiron_workflow\n\nThis notebook builds the Quantum Espresso energy-volume-curve workflow with [`pyiron_workflow`](https://github.com/pyiron/pyiron_workflow). Plain functions are converted to graph nodes with `to_function_node`, assembled into a `Workflow` via attribute access, and exported as a PWD `workflow.json`. The second half of the notebook loads that same JSON with `aiida-workgraph`, `jobflow` and `pyiron_base`." + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "44aa8e82-2d78-4015-a56d-cd487aefc48f", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from inspect import isfunction\n", + "import numpy as np\n", + "from pyiron_workflow._legacy import Workflow, to_function_node, as_function_node\n", + "from pyiron_workflow._legacy.api import inputs_to_dict\n", + "from python_workflow_definition.pyiron_workflow import write_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "341dab17-b329-42eb-a485-2f9326a048e9", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from workflow import (\n", + " calculate_qe as _calculate_qe, \n", + " generate_structures as _generate_structures, \n", + " get_bulk_structure as _get_bulk_structure, \n", + " plot_energy_volume_curve as _plot_energy_volume_curve,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "2d3f3ba6", + "source": "`pyiron_workflow` has no built-in equivalent of the `get_list` helper the other engines use to collect several outputs into a list, so `get_values_from_dict` is defined here as a custom node with `as_function_node` to turn a dict of energies/volumes into a plain list for the final plot.", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "729a1a3a-8377-4148-9b3c-a4a866f9c4ec", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "@as_function_node(\"output_dict\")\n", + "def get_values_from_dict(input_dict):\n", + " return list(input_dict.values())" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "6c2711ec-25f8-4ecd-9b9a-d9af1ec81316", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "workflow_json_filename = \"pyiron_workflow_qe.json\"" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "3e1492bc-49bd-4f9c-9703-582a5a60579b", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "calculate_qe = to_function_node(\"calculate_qe\", _calculate_qe, \"calculate_qe\")\n", + "generate_structures = to_function_node(\"generate_structures\", _generate_structures, \"generate_structures\")\n", + "get_bulk_structure = to_function_node(\"get_bulk_structure\", _get_bulk_structure, \"get_bulk_structure\")\n", + "plot_energy_volume_curve = to_function_node(\"plot_energy_volume_curve\", _plot_energy_volume_curve, \"plot_energy_volume_curve\", validate_output_labels=False)" + ] + }, + { + "cell_type": "markdown", + "id": "be84f115", + "source": "`to_function_node` wraps each plain Python function into a `pyiron_workflow` node type. `plot_energy_volume_curve` passes `validate_output_labels=False` since it has no return value, so its output cannot be matched to an explicit output label.", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "a4f2fe6d-bed4-49f8-b903-1ed69ff92eb7", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wf = Workflow(\"my_workflow\")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "62268668-7f09-4fee-99d2-c770b4e558d9", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wf.pseudopotentials = {\"Al\": \"Al.pbe-n-kjpaw_psl.1.0.0.UPF\"}" + ] + }, + { + "cell_type": "markdown", + "id": "c117be40", + "source": "Nodes are added to the `Workflow` by assigning their result to an attribute of `wf` (e.g. `wf.structure = get_bulk_structure(...)`), which both registers the node and gives it a name in the graph. Since `calculate_qe` expects a single `input_dict` argument, `inputs_to_dict` is used to bundle the structure, pseudopotentials, k-points, calculation type and smearing into one dict-valued node before the first (`vc-relax`) QE calculation.", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "b2ea76b0-f79b-461f-8126-7bac3bda4422", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wf.element = \"Al\"\n", + "wf.a = 4.04\n", + "wf.cubic = True\n", + "wf.structure = get_bulk_structure(\n", + " element=wf.element,\n", + " a=wf.a,\n", + " cubic=wf.cubic,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "01bc824f-c990-448c-a4da-1ff8b519e720", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wf.working_directory_0 = \"mini\"\n", + "input_dict = {\n", + " \"structure\": wf.structure, \n", + " \"pseudopotentials\": wf.pseudopotentials, \n", + " \"kpts\": (3, 3, 3), \n", + " \"calculation\": \"vc-relax\", \n", + " \"smearing\": 0.02,\n", + "}\n", + "wf.input_dict_0 = inputs_to_dict(\n", + " input_specification=list(input_dict.keys()),\n", + " **input_dict\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "95d168a1-48db-434a-b17d-abea6c1633f5", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wf.calc_mini = calculate_qe(\n", + " working_directory=wf.working_directory_0,\n", + " input_dict=wf.input_dict_0,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "6d21ce04", + "source": "`generate_structures` fans out the relaxed structure into `number_of_strains` (5) strained structures (`wf.structure_lst[\"s_0\"]` ... `[\"s_4\"]`). The loop below builds one `input_dict` and one independent `scf` `calculate_qe` node per strained structure, so five QE calculations run to sample the energy-volume curve.", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "fbfb0107-278d-4209-883c-8c0543c5c240", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "number_of_strains = 5\n", + "wf.strain_lst = np.linspace(0.9, 1.1, number_of_strains)\n", + "wf.structure_lst = generate_structures( # the generate_structures() function is not available in the workflow graph\n", + " structure=wf.calc_mini[\"structure\"],\n", + " strain_lst=wf.strain_lst,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "956184d1-887a-4632-9311-b917fb5d7370", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "job_strain_lst = []\n", + "for i in range(number_of_strains):\n", + " setattr(wf, \"input_dict_\" + str(i+1), inputs_to_dict(\n", + " input_specification=[\"structure\", \"pseudopotentials\", \"kpts\", \"calculation\", \"smearing\"],\n", + " structure=wf.structure_lst[\"s_\" + str(i)],\n", + " pseudopotentials=wf.pseudopotentials,\n", + " kpts=(3, 3, 3),\n", + " calculation=\"scf\",\n", + " smearing=0.02,\n", + " ))\n", + " setattr(wf, \"calc_strain_\" + str(i), calculate_qe(\n", + " working_directory=\"strain_\" + str(i),\n", + " input_dict=getattr(wf, \"input_dict_\" + str(i+1)),\n", + " ))\n", + " job_strain_lst.append(getattr(wf, \"calc_strain_\" + str(i)))" + ] + }, + { + "cell_type": "markdown", + "id": "edc600a3", + "source": "The `energy` and `volume` outputs of the five strained calculations are bundled with `inputs_to_dict` and then flattened into two plain lists with the `get_values_from_dict` node defined above, ready to be passed to `plot_energy_volume_curve`.", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "a0643f87-98f1-440e-9f0d-8cf316a69f0f", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "volume_dict = {\"s_\" + str(i): j[\"volume\"] for i, j in enumerate(job_strain_lst)}\n", + "wf.volume_dict = inputs_to_dict(\n", + " input_specification=list(volume_dict.keys()),\n", + " **volume_dict\n", + ")\n", + "energy_dict = {\"s_\" + str(i): j[\"energy\"] for i, j in enumerate(job_strain_lst)}\n", + "wf.energy_dict = inputs_to_dict(\n", + " input_specification=list(energy_dict.keys()),\n", + " **energy_dict,\n", + ")\n", + "wf.volume_lst = get_values_from_dict(\n", + " input_dict=wf.volume_dict\n", + ")\n", + "wf.energy_lst = get_values_from_dict(\n", + " input_dict=wf.energy_dict\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "96808641-c9e4-4d57-9f9c-8b1a9c1b1356", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wf.plot = plot_energy_volume_curve(volume_lst=wf.volume_lst, energy_lst=wf.energy_lst)" + ] + }, + { + "cell_type": "markdown", + "id": "e5408a80", + 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\"pseudopotentials\",\n", + " \"source\": 20,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 6,\n", + " \"targetPort\": \"kpts\",\n", + " \"source\": 21,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 6,\n", + " \"targetPort\": \"calculation\",\n", + " \"source\": 26,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 6,\n", + " \"targetPort\": \"smearing\",\n", + " \"source\": 23,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 7,\n", + " \"targetPort\": \"working_directory\",\n", + " \"source\": 28,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 8,\n", + " \"targetPort\": \"pseudopotentials\",\n", + " \"source\": 20,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 8,\n", + " \"targetPort\": \"kpts\",\n", + " \"source\": 21,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 8,\n", + " \"targetPort\": \"calculation\",\n", + " \"source\": 26,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 8,\n", + " \"targetPort\": \"smearing\",\n", + " \"source\": 23,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 9,\n", + " \"targetPort\": \"working_directory\",\n", + " \"source\": 29,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 10,\n", + " \"targetPort\": \"pseudopotentials\",\n", + " \"source\": 20,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 10,\n", + " \"targetPort\": \"kpts\",\n", + " \"source\": 21,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 10,\n", + " \"targetPort\": \"calculation\",\n", + " \"source\": 26,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 10,\n", + " \"targetPort\": \"smearing\",\n", + " \"source\": 23,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 11,\n", + " \"targetPort\": \"working_directory\",\n", + " \"source\": 30,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 12,\n", + " \"targetPort\": \"pseudopotentials\",\n", + " \"source\": 20,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 12,\n", + " \"targetPort\": \"kpts\",\n", + " \"source\": 21,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 12,\n", + " \"targetPort\": \"calculation\",\n", + " \"source\": 26,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 12,\n", + " \"targetPort\": \"smearing\",\n", + " \"source\": 23,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 13,\n", + " \"targetPort\": \"working_directory\",\n", + " \"source\": 31,\n", + " \"sourcePort\": null\n", + " },\n", + " {\n", + " \"target\": 32,\n", + " \"targetPort\": null,\n", + " \"source\": 16,\n", + " \"sourcePort\": null\n", + " }\n", + " ]\n", + "}" + ] + } + ], + "source": [ + "!cat {workflow_json_filename}" + ] + }, + { + "cell_type": "markdown", + "id": "fef7107a-5af3-4434-ae4c-a8d45e1d9b61", + "metadata": {}, + "source": "## Load Workflow with aiida\n\n`load_workflow_json` reconstructs the graph as an `aiida-workgraph` `WorkGraph`. The lattice constant `a` is overridden (4.04 -> 4.05) to show the loaded graph can still be edited like one built natively with `aiida-workgraph`, before running it with `wg.run()`." + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "5f4d2243-faf6-4d57-be70-5f7d1292e33e", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Profile" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from aiida import orm, load_profile\n", + "\n", + "load_profile()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "232c9447-8274-4a82-9c8c-468af7ec6c43", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from python_workflow_definition.aiida import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "97150c3d-dd11-4b24-8e19-a088bb85a2c8", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wg = load_workflow_json(file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "539e0245-c31c-4fb6-badd-c6ef155b43fa", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "wg.tasks.get_bulk_structure.inputs.a.value = orm.Float(4.05)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "dac6c4ad-297e-43b1-8d0a-ea841f3d6aa7", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "05/26/2025 05:57:55 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_bulk_structure1\n", + "05/26/2025 05:57:56 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_bulk_structure1, type: PyFunction, finished.\n", + "05/26/2025 05:57:56 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict2\n", + "05/26/2025 05:57:56 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_dict2, type: PyFunction, finished.\n", + "05/26/2025 05:57:56 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe3\n", + "[jupyter-pythonworkflow-fl--x---35e2fba5:00217] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 05:58:48 AM <86> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['energy', 'volume'])\n", + "05/26/2025 05:58:48 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: calculate_qe3, type: PyFunction, finished.\n", + "05/26/2025 05:58:48 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: generate_structures4\n", + "05/26/2025 05:58:49 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: generate_structures4, type: PyFunction, finished.\n", + "05/26/2025 05:58:49 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict5,get_dict7,get_dict9,get_dict11,get_dict13\n", + "05/26/2025 05:58:49 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_dict5, type: PyFunction, finished.\n", + "05/26/2025 05:58:50 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe6,get_dict7,get_dict9,get_dict11,get_dict13\n", + "[jupyter-pythonworkflow-fl--x---35e2fba5:00262] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 05:59:03 AM <86> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n", + "05/26/2025 05:59:04 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: calculate_qe6, type: PyFunction, finished.\n", + "05/26/2025 05:59:04 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict7,get_dict9,get_dict11,get_dict13\n", + "05/26/2025 05:59:04 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_dict7, type: PyFunction, finished.\n", + "05/26/2025 05:59:05 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe8,get_dict9,get_dict11,get_dict13\n", + "[jupyter-pythonworkflow-fl--x---35e2fba5:00273] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 05:59:16 AM <86> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n", + "05/26/2025 05:59:16 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: calculate_qe8, type: PyFunction, finished.\n", + "05/26/2025 05:59:16 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict9,get_dict11,get_dict13\n", + "05/26/2025 05:59:17 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_dict9, type: PyFunction, finished.\n", + "05/26/2025 05:59:17 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe10,get_dict11,get_dict13\n", + "[jupyter-pythonworkflow-fl--x---35e2fba5:00285] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 05:59:28 AM <86> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n", + "05/26/2025 05:59:29 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: calculate_qe10, type: PyFunction, finished.\n", + "05/26/2025 05:59:29 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict11,get_dict13\n", + "05/26/2025 05:59:29 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_dict11, type: PyFunction, finished.\n", + "05/26/2025 05:59:29 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe12,get_dict13\n", + "[jupyter-pythonworkflow-fl--x---35e2fba5:00296] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 05:59:43 AM <86> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n", + "05/26/2025 05:59:43 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: calculate_qe12, type: PyFunction, finished.\n", + "05/26/2025 05:59:43 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict13\n", + "05/26/2025 05:59:44 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_dict13, type: PyFunction, finished.\n", + "05/26/2025 05:59:44 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe14\n", + "[jupyter-pythonworkflow-fl--x---35e2fba5:00307] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "05/26/2025 05:59:58 AM <86> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n", + "05/26/2025 05:59:59 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: calculate_qe14, type: PyFunction, finished.\n", + "05/26/2025 05:59:59 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_list15,get_list16\n", + "05/26/2025 05:59:59 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_list15, type: PyFunction, finished.\n", + "05/26/2025 05:59:59 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_list16\n", + "05/26/2025 06:00:00 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: get_list16, type: PyFunction, finished.\n", + "05/26/2025 06:00:00 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: plot_energy_volume_curve17\n", + "05/26/2025 06:00:01 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|update_task_state]: Task: plot_energy_volume_curve17, type: PyFunction, finished.\n", + "05/26/2025 06:00:01 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n", + "05/26/2025 06:00:01 AM <86> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [17|WorkGraphEngine|finalize]: Finalize workgraph.\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "wg.run()" + ] + }, + { + "cell_type": "markdown", + "id": "9226d966-d90a-4ab2-9776-df1b50bd6a49", + "metadata": {}, + "source": "## Load Workflow with jobflow\n\nThe same JSON is loaded as a `jobflow` `Flow` and executed locally with `run_locally`, again after overriding the lattice constant `a`." + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "ba32ad83-385d-4f1a-87ea-28a1383e6067", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from python_workflow_definition.jobflow import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "4a39c916-a45b-48ac-b4a9-914688c5d85e", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from jobflow.managers.local import run_locally" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "9b03e3e7-3dba-4640-9869-76916413bfc0", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "flow = load_workflow_json(file_name=workflow_json_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "a3f050c8-9a29-461e-bb68-b6cdc5e1bb1b", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "flow[0].function_kwargs[\"a\"] = 4.05" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "19df3f74-8c2f-4563-a78a-f5307a9e084d", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 06:00:02,662 INFO Started executing jobs locally\n", + "2025-05-26 06:00:02,768 INFO Starting job - get_bulk_structure (2521ebff-2219-4e59-9425-4f3ab2851e2a)\n", + "2025-05-26 06:00:02,771 INFO Finished job - get_bulk_structure (2521ebff-2219-4e59-9425-4f3ab2851e2a)\n", + "2025-05-26 06:00:02,772 INFO Starting job - get_dict (16a60b49-6205-418e-a640-7a128111d10c)\n", + "2025-05-26 06:00:02,776 INFO Finished job - get_dict (16a60b49-6205-418e-a640-7a128111d10c)\n", + "2025-05-26 06:00:02,777 INFO Starting job - calculate_qe (ac278a4f-b187-498e-a234-4060e13f5b06)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---35e2fba5:00319] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 06:00:53,435 INFO Finished job - calculate_qe (ac278a4f-b187-498e-a234-4060e13f5b06)\n", + "2025-05-26 06:00:53,436 INFO Starting job - generate_structures (40215563-bfe0-47dc-a31b-124b15688007)\n", + "2025-05-26 06:00:53,440 INFO Finished job - generate_structures (40215563-bfe0-47dc-a31b-124b15688007)\n", + "2025-05-26 06:00:53,440 INFO Starting job - get_dict (65b32304-10b3-4711-9f55-2dcc5c405641)\n", + "2025-05-26 06:00:53,442 INFO Finished job - get_dict (65b32304-10b3-4711-9f55-2dcc5c405641)\n", + "2025-05-26 06:00:53,442 INFO Starting job - get_dict (77f8e7d0-2281-42cc-b39e-d7acc34f5458)\n", + "2025-05-26 06:00:53,444 INFO Finished job - get_dict (77f8e7d0-2281-42cc-b39e-d7acc34f5458)\n", + "2025-05-26 06:00:53,445 INFO Starting job - get_dict (65655d5b-ccf4-44bd-8c8d-6e833b329ede)\n", + "2025-05-26 06:00:53,446 INFO Finished job - get_dict (65655d5b-ccf4-44bd-8c8d-6e833b329ede)\n", + "2025-05-26 06:00:53,447 INFO Starting job - get_dict (bc4172ef-be1c-4ad0-86c0-156181da184a)\n", + "2025-05-26 06:00:53,448 INFO Finished job - get_dict (bc4172ef-be1c-4ad0-86c0-156181da184a)\n", + "2025-05-26 06:00:53,449 INFO Starting job - get_dict (46148184-d180-4a07-95f7-31bd43ada4b2)\n", + "2025-05-26 06:00:53,451 INFO Finished job - get_dict (46148184-d180-4a07-95f7-31bd43ada4b2)\n", + "2025-05-26 06:00:53,452 INFO Starting job - calculate_qe (1bae14bc-f3b4-4be4-a504-7c100cf1b54c)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---35e2fba5:00344] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 06:01:03,461 INFO Finished job - calculate_qe (1bae14bc-f3b4-4be4-a504-7c100cf1b54c)\n", + "2025-05-26 06:01:03,462 INFO Starting job - calculate_qe (8c6e7e3c-4acc-4434-b140-ce8c97100240)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---35e2fba5:00355] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 06:01:16,096 INFO Finished job - calculate_qe (8c6e7e3c-4acc-4434-b140-ce8c97100240)\n", + "2025-05-26 06:01:16,097 INFO Starting job - calculate_qe (45156baf-8ffa-4c3f-8da4-6b9121e77306)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---35e2fba5:00366] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 06:01:28,481 INFO Finished job - calculate_qe (45156baf-8ffa-4c3f-8da4-6b9121e77306)\n", + "2025-05-26 06:01:28,482 INFO Starting job - calculate_qe (7662120d-f6da-415a-9da8-5fbcadf166aa)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n", + "[jupyter-pythonworkflow-fl--x---35e2fba5:00378] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 06:01:41,772 INFO Finished job - calculate_qe (7662120d-f6da-415a-9da8-5fbcadf166aa)\n", + "2025-05-26 06:01:41,773 INFO Starting job - calculate_qe (9d38753b-3c9d-40f9-aa27-eceec701734b)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---35e2fba5:00389] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 06:01:54,979 INFO Finished job - calculate_qe (9d38753b-3c9d-40f9-aa27-eceec701734b)\n", + "2025-05-26 06:01:54,980 INFO Starting job - get_list (cd676100-1e89-4293-a77f-7ca752f228cd)\n", + "2025-05-26 06:01:54,983 INFO Finished job - get_list (cd676100-1e89-4293-a77f-7ca752f228cd)\n", + "2025-05-26 06:01:54,984 INFO Starting job - get_list (44aeb1e8-6af4-4b97-8345-fc78009db91c)\n", + "2025-05-26 06:01:54,987 INFO Finished job - get_list (44aeb1e8-6af4-4b97-8345-fc78009db91c)\n", + "2025-05-26 06:01:54,987 INFO Starting job - plot_energy_volume_curve (09bec337-1bd0-434d-a322-14b6485445bf)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "2025-05-26 06:01:55,044 INFO Finished job - plot_energy_volume_curve (09bec337-1bd0-434d-a322-14b6485445bf)\n", + "2025-05-26 06:01:55,045 INFO Finished executing jobs locally\n" + ] + }, + { + "data": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "result = run_locally(flow)\n", + "result" + ] + }, + { + "cell_type": "markdown", + "id": "e0c78db2-2ead-45d3-92ed-d087e19952ba", + "metadata": {}, + "source": "## Load Workflow with pyiron_base\n\nFinally, `pyiron_base`'s loader turns the graph into a list of delayed jobs. `.draw()` visualizes the dependency graph and `.pull()` executes the whole chain (relax + 5 strained SCF calculations), after overriding the lattice constant `a`." + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "319f466c-def2-45c3-82ba-fffca5d036db", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from python_workflow_definition.pyiron_base import load_workflow_json" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "ed2e964d-0251-488c-b623-28b794c46703", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + 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generate_structures_4d77d481fc8ea55229ec1ece04d63682 was saved and received the ID: 4\n", + "The job get_dict_83639a473c5a24b39cda4262a11ce660 was saved and received the ID: 5\n", + "The job calculate_qe_bc7507e47b3777418bec8bd6a10e8db9 was saved and received the ID: 6\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---35e2fba5:00423] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job get_dict_8911ea3b715c48fd9e6ebfd933827ad8 was saved and received the ID: 7\n", + "The job calculate_qe_3bf1743787b6db34eb1482e0cb2b49f2 was saved and received the ID: 8\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---35e2fba5:00435] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job get_dict_b30dd89506e55e06e63a020a5033af19 was saved and received the ID: 9\n", + "The job calculate_qe_7fdc96db9da025b4936748f5616be588 was saved and received the ID: 10\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---35e2fba5:00446] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job get_dict_899289e3717fb81edaca9c5c2b5d8f48 was saved and received the ID: 11\n", + "The job calculate_qe_9bb68591280fb0b90a58521fd3c6bc9d was saved and received the ID: 12\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---35e2fba5:00457] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job get_dict_12373ab37ecdba93cf91b2a4c3c016d6 was saved and received the ID: 13\n", + "The job calculate_qe_c41612cee84a2bc87674f7f0720f27af was saved and received the ID: 14\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[jupyter-pythonworkflow-fl--x---35e2fba5:00468] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n", + "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The job get_list_4a53d87f56ee9d519ca6c738ae2cef3f was saved and received the ID: 15\n", + "The job get_list_5a5af7c495c3bd034f3904760535ba3e was saved and received the ID: 16\n", + "The job plot_energy_volume_curve_aea478ca6598efbe0596a61e39e1154d was saved and received the ID: 17\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "delayed_object_lst[-1].pull()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "92a9efbb-b592-4888-a2a4-310acde774c9", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.8" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/_sources/example_workflows/quantum_espresso/universal_workflow.ipynb b/_sources/example_workflows/quantum_espresso/universal_workflow.ipynb new file mode 100644 index 00000000..6e834b72 --- /dev/null +++ b/_sources/example_workflows/quantum_espresso/universal_workflow.ipynb @@ -0,0 +1,505 @@ +{ + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.12.8", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + } + }, + "nbformat_minor": 4, + "nbformat": 4, + "cells": [ + { + "cell_type": "markdown", + "source": "# Load Quantum Espresso Energy Volume Curve Workflow\n\nThis notebook loads the same, already-exported [`workflow.json`](workflow.json) with six different backends in turn - `aiida-workgraph`, `executorlib`, `jobflow`, `pyiron_base`, `pyiron_workflow` and plain Python - to demonstrate that the PWD format is interoperable regardless of which engine originally produced it.", + "metadata": {} + }, + { + "cell_type": "markdown", + "source": "## Plot\n\n`python_workflow_definition.plot.plot` renders the raw node/edge structure of `workflow.json` as a graph, independent of any workflow engine - useful to inspect the relax -> strain -> 5x scf -> plot pipeline before executing it.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.plot import plot", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 1 + }, + { + "cell_type": "code", + "source": "plot(file_name='workflow.json')", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "", + "image/svg+xml": "\n\n\n\n\n0\n\nworkflow.get_bulk_structure\n\n\n\n13\n\npython_workflow_definition.shared.get_dict\n\n\n\n0->13\n\n\nstructure\n\n\n\n1\n\nworkflow.calculate_qe\n\n\n\n13->1\n\n\ninput_dict\n\n\n\n2\n\nworkflow.generate_structures\n\n\n\n1->2\n\n\nstructure=result[structure]\n\n\n\n20\n\npython_workflow_definition.shared.get_dict\n\n\n\n2->20\n\n\nstructure=result[s_0]\n\n\n\n23\n\npython_workflow_definition.shared.get_dict\n\n\n\n2->23\n\n\nstructure=result[s_1]\n\n\n\n25\n\npython_workflow_definition.shared.get_dict\n\n\n\n2->25\n\n\nstructure=result[s_2]\n\n\n\n27\n\npython_workflow_definition.shared.get_dict\n\n\n\n2->27\n\n\nstructure=result[s_3]\n\n\n\n29\n\npython_workflow_definition.shared.get_dict\n\n\n\n2->29\n\n\nstructure=result[s_4]\n\n\n\n3\n\nworkflow.calculate_qe\n\n\n\n20->3\n\n\ninput_dict\n\n\n\n4\n\nworkflow.calculate_qe\n\n\n\n23->4\n\n\ninput_dict\n\n\n\n5\n\nworkflow.calculate_qe\n\n\n\n25->5\n\n\ninput_dict\n\n\n\n6\n\nworkflow.calculate_qe\n\n\n\n27->6\n\n\ninput_dict\n\n\n\n7\n\nworkflow.calculate_qe\n\n\n\n29->7\n\n\ninput_dict\n\n\n\n30\n\npython_workflow_definition.shared.get_list\n\n\n\n3->30\n\n\n0=result[volume]\n\n\n\n31\n\npython_workflow_definition.shared.get_list\n\n\n\n3->31\n\n\n0=result[energy]\n\n\n\n8\n\nworkflow.plot_energy_volume_curve\n\n\n\n30->8\n\n\nvolume_lst\n\n\n\n31->8\n\n\nenergy_lst\n\n\n\n4->30\n\n\n1=result[volume]\n\n\n\n4->31\n\n\n1=result[energy]\n\n\n\n5->30\n\n\n2=result[volume]\n\n\n\n5->31\n\n\n2=result[energy]\n\n\n\n6->30\n\n\n3=result[volume]\n\n\n\n6->31\n\n\n3=result[energy]\n\n\n\n7->30\n\n\n4=result[volume]\n\n\n\n7->31\n\n\n4=result[energy]\n\n\n\n32\n\nresult\n\n\n\n8->32\n\n\n\n\n\n9\n\nAl\n\n\n\n9->0\n\n\nelement\n\n\n\n10\n\n4.05\n\n\n\n10->0\n\n\na\n\n\n\n11\n\nTrue\n\n\n\n11->0\n\n\ncubic\n\n\n\n12\n\nmini\n\n\n\n12->1\n\n\nworking_directory\n\n\n\n14\n\n{'Al': 'Al.pbe-n-kjpaw_psl.1.0.0.UPF'}\n\n\n\n14->13\n\n\npseudopotentials\n\n\n\n14->20\n\n\npseudopotentials\n\n\n\n14->23\n\n\npseudopotentials\n\n\n\n14->25\n\n\npseudopotentials\n\n\n\n14->27\n\n\npseudopotentials\n\n\n\n14->29\n\n\npseudopotentials\n\n\n\n15\n\n[3, 3, 3]\n\n\n\n15->13\n\n\nkpts\n\n\n\n15->20\n\n\nkpts\n\n\n\n15->23\n\n\nkpts\n\n\n\n15->25\n\n\nkpts\n\n\n\n15->27\n\n\nkpts\n\n\n\n15->29\n\n\nkpts\n\n\n\n16\n\nvc-relax\n\n\n\n16->13\n\n\ncalculation\n\n\n\n17\n\n0.02\n\n\n\n17->13\n\n\nsmearing\n\n\n\n17->20\n\n\nsmearing\n\n\n\n17->23\n\n\nsmearing\n\n\n\n17->25\n\n\nsmearing\n\n\n\n17->27\n\n\nsmearing\n\n\n\n17->29\n\n\nsmearing\n\n\n\n18\n\n[0.9, 0.95, 1.0, 1.05, 1.1]\n\n\n\n18->2\n\n\nstrain_lst\n\n\n\n19\n\nstrain_0\n\n\n\n19->3\n\n\nworking_directory\n\n\n\n21\n\nscf\n\n\n\n21->20\n\n\ncalculation\n\n\n\n21->23\n\n\ncalculation\n\n\n\n21->25\n\n\ncalculation\n\n\n\n21->27\n\n\ncalculation\n\n\n\n21->29\n\n\ncalculation\n\n\n\n22\n\nstrain_1\n\n\n\n22->4\n\n\nworking_directory\n\n\n\n24\n\nstrain_2\n\n\n\n24->5\n\n\nworking_directory\n\n\n\n26\n\nstrain_3\n\n\n\n26->6\n\n\nworking_directory\n\n\n\n28\n\nstrain_4\n\n\n\n28->7\n\n\nworking_directory\n\n\n" + }, + "metadata": {} + } + ], + "execution_count": 2 + }, + { + "cell_type": "markdown", + "source": "## Aiida\n\n`load_workflow_json` reconstructs the graph as an `aiida-workgraph` `WorkGraph`, after connecting to the local AiiDA profile with `load_profile()`. `wg.run()` executes the relax step followed by the 5 parallel strained SCF calculations and the final plot.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.aiida import load_workflow_json\nfrom aiida import load_profile\nload_profile()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 3, + "output_type": "execute_result", + "data": { + "text/plain": "Profile" + }, + "metadata": {} + } + ], + "execution_count": 3 + }, + { + "cell_type": "code", + "source": "wg = load_workflow_json(file_name='workflow.json')", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 4 + }, + { + "cell_type": "code", + "source": "wg", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 5, + "output_type": "execute_result", + "data": { + "text/plain": "NodeGraphWidget(settings={'minimap': True}, style={'width': '90%', 'height': '600px'}, value={'name': 'WorkGra…", + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 1, + "model_id": "ee61bd4c7d90449593a86d50e9eb6acc" + } + }, + "metadata": {} + } + ], + "execution_count": 5 + }, + { + "cell_type": "code", + "source": "wg.run()\n", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "05/24/2025 06:05:21 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_bulk_structure1\n05/24/2025 06:05:21 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: get_bulk_structure1, type: PyFunction, finished.\n05/24/2025 06:05:21 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict10\n05/24/2025 06:05:22 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: get_dict10, type: PyFunction, finished.\n05/24/2025 06:05:22 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe2\n[jupyter-pythonworkflow-fl--x---d7231032:10748] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n05/24/2025 06:06:12 AM <10674> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['energy', 'volume'])\n05/24/2025 06:06:12 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: calculate_qe2, type: PyFunction, finished.\n05/24/2025 06:06:12 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: generate_structures3\n05/24/2025 06:06:13 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: generate_structures3, type: PyFunction, finished.\n05/24/2025 06:06:13 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict11,get_dict12,get_dict13,get_dict14,get_dict15\n05/24/2025 06:06:14 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: get_dict11, type: PyFunction, finished.\n05/24/2025 06:06:14 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe4,get_dict12,get_dict13,get_dict14,get_dict15\n[jupyter-pythonworkflow-fl--x---d7231032:10760] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n05/24/2025 06:06:24 AM <10674> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n05/24/2025 06:06:24 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: calculate_qe4, type: PyFunction, finished.\n05/24/2025 06:06:24 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict12,get_dict13,get_dict14,get_dict15\n05/24/2025 06:06:25 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: get_dict12, type: PyFunction, finished.\n05/24/2025 06:06:25 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe5,get_dict13,get_dict14,get_dict15\n[jupyter-pythonworkflow-fl--x---d7231032:10770] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n05/24/2025 06:06:36 AM <10674> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n05/24/2025 06:06:36 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: calculate_qe5, type: PyFunction, finished.\n05/24/2025 06:06:36 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict13,get_dict14,get_dict15\n05/24/2025 06:06:37 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: get_dict13, type: PyFunction, finished.\n05/24/2025 06:06:37 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe6,get_dict14,get_dict15\n[jupyter-pythonworkflow-fl--x---d7231032:10781] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n05/24/2025 06:06:49 AM <10674> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n05/24/2025 06:06:49 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: calculate_qe6, type: PyFunction, finished.\n05/24/2025 06:06:49 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict14,get_dict15\n05/24/2025 06:06:50 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: get_dict14, type: PyFunction, finished.\n05/24/2025 06:06:50 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe7,get_dict15\n[jupyter-pythonworkflow-fl--x---d7231032:10792] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n05/24/2025 06:07:05 AM <10674> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n05/24/2025 06:07:06 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: calculate_qe7, type: PyFunction, finished.\n05/24/2025 06:07:06 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_dict15\n05/24/2025 06:07:06 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: get_dict15, type: PyFunction, finished.\n05/24/2025 06:07:06 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: calculate_qe8\n[jupyter-pythonworkflow-fl--x---d7231032:10804] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n05/24/2025 06:07:21 AM <10674> aiida.orm.nodes.process.calculation.calcfunction.CalcFunctionNode: [WARNING] Found extra results that are not included in the output: dict_keys(['structure'])\n05/24/2025 06:07:21 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: calculate_qe8, type: PyFunction, finished.\n05/24/2025 06:07:21 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_list16,get_list17\n05/24/2025 06:07:22 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: get_list16, type: PyFunction, finished.\n05/24/2025 06:07:22 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: get_list17\n05/24/2025 06:07:22 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: get_list17, type: PyFunction, finished.\n05/24/2025 06:07:22 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: plot_energy_volume_curve9\n05/24/2025 06:07:23 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|update_task_state]: Task: plot_energy_volume_curve9, type: PyFunction, finished.\n05/24/2025 06:07:23 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|continue_workgraph]: tasks ready to run: \n05/24/2025 06:07:23 AM <10674> aiida.orm.nodes.process.workflow.workchain.WorkChainNode: [REPORT] [342|WorkGraphEngine|finalize]: Finalize workgraph.\n" + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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" + }, + "metadata": {} + } + ], + "execution_count": 6 + }, + { + "cell_type": "markdown", + "source": "## executorlib\n\nHere `load_workflow_json` takes a live `exe` (a `SingleNodeExecutor`) and submits the whole graph to it, returning a `Future` for the final result; `.result()` blocks until every node - including the 5 fanned-out SCF calculations - has finished executing.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from executorlib import SingleNodeExecutor", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 7 + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.executorlib import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 8 + }, + { + "cell_type": "code", + "source": "with SingleNodeExecutor(max_workers=1) as exe:\n result = load_workflow_json(file_name=\"workflow.json\", exe=exe).result()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "[jupyter-pythonworkflow-fl--x---d7231032:10932] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-pythonworkflow-fl--x---d7231032:11164] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-pythonworkflow-fl--x---d7231032:11230] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-pythonworkflow-fl--x---d7231032:11301] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-pythonworkflow-fl--x---d7231032:11367] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-pythonworkflow-fl--x---d7231032:11433] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + } + ], + "execution_count": 9 + }, + { + "cell_type": "code", + "source": "result", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 10 + }, + { + "cell_type": "markdown", + "source": "## jobflow\n\nThe graph is loaded as a `jobflow` `Flow` and executed locally with `run_locally`, which runs the relax job, the 5 strained SCF jobs and the plotting job in dependency order.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from jobflow.managers.local import run_locally", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 11 + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.jobflow import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 12 + }, + { + "cell_type": "code", + "source": "flow = load_workflow_json(file_name=\"workflow.json\")", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 13 + }, + { + "cell_type": "code", + "source": "result = run_locally(flow)\nresult", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "2025-05-24 06:11:19,085 INFO Started executing jobs locally\n2025-05-24 06:11:19,088 INFO Starting job - get_bulk_structure (13fb19e6-ff0a-4b2e-9cdd-391f43580ede)\n2025-05-24 06:11:19,091 INFO Finished job - get_bulk_structure (13fb19e6-ff0a-4b2e-9cdd-391f43580ede)\n2025-05-24 06:11:19,091 INFO Starting job - get_dict (9d93f23c-2f31-4943-95eb-c30d527e0a7c)\n2025-05-24 06:11:19,093 INFO Finished job - get_dict (9d93f23c-2f31-4943-95eb-c30d527e0a7c)\n2025-05-24 06:11:19,093 INFO Starting job - calculate_qe (031ec4f2-37b7-4837-941d-943eb1a3a36f)\n" + }, + { + "name": "stderr", + "output_type": "stream", + "text": "[jupyter-pythonworkflow-fl--x---d7231032:12088] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + }, + { + "name": "stdout", + "output_type": "stream", + "text": "2025-05-24 06:12:09,004 INFO Finished job - calculate_qe (031ec4f2-37b7-4837-941d-943eb1a3a36f)\n2025-05-24 06:12:09,005 INFO Starting job - generate_structures (c26bc0f8-4833-4913-ae54-676004a2cee5)\n2025-05-24 06:12:09,009 INFO Finished job - generate_structures (c26bc0f8-4833-4913-ae54-676004a2cee5)\n2025-05-24 06:12:09,009 INFO Starting job - get_dict (d68d9722-53d8-489e-b3dd-831637c677ce)\n2025-05-24 06:12:09,011 INFO Finished job - get_dict (d68d9722-53d8-489e-b3dd-831637c677ce)\n2025-05-24 06:12:09,011 INFO Starting job - get_dict (a2a5e5ca-2862-48d4-a3d2-3090bc48ee44)\n2025-05-24 06:12:09,013 INFO Finished job - get_dict (a2a5e5ca-2862-48d4-a3d2-3090bc48ee44)\n2025-05-24 06:12:09,014 INFO Starting job - get_dict (752bccfa-8200-4fee-bcae-799506e75b3f)\n2025-05-24 06:12:09,015 INFO Finished job - get_dict (752bccfa-8200-4fee-bcae-799506e75b3f)\n2025-05-24 06:12:09,016 INFO Starting job - get_dict (8f26bac2-370b-431a-8e67-16205b118a8e)\n2025-05-24 06:12:09,017 INFO Finished job - get_dict (8f26bac2-370b-431a-8e67-16205b118a8e)\n2025-05-24 06:12:09,018 INFO Starting job - get_dict (86078da3-b1d1-47e5-98b6-666c8d1c925f)\n2025-05-24 06:12:09,019 INFO Finished job - get_dict (86078da3-b1d1-47e5-98b6-666c8d1c925f)\n2025-05-24 06:12:09,020 INFO Starting job - calculate_qe (8bf26748-191f-48c0-b55a-3c00dc23cbd4)\n" + }, + { + "name": "stderr", + "output_type": "stream", + "text": "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-pythonworkflow-fl--x---d7231032:12101] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + }, + { + "name": "stdout", + "output_type": "stream", + "text": "2025-05-24 06:12:19,833 INFO Finished job - calculate_qe (8bf26748-191f-48c0-b55a-3c00dc23cbd4)\n2025-05-24 06:12:19,834 INFO Starting job - calculate_qe (e248cdb3-3984-4c9e-8ed9-2d8ea4d0053b)\n" + }, + { + "name": "stderr", + "output_type": "stream", + "text": "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-pythonworkflow-fl--x---d7231032:12111] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + }, + { + "name": "stdout", + "output_type": "stream", + "text": "2025-05-24 06:12:30,295 INFO Finished job - calculate_qe (e248cdb3-3984-4c9e-8ed9-2d8ea4d0053b)\n2025-05-24 06:12:30,296 INFO Starting job - calculate_qe (b99732df-2c29-471a-a9dd-b43cf0765295)\n" + }, + { + "name": "stderr", + "output_type": "stream", + "text": "[jupyter-pythonworkflow-fl--x---d7231032:12121] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + }, + { + "name": "stdout", + "output_type": "stream", + "text": "2025-05-24 06:12:42,189 INFO Finished job - calculate_qe (b99732df-2c29-471a-a9dd-b43cf0765295)\n2025-05-24 06:12:42,189 INFO Starting job - calculate_qe (5316d29c-cdf2-4a43-934d-02518422acf5)\n" + }, + { + "name": "stderr", + "output_type": "stream", + "text": "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-pythonworkflow-fl--x---d7231032:12131] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + }, + { + "name": "stdout", + "output_type": "stream", + "text": "2025-05-24 06:12:55,607 INFO Finished job - calculate_qe (5316d29c-cdf2-4a43-934d-02518422acf5)\n2025-05-24 06:12:55,608 INFO Starting job - calculate_qe (dc161c3a-22d0-456d-9a79-bc0126f7296b)\n" + }, + { + "name": "stderr", + "output_type": "stream", + "text": "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-pythonworkflow-fl--x---d7231032:12141] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + }, + { + "name": "stdout", + "output_type": "stream", + "text": "2025-05-24 06:13:09,051 INFO Finished job - calculate_qe (dc161c3a-22d0-456d-9a79-bc0126f7296b)\n2025-05-24 06:13:09,052 INFO Starting job - get_list (a23aaea4-d7dc-4223-bedc-213cbf38f436)\n2025-05-24 06:13:09,054 INFO Finished job - get_list (a23aaea4-d7dc-4223-bedc-213cbf38f436)\n2025-05-24 06:13:09,055 INFO Starting job - get_list (09e90050-8621-403e-8f78-c50a7180f23c)\n2025-05-24 06:13:09,057 INFO Finished job - get_list (09e90050-8621-403e-8f78-c50a7180f23c)\n2025-05-24 06:13:09,058 INFO Starting job - plot_energy_volume_curve (1e007ae5-e596-4e71-baa0-7ac7a604a5fd)\n" + }, + { + "name": "stderr", + "output_type": "stream", + "text": "Note: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + }, + { + "name": "stdout", + "output_type": "stream", + "text": "2025-05-24 06:13:09,114 INFO Finished job - plot_energy_volume_curve (1e007ae5-e596-4e71-baa0-7ac7a604a5fd)\n2025-05-24 06:13:09,115 INFO Finished executing jobs locally\n" + }, + { + "execution_count": 14, + "output_type": "execute_result", + "data": { + "text/plain": "{'13fb19e6-ff0a-4b2e-9cdd-391f43580ede': {1: Response(output='{\"immutable_id\": null, \"last_modified\": null, \"elements\": [\"Al\"], \"nelements\": 1, \"elements_ratios\": [1.0], \"chemical_formula_descriptive\": \"Al4\", \"chemical_formula_reduced\": \"Al\", \"chemical_formula_hill\": null, \"chemical_formula_anonymous\": \"A\", \"dimension_types\": [1, 1, 1], \"nperiodic_dimensions\": 3, \"lattice_vectors\": [[4.05, 0.0, 0.0], [0.0, 4.05, 0.0], [0.0, 0.0, 4.05]], \"space_group_symmetry_operations_xyz\": null, \"space_group_symbol_hall\": null, \"space_group_symbol_hermann_mauguin\": null, \"space_group_symbol_hermann_mauguin_extended\": null, \"space_group_it_number\": null, \"cartesian_site_positions\": [[0.0, 0.0, 0.0], [0.0, 2.025, 2.025], [2.025, 0.0, 2.025], [2.025, 2.025, 0.0]], \"nsites\": 4, \"species\": [{\"name\": \"Al\", 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" + }, + "metadata": {} + } + ], + "execution_count": 14 + }, + { + "cell_type": "markdown", + "source": "## pyiron_base\n\n`load_workflow_json` turns the graph into a list of delayed pyiron jobs; `.draw()` visualizes the dependency graph (including the fan-out into 5 strained SCF jobs) and `.pull()` executes the whole chain.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.pyiron_base import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 15 + }, + { + "cell_type": "code", + "source": "delayed_object_lst = load_workflow_json(file_name=\"workflow.json\")\ndelayed_object_lst[-1].draw()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "", + "image/svg+xml": "\n\n\n\n\ncreate_function_job_9adf79b116ef7d1bd6234b8bd3fb8790\n\ncreate_function_job=<pyiron_base.project.delayed.DelayedObject object at 0x768578177f50>\n\n\n\nvolume_lst_9ecc37695722ff26a909e7df66fad761\n\nvolume_lst=<pyiron_base.project.delayed.DelayedObject object at 0x768578177ec0>\n\n\n\nvolume_lst_9ecc37695722ff26a909e7df66fad761->create_function_job_9adf79b116ef7d1bd6234b8bd3fb8790\n\n\n\n\n\n0_9ec2b766eb40591013f27b281c10fdf6\n\n0=<pyiron_base.project.delayed.DelayedObject object at 0x7685781761e0>\n\n\n\n0_9ec2b766eb40591013f27b281c10fdf6->volume_lst_9ecc37695722ff26a909e7df66fad761\n\n\n\n\n\nworking_directory_2e9abb255f1a31f7d29b4451ad422add\n\nworking_directory=strain_0\n\n\n\nworking_directory_2e9abb255f1a31f7d29b4451ad422add->0_9ec2b766eb40591013f27b281c10fdf6\n\n\n\n\n\n0_2ee29abc84e19e2a89c493d954bca047\n\n0=<pyiron_base.project.delayed.DelayedObject object at 0x768578177470>\n\n\n\nworking_directory_2e9abb255f1a31f7d29b4451ad422add->0_2ee29abc84e19e2a89c493d954bca047\n\n\n\n\n\nenergy_lst_d41078de6fda3484043c8f3407845d97\n\nenergy_lst=<pyiron_base.project.delayed.DelayedObject object at 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0x768578177020>\n\n\n\nstructure_02eea1a3dae4b8a2111c575ca7b757e4->input_dict_adda488913baad1684ada5811fc1bf07\n\n\n\n\n\ninput_dict_d5e1009e9a3698a7a581d7920d3308ba\n\ninput_dict=<pyiron_base.project.delayed.DelayedObject object at 0x768578176d20>\n\n\n\nstructure_f70fbf61dbacde3f86dbc99a31f544d6->input_dict_d5e1009e9a3698a7a581d7920d3308ba\n\n\n\n\n\ninput_dict_e4951879c0adfc1ee95c3f213d3670aa\n\ninput_dict=<pyiron_base.project.delayed.DelayedObject object at 0x7685781769f0>\n\n\n\nstructure_5bb5ba75f27ad166411ec7f96a67d795->input_dict_e4951879c0adfc1ee95c3f213d3670aa\n\n\n\n\n\ninput_dict_a404d97e273a3ac600efe8c07b153592\n\ninput_dict=<pyiron_base.project.delayed.DelayedObject object at 0x7685781766c0>\n\n\n\nstructure_2a68a68e8c70db7870ac8e42f8b1865d->input_dict_a404d97e273a3ac600efe8c07b153592\n\n\n\n\n\nworking_directory_a17ade9a563d8dcadb655fb2e1c743a7\n\nworking_directory=mini\n\n\n\nworking_directory_a17ade9a563d8dcadb655fb2e1c743a7->structure_199228a058c6c2abd4059cca704f33e6\n\n\n\n\n\ninput_dict_537467c3235749e6bbce7787ac63fcf2\n\ninput_dict=<pyiron_base.project.delayed.DelayedObject object at 0x768578175910>\n\n\n\ninput_dict_537467c3235749e6bbce7787ac63fcf2->structure_199228a058c6c2abd4059cca704f33e6\n\n\n\n\n\nstructure_1143d046335e4294dac52196bc2767db\n\nstructure=<pyiron_base.project.delayed.DelayedObject object at 0x768578175b50>\n\n\n\nstructure_1143d046335e4294dac52196bc2767db->input_dict_537467c3235749e6bbce7787ac63fcf2\n\n\n\n\n\nelement_467734216d9bd2497ffd28d5cd6daba0\n\nelement=Al\n\n\n\nelement_467734216d9bd2497ffd28d5cd6daba0->structure_1143d046335e4294dac52196bc2767db\n\n\n\n\n\na_aea0574e321c6f75f923c059730e9537\n\na=4.05\n\n\n\na_aea0574e321c6f75f923c059730e9537->structure_1143d046335e4294dac52196bc2767db\n\n\n\n\n\ncubic_bad787c53fa02a5559fe570238fdb23a\n\ncubic=True\n\n\n\ncubic_bad787c53fa02a5559fe570238fdb23a->structure_1143d046335e4294dac52196bc2767db\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10\n\npseudopotentials={'Al': 'Al.pbe-n-kjpaw_psl.1.0.0.UPF'}\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_87f4e1381ab79d513e7ddd2deecdd386\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_537467c3235749e6bbce7787ac63fcf2\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_adda488913baad1684ada5811fc1bf07\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_d5e1009e9a3698a7a581d7920d3308ba\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_e4951879c0adfc1ee95c3f213d3670aa\n\n\n\n\n\npseudopotentials_453cdcc0d627a851e196cd899d956d10->input_dict_a404d97e273a3ac600efe8c07b153592\n\n\n\n\n\n1_191bdde6d29a8110f9185c2dc2f36d40\n\n1=<pyiron_base.project.delayed.DelayedObject object at 0x768578176210>\n\n\n\ninput_dict_adda488913baad1684ada5811fc1bf07->1_191bdde6d29a8110f9185c2dc2f36d40\n\n\n\n\n\n1_4fc4ea22f90e9c5395aebcd832723a0b\n\n1=<pyiron_base.project.delayed.DelayedObject object at 0x768578177740>\n\n\n\ninput_dict_adda488913baad1684ada5811fc1bf07->1_4fc4ea22f90e9c5395aebcd832723a0b\n\n\n\n\n\n2_19f8c443d3f233fce65b180b8671f9d3\n\n2=<pyiron_base.project.delayed.DelayedObject object at 0x768578176810>\n\n\n\ninput_dict_d5e1009e9a3698a7a581d7920d3308ba->2_19f8c443d3f233fce65b180b8671f9d3\n\n\n\n\n\n2_a91f85ab07dda5e77e64539693175399\n\n2=<pyiron_base.project.delayed.DelayedObject object at 0x7685781771a0>\n\n\n\ninput_dict_d5e1009e9a3698a7a581d7920d3308ba->2_a91f85ab07dda5e77e64539693175399\n\n\n\n\n\n3_3ede2f537cf839143078e1512ff2ef2f\n\n3=<pyiron_base.project.delayed.DelayedObject object at 0x7685781759d0>\n\n\n\ninput_dict_e4951879c0adfc1ee95c3f213d3670aa->3_3ede2f537cf839143078e1512ff2ef2f\n\n\n\n\n\n3_5d8eeb1260eb131e15c0788d790e6449\n\n3=<pyiron_base.project.delayed.DelayedObject object at 0x768578176ed0>\n\n\n\ninput_dict_e4951879c0adfc1ee95c3f213d3670aa->3_5d8eeb1260eb131e15c0788d790e6449\n\n\n\n\n\n4_25a83d640c1b83e1d1be6ab4ab2fe22d\n\n4=<pyiron_base.project.delayed.DelayedObject object at 0x768578177c50>\n\n\n\ninput_dict_a404d97e273a3ac600efe8c07b153592->4_25a83d640c1b83e1d1be6ab4ab2fe22d\n\n\n\n\n\n4_24178a0d53ab74cdcd2d82759a89311b\n\n4=<pyiron_base.project.delayed.DelayedObject object at 0x768578177140>\n\n\n\ninput_dict_a404d97e273a3ac600efe8c07b153592->4_24178a0d53ab74cdcd2d82759a89311b\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa\n\nkpts=[3, 3, 3]\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_87f4e1381ab79d513e7ddd2deecdd386\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_537467c3235749e6bbce7787ac63fcf2\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_adda488913baad1684ada5811fc1bf07\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_d5e1009e9a3698a7a581d7920d3308ba\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_e4951879c0adfc1ee95c3f213d3670aa\n\n\n\n\n\nkpts_e961a9390797b0f6f8887a402ea3e9aa->input_dict_a404d97e273a3ac600efe8c07b153592\n\n\n\n\n\ncalculation_77b75a01e65d83962d14fa8a882d6c34\n\ncalculation=vc-relax\n\n\n\ncalculation_77b75a01e65d83962d14fa8a882d6c34->input_dict_537467c3235749e6bbce7787ac63fcf2\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9\n\nsmearing=0.02\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_87f4e1381ab79d513e7ddd2deecdd386\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_537467c3235749e6bbce7787ac63fcf2\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_adda488913baad1684ada5811fc1bf07\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_d5e1009e9a3698a7a581d7920d3308ba\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_e4951879c0adfc1ee95c3f213d3670aa\n\n\n\n\n\nsmearing_64a632a7e5bfbb7d0c6face9b82082a9->input_dict_a404d97e273a3ac600efe8c07b153592\n\n\n\n\n\nstrain_lst_2d8c38dac8f1aeeeecfa3c0b1cc8a781\n\nstrain_lst=[0.9, 0.95, 1.0, 1.05, 1.1]\n\n\n\nstrain_lst_2d8c38dac8f1aeeeecfa3c0b1cc8a781->structure_24283480cde4a82cb11a95ad8315004b\n\n\n\n\n\nstrain_lst_2d8c38dac8f1aeeeecfa3c0b1cc8a781->structure_02eea1a3dae4b8a2111c575ca7b757e4\n\n\n\n\n\nstrain_lst_2d8c38dac8f1aeeeecfa3c0b1cc8a781->structure_f70fbf61dbacde3f86dbc99a31f544d6\n\n\n\n\n\nstrain_lst_2d8c38dac8f1aeeeecfa3c0b1cc8a781->structure_5bb5ba75f27ad166411ec7f96a67d795\n\n\n\n\n\nstrain_lst_2d8c38dac8f1aeeeecfa3c0b1cc8a781->structure_2a68a68e8c70db7870ac8e42f8b1865d\n\n\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83\n\ncalculation=scf\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83->input_dict_87f4e1381ab79d513e7ddd2deecdd386\n\n\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83->input_dict_adda488913baad1684ada5811fc1bf07\n\n\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83->input_dict_d5e1009e9a3698a7a581d7920d3308ba\n\n\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83->input_dict_e4951879c0adfc1ee95c3f213d3670aa\n\n\n\n\n\ncalculation_bc91e0ce7227762f507f47b85f2f0a83->input_dict_a404d97e273a3ac600efe8c07b153592\n\n\n\n\n\n1_191bdde6d29a8110f9185c2dc2f36d40->volume_lst_9ecc37695722ff26a909e7df66fad761\n\n\n\n\n\nworking_directory_5423d2cc67129a6d0383af6f347df5bd\n\nworking_directory=strain_1\n\n\n\nworking_directory_5423d2cc67129a6d0383af6f347df5bd->1_191bdde6d29a8110f9185c2dc2f36d40\n\n\n\n\n\nworking_directory_5423d2cc67129a6d0383af6f347df5bd->1_4fc4ea22f90e9c5395aebcd832723a0b\n\n\n\n\n\n1_4fc4ea22f90e9c5395aebcd832723a0b->energy_lst_d41078de6fda3484043c8f3407845d97\n\n\n\n\n\n2_19f8c443d3f233fce65b180b8671f9d3->volume_lst_9ecc37695722ff26a909e7df66fad761\n\n\n\n\n\nworking_directory_cc646e064ddfc4b2811aba3d86d27992\n\nworking_directory=strain_2\n\n\n\nworking_directory_cc646e064ddfc4b2811aba3d86d27992->2_19f8c443d3f233fce65b180b8671f9d3\n\n\n\n\n\nworking_directory_cc646e064ddfc4b2811aba3d86d27992->2_a91f85ab07dda5e77e64539693175399\n\n\n\n\n\n2_a91f85ab07dda5e77e64539693175399->energy_lst_d41078de6fda3484043c8f3407845d97\n\n\n\n\n\n3_3ede2f537cf839143078e1512ff2ef2f->volume_lst_9ecc37695722ff26a909e7df66fad761\n\n\n\n\n\nworking_directory_e27768d53df6cd8dc245c52054ecf31f\n\nworking_directory=strain_3\n\n\n\nworking_directory_e27768d53df6cd8dc245c52054ecf31f->3_3ede2f537cf839143078e1512ff2ef2f\n\n\n\n\n\nworking_directory_e27768d53df6cd8dc245c52054ecf31f->3_5d8eeb1260eb131e15c0788d790e6449\n\n\n\n\n\n3_5d8eeb1260eb131e15c0788d790e6449->energy_lst_d41078de6fda3484043c8f3407845d97\n\n\n\n\n\n4_25a83d640c1b83e1d1be6ab4ab2fe22d->volume_lst_9ecc37695722ff26a909e7df66fad761\n\n\n\n\n\nworking_directory_72bba39b22d2b7ce154d37c7e8c658b7\n\nworking_directory=strain_4\n\n\n\nworking_directory_72bba39b22d2b7ce154d37c7e8c658b7->4_25a83d640c1b83e1d1be6ab4ab2fe22d\n\n\n\n\n\nworking_directory_72bba39b22d2b7ce154d37c7e8c658b7->4_24178a0d53ab74cdcd2d82759a89311b\n\n\n\n\n\n4_24178a0d53ab74cdcd2d82759a89311b->energy_lst_d41078de6fda3484043c8f3407845d97\n\n\n\n\n\nenergy_lst_d41078de6fda3484043c8f3407845d97->create_function_job_9adf79b116ef7d1bd6234b8bd3fb8790\n\n\n\n\n" + }, + "metadata": {} + } + ], + "execution_count": 16 + }, + { + "cell_type": "code", + "source": "delayed_object_lst[-1].pull()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "The job get_bulk_structure_2ca4aeae204ceaa28593c93054b07908 was saved and received the ID: 1\nThe job get_dict_1e47509b88d63a21fd421686554c8f4a was saved and received the ID: 2\nThe job calculate_qe_411e578f2700d09ba2df9a4c682b4582 was saved and received the ID: 3\n" + }, + { + "name": "stderr", + "output_type": "stream", + "text": "[jupyter-pythonworkflow-fl--x---d7231032:12175] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + }, + { + "name": "stdout", + "output_type": "stream", + "text": "The job generate_structures_29f44e1952b8f5678d84a2b016899fce was saved and received the ID: 4\nThe job get_dict_ef87933d61756398c7394b1132327107 was saved and received the ID: 5\nThe job calculate_qe_7a90048d1de9ecbd9a0d65912ce16a05 was saved and received the ID: 6\n" + }, + { + "name": "stderr", + "output_type": "stream", + "text": "[jupyter-pythonworkflow-fl--x---d7231032:12194] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + }, + { + "name": "stdout", + "output_type": "stream", + "text": "The job get_dict_8df97e882e2a6b51191dddf174e87731 was saved and received the ID: 7\nThe job calculate_qe_78019c29f3a9ab2782b972a871cf7b97 was saved and received the ID: 8\n" + }, + { + "name": "stderr", + "output_type": "stream", + "text": "[jupyter-pythonworkflow-fl--x---d7231032:12205] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + }, + { + "name": "stdout", + "output_type": "stream", + "text": "The job get_dict_be1c027670e9498836f67834851d04cc was saved and received the ID: 9\nThe job calculate_qe_aaa66ba36e55a9cc577037576b1e6ccb was saved and received the ID: 10\n" + }, + { + "name": "stderr", + "output_type": "stream", + "text": "[jupyter-pythonworkflow-fl--x---d7231032:12216] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + }, + { + "name": "stdout", + "output_type": "stream", + "text": "The job get_dict_52b5c75d597a1c4b528615e1125a0896 was saved and received the ID: 11\nThe job calculate_qe_62d76f231acf9ea944e9c695277ff831 was saved and received the ID: 12\n" + }, + { + "name": "stderr", + "output_type": "stream", + "text": "[jupyter-pythonworkflow-fl--x---d7231032:12227] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + }, + { + "name": "stdout", + "output_type": "stream", + "text": "The job get_dict_1c3ed4191b35cf54ac773bb8172f6947 was saved and received the ID: 13\nThe job calculate_qe_2589d637ad774f38e26fdd2b4529fcca was saved and received the ID: 14\n" + }, + { + "name": "stderr", + "output_type": "stream", + "text": "[jupyter-pythonworkflow-fl--x---d7231032:12237] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + }, + { + "name": "stdout", + "output_type": "stream", + "text": "The job get_list_274bff6e81bec86553cdd07a055e2b5e was saved and received the ID: 15\nThe job get_list_4457d79d3504f678b6f74963dd8f0e4c was saved and received the ID: 16\nThe job plot_energy_volume_curve_33e1f4fbca145ac4d2a72d20544cad9d was saved and received the ID: 17\n" + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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" + }, + "metadata": {} + } + ], + "execution_count": 17 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## Load Workflow with pyiron_workflow\n\nThe graph is loaded into a `pyiron_workflow` `Workflow`, drawn with `.draw()`, and executed with `.run()`." + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "from python_workflow_definition.pyiron_workflow import load_workflow_json" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf = load_workflow_json(file_name=\"workflow.json\")" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.draw(size=(10,10))" + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "wf.run()" + }, + { + "cell_type": "markdown", + "source": "## Python\n\n`python_workflow_definition.purepython.load_workflow_json` is a minimal reference implementation with no external workflow engine: it topologically sorts the nodes by their edges and calls each function directly in plain Python, returning the final result.", + "metadata": {} + }, + { + "cell_type": "code", + "source": "from python_workflow_definition.purepython import load_workflow_json", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 18 + }, + { + "cell_type": "code", + "source": "load_workflow_json(file_name=\"workflow.json\")", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "[jupyter-pythonworkflow-fl--x---d7231032:12248] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-pythonworkflow-fl--x---d7231032:12262] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-pythonworkflow-fl--x---d7231032:12277] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-pythonworkflow-fl--x---d7231032:12289] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-pythonworkflow-fl--x---d7231032:12299] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n[jupyter-pythonworkflow-fl--x---d7231032:12309] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\nNote: The following floating-point exceptions are signalling: IEEE_INVALID_FLAG\n" + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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+ }, + "metadata": {} + } + ], + "execution_count": 19 + } + ] +} \ No newline at end of file diff --git a/_sources/intro.md b/_sources/intro.md new file mode 100644 index 00000000..4ad92284 --- /dev/null +++ b/_sources/intro.md @@ -0,0 +1,24 @@ +# Definition +In the Python Workflow Definition (PWD) each node represents a Python function, with the edges defining the connection +between input and output of the different Python functions. + +## Format +Each workflow consists of three files, a Python module which defines the individual Pythons, a JSON file which defines +the connections between the different Python functions and a conda environment file to define the software dependencies. +The files are not intended to be human readable, but rather interact as a machine readable exchange format between the +different workflow engines to enable interoperability. + +## Workflow Engines +Currently supported workflow engines: +* [aiida-workgraph](https://github.com/aiidateam/aiida-workgraph) +* [jobflow](https://github.com/materialsproject/jobflow) +* [pyiron_base](https://github.com/pyiron/pyiron_base) +* [pyiron_workflow](https://github.com/pyiron/pyiron_workflow) +* [executorlib](https://github.com/pyiron/executorlib) +* [CWL](https://www.commonwl.org/) via [cwltool](https://github.com/common-workflow-language/cwltool) + +## Example Workflows +Three workflows are implemented: +* Simple workflow coupling two python functions +* Calculation of an [energy volume curve with quantum espresso](https://materialdigital.github.io/ADIS2023/) +* File based workflow benchmark from [NFDI4Ing](https://www.inggrid.org/article/id/3726/) diff --git a/_sources/nfdi.md b/_sources/nfdi.md new file mode 100644 index 00000000..1fa6a863 --- /dev/null +++ b/_sources/nfdi.md @@ -0,0 +1,61 @@ +# NFDI4Ing Benchmark +To demonstrate the compatibility of the Python Workflow Definition to file based workflows, the workflow benchmark +developed as part of [NFDI4Ing](https://www.inggrid.org/article/id/3726/) is implemented for all workflow engines +based on the Python Workflow Definition. + +## Workflow +Unlike the [arithmetic](arithmetic.md) and energy-volume-curve examples, which pass Python objects between functions, +this benchmark chains together external command line tools that each require their own conda environment (defined in +`source/envs/*.yaml`) and communicate through files rather than in-memory values. The +pipeline is defined by six Python functions in [workflow.py](example_workflows/nfdi/workflow.py), each of which +copies its inputs into a stage-specific subdirectory (`preprocessing`, `processing` or `postprocessing`) and calls +its external tool with `conda_subprocess.check_output`: +```python +def generate_mesh(domain_size: float, source_directory: str) -> str: ... +def convert_to_xdmf(gmsh_output_file: str) -> dict: ... +def poisson(meshio_output_xdmf: str, meshio_output_h5: str, source_directory: str) -> dict: ... +def plot_over_line(poisson_output_pvd_file: str, poisson_output_vtu_file: str, source_directory: str) -> str: ... +def substitute_macros(pvbatch_output_file: str, ndofs: int, domain_size: float, source_directory: str) -> str: ... +def compile_paper(macros_tex: str, plot_file: str, source_directory: str) -> str: ... +``` +* `generate_mesh` runs [`gmsh`](https://gmsh.info) on `unit_square.geo` to mesh a 2D square whose side length is set + by the `domain_size` parameter, producing a `.msh` file. +* `convert_to_xdmf` runs `meshio convert` to turn the gmsh mesh into an XDMF/H5 file pair that the FEM solver can read. +* `poisson` runs a [FEniCS](https://fenicsproject.org)-based `poisson.py` script that solves the Poisson equation on + the mesh, returning the number of degrees of freedom (`numdofs`) alongside the `.pvd`/`.vtu` result files. +* `plot_over_line` runs ParaView's `pvbatch` with `postprocessing.py` to sample the FEM solution along a line and + write it out as a CSV file. +* `substitute_macros` runs `prepare_paper_macros.py` to fill a LaTeX macro template with the plot data path, the + domain size and the number of degrees of freedom. +* `compile_paper` runs [`tectonic`](https://tectonic-typesetting.github.io) to compile `paper.tex`, which references + those macros and the plot, into `paper.pdf`. + +The connection of these Python functions is stored in the [workflow.json](example_workflows/nfdi/workflow.json) +JSON file, following the same `nodes`/`edges` structure as the other examples. Each function is a `function` node, +`domain_size` and `source_directory` are `input` nodes, and edges connect a function's input port either to another +function's output port or directly to an input node: +``` +{ + "version": "0.1.0", + "nodes": [ + {"id": 0, "type": "function", "value": "workflow.generate_mesh"}, + {"id": 1, "type": "function", "value": "workflow.convert_to_xdmf"}, + {"id": 6, "type": "input", "value": 2.0, "name": "domain_size"}, + {"id": 7, "type": "input", "value": "source", "name": "source_directory"}, + {"id": 8, "type": "output", "name": "result"} + ], + "edges": [ + {"target": 0, "targetPort": "domain_size", "source": 6, "sourcePort": null}, + {"target": 0, "targetPort": "source_directory", "source": 7, "sourcePort": null}, + {"target": 1, "targetPort": "gmsh_output_file", "source": 0, "sourcePort": null} + ] +} +``` +Since `convert_to_xdmf` and `poisson` return a `dict` instead of a single value, the edges that read their output +set `sourcePort` to the specific dictionary key (e.g. `"xdmf_file"` or `"numdofs"`) rather than `null`. + +Because every stage shells out to a different external tool in a different conda environment and passes file paths +along the graph, this benchmark exercises a different part of the Python Workflow Definition than the arithmetic and +energy-volume-curve examples: it shows that the same `workflow.json` produced by one engine can be handed to another +engine, an execution manager like [CWL](https://www.commonwl.org)/`cwltool`, or plain Python, and still reproduce the +same chain of `gmsh`, `meshio`, FEniCS, `pvbatch` and `tectonic` calls end to end. diff --git a/_sphinx_design_static/design-tabs.js b/_sphinx_design_static/design-tabs.js new file mode 100644 index 00000000..b25bd6a4 --- /dev/null +++ b/_sphinx_design_static/design-tabs.js @@ -0,0 +1,101 @@ +// @ts-check + +// Extra JS capability for selected tabs to be synced +// The selection is stored in local storage so that it persists across page 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{ + 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; +} + +.sig dd { + margin-top: 0px; + margin-bottom: 0px; +} + +.sig dl { + margin-top: 0px; + margin-bottom: 0px; +} + +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; +} + +.translated { + background-color: rgba(207, 255, 207, 0.2) +} + +.untranslated { + background-color: rgba(255, 207, 207, 0.2) +} + +/* -- 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/check-solid.svg b/_static/check-solid.svg new file mode 100644 index 00000000..92fad4b5 --- /dev/null +++ b/_static/check-solid.svg @@ -0,0 +1,4 @@ + + + + diff --git a/_static/clipboard.min.js b/_static/clipboard.min.js new file mode 100644 index 00000000..54b3c463 --- /dev/null +++ b/_static/clipboard.min.js @@ -0,0 +1,7 @@ +/*! + * clipboard.js v2.0.8 + * https://clipboardjs.com/ + * + * Licensed MIT © Zeno Rocha + */ +!function(t,e){"object"==typeof exports&&"object"==typeof module?module.exports=e():"function"==typeof define&&define.amd?define([],e):"object"==typeof exports?exports.ClipboardJS=e():t.ClipboardJS=e()}(this,function(){return n={686:function(t,e,n){"use strict";n.d(e,{default:function(){return o}});var e=n(279),i=n.n(e),e=n(370),u=n.n(e),e=n(817),c=n.n(e);function a(t){try{return document.execCommand(t)}catch(t){return}}var f=function(t){t=c()(t);return a("cut"),t};var l=function(t){var e,n,o,r=1 + + + + diff --git a/_static/copybutton.css b/_static/copybutton.css new file mode 100644 index 00000000..f1916ec7 --- /dev/null +++ b/_static/copybutton.css @@ -0,0 +1,94 @@ +/* Copy buttons */ +button.copybtn { + position: absolute; + display: flex; + top: .3em; + right: .3em; + width: 1.7em; + height: 1.7em; + opacity: 0; + transition: opacity 0.3s, border .3s, background-color .3s; + user-select: none; + padding: 0; + border: none; + outline: none; + border-radius: 0.4em; + /* The colors that GitHub uses */ + border: #1b1f2426 1px solid; + background-color: #f6f8fa; + color: #57606a; +} + +button.copybtn.success { + border-color: #22863a; + color: #22863a; +} + +button.copybtn svg { + stroke: currentColor; + width: 1.5em; + height: 1.5em; + padding: 0.1em; +} + +div.highlight { + position: relative; +} + +/* Show the copybutton */ +.highlight:hover button.copybtn, button.copybtn.success { + opacity: 1; +} + +.highlight button.copybtn:hover { + background-color: rgb(235, 235, 235); +} + +.highlight button.copybtn:active { + background-color: rgb(187, 187, 187); +} + +/** + * A minimal CSS-only tooltip copied from: + * https://codepen.io/mildrenben/pen/rVBrpK + * + * To use, write HTML like the following: + * + *

Short

+ */ + .o-tooltip--left { + position: relative; + } + + .o-tooltip--left:after { + opacity: 0; + visibility: hidden; + position: absolute; + content: attr(data-tooltip); + padding: .2em; + font-size: .8em; + left: -.2em; + background: grey; + color: white; + white-space: nowrap; + z-index: 2; + border-radius: 2px; + transform: translateX(-102%) translateY(0); + transition: opacity 0.2s cubic-bezier(0.64, 0.09, 0.08, 1), transform 0.2s cubic-bezier(0.64, 0.09, 0.08, 1); +} + +.o-tooltip--left:hover:after { + display: block; + opacity: 1; + visibility: visible; + transform: translateX(-100%) translateY(0); + transition: opacity 0.2s cubic-bezier(0.64, 0.09, 0.08, 1), transform 0.2s cubic-bezier(0.64, 0.09, 0.08, 1); + transition-delay: .5s; +} + +/* By default the copy button shouldn't show up when printing a page */ +@media print { + button.copybtn { + display: none; + } +} diff --git a/_static/copybutton.js b/_static/copybutton.js new file mode 100644 index 00000000..2ea7ff3e --- /dev/null +++ b/_static/copybutton.js @@ -0,0 +1,248 @@ +// Localization support +const messages = { + 'en': { + 'copy': 'Copy', + 'copy_to_clipboard': 'Copy to clipboard', + 'copy_success': 'Copied!', + 'copy_failure': 'Failed to copy', + }, + 'es' : { + 'copy': 'Copiar', + 'copy_to_clipboard': 'Copiar al portapapeles', + 'copy_success': '¡Copiado!', + 'copy_failure': 'Error al copiar', + }, + 'de' : { + 'copy': 'Kopieren', + 'copy_to_clipboard': 'In die Zwischenablage kopieren', + 'copy_success': 'Kopiert!', + 'copy_failure': 'Fehler beim Kopieren', + }, + 'fr' : { + 'copy': 'Copier', + 'copy_to_clipboard': 'Copier dans le presse-papier', + 'copy_success': 'Copié !', + 'copy_failure': 'Échec de la copie', + }, + 'ru': { + 'copy': 'Скопировать', + 'copy_to_clipboard': 'Скопировать в буфер', + 'copy_success': 'Скопировано!', + 'copy_failure': 'Не удалось скопировать', + }, + 'zh-CN': { + 'copy': '复制', + 'copy_to_clipboard': '复制到剪贴板', + 'copy_success': '复制成功!', + 'copy_failure': '复制失败', + }, + 'it' : { + 'copy': 'Copiare', + 'copy_to_clipboard': 'Copiato negli appunti', + 'copy_success': 'Copiato!', + 'copy_failure': 'Errore durante la copia', + } +} + +let locale = 'en' +if( document.documentElement.lang !== undefined + && messages[document.documentElement.lang] !== undefined ) { + locale = document.documentElement.lang +} + +let doc_url_root = DOCUMENTATION_OPTIONS.URL_ROOT; +if (doc_url_root == '#') { + doc_url_root = ''; +} + +/** + * SVG files for our copy buttons + */ +let iconCheck = ` + ${messages[locale]['copy_success']} + + +` + +// If the user specified their own SVG use that, otherwise use the default +let iconCopy = ``; +if (!iconCopy) { + iconCopy = ` + ${messages[locale]['copy_to_clipboard']} + + + +` +} + +/** + * Set up copy/paste for code blocks + */ + +const runWhenDOMLoaded = cb => { + if (document.readyState != 'loading') { + cb() + } else if (document.addEventListener) { + document.addEventListener('DOMContentLoaded', cb) + } else { + document.attachEvent('onreadystatechange', function() { + if (document.readyState == 'complete') cb() + }) + } +} + +const codeCellId = index => `codecell${index}` + +// Clears selected text since ClipboardJS will select the text when copying +const clearSelection = () => { + if (window.getSelection) { + window.getSelection().removeAllRanges() + } else if (document.selection) { + document.selection.empty() + } +} + +// Changes tooltip text for a moment, then changes it back +// We want the timeout of our `success` class to be a bit shorter than the +// tooltip and icon change, so that we can hide the icon before changing back. +var timeoutIcon = 2000; +var timeoutSuccessClass = 1500; + +const temporarilyChangeTooltip = (el, oldText, newText) => { + el.setAttribute('data-tooltip', newText) + el.classList.add('success') + // Remove success a little bit sooner than we change the tooltip + // So that we can use CSS to hide the copybutton first + setTimeout(() => el.classList.remove('success'), timeoutSuccessClass) + setTimeout(() => el.setAttribute('data-tooltip', oldText), timeoutIcon) +} + +// Changes the copy button icon for two seconds, then changes it back +const temporarilyChangeIcon = (el) => { + el.innerHTML = iconCheck; + setTimeout(() => {el.innerHTML = iconCopy}, timeoutIcon) +} + +const addCopyButtonToCodeCells = () => { + // If ClipboardJS hasn't loaded, wait a bit and try again. This + // happens because we load ClipboardJS asynchronously. + if (window.ClipboardJS === undefined) { + setTimeout(addCopyButtonToCodeCells, 250) + return + } + + // Add copybuttons to all of our code cells + const COPYBUTTON_SELECTOR = 'div.highlight pre'; + const codeCells = document.querySelectorAll(COPYBUTTON_SELECTOR) + codeCells.forEach((codeCell, index) => { + const id = codeCellId(index) + codeCell.setAttribute('id', id) + + const clipboardButton = id => + `` + codeCell.insertAdjacentHTML('afterend', clipboardButton(id)) + }) + +function escapeRegExp(string) { + return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string +} + +/** + * Removes excluded text from a Node. + * + * @param {Node} target Node to filter. + * @param {string} exclude CSS selector of nodes to exclude. + * @returns {DOMString} Text from `target` with text removed. + */ +function filterText(target, exclude) { + const clone = target.cloneNode(true); // clone as to not modify the live DOM + if (exclude) { + // remove excluded nodes + clone.querySelectorAll(exclude).forEach(node => node.remove()); + } + return clone.innerText; +} + +// Callback when a copy button is clicked. Will be passed the node that was clicked +// should then grab the text and replace pieces of text that shouldn't be used in output +function formatCopyText(textContent, copybuttonPromptText, isRegexp = false, onlyCopyPromptLines = true, removePrompts = true, copyEmptyLines = true, lineContinuationChar = "", hereDocDelim = "") { + var regexp; + var match; + + // Do we check for line continuation characters and "HERE-documents"? + var useLineCont = !!lineContinuationChar + var useHereDoc = !!hereDocDelim + + // create regexp to capture prompt and remaining line + if (isRegexp) { + regexp = new RegExp('^(' + copybuttonPromptText + ')(.*)') + } else { + regexp = new RegExp('^(' + escapeRegExp(copybuttonPromptText) + ')(.*)') + } + + const outputLines = []; + var promptFound = false; + var gotLineCont = false; + var gotHereDoc = false; + const lineGotPrompt = []; + for (const line of textContent.split('\n')) { + match = line.match(regexp) + if (match || gotLineCont || gotHereDoc) { + promptFound = regexp.test(line) + lineGotPrompt.push(promptFound) + if (removePrompts && promptFound) { + outputLines.push(match[2]) + } else { + outputLines.push(line) + } + gotLineCont = line.endsWith(lineContinuationChar) & useLineCont + if (line.includes(hereDocDelim) & useHereDoc) + gotHereDoc = !gotHereDoc + } else if (!onlyCopyPromptLines) { + outputLines.push(line) + } else if (copyEmptyLines && line.trim() === '') { + outputLines.push(line) + } + } + + // If no lines with the prompt were found then just use original lines + if (lineGotPrompt.some(v => v === true)) { + textContent = outputLines.join('\n'); + } + + // Remove a trailing newline to avoid auto-running when pasting + if (textContent.endsWith("\n")) { + textContent = textContent.slice(0, -1) + } + return textContent +} + + +var copyTargetText = (trigger) => { + var target = document.querySelector(trigger.attributes['data-clipboard-target'].value); + + // get filtered text + let exclude = '.linenos'; + + let text = filterText(target, exclude); + return formatCopyText(text, '', false, true, true, true, '', '') +} + + // Initialize with a callback so we can modify the text before copy + const clipboard = new ClipboardJS('.copybtn', {text: copyTargetText}) + + // Update UI with error/success messages + clipboard.on('success', event => { + clearSelection() + temporarilyChangeTooltip(event.trigger, messages[locale]['copy'], messages[locale]['copy_success']) + temporarilyChangeIcon(event.trigger) + }) + + clipboard.on('error', event => { + temporarilyChangeTooltip(event.trigger, messages[locale]['copy'], messages[locale]['copy_failure']) + }) +} + +runWhenDOMLoaded(addCopyButtonToCodeCells) \ No newline at end of file diff --git a/_static/copybutton_funcs.js b/_static/copybutton_funcs.js new file mode 100644 index 00000000..dbe1aaad --- /dev/null +++ b/_static/copybutton_funcs.js @@ -0,0 +1,73 @@ +function escapeRegExp(string) { + return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string +} + +/** + * Removes excluded text from a Node. + * + * @param {Node} target Node to filter. + * @param {string} exclude CSS selector of nodes to exclude. + * @returns {DOMString} Text from `target` with text removed. + */ +export function filterText(target, exclude) { + const clone = target.cloneNode(true); // clone as to not modify the live DOM + if (exclude) { + // remove excluded nodes + clone.querySelectorAll(exclude).forEach(node => node.remove()); + } + return clone.innerText; +} + +// Callback when a copy button is clicked. Will be passed the node that was clicked +// should then grab the text and replace pieces of text that shouldn't be used in output +export function formatCopyText(textContent, copybuttonPromptText, isRegexp = false, onlyCopyPromptLines = true, removePrompts = true, copyEmptyLines = true, lineContinuationChar = "", hereDocDelim = "") { + var regexp; + var match; + + // Do we check for line continuation characters and "HERE-documents"? + var useLineCont = !!lineContinuationChar + var useHereDoc = !!hereDocDelim + + // create regexp to capture prompt and remaining line + if (isRegexp) { + regexp = new RegExp('^(' + copybuttonPromptText + ')(.*)') + } else { + regexp = new RegExp('^(' + escapeRegExp(copybuttonPromptText) + ')(.*)') + } + + const outputLines = []; + var promptFound = false; + var gotLineCont = false; + var gotHereDoc = false; + const lineGotPrompt = []; + for (const line of textContent.split('\n')) { + match = line.match(regexp) + if (match || gotLineCont || gotHereDoc) { + promptFound = regexp.test(line) + lineGotPrompt.push(promptFound) + if (removePrompts && promptFound) { + outputLines.push(match[2]) + } else { + outputLines.push(line) + } + gotLineCont = line.endsWith(lineContinuationChar) & useLineCont + if (line.includes(hereDocDelim) & useHereDoc) + gotHereDoc = !gotHereDoc + } else if (!onlyCopyPromptLines) { + outputLines.push(line) + } else if (copyEmptyLines && line.trim() === '') { + outputLines.push(line) + } + } + + // If no lines with the prompt were found then just use original lines + if (lineGotPrompt.some(v => v === true)) { + textContent = outputLines.join('\n'); + } + + // Remove a trailing newline to avoid auto-running when pasting + if (textContent.endsWith("\n")) { + textContent = textContent.slice(0, -1) + } + return textContent +} diff --git a/_static/design-tabs.js b/_static/design-tabs.js new file mode 100644 index 00000000..b25bd6a4 --- /dev/null +++ b/_static/design-tabs.js @@ -0,0 +1,101 @@ +// @ts-check + +// Extra JS capability for selected tabs to be synced +// The selection is stored in local storage so that it persists across page loads. + +/** + * @type {Record} + */ +let sd_id_to_elements = {}; +const storageKeyPrefix = "sphinx-design-tab-id-"; + +/** + * Create a key for a tab element. + * @param {HTMLElement} el - The tab element. + * @returns {[string, string, string] | null} - The key. + * + */ +function create_key(el) { + let syncId = el.getAttribute("data-sync-id"); + let syncGroup = el.getAttribute("data-sync-group"); + if (!syncId || !syncGroup) return null; + return [syncGroup, syncId, syncGroup + "--" + syncId]; +} + +/** + * Initialize the tab selection. + * + */ +function ready() { + // Find all tabs with sync data + + /** @type {string[]} */ + let groups = []; + + document.querySelectorAll(".sd-tab-label").forEach((label) => { + if (label instanceof HTMLElement) { + let data = create_key(label); + if (data) { + let [group, id, key] = data; + + // add click event listener + // @ts-ignore + label.onclick = onSDLabelClick; + + // store map of key to elements + if (!sd_id_to_elements[key]) { + sd_id_to_elements[key] = []; + } + sd_id_to_elements[key].push(label); + + if (groups.indexOf(group) === -1) { + groups.push(group); + // Check if a specific tab has been selected via URL parameter + const tabParam = new URLSearchParams(window.location.search).get( + group + ); + if (tabParam) { + console.log( + "sphinx-design: Selecting tab id for group '" + + group + + "' from URL parameter: " + + tabParam + ); + window.sessionStorage.setItem(storageKeyPrefix + group, tabParam); + } + } + + // Check is a specific tab has been selected previously + let previousId = window.sessionStorage.getItem( + storageKeyPrefix + group + ); + if (previousId === id) { + // console.log( + // "sphinx-design: Selecting tab from session storage: " + id + // ); + // @ts-ignore + label.previousElementSibling.checked = true; + } + } + } + }); +} + +/** + * Activate other tabs with the same sync id. + * + * @this {HTMLElement} - The element that was clicked. + */ +function onSDLabelClick() { + let data = create_key(this); + if (!data) return; + let [group, id, key] = data; + for (const label of sd_id_to_elements[key]) { + if (label === this) continue; + // @ts-ignore + label.previousElementSibling.checked = true; + } + window.sessionStorage.setItem(storageKeyPrefix + group, id); +} + +document.addEventListener("DOMContentLoaded", ready, false); diff --git a/_static/doctools.js b/_static/doctools.js new file mode 100644 index 00000000..4d67807d --- /dev/null +++ b/_static/doctools.js @@ -0,0 +1,156 @@ +/* + * doctools.js + * ~~~~~~~~~~~ + * + * Base JavaScript utilities for all Sphinx HTML documentation. + * + * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS. + * :license: BSD, see LICENSE for details. + * + */ +"use strict"; + +const BLACKLISTED_KEY_CONTROL_ELEMENTS = new Set([ + "TEXTAREA", + "INPUT", + "SELECT", + "BUTTON", +]); + +const _ready = (callback) => { + if (document.readyState !== "loading") { + callback(); + } else { + document.addEventListener("DOMContentLoaded", callback); + } +}; + +/** + * Small JavaScript module for the documentation. + */ +const Documentation = { + init: () => { + 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; + }, + + /** + * 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; + + document.addEventListener("keydown", (event) => { + // 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) { + case "ArrowLeft": + if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break; + + const prevLink = document.querySelector('link[rel="prev"]'); + if (prevLink && prevLink.href) { + window.location.href = prevLink.href; + event.preventDefault(); + } + break; + case "ArrowRight": + if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break; + + const nextLink = document.querySelector('link[rel="next"]'); + if (nextLink && nextLink.href) { + window.location.href = nextLink.href; + event.preventDefault(); + } + break; + } + } + + // some keyboard layouts may need Shift to get / + switch (event.key) { + case "/": + if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) break; + Documentation.focusSearchBar(); + event.preventDefault(); + } + }); + }, +}; + +// quick alias for translations +const _ = Documentation.gettext; + +_ready(Documentation.init); diff --git a/_static/documentation_options.js b/_static/documentation_options.js new file mode 100644 index 00000000..dab586c0 --- /dev/null +++ b/_static/documentation_options.js @@ -0,0 +1,13 @@ +const DOCUMENTATION_OPTIONS = { + VERSION: '', + LANGUAGE: 'en', + COLLAPSE_INDEX: false, + BUILDER: 'html', + FILE_SUFFIX: '.html', + LINK_SUFFIX: '.html', + HAS_SOURCE: true, + SOURCELINK_SUFFIX: '', + NAVIGATION_WITH_KEYS: false, + SHOW_SEARCH_SUMMARY: true, + ENABLE_SEARCH_SHORTCUTS: true, +}; \ No newline at end of file diff --git a/_static/file.png b/_static/file.png new file mode 100644 index 00000000..a858a410 Binary files /dev/null and b/_static/file.png differ diff --git a/_static/images/logo_binder.svg b/_static/images/logo_binder.svg new file mode 100644 index 00000000..45fecf75 --- /dev/null +++ b/_static/images/logo_binder.svg @@ -0,0 +1,19 @@ + + + + +logo + + + + + + + + diff --git a/_static/images/logo_colab.png b/_static/images/logo_colab.png new file mode 100644 index 00000000..b7560ec2 Binary files /dev/null and b/_static/images/logo_colab.png differ diff --git a/_static/images/logo_deepnote.svg b/_static/images/logo_deepnote.svg new file mode 100644 index 00000000..fa77ebfc --- /dev/null +++ b/_static/images/logo_deepnote.svg @@ -0,0 +1 @@ + diff --git a/_static/images/logo_jupyterhub.svg b/_static/images/logo_jupyterhub.svg new file mode 100644 index 00000000..60cfe9f2 --- /dev/null +++ b/_static/images/logo_jupyterhub.svg @@ -0,0 +1 @@ +logo_jupyterhubHub diff --git a/_static/images/logo_jupyterlite.svg b/_static/images/logo_jupyterlite.svg new file mode 100644 index 00000000..09e821f6 --- /dev/null +++ b/_static/images/logo_jupyterlite.svg @@ -0,0 +1,17 @@ + + + + + + + + + + + + + + + + + diff --git a/_static/language_data.js b/_static/language_data.js new file mode 100644 index 00000000..367b8ed8 --- /dev/null +++ b/_static/language_data.js @@ -0,0 +1,199 @@ +/* + * language_data.js + * ~~~~~~~~~~~~~~~~ + * + * This script contains the language-specific data used by searchtools.js, + * namely the list of stopwords, stemmer, scorer and splitter. + * + * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS. + * :license: BSD, see LICENSE for details. + * + */ + +var stopwords = ["a", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "near", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"]; + + +/* Non-minified version is copied as a separate JS file, if available */ + +/** + * Porter Stemmer + */ +var Stemmer = function() { + + var step2list = { + ational: 'ate', + tional: 'tion', + enci: 'ence', + anci: 'ance', + izer: 'ize', + bli: 'ble', + alli: 'al', + entli: 'ent', + eli: 'e', + ousli: 'ous', + ization: 'ize', + ation: 'ate', + ator: 'ate', + alism: 'al', + iveness: 'ive', + fulness: 'ful', + ousness: 'ous', + aliti: 'al', + iviti: 'ive', + biliti: 'ble', + logi: 'log' + }; + + var step3list = { + icate: 'ic', + ative: '', + alize: 'al', + iciti: 'ic', + ical: 'ic', + ful: '', + ness: '' + }; + + var c = "[^aeiou]"; // consonant + var v = "[aeiouy]"; // vowel + var C = c + "[^aeiouy]*"; // consonant sequence + var V = v + "[aeiou]*"; // vowel sequence + + var mgr0 = "^(" + C + ")?" + V + C; // [C]VC... is m>0 + var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$"; // [C]VC[V] is m=1 + var mgr1 = "^(" + C + ")?" + V + C + V + C; // [C]VCVC... is m>1 + var s_v = "^(" + C + ")?" + v; // vowel in stem + + this.stemWord = function (w) { + var stem; + var suffix; + var firstch; + var origword = w; + + if (w.length < 3) + return w; + + var re; + var re2; + var re3; + var re4; + + firstch = w.substr(0,1); + if (firstch == "y") + w = firstch.toUpperCase() + w.substr(1); + + // Step 1a + re = /^(.+?)(ss|i)es$/; + re2 = /^(.+?)([^s])s$/; + + if (re.test(w)) + w = w.replace(re,"$1$2"); + else if (re2.test(w)) + w = w.replace(re2,"$1$2"); + + // Step 1b + re = /^(.+?)eed$/; + re2 = /^(.+?)(ed|ing)$/; + if (re.test(w)) { + var fp = re.exec(w); + re = new RegExp(mgr0); + if (re.test(fp[1])) { + re = /.$/; + w = w.replace(re,""); + } + } + else if (re2.test(w)) { + var fp = re2.exec(w); + stem = fp[1]; + re2 = new RegExp(s_v); + if (re2.test(stem)) { + w = stem; + re2 = /(at|bl|iz)$/; + re3 = new RegExp("([^aeiouylsz])\\1$"); + re4 = new RegExp("^" + C + v + "[^aeiouwxy]$"); + if (re2.test(w)) + w = w + "e"; + else if (re3.test(w)) { + re = /.$/; + w = w.replace(re,""); + } + else if (re4.test(w)) + w = w + "e"; + } + } + + // Step 1c + re = /^(.+?)y$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = new RegExp(s_v); + if (re.test(stem)) + w = stem + "i"; + } + + // Step 2 + re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + suffix = fp[2]; + re = new RegExp(mgr0); + if (re.test(stem)) + w = stem + step2list[suffix]; + } + + // Step 3 + re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + suffix = fp[2]; + re = new RegExp(mgr0); + if (re.test(stem)) + w = stem + step3list[suffix]; + } + + // Step 4 + re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/; + re2 = /^(.+?)(s|t)(ion)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = new RegExp(mgr1); + if (re.test(stem)) + w = stem; + } + else if (re2.test(w)) { + var fp = re2.exec(w); + stem = fp[1] + fp[2]; + re2 = new RegExp(mgr1); + if (re2.test(stem)) + w = stem; + } + + // Step 5 + re = /^(.+?)e$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = new RegExp(mgr1); + re2 = new RegExp(meq1); + re3 = new RegExp("^" + C + v + "[^aeiouwxy]$"); + if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) + w = stem; + } + re = /ll$/; + re2 = new RegExp(mgr1); + if (re.test(w) && re2.test(w)) { + re = /.$/; + w = w.replace(re,""); + } + + // and turn initial Y back to y + if (firstch == "y") + w = firstch.toLowerCase() + w.substr(1); + return w; + } +} + diff --git a/_static/locales/ar/LC_MESSAGES/booktheme.mo b/_static/locales/ar/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..15541a6a Binary files /dev/null and b/_static/locales/ar/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/ar/LC_MESSAGES/booktheme.po b/_static/locales/ar/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..066f20f9 --- /dev/null +++ b/_static/locales/ar/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ar\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "بواسطة" + +msgid "By" +msgstr "بواسطة" + +msgid "Contents" +msgstr "محتويات" + +msgid "Copyright" +msgstr "حقوق النشر" + +msgid "Download notebook file" +msgstr "تنزيل ملف دفتر الملاحظات" + +msgid "Download source file" +msgstr "تنزيل ملف المصدر" + +msgid "Download this page" +msgstr "قم بتنزيل هذه الصفحة" + +msgid "Edit this page" +msgstr "قم بتحرير هذه الصفحة" + +msgid "Fullscreen mode" +msgstr "وضع ملء الشاشة" + +msgid "Last updated on" +msgstr "آخر تحديث في" + +msgid "Launch" +msgstr "إطلاق" + +msgid "Open an issue" +msgstr "افتح قضية" + +msgid "Print to PDF" +msgstr "طباعة إلى PDF" + +msgid "Source repository" +msgstr "مستودع المصدر" + +msgid "Sphinx Book Theme" +msgstr "موضوع كتاب أبو الهول" + +msgid "Theme by the" +msgstr "موضوع بواسطة" + +msgid "Toggle navigation" +msgstr "تبديل التنقل" + +msgid "next page" +msgstr "الصفحة التالية" + +msgid "open issue" +msgstr "قضية مفتوحة" + +msgid "previous page" +msgstr "الصفحة السابقة" + +msgid "repository" +msgstr "مخزن" + +msgid "suggest edit" +msgstr "أقترح تحرير" diff --git a/_static/locales/bg/LC_MESSAGES/booktheme.mo b/_static/locales/bg/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..da951200 Binary files /dev/null and b/_static/locales/bg/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/bg/LC_MESSAGES/booktheme.po b/_static/locales/bg/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..0f22f49a --- /dev/null +++ b/_static/locales/bg/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: bg\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "По" + +msgid "By" +msgstr "От" + +msgid "Contents" +msgstr "Съдържание" + +msgid "Copyright" +msgstr "Авторско право" + +msgid "Download notebook file" +msgstr "Изтеглете файла на бележника" + +msgid "Download source file" +msgstr "Изтеглете изходния файл" + +msgid "Download this page" +msgstr "Изтеглете тази страница" + +msgid "Edit this page" +msgstr "Редактирайте тази страница" + +msgid "Fullscreen mode" +msgstr "Режим на цял екран" + +msgid "Last updated on" +msgstr "Последна актуализация на" + +msgid "Launch" +msgstr "Стартиране" + +msgid "Open an issue" +msgstr "Отворете проблем" + +msgid "Print to PDF" +msgstr "Печат в PDF" + +msgid "Source repository" +msgstr "Хранилище на източника" + +msgid "Sphinx Book Theme" +msgstr "Тема на книгата Sphinx" + +msgid "Theme by the" +msgstr "Тема от" + +msgid "Toggle navigation" +msgstr "Превключване на навигацията" + +msgid "next page" +msgstr "Следваща страница" + +msgid "open issue" +msgstr "отворен брой" + +msgid "previous page" +msgstr "предишна страница" + +msgid "repository" +msgstr "хранилище" + +msgid "suggest edit" +msgstr "предложи редактиране" diff --git a/_static/locales/bn/LC_MESSAGES/booktheme.mo b/_static/locales/bn/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..6b96639b Binary files /dev/null and b/_static/locales/bn/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/bn/LC_MESSAGES/booktheme.po b/_static/locales/bn/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..7202a5f3 --- /dev/null +++ b/_static/locales/bn/LC_MESSAGES/booktheme.po @@ -0,0 +1,63 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: bn\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "দ্বারা" + +msgid "By" +msgstr "দ্বারা" + +msgid "Copyright" +msgstr "কপিরাইট" + +msgid "Download notebook file" +msgstr "নোটবুক ফাইল ডাউনলোড করুন" + +msgid "Download source file" +msgstr "উত্স ফাইল ডাউনলোড করুন" + +msgid "Download this page" +msgstr "এই পৃষ্ঠাটি ডাউনলোড করুন" + +msgid "Edit this page" +msgstr "এই পৃষ্ঠাটি সম্পাদনা করুন" + +msgid "Last updated on" +msgstr "সর্বশেষ আপডেট" + +msgid "Launch" +msgstr "শুরু করা" + +msgid "Open an issue" +msgstr "একটি সমস্যা খুলুন" + +msgid "Print to PDF" +msgstr "পিডিএফ প্রিন্ট করুন" + +msgid "Source repository" +msgstr "উত্স সংগ্রহস্থল" + +msgid "Sphinx Book Theme" +msgstr "স্পিনিক্স বুক থিম" + +msgid "Theme by the" +msgstr "থিম দ্বারা" + +msgid "Toggle navigation" +msgstr "নেভিগেশন টগল করুন" + +msgid "next page" +msgstr "পরবর্তী পৃষ্ঠা" + +msgid "open issue" +msgstr "খোলা সমস্যা" + +msgid "previous page" +msgstr "আগের পৃষ্ঠা" diff --git a/_static/locales/ca/LC_MESSAGES/booktheme.mo b/_static/locales/ca/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..a4dd30e9 Binary files /dev/null and b/_static/locales/ca/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/ca/LC_MESSAGES/booktheme.po b/_static/locales/ca/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..a325041f --- /dev/null +++ b/_static/locales/ca/LC_MESSAGES/booktheme.po @@ -0,0 +1,66 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ca\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Per la" + +msgid "By" +msgstr "Per" + +msgid "Copyright" +msgstr "Copyright" + +msgid "Download notebook file" +msgstr "Descarregar fitxer de quadern" + +msgid "Download source file" +msgstr "Baixeu el fitxer font" + +msgid "Download this page" +msgstr "Descarregueu aquesta pàgina" + +msgid "Edit this page" +msgstr "Editeu aquesta pàgina" + +msgid "Last updated on" +msgstr "Darrera actualització el" + +msgid "Launch" +msgstr "Llançament" + +msgid "Open an issue" +msgstr "Obriu un número" + +msgid "Print to PDF" +msgstr "Imprimeix a PDF" + +msgid "Source repository" +msgstr "Dipòsit de fonts" + +msgid "Sphinx Book Theme" +msgstr "Tema del llibre Esfinx" + +msgid "Theme by the" +msgstr "Tema del" + +msgid "Toggle navigation" +msgstr "Commuta la navegació" + +msgid "next page" +msgstr "pàgina següent" + +msgid "open issue" +msgstr "número obert" + +msgid "previous page" +msgstr "Pàgina anterior" + +msgid "suggest edit" +msgstr "suggerir edició" diff --git a/_static/locales/cs/LC_MESSAGES/booktheme.mo b/_static/locales/cs/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..c39e01a6 Binary files /dev/null and b/_static/locales/cs/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/cs/LC_MESSAGES/booktheme.po b/_static/locales/cs/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..97e52e8a --- /dev/null +++ b/_static/locales/cs/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: cs\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Podle" + +msgid "By" +msgstr "Podle" + +msgid "Contents" +msgstr "Obsah" + +msgid "Copyright" +msgstr "autorská práva" + +msgid "Download notebook file" +msgstr "Stáhnout soubor poznámkového bloku" + +msgid "Download source file" +msgstr "Stáhněte si zdrojový soubor" + +msgid "Download this page" +msgstr "Stáhněte si tuto stránku" + +msgid "Edit this page" +msgstr "Upravit tuto stránku" + +msgid "Fullscreen mode" +msgstr "Režim celé obrazovky" + +msgid "Last updated on" +msgstr "Naposledy aktualizováno" + +msgid "Launch" +msgstr "Zahájení" + +msgid "Open an issue" +msgstr "Otevřete problém" + +msgid "Print to PDF" +msgstr "Tisk do PDF" + +msgid "Source repository" +msgstr "Zdrojové úložiště" + +msgid "Sphinx Book Theme" +msgstr "Téma knihy Sfinga" + +msgid "Theme by the" +msgstr "Téma od" + +msgid "Toggle navigation" +msgstr "Přepnout navigaci" + +msgid "next page" +msgstr "další strana" + +msgid "open issue" +msgstr "otevřené číslo" + +msgid "previous page" +msgstr "předchozí stránka" + +msgid "repository" +msgstr "úložiště" + +msgid "suggest edit" +msgstr "navrhnout úpravy" diff --git a/_static/locales/da/LC_MESSAGES/booktheme.mo b/_static/locales/da/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..f43157d7 Binary files /dev/null and b/_static/locales/da/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/da/LC_MESSAGES/booktheme.po b/_static/locales/da/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..084b4e57 --- /dev/null +++ b/_static/locales/da/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: da\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Ved" + +msgid "By" +msgstr "Ved" + +msgid "Contents" +msgstr "Indhold" + +msgid "Copyright" +msgstr "ophavsret" + +msgid "Download notebook file" +msgstr "Download notesbog-fil" + +msgid "Download source file" +msgstr "Download kildefil" + +msgid "Download this page" +msgstr "Download denne side" + +msgid "Edit this page" +msgstr "Rediger denne side" + +msgid "Fullscreen mode" +msgstr "Fuldskærmstilstand" + +msgid "Last updated on" +msgstr "Sidst opdateret den" + +msgid "Launch" +msgstr "Start" + +msgid "Open an issue" +msgstr "Åbn et problem" + +msgid "Print to PDF" +msgstr "Udskriv til PDF" + +msgid "Source repository" +msgstr "Kildelager" + +msgid "Sphinx Book Theme" +msgstr "Sphinx bogtema" + +msgid "Theme by the" +msgstr "Tema af" + +msgid "Toggle navigation" +msgstr "Skift navigation" + +msgid "next page" +msgstr "Næste side" + +msgid "open issue" +msgstr "åbent nummer" + +msgid "previous page" +msgstr "forrige side" + +msgid "repository" +msgstr "lager" + +msgid "suggest edit" +msgstr "foreslå redigering" diff --git a/_static/locales/de/LC_MESSAGES/booktheme.mo b/_static/locales/de/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..648b565c Binary files /dev/null and b/_static/locales/de/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/de/LC_MESSAGES/booktheme.po b/_static/locales/de/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..1ed1dc16 --- /dev/null +++ b/_static/locales/de/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: de\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Bis zum" + +msgid "By" +msgstr "Durch" + +msgid "Contents" +msgstr "Inhalt" + +msgid "Copyright" +msgstr "Urheberrechte ©" + +msgid "Download notebook file" +msgstr "Notebook-Datei herunterladen" + +msgid "Download source file" +msgstr "Quelldatei herunterladen" + +msgid "Download this page" +msgstr "Laden Sie diese Seite herunter" + +msgid "Edit this page" +msgstr "Bearbeite diese Seite" + +msgid "Fullscreen mode" +msgstr "Vollbildmodus" + +msgid "Last updated on" +msgstr "Zuletzt aktualisiert am" + +msgid "Launch" +msgstr "Starten" + +msgid "Open an issue" +msgstr "Öffnen Sie ein Problem" + +msgid "Print to PDF" +msgstr "In PDF drucken" + +msgid "Source repository" +msgstr "Quell-Repository" + +msgid "Sphinx Book Theme" +msgstr "Sphinx-Buch-Thema" + +msgid "Theme by the" +msgstr "Thema von der" + +msgid "Toggle navigation" +msgstr "Navigation umschalten" + +msgid "next page" +msgstr "Nächste Seite" + +msgid "open issue" +msgstr "offenes Thema" + +msgid "previous page" +msgstr "vorherige Seite" + +msgid "repository" +msgstr "Repository" + +msgid "suggest edit" +msgstr "vorschlagen zu bearbeiten" diff --git a/_static/locales/el/LC_MESSAGES/booktheme.mo b/_static/locales/el/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..fca6e935 Binary files /dev/null and b/_static/locales/el/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/el/LC_MESSAGES/booktheme.po b/_static/locales/el/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..27d1274a --- /dev/null +++ b/_static/locales/el/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: el\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Από το" + +msgid "By" +msgstr "Με" + +msgid "Contents" +msgstr "Περιεχόμενα" + +msgid "Copyright" +msgstr "Πνευματική ιδιοκτησία" + +msgid "Download notebook file" +msgstr "Λήψη αρχείου σημειωματάριου" + +msgid "Download source file" +msgstr "Λήψη αρχείου προέλευσης" + +msgid "Download this page" +msgstr "Λήψη αυτής της σελίδας" + +msgid "Edit this page" +msgstr "Επεξεργαστείτε αυτήν τη σελίδα" + +msgid "Fullscreen mode" +msgstr "ΛΕΙΤΟΥΡΓΙΑ ΠΛΗΡΟΥΣ ΟΘΟΝΗΣ" + +msgid "Last updated on" +msgstr "Τελευταία ενημέρωση στις" + +msgid "Launch" +msgstr "Εκτόξευση" + +msgid "Open an issue" +msgstr "Ανοίξτε ένα ζήτημα" + +msgid "Print to PDF" +msgstr "Εκτύπωση σε PDF" + +msgid "Source repository" +msgstr "Αποθήκη πηγής" + +msgid "Sphinx Book Theme" +msgstr "Θέμα βιβλίου Sphinx" + +msgid "Theme by the" +msgstr "Θέμα από το" + +msgid "Toggle navigation" +msgstr "Εναλλαγή πλοήγησης" + +msgid "next page" +msgstr "επόμενη σελίδα" + +msgid "open issue" +msgstr "ανοιχτό ζήτημα" + +msgid "previous page" +msgstr "προηγούμενη σελίδα" + +msgid "repository" +msgstr "αποθήκη" + +msgid "suggest edit" +msgstr "προτείνω επεξεργασία" diff --git a/_static/locales/eo/LC_MESSAGES/booktheme.mo b/_static/locales/eo/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..d1072bbe Binary files /dev/null and b/_static/locales/eo/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/eo/LC_MESSAGES/booktheme.po b/_static/locales/eo/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..1fda1bcd --- /dev/null +++ b/_static/locales/eo/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: eo\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Per la" + +msgid "By" +msgstr "De" + +msgid "Contents" +msgstr "Enhavo" + +msgid "Copyright" +msgstr "Kopirajto" + +msgid "Download notebook file" +msgstr "Elŝutu kajeran dosieron" + +msgid "Download source file" +msgstr "Elŝutu fontodosieron" + +msgid "Download this page" +msgstr "Elŝutu ĉi tiun paĝon" + +msgid "Edit this page" +msgstr "Redaktu ĉi tiun paĝon" + +msgid "Fullscreen mode" +msgstr "Plenekrana reĝimo" + +msgid "Last updated on" +msgstr "Laste ĝisdatigita la" + +msgid "Launch" +msgstr "Lanĉo" + +msgid "Open an issue" +msgstr "Malfermu numeron" + +msgid "Print to PDF" +msgstr "Presi al PDF" + +msgid "Source repository" +msgstr "Fonto-deponejo" + +msgid "Sphinx Book Theme" +msgstr "Sfinksa Libro-Temo" + +msgid "Theme by the" +msgstr "Temo de la" + +msgid "Toggle navigation" +msgstr "Ŝalti navigadon" + +msgid "next page" +msgstr "sekva paĝo" + +msgid "open issue" +msgstr "malferma numero" + +msgid "previous page" +msgstr "antaŭa paĝo" + +msgid "repository" +msgstr "deponejo" + +msgid "suggest edit" +msgstr "sugesti redaktadon" diff --git a/_static/locales/es/LC_MESSAGES/booktheme.mo b/_static/locales/es/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..ba2ee4dc Binary files /dev/null and b/_static/locales/es/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/es/LC_MESSAGES/booktheme.po b/_static/locales/es/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..c91b41b9 --- /dev/null +++ b/_static/locales/es/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: es\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Por el" + +msgid "By" +msgstr "Por" + +msgid "Contents" +msgstr "Contenido" + +msgid "Copyright" +msgstr "Derechos de autor" + +msgid "Download notebook file" +msgstr "Descargar archivo de cuaderno" + +msgid "Download source file" +msgstr "Descargar archivo fuente" + +msgid "Download this page" +msgstr "Descarga esta pagina" + +msgid "Edit this page" +msgstr "Edita esta página" + +msgid "Fullscreen mode" +msgstr "Modo de pantalla completa" + +msgid "Last updated on" +msgstr "Ultima actualización en" + +msgid "Launch" +msgstr "Lanzamiento" + +msgid "Open an issue" +msgstr "Abrir un problema" + +msgid "Print to PDF" +msgstr "Imprimir en PDF" + +msgid "Source repository" +msgstr "Repositorio de origen" + +msgid "Sphinx Book Theme" +msgstr "Tema del libro de la esfinge" + +msgid "Theme by the" +msgstr "Tema por el" + +msgid "Toggle navigation" +msgstr "Navegación de palanca" + +msgid "next page" +msgstr "siguiente página" + +msgid "open issue" +msgstr "Tema abierto" + +msgid "previous page" +msgstr "pagina anterior" + +msgid "repository" +msgstr "repositorio" + +msgid "suggest edit" +msgstr "sugerir editar" diff --git a/_static/locales/et/LC_MESSAGES/booktheme.mo b/_static/locales/et/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..983b8239 Binary files /dev/null and b/_static/locales/et/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/et/LC_MESSAGES/booktheme.po b/_static/locales/et/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..2fd1ea20 --- /dev/null +++ b/_static/locales/et/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: et\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Autor" + +msgid "By" +msgstr "Kõrval" + +msgid "Contents" +msgstr "Sisu" + +msgid "Copyright" +msgstr "Autoriõigus" + +msgid "Download notebook file" +msgstr "Laadige sülearvuti fail alla" + +msgid "Download source file" +msgstr "Laadige alla lähtefail" + +msgid "Download this page" +msgstr "Laadige see leht alla" + +msgid "Edit this page" +msgstr "Muutke seda lehte" + +msgid "Fullscreen mode" +msgstr "Täisekraanirežiim" + +msgid "Last updated on" +msgstr "Viimati uuendatud" + +msgid "Launch" +msgstr "Käivitage" + +msgid "Open an issue" +msgstr "Avage probleem" + +msgid "Print to PDF" +msgstr "Prindi PDF-i" + +msgid "Source repository" +msgstr "Allikahoidla" + +msgid "Sphinx Book Theme" +msgstr "Sfinksiraamatu teema" + +msgid "Theme by the" +msgstr "Teema" + +msgid "Toggle navigation" +msgstr "Lülita navigeerimine sisse" + +msgid "next page" +msgstr "järgmine leht" + +msgid "open issue" +msgstr "avatud küsimus" + +msgid "previous page" +msgstr "eelmine leht" + +msgid "repository" +msgstr "hoidla" + +msgid "suggest edit" +msgstr "soovita muuta" diff --git a/_static/locales/fi/LC_MESSAGES/booktheme.mo b/_static/locales/fi/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..d8ac0545 Binary files /dev/null and b/_static/locales/fi/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/fi/LC_MESSAGES/booktheme.po b/_static/locales/fi/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..2843f2c7 --- /dev/null +++ b/_static/locales/fi/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: fi\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Mukaan" + +msgid "By" +msgstr "Tekijä" + +msgid "Contents" +msgstr "Sisällys" + +msgid "Copyright" +msgstr "Tekijänoikeus" + +msgid "Download notebook file" +msgstr "Lataa muistikirjatiedosto" + +msgid "Download source file" +msgstr "Lataa lähdetiedosto" + +msgid "Download this page" +msgstr "Lataa tämä sivu" + +msgid "Edit this page" +msgstr "Muokkaa tätä sivua" + +msgid "Fullscreen mode" +msgstr "Koko näytön tila" + +msgid "Last updated on" +msgstr "Viimeksi päivitetty" + +msgid "Launch" +msgstr "Tuoda markkinoille" + +msgid "Open an issue" +msgstr "Avaa ongelma" + +msgid "Print to PDF" +msgstr "Tulosta PDF-tiedostoon" + +msgid "Source repository" +msgstr "Lähteen arkisto" + +msgid "Sphinx Book Theme" +msgstr "Sphinx-kirjan teema" + +msgid "Theme by the" +msgstr "Teeman tekijä" + +msgid "Toggle navigation" +msgstr "Vaihda navigointia" + +msgid "next page" +msgstr "seuraava sivu" + +msgid "open issue" +msgstr "avoin ongelma" + +msgid "previous page" +msgstr "Edellinen sivu" + +msgid "repository" +msgstr "arkisto" + +msgid "suggest edit" +msgstr "ehdottaa muokkausta" diff --git a/_static/locales/fr/LC_MESSAGES/booktheme.mo b/_static/locales/fr/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..f663d39f Binary files /dev/null and b/_static/locales/fr/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/fr/LC_MESSAGES/booktheme.po b/_static/locales/fr/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..351cddd6 --- /dev/null +++ b/_static/locales/fr/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: fr\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Par le" + +msgid "By" +msgstr "Par" + +msgid "Contents" +msgstr "Contenu" + +msgid "Copyright" +msgstr "droits d'auteur" + +msgid "Download notebook file" +msgstr "Télécharger le fichier notebook" + +msgid "Download source file" +msgstr "Télécharger le fichier source" + +msgid "Download this page" +msgstr "Téléchargez cette page" + +msgid "Edit this page" +msgstr "Modifier cette page" + +msgid "Fullscreen mode" +msgstr "Mode plein écran" + +msgid "Last updated on" +msgstr "Dernière mise à jour le" + +msgid "Launch" +msgstr "lancement" + +msgid "Open an issue" +msgstr "Ouvrez un problème" + +msgid "Print to PDF" +msgstr "Imprimer au format PDF" + +msgid "Source repository" +msgstr "Dépôt source" + +msgid "Sphinx Book Theme" +msgstr "Thème du livre Sphinx" + +msgid "Theme by the" +msgstr "Thème par le" + +msgid "Toggle navigation" +msgstr "Basculer la navigation" + +msgid "next page" +msgstr "page suivante" + +msgid "open issue" +msgstr "signaler un problème" + +msgid "previous page" +msgstr "page précédente" + +msgid "repository" +msgstr "dépôt" + +msgid "suggest edit" +msgstr "suggestion de modification" diff --git a/_static/locales/hr/LC_MESSAGES/booktheme.mo b/_static/locales/hr/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..eca4a1a2 Binary files /dev/null and b/_static/locales/hr/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/hr/LC_MESSAGES/booktheme.po b/_static/locales/hr/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..3c1cf079 --- /dev/null +++ b/_static/locales/hr/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: hr\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Od strane" + +msgid "By" +msgstr "Po" + +msgid "Contents" +msgstr "Sadržaj" + +msgid "Copyright" +msgstr "Autorska prava" + +msgid "Download notebook file" +msgstr "Preuzmi datoteku bilježnice" + +msgid "Download source file" +msgstr "Preuzmi izvornu datoteku" + +msgid "Download this page" +msgstr "Preuzmite ovu stranicu" + +msgid "Edit this page" +msgstr "Uredite ovu stranicu" + +msgid "Fullscreen mode" +msgstr "Način preko cijelog zaslona" + +msgid "Last updated on" +msgstr "Posljednje ažuriranje:" + +msgid "Launch" +msgstr "Pokrenite" + +msgid "Open an issue" +msgstr "Otvorite izdanje" + +msgid "Print to PDF" +msgstr "Ispis u PDF" + +msgid "Source repository" +msgstr "Izvorno spremište" + +msgid "Sphinx Book Theme" +msgstr "Tema knjige Sphinx" + +msgid "Theme by the" +msgstr "Tema autora" + +msgid "Toggle navigation" +msgstr "Uključi / isključi navigaciju" + +msgid "next page" +msgstr "sljedeća stranica" + +msgid "open issue" +msgstr "otvoreno izdanje" + +msgid "previous page" +msgstr "Prethodna stranica" + +msgid "repository" +msgstr "spremište" + +msgid "suggest edit" +msgstr "predloži uređivanje" diff --git a/_static/locales/id/LC_MESSAGES/booktheme.mo b/_static/locales/id/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..d07a06a9 Binary files /dev/null and b/_static/locales/id/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/id/LC_MESSAGES/booktheme.po b/_static/locales/id/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..809498c7 --- /dev/null +++ b/_static/locales/id/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: id\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Oleh" + +msgid "By" +msgstr "Oleh" + +msgid "Contents" +msgstr "Isi" + +msgid "Copyright" +msgstr "hak cipta" + +msgid "Download notebook file" +msgstr "Unduh file notebook" + +msgid "Download source file" +msgstr "Unduh file sumber" + +msgid "Download this page" +msgstr "Unduh halaman ini" + +msgid "Edit this page" +msgstr "Edit halaman ini" + +msgid "Fullscreen mode" +msgstr "Mode layar penuh" + +msgid "Last updated on" +msgstr "Terakhir diperbarui saat" + +msgid "Launch" +msgstr "Meluncurkan" + +msgid "Open an issue" +msgstr "Buka masalah" + +msgid "Print to PDF" +msgstr "Cetak ke PDF" + +msgid "Source repository" +msgstr "Repositori sumber" + +msgid "Sphinx Book Theme" +msgstr "Tema Buku Sphinx" + +msgid "Theme by the" +msgstr "Tema oleh" + +msgid "Toggle navigation" +msgstr "Alihkan navigasi" + +msgid "next page" +msgstr "halaman selanjutnya" + +msgid "open issue" +msgstr "masalah terbuka" + +msgid "previous page" +msgstr "halaman sebelumnya" + +msgid "repository" +msgstr "gudang" + +msgid "suggest edit" +msgstr "menyarankan edit" diff --git a/_static/locales/it/LC_MESSAGES/booktheme.mo b/_static/locales/it/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..53ba476e Binary files /dev/null and b/_static/locales/it/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/it/LC_MESSAGES/booktheme.po b/_static/locales/it/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..fbc8d03b --- /dev/null +++ b/_static/locales/it/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: it\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Dal" + +msgid "By" +msgstr "Di" + +msgid "Contents" +msgstr "Contenuti" + +msgid "Copyright" +msgstr "Diritto d'autore" + +msgid "Download notebook file" +msgstr "Scarica il file del taccuino" + +msgid "Download source file" +msgstr "Scarica il file sorgente" + +msgid "Download this page" +msgstr "Scarica questa pagina" + +msgid "Edit this page" +msgstr "Modifica questa pagina" + +msgid "Fullscreen mode" +msgstr "Modalità schermo intero" + +msgid "Last updated on" +msgstr "Ultimo aggiornamento il" + +msgid "Launch" +msgstr "Lanciare" + +msgid "Open an issue" +msgstr "Apri un problema" + +msgid "Print to PDF" +msgstr "Stampa in PDF" + +msgid "Source repository" +msgstr "Repository di origine" + +msgid "Sphinx Book Theme" +msgstr "Tema del libro della Sfinge" + +msgid "Theme by the" +msgstr "Tema di" + +msgid "Toggle navigation" +msgstr "Attiva / disattiva la navigazione" + +msgid "next page" +msgstr "pagina successiva" + +msgid "open issue" +msgstr "questione aperta" + +msgid "previous page" +msgstr "pagina precedente" + +msgid "repository" +msgstr "repository" + +msgid "suggest edit" +msgstr "suggerisci modifica" diff --git a/_static/locales/iw/LC_MESSAGES/booktheme.mo b/_static/locales/iw/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..a45c6575 Binary files /dev/null and b/_static/locales/iw/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/iw/LC_MESSAGES/booktheme.po b/_static/locales/iw/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..a82f3512 --- /dev/null +++ b/_static/locales/iw/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: iw\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "דרך" + +msgid "By" +msgstr "על ידי" + +msgid "Contents" +msgstr "תוכן" + +msgid "Copyright" +msgstr "זכויות יוצרים" + +msgid "Download notebook file" +msgstr "הורד קובץ מחברת" + +msgid "Download source file" +msgstr "הורד את קובץ המקור" + +msgid "Download this page" +msgstr "הורד דף זה" + +msgid "Edit this page" +msgstr "ערוך דף זה" + +msgid "Fullscreen mode" +msgstr "מצב מסך מלא" + +msgid "Last updated on" +msgstr "עודכן לאחרונה ב" + +msgid "Launch" +msgstr "לְהַשִׁיק" + +msgid "Open an issue" +msgstr "פתח גיליון" + +msgid "Print to PDF" +msgstr "הדפס לקובץ PDF" + +msgid "Source repository" +msgstr "מאגר המקורות" + +msgid "Sphinx Book Theme" +msgstr "נושא ספר ספינקס" + +msgid "Theme by the" +msgstr "נושא מאת" + +msgid "Toggle navigation" +msgstr "החלף ניווט" + +msgid "next page" +msgstr "עמוד הבא" + +msgid "open issue" +msgstr "בעיה פתוחה" + +msgid "previous page" +msgstr "עמוד קודם" + +msgid "repository" +msgstr "מאגר" + +msgid "suggest edit" +msgstr "מציע לערוך" diff --git a/_static/locales/ja/LC_MESSAGES/booktheme.mo b/_static/locales/ja/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..1cefd29c Binary files /dev/null and b/_static/locales/ja/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/ja/LC_MESSAGES/booktheme.po b/_static/locales/ja/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..3caab09e --- /dev/null +++ b/_static/locales/ja/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ja\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "によって" + +msgid "By" +msgstr "著者" + +msgid "Contents" +msgstr "目次" + +msgid "Copyright" +msgstr "Copyright" + +msgid "Download notebook file" +msgstr "ノートブックファイルをダウンロード" + +msgid "Download source file" +msgstr "ソースファイルをダウンロード" + +msgid "Download this page" +msgstr "このページをダウンロード" + +msgid "Edit this page" +msgstr "このページを編集" + +msgid "Fullscreen mode" +msgstr "全画面モード" + +msgid "Last updated on" +msgstr "最終更新日" + +msgid "Launch" +msgstr "起動" + +msgid "Open an issue" +msgstr "問題を報告" + +msgid "Print to PDF" +msgstr "PDFに印刷" + +msgid "Source repository" +msgstr "ソースリポジトリ" + +msgid "Sphinx Book Theme" +msgstr "スフィンクスの本のテーマ" + +msgid "Theme by the" +msgstr "のテーマ" + +msgid "Toggle navigation" +msgstr "ナビゲーションを切り替え" + +msgid "next page" +msgstr "次のページ" + +msgid "open issue" +msgstr "未解決の問題" + +msgid "previous page" +msgstr "前のページ" + +msgid "repository" +msgstr "リポジトリ" + +msgid "suggest edit" +msgstr "編集を提案する" diff --git a/_static/locales/ko/LC_MESSAGES/booktheme.mo b/_static/locales/ko/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..06c7ec93 Binary files /dev/null and b/_static/locales/ko/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/ko/LC_MESSAGES/booktheme.po b/_static/locales/ko/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..2db12a1b --- /dev/null +++ b/_static/locales/ko/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ko\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "에 의해" + +msgid "By" +msgstr "으로" + +msgid "Contents" +msgstr "내용" + +msgid "Copyright" +msgstr "저작권" + +msgid "Download notebook file" +msgstr "노트북 파일 다운로드" + +msgid "Download source file" +msgstr "소스 파일 다운로드" + +msgid "Download this page" +msgstr "이 페이지 다운로드" + +msgid "Edit this page" +msgstr "이 페이지 편집" + +msgid "Fullscreen mode" +msgstr "전체 화면으로보기" + +msgid "Last updated on" +msgstr "마지막 업데이트" + +msgid "Launch" +msgstr "시작하다" + +msgid "Open an issue" +msgstr "이슈 열기" + +msgid "Print to PDF" +msgstr "PDF로 인쇄" + +msgid "Source repository" +msgstr "소스 저장소" + +msgid "Sphinx Book Theme" +msgstr "스핑크스 도서 테마" + +msgid "Theme by the" +msgstr "테마별" + +msgid "Toggle navigation" +msgstr "탐색 전환" + +msgid "next page" +msgstr "다음 페이지" + +msgid "open issue" +msgstr "열린 문제" + +msgid "previous page" +msgstr "이전 페이지" + +msgid "repository" +msgstr "저장소" + +msgid "suggest edit" +msgstr "편집 제안" diff --git a/_static/locales/lt/LC_MESSAGES/booktheme.mo b/_static/locales/lt/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..4468ba04 Binary files /dev/null and b/_static/locales/lt/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/lt/LC_MESSAGES/booktheme.po b/_static/locales/lt/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..07b64680 --- /dev/null +++ b/_static/locales/lt/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: lt\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Prie" + +msgid "By" +msgstr "Iki" + +msgid "Contents" +msgstr "Turinys" + +msgid "Copyright" +msgstr "Autorių teisės" + +msgid "Download notebook file" +msgstr "Atsisiųsti nešiojamojo kompiuterio failą" + +msgid "Download source file" +msgstr "Atsisiųsti šaltinio failą" + +msgid "Download this page" +msgstr "Atsisiųskite šį puslapį" + +msgid "Edit this page" +msgstr "Redaguoti šį puslapį" + +msgid "Fullscreen mode" +msgstr "Pilno ekrano režimas" + +msgid "Last updated on" +msgstr "Paskutinį kartą atnaujinta" + +msgid "Launch" +msgstr "Paleiskite" + +msgid "Open an issue" +msgstr "Atidarykite problemą" + +msgid "Print to PDF" +msgstr "Spausdinti į PDF" + +msgid "Source repository" +msgstr "Šaltinio saugykla" + +msgid "Sphinx Book Theme" +msgstr "Sfinkso knygos tema" + +msgid "Theme by the" +msgstr "Tema" + +msgid "Toggle navigation" +msgstr "Perjungti naršymą" + +msgid "next page" +msgstr "Kitas puslapis" + +msgid "open issue" +msgstr "atviras klausimas" + +msgid "previous page" +msgstr "Ankstesnis puslapis" + +msgid "repository" +msgstr "saugykla" + +msgid "suggest edit" +msgstr "pasiūlyti redaguoti" diff --git a/_static/locales/lv/LC_MESSAGES/booktheme.mo b/_static/locales/lv/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..74aa4d89 Binary files /dev/null and b/_static/locales/lv/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/lv/LC_MESSAGES/booktheme.po b/_static/locales/lv/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..b741c289 --- /dev/null +++ b/_static/locales/lv/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: lv\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Ar" + +msgid "By" +msgstr "Autors" + +msgid "Contents" +msgstr "Saturs" + +msgid "Copyright" +msgstr "Autortiesības" + +msgid "Download notebook file" +msgstr "Lejupielādēt piezīmju grāmatiņu" + +msgid "Download source file" +msgstr "Lejupielādēt avota failu" + +msgid "Download this page" +msgstr "Lejupielādējiet šo lapu" + +msgid "Edit this page" +msgstr "Rediģēt šo lapu" + +msgid "Fullscreen mode" +msgstr "Pilnekrāna režīms" + +msgid "Last updated on" +msgstr "Pēdējoreiz atjaunināts" + +msgid "Launch" +msgstr "Uzsākt" + +msgid "Open an issue" +msgstr "Atveriet problēmu" + +msgid "Print to PDF" +msgstr "Drukāt PDF formātā" + +msgid "Source repository" +msgstr "Avota krātuve" + +msgid "Sphinx Book Theme" +msgstr "Sfinksa grāmatas tēma" + +msgid "Theme by the" +msgstr "Autora tēma" + +msgid "Toggle navigation" +msgstr "Pārslēgt navigāciju" + +msgid "next page" +msgstr "nākamā lapaspuse" + +msgid "open issue" +msgstr "atklāts jautājums" + +msgid "previous page" +msgstr "iepriekšējā lapa" + +msgid "repository" +msgstr "krātuve" + +msgid "suggest edit" +msgstr "ieteikt rediģēt" diff --git a/_static/locales/ml/LC_MESSAGES/booktheme.mo b/_static/locales/ml/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..2736e8fc Binary files /dev/null and b/_static/locales/ml/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/ml/LC_MESSAGES/booktheme.po b/_static/locales/ml/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..bdad3de2 --- /dev/null +++ b/_static/locales/ml/LC_MESSAGES/booktheme.po @@ -0,0 +1,66 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ml\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "എഴുതിയത്" + +msgid "By" +msgstr "എഴുതിയത്" + +msgid "Copyright" +msgstr "പകർപ്പവകാശം" + +msgid "Download notebook file" +msgstr "നോട്ട്ബുക്ക് ഫയൽ ഡൺലോഡ് ചെയ്യുക" + +msgid "Download source file" +msgstr "ഉറവിട ഫയൽ ഡൗൺലോഡുചെയ്യുക" + +msgid "Download this page" +msgstr "ഈ പേജ് ഡൗൺലോഡുചെയ്യുക" + +msgid "Edit this page" +msgstr "ഈ പേജ് എഡിറ്റുചെയ്യുക" + +msgid "Last updated on" +msgstr "അവസാനം അപ്‌ഡേറ്റുചെയ്‌തത്" + +msgid "Launch" +msgstr "സമാരംഭിക്കുക" + +msgid "Open an issue" +msgstr "ഒരു പ്രശ്നം തുറക്കുക" + +msgid "Print to PDF" +msgstr "PDF- ലേക്ക് പ്രിന്റുചെയ്യുക" + +msgid "Source repository" +msgstr "ഉറവിട ശേഖരം" + +msgid "Sphinx Book Theme" +msgstr "സ്ഫിങ്ക്സ് പുസ്തക തീം" + +msgid "Theme by the" +msgstr "പ്രമേയം" + +msgid "Toggle navigation" +msgstr "നാവിഗേഷൻ ടോഗിൾ ചെയ്യുക" + +msgid "next page" +msgstr "അടുത്ത പേജ്" + +msgid "open issue" +msgstr "തുറന്ന പ്രശ്നം" + +msgid "previous page" +msgstr "മുൻപത്തെ താൾ" + +msgid "suggest edit" +msgstr "എഡിറ്റുചെയ്യാൻ നിർദ്ദേശിക്കുക" diff --git a/_static/locales/mr/LC_MESSAGES/booktheme.mo b/_static/locales/mr/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..fe530100 Binary files /dev/null and b/_static/locales/mr/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/mr/LC_MESSAGES/booktheme.po b/_static/locales/mr/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..61bfad4d --- /dev/null +++ b/_static/locales/mr/LC_MESSAGES/booktheme.po @@ -0,0 +1,66 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: mr\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "द्वारा" + +msgid "By" +msgstr "द्वारा" + +msgid "Copyright" +msgstr "कॉपीराइट" + +msgid "Download notebook file" +msgstr "नोटबुक फाईल डाउनलोड करा" + +msgid "Download source file" +msgstr "स्त्रोत फाइल डाउनलोड करा" + +msgid "Download this page" +msgstr "हे पृष्ठ डाउनलोड करा" + +msgid "Edit this page" +msgstr "हे पृष्ठ संपादित करा" + +msgid "Last updated on" +msgstr "अखेरचे अद्यतनित" + +msgid "Launch" +msgstr "लाँच करा" + +msgid "Open an issue" +msgstr "एक मुद्दा उघडा" + +msgid "Print to PDF" +msgstr "पीडीएफवर मुद्रित करा" + +msgid "Source repository" +msgstr "स्त्रोत भांडार" + +msgid "Sphinx Book Theme" +msgstr "स्फिंक्स बुक थीम" + +msgid "Theme by the" +msgstr "द्वारा थीम" + +msgid "Toggle navigation" +msgstr "नेव्हिगेशन टॉगल करा" + +msgid "next page" +msgstr "पुढील पृष्ठ" + +msgid "open issue" +msgstr "खुला मुद्दा" + +msgid "previous page" +msgstr "मागील पान" + +msgid "suggest edit" +msgstr "संपादन सुचवा" diff --git a/_static/locales/ms/LC_MESSAGES/booktheme.mo b/_static/locales/ms/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..f02603fa Binary files /dev/null and b/_static/locales/ms/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/ms/LC_MESSAGES/booktheme.po b/_static/locales/ms/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..ade6515a --- /dev/null +++ b/_static/locales/ms/LC_MESSAGES/booktheme.po @@ -0,0 +1,66 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ms\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Oleh" + +msgid "By" +msgstr "Oleh" + +msgid "Copyright" +msgstr "hak cipta" + +msgid "Download notebook file" +msgstr "Muat turun fail buku nota" + +msgid "Download source file" +msgstr "Muat turun fail sumber" + +msgid "Download this page" +msgstr "Muat turun halaman ini" + +msgid "Edit this page" +msgstr "Edit halaman ini" + +msgid "Last updated on" +msgstr "Terakhir dikemas kini pada" + +msgid "Launch" +msgstr "Lancarkan" + +msgid "Open an issue" +msgstr "Buka masalah" + +msgid "Print to PDF" +msgstr "Cetak ke PDF" + +msgid "Source repository" +msgstr "Repositori sumber" + +msgid "Sphinx Book Theme" +msgstr "Tema Buku Sphinx" + +msgid "Theme by the" +msgstr "Tema oleh" + +msgid "Toggle navigation" +msgstr "Togol navigasi" + +msgid "next page" +msgstr "muka surat seterusnya" + +msgid "open issue" +msgstr "isu terbuka" + +msgid "previous page" +msgstr "halaman sebelumnya" + +msgid "suggest edit" +msgstr "cadangkan edit" diff --git a/_static/locales/nl/LC_MESSAGES/booktheme.mo b/_static/locales/nl/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..e59e7ecb Binary files /dev/null and b/_static/locales/nl/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/nl/LC_MESSAGES/booktheme.po b/_static/locales/nl/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..e114611d --- /dev/null +++ b/_static/locales/nl/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: nl\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Door de" + +msgid "By" +msgstr "Door" + +msgid "Contents" +msgstr "Inhoud" + +msgid "Copyright" +msgstr "auteursrechten" + +msgid "Download notebook file" +msgstr "Download notebookbestand" + +msgid "Download source file" +msgstr "Download het bronbestand" + +msgid "Download this page" +msgstr "Download deze pagina" + +msgid "Edit this page" +msgstr "bewerk deze pagina" + +msgid "Fullscreen mode" +msgstr "Volledig scherm" + +msgid "Last updated on" +msgstr "Laatst geupdate op" + +msgid "Launch" +msgstr "Lancering" + +msgid "Open an issue" +msgstr "Open een probleem" + +msgid "Print to PDF" +msgstr "Afdrukken naar pdf" + +msgid "Source repository" +msgstr "Bronopslagplaats" + +msgid "Sphinx Book Theme" +msgstr "Sphinx-boekthema" + +msgid "Theme by the" +msgstr "Thema door de" + +msgid "Toggle navigation" +msgstr "Schakel navigatie" + +msgid "next page" +msgstr "volgende bladzijde" + +msgid "open issue" +msgstr "open probleem" + +msgid "previous page" +msgstr "vorige pagina" + +msgid "repository" +msgstr "repository" + +msgid "suggest edit" +msgstr "suggereren bewerken" diff --git a/_static/locales/no/LC_MESSAGES/booktheme.mo b/_static/locales/no/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..6cd15c88 Binary files /dev/null and b/_static/locales/no/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/no/LC_MESSAGES/booktheme.po b/_static/locales/no/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..53fa9fc3 --- /dev/null +++ b/_static/locales/no/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: no\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Ved" + +msgid "By" +msgstr "Av" + +msgid "Contents" +msgstr "Innhold" + +msgid "Copyright" +msgstr "opphavsrett" + +msgid "Download notebook file" +msgstr "Last ned notatbokfilen" + +msgid "Download source file" +msgstr "Last ned kildefilen" + +msgid "Download this page" +msgstr "Last ned denne siden" + +msgid "Edit this page" +msgstr "Rediger denne siden" + +msgid "Fullscreen mode" +msgstr "Fullskjerm-modus" + +msgid "Last updated on" +msgstr "Sist oppdatert den" + +msgid "Launch" +msgstr "Start" + +msgid "Open an issue" +msgstr "Åpne et problem" + +msgid "Print to PDF" +msgstr "Skriv ut til PDF" + +msgid "Source repository" +msgstr "Kildedepot" + +msgid "Sphinx Book Theme" +msgstr "Sphinx boktema" + +msgid "Theme by the" +msgstr "Tema av" + +msgid "Toggle navigation" +msgstr "Bytt navigasjon" + +msgid "next page" +msgstr "neste side" + +msgid "open issue" +msgstr "åpent nummer" + +msgid "previous page" +msgstr "forrige side" + +msgid "repository" +msgstr "oppbevaringssted" + +msgid "suggest edit" +msgstr "foreslå redigering" diff --git a/_static/locales/pl/LC_MESSAGES/booktheme.mo b/_static/locales/pl/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..9ebb584f Binary files /dev/null and b/_static/locales/pl/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/pl/LC_MESSAGES/booktheme.po b/_static/locales/pl/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..a4822159 --- /dev/null +++ b/_static/locales/pl/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: pl\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Przez" + +msgid "By" +msgstr "Przez" + +msgid "Contents" +msgstr "Zawartość" + +msgid "Copyright" +msgstr "prawa autorskie" + +msgid "Download notebook file" +msgstr "Pobierz plik notatnika" + +msgid "Download source file" +msgstr "Pobierz plik źródłowy" + +msgid "Download this page" +msgstr "Pobierz tę stronę" + +msgid "Edit this page" +msgstr "Edytuj tę strone" + +msgid "Fullscreen mode" +msgstr "Pełny ekran" + +msgid "Last updated on" +msgstr "Ostatnia aktualizacja" + +msgid "Launch" +msgstr "Uruchomić" + +msgid "Open an issue" +msgstr "Otwórz problem" + +msgid "Print to PDF" +msgstr "Drukuj do PDF" + +msgid "Source repository" +msgstr "Repozytorium źródłowe" + +msgid "Sphinx Book Theme" +msgstr "Motyw książki Sphinx" + +msgid "Theme by the" +msgstr "Motyw autorstwa" + +msgid "Toggle navigation" +msgstr "Przełącz nawigację" + +msgid "next page" +msgstr "Następna strona" + +msgid "open issue" +msgstr "otwarty problem" + +msgid "previous page" +msgstr "Poprzednia strona" + +msgid "repository" +msgstr "magazyn" + +msgid "suggest edit" +msgstr "zaproponuj edycję" diff --git a/_static/locales/pt/LC_MESSAGES/booktheme.mo b/_static/locales/pt/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..d0ddb872 Binary files /dev/null and b/_static/locales/pt/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/pt/LC_MESSAGES/booktheme.po b/_static/locales/pt/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..bbc872d0 --- /dev/null +++ b/_static/locales/pt/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: pt\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Pelo" + +msgid "By" +msgstr "De" + +msgid "Contents" +msgstr "Conteúdo" + +msgid "Copyright" +msgstr "direito autoral" + +msgid "Download notebook file" +msgstr "Baixar arquivo de notebook" + +msgid "Download source file" +msgstr "Baixar arquivo fonte" + +msgid "Download this page" +msgstr "Baixe esta página" + +msgid "Edit this page" +msgstr "Edite essa página" + +msgid "Fullscreen mode" +msgstr "Modo tela cheia" + +msgid "Last updated on" +msgstr "Última atualização em" + +msgid "Launch" +msgstr "Lançamento" + +msgid "Open an issue" +msgstr "Abra um problema" + +msgid "Print to PDF" +msgstr "Imprimir em PDF" + +msgid "Source repository" +msgstr "Repositório fonte" + +msgid "Sphinx Book Theme" +msgstr "Tema do livro Sphinx" + +msgid "Theme by the" +msgstr "Tema por" + +msgid "Toggle navigation" +msgstr "Alternar de navegação" + +msgid "next page" +msgstr "próxima página" + +msgid "open issue" +msgstr "questão aberta" + +msgid "previous page" +msgstr "página anterior" + +msgid "repository" +msgstr "repositório" + +msgid "suggest edit" +msgstr "sugerir edição" diff --git a/_static/locales/ro/LC_MESSAGES/booktheme.mo b/_static/locales/ro/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..3c36ab1d Binary files /dev/null and b/_static/locales/ro/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/ro/LC_MESSAGES/booktheme.po b/_static/locales/ro/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..b9b8b4f3 --- /dev/null +++ b/_static/locales/ro/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ro\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Langa" + +msgid "By" +msgstr "De" + +msgid "Contents" +msgstr "Cuprins" + +msgid "Copyright" +msgstr "Drepturi de autor" + +msgid "Download notebook file" +msgstr "Descărcați fișierul notebook" + +msgid "Download source file" +msgstr "Descărcați fișierul sursă" + +msgid "Download this page" +msgstr "Descarcă această pagină" + +msgid "Edit this page" +msgstr "Editați această pagină" + +msgid "Fullscreen mode" +msgstr "Modul ecran întreg" + +msgid "Last updated on" +msgstr "Ultima actualizare la" + +msgid "Launch" +msgstr "Lansa" + +msgid "Open an issue" +msgstr "Deschideți o problemă" + +msgid "Print to PDF" +msgstr "Imprimați în PDF" + +msgid "Source repository" +msgstr "Depozit sursă" + +msgid "Sphinx Book Theme" +msgstr "Tema Sphinx Book" + +msgid "Theme by the" +msgstr "Tema de" + +msgid "Toggle navigation" +msgstr "Comutare navigare" + +msgid "next page" +msgstr "pagina următoare" + +msgid "open issue" +msgstr "problema deschisă" + +msgid "previous page" +msgstr "pagina anterioară" + +msgid "repository" +msgstr "repertoriu" + +msgid "suggest edit" +msgstr "sugerează editare" diff --git a/_static/locales/ru/LC_MESSAGES/booktheme.mo b/_static/locales/ru/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..5ea2e5c9 Binary files /dev/null and b/_static/locales/ru/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/ru/LC_MESSAGES/booktheme.po b/_static/locales/ru/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..e0f35551 --- /dev/null +++ b/_static/locales/ru/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ru\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Посредством" + +msgid "By" +msgstr "Автор:" + +msgid "Contents" +msgstr "Содержание" + +msgid "Copyright" +msgstr "авторское право" + +msgid "Download notebook file" +msgstr "Скачать файл записной книжки" + +msgid "Download source file" +msgstr "Скачать исходный файл" + +msgid "Download this page" +msgstr "Загрузите эту страницу" + +msgid "Edit this page" +msgstr "Редактировать эту страницу" + +msgid "Fullscreen mode" +msgstr "Полноэкранный режим" + +msgid "Last updated on" +msgstr "Последнее обновление" + +msgid "Launch" +msgstr "Запуск" + +msgid "Open an issue" +msgstr "Открыть вопрос" + +msgid "Print to PDF" +msgstr "Распечатать в PDF" + +msgid "Source repository" +msgstr "Исходный репозиторий" + +msgid "Sphinx Book Theme" +msgstr "Тема книги Сфинкс" + +msgid "Theme by the" +msgstr "Тема от" + +msgid "Toggle navigation" +msgstr "Переключить навигацию" + +msgid "next page" +msgstr "Следующая страница" + +msgid "open issue" +msgstr "открытый вопрос" + +msgid "previous page" +msgstr "Предыдущая страница" + +msgid "repository" +msgstr "хранилище" + +msgid "suggest edit" +msgstr "предложить редактировать" diff --git a/_static/locales/sk/LC_MESSAGES/booktheme.mo b/_static/locales/sk/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..59bd0ddf Binary files /dev/null and b/_static/locales/sk/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/sk/LC_MESSAGES/booktheme.po b/_static/locales/sk/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..4b5225a3 --- /dev/null +++ b/_static/locales/sk/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: sk\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Podľa" + +msgid "By" +msgstr "Autor:" + +msgid "Contents" +msgstr "Obsah" + +msgid "Copyright" +msgstr "Autorské práva" + +msgid "Download notebook file" +msgstr "Stiahnite si zošit" + +msgid "Download source file" +msgstr "Stiahnite si zdrojový súbor" + +msgid "Download this page" +msgstr "Stiahnite si túto stránku" + +msgid "Edit this page" +msgstr "Upraviť túto stránku" + +msgid "Fullscreen mode" +msgstr "Režim celej obrazovky" + +msgid "Last updated on" +msgstr "Posledná aktualizácia dňa" + +msgid "Launch" +msgstr "Spustiť" + +msgid "Open an issue" +msgstr "Otvorte problém" + +msgid "Print to PDF" +msgstr "Tlač do PDF" + +msgid "Source repository" +msgstr "Zdrojové úložisko" + +msgid "Sphinx Book Theme" +msgstr "Téma knihy Sfinga" + +msgid "Theme by the" +msgstr "Téma od" + +msgid "Toggle navigation" +msgstr "Prepnúť navigáciu" + +msgid "next page" +msgstr "ďalšia strana" + +msgid "open issue" +msgstr "otvorené vydanie" + +msgid "previous page" +msgstr "predchádzajúca strana" + +msgid "repository" +msgstr "Úložisko" + +msgid "suggest edit" +msgstr "navrhnúť úpravu" diff --git a/_static/locales/sl/LC_MESSAGES/booktheme.mo b/_static/locales/sl/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..87bf26de Binary files /dev/null and b/_static/locales/sl/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/sl/LC_MESSAGES/booktheme.po b/_static/locales/sl/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..45592e71 --- /dev/null +++ b/_static/locales/sl/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: sl\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Avtor" + +msgid "By" +msgstr "Avtor" + +msgid "Contents" +msgstr "Vsebina" + +msgid "Copyright" +msgstr "avtorske pravice" + +msgid "Download notebook file" +msgstr "Prenesite datoteko zvezka" + +msgid "Download source file" +msgstr "Prenesite izvorno datoteko" + +msgid "Download this page" +msgstr "Prenesite to stran" + +msgid "Edit this page" +msgstr "Uredite to stran" + +msgid "Fullscreen mode" +msgstr "Celozaslonski način" + +msgid "Last updated on" +msgstr "Nazadnje posodobljeno dne" + +msgid "Launch" +msgstr "Kosilo" + +msgid "Open an issue" +msgstr "Odprite številko" + +msgid "Print to PDF" +msgstr "Natisni v PDF" + +msgid "Source repository" +msgstr "Izvorno skladišče" + +msgid "Sphinx Book Theme" +msgstr "Tema knjige Sphinx" + +msgid "Theme by the" +msgstr "Tema avtorja" + +msgid "Toggle navigation" +msgstr "Preklopi navigacijo" + +msgid "next page" +msgstr "Naslednja stran" + +msgid "open issue" +msgstr "odprto vprašanje" + +msgid "previous page" +msgstr "Prejšnja stran" + +msgid "repository" +msgstr "odlagališče" + +msgid "suggest edit" +msgstr "predlagajte urejanje" diff --git a/_static/locales/sr/LC_MESSAGES/booktheme.mo b/_static/locales/sr/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..ec740f48 Binary files /dev/null and b/_static/locales/sr/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/sr/LC_MESSAGES/booktheme.po b/_static/locales/sr/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..4ddf693d --- /dev/null +++ b/_static/locales/sr/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: sr\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Од" + +msgid "By" +msgstr "Од стране" + +msgid "Contents" +msgstr "Садржај" + +msgid "Copyright" +msgstr "Ауторско право" + +msgid "Download notebook file" +msgstr "Преузмите датотеку бележнице" + +msgid "Download source file" +msgstr "Преузми изворну датотеку" + +msgid "Download this page" +msgstr "Преузмите ову страницу" + +msgid "Edit this page" +msgstr "Уредите ову страницу" + +msgid "Fullscreen mode" +msgstr "Режим целог екрана" + +msgid "Last updated on" +msgstr "Последње ажурирање" + +msgid "Launch" +msgstr "Лансирање" + +msgid "Open an issue" +msgstr "Отворите издање" + +msgid "Print to PDF" +msgstr "Испис у ПДФ" + +msgid "Source repository" +msgstr "Изворно спремиште" + +msgid "Sphinx Book Theme" +msgstr "Тема књиге Спхинк" + +msgid "Theme by the" +msgstr "Тхеме би" + +msgid "Toggle navigation" +msgstr "Укључи / искључи навигацију" + +msgid "next page" +msgstr "Следећа страна" + +msgid "open issue" +msgstr "отворено издање" + +msgid "previous page" +msgstr "Претходна страница" + +msgid "repository" +msgstr "спремиште" + +msgid "suggest edit" +msgstr "предложи уређивање" diff --git a/_static/locales/sv/LC_MESSAGES/booktheme.mo b/_static/locales/sv/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..b07dc76f Binary files /dev/null and b/_static/locales/sv/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/sv/LC_MESSAGES/booktheme.po b/_static/locales/sv/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..a5587a56 --- /dev/null +++ b/_static/locales/sv/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: sv\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Av den" + +msgid "By" +msgstr "Av" + +msgid "Contents" +msgstr "Innehåll" + +msgid "Copyright" +msgstr "Upphovsrätt" + +msgid "Download notebook file" +msgstr "Ladda ner notebook-fil" + +msgid "Download source file" +msgstr "Ladda ner källfil" + +msgid "Download this page" +msgstr "Ladda ner den här sidan" + +msgid "Edit this page" +msgstr "Redigera den här sidan" + +msgid "Fullscreen mode" +msgstr "Fullskärmsläge" + +msgid "Last updated on" +msgstr "Senast uppdaterad den" + +msgid "Launch" +msgstr "Öppna" + +msgid "Open an issue" +msgstr "Öppna en problemrapport" + +msgid "Print to PDF" +msgstr "Skriv ut till PDF" + +msgid "Source repository" +msgstr "Källkodsrepositorium" + +msgid "Sphinx Book Theme" +msgstr "Sphinx Boktema" + +msgid "Theme by the" +msgstr "Tema av" + +msgid "Toggle navigation" +msgstr "Växla navigering" + +msgid "next page" +msgstr "nästa sida" + +msgid "open issue" +msgstr "öppna problemrapport" + +msgid "previous page" +msgstr "föregående sida" + +msgid "repository" +msgstr "repositorium" + +msgid "suggest edit" +msgstr "föreslå ändring" diff --git a/_static/locales/ta/LC_MESSAGES/booktheme.mo b/_static/locales/ta/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..29f52e1f Binary files /dev/null and b/_static/locales/ta/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/ta/LC_MESSAGES/booktheme.po b/_static/locales/ta/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..fb871e23 --- /dev/null +++ b/_static/locales/ta/LC_MESSAGES/booktheme.po @@ -0,0 +1,66 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ta\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "மூலம்" + +msgid "By" +msgstr "வழங்கியவர்" + +msgid "Copyright" +msgstr "பதிப்புரிமை" + +msgid "Download notebook file" +msgstr "நோட்புக் கோப்பைப் பதிவிறக்கவும்" + +msgid "Download source file" +msgstr "மூல கோப்பைப் பதிவிறக்குக" + +msgid "Download this page" +msgstr "இந்தப் பக்கத்தைப் பதிவிறக்கவும்" + +msgid "Edit this page" +msgstr "இந்தப் பக்கத்தைத் திருத்தவும்" + +msgid "Last updated on" +msgstr "கடைசியாக புதுப்பிக்கப்பட்டது" + +msgid "Launch" +msgstr "தொடங்க" + +msgid "Open an issue" +msgstr "சிக்கலைத் திறக்கவும்" + +msgid "Print to PDF" +msgstr "PDF இல் அச்சிடுக" + +msgid "Source repository" +msgstr "மூல களஞ்சியம்" + +msgid "Sphinx Book Theme" +msgstr "ஸ்பிங்க்ஸ் புத்தக தீம்" + +msgid "Theme by the" +msgstr "வழங்கிய தீம்" + +msgid "Toggle navigation" +msgstr "வழிசெலுத்தலை நிலைமாற்று" + +msgid "next page" +msgstr "அடுத்த பக்கம்" + +msgid "open issue" +msgstr "திறந்த பிரச்சினை" + +msgid "previous page" +msgstr "முந்தைய பக்கம்" + +msgid "suggest edit" +msgstr "திருத்த பரிந்துரைக்கவும்" diff --git a/_static/locales/te/LC_MESSAGES/booktheme.mo b/_static/locales/te/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..0a5f4b46 Binary files /dev/null and b/_static/locales/te/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/te/LC_MESSAGES/booktheme.po b/_static/locales/te/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..22ab77c1 --- /dev/null +++ b/_static/locales/te/LC_MESSAGES/booktheme.po @@ -0,0 +1,66 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: te\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "ద్వారా" + +msgid "By" +msgstr "ద్వారా" + +msgid "Copyright" +msgstr "కాపీరైట్" + +msgid "Download notebook file" +msgstr "నోట్బుక్ ఫైల్ను డౌన్లోడ్ చేయండి" + +msgid "Download source file" +msgstr "మూల ఫైల్‌ను డౌన్‌లోడ్ చేయండి" + +msgid "Download this page" +msgstr "ఈ పేజీని డౌన్‌లోడ్ చేయండి" + +msgid "Edit this page" +msgstr "ఈ పేజీని సవరించండి" + +msgid "Last updated on" +msgstr "చివరిగా నవీకరించబడింది" + +msgid "Launch" +msgstr "ప్రారంభించండి" + +msgid "Open an issue" +msgstr "సమస్యను తెరవండి" + +msgid "Print to PDF" +msgstr "PDF కి ముద్రించండి" + +msgid "Source repository" +msgstr "మూల రిపోజిటరీ" + +msgid "Sphinx Book Theme" +msgstr "సింహిక పుస్తక థీమ్" + +msgid "Theme by the" +msgstr "ద్వారా థీమ్" + +msgid "Toggle navigation" +msgstr "నావిగేషన్‌ను టోగుల్ చేయండి" + +msgid "next page" +msgstr "తరువాతి పేజీ" + +msgid "open issue" +msgstr "ఓపెన్ ఇష్యూ" + +msgid "previous page" +msgstr "ముందు పేజి" + +msgid "suggest edit" +msgstr "సవరించమని సూచించండి" diff --git a/_static/locales/tg/LC_MESSAGES/booktheme.mo b/_static/locales/tg/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..b21c6c63 Binary files /dev/null and b/_static/locales/tg/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/tg/LC_MESSAGES/booktheme.po b/_static/locales/tg/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..e499352d --- /dev/null +++ b/_static/locales/tg/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: tg\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Бо" + +msgid "By" +msgstr "Бо" + +msgid "Contents" +msgstr "Мундариҷа" + +msgid "Copyright" +msgstr "Ҳуқуқи муаллиф" + +msgid "Download notebook file" +msgstr "Файли дафтарро зеркашӣ кунед" + +msgid "Download source file" +msgstr "Файли манбаъро зеркашӣ кунед" + +msgid "Download this page" +msgstr "Ин саҳифаро зеркашӣ кунед" + +msgid "Edit this page" +msgstr "Ин саҳифаро таҳрир кунед" + +msgid "Fullscreen mode" +msgstr "Ҳолати экрани пурра" + +msgid "Last updated on" +msgstr "Last навсозӣ дар" + +msgid "Launch" +msgstr "Оғоз" + +msgid "Open an issue" +msgstr "Масъаларо кушоед" + +msgid "Print to PDF" +msgstr "Чоп ба PDF" + +msgid "Source repository" +msgstr "Анбори манбаъ" + +msgid "Sphinx Book Theme" +msgstr "Сфинкс Мавзӯи китоб" + +msgid "Theme by the" +msgstr "Мавзӯъи аз" + +msgid "Toggle navigation" +msgstr "Гузаришро иваз кунед" + +msgid "next page" +msgstr "саҳифаи оянда" + +msgid "open issue" +msgstr "барориши кушод" + +msgid "previous page" +msgstr "саҳифаи қаблӣ" + +msgid "repository" +msgstr "анбор" + +msgid "suggest edit" +msgstr "пешниҳод вироиш" diff --git a/_static/locales/th/LC_MESSAGES/booktheme.mo b/_static/locales/th/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..abede98a Binary files /dev/null and b/_static/locales/th/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/th/LC_MESSAGES/booktheme.po b/_static/locales/th/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..6f0103ea --- /dev/null +++ b/_static/locales/th/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: th\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "โดย" + +msgid "By" +msgstr "โดย" + +msgid "Contents" +msgstr "สารบัญ" + +msgid "Copyright" +msgstr "ลิขสิทธิ์" + +msgid "Download notebook file" +msgstr "ดาวน์โหลดไฟล์สมุดบันทึก" + +msgid "Download source file" +msgstr "ดาวน์โหลดไฟล์ต้นฉบับ" + +msgid "Download this page" +msgstr "ดาวน์โหลดหน้านี้" + +msgid "Edit this page" +msgstr "แก้ไขหน้านี้" + +msgid "Fullscreen mode" +msgstr "โหมดเต็มหน้าจอ" + +msgid "Last updated on" +msgstr "ปรับปรุงล่าสุดเมื่อ" + +msgid "Launch" +msgstr "เปิด" + +msgid "Open an issue" +msgstr "เปิดปัญหา" + +msgid "Print to PDF" +msgstr "พิมพ์เป็น PDF" + +msgid "Source repository" +msgstr "ที่เก็บซอร์ส" + +msgid "Sphinx Book Theme" +msgstr "ธีมหนังสือสฟิงซ์" + +msgid "Theme by the" +msgstr "ธีมโดย" + +msgid "Toggle navigation" +msgstr "ไม่ต้องสลับช่องทาง" + +msgid "next page" +msgstr "หน้าต่อไป" + +msgid "open issue" +msgstr "เปิดปัญหา" + +msgid "previous page" +msgstr "หน้าที่แล้ว" + +msgid "repository" +msgstr "ที่เก็บ" + +msgid "suggest edit" +msgstr "แนะนำแก้ไข" diff --git a/_static/locales/tl/LC_MESSAGES/booktheme.mo b/_static/locales/tl/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..8df1b733 Binary files /dev/null and b/_static/locales/tl/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/tl/LC_MESSAGES/booktheme.po b/_static/locales/tl/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..dbeb2565 --- /dev/null +++ b/_static/locales/tl/LC_MESSAGES/booktheme.po @@ -0,0 +1,66 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: tl\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Sa pamamagitan ng" + +msgid "By" +msgstr "Ni" + +msgid "Copyright" +msgstr "Copyright" + +msgid "Download notebook file" +msgstr "Mag-download ng file ng notebook" + +msgid "Download source file" +msgstr "Mag-download ng file ng pinagmulan" + +msgid "Download this page" +msgstr "I-download ang pahinang ito" + +msgid "Edit this page" +msgstr "I-edit ang pahinang ito" + +msgid "Last updated on" +msgstr "Huling na-update noong" + +msgid "Launch" +msgstr "Ilunsad" + +msgid "Open an issue" +msgstr "Magbukas ng isyu" + +msgid "Print to PDF" +msgstr "I-print sa PDF" + +msgid "Source repository" +msgstr "Pinagmulan ng imbakan" + +msgid "Sphinx Book Theme" +msgstr "Tema ng Sphinx Book" + +msgid "Theme by the" +msgstr "Tema ng" + +msgid "Toggle navigation" +msgstr "I-toggle ang pag-navigate" + +msgid "next page" +msgstr "Susunod na pahina" + +msgid "open issue" +msgstr "bukas na isyu" + +msgid "previous page" +msgstr "Nakaraang pahina" + +msgid "suggest edit" +msgstr "iminumungkahi i-edit" diff --git a/_static/locales/tr/LC_MESSAGES/booktheme.mo b/_static/locales/tr/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..029ae18a Binary files /dev/null and b/_static/locales/tr/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/tr/LC_MESSAGES/booktheme.po b/_static/locales/tr/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..610c1ab0 --- /dev/null +++ b/_static/locales/tr/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: tr\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Tarafından" + +msgid "By" +msgstr "Tarafından" + +msgid "Contents" +msgstr "İçindekiler" + +msgid "Copyright" +msgstr "Telif hakkı" + +msgid "Download notebook file" +msgstr "Defter dosyasını indirin" + +msgid "Download source file" +msgstr "Kaynak dosyayı indirin" + +msgid "Download this page" +msgstr "Bu sayfayı indirin" + +msgid "Edit this page" +msgstr "Bu sayfayı düzenle" + +msgid "Fullscreen mode" +msgstr "Tam ekran modu" + +msgid "Last updated on" +msgstr "Son güncelleme tarihi" + +msgid "Launch" +msgstr "Başlatmak" + +msgid "Open an issue" +msgstr "Bir sorunu açın" + +msgid "Print to PDF" +msgstr "PDF olarak yazdır" + +msgid "Source repository" +msgstr "Kaynak kod deposu" + +msgid "Sphinx Book Theme" +msgstr "Sfenks Kitap Teması" + +msgid "Theme by the" +msgstr "Tarafından tema" + +msgid "Toggle navigation" +msgstr "Gezinmeyi değiştir" + +msgid "next page" +msgstr "sonraki Sayfa" + +msgid "open issue" +msgstr "Açık konu" + +msgid "previous page" +msgstr "önceki sayfa" + +msgid "repository" +msgstr "depo" + +msgid "suggest edit" +msgstr "düzenleme öner" diff --git a/_static/locales/uk/LC_MESSAGES/booktheme.mo b/_static/locales/uk/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..16ab7890 Binary files /dev/null and b/_static/locales/uk/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/uk/LC_MESSAGES/booktheme.po b/_static/locales/uk/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..8ae61c48 --- /dev/null +++ b/_static/locales/uk/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: uk\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "По" + +msgid "By" +msgstr "Автор" + +msgid "Contents" +msgstr "Зміст" + +msgid "Copyright" +msgstr "Авторське право" + +msgid "Download notebook file" +msgstr "Завантажте файл блокнота" + +msgid "Download source file" +msgstr "Завантажити вихідний файл" + +msgid "Download this page" +msgstr "Завантажте цю сторінку" + +msgid "Edit this page" +msgstr "Редагувати цю сторінку" + +msgid "Fullscreen mode" +msgstr "Повноекранний режим" + +msgid "Last updated on" +msgstr "Останнє оновлення:" + +msgid "Launch" +msgstr "Запуск" + +msgid "Open an issue" +msgstr "Відкрийте випуск" + +msgid "Print to PDF" +msgstr "Друк у форматі PDF" + +msgid "Source repository" +msgstr "Джерело сховища" + +msgid "Sphinx Book Theme" +msgstr "Тема книги \"Сфінкс\"" + +msgid "Theme by the" +msgstr "Тема від" + +msgid "Toggle navigation" +msgstr "Переключити навігацію" + +msgid "next page" +msgstr "Наступна сторінка" + +msgid "open issue" +msgstr "відкритий випуск" + +msgid "previous page" +msgstr "Попередня сторінка" + +msgid "repository" +msgstr "сховище" + +msgid "suggest edit" +msgstr "запропонувати редагувати" diff --git a/_static/locales/ur/LC_MESSAGES/booktheme.mo b/_static/locales/ur/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..de8c84b9 Binary files /dev/null and b/_static/locales/ur/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/ur/LC_MESSAGES/booktheme.po b/_static/locales/ur/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..63018eae --- /dev/null +++ b/_static/locales/ur/LC_MESSAGES/booktheme.po @@ -0,0 +1,66 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: ur\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "کی طرف" + +msgid "By" +msgstr "بذریعہ" + +msgid "Copyright" +msgstr "کاپی رائٹ" + +msgid "Download notebook file" +msgstr "نوٹ بک فائل ڈاؤن لوڈ کریں" + +msgid "Download source file" +msgstr "سورس فائل ڈاؤن لوڈ کریں" + +msgid "Download this page" +msgstr "اس صفحے کو ڈاؤن لوڈ کریں" + +msgid "Edit this page" +msgstr "اس صفحے میں ترمیم کریں" + +msgid "Last updated on" +msgstr "آخری بار تازہ کاری ہوئی" + +msgid "Launch" +msgstr "لانچ کریں" + +msgid "Open an issue" +msgstr "ایک مسئلہ کھولیں" + +msgid "Print to PDF" +msgstr "پی ڈی ایف پرنٹ کریں" + +msgid "Source repository" +msgstr "ماخذ ذخیرہ" + +msgid "Sphinx Book Theme" +msgstr "سپنکس بک تھیم" + +msgid "Theme by the" +msgstr "کے ذریعہ تھیم" + +msgid "Toggle navigation" +msgstr "نیویگیشن ٹوگل کریں" + +msgid "next page" +msgstr "اگلا صفحہ" + +msgid "open issue" +msgstr "کھلا مسئلہ" + +msgid "previous page" +msgstr "سابقہ ​​صفحہ" + +msgid "suggest edit" +msgstr "ترمیم کی تجویز کریں" diff --git a/_static/locales/vi/LC_MESSAGES/booktheme.mo b/_static/locales/vi/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..2bb32555 Binary files /dev/null and b/_static/locales/vi/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/vi/LC_MESSAGES/booktheme.po b/_static/locales/vi/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..ac91b0f1 --- /dev/null +++ b/_static/locales/vi/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: vi\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "Bằng" + +msgid "By" +msgstr "Bởi" + +msgid "Contents" +msgstr "Nội dung" + +msgid "Copyright" +msgstr "Bản quyền" + +msgid "Download notebook file" +msgstr "Tải xuống tệp sổ tay" + +msgid "Download source file" +msgstr "Tải xuống tệp nguồn" + +msgid "Download this page" +msgstr "Tải xuống trang này" + +msgid "Edit this page" +msgstr "chỉnh sửa trang này" + +msgid "Fullscreen mode" +msgstr "Chế độ toàn màn hình" + +msgid "Last updated on" +msgstr "Cập nhật lần cuối vào" + +msgid "Launch" +msgstr "Phóng" + +msgid "Open an issue" +msgstr "Mở một vấn đề" + +msgid "Print to PDF" +msgstr "In sang PDF" + +msgid "Source repository" +msgstr "Kho nguồn" + +msgid "Sphinx Book Theme" +msgstr "Chủ đề sách nhân sư" + +msgid "Theme by the" +msgstr "Chủ đề của" + +msgid "Toggle navigation" +msgstr "Chuyển đổi điều hướng thành" + +msgid "next page" +msgstr "Trang tiếp theo" + +msgid "open issue" +msgstr "vấn đề mở" + +msgid "previous page" +msgstr "trang trước" + +msgid "repository" +msgstr "kho" + +msgid "suggest edit" +msgstr "đề nghị chỉnh sửa" diff --git a/_static/locales/zh_CN/LC_MESSAGES/booktheme.mo b/_static/locales/zh_CN/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..0e3235d0 Binary files /dev/null and b/_static/locales/zh_CN/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/zh_CN/LC_MESSAGES/booktheme.po b/_static/locales/zh_CN/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..ff1c9383 --- /dev/null +++ b/_static/locales/zh_CN/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: zh_CN\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "作者：" + +msgid "By" +msgstr "作者：" + +msgid "Contents" +msgstr "目录" + +msgid "Copyright" +msgstr "版权" + +msgid "Download notebook file" +msgstr "下载笔记本文件" + +msgid "Download source file" +msgstr "下载源文件" + +msgid "Download this page" +msgstr "下载此页面" + +msgid "Edit this page" +msgstr "编辑此页面" + +msgid "Fullscreen mode" +msgstr "全屏模式" + +msgid "Last updated on" +msgstr "上次更新时间：" + +msgid "Launch" +msgstr "启动" + +msgid "Open an issue" +msgstr "创建议题" + +msgid "Print to PDF" +msgstr "列印成 PDF" + +msgid "Source repository" +msgstr "源码库" + +msgid "Sphinx Book Theme" +msgstr "Sphinx Book 主题" + +msgid "Theme by the" +msgstr "主题作者：" + +msgid "Toggle navigation" +msgstr "显示或隐藏导航栏" + +msgid "next page" +msgstr "下一页" + +msgid "open issue" +msgstr "创建议题" + +msgid "previous page" +msgstr "上一页" + +msgid "repository" +msgstr "仓库" + +msgid "suggest edit" +msgstr "提出修改建议" diff --git a/_static/locales/zh_TW/LC_MESSAGES/booktheme.mo b/_static/locales/zh_TW/LC_MESSAGES/booktheme.mo new file mode 100644 index 00000000..9116fa95 Binary files /dev/null and b/_static/locales/zh_TW/LC_MESSAGES/booktheme.mo differ diff --git a/_static/locales/zh_TW/LC_MESSAGES/booktheme.po b/_static/locales/zh_TW/LC_MESSAGES/booktheme.po new file mode 100644 index 00000000..f2b300fa --- /dev/null +++ b/_static/locales/zh_TW/LC_MESSAGES/booktheme.po @@ -0,0 +1,75 @@ + +msgid "" +msgstr "" +"Project-Id-Version: Sphinx-Book-Theme\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Language: zh_TW\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" + +msgid "By the" +msgstr "作者：" + +msgid "By" +msgstr "作者：" + +msgid "Contents" +msgstr "目錄" + +msgid "Copyright" +msgstr "Copyright" + +msgid "Download notebook file" +msgstr "下載 Notebook 檔案" + +msgid "Download source file" +msgstr "下載原始檔" + +msgid "Download this page" +msgstr "下載此頁面" + +msgid "Edit this page" +msgstr "編輯此頁面" + +msgid "Fullscreen mode" +msgstr "全螢幕模式" + +msgid "Last updated on" +msgstr "最後更新時間：" + +msgid "Launch" +msgstr "啟動" + +msgid "Open an issue" +msgstr "開啟議題" + +msgid "Print to PDF" +msgstr "列印成 PDF" + +msgid "Source repository" +msgstr "來源儲存庫" + +msgid "Sphinx Book Theme" +msgstr "Sphinx Book 佈景主題" + +msgid "Theme by the" +msgstr "佈景主題作者：" + +msgid "Toggle navigation" +msgstr "顯示或隱藏導覽列" + +msgid "next page" +msgstr "下一頁" + +msgid "open issue" +msgstr "公開的問題" + +msgid "previous page" +msgstr "上一頁" + +msgid "repository" +msgstr "儲存庫" + +msgid "suggest edit" +msgstr "提出修改建議" diff --git a/_static/logo.png b/_static/logo.png new file mode 100644 index 00000000..8389c11f Binary files /dev/null and b/_static/logo.png differ diff --git a/_static/minus.png b/_static/minus.png new file mode 100644 index 00000000..d96755fd Binary files /dev/null and b/_static/minus.png differ diff --git a/_static/mystnb.11b39860a7a0cbfd473a3ad8a317855267ff0bd372690045ca344a6b62be495e.css b/_static/mystnb.11b39860a7a0cbfd473a3ad8a317855267ff0bd372690045ca344a6b62be495e.css new file mode 100644 index 00000000..9f3d7646 --- /dev/null +++ b/_static/mystnb.11b39860a7a0cbfd473a3ad8a317855267ff0bd372690045ca344a6b62be495e.css @@ -0,0 +1,2449 @@ +/* Dark mode support: + * if (e.g. Furo theme) or (e.g. PyData theme) has `data-theme` set, respect it. + * else default to the system color scheme + */ +@media (prefers-color-scheme: dark) { + :root { + --light: ; + --dark: initial; + } +} + +@media (prefers-color-scheme: light) { + :root { + --dark: ; + --light: initial; + } +} + +:is(html, body)[data-theme="dark"] { + --light: ; + --dark: initial; +} + +:is(html, body)[data-theme="light"] { + --dark: ; + --light: initial; +} + +/* Variables */ +:root { + /* + Following palettes are generated by using https://m2.material.io/design/color/the-color-system.html#tools-for-picking-colors + - neutral palette with #fcfcfc and danger palette with #ffdddd as base colors. + 50 means lightest, 900 means darkest; less used intermediate shades are omitted + but can be added when needed by accessing full palette from the above link. + */ + --mystnb-neutral-palette-50: #fcfcfc; + --mystnb-neutral-palette-100: #f7f7f7; + --mystnb-neutral-palette-400: #cccccc; + --mystnb-neutral-palette-500: #afafaf; + --mystnb-neutral-palette-800: #505050; + --mystnb-neutral-palette-900: #2d2d2d; + + --mystnb-danger-palette-50: #ffdddd; + --mystnb-danger-palette-100: #f5acad; + --mystnb-danger-palette-400: #c42029; + --mystnb-danger-palette-500: #b40008; + --mystnb-danger-palette-800: #850010; + --mystnb-danger-palette-900: #680010; + + /* MyST-NB specific variables; colors should be logically picked from palettes */ + --mystnb-source-bg-color: var(--light, var(--mystnb-neutral-palette-100)) var(--dark, var(--mystnb-neutral-palette-800)); + --mystnb-stdout-bg-color: var(--light, var(--mystnb-neutral-palette-50)) var(--dark, var(--mystnb-neutral-palette-900)); + --mystnb-stderr-bg-color: var(--light, var(--mystnb-danger-palette-50)) var(--dark, var(--mystnb-danger-palette-900)); + --mystnb-traceback-bg-color: var(--light, var(--mystnb-neutral-palette-50)) var(--dark, var(--mystnb-neutral-palette-900)); + --mystnb-source-border-color: var(--light, var(--mystnb-neutral-palette-400)) var(--dark, var(--mystnb-neutral-palette-500)); + --mystnb-source-margin-color: green; + --mystnb-stdout-border-color: var(--light, var(--mystnb-neutral-palette-100)) var(--dark, var(--mystnb-neutral-palette-800)); + --mystnb-stderr-border-color: var(--light, var(--mystnb-neutral-palette-100)) var(--dark, var(--mystnb-neutral-palette-800)); + --mystnb-traceback-border-color: var(--light, var(--mystnb-danger-palette-100)) var(--dark, var(--mystnb-danger-palette-800)); + --mystnb-hide-prompt-opacity: 70%; + --mystnb-source-border-radius: .4em; + --mystnb-source-border-width: 1px; + --mystnb-scrollbar-width: 0.3rem; + --mystnb-scrollbar-height: 0.3rem; + --mystnb-scrollbar-thumb-color: var(--light, var(--mystnb-neutral-palette-400)) var(--dark, var(--mystnb-neutral-palette-500)); + --mystnb-scrollbar-thumb-hover-color: var(--light, var(--mystnb-neutral-palette-500)) var(--dark, var(--mystnb-neutral-palette-400)); + --mystnb-scrollbar-thumb-border-radius: 0.25rem; +} + + +/* Whole cell */ +div.container.cell { + padding-left: 0; + margin-bottom: 1em; +} + +/* Removing all background formatting so we can control at the div level */ +.cell_input div.highlight, +.cell_output pre, +.cell_input pre, +.cell_output .output { + border: none; + box-shadow: none; +} + +.cell_output .output pre, +.cell_input pre { + margin: 0px; +} + +/* Input cells */ +div.cell > div.cell_input { + padding-left: 0em; + padding-right: 0em; + border: var(--mystnb-source-border-width) var(--mystnb-source-border-color) solid; + background-color: var(--mystnb-source-bg-color); + border-left-color: var(--mystnb-source-margin-color); + border-left-width: medium; + border-radius: var(--mystnb-source-border-radius); +} + +div.cell_input>div, +div.cell_output div.output>div.highlight { + margin: 0em !important; + border: none !important; +} + +/* All cell outputs */ +.cell_output { + padding-left: 1em; + padding-right: 0em; + margin-top: 1em; +} + +/* Text outputs from cells */ +.cell_output .output.text_plain, +.cell_output .output.traceback, +.cell_output .output.stream, +.cell_output .output.stderr { + margin-top: 1em; + margin-bottom: 0em; + box-shadow: none; +} + +.cell_output .output.text_plain:not(:has(.highlight)), +.cell_output .output.stream:not(:has(.highlight)) { + /* plain (or stream of) output, not containing a pygments-highlighted block */ + background: var(--mystnb-stdout-bg-color); + border: 1px solid var(--mystnb-stdout-border-color); +} + +.cell_output .output.stderr { + background: var(--mystnb-stderr-bg-color); + border: 1px solid var(--mystnb-stderr-border-color); +} + +.cell_output .output.traceback { + background: var(--mystnb-traceback-bg-color); + border: 1px solid var(--mystnb-traceback-border-color); +} + +/* --- Collapsible cell content --- */ + +/* +encourage summary container to blend in with its parent. +p.admonition-title should hold the title styles. +*/ +div.cell details.hide summary { + border-left: unset; + padding: inherit; + margin: inherit; + background-color: inherit; +} + +/* Neighboring input/output elements - spacing, borders */ +div.cell details.hide.above-input + details.below-input, +div.cell div.cell_input + details.below-input +{ + margin-top: 0; +} + +div.cell details.hide.above-input:has(+ details.below-input), +div.cell div.cell_input:has(+ details.below-input) +{ + margin-bottom: 0; +} + +div.cell:has(> *:nth-child(2)) div.cell_input:first-child, +div.cell:has(> *:nth-child(2)) details:first-child +{ + border-bottom-left-radius: 0; + border-bottom-right-radius: 0; +} + +div.cell:has(> *:nth-child(2)) div.cell_input:last-child, +div.cell:has(> *:nth-child(2)) details:last-child +{ + border-top-left-radius: 0; + border-top-right-radius: 0; +} + +/* intra-label styles for collapsibles */ +div.cell.container details.hide.above-input>summary, +div.cell.container details.hide.below-input>summary, +div.cell.container details.hide.above-output>summary +{ + display: block; + border-left: none; +} + +div.cell details.hide>summary>p.admonition-title { + display: list-item; + margin-bottom: 0; +} + +div.cell details.hide:not([open]) { + padding-bottom: 0; +} + +div.cell details.hide[open]>summary>p.collapsed { + display: none; +} + +div.cell details.hide:not([open])>summary>p.expanded { + display: none; +} + +@keyframes collapsed-fade-in { + 0% { + opacity: 0; + } + + 100% { + opacity: 1; + } +} +div.cell details.hide[open]>summary~* { + -moz-animation: collapsed-fade-in 0.3s ease-in-out; + -webkit-animation: collapsed-fade-in 0.3s ease-in-out; + animation: collapsed-fade-in 0.3s ease-in-out; +} + +/* Clear conflicting styles for details and admonitions set by some themes */ +div.cell details.admonition summary::before { + content: unset; +} + +/* Math align to the left */ +.cell_output .MathJax_Display { + text-align: left !important; +} + +/** source code line numbers **/ +span.linenos { + opacity: 0.5; +} + +/* Inline text from `paste` operation */ + +span.pasted-text { + font-weight: bold; +} + +span.pasted-inline img { + max-height: 2em; +} + +tbody span.pasted-inline img { + max-height: none; +} + + +/* Adding scroll bars if tags: output_scroll, scroll-output, and scroll-input + * On screens, we want to scroll, but on print show all + * + * It was before in https://github.com/executablebooks/sphinx-book-theme/blob/eb1b6baf098b27605e8f2b7b2979b17ebf1b9540/src/sphinx_book_theme/assets/styles/extensions/_myst-nb.scss +*/ +div.cell:is( + .tag_output_scroll, + .tag_scroll-output, + .config_scroll_outputs + ) + div.cell_output, +div.cell.tag_scroll-input div.cell_input { + max-height: 24em; + overflow-y: auto; + max-width: 100%; + overflow-x: auto; +} + +div.cell.config_scroll_outputs div.cell_output:has(img) { + /* If the output cell has image(s), allow it to take 90% of viewport height + but still bounded between 24em and 60em */ + max-height: clamp(24em, 90vh, 60em); +} + +/* Custom scrollbars */ +div.cell:is( + .tag_output_scroll, + .tag_scroll-output, + .config_scroll_outputs + ) + div.cell_output::-webkit-scrollbar, +div.cell.tag_scroll-input div.cell_input::-webkit-scrollbar { + width: var(--mystnb-scrollbar-width); + height: var(--mystnb-scrollbar-height); +} + +div.cell:is( + .tag_output_scroll, + .tag_scroll-output, + .config_scroll_outputs + ) + div.cell_output::-webkit-scrollbar-thumb, +div.cell.tag_scroll-input div.cell_input::-webkit-scrollbar-thumb { + background: var(--mystnb-scrollbar-thumb-color); + border-radius: var(--mystnb-scrollbar-thumb-border-radius); +} + +div.cell:is( + .tag_output_scroll, + .tag_scroll-output, + .config_scroll_outputs + ) + div.cell_output::-webkit-scrollbar-thumb:hover, +div.cell.tag_scroll-input div.cell_input::-webkit-scrollbar-thumb:hover { + background: var(--mystnb-scrollbar-thumb-hover-color); +} + +/* In print mode, unset scroll styles */ +@media print { + div.cell:is( + .tag_output_scroll, + .tag_scroll-output, + .config_scroll_outputs + ) + div.cell_output, + div.cell.tag_scroll-input div.cell_input { + max-height: unset; + overflow-y: visible; + max-width: unset; + overflow-x: visible; + } +} + +/* Font colors for translated ANSI escape sequences +Color values are copied from Jupyter Notebook +https://github.com/jupyter/notebook/blob/52581f8eda9b319eb0390ac77fe5903c38f81e3e/notebook/static/notebook/less/ansicolors.less#L14-L21 +Background colors from +https://nbsphinx.readthedocs.io/en/latest/code-cells.html#ANSI-Colors +*/ +div.highlight .-Color-Bold { + font-weight: bold; +} + +div.highlight .-Color[class*=-Black] { + color: #3E424D +} + +div.highlight .-Color[class*=-Red] { + color: #E75C58 +} + +div.highlight .-Color[class*=-Green] { + color: #00A250 +} + +div.highlight .-Color[class*=-Yellow] { + color: #DDB62B +} + +div.highlight .-Color[class*=-Blue] { + color: #208FFB +} + +div.highlight .-Color[class*=-Magenta] { + color: #D160C4 +} + +div.highlight .-Color[class*=-Cyan] { + color: #60C6C8 +} + +div.highlight .-Color[class*=-White] { + color: #C5C1B4 +} + +div.highlight .-Color[class*=-BGBlack] { + background-color: #3E424D +} + +div.highlight .-Color[class*=-BGRed] { + background-color: #E75C58 +} + +div.highlight .-Color[class*=-BGGreen] { + background-color: #00A250 +} + +div.highlight .-Color[class*=-BGYellow] { + background-color: #DDB62B +} + +div.highlight .-Color[class*=-BGBlue] { + background-color: #208FFB +} + +div.highlight .-Color[class*=-BGMagenta] { + background-color: #D160C4 +} + +div.highlight .-Color[class*=-BGCyan] { + background-color: #60C6C8 +} + +div.highlight .-Color[class*=-BGWhite] { + background-color: #C5C1B4 +} + +/* Font colors for 8-bit ANSI */ + +div.highlight .-Color[class*=-C0] { + color: #000000 +} + +div.highlight .-Color[class*=-BGC0] { + background-color: #000000 +} + +div.highlight .-Color[class*=-C1] { + color: #800000 +} + +div.highlight .-Color[class*=-BGC1] { + background-color: #800000 +} + +div.highlight .-Color[class*=-C2] { + color: #008000 +} + +div.highlight .-Color[class*=-BGC2] { + background-color: #008000 +} + +div.highlight .-Color[class*=-C3] { + color: #808000 +} + +div.highlight .-Color[class*=-BGC3] { + background-color: #808000 +} + +div.highlight .-Color[class*=-C4] { + color: #000080 +} + +div.highlight .-Color[class*=-BGC4] { + background-color: #000080 +} + +div.highlight .-Color[class*=-C5] { + color: #800080 +} + +div.highlight .-Color[class*=-BGC5] { + background-color: #800080 +} + +div.highlight .-Color[class*=-C6] { + color: #008080 +} + +div.highlight .-Color[class*=-BGC6] { + background-color: #008080 +} + +div.highlight .-Color[class*=-C7] { + color: #C0C0C0 +} + +div.highlight .-Color[class*=-BGC7] { + background-color: #C0C0C0 +} + +div.highlight .-Color[class*=-C8] { + color: #808080 +} + +div.highlight .-Color[class*=-BGC8] { + background-color: #808080 +} + +div.highlight .-Color[class*=-C9] { + color: #FF0000 +} + +div.highlight .-Color[class*=-BGC9] { + background-color: #FF0000 +} + +div.highlight .-Color[class*=-C10] { + color: #00FF00 +} + +div.highlight .-Color[class*=-BGC10] { + background-color: #00FF00 +} + +div.highlight .-Color[class*=-C11] { + color: #FFFF00 +} + +div.highlight .-Color[class*=-BGC11] { + background-color: #FFFF00 +} + +div.highlight .-Color[class*=-C12] { + color: #0000FF +} + +div.highlight .-Color[class*=-BGC12] { + background-color: #0000FF +} + +div.highlight .-Color[class*=-C13] { + color: #FF00FF +} + +div.highlight .-Color[class*=-BGC13] { + background-color: #FF00FF +} + +div.highlight .-Color[class*=-C14] { + color: #00FFFF +} + +div.highlight .-Color[class*=-BGC14] { + background-color: #00FFFF +} + +div.highlight .-Color[class*=-C15] { + color: #FFFFFF +} + +div.highlight .-Color[class*=-BGC15] { + background-color: #FFFFFF +} + +div.highlight .-Color[class*=-C16] { + color: #000000 +} + +div.highlight .-Color[class*=-BGC16] { + background-color: #000000 +} + +div.highlight .-Color[class*=-C17] { + color: #00005F +} + +div.highlight .-Color[class*=-BGC17] { + background-color: #00005F +} + +div.highlight .-Color[class*=-C18] { + color: #000087 +} + +div.highlight .-Color[class*=-BGC18] { + background-color: #000087 +} + +div.highlight .-Color[class*=-C19] { + color: #0000AF +} + +div.highlight .-Color[class*=-BGC19] { + background-color: #0000AF +} + +div.highlight .-Color[class*=-C20] { + color: #0000D7 +} + +div.highlight .-Color[class*=-BGC20] { + background-color: #0000D7 +} + +div.highlight .-Color[class*=-C21] { + color: #0000FF +} + +div.highlight .-Color[class*=-BGC21] { + background-color: #0000FF +} + +div.highlight .-Color[class*=-C22] { + color: #005F00 +} + +div.highlight .-Color[class*=-BGC22] { + background-color: #005F00 +} + +div.highlight .-Color[class*=-C23] { + color: #005F5F +} + +div.highlight .-Color[class*=-BGC23] { + background-color: #005F5F +} + +div.highlight .-Color[class*=-C24] { + color: #005F87 +} + +div.highlight .-Color[class*=-BGC24] { + background-color: #005F87 +} + +div.highlight .-Color[class*=-C25] { + color: #005FAF +} + +div.highlight .-Color[class*=-BGC25] { + background-color: #005FAF +} + +div.highlight .-Color[class*=-C26] { + color: #005FD7 +} + +div.highlight .-Color[class*=-BGC26] { + background-color: #005FD7 +} + +div.highlight .-Color[class*=-C27] { + color: #005FFF +} + +div.highlight .-Color[class*=-BGC27] { + background-color: #005FFF +} + +div.highlight .-Color[class*=-C28] { + color: #008700 +} + +div.highlight .-Color[class*=-BGC28] { + background-color: #008700 +} + +div.highlight .-Color[class*=-C29] { + color: #00875F +} + +div.highlight .-Color[class*=-BGC29] { + background-color: #00875F +} + +div.highlight .-Color[class*=-C30] { + color: #008787 +} + +div.highlight .-Color[class*=-BGC30] { + background-color: #008787 +} + +div.highlight .-Color[class*=-C31] { + color: #0087AF +} + +div.highlight .-Color[class*=-BGC31] { + background-color: #0087AF +} + +div.highlight .-Color[class*=-C32] { + color: #0087D7 +} + +div.highlight .-Color[class*=-BGC32] { + background-color: #0087D7 +} + +div.highlight .-Color[class*=-C33] { + color: #0087FF +} + +div.highlight .-Color[class*=-BGC33] { + background-color: #0087FF +} + +div.highlight .-Color[class*=-C34] { + color: #00AF00 +} + +div.highlight .-Color[class*=-BGC34] { + background-color: #00AF00 +} + +div.highlight .-Color[class*=-C35] { + color: #00AF5F +} + +div.highlight .-Color[class*=-BGC35] { + background-color: #00AF5F +} + +div.highlight .-Color[class*=-C36] { + color: #00AF87 +} + +div.highlight .-Color[class*=-BGC36] { + background-color: #00AF87 +} + +div.highlight .-Color[class*=-C37] { + color: #00AFAF +} + +div.highlight .-Color[class*=-BGC37] { + background-color: #00AFAF +} + +div.highlight .-Color[class*=-C38] { + color: #00AFD7 +} + +div.highlight .-Color[class*=-BGC38] { + background-color: #00AFD7 +} + +div.highlight .-Color[class*=-C39] { + color: #00AFFF +} + +div.highlight .-Color[class*=-BGC39] { + background-color: #00AFFF +} + +div.highlight .-Color[class*=-C40] { + color: #00D700 +} + +div.highlight .-Color[class*=-BGC40] { + background-color: #00D700 +} + +div.highlight .-Color[class*=-C41] { + color: #00D75F +} + +div.highlight .-Color[class*=-BGC41] { + background-color: #00D75F +} + +div.highlight .-Color[class*=-C42] { + color: #00D787 +} + +div.highlight .-Color[class*=-BGC42] { + background-color: #00D787 +} + +div.highlight .-Color[class*=-C43] { + color: #00D7AF +} + +div.highlight .-Color[class*=-BGC43] { + background-color: #00D7AF +} + +div.highlight .-Color[class*=-C44] { + color: #00D7D7 +} + +div.highlight .-Color[class*=-BGC44] { + background-color: #00D7D7 +} + +div.highlight .-Color[class*=-C45] { + color: #00D7FF +} + +div.highlight .-Color[class*=-BGC45] { + background-color: #00D7FF +} + +div.highlight .-Color[class*=-C46] { + color: #00FF00 +} + +div.highlight .-Color[class*=-BGC46] { + background-color: #00FF00 +} + +div.highlight .-Color[class*=-C47] { + color: #00FF5F +} + +div.highlight .-Color[class*=-BGC47] { + background-color: #00FF5F +} + +div.highlight .-Color[class*=-C48] { + color: #00FF87 +} + +div.highlight .-Color[class*=-BGC48] { + background-color: #00FF87 +} + +div.highlight .-Color[class*=-C49] { + color: #00FFAF +} + +div.highlight .-Color[class*=-BGC49] { + background-color: #00FFAF +} + +div.highlight .-Color[class*=-C50] { + color: #00FFD7 +} + +div.highlight .-Color[class*=-BGC50] { + background-color: #00FFD7 +} + +div.highlight .-Color[class*=-C51] { + color: #00FFFF +} + +div.highlight .-Color[class*=-BGC51] { + background-color: #00FFFF +} + +div.highlight .-Color[class*=-C52] { + color: #5F0000 +} + +div.highlight .-Color[class*=-BGC52] { + background-color: #5F0000 +} + +div.highlight .-Color[class*=-C53] { + color: #5F005F +} + +div.highlight .-Color[class*=-BGC53] { + background-color: #5F005F +} + +div.highlight .-Color[class*=-C54] { + color: #5F0087 +} + +div.highlight .-Color[class*=-BGC54] { + background-color: #5F0087 +} + +div.highlight .-Color[class*=-C55] { + color: #5F00AF +} + +div.highlight .-Color[class*=-BGC55] { + background-color: #5F00AF +} + +div.highlight .-Color[class*=-C56] { + color: #5F00D7 +} + +div.highlight .-Color[class*=-BGC56] { + background-color: #5F00D7 +} + +div.highlight .-Color[class*=-C57] { + color: #5F00FF +} + +div.highlight .-Color[class*=-BGC57] { + background-color: #5F00FF +} + +div.highlight .-Color[class*=-C58] { + color: #5F5F00 +} + +div.highlight .-Color[class*=-BGC58] { + background-color: #5F5F00 +} + +div.highlight .-Color[class*=-C59] { + color: #5F5F5F +} + +div.highlight .-Color[class*=-BGC59] { + background-color: #5F5F5F +} + +div.highlight .-Color[class*=-C60] { + color: #5F5F87 +} + +div.highlight .-Color[class*=-BGC60] { + background-color: #5F5F87 +} + +div.highlight .-Color[class*=-C61] { + color: #5F5FAF +} + +div.highlight .-Color[class*=-BGC61] { + background-color: #5F5FAF +} + +div.highlight .-Color[class*=-C62] { + color: #5F5FD7 +} + +div.highlight .-Color[class*=-BGC62] { + background-color: #5F5FD7 +} + +div.highlight .-Color[class*=-C63] { + color: #5F5FFF +} + +div.highlight .-Color[class*=-BGC63] { + background-color: #5F5FFF +} + +div.highlight .-Color[class*=-C64] { + color: #5F8700 +} + +div.highlight .-Color[class*=-BGC64] { + background-color: #5F8700 +} + +div.highlight .-Color[class*=-C65] { + color: #5F875F +} + +div.highlight .-Color[class*=-BGC65] { + background-color: #5F875F +} + +div.highlight .-Color[class*=-C66] { + color: #5F8787 +} + +div.highlight .-Color[class*=-BGC66] { + background-color: #5F8787 +} + +div.highlight .-Color[class*=-C67] { + color: #5F87AF +} + +div.highlight .-Color[class*=-BGC67] { + background-color: #5F87AF +} + +div.highlight .-Color[class*=-C68] { + color: #5F87D7 +} + +div.highlight .-Color[class*=-BGC68] { + background-color: #5F87D7 +} + +div.highlight .-Color[class*=-C69] { + color: #5F87FF +} + +div.highlight .-Color[class*=-BGC69] { + background-color: #5F87FF +} + +div.highlight .-Color[class*=-C70] { + color: #5FAF00 +} + +div.highlight .-Color[class*=-BGC70] { + background-color: #5FAF00 +} + +div.highlight .-Color[class*=-C71] { + color: #5FAF5F +} + +div.highlight .-Color[class*=-BGC71] { + background-color: #5FAF5F +} + +div.highlight .-Color[class*=-C72] { + color: #5FAF87 +} + +div.highlight .-Color[class*=-BGC72] { + background-color: #5FAF87 +} + +div.highlight .-Color[class*=-C73] { + color: #5FAFAF +} + +div.highlight .-Color[class*=-BGC73] { + background-color: #5FAFAF +} + +div.highlight .-Color[class*=-C74] { + color: #5FAFD7 +} + +div.highlight .-Color[class*=-BGC74] { + background-color: #5FAFD7 +} + +div.highlight .-Color[class*=-C75] { + color: #5FAFFF +} + +div.highlight .-Color[class*=-BGC75] { + background-color: #5FAFFF +} + +div.highlight .-Color[class*=-C76] { + color: #5FD700 +} + +div.highlight .-Color[class*=-BGC76] { + background-color: #5FD700 +} + +div.highlight .-Color[class*=-C77] { + color: #5FD75F +} + +div.highlight .-Color[class*=-BGC77] { + background-color: #5FD75F +} + +div.highlight .-Color[class*=-C78] { + color: #5FD787 +} + +div.highlight .-Color[class*=-BGC78] { + background-color: #5FD787 +} + +div.highlight .-Color[class*=-C79] { + color: #5FD7AF +} + +div.highlight .-Color[class*=-BGC79] { + background-color: #5FD7AF +} + +div.highlight .-Color[class*=-C80] { + color: #5FD7D7 +} + +div.highlight .-Color[class*=-BGC80] { + background-color: #5FD7D7 +} + +div.highlight .-Color[class*=-C81] { + color: #5FD7FF +} + +div.highlight .-Color[class*=-BGC81] { + background-color: #5FD7FF +} + +div.highlight .-Color[class*=-C82] { + color: #5FFF00 +} + +div.highlight .-Color[class*=-BGC82] { + background-color: #5FFF00 +} + +div.highlight .-Color[class*=-C83] { + color: #5FFF5F +} + +div.highlight .-Color[class*=-BGC83] { + background-color: #5FFF5F +} + +div.highlight .-Color[class*=-C84] { + color: #5FFF87 +} + +div.highlight .-Color[class*=-BGC84] { + background-color: #5FFF87 +} + +div.highlight .-Color[class*=-C85] { + color: #5FFFAF +} + +div.highlight .-Color[class*=-BGC85] { + background-color: #5FFFAF +} + +div.highlight .-Color[class*=-C86] { + color: #5FFFD7 +} + +div.highlight .-Color[class*=-BGC86] { + background-color: #5FFFD7 +} + +div.highlight .-Color[class*=-C87] { + color: #5FFFFF +} + +div.highlight .-Color[class*=-BGC87] { + background-color: #5FFFFF +} + +div.highlight .-Color[class*=-C88] { + color: #870000 +} + +div.highlight .-Color[class*=-BGC88] { + background-color: #870000 +} + +div.highlight .-Color[class*=-C89] { + color: #87005F +} + +div.highlight .-Color[class*=-BGC89] { + background-color: #87005F +} + +div.highlight .-Color[class*=-C90] { + color: #870087 +} + +div.highlight .-Color[class*=-BGC90] { + background-color: #870087 +} + +div.highlight .-Color[class*=-C91] { + color: #8700AF +} + +div.highlight .-Color[class*=-BGC91] { + background-color: #8700AF +} + +div.highlight .-Color[class*=-C92] { + color: #8700D7 +} + +div.highlight .-Color[class*=-BGC92] { + background-color: #8700D7 +} + +div.highlight .-Color[class*=-C93] { + color: #8700FF +} + +div.highlight .-Color[class*=-BGC93] { + background-color: #8700FF +} + +div.highlight .-Color[class*=-C94] { + color: #875F00 +} + +div.highlight .-Color[class*=-BGC94] { + background-color: #875F00 +} + +div.highlight .-Color[class*=-C95] { + color: #875F5F +} + +div.highlight .-Color[class*=-BGC95] { + background-color: #875F5F +} + +div.highlight .-Color[class*=-C96] { + color: #875F87 +} + +div.highlight .-Color[class*=-BGC96] { + background-color: #875F87 +} + +div.highlight .-Color[class*=-C97] { + color: #875FAF +} + +div.highlight .-Color[class*=-BGC97] { + background-color: #875FAF +} + +div.highlight .-Color[class*=-C98] { + color: #875FD7 +} + +div.highlight .-Color[class*=-BGC98] { + background-color: #875FD7 +} + +div.highlight .-Color[class*=-C99] { + color: #875FFF +} + +div.highlight .-Color[class*=-BGC99] { + background-color: #875FFF +} + +div.highlight .-Color[class*=-C100] { + color: #878700 +} + +div.highlight .-Color[class*=-BGC100] { + background-color: #878700 +} + +div.highlight .-Color[class*=-C101] { + color: #87875F +} + +div.highlight .-Color[class*=-BGC101] { + background-color: #87875F +} + +div.highlight .-Color[class*=-C102] { + color: #878787 +} + +div.highlight .-Color[class*=-BGC102] { + background-color: #878787 +} + +div.highlight .-Color[class*=-C103] { + color: #8787AF +} + +div.highlight .-Color[class*=-BGC103] { + background-color: #8787AF +} + +div.highlight .-Color[class*=-C104] { + color: #8787D7 +} + +div.highlight .-Color[class*=-BGC104] { + background-color: #8787D7 +} + +div.highlight .-Color[class*=-C105] { + color: #8787FF +} + +div.highlight .-Color[class*=-BGC105] { + background-color: #8787FF +} + +div.highlight .-Color[class*=-C106] { + color: #87AF00 +} + +div.highlight .-Color[class*=-BGC106] { + background-color: #87AF00 +} + +div.highlight .-Color[class*=-C107] { + color: #87AF5F +} + +div.highlight .-Color[class*=-BGC107] { + background-color: #87AF5F +} + +div.highlight .-Color[class*=-C108] { + color: #87AF87 +} + +div.highlight .-Color[class*=-BGC108] { + background-color: #87AF87 +} + +div.highlight .-Color[class*=-C109] { + color: #87AFAF +} + +div.highlight .-Color[class*=-BGC109] { + background-color: #87AFAF +} + +div.highlight .-Color[class*=-C110] { + color: #87AFD7 +} + +div.highlight .-Color[class*=-BGC110] { + background-color: #87AFD7 +} + +div.highlight .-Color[class*=-C111] { + color: #87AFFF +} + +div.highlight .-Color[class*=-BGC111] { + background-color: #87AFFF +} + +div.highlight .-Color[class*=-C112] { + color: #87D700 +} + +div.highlight .-Color[class*=-BGC112] { + background-color: #87D700 +} + +div.highlight .-Color[class*=-C113] { + color: #87D75F +} + +div.highlight .-Color[class*=-BGC113] { + background-color: #87D75F +} + +div.highlight .-Color[class*=-C114] { + color: #87D787 +} + +div.highlight .-Color[class*=-BGC114] { + background-color: #87D787 +} + +div.highlight .-Color[class*=-C115] { + color: #87D7AF +} + +div.highlight .-Color[class*=-BGC115] { + background-color: #87D7AF +} + +div.highlight .-Color[class*=-C116] { + color: #87D7D7 +} + +div.highlight .-Color[class*=-BGC116] { + background-color: #87D7D7 +} + +div.highlight .-Color[class*=-C117] { + color: #87D7FF +} + +div.highlight .-Color[class*=-BGC117] { + background-color: #87D7FF +} + +div.highlight .-Color[class*=-C118] { + color: #87FF00 +} + +div.highlight .-Color[class*=-BGC118] { + background-color: #87FF00 +} + +div.highlight .-Color[class*=-C119] { + color: #87FF5F +} + +div.highlight .-Color[class*=-BGC119] { + background-color: #87FF5F +} + +div.highlight .-Color[class*=-C120] { + color: #87FF87 +} + +div.highlight .-Color[class*=-BGC120] { + background-color: #87FF87 +} + +div.highlight .-Color[class*=-C121] { + color: #87FFAF +} + +div.highlight .-Color[class*=-BGC121] { + background-color: #87FFAF +} + +div.highlight .-Color[class*=-C122] { + color: #87FFD7 +} + +div.highlight .-Color[class*=-BGC122] { + background-color: #87FFD7 +} + +div.highlight .-Color[class*=-C123] { + color: #87FFFF +} + +div.highlight .-Color[class*=-BGC123] { + background-color: #87FFFF +} + +div.highlight .-Color[class*=-C124] { + color: #AF0000 +} + +div.highlight .-Color[class*=-BGC124] { + background-color: #AF0000 +} + +div.highlight .-Color[class*=-C125] { + color: #AF005F +} + +div.highlight .-Color[class*=-BGC125] { + background-color: #AF005F +} + +div.highlight .-Color[class*=-C126] { + color: #AF0087 +} + +div.highlight .-Color[class*=-BGC126] { + background-color: #AF0087 +} + +div.highlight .-Color[class*=-C127] { + color: #AF00AF +} + +div.highlight .-Color[class*=-BGC127] { + background-color: #AF00AF +} + +div.highlight .-Color[class*=-C128] { + color: #AF00D7 +} + +div.highlight .-Color[class*=-BGC128] { + background-color: #AF00D7 +} + +div.highlight .-Color[class*=-C129] { + color: #AF00FF +} + +div.highlight .-Color[class*=-BGC129] { + background-color: #AF00FF +} + +div.highlight .-Color[class*=-C130] { + color: #AF5F00 +} + +div.highlight .-Color[class*=-BGC130] { + background-color: #AF5F00 +} + +div.highlight .-Color[class*=-C131] { + color: #AF5F5F +} + +div.highlight .-Color[class*=-BGC131] { + background-color: #AF5F5F +} + +div.highlight .-Color[class*=-C132] { + color: #AF5F87 +} + +div.highlight .-Color[class*=-BGC132] { + background-color: #AF5F87 +} + +div.highlight .-Color[class*=-C133] { + color: #AF5FAF +} + +div.highlight .-Color[class*=-BGC133] { + background-color: #AF5FAF +} + +div.highlight .-Color[class*=-C134] { + color: #AF5FD7 +} + +div.highlight .-Color[class*=-BGC134] { + background-color: #AF5FD7 +} + +div.highlight .-Color[class*=-C135] { + color: #AF5FFF +} + +div.highlight .-Color[class*=-BGC135] { + background-color: #AF5FFF +} + +div.highlight .-Color[class*=-C136] { + color: #AF8700 +} + +div.highlight .-Color[class*=-BGC136] { + background-color: #AF8700 +} + +div.highlight .-Color[class*=-C137] { + color: #AF875F +} + +div.highlight .-Color[class*=-BGC137] { + background-color: #AF875F +} + +div.highlight .-Color[class*=-C138] { + color: #AF8787 +} + +div.highlight .-Color[class*=-BGC138] { + background-color: #AF8787 +} + +div.highlight .-Color[class*=-C139] { + color: #AF87AF +} + +div.highlight .-Color[class*=-BGC139] { + background-color: #AF87AF +} + +div.highlight .-Color[class*=-C140] { + color: #AF87D7 +} + +div.highlight .-Color[class*=-BGC140] { + background-color: #AF87D7 +} + +div.highlight .-Color[class*=-C141] { + color: #AF87FF +} + +div.highlight .-Color[class*=-BGC141] { + background-color: #AF87FF +} + +div.highlight .-Color[class*=-C142] { + color: #AFAF00 +} + +div.highlight .-Color[class*=-BGC142] { + background-color: #AFAF00 +} + +div.highlight .-Color[class*=-C143] { + color: #AFAF5F +} + +div.highlight .-Color[class*=-BGC143] { + background-color: #AFAF5F +} + +div.highlight .-Color[class*=-C144] { + color: #AFAF87 +} + +div.highlight .-Color[class*=-BGC144] { + background-color: #AFAF87 +} + +div.highlight .-Color[class*=-C145] { + color: #AFAFAF +} + +div.highlight .-Color[class*=-BGC145] { + background-color: #AFAFAF +} + +div.highlight .-Color[class*=-C146] { + color: #AFAFD7 +} + +div.highlight .-Color[class*=-BGC146] { + background-color: #AFAFD7 +} + +div.highlight .-Color[class*=-C147] { + color: #AFAFFF +} + +div.highlight .-Color[class*=-BGC147] { + background-color: #AFAFFF +} + +div.highlight .-Color[class*=-C148] { + color: #AFD700 +} + +div.highlight .-Color[class*=-BGC148] { + background-color: #AFD700 +} + +div.highlight .-Color[class*=-C149] { + color: #AFD75F +} + +div.highlight .-Color[class*=-BGC149] { + background-color: #AFD75F +} + +div.highlight .-Color[class*=-C150] { + color: #AFD787 +} + +div.highlight .-Color[class*=-BGC150] { + background-color: #AFD787 +} + +div.highlight .-Color[class*=-C151] { + color: #AFD7AF +} + +div.highlight .-Color[class*=-BGC151] { + background-color: #AFD7AF +} + +div.highlight .-Color[class*=-C152] { + color: #AFD7D7 +} + +div.highlight .-Color[class*=-BGC152] { + background-color: #AFD7D7 +} + +div.highlight .-Color[class*=-C153] { + color: #AFD7FF +} + +div.highlight .-Color[class*=-BGC153] { + background-color: #AFD7FF +} + +div.highlight .-Color[class*=-C154] { + color: #AFFF00 +} + +div.highlight .-Color[class*=-BGC154] { + background-color: #AFFF00 +} + +div.highlight .-Color[class*=-C155] { + color: #AFFF5F +} + +div.highlight .-Color[class*=-BGC155] { + background-color: #AFFF5F +} + +div.highlight .-Color[class*=-C156] { + color: #AFFF87 +} + +div.highlight .-Color[class*=-BGC156] { + background-color: #AFFF87 +} + +div.highlight .-Color[class*=-C157] { + color: #AFFFAF +} + +div.highlight .-Color[class*=-BGC157] { + background-color: #AFFFAF +} + +div.highlight .-Color[class*=-C158] { + color: #AFFFD7 +} + +div.highlight .-Color[class*=-BGC158] { + background-color: #AFFFD7 +} + +div.highlight .-Color[class*=-C159] { + color: #AFFFFF +} + +div.highlight .-Color[class*=-BGC159] { + background-color: #AFFFFF +} + +div.highlight .-Color[class*=-C160] { + color: #D70000 +} + +div.highlight .-Color[class*=-BGC160] { + background-color: #D70000 +} + +div.highlight .-Color[class*=-C161] { + color: #D7005F +} + +div.highlight .-Color[class*=-BGC161] { + background-color: #D7005F +} + +div.highlight .-Color[class*=-C162] { + color: #D70087 +} + +div.highlight .-Color[class*=-BGC162] { + background-color: #D70087 +} + +div.highlight .-Color[class*=-C163] { + color: #D700AF +} + +div.highlight .-Color[class*=-BGC163] { + background-color: #D700AF +} + +div.highlight .-Color[class*=-C164] { + color: #D700D7 +} + +div.highlight .-Color[class*=-BGC164] { + background-color: #D700D7 +} + +div.highlight .-Color[class*=-C165] { + color: #D700FF +} + +div.highlight .-Color[class*=-BGC165] { + background-color: #D700FF +} + +div.highlight .-Color[class*=-C166] { + color: #D75F00 +} + +div.highlight .-Color[class*=-BGC166] { + background-color: #D75F00 +} + +div.highlight .-Color[class*=-C167] { + color: #D75F5F +} + +div.highlight .-Color[class*=-BGC167] { + background-color: #D75F5F +} + +div.highlight .-Color[class*=-C168] { + color: #D75F87 +} + +div.highlight .-Color[class*=-BGC168] { + background-color: #D75F87 +} + +div.highlight .-Color[class*=-C169] { + color: #D75FAF +} + +div.highlight .-Color[class*=-BGC169] { + background-color: #D75FAF +} + +div.highlight .-Color[class*=-C170] { + color: #D75FD7 +} + 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Default(){return Pe}static get DefaultType(){return Me}static get NAME(){return"swipe"}dispose(){fe.off(this._element,Le)}_start(t){this._supportPointerEvents?this._eventIsPointerPenTouch(t)&&(this._deltaX=t.clientX):this._deltaX=t.touches[0].clientX}_end(t){this._eventIsPointerPenTouch(t)&&(this._deltaX=t.clientX-this._deltaX),this._handleSwipe(),Xt(this._config.endCallback)}_move(t){this._deltaX=t.touches&&t.touches.length>1?0:t.touches[0].clientX-this._deltaX}_handleSwipe(){const t=Math.abs(this._deltaX);if(t<=40)return;const e=t/this._deltaX;this._deltaX=0,e&&Xt(e>0?this._config.rightCallback:this._config.leftCallback)}_initEvents(){this._supportPointerEvents?(fe.on(this._element,Ie,(t=>this._start(t))),fe.on(this._element,Ne,(t=>this._end(t))),this._element.classList.add("pointer-event")):(fe.on(this._element,Se,(t=>this._start(t))),fe.on(this._element,De,(t=>this._move(t))),fe.on(this._element,$e,(t=>this._end(t))))}_eventIsPointerPenTouch(t){return this._supportPointerEvents&&("pen"===t.pointerType||"touch"===t.pointerType)}static isSupported(){return"ontouchstart"in document.documentElement||navigator.maxTouchPoints>0}}const Fe=".bs.carousel",He=".data-api",Be="ArrowLeft",We="ArrowRight",ze="next",Re="prev",qe="left",Ve="right",Ye=`slide${Fe}`,Ke=`slid${Fe}`,Qe=`keydown${Fe}`,Xe=`mouseenter${Fe}`,Ue=`mouseleave${Fe}`,Ge=`dragstart${Fe}`,Je=`load${Fe}${He}`,Ze=`click${Fe}${He}`,ti="carousel",ei="active",ii=".active",ni=".carousel-item",si=ii+ni,oi={[Be]:Ve,[We]:qe},ri={interval:5e3,keyboard:!0,pause:"hover",ride:!1,touch:!0,wrap:!0},ai={interval:"(number|boolean)",keyboard:"boolean",pause:"(string|boolean)",ride:"(boolean|string)",touch:"boolean",wrap:"boolean"};class li extends ve{constructor(t,e){super(t,e),this._interval=null,this._activeElement=null,this._isSliding=!1,this.touchTimeout=null,this._swipeHelper=null,this._indicatorsElement=we.findOne(".carousel-indicators",this._element),this._addEventListeners(),this._config.ride===ti&&this.cycle()}static get Default(){return ri}static get DefaultType(){return ai}static get NAME(){return"carousel"}next(){this._slide(ze)}nextWhenVisible(){!document.hidden&&Bt(this._element)&&this.next()}prev(){this._slide(Re)}pause(){this._isSliding&&jt(this._element),this._clearInterval()}cycle(){this._clearInterval(),this._updateInterval(),this._interval=setInterval((()=>this.nextWhenVisible()),this._config.interval)}_maybeEnableCycle(){this._config.ride&&(this._isSliding?fe.one(this._element,Ke,(()=>this.cycle())):this.cycle())}to(t){const e=this._getItems();if(t>e.length-1||t<0)return;if(this._isSliding)return void fe.one(this._element,Ke,(()=>this.to(t)));const i=this._getItemIndex(this._getActive());if(i===t)return;const n=t>i?ze:Re;this._slide(n,e[t])}dispose(){this._swipeHelper&&this._swipeHelper.dispose(),super.dispose()}_configAfterMerge(t){return t.defaultInterval=t.interval,t}_addEventListeners(){this._config.keyboard&&fe.on(this._element,Qe,(t=>this._keydown(t))),"hover"===this._config.pause&&(fe.on(this._element,Xe,(()=>this.pause())),fe.on(this._element,Ue,(()=>this._maybeEnableCycle()))),this._config.touch&&je.isSupported()&&this._addTouchEventListeners()}_addTouchEventListeners(){for(const t of we.find(".carousel-item img",this._element))fe.on(t,Ge,(t=>t.preventDefault()));const t={leftCallback:()=>this._slide(this._directionToOrder(qe)),rightCallback:()=>this._slide(this._directionToOrder(Ve)),endCallback:()=>{"hover"===this._config.pause&&(this.pause(),this.touchTimeout&&clearTimeout(this.touchTimeout),this.touchTimeout=setTimeout((()=>this._maybeEnableCycle()),500+this._config.interval))}};this._swipeHelper=new je(this._element,t)}_keydown(t){if(/input|textarea/i.test(t.target.tagName))return;const e=oi[t.key];e&&(t.preventDefault(),this._slide(this._directionToOrder(e)))}_getItemIndex(t){return this._getItems().indexOf(t)}_setActiveIndicatorElement(t){if(!this._indicatorsElement)return;const e=we.findOne(ii,this._indicatorsElement);e.classList.remove(ei),e.removeAttribute("aria-current");const i=we.findOne(`[data-bs-slide-to="${t}"]`,this._indicatorsElement);i&&(i.classList.add(ei),i.setAttribute("aria-current","true"))}_updateInterval(){const t=this._activeElement||this._getActive();if(!t)return;const e=Number.parseInt(t.getAttribute("data-bs-interval"),10);this._config.interval=e||this._config.defaultInterval}_slide(t,e=null){if(this._isSliding)return;const i=this._getActive(),n=t===ze,s=e||Gt(this._getItems(),i,n,this._config.wrap);if(s===i)return;const o=this._getItemIndex(s),r=e=>fe.trigger(this._element,e,{relatedTarget:s,direction:this._orderToDirection(t),from:this._getItemIndex(i),to:o});if(r(Ye).defaultPrevented)return;if(!i||!s)return;const a=Boolean(this._interval);this.pause(),this._isSliding=!0,this._setActiveIndicatorElement(o),this._activeElement=s;const l=n?"carousel-item-start":"carousel-item-end",c=n?"carousel-item-next":"carousel-item-prev";s.classList.add(c),qt(s),i.classList.add(l),s.classList.add(l),this._queueCallback((()=>{s.classList.remove(l,c),s.classList.add(ei),i.classList.remove(ei,c,l),this._isSliding=!1,r(Ke)}),i,this._isAnimated()),a&&this.cycle()}_isAnimated(){return this._element.classList.contains("slide")}_getActive(){return we.findOne(si,this._element)}_getItems(){return we.find(ni,this._element)}_clearInterval(){this._interval&&(clearInterval(this._interval),this._interval=null)}_directionToOrder(t){return Kt()?t===qe?Re:ze:t===qe?ze:Re}_orderToDirection(t){return Kt()?t===Re?qe:Ve:t===Re?Ve:qe}static jQueryInterface(t){return this.each((function(){const e=li.getOrCreateInstance(this,t);if("number"!=typeof t){if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}else e.to(t)}))}}fe.on(document,Ze,"[data-bs-slide], [data-bs-slide-to]",(function(t){const e=we.getElementFromSelector(this);if(!e||!e.classList.contains(ti))return;t.preventDefault();const i=li.getOrCreateInstance(e),n=this.getAttribute("data-bs-slide-to");return n?(i.to(n),void i._maybeEnableCycle()):"next"===_e.getDataAttribute(this,"slide")?(i.next(),void i._maybeEnableCycle()):(i.prev(),void i._maybeEnableCycle())})),fe.on(window,Je,(()=>{const t=we.find('[data-bs-ride="carousel"]');for(const e of t)li.getOrCreateInstance(e)})),Qt(li);const ci=".bs.collapse",hi=`show${ci}`,di=`shown${ci}`,ui=`hide${ci}`,fi=`hidden${ci}`,pi=`click${ci}.data-api`,mi="show",gi="collapse",_i="collapsing",bi=`:scope .${gi} .${gi}`,vi='[data-bs-toggle="collapse"]',yi={parent:null,toggle:!0},wi={parent:"(null|element)",toggle:"boolean"};class Ei extends ve{constructor(t,e){super(t,e),this._isTransitioning=!1,this._triggerArray=[];const i=we.find(vi);for(const t of i){const e=we.getSelectorFromElement(t),i=we.find(e).filter((t=>t===this._element));null!==e&&i.length&&this._triggerArray.push(t)}this._initializeChildren(),this._config.parent||this._addAriaAndCollapsedClass(this._triggerArray,this._isShown()),this._config.toggle&&this.toggle()}static get Default(){return yi}static get DefaultType(){return wi}static get NAME(){return"collapse"}toggle(){this._isShown()?this.hide():this.show()}show(){if(this._isTransitioning||this._isShown())return;let t=[];if(this._config.parent&&(t=this._getFirstLevelChildren(".collapse.show, .collapse.collapsing").filter((t=>t!==this._element)).map((t=>Ei.getOrCreateInstance(t,{toggle:!1})))),t.length&&t[0]._isTransitioning)return;if(fe.trigger(this._element,hi).defaultPrevented)return;for(const e of t)e.hide();const e=this._getDimension();this._element.classList.remove(gi),this._element.classList.add(_i),this._element.style[e]=0,this._addAriaAndCollapsedClass(this._triggerArray,!0),this._isTransitioning=!0;const i=`scroll${e[0].toUpperCase()+e.slice(1)}`;this._queueCallback((()=>{this._isTransitioning=!1,this._element.classList.remove(_i),this._element.classList.add(gi,mi),this._element.style[e]="",fe.trigger(this._element,di)}),this._element,!0),this._element.style[e]=`${this._element[i]}px`}hide(){if(this._isTransitioning||!this._isShown())return;if(fe.trigger(this._element,ui).defaultPrevented)return;const t=this._getDimension();this._element.style[t]=`${this._element.getBoundingClientRect()[t]}px`,qt(this._element),this._element.classList.add(_i),this._element.classList.remove(gi,mi);for(const t of this._triggerArray){const e=we.getElementFromSelector(t);e&&!this._isShown(e)&&this._addAriaAndCollapsedClass([t],!1)}this._isTransitioning=!0,this._element.style[t]="",this._queueCallback((()=>{this._isTransitioning=!1,this._element.classList.remove(_i),this._element.classList.add(gi),fe.trigger(this._element,fi)}),this._element,!0)}_isShown(t=this._element){return t.classList.contains(mi)}_configAfterMerge(t){return t.toggle=Boolean(t.toggle),t.parent=Ht(t.parent),t}_getDimension(){return this._element.classList.contains("collapse-horizontal")?"width":"height"}_initializeChildren(){if(!this._config.parent)return;const t=this._getFirstLevelChildren(vi);for(const e of t){const t=we.getElementFromSelector(e);t&&this._addAriaAndCollapsedClass([e],this._isShown(t))}}_getFirstLevelChildren(t){const e=we.find(bi,this._config.parent);return we.find(t,this._config.parent).filter((t=>!e.includes(t)))}_addAriaAndCollapsedClass(t,e){if(t.length)for(const i of t)i.classList.toggle("collapsed",!e),i.setAttribute("aria-expanded",e)}static jQueryInterface(t){const e={};return"string"==typeof t&&/show|hide/.test(t)&&(e.toggle=!1),this.each((function(){const i=Ei.getOrCreateInstance(this,e);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t]()}}))}}fe.on(document,pi,vi,(function(t){("A"===t.target.tagName||t.delegateTarget&&"A"===t.delegateTarget.tagName)&&t.preventDefault();for(const t of we.getMultipleElementsFromSelector(this))Ei.getOrCreateInstance(t,{toggle:!1}).toggle()})),Qt(Ei);const Ai="dropdown",Ti=".bs.dropdown",Ci=".data-api",Oi="ArrowUp",xi="ArrowDown",ki=`hide${Ti}`,Li=`hidden${Ti}`,Si=`show${Ti}`,Di=`shown${Ti}`,$i=`click${Ti}${Ci}`,Ii=`keydown${Ti}${Ci}`,Ni=`keyup${Ti}${Ci}`,Pi="show",Mi='[data-bs-toggle="dropdown"]:not(.disabled):not(:disabled)',ji=`${Mi}.${Pi}`,Fi=".dropdown-menu",Hi=Kt()?"top-end":"top-start",Bi=Kt()?"top-start":"top-end",Wi=Kt()?"bottom-end":"bottom-start",zi=Kt()?"bottom-start":"bottom-end",Ri=Kt()?"left-start":"right-start",qi=Kt()?"right-start":"left-start",Vi={autoClose:!0,boundary:"clippingParents",display:"dynamic",offset:[0,2],popperConfig:null,reference:"toggle"},Yi={autoClose:"(boolean|string)",boundary:"(string|element)",display:"string",offset:"(array|string|function)",popperConfig:"(null|object|function)",reference:"(string|element|object)"};class Ki extends ve{constructor(t,e){super(t,e),this._popper=null,this._parent=this._element.parentNode,this._menu=we.next(this._element,Fi)[0]||we.prev(this._element,Fi)[0]||we.findOne(Fi,this._parent),this._inNavbar=this._detectNavbar()}static get Default(){return Vi}static get DefaultType(){return Yi}static get NAME(){return Ai}toggle(){return this._isShown()?this.hide():this.show()}show(){if(Wt(this._element)||this._isShown())return;const t={relatedTarget:this._element};if(!fe.trigger(this._element,Si,t).defaultPrevented){if(this._createPopper(),"ontouchstart"in document.documentElement&&!this._parent.closest(".navbar-nav"))for(const t of[].concat(...document.body.children))fe.on(t,"mouseover",Rt);this._element.focus(),this._element.setAttribute("aria-expanded",!0),this._menu.classList.add(Pi),this._element.classList.add(Pi),fe.trigger(this._element,Di,t)}}hide(){if(Wt(this._element)||!this._isShown())return;const t={relatedTarget:this._element};this._completeHide(t)}dispose(){this._popper&&this._popper.destroy(),super.dispose()}update(){this._inNavbar=this._detectNavbar(),this._popper&&this._popper.update()}_completeHide(t){if(!fe.trigger(this._element,ki,t).defaultPrevented){if("ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))fe.off(t,"mouseover",Rt);this._popper&&this._popper.destroy(),this._menu.classList.remove(Pi),this._element.classList.remove(Pi),this._element.setAttribute("aria-expanded","false"),_e.removeDataAttribute(this._menu,"popper"),fe.trigger(this._element,Li,t)}}_getConfig(t){if("object"==typeof(t=super._getConfig(t)).reference&&!Ft(t.reference)&&"function"!=typeof t.reference.getBoundingClientRect)throw new TypeError(`${Ai.toUpperCase()}: Option "reference" provided type "object" without a required "getBoundingClientRect" method.`);return t}_createPopper(){if(void 0===e)throw new TypeError("Bootstrap's dropdowns require Popper (https://popper.js.org)");let t=this._element;"parent"===this._config.reference?t=this._parent:Ft(this._config.reference)?t=Ht(this._config.reference):"object"==typeof this._config.reference&&(t=this._config.reference);const i=this._getPopperConfig();this._popper=Dt(t,this._menu,i)}_isShown(){return this._menu.classList.contains(Pi)}_getPlacement(){const t=this._parent;if(t.classList.contains("dropend"))return Ri;if(t.classList.contains("dropstart"))return qi;if(t.classList.contains("dropup-center"))return"top";if(t.classList.contains("dropdown-center"))return"bottom";const e="end"===getComputedStyle(this._menu).getPropertyValue("--bs-position").trim();return t.classList.contains("dropup")?e?Bi:Hi:e?zi:Wi}_detectNavbar(){return null!==this._element.closest(".navbar")}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return(this._inNavbar||"static"===this._config.display)&&(_e.setDataAttribute(this._menu,"popper","static"),t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,...Xt(this._config.popperConfig,[t])}}_selectMenuItem({key:t,target:e}){const i=we.find(".dropdown-menu .dropdown-item:not(.disabled):not(:disabled)",this._menu).filter((t=>Bt(t)));i.length&&Gt(i,e,t===xi,!i.includes(e)).focus()}static jQueryInterface(t){return this.each((function(){const e=Ki.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}static clearMenus(t){if(2===t.button||"keyup"===t.type&&"Tab"!==t.key)return;const e=we.find(ji);for(const i of e){const e=Ki.getInstance(i);if(!e||!1===e._config.autoClose)continue;const n=t.composedPath(),s=n.includes(e._menu);if(n.includes(e._element)||"inside"===e._config.autoClose&&!s||"outside"===e._config.autoClose&&s)continue;if(e._menu.contains(t.target)&&("keyup"===t.type&&"Tab"===t.key||/input|select|option|textarea|form/i.test(t.target.tagName)))continue;const o={relatedTarget:e._element};"click"===t.type&&(o.clickEvent=t),e._completeHide(o)}}static dataApiKeydownHandler(t){const e=/input|textarea/i.test(t.target.tagName),i="Escape"===t.key,n=[Oi,xi].includes(t.key);if(!n&&!i)return;if(e&&!i)return;t.preventDefault();const s=this.matches(Mi)?this:we.prev(this,Mi)[0]||we.next(this,Mi)[0]||we.findOne(Mi,t.delegateTarget.parentNode),o=Ki.getOrCreateInstance(s);if(n)return t.stopPropagation(),o.show(),void o._selectMenuItem(t);o._isShown()&&(t.stopPropagation(),o.hide(),s.focus())}}fe.on(document,Ii,Mi,Ki.dataApiKeydownHandler),fe.on(document,Ii,Fi,Ki.dataApiKeydownHandler),fe.on(document,$i,Ki.clearMenus),fe.on(document,Ni,Ki.clearMenus),fe.on(document,$i,Mi,(function(t){t.preventDefault(),Ki.getOrCreateInstance(this).toggle()})),Qt(Ki);const Qi="backdrop",Xi="show",Ui=`mousedown.bs.${Qi}`,Gi={className:"modal-backdrop",clickCallback:null,isAnimated:!1,isVisible:!0,rootElement:"body"},Ji={className:"string",clickCallback:"(function|null)",isAnimated:"boolean",isVisible:"boolean",rootElement:"(element|string)"};class Zi extends be{constructor(t){super(),this._config=this._getConfig(t),this._isAppended=!1,this._element=null}static get Default(){return Gi}static get DefaultType(){return Ji}static get NAME(){return Qi}show(t){if(!this._config.isVisible)return void Xt(t);this._append();const e=this._getElement();this._config.isAnimated&&qt(e),e.classList.add(Xi),this._emulateAnimation((()=>{Xt(t)}))}hide(t){this._config.isVisible?(this._getElement().classList.remove(Xi),this._emulateAnimation((()=>{this.dispose(),Xt(t)}))):Xt(t)}dispose(){this._isAppended&&(fe.off(this._element,Ui),this._element.remove(),this._isAppended=!1)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_configAfterMerge(t){return t.rootElement=Ht(t.rootElement),t}_append(){if(this._isAppended)return;const t=this._getElement();this._config.rootElement.append(t),fe.on(t,Ui,(()=>{Xt(this._config.clickCallback)})),this._isAppended=!0}_emulateAnimation(t){Ut(t,this._getElement(),this._config.isAnimated)}}const tn=".bs.focustrap",en=`focusin${tn}`,nn=`keydown.tab${tn}`,sn="backward",on={autofocus:!0,trapElement:null},rn={autofocus:"boolean",trapElement:"element"};class an extends be{constructor(t){super(),this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}static get Default(){return on}static get DefaultType(){return rn}static get NAME(){return"focustrap"}activate(){this._isActive||(this._config.autofocus&&this._config.trapElement.focus(),fe.off(document,tn),fe.on(document,en,(t=>this._handleFocusin(t))),fe.on(document,nn,(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,fe.off(document,tn))}_handleFocusin(t){const{trapElement:e}=this._config;if(t.target===document||t.target===e||e.contains(t.target))return;const i=we.focusableChildren(e);0===i.length?e.focus():this._lastTabNavDirection===sn?i[i.length-1].focus():i[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?sn:"forward")}}const ln=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",cn=".sticky-top",hn="padding-right",dn="margin-right";class un{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,hn,(e=>e+t)),this._setElementAttributes(ln,hn,(e=>e+t)),this._setElementAttributes(cn,dn,(e=>e-t))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,hn),this._resetElementAttributes(ln,hn),this._resetElementAttributes(cn,dn)}isOverflowing(){return this.getWidth()>0}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t).getPropertyValue(e);t.style.setProperty(e,`${i(Number.parseFloat(s))}px`)}))}_saveInitialAttribute(t,e){const i=t.style.getPropertyValue(e);i&&_e.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=_e.getDataAttribute(t,e);null!==i?(_e.removeDataAttribute(t,e),t.style.setProperty(e,i)):t.style.removeProperty(e)}))}_applyManipulationCallback(t,e){if(Ft(t))e(t);else for(const i of we.find(t,this._element))e(i)}}const fn=".bs.modal",pn=`hide${fn}`,mn=`hidePrevented${fn}`,gn=`hidden${fn}`,_n=`show${fn}`,bn=`shown${fn}`,vn=`resize${fn}`,yn=`click.dismiss${fn}`,wn=`mousedown.dismiss${fn}`,En=`keydown.dismiss${fn}`,An=`click${fn}.data-api`,Tn="modal-open",Cn="show",On="modal-static",xn={backdrop:!0,focus:!0,keyboard:!0},kn={backdrop:"(boolean|string)",focus:"boolean",keyboard:"boolean"};class Ln extends ve{constructor(t,e){super(t,e),this._dialog=we.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._isTransitioning=!1,this._scrollBar=new un,this._addEventListeners()}static get Default(){return xn}static get DefaultType(){return kn}static get NAME(){return"modal"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||fe.trigger(this._element,_n,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isTransitioning=!0,this._scrollBar.hide(),document.body.classList.add(Tn),this._adjustDialog(),this._backdrop.show((()=>this._showElement(t))))}hide(){this._isShown&&!this._isTransitioning&&(fe.trigger(this._element,pn).defaultPrevented||(this._isShown=!1,this._isTransitioning=!0,this._focustrap.deactivate(),this._element.classList.remove(Cn),this._queueCallback((()=>this._hideModal()),this._element,this._isAnimated())))}dispose(){fe.off(window,fn),fe.off(this._dialog,fn),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new Zi({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new an({trapElement:this._element})}_showElement(t){document.body.contains(this._element)||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0;const e=we.findOne(".modal-body",this._dialog);e&&(e.scrollTop=0),qt(this._element),this._element.classList.add(Cn),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,fe.trigger(this._element,bn,{relatedTarget:t})}),this._dialog,this._isAnimated())}_addEventListeners(){fe.on(this._element,En,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():this._triggerBackdropTransition())})),fe.on(window,vn,(()=>{this._isShown&&!this._isTransitioning&&this._adjustDialog()})),fe.on(this._element,wn,(t=>{fe.one(this._element,yn,(e=>{this._element===t.target&&this._element===e.target&&("static"!==this._config.backdrop?this._config.backdrop&&this.hide():this._triggerBackdropTransition())}))}))}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(Tn),this._resetAdjustments(),this._scrollBar.reset(),fe.trigger(this._element,gn)}))}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(fe.trigger(this._element,mn).defaultPrevented)return;const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._element.style.overflowY;"hidden"===e||this._element.classList.contains(On)||(t||(this._element.style.overflowY="hidden"),this._element.classList.add(On),this._queueCallback((()=>{this._element.classList.remove(On),this._queueCallback((()=>{this._element.style.overflowY=e}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;if(i&&!t){const t=Kt()?"paddingLeft":"paddingRight";this._element.style[t]=`${e}px`}if(!i&&t){const t=Kt()?"paddingRight":"paddingLeft";this._element.style[t]=`${e}px`}}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=Ln.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}fe.on(document,An,'[data-bs-toggle="modal"]',(function(t){const e=we.getElementFromSelector(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),fe.one(e,_n,(t=>{t.defaultPrevented||fe.one(e,gn,(()=>{Bt(this)&&this.focus()}))}));const i=we.findOne(".modal.show");i&&Ln.getInstance(i).hide(),Ln.getOrCreateInstance(e).toggle(this)})),Ee(Ln),Qt(Ln);const Sn=".bs.offcanvas",Dn=".data-api",$n=`load${Sn}${Dn}`,In="show",Nn="showing",Pn="hiding",Mn=".offcanvas.show",jn=`show${Sn}`,Fn=`shown${Sn}`,Hn=`hide${Sn}`,Bn=`hidePrevented${Sn}`,Wn=`hidden${Sn}`,zn=`resize${Sn}`,Rn=`click${Sn}${Dn}`,qn=`keydown.dismiss${Sn}`,Vn={backdrop:!0,keyboard:!0,scroll:!1},Yn={backdrop:"(boolean|string)",keyboard:"boolean",scroll:"boolean"};class Kn extends ve{constructor(t,e){super(t,e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get Default(){return Vn}static get DefaultType(){return Yn}static get NAME(){return"offcanvas"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||fe.trigger(this._element,jn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._backdrop.show(),this._config.scroll||(new un).hide(),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add(Nn),this._queueCallback((()=>{this._config.scroll&&!this._config.backdrop||this._focustrap.activate(),this._element.classList.add(In),this._element.classList.remove(Nn),fe.trigger(this._element,Fn,{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(fe.trigger(this._element,Hn).defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.add(Pn),this._backdrop.hide(),this._queueCallback((()=>{this._element.classList.remove(In,Pn),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._config.scroll||(new un).reset(),fe.trigger(this._element,Wn)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_initializeBackDrop(){const t=Boolean(this._config.backdrop);return new Zi({className:"offcanvas-backdrop",isVisible:t,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:t?()=>{"static"!==this._config.backdrop?this.hide():fe.trigger(this._element,Bn)}:null})}_initializeFocusTrap(){return new an({trapElement:this._element})}_addEventListeners(){fe.on(this._element,qn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():fe.trigger(this._element,Bn))}))}static jQueryInterface(t){return this.each((function(){const e=Kn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}fe.on(document,Rn,'[data-bs-toggle="offcanvas"]',(function(t){const e=we.getElementFromSelector(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),Wt(this))return;fe.one(e,Wn,(()=>{Bt(this)&&this.focus()}));const i=we.findOne(Mn);i&&i!==e&&Kn.getInstance(i).hide(),Kn.getOrCreateInstance(e).toggle(this)})),fe.on(window,$n,(()=>{for(const t of we.find(Mn))Kn.getOrCreateInstance(t).show()})),fe.on(window,zn,(()=>{for(const t of we.find("[aria-modal][class*=show][class*=offcanvas-]"))"fixed"!==getComputedStyle(t).position&&Kn.getOrCreateInstance(t).hide()})),Ee(Kn),Qt(Kn);const Qn={"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],dd:[],div:[],dl:[],dt:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},Xn=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Un=/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i,Gn=(t,e)=>{const i=t.nodeName.toLowerCase();return e.includes(i)?!Xn.has(i)||Boolean(Un.test(t.nodeValue)):e.filter((t=>t instanceof RegExp)).some((t=>t.test(i)))},Jn={allowList:Qn,content:{},extraClass:"",html:!1,sanitize:!0,sanitizeFn:null,template:"
"},Zn={allowList:"object",content:"object",extraClass:"(string|function)",html:"boolean",sanitize:"boolean",sanitizeFn:"(null|function)",template:"string"},ts={entry:"(string|element|function|null)",selector:"(string|element)"};class es extends be{constructor(t){super(),this._config=this._getConfig(t)}static get Default(){return Jn}static get DefaultType(){return Zn}static get NAME(){return"TemplateFactory"}getContent(){return Object.values(this._config.content).map((t=>this._resolvePossibleFunction(t))).filter(Boolean)}hasContent(){return this.getContent().length>0}changeContent(t){return this._checkContent(t),this._config.content={...this._config.content,...t},this}toHtml(){const t=document.createElement("div");t.innerHTML=this._maybeSanitize(this._config.template);for(const[e,i]of Object.entries(this._config.content))this._setContent(t,i,e);const e=t.children[0],i=this._resolvePossibleFunction(this._config.extraClass);return i&&e.classList.add(...i.split(" ")),e}_typeCheckConfig(t){super._typeCheckConfig(t),this._checkContent(t.content)}_checkContent(t){for(const[e,i]of Object.entries(t))super._typeCheckConfig({selector:e,entry:i},ts)}_setContent(t,e,i){const n=we.findOne(i,t);n&&((e=this._resolvePossibleFunction(e))?Ft(e)?this._putElementInTemplate(Ht(e),n):this._config.html?n.innerHTML=this._maybeSanitize(e):n.textContent=e:n.remove())}_maybeSanitize(t){return this._config.sanitize?function(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(const t of s){const i=t.nodeName.toLowerCase();if(!Object.keys(e).includes(i)){t.remove();continue}const n=[].concat(...t.attributes),s=[].concat(e["*"]||[],e[i]||[]);for(const e of n)Gn(e,s)||t.removeAttribute(e.nodeName)}return n.body.innerHTML}(t,this._config.allowList,this._config.sanitizeFn):t}_resolvePossibleFunction(t){return Xt(t,[this])}_putElementInTemplate(t,e){if(this._config.html)return e.innerHTML="",void e.append(t);e.textContent=t.textContent}}const is=new Set(["sanitize","allowList","sanitizeFn"]),ns="fade",ss="show",os=".tooltip-inner",rs=".modal",as="hide.bs.modal",ls="hover",cs="focus",hs={AUTO:"auto",TOP:"top",RIGHT:Kt()?"left":"right",BOTTOM:"bottom",LEFT:Kt()?"right":"left"},ds={allowList:Qn,animation:!0,boundary:"clippingParents",container:!1,customClass:"",delay:0,fallbackPlacements:["top","right","bottom","left"],html:!1,offset:[0,6],placement:"top",popperConfig:null,sanitize:!0,sanitizeFn:null,selector:!1,template:'',title:"",trigger:"hover focus"},us={allowList:"object",animation:"boolean",boundary:"(string|element)",container:"(string|element|boolean)",customClass:"(string|function)",delay:"(number|object)",fallbackPlacements:"array",html:"boolean",offset:"(array|string|function)",placement:"(string|function)",popperConfig:"(null|object|function)",sanitize:"boolean",sanitizeFn:"(null|function)",selector:"(string|boolean)",template:"string",title:"(string|element|function)",trigger:"string"};class fs extends ve{constructor(t,i){if(void 0===e)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t,i),this._isEnabled=!0,this._timeout=0,this._isHovered=null,this._activeTrigger={},this._popper=null,this._templateFactory=null,this._newContent=null,this.tip=null,this._setListeners(),this._config.selector||this._fixTitle()}static get Default(){return ds}static get DefaultType(){return us}static get NAME(){return"tooltip"}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(){this._isEnabled&&(this._activeTrigger.click=!this._activeTrigger.click,this._isShown()?this._leave():this._enter())}dispose(){clearTimeout(this._timeout),fe.off(this._element.closest(rs),as,this._hideModalHandler),this._element.getAttribute("data-bs-original-title")&&this._element.setAttribute("title",this._element.getAttribute("data-bs-original-title")),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this._isWithContent()||!this._isEnabled)return;const t=fe.trigger(this._element,this.constructor.eventName("show")),e=(zt(this._element)||this._element.ownerDocument.documentElement).contains(this._element);if(t.defaultPrevented||!e)return;this._disposePopper();const i=this._getTipElement();this._element.setAttribute("aria-describedby",i.getAttribute("id"));const{container:n}=this._config;if(this._element.ownerDocument.documentElement.contains(this.tip)||(n.append(i),fe.trigger(this._element,this.constructor.eventName("inserted"))),this._popper=this._createPopper(i),i.classList.add(ss),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))fe.on(t,"mouseover",Rt);this._queueCallback((()=>{fe.trigger(this._element,this.constructor.eventName("shown")),!1===this._isHovered&&this._leave(),this._isHovered=!1}),this.tip,this._isAnimated())}hide(){if(this._isShown()&&!fe.trigger(this._element,this.constructor.eventName("hide")).defaultPrevented){if(this._getTipElement().classList.remove(ss),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))fe.off(t,"mouseover",Rt);this._activeTrigger.click=!1,this._activeTrigger[cs]=!1,this._activeTrigger[ls]=!1,this._isHovered=null,this._queueCallback((()=>{this._isWithActiveTrigger()||(this._isHovered||this._disposePopper(),this._element.removeAttribute("aria-describedby"),fe.trigger(this._element,this.constructor.eventName("hidden")))}),this.tip,this._isAnimated())}}update(){this._popper&&this._popper.update()}_isWithContent(){return Boolean(this._getTitle())}_getTipElement(){return this.tip||(this.tip=this._createTipElement(this._newContent||this._getContentForTemplate())),this.tip}_createTipElement(t){const e=this._getTemplateFactory(t).toHtml();if(!e)return null;e.classList.remove(ns,ss),e.classList.add(`bs-${this.constructor.NAME}-auto`);const i=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME).toString();return e.setAttribute("id",i),this._isAnimated()&&e.classList.add(ns),e}setContent(t){this._newContent=t,this._isShown()&&(this._disposePopper(),this.show())}_getTemplateFactory(t){return this._templateFactory?this._templateFactory.changeContent(t):this._templateFactory=new es({...this._config,content:t,extraClass:this._resolvePossibleFunction(this._config.customClass)}),this._templateFactory}_getContentForTemplate(){return{[os]:this._getTitle()}}_getTitle(){return this._resolvePossibleFunction(this._config.title)||this._element.getAttribute("data-bs-original-title")}_initializeOnDelegatedTarget(t){return this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_isAnimated(){return this._config.animation||this.tip&&this.tip.classList.contains(ns)}_isShown(){return this.tip&&this.tip.classList.contains(ss)}_createPopper(t){const e=Xt(this._config.placement,[this,t,this._element]),i=hs[e.toUpperCase()];return Dt(this._element,t,this._getPopperConfig(i))}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return Xt(t,[this._element])}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"preSetPlacement",enabled:!0,phase:"beforeMain",fn:t=>{this._getTipElement().setAttribute("data-popper-placement",t.state.placement)}}]};return{...e,...Xt(this._config.popperConfig,[e])}}_setListeners(){const t=this._config.trigger.split(" ");for(const e of t)if("click"===e)fe.on(this._element,this.constructor.eventName("click"),this._config.selector,(t=>{this._initializeOnDelegatedTarget(t).toggle()}));else if("manual"!==e){const t=e===ls?this.constructor.eventName("mouseenter"):this.constructor.eventName("focusin"),i=e===ls?this.constructor.eventName("mouseleave"):this.constructor.eventName("focusout");fe.on(this._element,t,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusin"===t.type?cs:ls]=!0,e._enter()})),fe.on(this._element,i,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusout"===t.type?cs:ls]=e._element.contains(t.relatedTarget),e._leave()}))}this._hideModalHandler=()=>{this._element&&this.hide()},fe.on(this._element.closest(rs),as,this._hideModalHandler)}_fixTitle(){const t=this._element.getAttribute("title");t&&(this._element.getAttribute("aria-label")||this._element.textContent.trim()||this._element.setAttribute("aria-label",t),this._element.setAttribute("data-bs-original-title",t),this._element.removeAttribute("title"))}_enter(){this._isShown()||this._isHovered?this._isHovered=!0:(this._isHovered=!0,this._setTimeout((()=>{this._isHovered&&this.show()}),this._config.delay.show))}_leave(){this._isWithActiveTrigger()||(this._isHovered=!1,this._setTimeout((()=>{this._isHovered||this.hide()}),this._config.delay.hide))}_setTimeout(t,e){clearTimeout(this._timeout),this._timeout=setTimeout(t,e)}_isWithActiveTrigger(){return Object.values(this._activeTrigger).includes(!0)}_getConfig(t){const e=_e.getDataAttributes(this._element);for(const t of Object.keys(e))is.has(t)&&delete e[t];return t={...e,..."object"==typeof t&&t?t:{}},t=this._mergeConfigObj(t),t=this._configAfterMerge(t),this._typeCheckConfig(t),t}_configAfterMerge(t){return t.container=!1===t.container?document.body:Ht(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),t}_getDelegateConfig(){const t={};for(const[e,i]of Object.entries(this._config))this.constructor.Default[e]!==i&&(t[e]=i);return t.selector=!1,t.trigger="manual",t}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null),this.tip&&(this.tip.remove(),this.tip=null)}static jQueryInterface(t){return this.each((function(){const e=fs.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}Qt(fs);const ps=".popover-header",ms=".popover-body",gs={...fs.Default,content:"",offset:[0,8],placement:"right",template:'',trigger:"click"},_s={...fs.DefaultType,content:"(null|string|element|function)"};class bs extends fs{static get Default(){return gs}static get DefaultType(){return _s}static get NAME(){return"popover"}_isWithContent(){return this._getTitle()||this._getContent()}_getContentForTemplate(){return{[ps]:this._getTitle(),[ms]:this._getContent()}}_getContent(){return this._resolvePossibleFunction(this._config.content)}static jQueryInterface(t){return this.each((function(){const e=bs.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}Qt(bs);const vs=".bs.scrollspy",ys=`activate${vs}`,ws=`click${vs}`,Es=`load${vs}.data-api`,As="active",Ts="[href]",Cs=".nav-link",Os=`${Cs}, .nav-item > ${Cs}, .list-group-item`,xs={offset:null,rootMargin:"0px 0px -25%",smoothScroll:!1,target:null,threshold:[.1,.5,1]},ks={offset:"(number|null)",rootMargin:"string",smoothScroll:"boolean",target:"element",threshold:"array"};class Ls extends ve{constructor(t,e){super(t,e),this._targetLinks=new Map,this._observableSections=new Map,this._rootElement="visible"===getComputedStyle(this._element).overflowY?null:this._element,this._activeTarget=null,this._observer=null,this._previousScrollData={visibleEntryTop:0,parentScrollTop:0},this.refresh()}static get Default(){return xs}static get DefaultType(){return ks}static get NAME(){return"scrollspy"}refresh(){this._initializeTargetsAndObservables(),this._maybeEnableSmoothScroll(),this._observer?this._observer.disconnect():this._observer=this._getNewObserver();for(const t of this._observableSections.values())this._observer.observe(t)}dispose(){this._observer.disconnect(),super.dispose()}_configAfterMerge(t){return t.target=Ht(t.target)||document.body,t.rootMargin=t.offset?`${t.offset}px 0px -30%`:t.rootMargin,"string"==typeof t.threshold&&(t.threshold=t.threshold.split(",").map((t=>Number.parseFloat(t)))),t}_maybeEnableSmoothScroll(){this._config.smoothScroll&&(fe.off(this._config.target,ws),fe.on(this._config.target,ws,Ts,(t=>{const e=this._observableSections.get(t.target.hash);if(e){t.preventDefault();const i=this._rootElement||window,n=e.offsetTop-this._element.offsetTop;if(i.scrollTo)return void i.scrollTo({top:n,behavior:"smooth"});i.scrollTop=n}})))}_getNewObserver(){const t={root:this._rootElement,threshold:this._config.threshold,rootMargin:this._config.rootMargin};return new IntersectionObserver((t=>this._observerCallback(t)),t)}_observerCallback(t){const e=t=>this._targetLinks.get(`#${t.target.id}`),i=t=>{this._previousScrollData.visibleEntryTop=t.target.offsetTop,this._process(e(t))},n=(this._rootElement||document.documentElement).scrollTop,s=n>=this._previousScrollData.parentScrollTop;this._previousScrollData.parentScrollTop=n;for(const o of t){if(!o.isIntersecting){this._activeTarget=null,this._clearActiveClass(e(o));continue}const t=o.target.offsetTop>=this._previousScrollData.visibleEntryTop;if(s&&t){if(i(o),!n)return}else s||t||i(o)}}_initializeTargetsAndObservables(){this._targetLinks=new Map,this._observableSections=new Map;const t=we.find(Ts,this._config.target);for(const e of t){if(!e.hash||Wt(e))continue;const t=we.findOne(decodeURI(e.hash),this._element);Bt(t)&&(this._targetLinks.set(decodeURI(e.hash),e),this._observableSections.set(e.hash,t))}}_process(t){this._activeTarget!==t&&(this._clearActiveClass(this._config.target),this._activeTarget=t,t.classList.add(As),this._activateParents(t),fe.trigger(this._element,ys,{relatedTarget:t}))}_activateParents(t){if(t.classList.contains("dropdown-item"))we.findOne(".dropdown-toggle",t.closest(".dropdown")).classList.add(As);else for(const e of we.parents(t,".nav, .list-group"))for(const t of we.prev(e,Os))t.classList.add(As)}_clearActiveClass(t){t.classList.remove(As);const e=we.find(`${Ts}.${As}`,t);for(const t of e)t.classList.remove(As)}static jQueryInterface(t){return this.each((function(){const e=Ls.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}))}}fe.on(window,Es,(()=>{for(const t of we.find('[data-bs-spy="scroll"]'))Ls.getOrCreateInstance(t)})),Qt(Ls);const Ss=".bs.tab",Ds=`hide${Ss}`,$s=`hidden${Ss}`,Is=`show${Ss}`,Ns=`shown${Ss}`,Ps=`click${Ss}`,Ms=`keydown${Ss}`,js=`load${Ss}`,Fs="ArrowLeft",Hs="ArrowRight",Bs="ArrowUp",Ws="ArrowDown",zs="Home",Rs="End",qs="active",Vs="fade",Ys="show",Ks=".dropdown-toggle",Qs=`:not(${Ks})`,Xs='[data-bs-toggle="tab"], [data-bs-toggle="pill"], [data-bs-toggle="list"]',Us=`.nav-link${Qs}, .list-group-item${Qs}, [role="tab"]${Qs}, ${Xs}`,Gs=`.${qs}[data-bs-toggle="tab"], .${qs}[data-bs-toggle="pill"], .${qs}[data-bs-toggle="list"]`;class Js extends ve{constructor(t){super(t),this._parent=this._element.closest('.list-group, .nav, [role="tablist"]'),this._parent&&(this._setInitialAttributes(this._parent,this._getChildren()),fe.on(this._element,Ms,(t=>this._keydown(t))))}static get NAME(){return"tab"}show(){const t=this._element;if(this._elemIsActive(t))return;const 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00000000..28755c2c --- /dev/null +++ b/_static/scripts/bootstrap.js.LICENSE.txt @@ -0,0 +1,5 @@ +/*! + * Bootstrap v5.3.3 (https://getbootstrap.com/) + * Copyright 2011-2024 The Bootstrap Authors (https://github.com/twbs/bootstrap/graphs/contributors) + * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE) + */ diff --git a/_static/scripts/bootstrap.js.map b/_static/scripts/bootstrap.js.map new file mode 100644 index 00000000..4a3502ae --- /dev/null +++ b/_static/scripts/bootstrap.js.map @@ -0,0 +1 @@ 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(element.nodeName || '').toLowerCase() : null;\n}","export default function getWindow(node) {\n if (node == null) {\n return window;\n }\n\n if (node.toString() !== '[object Window]') {\n var ownerDocument = node.ownerDocument;\n return ownerDocument ? ownerDocument.defaultView || window : window;\n }\n\n return node;\n}","import getWindow from \"./getWindow.js\";\n\nfunction isElement(node) {\n var OwnElement = getWindow(node).Element;\n return node instanceof OwnElement || node instanceof Element;\n}\n\nfunction isHTMLElement(node) {\n var OwnElement = getWindow(node).HTMLElement;\n return node instanceof OwnElement || node instanceof HTMLElement;\n}\n\nfunction isShadowRoot(node) {\n // IE 11 has no ShadowRoot\n if (typeof ShadowRoot === 'undefined') {\n return false;\n }\n\n var OwnElement = getWindow(node).ShadowRoot;\n return node instanceof OwnElement || node instanceof ShadowRoot;\n}\n\nexport { isElement, isHTMLElement, isShadowRoot };","import getNodeName from \"../dom-utils/getNodeName.js\";\nimport { isHTMLElement } from \"../dom-utils/instanceOf.js\"; // This modifier takes the styles prepared by the `computeStyles` modifier\n// and applies them to the HTMLElements such as popper and arrow\n\nfunction applyStyles(_ref) {\n var state = _ref.state;\n Object.keys(state.elements).forEach(function (name) {\n var style = state.styles[name] || {};\n var attributes = state.attributes[name] || {};\n var element = state.elements[name]; // arrow is optional + virtual elements\n\n if (!isHTMLElement(element) || !getNodeName(element)) {\n return;\n } // Flow doesn't support to extend this property, but it's the most\n // effective way to apply styles to an HTMLElement\n // $FlowFixMe[cannot-write]\n\n\n Object.assign(element.style, style);\n Object.keys(attributes).forEach(function (name) {\n var value = attributes[name];\n\n if (value === false) {\n element.removeAttribute(name);\n } else {\n element.setAttribute(name, value === true ? '' : value);\n }\n });\n });\n}\n\nfunction effect(_ref2) {\n var state = _ref2.state;\n var initialStyles = {\n popper: {\n position: state.options.strategy,\n left: '0',\n top: '0',\n margin: '0'\n },\n arrow: {\n position: 'absolute'\n },\n reference: {}\n };\n Object.assign(state.elements.popper.style, initialStyles.popper);\n state.styles = initialStyles;\n\n if (state.elements.arrow) {\n Object.assign(state.elements.arrow.style, initialStyles.arrow);\n }\n\n return function () {\n Object.keys(state.elements).forEach(function (name) {\n var element = state.elements[name];\n var attributes = state.attributes[name] || {};\n var styleProperties = Object.keys(state.styles.hasOwnProperty(name) ? state.styles[name] : initialStyles[name]); // Set all values to an empty string to unset them\n\n var style = styleProperties.reduce(function (style, property) {\n style[property] = '';\n return style;\n }, {}); // arrow is optional + virtual elements\n\n if (!isHTMLElement(element) || !getNodeName(element)) {\n return;\n }\n\n Object.assign(element.style, style);\n Object.keys(attributes).forEach(function (attribute) {\n element.removeAttribute(attribute);\n });\n });\n };\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'applyStyles',\n enabled: true,\n phase: 'write',\n fn: applyStyles,\n effect: effect,\n requires: ['computeStyles']\n};","import { auto } from \"../enums.js\";\nexport default function getBasePlacement(placement) {\n return placement.split('-')[0];\n}","export var max = Math.max;\nexport var min = Math.min;\nexport var round = Math.round;","export default function getUAString() {\n var uaData = navigator.userAgentData;\n\n if (uaData != null && uaData.brands && Array.isArray(uaData.brands)) {\n return uaData.brands.map(function (item) {\n return item.brand + \"/\" + item.version;\n }).join(' ');\n }\n\n return navigator.userAgent;\n}","import getUAString from \"../utils/userAgent.js\";\nexport default function isLayoutViewport() {\n return !/^((?!chrome|android).)*safari/i.test(getUAString());\n}","import { isElement, isHTMLElement } from \"./instanceOf.js\";\nimport { round } from \"../utils/math.js\";\nimport getWindow from \"./getWindow.js\";\nimport isLayoutViewport from \"./isLayoutViewport.js\";\nexport default function getBoundingClientRect(element, includeScale, isFixedStrategy) {\n if (includeScale === void 0) {\n includeScale = false;\n }\n\n if (isFixedStrategy === void 0) {\n isFixedStrategy = false;\n }\n\n var clientRect = element.getBoundingClientRect();\n var scaleX = 1;\n var scaleY = 1;\n\n if (includeScale && isHTMLElement(element)) {\n scaleX = element.offsetWidth > 0 ? round(clientRect.width) / element.offsetWidth || 1 : 1;\n scaleY = element.offsetHeight > 0 ? round(clientRect.height) / element.offsetHeight || 1 : 1;\n }\n\n var _ref = isElement(element) ? getWindow(element) : window,\n visualViewport = _ref.visualViewport;\n\n var addVisualOffsets = !isLayoutViewport() && isFixedStrategy;\n var x = (clientRect.left + (addVisualOffsets && visualViewport ? visualViewport.offsetLeft : 0)) / scaleX;\n var y = (clientRect.top + (addVisualOffsets && visualViewport ? visualViewport.offsetTop : 0)) / scaleY;\n var width = clientRect.width / scaleX;\n var height = clientRect.height / scaleY;\n return {\n width: width,\n height: height,\n top: y,\n right: x + width,\n bottom: y + height,\n left: x,\n x: x,\n y: y\n };\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\"; // Returns the layout rect of an element relative to its offsetParent. Layout\n// means it doesn't take into account transforms.\n\nexport default function getLayoutRect(element) {\n var clientRect = getBoundingClientRect(element); // Use the clientRect sizes if it's not been transformed.\n // Fixes https://github.com/popperjs/popper-core/issues/1223\n\n var width = element.offsetWidth;\n var height = element.offsetHeight;\n\n if (Math.abs(clientRect.width - width) <= 1) {\n width = clientRect.width;\n }\n\n if (Math.abs(clientRect.height - height) <= 1) {\n height = clientRect.height;\n }\n\n return {\n x: element.offsetLeft,\n y: element.offsetTop,\n width: width,\n height: height\n };\n}","import { isShadowRoot } from \"./instanceOf.js\";\nexport default function contains(parent, child) {\n var rootNode = child.getRootNode && child.getRootNode(); // First, attempt with faster native method\n\n if (parent.contains(child)) {\n return true;\n } // then fallback to custom implementation with Shadow DOM support\n else if (rootNode && isShadowRoot(rootNode)) {\n var next = child;\n\n do {\n if (next && parent.isSameNode(next)) {\n return true;\n } // $FlowFixMe[prop-missing]: need a better way to handle this...\n\n\n next = next.parentNode || next.host;\n } while (next);\n } // Give up, the result is false\n\n\n return false;\n}","import getWindow from \"./getWindow.js\";\nexport default function getComputedStyle(element) {\n return getWindow(element).getComputedStyle(element);\n}","import getNodeName from \"./getNodeName.js\";\nexport default function isTableElement(element) {\n return ['table', 'td', 'th'].indexOf(getNodeName(element)) >= 0;\n}","import { isElement } from \"./instanceOf.js\";\nexport default function getDocumentElement(element) {\n // $FlowFixMe[incompatible-return]: assume body is always available\n return ((isElement(element) ? element.ownerDocument : // $FlowFixMe[prop-missing]\n element.document) || window.document).documentElement;\n}","import getNodeName from \"./getNodeName.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport { isShadowRoot } from \"./instanceOf.js\";\nexport default function getParentNode(element) {\n if (getNodeName(element) === 'html') {\n return element;\n }\n\n return (// this is a quicker (but less type safe) way to save quite some bytes from the bundle\n // $FlowFixMe[incompatible-return]\n // $FlowFixMe[prop-missing]\n element.assignedSlot || // step into the shadow DOM of the parent of a slotted node\n element.parentNode || ( // DOM Element detected\n isShadowRoot(element) ? element.host : null) || // ShadowRoot detected\n // $FlowFixMe[incompatible-call]: HTMLElement is a Node\n getDocumentElement(element) // fallback\n\n );\n}","import getWindow from \"./getWindow.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport { isHTMLElement, isShadowRoot } from \"./instanceOf.js\";\nimport isTableElement from \"./isTableElement.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport getUAString from \"../utils/userAgent.js\";\n\nfunction getTrueOffsetParent(element) {\n if (!isHTMLElement(element) || // https://github.com/popperjs/popper-core/issues/837\n getComputedStyle(element).position === 'fixed') {\n return null;\n }\n\n return element.offsetParent;\n} // `.offsetParent` reports `null` for fixed elements, while absolute elements\n// return the containing block\n\n\nfunction getContainingBlock(element) {\n var isFirefox = /firefox/i.test(getUAString());\n var isIE = /Trident/i.test(getUAString());\n\n if (isIE && isHTMLElement(element)) {\n // In IE 9, 10 and 11 fixed elements containing block is always established by the viewport\n var elementCss = getComputedStyle(element);\n\n if (elementCss.position === 'fixed') {\n return null;\n }\n }\n\n var currentNode = getParentNode(element);\n\n if (isShadowRoot(currentNode)) {\n currentNode = currentNode.host;\n }\n\n while (isHTMLElement(currentNode) && ['html', 'body'].indexOf(getNodeName(currentNode)) < 0) {\n var css = getComputedStyle(currentNode); // This is non-exhaustive but covers the most common CSS properties that\n // create a containing block.\n // https://developer.mozilla.org/en-US/docs/Web/CSS/Containing_block#identifying_the_containing_block\n\n if (css.transform !== 'none' || css.perspective !== 'none' || css.contain === 'paint' || ['transform', 'perspective'].indexOf(css.willChange) !== -1 || isFirefox && css.willChange === 'filter' || isFirefox && css.filter && css.filter !== 'none') {\n return currentNode;\n } else {\n currentNode = currentNode.parentNode;\n }\n }\n\n return null;\n} // Gets the closest ancestor positioned element. Handles some edge cases,\n// such as table ancestors and cross browser bugs.\n\n\nexport default function getOffsetParent(element) {\n var window = getWindow(element);\n var offsetParent = getTrueOffsetParent(element);\n\n while (offsetParent && isTableElement(offsetParent) && getComputedStyle(offsetParent).position === 'static') {\n offsetParent = getTrueOffsetParent(offsetParent);\n }\n\n if (offsetParent && (getNodeName(offsetParent) === 'html' || getNodeName(offsetParent) === 'body' && getComputedStyle(offsetParent).position === 'static')) {\n return window;\n }\n\n return offsetParent || getContainingBlock(element) || window;\n}","export default function getMainAxisFromPlacement(placement) {\n return ['top', 'bottom'].indexOf(placement) >= 0 ? 'x' : 'y';\n}","import { max as mathMax, min as mathMin } from \"./math.js\";\nexport function within(min, value, max) {\n return mathMax(min, mathMin(value, max));\n}\nexport function withinMaxClamp(min, value, max) {\n var v = within(min, value, max);\n return v > max ? max : v;\n}","import getFreshSideObject from \"./getFreshSideObject.js\";\nexport default function mergePaddingObject(paddingObject) {\n return Object.assign({}, getFreshSideObject(), paddingObject);\n}","export default function getFreshSideObject() {\n return {\n top: 0,\n right: 0,\n bottom: 0,\n left: 0\n };\n}","export default function expandToHashMap(value, keys) {\n return keys.reduce(function (hashMap, key) {\n hashMap[key] = value;\n return hashMap;\n }, {});\n}","import getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getLayoutRect from \"../dom-utils/getLayoutRect.js\";\nimport contains from \"../dom-utils/contains.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport getMainAxisFromPlacement from \"../utils/getMainAxisFromPlacement.js\";\nimport { within } from \"../utils/within.js\";\nimport mergePaddingObject from \"../utils/mergePaddingObject.js\";\nimport expandToHashMap from \"../utils/expandToHashMap.js\";\nimport { left, right, basePlacements, top, bottom } from \"../enums.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar toPaddingObject = function toPaddingObject(padding, state) {\n padding = typeof padding === 'function' ? padding(Object.assign({}, state.rects, {\n placement: state.placement\n })) : padding;\n return mergePaddingObject(typeof padding !== 'number' ? padding : expandToHashMap(padding, basePlacements));\n};\n\nfunction arrow(_ref) {\n var _state$modifiersData$;\n\n var state = _ref.state,\n name = _ref.name,\n options = _ref.options;\n var arrowElement = state.elements.arrow;\n var popperOffsets = state.modifiersData.popperOffsets;\n var basePlacement = getBasePlacement(state.placement);\n var axis = getMainAxisFromPlacement(basePlacement);\n var isVertical = [left, right].indexOf(basePlacement) >= 0;\n var len = isVertical ? 'height' : 'width';\n\n if (!arrowElement || !popperOffsets) {\n return;\n }\n\n var paddingObject = toPaddingObject(options.padding, state);\n var arrowRect = getLayoutRect(arrowElement);\n var minProp = axis === 'y' ? top : left;\n var maxProp = axis === 'y' ? bottom : right;\n var endDiff = state.rects.reference[len] + state.rects.reference[axis] - popperOffsets[axis] - state.rects.popper[len];\n var startDiff = popperOffsets[axis] - state.rects.reference[axis];\n var arrowOffsetParent = getOffsetParent(arrowElement);\n var clientSize = arrowOffsetParent ? axis === 'y' ? arrowOffsetParent.clientHeight || 0 : arrowOffsetParent.clientWidth || 0 : 0;\n var centerToReference = endDiff / 2 - startDiff / 2; // Make sure the arrow doesn't overflow the popper if the center point is\n // outside of the popper bounds\n\n var min = paddingObject[minProp];\n var max = clientSize - arrowRect[len] - paddingObject[maxProp];\n var center = clientSize / 2 - arrowRect[len] / 2 + centerToReference;\n var offset = within(min, center, max); // Prevents breaking syntax highlighting...\n\n var axisProp = axis;\n state.modifiersData[name] = (_state$modifiersData$ = {}, _state$modifiersData$[axisProp] = offset, _state$modifiersData$.centerOffset = offset - center, _state$modifiersData$);\n}\n\nfunction effect(_ref2) {\n var state = _ref2.state,\n options = _ref2.options;\n var _options$element = options.element,\n arrowElement = _options$element === void 0 ? '[data-popper-arrow]' : _options$element;\n\n if (arrowElement == null) {\n return;\n } // CSS selector\n\n\n if (typeof arrowElement === 'string') {\n arrowElement = state.elements.popper.querySelector(arrowElement);\n\n if (!arrowElement) {\n return;\n }\n }\n\n if (!contains(state.elements.popper, arrowElement)) {\n return;\n }\n\n state.elements.arrow = arrowElement;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'arrow',\n enabled: true,\n phase: 'main',\n fn: arrow,\n effect: effect,\n requires: ['popperOffsets'],\n requiresIfExists: ['preventOverflow']\n};","export default function getVariation(placement) {\n return placement.split('-')[1];\n}","import { top, left, right, bottom, end } from \"../enums.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport getWindow from \"../dom-utils/getWindow.js\";\nimport getDocumentElement from \"../dom-utils/getDocumentElement.js\";\nimport getComputedStyle from \"../dom-utils/getComputedStyle.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getVariation from \"../utils/getVariation.js\";\nimport { round } from \"../utils/math.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar unsetSides = {\n top: 'auto',\n right: 'auto',\n bottom: 'auto',\n left: 'auto'\n}; // Round the offsets to the nearest suitable subpixel based on the DPR.\n// Zooming can change the DPR, but it seems to report a value that will\n// cleanly divide the values into the appropriate subpixels.\n\nfunction roundOffsetsByDPR(_ref, win) {\n var x = _ref.x,\n y = _ref.y;\n var dpr = win.devicePixelRatio || 1;\n return {\n x: round(x * dpr) / dpr || 0,\n y: round(y * dpr) / dpr || 0\n };\n}\n\nexport function mapToStyles(_ref2) {\n var _Object$assign2;\n\n var popper = _ref2.popper,\n popperRect = _ref2.popperRect,\n placement = _ref2.placement,\n variation = _ref2.variation,\n offsets = _ref2.offsets,\n position = _ref2.position,\n gpuAcceleration = _ref2.gpuAcceleration,\n adaptive = _ref2.adaptive,\n roundOffsets = _ref2.roundOffsets,\n isFixed = _ref2.isFixed;\n var _offsets$x = offsets.x,\n x = _offsets$x === void 0 ? 0 : _offsets$x,\n _offsets$y = offsets.y,\n y = _offsets$y === void 0 ? 0 : _offsets$y;\n\n var _ref3 = typeof roundOffsets === 'function' ? roundOffsets({\n x: x,\n y: y\n }) : {\n x: x,\n y: y\n };\n\n x = _ref3.x;\n y = _ref3.y;\n var hasX = offsets.hasOwnProperty('x');\n var hasY = offsets.hasOwnProperty('y');\n var sideX = left;\n var sideY = top;\n var win = window;\n\n if (adaptive) {\n var offsetParent = getOffsetParent(popper);\n var heightProp = 'clientHeight';\n var widthProp = 'clientWidth';\n\n if (offsetParent === getWindow(popper)) {\n offsetParent = getDocumentElement(popper);\n\n if (getComputedStyle(offsetParent).position !== 'static' && position === 'absolute') {\n heightProp = 'scrollHeight';\n widthProp = 'scrollWidth';\n }\n } // $FlowFixMe[incompatible-cast]: force type refinement, we compare offsetParent with window above, but Flow doesn't detect it\n\n\n offsetParent = offsetParent;\n\n if (placement === top || (placement === left || placement === right) && variation === end) {\n sideY = bottom;\n var offsetY = isFixed && offsetParent === win && win.visualViewport ? win.visualViewport.height : // $FlowFixMe[prop-missing]\n offsetParent[heightProp];\n y -= offsetY - popperRect.height;\n y *= gpuAcceleration ? 1 : -1;\n }\n\n if (placement === left || (placement === top || placement === bottom) && variation === end) {\n sideX = right;\n var offsetX = isFixed && offsetParent === win && win.visualViewport ? win.visualViewport.width : // $FlowFixMe[prop-missing]\n offsetParent[widthProp];\n x -= offsetX - popperRect.width;\n x *= gpuAcceleration ? 1 : -1;\n }\n }\n\n var commonStyles = Object.assign({\n position: position\n }, adaptive && unsetSides);\n\n var _ref4 = roundOffsets === true ? roundOffsetsByDPR({\n x: x,\n y: y\n }, getWindow(popper)) : {\n x: x,\n y: y\n };\n\n x = _ref4.x;\n y = _ref4.y;\n\n if (gpuAcceleration) {\n var _Object$assign;\n\n return Object.assign({}, commonStyles, (_Object$assign = {}, _Object$assign[sideY] = hasY ? '0' : '', _Object$assign[sideX] = hasX ? '0' : '', _Object$assign.transform = (win.devicePixelRatio || 1) <= 1 ? \"translate(\" + x + \"px, \" + y + \"px)\" : \"translate3d(\" + x + \"px, \" + y + \"px, 0)\", _Object$assign));\n }\n\n return Object.assign({}, commonStyles, (_Object$assign2 = {}, _Object$assign2[sideY] = hasY ? y + \"px\" : '', _Object$assign2[sideX] = hasX ? x + \"px\" : '', _Object$assign2.transform = '', _Object$assign2));\n}\n\nfunction computeStyles(_ref5) {\n var state = _ref5.state,\n options = _ref5.options;\n var _options$gpuAccelerat = options.gpuAcceleration,\n gpuAcceleration = _options$gpuAccelerat === void 0 ? true : _options$gpuAccelerat,\n _options$adaptive = options.adaptive,\n adaptive = _options$adaptive === void 0 ? true : _options$adaptive,\n _options$roundOffsets = options.roundOffsets,\n roundOffsets = _options$roundOffsets === void 0 ? true : _options$roundOffsets;\n var commonStyles = {\n placement: getBasePlacement(state.placement),\n variation: getVariation(state.placement),\n popper: state.elements.popper,\n popperRect: state.rects.popper,\n gpuAcceleration: gpuAcceleration,\n isFixed: state.options.strategy === 'fixed'\n };\n\n if (state.modifiersData.popperOffsets != null) {\n state.styles.popper = Object.assign({}, state.styles.popper, mapToStyles(Object.assign({}, commonStyles, {\n offsets: state.modifiersData.popperOffsets,\n position: state.options.strategy,\n adaptive: adaptive,\n roundOffsets: roundOffsets\n })));\n }\n\n if (state.modifiersData.arrow != null) {\n state.styles.arrow = Object.assign({}, state.styles.arrow, mapToStyles(Object.assign({}, commonStyles, {\n offsets: state.modifiersData.arrow,\n position: 'absolute',\n adaptive: false,\n roundOffsets: roundOffsets\n })));\n }\n\n state.attributes.popper = Object.assign({}, state.attributes.popper, {\n 'data-popper-placement': state.placement\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'computeStyles',\n enabled: true,\n phase: 'beforeWrite',\n fn: computeStyles,\n data: {}\n};","import getWindow from \"../dom-utils/getWindow.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar passive = {\n passive: true\n};\n\nfunction effect(_ref) {\n var state = _ref.state,\n instance = _ref.instance,\n options = _ref.options;\n var _options$scroll = options.scroll,\n scroll = _options$scroll === void 0 ? true : _options$scroll,\n _options$resize = options.resize,\n resize = _options$resize === void 0 ? true : _options$resize;\n var window = getWindow(state.elements.popper);\n var scrollParents = [].concat(state.scrollParents.reference, state.scrollParents.popper);\n\n if (scroll) {\n scrollParents.forEach(function (scrollParent) {\n scrollParent.addEventListener('scroll', instance.update, passive);\n });\n }\n\n if (resize) {\n window.addEventListener('resize', instance.update, passive);\n }\n\n return function () {\n if (scroll) {\n scrollParents.forEach(function (scrollParent) {\n scrollParent.removeEventListener('scroll', instance.update, passive);\n });\n }\n\n if (resize) {\n window.removeEventListener('resize', instance.update, passive);\n }\n };\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'eventListeners',\n enabled: true,\n phase: 'write',\n fn: function fn() {},\n effect: effect,\n data: {}\n};","var hash = {\n left: 'right',\n right: 'left',\n bottom: 'top',\n top: 'bottom'\n};\nexport default function getOppositePlacement(placement) {\n return placement.replace(/left|right|bottom|top/g, function (matched) {\n return hash[matched];\n });\n}","var hash = {\n start: 'end',\n end: 'start'\n};\nexport default function getOppositeVariationPlacement(placement) {\n return placement.replace(/start|end/g, function (matched) {\n return hash[matched];\n });\n}","import getWindow from \"./getWindow.js\";\nexport default function getWindowScroll(node) {\n var win = getWindow(node);\n var scrollLeft = win.pageXOffset;\n var scrollTop = win.pageYOffset;\n return {\n scrollLeft: scrollLeft,\n scrollTop: scrollTop\n };\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getWindowScroll from \"./getWindowScroll.js\";\nexport default function getWindowScrollBarX(element) {\n // If has a CSS width greater than the viewport, then this will be\n // incorrect for RTL.\n // Popper 1 is broken in this case and never had a bug report so let's assume\n // it's not an issue. I don't think anyone ever specifies width on \n // anyway.\n // Browsers where the left scrollbar doesn't cause an issue report `0` for\n // this (e.g. Edge 2019, IE11, Safari)\n return getBoundingClientRect(getDocumentElement(element)).left + getWindowScroll(element).scrollLeft;\n}","import getComputedStyle from \"./getComputedStyle.js\";\nexport default function isScrollParent(element) {\n // Firefox wants us to check `-x` and `-y` variations as well\n var _getComputedStyle = getComputedStyle(element),\n overflow = _getComputedStyle.overflow,\n overflowX = _getComputedStyle.overflowX,\n overflowY = _getComputedStyle.overflowY;\n\n return /auto|scroll|overlay|hidden/.test(overflow + overflowY + overflowX);\n}","import getParentNode from \"./getParentNode.js\";\nimport isScrollParent from \"./isScrollParent.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nexport default function getScrollParent(node) {\n if (['html', 'body', '#document'].indexOf(getNodeName(node)) >= 0) {\n // $FlowFixMe[incompatible-return]: assume body is always available\n return node.ownerDocument.body;\n }\n\n if (isHTMLElement(node) && isScrollParent(node)) {\n return node;\n }\n\n return getScrollParent(getParentNode(node));\n}","import getScrollParent from \"./getScrollParent.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport getWindow from \"./getWindow.js\";\nimport isScrollParent from \"./isScrollParent.js\";\n/*\ngiven a DOM element, return the list of all scroll parents, up the list of ancesors\nuntil we get to the top window object. This list is what we attach scroll listeners\nto, because if any of these parent elements scroll, we'll need to re-calculate the\nreference element's position.\n*/\n\nexport default function listScrollParents(element, list) {\n var _element$ownerDocumen;\n\n if (list === void 0) {\n list = [];\n }\n\n var scrollParent = getScrollParent(element);\n var isBody = scrollParent === ((_element$ownerDocumen = element.ownerDocument) == null ? void 0 : _element$ownerDocumen.body);\n var win = getWindow(scrollParent);\n var target = isBody ? [win].concat(win.visualViewport || [], isScrollParent(scrollParent) ? scrollParent : []) : scrollParent;\n var updatedList = list.concat(target);\n return isBody ? updatedList : // $FlowFixMe[incompatible-call]: isBody tells us target will be an HTMLElement here\n updatedList.concat(listScrollParents(getParentNode(target)));\n}","export default function rectToClientRect(rect) {\n return Object.assign({}, rect, {\n left: rect.x,\n top: rect.y,\n right: rect.x + rect.width,\n bottom: rect.y + rect.height\n });\n}","import { viewport } from \"../enums.js\";\nimport getViewportRect from \"./getViewportRect.js\";\nimport getDocumentRect from \"./getDocumentRect.js\";\nimport listScrollParents from \"./listScrollParents.js\";\nimport getOffsetParent from \"./getOffsetParent.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport { isElement, isHTMLElement } from \"./instanceOf.js\";\nimport getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport contains from \"./contains.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport rectToClientRect from \"../utils/rectToClientRect.js\";\nimport { max, min } from \"../utils/math.js\";\n\nfunction getInnerBoundingClientRect(element, strategy) {\n var rect = getBoundingClientRect(element, false, strategy === 'fixed');\n rect.top = rect.top + element.clientTop;\n rect.left = rect.left + element.clientLeft;\n rect.bottom = rect.top + element.clientHeight;\n rect.right = rect.left + element.clientWidth;\n rect.width = element.clientWidth;\n rect.height = element.clientHeight;\n rect.x = rect.left;\n rect.y = rect.top;\n return rect;\n}\n\nfunction getClientRectFromMixedType(element, clippingParent, strategy) {\n return clippingParent === viewport ? rectToClientRect(getViewportRect(element, strategy)) : isElement(clippingParent) ? getInnerBoundingClientRect(clippingParent, strategy) : rectToClientRect(getDocumentRect(getDocumentElement(element)));\n} // A \"clipping parent\" is an overflowable container with the characteristic of\n// clipping (or hiding) overflowing elements with a position different from\n// `initial`\n\n\nfunction getClippingParents(element) {\n var clippingParents = listScrollParents(getParentNode(element));\n var canEscapeClipping = ['absolute', 'fixed'].indexOf(getComputedStyle(element).position) >= 0;\n var clipperElement = canEscapeClipping && isHTMLElement(element) ? getOffsetParent(element) : element;\n\n if (!isElement(clipperElement)) {\n return [];\n } // $FlowFixMe[incompatible-return]: https://github.com/facebook/flow/issues/1414\n\n\n return clippingParents.filter(function (clippingParent) {\n return isElement(clippingParent) && contains(clippingParent, clipperElement) && getNodeName(clippingParent) !== 'body';\n });\n} // Gets the maximum area that the element is visible in due to any number of\n// clipping parents\n\n\nexport default function getClippingRect(element, boundary, rootBoundary, strategy) {\n var mainClippingParents = boundary === 'clippingParents' ? getClippingParents(element) : [].concat(boundary);\n var clippingParents = [].concat(mainClippingParents, [rootBoundary]);\n var firstClippingParent = clippingParents[0];\n var clippingRect = clippingParents.reduce(function (accRect, clippingParent) {\n var rect = getClientRectFromMixedType(element, clippingParent, strategy);\n accRect.top = max(rect.top, accRect.top);\n accRect.right = min(rect.right, accRect.right);\n accRect.bottom = min(rect.bottom, accRect.bottom);\n accRect.left = max(rect.left, accRect.left);\n return accRect;\n }, getClientRectFromMixedType(element, firstClippingParent, strategy));\n clippingRect.width = clippingRect.right - clippingRect.left;\n clippingRect.height = clippingRect.bottom - clippingRect.top;\n clippingRect.x = clippingRect.left;\n clippingRect.y = clippingRect.top;\n return clippingRect;\n}","import getWindow from \"./getWindow.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport isLayoutViewport from \"./isLayoutViewport.js\";\nexport default function getViewportRect(element, strategy) {\n var win = getWindow(element);\n var html = getDocumentElement(element);\n var visualViewport = win.visualViewport;\n var width = html.clientWidth;\n var height = html.clientHeight;\n var x = 0;\n var y = 0;\n\n if (visualViewport) {\n width = visualViewport.width;\n height = visualViewport.height;\n var layoutViewport = isLayoutViewport();\n\n if (layoutViewport || !layoutViewport && strategy === 'fixed') {\n x = visualViewport.offsetLeft;\n y = visualViewport.offsetTop;\n }\n }\n\n return {\n width: width,\n height: height,\n x: x + getWindowScrollBarX(element),\n y: y\n };\n}","import getDocumentElement from \"./getDocumentElement.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport getWindowScroll from \"./getWindowScroll.js\";\nimport { max } from \"../utils/math.js\"; // Gets the entire size of the scrollable document area, even extending outside\n// of the `` and `` rect bounds if horizontally scrollable\n\nexport default function getDocumentRect(element) {\n var _element$ownerDocumen;\n\n var html = getDocumentElement(element);\n var winScroll = getWindowScroll(element);\n var body = (_element$ownerDocumen = element.ownerDocument) == null ? void 0 : _element$ownerDocumen.body;\n var width = max(html.scrollWidth, html.clientWidth, body ? body.scrollWidth : 0, body ? body.clientWidth : 0);\n var height = max(html.scrollHeight, html.clientHeight, body ? body.scrollHeight : 0, body ? body.clientHeight : 0);\n var x = -winScroll.scrollLeft + getWindowScrollBarX(element);\n var y = -winScroll.scrollTop;\n\n if (getComputedStyle(body || html).direction === 'rtl') {\n x += max(html.clientWidth, body ? body.clientWidth : 0) - width;\n }\n\n return {\n width: width,\n height: height,\n x: x,\n y: y\n };\n}","import getBasePlacement from \"./getBasePlacement.js\";\nimport getVariation from \"./getVariation.js\";\nimport getMainAxisFromPlacement from \"./getMainAxisFromPlacement.js\";\nimport { top, right, bottom, left, start, end } from \"../enums.js\";\nexport default function computeOffsets(_ref) {\n var reference = _ref.reference,\n element = _ref.element,\n placement = _ref.placement;\n var basePlacement = placement ? getBasePlacement(placement) : null;\n var variation = placement ? getVariation(placement) : null;\n var commonX = reference.x + reference.width / 2 - element.width / 2;\n var commonY = reference.y + reference.height / 2 - element.height / 2;\n var offsets;\n\n switch (basePlacement) {\n case top:\n offsets = {\n x: commonX,\n y: reference.y - element.height\n };\n break;\n\n case bottom:\n offsets = {\n x: commonX,\n y: reference.y + reference.height\n };\n break;\n\n case right:\n offsets = {\n x: reference.x + reference.width,\n y: commonY\n };\n break;\n\n case left:\n offsets = {\n x: reference.x - element.width,\n y: commonY\n };\n break;\n\n default:\n offsets = {\n x: reference.x,\n y: reference.y\n };\n }\n\n var mainAxis = basePlacement ? getMainAxisFromPlacement(basePlacement) : null;\n\n if (mainAxis != null) {\n var len = mainAxis === 'y' ? 'height' : 'width';\n\n switch (variation) {\n case start:\n offsets[mainAxis] = offsets[mainAxis] - (reference[len] / 2 - element[len] / 2);\n break;\n\n case end:\n offsets[mainAxis] = offsets[mainAxis] + (reference[len] / 2 - element[len] / 2);\n break;\n\n default:\n }\n }\n\n return offsets;\n}","import getClippingRect from \"../dom-utils/getClippingRect.js\";\nimport getDocumentElement from \"../dom-utils/getDocumentElement.js\";\nimport getBoundingClientRect from \"../dom-utils/getBoundingClientRect.js\";\nimport computeOffsets from \"./computeOffsets.js\";\nimport rectToClientRect from \"./rectToClientRect.js\";\nimport { clippingParents, reference, popper, bottom, top, right, basePlacements, viewport } from \"../enums.js\";\nimport { isElement } from \"../dom-utils/instanceOf.js\";\nimport mergePaddingObject from \"./mergePaddingObject.js\";\nimport expandToHashMap from \"./expandToHashMap.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport default function detectOverflow(state, options) {\n if (options === void 0) {\n options = {};\n }\n\n var _options = options,\n _options$placement = _options.placement,\n placement = _options$placement === void 0 ? state.placement : _options$placement,\n _options$strategy = _options.strategy,\n strategy = _options$strategy === void 0 ? state.strategy : _options$strategy,\n _options$boundary = _options.boundary,\n boundary = _options$boundary === void 0 ? clippingParents : _options$boundary,\n _options$rootBoundary = _options.rootBoundary,\n rootBoundary = _options$rootBoundary === void 0 ? viewport : _options$rootBoundary,\n _options$elementConte = _options.elementContext,\n elementContext = _options$elementConte === void 0 ? popper : _options$elementConte,\n _options$altBoundary = _options.altBoundary,\n altBoundary = _options$altBoundary === void 0 ? false : _options$altBoundary,\n _options$padding = _options.padding,\n padding = _options$padding === void 0 ? 0 : _options$padding;\n var paddingObject = mergePaddingObject(typeof padding !== 'number' ? padding : expandToHashMap(padding, basePlacements));\n var altContext = elementContext === popper ? reference : popper;\n var popperRect = state.rects.popper;\n var element = state.elements[altBoundary ? altContext : elementContext];\n var clippingClientRect = getClippingRect(isElement(element) ? element : element.contextElement || getDocumentElement(state.elements.popper), boundary, rootBoundary, strategy);\n var referenceClientRect = getBoundingClientRect(state.elements.reference);\n var popperOffsets = computeOffsets({\n reference: referenceClientRect,\n element: popperRect,\n strategy: 'absolute',\n placement: placement\n });\n var popperClientRect = rectToClientRect(Object.assign({}, popperRect, popperOffsets));\n var elementClientRect = elementContext === popper ? popperClientRect : referenceClientRect; // positive = overflowing the clipping rect\n // 0 or negative = within the clipping rect\n\n var overflowOffsets = {\n top: clippingClientRect.top - elementClientRect.top + paddingObject.top,\n bottom: elementClientRect.bottom - clippingClientRect.bottom + paddingObject.bottom,\n left: clippingClientRect.left - elementClientRect.left + paddingObject.left,\n right: elementClientRect.right - clippingClientRect.right + paddingObject.right\n };\n var offsetData = state.modifiersData.offset; // Offsets can be applied only to the popper element\n\n if (elementContext === popper && offsetData) {\n var offset = offsetData[placement];\n Object.keys(overflowOffsets).forEach(function (key) {\n var multiply = [right, bottom].indexOf(key) >= 0 ? 1 : -1;\n var axis = [top, bottom].indexOf(key) >= 0 ? 'y' : 'x';\n overflowOffsets[key] += offset[axis] * multiply;\n });\n }\n\n return overflowOffsets;\n}","import getOppositePlacement from \"../utils/getOppositePlacement.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getOppositeVariationPlacement from \"../utils/getOppositeVariationPlacement.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\nimport computeAutoPlacement from \"../utils/computeAutoPlacement.js\";\nimport { bottom, top, start, right, left, auto } from \"../enums.js\";\nimport getVariation from \"../utils/getVariation.js\"; // eslint-disable-next-line import/no-unused-modules\n\nfunction getExpandedFallbackPlacements(placement) {\n if (getBasePlacement(placement) === auto) {\n return [];\n }\n\n var oppositePlacement = getOppositePlacement(placement);\n return [getOppositeVariationPlacement(placement), oppositePlacement, getOppositeVariationPlacement(oppositePlacement)];\n}\n\nfunction flip(_ref) {\n var state = _ref.state,\n options = _ref.options,\n name = _ref.name;\n\n if (state.modifiersData[name]._skip) {\n return;\n }\n\n var _options$mainAxis = options.mainAxis,\n checkMainAxis = _options$mainAxis === void 0 ? true : _options$mainAxis,\n _options$altAxis = options.altAxis,\n checkAltAxis = _options$altAxis === void 0 ? true : _options$altAxis,\n specifiedFallbackPlacements = options.fallbackPlacements,\n padding = options.padding,\n boundary = options.boundary,\n rootBoundary = options.rootBoundary,\n altBoundary = options.altBoundary,\n _options$flipVariatio = options.flipVariations,\n flipVariations = _options$flipVariatio === void 0 ? true : _options$flipVariatio,\n allowedAutoPlacements = options.allowedAutoPlacements;\n var preferredPlacement = state.options.placement;\n var basePlacement = getBasePlacement(preferredPlacement);\n var isBasePlacement = basePlacement === preferredPlacement;\n var fallbackPlacements = specifiedFallbackPlacements || (isBasePlacement || !flipVariations ? [getOppositePlacement(preferredPlacement)] : getExpandedFallbackPlacements(preferredPlacement));\n var placements = [preferredPlacement].concat(fallbackPlacements).reduce(function (acc, placement) {\n return acc.concat(getBasePlacement(placement) === auto ? computeAutoPlacement(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding,\n flipVariations: flipVariations,\n allowedAutoPlacements: allowedAutoPlacements\n }) : placement);\n }, []);\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var checksMap = new Map();\n var makeFallbackChecks = true;\n var firstFittingPlacement = placements[0];\n\n for (var i = 0; i < placements.length; i++) {\n var placement = placements[i];\n\n var _basePlacement = getBasePlacement(placement);\n\n var isStartVariation = getVariation(placement) === start;\n var isVertical = [top, bottom].indexOf(_basePlacement) >= 0;\n var len = isVertical ? 'width' : 'height';\n var overflow = detectOverflow(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n altBoundary: altBoundary,\n padding: padding\n });\n var mainVariationSide = isVertical ? isStartVariation ? right : left : isStartVariation ? bottom : top;\n\n if (referenceRect[len] > popperRect[len]) {\n mainVariationSide = getOppositePlacement(mainVariationSide);\n }\n\n var altVariationSide = getOppositePlacement(mainVariationSide);\n var checks = [];\n\n if (checkMainAxis) {\n checks.push(overflow[_basePlacement] <= 0);\n }\n\n if (checkAltAxis) {\n checks.push(overflow[mainVariationSide] <= 0, overflow[altVariationSide] <= 0);\n }\n\n if (checks.every(function (check) {\n return check;\n })) {\n firstFittingPlacement = placement;\n makeFallbackChecks = false;\n break;\n }\n\n checksMap.set(placement, checks);\n }\n\n if (makeFallbackChecks) {\n // `2` may be desired in some cases – research later\n var numberOfChecks = flipVariations ? 3 : 1;\n\n var _loop = function _loop(_i) {\n var fittingPlacement = placements.find(function (placement) {\n var checks = checksMap.get(placement);\n\n if (checks) {\n return checks.slice(0, _i).every(function (check) {\n return check;\n });\n }\n });\n\n if (fittingPlacement) {\n firstFittingPlacement = fittingPlacement;\n return \"break\";\n }\n };\n\n for (var _i = numberOfChecks; _i > 0; _i--) {\n var _ret = _loop(_i);\n\n if (_ret === \"break\") break;\n }\n }\n\n if (state.placement !== firstFittingPlacement) {\n state.modifiersData[name]._skip = true;\n state.placement = firstFittingPlacement;\n state.reset = true;\n }\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'flip',\n enabled: true,\n phase: 'main',\n fn: flip,\n requiresIfExists: ['offset'],\n data: {\n _skip: false\n }\n};","import getVariation from \"./getVariation.js\";\nimport { variationPlacements, basePlacements, placements as allPlacements } from \"../enums.js\";\nimport detectOverflow from \"./detectOverflow.js\";\nimport getBasePlacement from \"./getBasePlacement.js\";\nexport default function computeAutoPlacement(state, options) {\n if (options === void 0) {\n options = {};\n }\n\n var _options = options,\n placement = _options.placement,\n boundary = _options.boundary,\n rootBoundary = _options.rootBoundary,\n padding = _options.padding,\n flipVariations = _options.flipVariations,\n _options$allowedAutoP = _options.allowedAutoPlacements,\n allowedAutoPlacements = _options$allowedAutoP === void 0 ? allPlacements : _options$allowedAutoP;\n var variation = getVariation(placement);\n var placements = variation ? flipVariations ? variationPlacements : variationPlacements.filter(function (placement) {\n return getVariation(placement) === variation;\n }) : basePlacements;\n var allowedPlacements = placements.filter(function (placement) {\n return allowedAutoPlacements.indexOf(placement) >= 0;\n });\n\n if (allowedPlacements.length === 0) {\n allowedPlacements = placements;\n } // $FlowFixMe[incompatible-type]: Flow seems to have problems with two array unions...\n\n\n var overflows = allowedPlacements.reduce(function (acc, placement) {\n acc[placement] = detectOverflow(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding\n })[getBasePlacement(placement)];\n return acc;\n }, {});\n return Object.keys(overflows).sort(function (a, b) {\n return overflows[a] - overflows[b];\n });\n}","import { top, bottom, left, right } from \"../enums.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\n\nfunction getSideOffsets(overflow, rect, preventedOffsets) {\n if (preventedOffsets === void 0) {\n preventedOffsets = {\n x: 0,\n y: 0\n };\n }\n\n return {\n top: overflow.top - rect.height - preventedOffsets.y,\n right: overflow.right - rect.width + preventedOffsets.x,\n bottom: overflow.bottom - rect.height + preventedOffsets.y,\n left: overflow.left - rect.width - preventedOffsets.x\n };\n}\n\nfunction isAnySideFullyClipped(overflow) {\n return [top, right, bottom, left].some(function (side) {\n return overflow[side] >= 0;\n });\n}\n\nfunction hide(_ref) {\n var state = _ref.state,\n name = _ref.name;\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var preventedOffsets = state.modifiersData.preventOverflow;\n var referenceOverflow = detectOverflow(state, {\n elementContext: 'reference'\n });\n var popperAltOverflow = detectOverflow(state, {\n altBoundary: true\n });\n var referenceClippingOffsets = getSideOffsets(referenceOverflow, referenceRect);\n var popperEscapeOffsets = getSideOffsets(popperAltOverflow, popperRect, preventedOffsets);\n var isReferenceHidden = isAnySideFullyClipped(referenceClippingOffsets);\n var hasPopperEscaped = isAnySideFullyClipped(popperEscapeOffsets);\n state.modifiersData[name] = {\n referenceClippingOffsets: referenceClippingOffsets,\n popperEscapeOffsets: popperEscapeOffsets,\n isReferenceHidden: isReferenceHidden,\n hasPopperEscaped: hasPopperEscaped\n };\n state.attributes.popper = Object.assign({}, state.attributes.popper, {\n 'data-popper-reference-hidden': isReferenceHidden,\n 'data-popper-escaped': hasPopperEscaped\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'hide',\n enabled: true,\n phase: 'main',\n requiresIfExists: ['preventOverflow'],\n fn: hide\n};","import getBasePlacement from \"../utils/getBasePlacement.js\";\nimport { top, left, right, placements } from \"../enums.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport function distanceAndSkiddingToXY(placement, rects, offset) {\n var basePlacement = getBasePlacement(placement);\n var invertDistance = [left, top].indexOf(basePlacement) >= 0 ? -1 : 1;\n\n var _ref = typeof offset === 'function' ? offset(Object.assign({}, rects, {\n placement: placement\n })) : offset,\n skidding = _ref[0],\n distance = _ref[1];\n\n skidding = skidding || 0;\n distance = (distance || 0) * invertDistance;\n return [left, right].indexOf(basePlacement) >= 0 ? {\n x: distance,\n y: skidding\n } : {\n x: skidding,\n y: distance\n };\n}\n\nfunction offset(_ref2) {\n var state = _ref2.state,\n options = _ref2.options,\n name = _ref2.name;\n var _options$offset = options.offset,\n offset = _options$offset === void 0 ? [0, 0] : _options$offset;\n var data = placements.reduce(function (acc, placement) {\n acc[placement] = distanceAndSkiddingToXY(placement, state.rects, offset);\n return acc;\n }, {});\n var _data$state$placement = data[state.placement],\n x = _data$state$placement.x,\n y = _data$state$placement.y;\n\n if (state.modifiersData.popperOffsets != null) {\n state.modifiersData.popperOffsets.x += x;\n state.modifiersData.popperOffsets.y += y;\n }\n\n state.modifiersData[name] = data;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'offset',\n enabled: true,\n phase: 'main',\n requires: ['popperOffsets'],\n fn: offset\n};","import computeOffsets from \"../utils/computeOffsets.js\";\n\nfunction popperOffsets(_ref) {\n var state = _ref.state,\n name = _ref.name;\n // Offsets are the actual position the popper needs to have to be\n // properly positioned near its reference element\n // This is the most basic placement, and will be adjusted by\n // the modifiers in the next step\n state.modifiersData[name] = computeOffsets({\n reference: state.rects.reference,\n element: state.rects.popper,\n strategy: 'absolute',\n placement: state.placement\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'popperOffsets',\n enabled: true,\n phase: 'read',\n fn: popperOffsets,\n data: {}\n};","import { top, left, right, bottom, start } from \"../enums.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getMainAxisFromPlacement from \"../utils/getMainAxisFromPlacement.js\";\nimport getAltAxis from \"../utils/getAltAxis.js\";\nimport { within, withinMaxClamp } from \"../utils/within.js\";\nimport getLayoutRect from \"../dom-utils/getLayoutRect.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\nimport getVariation from \"../utils/getVariation.js\";\nimport getFreshSideObject from \"../utils/getFreshSideObject.js\";\nimport { min as mathMin, max as mathMax } from \"../utils/math.js\";\n\nfunction preventOverflow(_ref) {\n var state = _ref.state,\n options = _ref.options,\n name = _ref.name;\n var _options$mainAxis = options.mainAxis,\n checkMainAxis = _options$mainAxis === void 0 ? true : _options$mainAxis,\n _options$altAxis = options.altAxis,\n checkAltAxis = _options$altAxis === void 0 ? false : _options$altAxis,\n boundary = options.boundary,\n rootBoundary = options.rootBoundary,\n altBoundary = options.altBoundary,\n padding = options.padding,\n _options$tether = options.tether,\n tether = _options$tether === void 0 ? true : _options$tether,\n _options$tetherOffset = options.tetherOffset,\n tetherOffset = _options$tetherOffset === void 0 ? 0 : _options$tetherOffset;\n var overflow = detectOverflow(state, {\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding,\n altBoundary: altBoundary\n });\n var basePlacement = getBasePlacement(state.placement);\n var variation = getVariation(state.placement);\n var isBasePlacement = !variation;\n var mainAxis = getMainAxisFromPlacement(basePlacement);\n var altAxis = getAltAxis(mainAxis);\n var popperOffsets = state.modifiersData.popperOffsets;\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var tetherOffsetValue = typeof tetherOffset === 'function' ? tetherOffset(Object.assign({}, state.rects, {\n placement: state.placement\n })) : tetherOffset;\n var normalizedTetherOffsetValue = typeof tetherOffsetValue === 'number' ? {\n mainAxis: tetherOffsetValue,\n altAxis: tetherOffsetValue\n } : Object.assign({\n mainAxis: 0,\n altAxis: 0\n }, tetherOffsetValue);\n var offsetModifierState = state.modifiersData.offset ? state.modifiersData.offset[state.placement] : null;\n var data = {\n x: 0,\n y: 0\n };\n\n if (!popperOffsets) {\n return;\n }\n\n if (checkMainAxis) {\n var _offsetModifierState$;\n\n var mainSide = mainAxis === 'y' ? top : left;\n var altSide = mainAxis === 'y' ? bottom : right;\n var len = mainAxis === 'y' ? 'height' : 'width';\n var offset = popperOffsets[mainAxis];\n var min = offset + overflow[mainSide];\n var max = offset - overflow[altSide];\n var additive = tether ? -popperRect[len] / 2 : 0;\n var minLen = variation === start ? referenceRect[len] : popperRect[len];\n var maxLen = variation === start ? -popperRect[len] : -referenceRect[len]; // We need to include the arrow in the calculation so the arrow doesn't go\n // outside the reference bounds\n\n var arrowElement = state.elements.arrow;\n var arrowRect = tether && arrowElement ? getLayoutRect(arrowElement) : {\n width: 0,\n height: 0\n };\n var arrowPaddingObject = state.modifiersData['arrow#persistent'] ? state.modifiersData['arrow#persistent'].padding : getFreshSideObject();\n var arrowPaddingMin = arrowPaddingObject[mainSide];\n var arrowPaddingMax = arrowPaddingObject[altSide]; // If the reference length is smaller than the arrow length, we don't want\n // to include its full size in the calculation. If the reference is small\n // and near the edge of a boundary, the popper can overflow even if the\n // reference is not overflowing as well (e.g. virtual elements with no\n // width or height)\n\n var arrowLen = within(0, referenceRect[len], arrowRect[len]);\n var minOffset = isBasePlacement ? referenceRect[len] / 2 - additive - arrowLen - arrowPaddingMin - normalizedTetherOffsetValue.mainAxis : minLen - arrowLen - arrowPaddingMin - normalizedTetherOffsetValue.mainAxis;\n var maxOffset = isBasePlacement ? -referenceRect[len] / 2 + additive + arrowLen + arrowPaddingMax + normalizedTetherOffsetValue.mainAxis : maxLen + arrowLen + arrowPaddingMax + normalizedTetherOffsetValue.mainAxis;\n var arrowOffsetParent = state.elements.arrow && getOffsetParent(state.elements.arrow);\n var clientOffset = arrowOffsetParent ? mainAxis === 'y' ? arrowOffsetParent.clientTop || 0 : arrowOffsetParent.clientLeft || 0 : 0;\n var offsetModifierValue = (_offsetModifierState$ = offsetModifierState == null ? void 0 : offsetModifierState[mainAxis]) != null ? _offsetModifierState$ : 0;\n var tetherMin = offset + minOffset - offsetModifierValue - clientOffset;\n var tetherMax = offset + maxOffset - offsetModifierValue;\n var preventedOffset = within(tether ? mathMin(min, tetherMin) : min, offset, tether ? mathMax(max, tetherMax) : max);\n popperOffsets[mainAxis] = preventedOffset;\n data[mainAxis] = preventedOffset - offset;\n }\n\n if (checkAltAxis) {\n var _offsetModifierState$2;\n\n var _mainSide = mainAxis === 'x' ? top : left;\n\n var _altSide = mainAxis === 'x' ? bottom : right;\n\n var _offset = popperOffsets[altAxis];\n\n var _len = altAxis === 'y' ? 'height' : 'width';\n\n var _min = _offset + overflow[_mainSide];\n\n var _max = _offset - overflow[_altSide];\n\n var isOriginSide = [top, left].indexOf(basePlacement) !== -1;\n\n var _offsetModifierValue = (_offsetModifierState$2 = offsetModifierState == null ? void 0 : offsetModifierState[altAxis]) != null ? _offsetModifierState$2 : 0;\n\n var _tetherMin = isOriginSide ? _min : _offset - referenceRect[_len] - popperRect[_len] - _offsetModifierValue + normalizedTetherOffsetValue.altAxis;\n\n var _tetherMax = isOriginSide ? _offset + referenceRect[_len] + popperRect[_len] - _offsetModifierValue - normalizedTetherOffsetValue.altAxis : _max;\n\n var _preventedOffset = tether && isOriginSide ? withinMaxClamp(_tetherMin, _offset, _tetherMax) : within(tether ? _tetherMin : _min, _offset, tether ? _tetherMax : _max);\n\n popperOffsets[altAxis] = _preventedOffset;\n data[altAxis] = _preventedOffset - _offset;\n }\n\n state.modifiersData[name] = data;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'preventOverflow',\n enabled: true,\n phase: 'main',\n fn: preventOverflow,\n requiresIfExists: ['offset']\n};","export default function getAltAxis(axis) {\n return axis === 'x' ? 'y' : 'x';\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getNodeScroll from \"./getNodeScroll.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport isScrollParent from \"./isScrollParent.js\";\nimport { round } from \"../utils/math.js\";\n\nfunction isElementScaled(element) {\n var rect = element.getBoundingClientRect();\n var scaleX = round(rect.width) / element.offsetWidth || 1;\n var scaleY = round(rect.height) / element.offsetHeight || 1;\n return scaleX !== 1 || scaleY !== 1;\n} // Returns the composite rect of an element relative to its offsetParent.\n// Composite means it takes into account transforms as well as layout.\n\n\nexport default function getCompositeRect(elementOrVirtualElement, offsetParent, isFixed) {\n if (isFixed === void 0) {\n isFixed = false;\n }\n\n var isOffsetParentAnElement = isHTMLElement(offsetParent);\n var offsetParentIsScaled = isHTMLElement(offsetParent) && isElementScaled(offsetParent);\n var documentElement = getDocumentElement(offsetParent);\n var rect = getBoundingClientRect(elementOrVirtualElement, offsetParentIsScaled, isFixed);\n var scroll = {\n scrollLeft: 0,\n scrollTop: 0\n };\n var offsets = {\n x: 0,\n y: 0\n };\n\n if (isOffsetParentAnElement || !isOffsetParentAnElement && !isFixed) {\n if (getNodeName(offsetParent) !== 'body' || // https://github.com/popperjs/popper-core/issues/1078\n isScrollParent(documentElement)) {\n scroll = getNodeScroll(offsetParent);\n }\n\n if (isHTMLElement(offsetParent)) {\n offsets = getBoundingClientRect(offsetParent, true);\n offsets.x += offsetParent.clientLeft;\n offsets.y += offsetParent.clientTop;\n } else if (documentElement) {\n offsets.x = getWindowScrollBarX(documentElement);\n }\n }\n\n return {\n x: rect.left + scroll.scrollLeft - offsets.x,\n y: rect.top + scroll.scrollTop - offsets.y,\n width: rect.width,\n height: rect.height\n };\n}","import getWindowScroll from \"./getWindowScroll.js\";\nimport getWindow from \"./getWindow.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nimport getHTMLElementScroll from \"./getHTMLElementScroll.js\";\nexport default function getNodeScroll(node) {\n if (node === getWindow(node) || !isHTMLElement(node)) {\n return getWindowScroll(node);\n } else {\n return getHTMLElementScroll(node);\n }\n}","export default function getHTMLElementScroll(element) {\n return {\n scrollLeft: element.scrollLeft,\n scrollTop: element.scrollTop\n };\n}","import { modifierPhases } from \"../enums.js\"; // source: https://stackoverflow.com/questions/49875255\n\nfunction order(modifiers) {\n var map = new Map();\n var visited = new Set();\n var result = [];\n modifiers.forEach(function (modifier) {\n map.set(modifier.name, modifier);\n }); // On visiting object, check for its dependencies and visit them recursively\n\n function sort(modifier) {\n visited.add(modifier.name);\n var requires = [].concat(modifier.requires || [], modifier.requiresIfExists || []);\n requires.forEach(function (dep) {\n if (!visited.has(dep)) {\n var depModifier = map.get(dep);\n\n if (depModifier) {\n sort(depModifier);\n }\n }\n });\n result.push(modifier);\n }\n\n modifiers.forEach(function (modifier) {\n if (!visited.has(modifier.name)) {\n // check for visited object\n sort(modifier);\n }\n });\n return result;\n}\n\nexport default function orderModifiers(modifiers) {\n // order based on dependencies\n var orderedModifiers = order(modifiers); // order based on phase\n\n return modifierPhases.reduce(function (acc, phase) {\n return acc.concat(orderedModifiers.filter(function (modifier) {\n return modifier.phase === phase;\n }));\n }, []);\n}","import getCompositeRect from \"./dom-utils/getCompositeRect.js\";\nimport getLayoutRect from \"./dom-utils/getLayoutRect.js\";\nimport listScrollParents from \"./dom-utils/listScrollParents.js\";\nimport getOffsetParent from \"./dom-utils/getOffsetParent.js\";\nimport orderModifiers from \"./utils/orderModifiers.js\";\nimport debounce from \"./utils/debounce.js\";\nimport mergeByName from \"./utils/mergeByName.js\";\nimport detectOverflow from \"./utils/detectOverflow.js\";\nimport { isElement } from \"./dom-utils/instanceOf.js\";\nvar DEFAULT_OPTIONS = {\n placement: 'bottom',\n modifiers: [],\n strategy: 'absolute'\n};\n\nfunction areValidElements() {\n for (var _len = arguments.length, args = new Array(_len), _key = 0; _key < _len; _key++) {\n args[_key] = arguments[_key];\n }\n\n return !args.some(function (element) {\n return !(element && typeof element.getBoundingClientRect === 'function');\n });\n}\n\nexport function popperGenerator(generatorOptions) {\n if (generatorOptions === void 0) {\n generatorOptions = {};\n }\n\n var _generatorOptions = generatorOptions,\n _generatorOptions$def = _generatorOptions.defaultModifiers,\n defaultModifiers = _generatorOptions$def === void 0 ? [] : _generatorOptions$def,\n _generatorOptions$def2 = _generatorOptions.defaultOptions,\n defaultOptions = _generatorOptions$def2 === void 0 ? DEFAULT_OPTIONS : _generatorOptions$def2;\n return function createPopper(reference, popper, options) {\n if (options === void 0) {\n options = defaultOptions;\n }\n\n var state = {\n placement: 'bottom',\n orderedModifiers: [],\n options: Object.assign({}, DEFAULT_OPTIONS, defaultOptions),\n modifiersData: {},\n elements: {\n reference: reference,\n popper: popper\n },\n attributes: {},\n styles: {}\n };\n var effectCleanupFns = [];\n var isDestroyed = false;\n var instance = {\n state: state,\n setOptions: function setOptions(setOptionsAction) {\n var options = typeof setOptionsAction === 'function' ? setOptionsAction(state.options) : setOptionsAction;\n cleanupModifierEffects();\n state.options = Object.assign({}, defaultOptions, state.options, options);\n state.scrollParents = {\n reference: isElement(reference) ? listScrollParents(reference) : reference.contextElement ? listScrollParents(reference.contextElement) : [],\n popper: listScrollParents(popper)\n }; // Orders the modifiers based on their dependencies and `phase`\n // properties\n\n var orderedModifiers = orderModifiers(mergeByName([].concat(defaultModifiers, state.options.modifiers))); // Strip out disabled modifiers\n\n state.orderedModifiers = orderedModifiers.filter(function (m) {\n return m.enabled;\n });\n runModifierEffects();\n return instance.update();\n },\n // Sync update – it will always be executed, even if not necessary. This\n // is useful for low frequency updates where sync behavior simplifies the\n // logic.\n // For high frequency updates (e.g. `resize` and `scroll` events), always\n // prefer the async Popper#update method\n forceUpdate: function forceUpdate() {\n if (isDestroyed) {\n return;\n }\n\n var _state$elements = state.elements,\n reference = _state$elements.reference,\n popper = _state$elements.popper; // Don't proceed if `reference` or `popper` are not valid elements\n // anymore\n\n if (!areValidElements(reference, popper)) {\n return;\n } // Store the reference and popper rects to be read by modifiers\n\n\n state.rects = {\n reference: getCompositeRect(reference, getOffsetParent(popper), state.options.strategy === 'fixed'),\n popper: getLayoutRect(popper)\n }; // Modifiers have the ability to reset the current update cycle. The\n // most common use case for this is the `flip` modifier changing the\n // placement, which then needs to re-run all the modifiers, because the\n // logic was previously ran for the previous placement and is therefore\n // stale/incorrect\n\n state.reset = false;\n state.placement = state.options.placement; // On each update cycle, the `modifiersData` property for each modifier\n // is filled with the initial data specified by the modifier. This means\n // it doesn't persist and is fresh on each update.\n // To ensure persistent data, use `${name}#persistent`\n\n state.orderedModifiers.forEach(function (modifier) {\n return state.modifiersData[modifier.name] = Object.assign({}, modifier.data);\n });\n\n for (var index = 0; index < state.orderedModifiers.length; index++) {\n if (state.reset === true) {\n state.reset = false;\n index = -1;\n continue;\n }\n\n var _state$orderedModifie = state.orderedModifiers[index],\n fn = _state$orderedModifie.fn,\n _state$orderedModifie2 = _state$orderedModifie.options,\n _options = _state$orderedModifie2 === void 0 ? {} : _state$orderedModifie2,\n name = _state$orderedModifie.name;\n\n if (typeof fn === 'function') {\n state = fn({\n state: state,\n options: _options,\n name: name,\n instance: instance\n }) || state;\n }\n }\n },\n // Async and optimistically optimized update – it will not be executed if\n // not necessary (debounced to run at most once-per-tick)\n update: debounce(function () {\n return new Promise(function (resolve) {\n instance.forceUpdate();\n resolve(state);\n });\n }),\n destroy: function destroy() {\n cleanupModifierEffects();\n isDestroyed = true;\n }\n };\n\n if (!areValidElements(reference, popper)) {\n return instance;\n }\n\n instance.setOptions(options).then(function (state) {\n if (!isDestroyed && options.onFirstUpdate) {\n options.onFirstUpdate(state);\n }\n }); // Modifiers have the ability to execute arbitrary code before the first\n // update cycle runs. They will be executed in the same order as the update\n // cycle. This is useful when a modifier adds some persistent data that\n // other modifiers need to use, but the modifier is run after the dependent\n // one.\n\n function runModifierEffects() {\n state.orderedModifiers.forEach(function (_ref) {\n var name = _ref.name,\n _ref$options = _ref.options,\n options = _ref$options === void 0 ? {} : _ref$options,\n effect = _ref.effect;\n\n if (typeof effect === 'function') {\n var cleanupFn = effect({\n state: state,\n name: name,\n instance: instance,\n options: options\n });\n\n var noopFn = function noopFn() {};\n\n effectCleanupFns.push(cleanupFn || noopFn);\n }\n });\n }\n\n function cleanupModifierEffects() {\n effectCleanupFns.forEach(function (fn) {\n return fn();\n });\n effectCleanupFns = [];\n }\n\n return instance;\n };\n}\nexport var createPopper = /*#__PURE__*/popperGenerator(); // eslint-disable-next-line import/no-unused-modules\n\nexport { detectOverflow };","export default function debounce(fn) {\n var pending;\n return function () {\n if (!pending) {\n pending = new Promise(function (resolve) {\n Promise.resolve().then(function () {\n pending = undefined;\n resolve(fn());\n });\n });\n }\n\n return pending;\n };\n}","export default function mergeByName(modifiers) {\n var merged = modifiers.reduce(function (merged, current) {\n var existing = merged[current.name];\n merged[current.name] = existing ? Object.assign({}, existing, current, {\n options: Object.assign({}, existing.options, current.options),\n data: Object.assign({}, existing.data, current.data)\n }) : current;\n return merged;\n }, {}); // IE11 does not support Object.values\n\n return Object.keys(merged).map(function (key) {\n return merged[key];\n });\n}","import { popperGenerator, detectOverflow } from \"./createPopper.js\";\nimport eventListeners from \"./modifiers/eventListeners.js\";\nimport popperOffsets from \"./modifiers/popperOffsets.js\";\nimport computeStyles from \"./modifiers/computeStyles.js\";\nimport applyStyles from \"./modifiers/applyStyles.js\";\nimport offset from \"./modifiers/offset.js\";\nimport flip from \"./modifiers/flip.js\";\nimport preventOverflow from \"./modifiers/preventOverflow.js\";\nimport arrow from \"./modifiers/arrow.js\";\nimport hide from \"./modifiers/hide.js\";\nvar defaultModifiers = [eventListeners, popperOffsets, computeStyles, applyStyles, offset, flip, preventOverflow, arrow, hide];\nvar createPopper = /*#__PURE__*/popperGenerator({\n defaultModifiers: defaultModifiers\n}); // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper, popperGenerator, defaultModifiers, detectOverflow }; // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper as createPopperLite } from \"./popper-lite.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport * from \"./modifiers/index.js\";","import { popperGenerator, detectOverflow } from \"./createPopper.js\";\nimport eventListeners from \"./modifiers/eventListeners.js\";\nimport popperOffsets from \"./modifiers/popperOffsets.js\";\nimport computeStyles from \"./modifiers/computeStyles.js\";\nimport applyStyles from \"./modifiers/applyStyles.js\";\nvar defaultModifiers = [eventListeners, popperOffsets, computeStyles, applyStyles];\nvar createPopper = /*#__PURE__*/popperGenerator({\n defaultModifiers: defaultModifiers\n}); // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper, popperGenerator, defaultModifiers, detectOverflow };","/*!\n * Bootstrap v5.3.3 (https://getbootstrap.com/)\n * Copyright 2011-2024 The Bootstrap Authors (https://github.com/twbs/bootstrap/graphs/contributors)\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n */\nimport * as Popper from '@popperjs/core';\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/data.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n/**\n * Constants\n */\n\nconst elementMap = new Map();\nconst Data = {\n set(element, key, instance) {\n if (!elementMap.has(element)) {\n elementMap.set(element, new Map());\n }\n const instanceMap = elementMap.get(element);\n\n // make it clear we only want one instance per element\n // can be removed later when multiple key/instances are fine to be used\n if (!instanceMap.has(key) && instanceMap.size !== 0) {\n // eslint-disable-next-line no-console\n console.error(`Bootstrap doesn't allow more than one instance per element. Bound instance: ${Array.from(instanceMap.keys())[0]}.`);\n return;\n }\n instanceMap.set(key, instance);\n },\n get(element, key) {\n if (elementMap.has(element)) {\n return elementMap.get(element).get(key) || null;\n }\n return null;\n },\n remove(element, key) {\n if (!elementMap.has(element)) {\n return;\n }\n const instanceMap = elementMap.get(element);\n instanceMap.delete(key);\n\n // free up element references if there are no instances left for an element\n if (instanceMap.size === 0) {\n elementMap.delete(element);\n }\n }\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/index.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst MAX_UID = 1000000;\nconst MILLISECONDS_MULTIPLIER = 1000;\nconst TRANSITION_END = 'transitionend';\n\n/**\n * Properly escape IDs selectors to handle weird IDs\n * @param {string} selector\n * @returns {string}\n */\nconst parseSelector = selector => {\n if (selector && window.CSS && window.CSS.escape) {\n // document.querySelector needs escaping to handle IDs (html5+) containing for instance /\n selector = selector.replace(/#([^\\s\"#']+)/g, (match, id) => `#${CSS.escape(id)}`);\n }\n return selector;\n};\n\n// Shout-out Angus Croll (https://goo.gl/pxwQGp)\nconst toType = object => {\n if (object === null || object === undefined) {\n return `${object}`;\n }\n return Object.prototype.toString.call(object).match(/\\s([a-z]+)/i)[1].toLowerCase();\n};\n\n/**\n * Public Util API\n */\n\nconst getUID = prefix => {\n do {\n prefix += Math.floor(Math.random() * MAX_UID);\n } while (document.getElementById(prefix));\n return prefix;\n};\nconst getTransitionDurationFromElement = element => {\n if (!element) {\n return 0;\n }\n\n // Get transition-duration of the element\n let {\n transitionDuration,\n transitionDelay\n } = window.getComputedStyle(element);\n const floatTransitionDuration = Number.parseFloat(transitionDuration);\n const floatTransitionDelay = Number.parseFloat(transitionDelay);\n\n // Return 0 if element or transition duration is not found\n if (!floatTransitionDuration && !floatTransitionDelay) {\n return 0;\n }\n\n // If multiple durations are defined, take the first\n transitionDuration = transitionDuration.split(',')[0];\n transitionDelay = transitionDelay.split(',')[0];\n return (Number.parseFloat(transitionDuration) + Number.parseFloat(transitionDelay)) * MILLISECONDS_MULTIPLIER;\n};\nconst triggerTransitionEnd = element => {\n element.dispatchEvent(new Event(TRANSITION_END));\n};\nconst isElement = object => {\n if (!object || typeof object !== 'object') {\n return false;\n }\n if (typeof object.jquery !== 'undefined') {\n object = object[0];\n }\n return typeof object.nodeType !== 'undefined';\n};\nconst getElement = object => {\n // it's a jQuery object or a node element\n if (isElement(object)) {\n return object.jquery ? object[0] : object;\n }\n if (typeof object === 'string' && object.length > 0) {\n return document.querySelector(parseSelector(object));\n }\n return null;\n};\nconst isVisible = element => {\n if (!isElement(element) || element.getClientRects().length === 0) {\n return false;\n }\n const elementIsVisible = getComputedStyle(element).getPropertyValue('visibility') === 'visible';\n // Handle `details` element as its content may falsie appear visible when it is closed\n const closedDetails = element.closest('details:not([open])');\n if (!closedDetails) {\n return elementIsVisible;\n }\n if (closedDetails !== element) {\n const summary = element.closest('summary');\n if (summary && summary.parentNode !== closedDetails) {\n return false;\n }\n if (summary === null) {\n return false;\n }\n }\n return elementIsVisible;\n};\nconst isDisabled = element => {\n if (!element || element.nodeType !== Node.ELEMENT_NODE) {\n return true;\n }\n if (element.classList.contains('disabled')) {\n return true;\n }\n if (typeof element.disabled !== 'undefined') {\n return element.disabled;\n }\n return element.hasAttribute('disabled') && element.getAttribute('disabled') !== 'false';\n};\nconst findShadowRoot = element => {\n if (!document.documentElement.attachShadow) {\n return null;\n }\n\n // Can find the shadow root otherwise it'll return the document\n if (typeof element.getRootNode === 'function') {\n const root = element.getRootNode();\n return root instanceof ShadowRoot ? root : null;\n }\n if (element instanceof ShadowRoot) {\n return element;\n }\n\n // when we don't find a shadow root\n if (!element.parentNode) {\n return null;\n }\n return findShadowRoot(element.parentNode);\n};\nconst noop = () => {};\n\n/**\n * Trick to restart an element's animation\n *\n * @param {HTMLElement} element\n * @return void\n *\n * @see https://www.charistheo.io/blog/2021/02/restart-a-css-animation-with-javascript/#restarting-a-css-animation\n */\nconst reflow = element => {\n element.offsetHeight; // eslint-disable-line no-unused-expressions\n};\nconst getjQuery = () => {\n if (window.jQuery && !document.body.hasAttribute('data-bs-no-jquery')) {\n return window.jQuery;\n }\n return null;\n};\nconst DOMContentLoadedCallbacks = [];\nconst onDOMContentLoaded = callback => {\n if (document.readyState === 'loading') {\n // add listener on the first call when the document is in loading state\n if (!DOMContentLoadedCallbacks.length) {\n document.addEventListener('DOMContentLoaded', () => {\n for (const callback of DOMContentLoadedCallbacks) {\n callback();\n }\n });\n }\n DOMContentLoadedCallbacks.push(callback);\n } else {\n callback();\n }\n};\nconst isRTL = () => document.documentElement.dir === 'rtl';\nconst defineJQueryPlugin = plugin => {\n onDOMContentLoaded(() => {\n const $ = getjQuery();\n /* istanbul ignore if */\n if ($) {\n const name = plugin.NAME;\n const JQUERY_NO_CONFLICT = $.fn[name];\n $.fn[name] = plugin.jQueryInterface;\n $.fn[name].Constructor = plugin;\n $.fn[name].noConflict = () => {\n $.fn[name] = JQUERY_NO_CONFLICT;\n return plugin.jQueryInterface;\n };\n }\n });\n};\nconst execute = (possibleCallback, args = [], defaultValue = possibleCallback) => {\n return typeof possibleCallback === 'function' ? possibleCallback(...args) : defaultValue;\n};\nconst executeAfterTransition = (callback, transitionElement, waitForTransition = true) => {\n if (!waitForTransition) {\n execute(callback);\n return;\n }\n const durationPadding = 5;\n const emulatedDuration = getTransitionDurationFromElement(transitionElement) + durationPadding;\n let called = false;\n const handler = ({\n target\n }) => {\n if (target !== transitionElement) {\n return;\n }\n called = true;\n transitionElement.removeEventListener(TRANSITION_END, handler);\n execute(callback);\n };\n transitionElement.addEventListener(TRANSITION_END, handler);\n setTimeout(() => {\n if (!called) {\n triggerTransitionEnd(transitionElement);\n }\n }, emulatedDuration);\n};\n\n/**\n * Return the previous/next element of a list.\n *\n * @param {array} list The list of elements\n * @param activeElement The active element\n * @param shouldGetNext Choose to get next or previous element\n * @param isCycleAllowed\n * @return {Element|elem} The proper element\n */\nconst getNextActiveElement = (list, activeElement, shouldGetNext, isCycleAllowed) => {\n const listLength = list.length;\n let index = list.indexOf(activeElement);\n\n // if the element does not exist in the list return an element\n // depending on the direction and if cycle is allowed\n if (index === -1) {\n return !shouldGetNext && isCycleAllowed ? list[listLength - 1] : list[0];\n }\n index += shouldGetNext ? 1 : -1;\n if (isCycleAllowed) {\n index = (index + listLength) % listLength;\n }\n return list[Math.max(0, Math.min(index, listLength - 1))];\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/event-handler.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst namespaceRegex = /[^.]*(?=\\..*)\\.|.*/;\nconst stripNameRegex = /\\..*/;\nconst stripUidRegex = /::\\d+$/;\nconst eventRegistry = {}; // Events storage\nlet uidEvent = 1;\nconst customEvents = {\n mouseenter: 'mouseover',\n mouseleave: 'mouseout'\n};\nconst nativeEvents = new Set(['click', 'dblclick', 'mouseup', 'mousedown', 'contextmenu', 'mousewheel', 'DOMMouseScroll', 'mouseover', 'mouseout', 'mousemove', 'selectstart', 'selectend', 'keydown', 'keypress', 'keyup', 'orientationchange', 'touchstart', 'touchmove', 'touchend', 'touchcancel', 'pointerdown', 'pointermove', 'pointerup', 'pointerleave', 'pointercancel', 'gesturestart', 'gesturechange', 'gestureend', 'focus', 'blur', 'change', 'reset', 'select', 'submit', 'focusin', 'focusout', 'load', 'unload', 'beforeunload', 'resize', 'move', 'DOMContentLoaded', 'readystatechange', 'error', 'abort', 'scroll']);\n\n/**\n * Private methods\n */\n\nfunction makeEventUid(element, uid) {\n return uid && `${uid}::${uidEvent++}` || element.uidEvent || uidEvent++;\n}\nfunction getElementEvents(element) {\n const uid = makeEventUid(element);\n element.uidEvent = uid;\n eventRegistry[uid] = eventRegistry[uid] || {};\n return eventRegistry[uid];\n}\nfunction bootstrapHandler(element, fn) {\n return function handler(event) {\n hydrateObj(event, {\n delegateTarget: element\n });\n if (handler.oneOff) {\n EventHandler.off(element, event.type, fn);\n }\n return fn.apply(element, [event]);\n };\n}\nfunction bootstrapDelegationHandler(element, selector, fn) {\n return function handler(event) {\n const domElements = element.querySelectorAll(selector);\n for (let {\n target\n } = event; target && target !== this; target = target.parentNode) {\n for (const domElement of domElements) {\n if (domElement !== target) {\n continue;\n }\n hydrateObj(event, {\n delegateTarget: target\n });\n if (handler.oneOff) {\n EventHandler.off(element, event.type, selector, fn);\n }\n return fn.apply(target, [event]);\n }\n }\n };\n}\nfunction findHandler(events, callable, delegationSelector = null) {\n return Object.values(events).find(event => event.callable === callable && event.delegationSelector === delegationSelector);\n}\nfunction normalizeParameters(originalTypeEvent, handler, delegationFunction) {\n const isDelegated = typeof handler === 'string';\n // TODO: tooltip passes `false` instead of selector, so we need to check\n const callable = isDelegated ? delegationFunction : handler || delegationFunction;\n let typeEvent = getTypeEvent(originalTypeEvent);\n if (!nativeEvents.has(typeEvent)) {\n typeEvent = originalTypeEvent;\n }\n return [isDelegated, callable, typeEvent];\n}\nfunction addHandler(element, originalTypeEvent, handler, delegationFunction, oneOff) {\n if (typeof originalTypeEvent !== 'string' || !element) {\n return;\n }\n let [isDelegated, callable, typeEvent] = normalizeParameters(originalTypeEvent, handler, delegationFunction);\n\n // in case of mouseenter or mouseleave wrap the handler within a function that checks for its DOM position\n // this prevents the handler from being dispatched the same way as mouseover or mouseout does\n if (originalTypeEvent in customEvents) {\n const wrapFunction = fn => {\n return function (event) {\n if (!event.relatedTarget || event.relatedTarget !== event.delegateTarget && !event.delegateTarget.contains(event.relatedTarget)) {\n return fn.call(this, event);\n }\n };\n };\n callable = wrapFunction(callable);\n }\n const events = getElementEvents(element);\n const handlers = events[typeEvent] || (events[typeEvent] = {});\n const previousFunction = findHandler(handlers, callable, isDelegated ? handler : null);\n if (previousFunction) {\n previousFunction.oneOff = previousFunction.oneOff && oneOff;\n return;\n }\n const uid = makeEventUid(callable, originalTypeEvent.replace(namespaceRegex, ''));\n const fn = isDelegated ? bootstrapDelegationHandler(element, handler, callable) : bootstrapHandler(element, callable);\n fn.delegationSelector = isDelegated ? handler : null;\n fn.callable = callable;\n fn.oneOff = oneOff;\n fn.uidEvent = uid;\n handlers[uid] = fn;\n element.addEventListener(typeEvent, fn, isDelegated);\n}\nfunction removeHandler(element, events, typeEvent, handler, delegationSelector) {\n const fn = findHandler(events[typeEvent], handler, delegationSelector);\n if (!fn) {\n return;\n }\n element.removeEventListener(typeEvent, fn, Boolean(delegationSelector));\n delete events[typeEvent][fn.uidEvent];\n}\nfunction removeNamespacedHandlers(element, events, typeEvent, namespace) {\n const storeElementEvent = events[typeEvent] || {};\n for (const [handlerKey, event] of Object.entries(storeElementEvent)) {\n if (handlerKey.includes(namespace)) {\n removeHandler(element, events, typeEvent, event.callable, event.delegationSelector);\n }\n }\n}\nfunction getTypeEvent(event) {\n // allow to get the native events from namespaced events ('click.bs.button' --> 'click')\n event = event.replace(stripNameRegex, '');\n return customEvents[event] || event;\n}\nconst EventHandler = {\n on(element, event, handler, delegationFunction) {\n addHandler(element, event, handler, delegationFunction, false);\n },\n one(element, event, handler, delegationFunction) {\n addHandler(element, event, handler, delegationFunction, true);\n },\n off(element, originalTypeEvent, handler, delegationFunction) {\n if (typeof originalTypeEvent !== 'string' || !element) {\n return;\n }\n const [isDelegated, callable, typeEvent] = normalizeParameters(originalTypeEvent, handler, delegationFunction);\n const inNamespace = typeEvent !== originalTypeEvent;\n const events = getElementEvents(element);\n const storeElementEvent = events[typeEvent] || {};\n const isNamespace = originalTypeEvent.startsWith('.');\n if (typeof callable !== 'undefined') {\n // Simplest case: handler is passed, remove that listener ONLY.\n if (!Object.keys(storeElementEvent).length) {\n return;\n }\n removeHandler(element, events, typeEvent, callable, isDelegated ? handler : null);\n return;\n }\n if (isNamespace) {\n for (const elementEvent of Object.keys(events)) {\n removeNamespacedHandlers(element, events, elementEvent, originalTypeEvent.slice(1));\n }\n }\n for (const [keyHandlers, event] of Object.entries(storeElementEvent)) {\n const handlerKey = keyHandlers.replace(stripUidRegex, '');\n if (!inNamespace || originalTypeEvent.includes(handlerKey)) {\n removeHandler(element, events, typeEvent, event.callable, event.delegationSelector);\n }\n }\n },\n trigger(element, event, args) {\n if (typeof event !== 'string' || !element) {\n return null;\n }\n const $ = getjQuery();\n const typeEvent = getTypeEvent(event);\n const inNamespace = event !== typeEvent;\n let jQueryEvent = null;\n let bubbles = true;\n let nativeDispatch = true;\n let defaultPrevented = false;\n if (inNamespace && $) {\n jQueryEvent = $.Event(event, args);\n $(element).trigger(jQueryEvent);\n bubbles = !jQueryEvent.isPropagationStopped();\n nativeDispatch = !jQueryEvent.isImmediatePropagationStopped();\n defaultPrevented = jQueryEvent.isDefaultPrevented();\n }\n const evt = hydrateObj(new Event(event, {\n bubbles,\n cancelable: true\n }), args);\n if (defaultPrevented) {\n evt.preventDefault();\n }\n if (nativeDispatch) {\n element.dispatchEvent(evt);\n }\n if (evt.defaultPrevented && jQueryEvent) {\n jQueryEvent.preventDefault();\n }\n return evt;\n }\n};\nfunction hydrateObj(obj, meta = {}) {\n for (const [key, value] of Object.entries(meta)) {\n try {\n obj[key] = value;\n } catch (_unused) {\n Object.defineProperty(obj, key, {\n configurable: true,\n get() {\n return value;\n }\n });\n }\n }\n return obj;\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/manipulator.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nfunction normalizeData(value) {\n if (value === 'true') {\n return true;\n }\n if (value === 'false') {\n return false;\n }\n if (value === Number(value).toString()) {\n return Number(value);\n }\n if (value === '' || value === 'null') {\n return null;\n }\n if (typeof value !== 'string') {\n return value;\n }\n try {\n return JSON.parse(decodeURIComponent(value));\n } catch (_unused) {\n return value;\n }\n}\nfunction normalizeDataKey(key) {\n return key.replace(/[A-Z]/g, chr => `-${chr.toLowerCase()}`);\n}\nconst Manipulator = {\n setDataAttribute(element, key, value) {\n element.setAttribute(`data-bs-${normalizeDataKey(key)}`, value);\n },\n removeDataAttribute(element, key) {\n element.removeAttribute(`data-bs-${normalizeDataKey(key)}`);\n },\n getDataAttributes(element) {\n if (!element) {\n return {};\n }\n const attributes = {};\n const bsKeys = Object.keys(element.dataset).filter(key => key.startsWith('bs') && !key.startsWith('bsConfig'));\n for (const key of bsKeys) {\n let pureKey = key.replace(/^bs/, '');\n pureKey = pureKey.charAt(0).toLowerCase() + pureKey.slice(1, pureKey.length);\n attributes[pureKey] = normalizeData(element.dataset[key]);\n }\n return attributes;\n },\n getDataAttribute(element, key) {\n return normalizeData(element.getAttribute(`data-bs-${normalizeDataKey(key)}`));\n }\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/config.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Class definition\n */\n\nclass Config {\n // Getters\n static get Default() {\n return {};\n }\n static get DefaultType() {\n return {};\n }\n static get NAME() {\n throw new Error('You have to implement the static method \"NAME\", for each component!');\n }\n _getConfig(config) {\n config = this._mergeConfigObj(config);\n config = this._configAfterMerge(config);\n this._typeCheckConfig(config);\n return config;\n }\n _configAfterMerge(config) {\n return config;\n }\n _mergeConfigObj(config, element) {\n const jsonConfig = isElement(element) ? Manipulator.getDataAttribute(element, 'config') : {}; // try to parse\n\n return {\n ...this.constructor.Default,\n ...(typeof jsonConfig === 'object' ? jsonConfig : {}),\n ...(isElement(element) ? Manipulator.getDataAttributes(element) : {}),\n ...(typeof config === 'object' ? config : {})\n };\n }\n _typeCheckConfig(config, configTypes = this.constructor.DefaultType) {\n for (const [property, expectedTypes] of Object.entries(configTypes)) {\n const value = config[property];\n const valueType = isElement(value) ? 'element' : toType(value);\n if (!new RegExp(expectedTypes).test(valueType)) {\n throw new TypeError(`${this.constructor.NAME.toUpperCase()}: Option \"${property}\" provided type \"${valueType}\" but expected type \"${expectedTypes}\".`);\n }\n }\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap base-component.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst VERSION = '5.3.3';\n\n/**\n * Class definition\n */\n\nclass BaseComponent extends Config {\n constructor(element, config) {\n super();\n element = getElement(element);\n if (!element) {\n return;\n }\n this._element = element;\n this._config = this._getConfig(config);\n Data.set(this._element, this.constructor.DATA_KEY, this);\n }\n\n // Public\n dispose() {\n Data.remove(this._element, this.constructor.DATA_KEY);\n EventHandler.off(this._element, this.constructor.EVENT_KEY);\n for (const propertyName of Object.getOwnPropertyNames(this)) {\n this[propertyName] = null;\n }\n }\n _queueCallback(callback, element, isAnimated = true) {\n executeAfterTransition(callback, element, isAnimated);\n }\n _getConfig(config) {\n config = this._mergeConfigObj(config, this._element);\n config = this._configAfterMerge(config);\n this._typeCheckConfig(config);\n return config;\n }\n\n // Static\n static getInstance(element) {\n return Data.get(getElement(element), this.DATA_KEY);\n }\n static getOrCreateInstance(element, config = {}) {\n return this.getInstance(element) || new this(element, typeof config === 'object' ? config : null);\n }\n static get VERSION() {\n return VERSION;\n }\n static get DATA_KEY() {\n return `bs.${this.NAME}`;\n }\n static get EVENT_KEY() {\n return `.${this.DATA_KEY}`;\n }\n static eventName(name) {\n return `${name}${this.EVENT_KEY}`;\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/selector-engine.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst getSelector = element => {\n let selector = element.getAttribute('data-bs-target');\n if (!selector || selector === '#') {\n let hrefAttribute = element.getAttribute('href');\n\n // The only valid content that could double as a selector are IDs or classes,\n // so everything starting with `#` or `.`. If a \"real\" URL is used as the selector,\n // `document.querySelector` will rightfully complain it is invalid.\n // See https://github.com/twbs/bootstrap/issues/32273\n if (!hrefAttribute || !hrefAttribute.includes('#') && !hrefAttribute.startsWith('.')) {\n return null;\n }\n\n // Just in case some CMS puts out a full URL with the anchor appended\n if (hrefAttribute.includes('#') && !hrefAttribute.startsWith('#')) {\n hrefAttribute = `#${hrefAttribute.split('#')[1]}`;\n }\n selector = hrefAttribute && hrefAttribute !== '#' ? hrefAttribute.trim() : null;\n }\n return selector ? selector.split(',').map(sel => parseSelector(sel)).join(',') : null;\n};\nconst SelectorEngine = {\n find(selector, element = document.documentElement) {\n return [].concat(...Element.prototype.querySelectorAll.call(element, selector));\n },\n findOne(selector, element = document.documentElement) {\n return Element.prototype.querySelector.call(element, selector);\n },\n children(element, selector) {\n return [].concat(...element.children).filter(child => child.matches(selector));\n },\n parents(element, selector) {\n const parents = [];\n let ancestor = element.parentNode.closest(selector);\n while (ancestor) {\n parents.push(ancestor);\n ancestor = ancestor.parentNode.closest(selector);\n }\n return parents;\n },\n prev(element, selector) {\n let previous = element.previousElementSibling;\n while (previous) {\n if (previous.matches(selector)) {\n return [previous];\n }\n previous = previous.previousElementSibling;\n }\n return [];\n },\n // TODO: this is now unused; remove later along with prev()\n next(element, selector) {\n let next = element.nextElementSibling;\n while (next) {\n if (next.matches(selector)) {\n return [next];\n }\n next = next.nextElementSibling;\n }\n return [];\n },\n focusableChildren(element) {\n const focusables = ['a', 'button', 'input', 'textarea', 'select', 'details', '[tabindex]', '[contenteditable=\"true\"]'].map(selector => `${selector}:not([tabindex^=\"-\"])`).join(',');\n return this.find(focusables, element).filter(el => !isDisabled(el) && isVisible(el));\n },\n getSelectorFromElement(element) {\n const selector = getSelector(element);\n if (selector) {\n return SelectorEngine.findOne(selector) ? selector : null;\n }\n return null;\n },\n getElementFromSelector(element) {\n const selector = getSelector(element);\n return selector ? SelectorEngine.findOne(selector) : null;\n },\n getMultipleElementsFromSelector(element) {\n const selector = getSelector(element);\n return selector ? SelectorEngine.find(selector) : [];\n }\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/component-functions.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst enableDismissTrigger = (component, method = 'hide') => {\n const clickEvent = `click.dismiss${component.EVENT_KEY}`;\n const name = component.NAME;\n EventHandler.on(document, clickEvent, `[data-bs-dismiss=\"${name}\"]`, function (event) {\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault();\n }\n if (isDisabled(this)) {\n return;\n }\n const target = SelectorEngine.getElementFromSelector(this) || this.closest(`.${name}`);\n const instance = component.getOrCreateInstance(target);\n\n // Method argument is left, for Alert and only, as it doesn't implement the 'hide' method\n instance[method]();\n });\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap alert.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$f = 'alert';\nconst DATA_KEY$a = 'bs.alert';\nconst EVENT_KEY$b = `.${DATA_KEY$a}`;\nconst EVENT_CLOSE = `close${EVENT_KEY$b}`;\nconst EVENT_CLOSED = `closed${EVENT_KEY$b}`;\nconst CLASS_NAME_FADE$5 = 'fade';\nconst CLASS_NAME_SHOW$8 = 'show';\n\n/**\n * Class definition\n */\n\nclass Alert extends BaseComponent {\n // Getters\n static get NAME() {\n return NAME$f;\n }\n\n // Public\n close() {\n const closeEvent = EventHandler.trigger(this._element, EVENT_CLOSE);\n if (closeEvent.defaultPrevented) {\n return;\n }\n this._element.classList.remove(CLASS_NAME_SHOW$8);\n const isAnimated = this._element.classList.contains(CLASS_NAME_FADE$5);\n this._queueCallback(() => this._destroyElement(), this._element, isAnimated);\n }\n\n // Private\n _destroyElement() {\n this._element.remove();\n EventHandler.trigger(this._element, EVENT_CLOSED);\n this.dispose();\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Alert.getOrCreateInstance(this);\n if (typeof config !== 'string') {\n return;\n }\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config](this);\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nenableDismissTrigger(Alert, 'close');\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Alert);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap button.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$e = 'button';\nconst DATA_KEY$9 = 'bs.button';\nconst EVENT_KEY$a = `.${DATA_KEY$9}`;\nconst DATA_API_KEY$6 = '.data-api';\nconst CLASS_NAME_ACTIVE$3 = 'active';\nconst SELECTOR_DATA_TOGGLE$5 = '[data-bs-toggle=\"button\"]';\nconst EVENT_CLICK_DATA_API$6 = `click${EVENT_KEY$a}${DATA_API_KEY$6}`;\n\n/**\n * Class definition\n */\n\nclass Button extends BaseComponent {\n // Getters\n static get NAME() {\n return NAME$e;\n }\n\n // Public\n toggle() {\n // Toggle class and sync the `aria-pressed` attribute with the return value of the `.toggle()` method\n this._element.setAttribute('aria-pressed', this._element.classList.toggle(CLASS_NAME_ACTIVE$3));\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Button.getOrCreateInstance(this);\n if (config === 'toggle') {\n data[config]();\n }\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$6, SELECTOR_DATA_TOGGLE$5, event => {\n event.preventDefault();\n const button = event.target.closest(SELECTOR_DATA_TOGGLE$5);\n const data = Button.getOrCreateInstance(button);\n data.toggle();\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Button);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/swipe.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$d = 'swipe';\nconst EVENT_KEY$9 = '.bs.swipe';\nconst EVENT_TOUCHSTART = `touchstart${EVENT_KEY$9}`;\nconst EVENT_TOUCHMOVE = `touchmove${EVENT_KEY$9}`;\nconst EVENT_TOUCHEND = `touchend${EVENT_KEY$9}`;\nconst EVENT_POINTERDOWN = `pointerdown${EVENT_KEY$9}`;\nconst EVENT_POINTERUP = `pointerup${EVENT_KEY$9}`;\nconst POINTER_TYPE_TOUCH = 'touch';\nconst POINTER_TYPE_PEN = 'pen';\nconst CLASS_NAME_POINTER_EVENT = 'pointer-event';\nconst SWIPE_THRESHOLD = 40;\nconst Default$c = {\n endCallback: null,\n leftCallback: null,\n rightCallback: null\n};\nconst DefaultType$c = {\n endCallback: '(function|null)',\n leftCallback: '(function|null)',\n rightCallback: '(function|null)'\n};\n\n/**\n * Class definition\n */\n\nclass Swipe extends Config {\n constructor(element, config) {\n super();\n this._element = element;\n if (!element || !Swipe.isSupported()) {\n return;\n }\n this._config = this._getConfig(config);\n this._deltaX = 0;\n this._supportPointerEvents = Boolean(window.PointerEvent);\n this._initEvents();\n }\n\n // Getters\n static get Default() {\n return Default$c;\n }\n static get DefaultType() {\n return DefaultType$c;\n }\n static get NAME() {\n return NAME$d;\n }\n\n // Public\n dispose() {\n EventHandler.off(this._element, EVENT_KEY$9);\n }\n\n // Private\n _start(event) {\n if (!this._supportPointerEvents) {\n this._deltaX = event.touches[0].clientX;\n return;\n }\n if (this._eventIsPointerPenTouch(event)) {\n this._deltaX = event.clientX;\n }\n }\n _end(event) {\n if (this._eventIsPointerPenTouch(event)) {\n this._deltaX = event.clientX - this._deltaX;\n }\n this._handleSwipe();\n execute(this._config.endCallback);\n }\n _move(event) {\n this._deltaX = event.touches && event.touches.length > 1 ? 0 : event.touches[0].clientX - this._deltaX;\n }\n _handleSwipe() {\n const absDeltaX = Math.abs(this._deltaX);\n if (absDeltaX <= SWIPE_THRESHOLD) {\n return;\n }\n const direction = absDeltaX / this._deltaX;\n this._deltaX = 0;\n if (!direction) {\n return;\n }\n execute(direction > 0 ? this._config.rightCallback : this._config.leftCallback);\n }\n _initEvents() {\n if (this._supportPointerEvents) {\n EventHandler.on(this._element, EVENT_POINTERDOWN, event => this._start(event));\n EventHandler.on(this._element, EVENT_POINTERUP, event => this._end(event));\n this._element.classList.add(CLASS_NAME_POINTER_EVENT);\n } else {\n EventHandler.on(this._element, EVENT_TOUCHSTART, event => this._start(event));\n EventHandler.on(this._element, EVENT_TOUCHMOVE, event => this._move(event));\n EventHandler.on(this._element, EVENT_TOUCHEND, event => this._end(event));\n }\n }\n _eventIsPointerPenTouch(event) {\n return this._supportPointerEvents && (event.pointerType === POINTER_TYPE_PEN || event.pointerType === POINTER_TYPE_TOUCH);\n }\n\n // Static\n static isSupported() {\n return 'ontouchstart' in document.documentElement || navigator.maxTouchPoints > 0;\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap carousel.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$c = 'carousel';\nconst DATA_KEY$8 = 'bs.carousel';\nconst EVENT_KEY$8 = `.${DATA_KEY$8}`;\nconst DATA_API_KEY$5 = '.data-api';\nconst ARROW_LEFT_KEY$1 = 'ArrowLeft';\nconst ARROW_RIGHT_KEY$1 = 'ArrowRight';\nconst TOUCHEVENT_COMPAT_WAIT = 500; // Time for mouse compat events to fire after touch\n\nconst ORDER_NEXT = 'next';\nconst ORDER_PREV = 'prev';\nconst DIRECTION_LEFT = 'left';\nconst DIRECTION_RIGHT = 'right';\nconst EVENT_SLIDE = `slide${EVENT_KEY$8}`;\nconst EVENT_SLID = `slid${EVENT_KEY$8}`;\nconst EVENT_KEYDOWN$1 = `keydown${EVENT_KEY$8}`;\nconst EVENT_MOUSEENTER$1 = `mouseenter${EVENT_KEY$8}`;\nconst EVENT_MOUSELEAVE$1 = `mouseleave${EVENT_KEY$8}`;\nconst EVENT_DRAG_START = `dragstart${EVENT_KEY$8}`;\nconst EVENT_LOAD_DATA_API$3 = `load${EVENT_KEY$8}${DATA_API_KEY$5}`;\nconst EVENT_CLICK_DATA_API$5 = `click${EVENT_KEY$8}${DATA_API_KEY$5}`;\nconst CLASS_NAME_CAROUSEL = 'carousel';\nconst CLASS_NAME_ACTIVE$2 = 'active';\nconst CLASS_NAME_SLIDE = 'slide';\nconst CLASS_NAME_END = 'carousel-item-end';\nconst CLASS_NAME_START = 'carousel-item-start';\nconst CLASS_NAME_NEXT = 'carousel-item-next';\nconst CLASS_NAME_PREV = 'carousel-item-prev';\nconst SELECTOR_ACTIVE = '.active';\nconst SELECTOR_ITEM = '.carousel-item';\nconst SELECTOR_ACTIVE_ITEM = SELECTOR_ACTIVE + SELECTOR_ITEM;\nconst SELECTOR_ITEM_IMG = '.carousel-item img';\nconst SELECTOR_INDICATORS = '.carousel-indicators';\nconst SELECTOR_DATA_SLIDE = '[data-bs-slide], [data-bs-slide-to]';\nconst SELECTOR_DATA_RIDE = '[data-bs-ride=\"carousel\"]';\nconst KEY_TO_DIRECTION = {\n [ARROW_LEFT_KEY$1]: DIRECTION_RIGHT,\n [ARROW_RIGHT_KEY$1]: DIRECTION_LEFT\n};\nconst Default$b = {\n interval: 5000,\n keyboard: true,\n pause: 'hover',\n ride: false,\n touch: true,\n wrap: true\n};\nconst DefaultType$b = {\n interval: '(number|boolean)',\n // TODO:v6 remove boolean support\n keyboard: 'boolean',\n pause: '(string|boolean)',\n ride: '(boolean|string)',\n touch: 'boolean',\n wrap: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Carousel extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._interval = null;\n this._activeElement = null;\n this._isSliding = false;\n this.touchTimeout = null;\n this._swipeHelper = null;\n this._indicatorsElement = SelectorEngine.findOne(SELECTOR_INDICATORS, this._element);\n this._addEventListeners();\n if (this._config.ride === CLASS_NAME_CAROUSEL) {\n this.cycle();\n }\n }\n\n // Getters\n static get Default() {\n return Default$b;\n }\n static get DefaultType() {\n return DefaultType$b;\n }\n static get NAME() {\n return NAME$c;\n }\n\n // Public\n next() {\n this._slide(ORDER_NEXT);\n }\n nextWhenVisible() {\n // FIXME TODO use `document.visibilityState`\n // Don't call next when the page isn't visible\n // or the carousel or its parent isn't visible\n if (!document.hidden && isVisible(this._element)) {\n this.next();\n }\n }\n prev() {\n this._slide(ORDER_PREV);\n }\n pause() {\n if (this._isSliding) {\n triggerTransitionEnd(this._element);\n }\n this._clearInterval();\n }\n cycle() {\n this._clearInterval();\n this._updateInterval();\n this._interval = setInterval(() => this.nextWhenVisible(), this._config.interval);\n }\n _maybeEnableCycle() {\n if (!this._config.ride) {\n return;\n }\n if (this._isSliding) {\n EventHandler.one(this._element, EVENT_SLID, () => this.cycle());\n return;\n }\n this.cycle();\n }\n to(index) {\n const items = this._getItems();\n if (index > items.length - 1 || index < 0) {\n return;\n }\n if (this._isSliding) {\n EventHandler.one(this._element, EVENT_SLID, () => this.to(index));\n return;\n }\n const activeIndex = this._getItemIndex(this._getActive());\n if (activeIndex === index) {\n return;\n }\n const order = index > activeIndex ? ORDER_NEXT : ORDER_PREV;\n this._slide(order, items[index]);\n }\n dispose() {\n if (this._swipeHelper) {\n this._swipeHelper.dispose();\n }\n super.dispose();\n }\n\n // Private\n _configAfterMerge(config) {\n config.defaultInterval = config.interval;\n return config;\n }\n _addEventListeners() {\n if (this._config.keyboard) {\n EventHandler.on(this._element, EVENT_KEYDOWN$1, event => this._keydown(event));\n }\n if (this._config.pause === 'hover') {\n EventHandler.on(this._element, EVENT_MOUSEENTER$1, () => this.pause());\n EventHandler.on(this._element, EVENT_MOUSELEAVE$1, () => this._maybeEnableCycle());\n }\n if (this._config.touch && Swipe.isSupported()) {\n this._addTouchEventListeners();\n }\n }\n _addTouchEventListeners() {\n for (const img of SelectorEngine.find(SELECTOR_ITEM_IMG, this._element)) {\n EventHandler.on(img, EVENT_DRAG_START, event => event.preventDefault());\n }\n const endCallBack = () => {\n if (this._config.pause !== 'hover') {\n return;\n }\n\n // If it's a touch-enabled device, mouseenter/leave are fired as\n // part of the mouse compatibility events on first tap - the carousel\n // would stop cycling until user tapped out of it;\n // here, we listen for touchend, explicitly pause the carousel\n // (as if it's the second time we tap on it, mouseenter compat event\n // is NOT fired) and after a timeout (to allow for mouse compatibility\n // events to fire) we explicitly restart cycling\n\n this.pause();\n if (this.touchTimeout) {\n clearTimeout(this.touchTimeout);\n }\n this.touchTimeout = setTimeout(() => this._maybeEnableCycle(), TOUCHEVENT_COMPAT_WAIT + this._config.interval);\n };\n const swipeConfig = {\n leftCallback: () => this._slide(this._directionToOrder(DIRECTION_LEFT)),\n rightCallback: () => this._slide(this._directionToOrder(DIRECTION_RIGHT)),\n endCallback: endCallBack\n };\n this._swipeHelper = new Swipe(this._element, swipeConfig);\n }\n _keydown(event) {\n if (/input|textarea/i.test(event.target.tagName)) {\n return;\n }\n const direction = KEY_TO_DIRECTION[event.key];\n if (direction) {\n event.preventDefault();\n this._slide(this._directionToOrder(direction));\n }\n }\n _getItemIndex(element) {\n return this._getItems().indexOf(element);\n }\n _setActiveIndicatorElement(index) {\n if (!this._indicatorsElement) {\n return;\n }\n const activeIndicator = SelectorEngine.findOne(SELECTOR_ACTIVE, this._indicatorsElement);\n activeIndicator.classList.remove(CLASS_NAME_ACTIVE$2);\n activeIndicator.removeAttribute('aria-current');\n const newActiveIndicator = SelectorEngine.findOne(`[data-bs-slide-to=\"${index}\"]`, this._indicatorsElement);\n if (newActiveIndicator) {\n newActiveIndicator.classList.add(CLASS_NAME_ACTIVE$2);\n newActiveIndicator.setAttribute('aria-current', 'true');\n }\n }\n _updateInterval() {\n const element = this._activeElement || this._getActive();\n if (!element) {\n return;\n }\n const elementInterval = Number.parseInt(element.getAttribute('data-bs-interval'), 10);\n this._config.interval = elementInterval || this._config.defaultInterval;\n }\n _slide(order, element = null) {\n if (this._isSliding) {\n return;\n }\n const activeElement = this._getActive();\n const isNext = order === ORDER_NEXT;\n const nextElement = element || getNextActiveElement(this._getItems(), activeElement, isNext, this._config.wrap);\n if (nextElement === activeElement) {\n return;\n }\n const nextElementIndex = this._getItemIndex(nextElement);\n const triggerEvent = eventName => {\n return EventHandler.trigger(this._element, eventName, {\n relatedTarget: nextElement,\n direction: this._orderToDirection(order),\n from: this._getItemIndex(activeElement),\n to: nextElementIndex\n });\n };\n const slideEvent = triggerEvent(EVENT_SLIDE);\n if (slideEvent.defaultPrevented) {\n return;\n }\n if (!activeElement || !nextElement) {\n // Some weirdness is happening, so we bail\n // TODO: change tests that use empty divs to avoid this check\n return;\n }\n const isCycling = Boolean(this._interval);\n this.pause();\n this._isSliding = true;\n this._setActiveIndicatorElement(nextElementIndex);\n this._activeElement = nextElement;\n const directionalClassName = isNext ? CLASS_NAME_START : CLASS_NAME_END;\n const orderClassName = isNext ? CLASS_NAME_NEXT : CLASS_NAME_PREV;\n nextElement.classList.add(orderClassName);\n reflow(nextElement);\n activeElement.classList.add(directionalClassName);\n nextElement.classList.add(directionalClassName);\n const completeCallBack = () => {\n nextElement.classList.remove(directionalClassName, orderClassName);\n nextElement.classList.add(CLASS_NAME_ACTIVE$2);\n activeElement.classList.remove(CLASS_NAME_ACTIVE$2, orderClassName, directionalClassName);\n this._isSliding = false;\n triggerEvent(EVENT_SLID);\n };\n this._queueCallback(completeCallBack, activeElement, this._isAnimated());\n if (isCycling) {\n this.cycle();\n }\n }\n _isAnimated() {\n return this._element.classList.contains(CLASS_NAME_SLIDE);\n }\n _getActive() {\n return SelectorEngine.findOne(SELECTOR_ACTIVE_ITEM, this._element);\n }\n _getItems() {\n return SelectorEngine.find(SELECTOR_ITEM, this._element);\n }\n _clearInterval() {\n if (this._interval) {\n clearInterval(this._interval);\n this._interval = null;\n }\n }\n _directionToOrder(direction) {\n if (isRTL()) {\n return direction === DIRECTION_LEFT ? ORDER_PREV : ORDER_NEXT;\n }\n return direction === DIRECTION_LEFT ? ORDER_NEXT : ORDER_PREV;\n }\n _orderToDirection(order) {\n if (isRTL()) {\n return order === ORDER_PREV ? DIRECTION_LEFT : DIRECTION_RIGHT;\n }\n return order === ORDER_PREV ? DIRECTION_RIGHT : DIRECTION_LEFT;\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Carousel.getOrCreateInstance(this, config);\n if (typeof config === 'number') {\n data.to(config);\n return;\n }\n if (typeof config === 'string') {\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n }\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$5, SELECTOR_DATA_SLIDE, function (event) {\n const target = SelectorEngine.getElementFromSelector(this);\n if (!target || !target.classList.contains(CLASS_NAME_CAROUSEL)) {\n return;\n }\n event.preventDefault();\n const carousel = Carousel.getOrCreateInstance(target);\n const slideIndex = this.getAttribute('data-bs-slide-to');\n if (slideIndex) {\n carousel.to(slideIndex);\n carousel._maybeEnableCycle();\n return;\n }\n if (Manipulator.getDataAttribute(this, 'slide') === 'next') {\n carousel.next();\n carousel._maybeEnableCycle();\n return;\n }\n carousel.prev();\n carousel._maybeEnableCycle();\n});\nEventHandler.on(window, EVENT_LOAD_DATA_API$3, () => {\n const carousels = SelectorEngine.find(SELECTOR_DATA_RIDE);\n for (const carousel of carousels) {\n Carousel.getOrCreateInstance(carousel);\n }\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Carousel);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap collapse.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$b = 'collapse';\nconst DATA_KEY$7 = 'bs.collapse';\nconst EVENT_KEY$7 = `.${DATA_KEY$7}`;\nconst DATA_API_KEY$4 = '.data-api';\nconst EVENT_SHOW$6 = `show${EVENT_KEY$7}`;\nconst EVENT_SHOWN$6 = `shown${EVENT_KEY$7}`;\nconst EVENT_HIDE$6 = `hide${EVENT_KEY$7}`;\nconst EVENT_HIDDEN$6 = `hidden${EVENT_KEY$7}`;\nconst EVENT_CLICK_DATA_API$4 = `click${EVENT_KEY$7}${DATA_API_KEY$4}`;\nconst CLASS_NAME_SHOW$7 = 'show';\nconst CLASS_NAME_COLLAPSE = 'collapse';\nconst CLASS_NAME_COLLAPSING = 'collapsing';\nconst CLASS_NAME_COLLAPSED = 'collapsed';\nconst CLASS_NAME_DEEPER_CHILDREN = `:scope .${CLASS_NAME_COLLAPSE} .${CLASS_NAME_COLLAPSE}`;\nconst CLASS_NAME_HORIZONTAL = 'collapse-horizontal';\nconst WIDTH = 'width';\nconst HEIGHT = 'height';\nconst SELECTOR_ACTIVES = '.collapse.show, .collapse.collapsing';\nconst SELECTOR_DATA_TOGGLE$4 = '[data-bs-toggle=\"collapse\"]';\nconst Default$a = {\n parent: null,\n toggle: true\n};\nconst DefaultType$a = {\n parent: '(null|element)',\n toggle: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Collapse extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._isTransitioning = false;\n this._triggerArray = [];\n const toggleList = SelectorEngine.find(SELECTOR_DATA_TOGGLE$4);\n for (const elem of toggleList) {\n const selector = SelectorEngine.getSelectorFromElement(elem);\n const filterElement = SelectorEngine.find(selector).filter(foundElement => foundElement === this._element);\n if (selector !== null && filterElement.length) {\n this._triggerArray.push(elem);\n }\n }\n this._initializeChildren();\n if (!this._config.parent) {\n this._addAriaAndCollapsedClass(this._triggerArray, this._isShown());\n }\n if (this._config.toggle) {\n this.toggle();\n }\n }\n\n // Getters\n static get Default() {\n return Default$a;\n }\n static get DefaultType() {\n return DefaultType$a;\n }\n static get NAME() {\n return NAME$b;\n }\n\n // Public\n toggle() {\n if (this._isShown()) {\n this.hide();\n } else {\n this.show();\n }\n }\n show() {\n if (this._isTransitioning || this._isShown()) {\n return;\n }\n let activeChildren = [];\n\n // find active children\n if (this._config.parent) {\n activeChildren = this._getFirstLevelChildren(SELECTOR_ACTIVES).filter(element => element !== this._element).map(element => Collapse.getOrCreateInstance(element, {\n toggle: false\n }));\n }\n if (activeChildren.length && activeChildren[0]._isTransitioning) {\n return;\n }\n const startEvent = EventHandler.trigger(this._element, EVENT_SHOW$6);\n if (startEvent.defaultPrevented) {\n return;\n }\n for (const activeInstance of activeChildren) {\n activeInstance.hide();\n }\n const dimension = this._getDimension();\n this._element.classList.remove(CLASS_NAME_COLLAPSE);\n this._element.classList.add(CLASS_NAME_COLLAPSING);\n this._element.style[dimension] = 0;\n this._addAriaAndCollapsedClass(this._triggerArray, true);\n this._isTransitioning = true;\n const complete = () => {\n this._isTransitioning = false;\n this._element.classList.remove(CLASS_NAME_COLLAPSING);\n this._element.classList.add(CLASS_NAME_COLLAPSE, CLASS_NAME_SHOW$7);\n this._element.style[dimension] = '';\n EventHandler.trigger(this._element, EVENT_SHOWN$6);\n };\n const capitalizedDimension = dimension[0].toUpperCase() + dimension.slice(1);\n const scrollSize = `scroll${capitalizedDimension}`;\n this._queueCallback(complete, this._element, true);\n this._element.style[dimension] = `${this._element[scrollSize]}px`;\n }\n hide() {\n if (this._isTransitioning || !this._isShown()) {\n return;\n }\n const startEvent = EventHandler.trigger(this._element, EVENT_HIDE$6);\n if (startEvent.defaultPrevented) {\n return;\n }\n const dimension = this._getDimension();\n this._element.style[dimension] = `${this._element.getBoundingClientRect()[dimension]}px`;\n reflow(this._element);\n this._element.classList.add(CLASS_NAME_COLLAPSING);\n this._element.classList.remove(CLASS_NAME_COLLAPSE, CLASS_NAME_SHOW$7);\n for (const trigger of this._triggerArray) {\n const element = SelectorEngine.getElementFromSelector(trigger);\n if (element && !this._isShown(element)) {\n this._addAriaAndCollapsedClass([trigger], false);\n }\n }\n this._isTransitioning = true;\n const complete = () => {\n this._isTransitioning = false;\n this._element.classList.remove(CLASS_NAME_COLLAPSING);\n this._element.classList.add(CLASS_NAME_COLLAPSE);\n EventHandler.trigger(this._element, EVENT_HIDDEN$6);\n };\n this._element.style[dimension] = '';\n this._queueCallback(complete, this._element, true);\n }\n _isShown(element = this._element) {\n return element.classList.contains(CLASS_NAME_SHOW$7);\n }\n\n // Private\n _configAfterMerge(config) {\n config.toggle = Boolean(config.toggle); // Coerce string values\n config.parent = getElement(config.parent);\n return config;\n }\n _getDimension() {\n return this._element.classList.contains(CLASS_NAME_HORIZONTAL) ? WIDTH : HEIGHT;\n }\n _initializeChildren() {\n if (!this._config.parent) {\n return;\n }\n const children = this._getFirstLevelChildren(SELECTOR_DATA_TOGGLE$4);\n for (const element of children) {\n const selected = SelectorEngine.getElementFromSelector(element);\n if (selected) {\n this._addAriaAndCollapsedClass([element], this._isShown(selected));\n }\n }\n }\n _getFirstLevelChildren(selector) {\n const children = SelectorEngine.find(CLASS_NAME_DEEPER_CHILDREN, this._config.parent);\n // remove children if greater depth\n return SelectorEngine.find(selector, this._config.parent).filter(element => !children.includes(element));\n }\n _addAriaAndCollapsedClass(triggerArray, isOpen) {\n if (!triggerArray.length) {\n return;\n }\n for (const element of triggerArray) {\n element.classList.toggle(CLASS_NAME_COLLAPSED, !isOpen);\n element.setAttribute('aria-expanded', isOpen);\n }\n }\n\n // Static\n static jQueryInterface(config) {\n const _config = {};\n if (typeof config === 'string' && /show|hide/.test(config)) {\n _config.toggle = false;\n }\n return this.each(function () {\n const data = Collapse.getOrCreateInstance(this, _config);\n if (typeof config === 'string') {\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n }\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$4, SELECTOR_DATA_TOGGLE$4, function (event) {\n // preventDefault only for elements (which change the URL) not inside the collapsible element\n if (event.target.tagName === 'A' || event.delegateTarget && event.delegateTarget.tagName === 'A') {\n event.preventDefault();\n }\n for (const element of SelectorEngine.getMultipleElementsFromSelector(this)) {\n Collapse.getOrCreateInstance(element, {\n toggle: false\n }).toggle();\n }\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Collapse);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dropdown.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$a = 'dropdown';\nconst DATA_KEY$6 = 'bs.dropdown';\nconst EVENT_KEY$6 = `.${DATA_KEY$6}`;\nconst DATA_API_KEY$3 = '.data-api';\nconst ESCAPE_KEY$2 = 'Escape';\nconst TAB_KEY$1 = 'Tab';\nconst ARROW_UP_KEY$1 = 'ArrowUp';\nconst ARROW_DOWN_KEY$1 = 'ArrowDown';\nconst RIGHT_MOUSE_BUTTON = 2; // MouseEvent.button value for the secondary button, usually the right button\n\nconst EVENT_HIDE$5 = `hide${EVENT_KEY$6}`;\nconst EVENT_HIDDEN$5 = `hidden${EVENT_KEY$6}`;\nconst EVENT_SHOW$5 = `show${EVENT_KEY$6}`;\nconst EVENT_SHOWN$5 = `shown${EVENT_KEY$6}`;\nconst EVENT_CLICK_DATA_API$3 = `click${EVENT_KEY$6}${DATA_API_KEY$3}`;\nconst EVENT_KEYDOWN_DATA_API = `keydown${EVENT_KEY$6}${DATA_API_KEY$3}`;\nconst EVENT_KEYUP_DATA_API = `keyup${EVENT_KEY$6}${DATA_API_KEY$3}`;\nconst CLASS_NAME_SHOW$6 = 'show';\nconst CLASS_NAME_DROPUP = 'dropup';\nconst CLASS_NAME_DROPEND = 'dropend';\nconst CLASS_NAME_DROPSTART = 'dropstart';\nconst CLASS_NAME_DROPUP_CENTER = 'dropup-center';\nconst CLASS_NAME_DROPDOWN_CENTER = 'dropdown-center';\nconst SELECTOR_DATA_TOGGLE$3 = '[data-bs-toggle=\"dropdown\"]:not(.disabled):not(:disabled)';\nconst SELECTOR_DATA_TOGGLE_SHOWN = `${SELECTOR_DATA_TOGGLE$3}.${CLASS_NAME_SHOW$6}`;\nconst SELECTOR_MENU = '.dropdown-menu';\nconst SELECTOR_NAVBAR = '.navbar';\nconst SELECTOR_NAVBAR_NAV = '.navbar-nav';\nconst SELECTOR_VISIBLE_ITEMS = '.dropdown-menu .dropdown-item:not(.disabled):not(:disabled)';\nconst PLACEMENT_TOP = isRTL() ? 'top-end' : 'top-start';\nconst PLACEMENT_TOPEND = isRTL() ? 'top-start' : 'top-end';\nconst PLACEMENT_BOTTOM = isRTL() ? 'bottom-end' : 'bottom-start';\nconst PLACEMENT_BOTTOMEND = isRTL() ? 'bottom-start' : 'bottom-end';\nconst PLACEMENT_RIGHT = isRTL() ? 'left-start' : 'right-start';\nconst PLACEMENT_LEFT = isRTL() ? 'right-start' : 'left-start';\nconst PLACEMENT_TOPCENTER = 'top';\nconst PLACEMENT_BOTTOMCENTER = 'bottom';\nconst Default$9 = {\n autoClose: true,\n boundary: 'clippingParents',\n display: 'dynamic',\n offset: [0, 2],\n popperConfig: null,\n reference: 'toggle'\n};\nconst DefaultType$9 = {\n autoClose: '(boolean|string)',\n boundary: '(string|element)',\n display: 'string',\n offset: '(array|string|function)',\n popperConfig: '(null|object|function)',\n reference: '(string|element|object)'\n};\n\n/**\n * Class definition\n */\n\nclass Dropdown extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._popper = null;\n this._parent = this._element.parentNode; // dropdown wrapper\n // TODO: v6 revert #37011 & change markup https://getbootstrap.com/docs/5.3/forms/input-group/\n this._menu = SelectorEngine.next(this._element, SELECTOR_MENU)[0] || SelectorEngine.prev(this._element, SELECTOR_MENU)[0] || SelectorEngine.findOne(SELECTOR_MENU, this._parent);\n this._inNavbar = this._detectNavbar();\n }\n\n // Getters\n static get Default() {\n return Default$9;\n }\n static get DefaultType() {\n return DefaultType$9;\n }\n static get NAME() {\n return NAME$a;\n }\n\n // Public\n toggle() {\n return this._isShown() ? this.hide() : this.show();\n }\n show() {\n if (isDisabled(this._element) || this._isShown()) {\n return;\n }\n const relatedTarget = {\n relatedTarget: this._element\n };\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW$5, relatedTarget);\n if (showEvent.defaultPrevented) {\n return;\n }\n this._createPopper();\n\n // If this is a touch-enabled device we add extra\n // empty mouseover listeners to the body's immediate children;\n // only needed because of broken event delegation on iOS\n // https://www.quirksmode.org/blog/archives/2014/02/mouse_event_bub.html\n if ('ontouchstart' in document.documentElement && !this._parent.closest(SELECTOR_NAVBAR_NAV)) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.on(element, 'mouseover', noop);\n }\n }\n this._element.focus();\n this._element.setAttribute('aria-expanded', true);\n this._menu.classList.add(CLASS_NAME_SHOW$6);\n this._element.classList.add(CLASS_NAME_SHOW$6);\n EventHandler.trigger(this._element, EVENT_SHOWN$5, relatedTarget);\n }\n hide() {\n if (isDisabled(this._element) || !this._isShown()) {\n return;\n }\n const relatedTarget = {\n relatedTarget: this._element\n };\n this._completeHide(relatedTarget);\n }\n dispose() {\n if (this._popper) {\n this._popper.destroy();\n }\n super.dispose();\n }\n update() {\n this._inNavbar = this._detectNavbar();\n if (this._popper) {\n this._popper.update();\n }\n }\n\n // Private\n _completeHide(relatedTarget) {\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE$5, relatedTarget);\n if (hideEvent.defaultPrevented) {\n return;\n }\n\n // If this is a touch-enabled device we remove the extra\n // empty mouseover listeners we added for iOS support\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.off(element, 'mouseover', noop);\n }\n }\n if (this._popper) {\n this._popper.destroy();\n }\n this._menu.classList.remove(CLASS_NAME_SHOW$6);\n this._element.classList.remove(CLASS_NAME_SHOW$6);\n this._element.setAttribute('aria-expanded', 'false');\n Manipulator.removeDataAttribute(this._menu, 'popper');\n EventHandler.trigger(this._element, EVENT_HIDDEN$5, relatedTarget);\n }\n _getConfig(config) {\n config = super._getConfig(config);\n if (typeof config.reference === 'object' && !isElement(config.reference) && typeof config.reference.getBoundingClientRect !== 'function') {\n // Popper virtual elements require a getBoundingClientRect method\n throw new TypeError(`${NAME$a.toUpperCase()}: Option \"reference\" provided type \"object\" without a required \"getBoundingClientRect\" method.`);\n }\n return config;\n }\n _createPopper() {\n if (typeof Popper === 'undefined') {\n throw new TypeError('Bootstrap\\'s dropdowns require Popper (https://popper.js.org)');\n }\n let referenceElement = this._element;\n if (this._config.reference === 'parent') {\n referenceElement = this._parent;\n } else if (isElement(this._config.reference)) {\n referenceElement = getElement(this._config.reference);\n } else if (typeof this._config.reference === 'object') {\n referenceElement = this._config.reference;\n }\n const popperConfig = this._getPopperConfig();\n this._popper = Popper.createPopper(referenceElement, this._menu, popperConfig);\n }\n _isShown() {\n return this._menu.classList.contains(CLASS_NAME_SHOW$6);\n }\n _getPlacement() {\n const parentDropdown = this._parent;\n if (parentDropdown.classList.contains(CLASS_NAME_DROPEND)) {\n return PLACEMENT_RIGHT;\n }\n if (parentDropdown.classList.contains(CLASS_NAME_DROPSTART)) {\n return PLACEMENT_LEFT;\n }\n if (parentDropdown.classList.contains(CLASS_NAME_DROPUP_CENTER)) {\n return PLACEMENT_TOPCENTER;\n }\n if (parentDropdown.classList.contains(CLASS_NAME_DROPDOWN_CENTER)) {\n return PLACEMENT_BOTTOMCENTER;\n }\n\n // We need to trim the value because custom properties can also include spaces\n const isEnd = getComputedStyle(this._menu).getPropertyValue('--bs-position').trim() === 'end';\n if (parentDropdown.classList.contains(CLASS_NAME_DROPUP)) {\n return isEnd ? PLACEMENT_TOPEND : PLACEMENT_TOP;\n }\n return isEnd ? PLACEMENT_BOTTOMEND : PLACEMENT_BOTTOM;\n }\n _detectNavbar() {\n return this._element.closest(SELECTOR_NAVBAR) !== null;\n }\n _getOffset() {\n const {\n offset\n } = this._config;\n if (typeof offset === 'string') {\n return offset.split(',').map(value => Number.parseInt(value, 10));\n }\n if (typeof offset === 'function') {\n return popperData => offset(popperData, this._element);\n }\n return offset;\n }\n _getPopperConfig() {\n const defaultBsPopperConfig = {\n placement: this._getPlacement(),\n modifiers: [{\n name: 'preventOverflow',\n options: {\n boundary: this._config.boundary\n }\n }, {\n name: 'offset',\n options: {\n offset: this._getOffset()\n }\n }]\n };\n\n // Disable Popper if we have a static display or Dropdown is in Navbar\n if (this._inNavbar || this._config.display === 'static') {\n Manipulator.setDataAttribute(this._menu, 'popper', 'static'); // TODO: v6 remove\n defaultBsPopperConfig.modifiers = [{\n name: 'applyStyles',\n enabled: false\n }];\n }\n return {\n ...defaultBsPopperConfig,\n ...execute(this._config.popperConfig, [defaultBsPopperConfig])\n };\n }\n _selectMenuItem({\n key,\n target\n }) {\n const items = SelectorEngine.find(SELECTOR_VISIBLE_ITEMS, this._menu).filter(element => isVisible(element));\n if (!items.length) {\n return;\n }\n\n // if target isn't included in items (e.g. when expanding the dropdown)\n // allow cycling to get the last item in case key equals ARROW_UP_KEY\n getNextActiveElement(items, target, key === ARROW_DOWN_KEY$1, !items.includes(target)).focus();\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Dropdown.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n });\n }\n static clearMenus(event) {\n if (event.button === RIGHT_MOUSE_BUTTON || event.type === 'keyup' && event.key !== TAB_KEY$1) {\n return;\n }\n const openToggles = SelectorEngine.find(SELECTOR_DATA_TOGGLE_SHOWN);\n for (const toggle of openToggles) {\n const context = Dropdown.getInstance(toggle);\n if (!context || context._config.autoClose === false) {\n continue;\n }\n const composedPath = event.composedPath();\n const isMenuTarget = composedPath.includes(context._menu);\n if (composedPath.includes(context._element) || context._config.autoClose === 'inside' && !isMenuTarget || context._config.autoClose === 'outside' && isMenuTarget) {\n continue;\n }\n\n // Tab navigation through the dropdown menu or events from contained inputs shouldn't close the menu\n if (context._menu.contains(event.target) && (event.type === 'keyup' && event.key === TAB_KEY$1 || /input|select|option|textarea|form/i.test(event.target.tagName))) {\n continue;\n }\n const relatedTarget = {\n relatedTarget: context._element\n };\n if (event.type === 'click') {\n relatedTarget.clickEvent = event;\n }\n context._completeHide(relatedTarget);\n }\n }\n static dataApiKeydownHandler(event) {\n // If not an UP | DOWN | ESCAPE key => not a dropdown command\n // If input/textarea && if key is other than ESCAPE => not a dropdown command\n\n const isInput = /input|textarea/i.test(event.target.tagName);\n const isEscapeEvent = event.key === ESCAPE_KEY$2;\n const isUpOrDownEvent = [ARROW_UP_KEY$1, ARROW_DOWN_KEY$1].includes(event.key);\n if (!isUpOrDownEvent && !isEscapeEvent) {\n return;\n }\n if (isInput && !isEscapeEvent) {\n return;\n }\n event.preventDefault();\n\n // TODO: v6 revert #37011 & change markup https://getbootstrap.com/docs/5.3/forms/input-group/\n const getToggleButton = this.matches(SELECTOR_DATA_TOGGLE$3) ? this : SelectorEngine.prev(this, SELECTOR_DATA_TOGGLE$3)[0] || SelectorEngine.next(this, SELECTOR_DATA_TOGGLE$3)[0] || SelectorEngine.findOne(SELECTOR_DATA_TOGGLE$3, event.delegateTarget.parentNode);\n const instance = Dropdown.getOrCreateInstance(getToggleButton);\n if (isUpOrDownEvent) {\n event.stopPropagation();\n instance.show();\n instance._selectMenuItem(event);\n return;\n }\n if (instance._isShown()) {\n // else is escape and we check if it is shown\n event.stopPropagation();\n instance.hide();\n getToggleButton.focus();\n }\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_KEYDOWN_DATA_API, SELECTOR_DATA_TOGGLE$3, Dropdown.dataApiKeydownHandler);\nEventHandler.on(document, EVENT_KEYDOWN_DATA_API, SELECTOR_MENU, Dropdown.dataApiKeydownHandler);\nEventHandler.on(document, EVENT_CLICK_DATA_API$3, Dropdown.clearMenus);\nEventHandler.on(document, EVENT_KEYUP_DATA_API, Dropdown.clearMenus);\nEventHandler.on(document, EVENT_CLICK_DATA_API$3, SELECTOR_DATA_TOGGLE$3, function (event) {\n event.preventDefault();\n Dropdown.getOrCreateInstance(this).toggle();\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Dropdown);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/backdrop.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$9 = 'backdrop';\nconst CLASS_NAME_FADE$4 = 'fade';\nconst CLASS_NAME_SHOW$5 = 'show';\nconst EVENT_MOUSEDOWN = `mousedown.bs.${NAME$9}`;\nconst Default$8 = {\n className: 'modal-backdrop',\n clickCallback: null,\n isAnimated: false,\n isVisible: true,\n // if false, we use the backdrop helper without adding any element to the dom\n rootElement: 'body' // give the choice to place backdrop under different elements\n};\nconst DefaultType$8 = {\n className: 'string',\n clickCallback: '(function|null)',\n isAnimated: 'boolean',\n isVisible: 'boolean',\n rootElement: '(element|string)'\n};\n\n/**\n * Class definition\n */\n\nclass Backdrop extends Config {\n constructor(config) {\n super();\n this._config = this._getConfig(config);\n this._isAppended = false;\n this._element = null;\n }\n\n // Getters\n static get Default() {\n return Default$8;\n }\n static get DefaultType() {\n return DefaultType$8;\n }\n static get NAME() {\n return NAME$9;\n }\n\n // Public\n show(callback) {\n if (!this._config.isVisible) {\n execute(callback);\n return;\n }\n this._append();\n const element = this._getElement();\n if (this._config.isAnimated) {\n reflow(element);\n }\n element.classList.add(CLASS_NAME_SHOW$5);\n this._emulateAnimation(() => {\n execute(callback);\n });\n }\n hide(callback) {\n if (!this._config.isVisible) {\n execute(callback);\n return;\n }\n this._getElement().classList.remove(CLASS_NAME_SHOW$5);\n this._emulateAnimation(() => {\n this.dispose();\n execute(callback);\n });\n }\n dispose() {\n if (!this._isAppended) {\n return;\n }\n EventHandler.off(this._element, EVENT_MOUSEDOWN);\n this._element.remove();\n this._isAppended = false;\n }\n\n // Private\n _getElement() {\n if (!this._element) {\n const backdrop = document.createElement('div');\n backdrop.className = this._config.className;\n if (this._config.isAnimated) {\n backdrop.classList.add(CLASS_NAME_FADE$4);\n }\n this._element = backdrop;\n }\n return this._element;\n }\n _configAfterMerge(config) {\n // use getElement() with the default \"body\" to get a fresh Element on each instantiation\n config.rootElement = getElement(config.rootElement);\n return config;\n }\n _append() {\n if (this._isAppended) {\n return;\n }\n const element = this._getElement();\n this._config.rootElement.append(element);\n EventHandler.on(element, EVENT_MOUSEDOWN, () => {\n execute(this._config.clickCallback);\n });\n this._isAppended = true;\n }\n _emulateAnimation(callback) {\n executeAfterTransition(callback, this._getElement(), this._config.isAnimated);\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/focustrap.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$8 = 'focustrap';\nconst DATA_KEY$5 = 'bs.focustrap';\nconst EVENT_KEY$5 = `.${DATA_KEY$5}`;\nconst EVENT_FOCUSIN$2 = `focusin${EVENT_KEY$5}`;\nconst EVENT_KEYDOWN_TAB = `keydown.tab${EVENT_KEY$5}`;\nconst TAB_KEY = 'Tab';\nconst TAB_NAV_FORWARD = 'forward';\nconst TAB_NAV_BACKWARD = 'backward';\nconst Default$7 = {\n autofocus: true,\n trapElement: null // The element to trap focus inside of\n};\nconst DefaultType$7 = {\n autofocus: 'boolean',\n trapElement: 'element'\n};\n\n/**\n * Class definition\n */\n\nclass FocusTrap extends Config {\n constructor(config) {\n super();\n this._config = this._getConfig(config);\n this._isActive = false;\n this._lastTabNavDirection = null;\n }\n\n // Getters\n static get Default() {\n return Default$7;\n }\n static get DefaultType() {\n return DefaultType$7;\n }\n static get NAME() {\n return NAME$8;\n }\n\n // Public\n activate() {\n if (this._isActive) {\n return;\n }\n if (this._config.autofocus) {\n this._config.trapElement.focus();\n }\n EventHandler.off(document, EVENT_KEY$5); // guard against infinite focus loop\n EventHandler.on(document, EVENT_FOCUSIN$2, event => this._handleFocusin(event));\n EventHandler.on(document, EVENT_KEYDOWN_TAB, event => this._handleKeydown(event));\n this._isActive = true;\n }\n deactivate() {\n if (!this._isActive) {\n return;\n }\n this._isActive = false;\n EventHandler.off(document, EVENT_KEY$5);\n }\n\n // Private\n _handleFocusin(event) {\n const {\n trapElement\n } = this._config;\n if (event.target === document || event.target === trapElement || trapElement.contains(event.target)) {\n return;\n }\n const elements = SelectorEngine.focusableChildren(trapElement);\n if (elements.length === 0) {\n trapElement.focus();\n } else if (this._lastTabNavDirection === TAB_NAV_BACKWARD) {\n elements[elements.length - 1].focus();\n } else {\n elements[0].focus();\n }\n }\n _handleKeydown(event) {\n if (event.key !== TAB_KEY) {\n return;\n }\n this._lastTabNavDirection = event.shiftKey ? TAB_NAV_BACKWARD : TAB_NAV_FORWARD;\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/scrollBar.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst SELECTOR_FIXED_CONTENT = '.fixed-top, .fixed-bottom, .is-fixed, .sticky-top';\nconst SELECTOR_STICKY_CONTENT = '.sticky-top';\nconst PROPERTY_PADDING = 'padding-right';\nconst PROPERTY_MARGIN = 'margin-right';\n\n/**\n * Class definition\n */\n\nclass ScrollBarHelper {\n constructor() {\n this._element = document.body;\n }\n\n // Public\n getWidth() {\n // https://developer.mozilla.org/en-US/docs/Web/API/Window/innerWidth#usage_notes\n const documentWidth = document.documentElement.clientWidth;\n return Math.abs(window.innerWidth - documentWidth);\n }\n hide() {\n const width = this.getWidth();\n this._disableOverFlow();\n // give padding to element to balance the hidden scrollbar width\n this._setElementAttributes(this._element, PROPERTY_PADDING, calculatedValue => calculatedValue + width);\n // trick: We adjust positive paddingRight and negative marginRight to sticky-top elements to keep showing fullwidth\n this._setElementAttributes(SELECTOR_FIXED_CONTENT, PROPERTY_PADDING, calculatedValue => calculatedValue + width);\n this._setElementAttributes(SELECTOR_STICKY_CONTENT, PROPERTY_MARGIN, calculatedValue => calculatedValue - width);\n }\n reset() {\n this._resetElementAttributes(this._element, 'overflow');\n this._resetElementAttributes(this._element, PROPERTY_PADDING);\n this._resetElementAttributes(SELECTOR_FIXED_CONTENT, PROPERTY_PADDING);\n this._resetElementAttributes(SELECTOR_STICKY_CONTENT, PROPERTY_MARGIN);\n }\n isOverflowing() {\n return this.getWidth() > 0;\n }\n\n // Private\n _disableOverFlow() {\n this._saveInitialAttribute(this._element, 'overflow');\n this._element.style.overflow = 'hidden';\n }\n _setElementAttributes(selector, styleProperty, callback) {\n const scrollbarWidth = this.getWidth();\n const manipulationCallBack = element => {\n if (element !== this._element && window.innerWidth > element.clientWidth + scrollbarWidth) {\n return;\n }\n this._saveInitialAttribute(element, styleProperty);\n const calculatedValue = window.getComputedStyle(element).getPropertyValue(styleProperty);\n element.style.setProperty(styleProperty, `${callback(Number.parseFloat(calculatedValue))}px`);\n };\n this._applyManipulationCallback(selector, manipulationCallBack);\n }\n _saveInitialAttribute(element, styleProperty) {\n const actualValue = element.style.getPropertyValue(styleProperty);\n if (actualValue) {\n Manipulator.setDataAttribute(element, styleProperty, actualValue);\n }\n }\n _resetElementAttributes(selector, styleProperty) {\n const manipulationCallBack = element => {\n const value = Manipulator.getDataAttribute(element, styleProperty);\n // We only want to remove the property if the value is `null`; the value can also be zero\n if (value === null) {\n element.style.removeProperty(styleProperty);\n return;\n }\n Manipulator.removeDataAttribute(element, styleProperty);\n element.style.setProperty(styleProperty, value);\n };\n this._applyManipulationCallback(selector, manipulationCallBack);\n }\n _applyManipulationCallback(selector, callBack) {\n if (isElement(selector)) {\n callBack(selector);\n return;\n }\n for (const sel of SelectorEngine.find(selector, this._element)) {\n callBack(sel);\n }\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap modal.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$7 = 'modal';\nconst DATA_KEY$4 = 'bs.modal';\nconst EVENT_KEY$4 = `.${DATA_KEY$4}`;\nconst DATA_API_KEY$2 = '.data-api';\nconst ESCAPE_KEY$1 = 'Escape';\nconst EVENT_HIDE$4 = `hide${EVENT_KEY$4}`;\nconst EVENT_HIDE_PREVENTED$1 = `hidePrevented${EVENT_KEY$4}`;\nconst EVENT_HIDDEN$4 = `hidden${EVENT_KEY$4}`;\nconst EVENT_SHOW$4 = `show${EVENT_KEY$4}`;\nconst EVENT_SHOWN$4 = `shown${EVENT_KEY$4}`;\nconst EVENT_RESIZE$1 = `resize${EVENT_KEY$4}`;\nconst EVENT_CLICK_DISMISS = `click.dismiss${EVENT_KEY$4}`;\nconst EVENT_MOUSEDOWN_DISMISS = `mousedown.dismiss${EVENT_KEY$4}`;\nconst EVENT_KEYDOWN_DISMISS$1 = `keydown.dismiss${EVENT_KEY$4}`;\nconst EVENT_CLICK_DATA_API$2 = `click${EVENT_KEY$4}${DATA_API_KEY$2}`;\nconst CLASS_NAME_OPEN = 'modal-open';\nconst CLASS_NAME_FADE$3 = 'fade';\nconst CLASS_NAME_SHOW$4 = 'show';\nconst CLASS_NAME_STATIC = 'modal-static';\nconst OPEN_SELECTOR$1 = '.modal.show';\nconst SELECTOR_DIALOG = '.modal-dialog';\nconst SELECTOR_MODAL_BODY = '.modal-body';\nconst SELECTOR_DATA_TOGGLE$2 = '[data-bs-toggle=\"modal\"]';\nconst Default$6 = {\n backdrop: true,\n focus: true,\n keyboard: true\n};\nconst DefaultType$6 = {\n backdrop: '(boolean|string)',\n focus: 'boolean',\n keyboard: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Modal extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._dialog = SelectorEngine.findOne(SELECTOR_DIALOG, this._element);\n this._backdrop = this._initializeBackDrop();\n this._focustrap = this._initializeFocusTrap();\n this._isShown = false;\n this._isTransitioning = false;\n this._scrollBar = new ScrollBarHelper();\n this._addEventListeners();\n }\n\n // Getters\n static get Default() {\n return Default$6;\n }\n static get DefaultType() {\n return DefaultType$6;\n }\n static get NAME() {\n return NAME$7;\n }\n\n // Public\n toggle(relatedTarget) {\n return this._isShown ? this.hide() : this.show(relatedTarget);\n }\n show(relatedTarget) {\n if (this._isShown || this._isTransitioning) {\n return;\n }\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW$4, {\n relatedTarget\n });\n if (showEvent.defaultPrevented) {\n return;\n }\n this._isShown = true;\n this._isTransitioning = true;\n this._scrollBar.hide();\n document.body.classList.add(CLASS_NAME_OPEN);\n this._adjustDialog();\n this._backdrop.show(() => this._showElement(relatedTarget));\n }\n hide() {\n if (!this._isShown || this._isTransitioning) {\n return;\n }\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE$4);\n if (hideEvent.defaultPrevented) {\n return;\n }\n this._isShown = false;\n this._isTransitioning = true;\n this._focustrap.deactivate();\n this._element.classList.remove(CLASS_NAME_SHOW$4);\n this._queueCallback(() => this._hideModal(), this._element, this._isAnimated());\n }\n dispose() {\n EventHandler.off(window, EVENT_KEY$4);\n EventHandler.off(this._dialog, EVENT_KEY$4);\n this._backdrop.dispose();\n this._focustrap.deactivate();\n super.dispose();\n }\n handleUpdate() {\n this._adjustDialog();\n }\n\n // Private\n _initializeBackDrop() {\n return new Backdrop({\n isVisible: Boolean(this._config.backdrop),\n // 'static' option will be translated to true, and booleans will keep their value,\n isAnimated: this._isAnimated()\n });\n }\n _initializeFocusTrap() {\n return new FocusTrap({\n trapElement: this._element\n });\n }\n _showElement(relatedTarget) {\n // try to append dynamic modal\n if (!document.body.contains(this._element)) {\n document.body.append(this._element);\n }\n this._element.style.display = 'block';\n this._element.removeAttribute('aria-hidden');\n this._element.setAttribute('aria-modal', true);\n this._element.setAttribute('role', 'dialog');\n this._element.scrollTop = 0;\n const modalBody = SelectorEngine.findOne(SELECTOR_MODAL_BODY, this._dialog);\n if (modalBody) {\n modalBody.scrollTop = 0;\n }\n reflow(this._element);\n this._element.classList.add(CLASS_NAME_SHOW$4);\n const transitionComplete = () => {\n if (this._config.focus) {\n this._focustrap.activate();\n }\n this._isTransitioning = false;\n EventHandler.trigger(this._element, EVENT_SHOWN$4, {\n relatedTarget\n });\n };\n this._queueCallback(transitionComplete, this._dialog, this._isAnimated());\n }\n _addEventListeners() {\n EventHandler.on(this._element, EVENT_KEYDOWN_DISMISS$1, event => {\n if (event.key !== ESCAPE_KEY$1) {\n return;\n }\n if (this._config.keyboard) {\n this.hide();\n return;\n }\n this._triggerBackdropTransition();\n });\n EventHandler.on(window, EVENT_RESIZE$1, () => {\n if (this._isShown && !this._isTransitioning) {\n this._adjustDialog();\n }\n });\n EventHandler.on(this._element, EVENT_MOUSEDOWN_DISMISS, event => {\n // a bad trick to segregate clicks that may start inside dialog but end outside, and avoid listen to scrollbar clicks\n EventHandler.one(this._element, EVENT_CLICK_DISMISS, event2 => {\n if (this._element !== event.target || this._element !== event2.target) {\n return;\n }\n if (this._config.backdrop === 'static') {\n this._triggerBackdropTransition();\n return;\n }\n if (this._config.backdrop) {\n this.hide();\n }\n });\n });\n }\n _hideModal() {\n this._element.style.display = 'none';\n this._element.setAttribute('aria-hidden', true);\n this._element.removeAttribute('aria-modal');\n this._element.removeAttribute('role');\n this._isTransitioning = false;\n this._backdrop.hide(() => {\n document.body.classList.remove(CLASS_NAME_OPEN);\n this._resetAdjustments();\n this._scrollBar.reset();\n EventHandler.trigger(this._element, EVENT_HIDDEN$4);\n });\n }\n _isAnimated() {\n return this._element.classList.contains(CLASS_NAME_FADE$3);\n }\n _triggerBackdropTransition() {\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED$1);\n if (hideEvent.defaultPrevented) {\n return;\n }\n const isModalOverflowing = this._element.scrollHeight > document.documentElement.clientHeight;\n const initialOverflowY = this._element.style.overflowY;\n // return if the following background transition hasn't yet completed\n if (initialOverflowY === 'hidden' || this._element.classList.contains(CLASS_NAME_STATIC)) {\n return;\n }\n if (!isModalOverflowing) {\n this._element.style.overflowY = 'hidden';\n }\n this._element.classList.add(CLASS_NAME_STATIC);\n this._queueCallback(() => {\n this._element.classList.remove(CLASS_NAME_STATIC);\n this._queueCallback(() => {\n this._element.style.overflowY = initialOverflowY;\n }, this._dialog);\n }, this._dialog);\n this._element.focus();\n }\n\n /**\n * The following methods are used to handle overflowing modals\n */\n\n _adjustDialog() {\n const isModalOverflowing = this._element.scrollHeight > document.documentElement.clientHeight;\n const scrollbarWidth = this._scrollBar.getWidth();\n const isBodyOverflowing = scrollbarWidth > 0;\n if (isBodyOverflowing && !isModalOverflowing) {\n const property = isRTL() ? 'paddingLeft' : 'paddingRight';\n this._element.style[property] = `${scrollbarWidth}px`;\n }\n if (!isBodyOverflowing && isModalOverflowing) {\n const property = isRTL() ? 'paddingRight' : 'paddingLeft';\n this._element.style[property] = `${scrollbarWidth}px`;\n }\n }\n _resetAdjustments() {\n this._element.style.paddingLeft = '';\n this._element.style.paddingRight = '';\n }\n\n // Static\n static jQueryInterface(config, relatedTarget) {\n return this.each(function () {\n const data = Modal.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config](relatedTarget);\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$2, SELECTOR_DATA_TOGGLE$2, function (event) {\n const target = SelectorEngine.getElementFromSelector(this);\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault();\n }\n EventHandler.one(target, EVENT_SHOW$4, showEvent => {\n if (showEvent.defaultPrevented) {\n // only register focus restorer if modal will actually get shown\n return;\n }\n EventHandler.one(target, EVENT_HIDDEN$4, () => {\n if (isVisible(this)) {\n this.focus();\n }\n });\n });\n\n // avoid conflict when clicking modal toggler while another one is open\n const alreadyOpen = SelectorEngine.findOne(OPEN_SELECTOR$1);\n if (alreadyOpen) {\n Modal.getInstance(alreadyOpen).hide();\n }\n const data = Modal.getOrCreateInstance(target);\n data.toggle(this);\n});\nenableDismissTrigger(Modal);\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Modal);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap offcanvas.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$6 = 'offcanvas';\nconst DATA_KEY$3 = 'bs.offcanvas';\nconst EVENT_KEY$3 = `.${DATA_KEY$3}`;\nconst DATA_API_KEY$1 = '.data-api';\nconst EVENT_LOAD_DATA_API$2 = `load${EVENT_KEY$3}${DATA_API_KEY$1}`;\nconst ESCAPE_KEY = 'Escape';\nconst CLASS_NAME_SHOW$3 = 'show';\nconst CLASS_NAME_SHOWING$1 = 'showing';\nconst CLASS_NAME_HIDING = 'hiding';\nconst CLASS_NAME_BACKDROP = 'offcanvas-backdrop';\nconst OPEN_SELECTOR = '.offcanvas.show';\nconst EVENT_SHOW$3 = `show${EVENT_KEY$3}`;\nconst EVENT_SHOWN$3 = `shown${EVENT_KEY$3}`;\nconst EVENT_HIDE$3 = `hide${EVENT_KEY$3}`;\nconst EVENT_HIDE_PREVENTED = `hidePrevented${EVENT_KEY$3}`;\nconst EVENT_HIDDEN$3 = `hidden${EVENT_KEY$3}`;\nconst EVENT_RESIZE = `resize${EVENT_KEY$3}`;\nconst EVENT_CLICK_DATA_API$1 = `click${EVENT_KEY$3}${DATA_API_KEY$1}`;\nconst EVENT_KEYDOWN_DISMISS = `keydown.dismiss${EVENT_KEY$3}`;\nconst SELECTOR_DATA_TOGGLE$1 = '[data-bs-toggle=\"offcanvas\"]';\nconst Default$5 = {\n backdrop: true,\n keyboard: true,\n scroll: false\n};\nconst DefaultType$5 = {\n backdrop: '(boolean|string)',\n keyboard: 'boolean',\n scroll: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Offcanvas extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._isShown = false;\n this._backdrop = this._initializeBackDrop();\n this._focustrap = this._initializeFocusTrap();\n this._addEventListeners();\n }\n\n // Getters\n static get Default() {\n return Default$5;\n }\n static get DefaultType() {\n return DefaultType$5;\n }\n static get NAME() {\n return NAME$6;\n }\n\n // Public\n toggle(relatedTarget) {\n return this._isShown ? this.hide() : this.show(relatedTarget);\n }\n show(relatedTarget) {\n if (this._isShown) {\n return;\n }\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW$3, {\n relatedTarget\n });\n if (showEvent.defaultPrevented) {\n return;\n }\n this._isShown = true;\n this._backdrop.show();\n if (!this._config.scroll) {\n new ScrollBarHelper().hide();\n }\n this._element.setAttribute('aria-modal', true);\n this._element.setAttribute('role', 'dialog');\n this._element.classList.add(CLASS_NAME_SHOWING$1);\n const completeCallBack = () => {\n if (!this._config.scroll || this._config.backdrop) {\n this._focustrap.activate();\n }\n this._element.classList.add(CLASS_NAME_SHOW$3);\n this._element.classList.remove(CLASS_NAME_SHOWING$1);\n EventHandler.trigger(this._element, EVENT_SHOWN$3, {\n relatedTarget\n });\n };\n this._queueCallback(completeCallBack, this._element, true);\n }\n hide() {\n if (!this._isShown) {\n return;\n }\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE$3);\n if (hideEvent.defaultPrevented) {\n return;\n }\n this._focustrap.deactivate();\n this._element.blur();\n this._isShown = false;\n this._element.classList.add(CLASS_NAME_HIDING);\n this._backdrop.hide();\n const completeCallback = () => {\n this._element.classList.remove(CLASS_NAME_SHOW$3, CLASS_NAME_HIDING);\n this._element.removeAttribute('aria-modal');\n this._element.removeAttribute('role');\n if (!this._config.scroll) {\n new ScrollBarHelper().reset();\n }\n EventHandler.trigger(this._element, EVENT_HIDDEN$3);\n };\n this._queueCallback(completeCallback, this._element, true);\n }\n dispose() {\n this._backdrop.dispose();\n this._focustrap.deactivate();\n super.dispose();\n }\n\n // Private\n _initializeBackDrop() {\n const clickCallback = () => {\n if (this._config.backdrop === 'static') {\n EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED);\n return;\n }\n this.hide();\n };\n\n // 'static' option will be translated to true, and booleans will keep their value\n const isVisible = Boolean(this._config.backdrop);\n return new Backdrop({\n className: CLASS_NAME_BACKDROP,\n isVisible,\n isAnimated: true,\n rootElement: this._element.parentNode,\n clickCallback: isVisible ? clickCallback : null\n });\n }\n _initializeFocusTrap() {\n return new FocusTrap({\n trapElement: this._element\n });\n }\n _addEventListeners() {\n EventHandler.on(this._element, EVENT_KEYDOWN_DISMISS, event => {\n if (event.key !== ESCAPE_KEY) {\n return;\n }\n if (this._config.keyboard) {\n this.hide();\n return;\n }\n EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED);\n });\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Offcanvas.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config](this);\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$1, SELECTOR_DATA_TOGGLE$1, function (event) {\n const target = SelectorEngine.getElementFromSelector(this);\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault();\n }\n if (isDisabled(this)) {\n return;\n }\n EventHandler.one(target, EVENT_HIDDEN$3, () => {\n // focus on trigger when it is closed\n if (isVisible(this)) {\n this.focus();\n }\n });\n\n // avoid conflict when clicking a toggler of an offcanvas, while another is open\n const alreadyOpen = SelectorEngine.findOne(OPEN_SELECTOR);\n if (alreadyOpen && alreadyOpen !== target) {\n Offcanvas.getInstance(alreadyOpen).hide();\n }\n const data = Offcanvas.getOrCreateInstance(target);\n data.toggle(this);\n});\nEventHandler.on(window, EVENT_LOAD_DATA_API$2, () => {\n for (const selector of SelectorEngine.find(OPEN_SELECTOR)) {\n Offcanvas.getOrCreateInstance(selector).show();\n }\n});\nEventHandler.on(window, EVENT_RESIZE, () => {\n for (const element of SelectorEngine.find('[aria-modal][class*=show][class*=offcanvas-]')) {\n if (getComputedStyle(element).position !== 'fixed') {\n Offcanvas.getOrCreateInstance(element).hide();\n }\n }\n});\nenableDismissTrigger(Offcanvas);\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Offcanvas);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/sanitizer.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n// js-docs-start allow-list\nconst ARIA_ATTRIBUTE_PATTERN = /^aria-[\\w-]*$/i;\nconst DefaultAllowlist = {\n // Global attributes allowed on any supplied element below.\n '*': ['class', 'dir', 'id', 'lang', 'role', ARIA_ATTRIBUTE_PATTERN],\n a: ['target', 'href', 'title', 'rel'],\n area: [],\n b: [],\n br: [],\n col: [],\n code: [],\n dd: [],\n div: [],\n dl: [],\n dt: [],\n em: [],\n hr: [],\n h1: [],\n h2: [],\n h3: [],\n h4: [],\n h5: [],\n h6: [],\n i: [],\n img: ['src', 'srcset', 'alt', 'title', 'width', 'height'],\n li: [],\n ol: [],\n p: [],\n pre: [],\n s: [],\n small: [],\n span: [],\n sub: [],\n sup: [],\n strong: [],\n u: [],\n ul: []\n};\n// js-docs-end allow-list\n\nconst uriAttributes = new Set(['background', 'cite', 'href', 'itemtype', 'longdesc', 'poster', 'src', 'xlink:href']);\n\n/**\n * A pattern that recognizes URLs that are safe wrt. XSS in URL navigation\n * contexts.\n *\n * Shout-out to Angular https://github.com/angular/angular/blob/15.2.8/packages/core/src/sanitization/url_sanitizer.ts#L38\n */\n// eslint-disable-next-line unicorn/better-regex\nconst SAFE_URL_PATTERN = /^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i;\nconst allowedAttribute = (attribute, allowedAttributeList) => {\n const attributeName = attribute.nodeName.toLowerCase();\n if (allowedAttributeList.includes(attributeName)) {\n if (uriAttributes.has(attributeName)) {\n return Boolean(SAFE_URL_PATTERN.test(attribute.nodeValue));\n }\n return true;\n }\n\n // Check if a regular expression validates the attribute.\n return allowedAttributeList.filter(attributeRegex => attributeRegex instanceof RegExp).some(regex => regex.test(attributeName));\n};\nfunction sanitizeHtml(unsafeHtml, allowList, sanitizeFunction) {\n if (!unsafeHtml.length) {\n return unsafeHtml;\n }\n if (sanitizeFunction && typeof sanitizeFunction === 'function') {\n return sanitizeFunction(unsafeHtml);\n }\n const domParser = new window.DOMParser();\n const createdDocument = domParser.parseFromString(unsafeHtml, 'text/html');\n const elements = [].concat(...createdDocument.body.querySelectorAll('*'));\n for (const element of elements) {\n const elementName = element.nodeName.toLowerCase();\n if (!Object.keys(allowList).includes(elementName)) {\n element.remove();\n continue;\n }\n const attributeList = [].concat(...element.attributes);\n const allowedAttributes = [].concat(allowList['*'] || [], allowList[elementName] || []);\n for (const attribute of attributeList) {\n if (!allowedAttribute(attribute, allowedAttributes)) {\n element.removeAttribute(attribute.nodeName);\n }\n }\n }\n return createdDocument.body.innerHTML;\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/template-factory.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$5 = 'TemplateFactory';\nconst Default$4 = {\n allowList: DefaultAllowlist,\n content: {},\n // { selector : text , selector2 : text2 , }\n extraClass: '',\n html: false,\n sanitize: true,\n sanitizeFn: null,\n template: '
'\n};\nconst DefaultType$4 = {\n allowList: 'object',\n content: 'object',\n extraClass: '(string|function)',\n html: 'boolean',\n sanitize: 'boolean',\n sanitizeFn: '(null|function)',\n template: 'string'\n};\nconst DefaultContentType = {\n entry: '(string|element|function|null)',\n selector: '(string|element)'\n};\n\n/**\n * Class definition\n */\n\nclass TemplateFactory extends Config {\n constructor(config) {\n super();\n this._config = this._getConfig(config);\n }\n\n // Getters\n static get Default() {\n return Default$4;\n }\n static get DefaultType() {\n return DefaultType$4;\n }\n static get NAME() {\n return NAME$5;\n }\n\n // Public\n getContent() {\n return Object.values(this._config.content).map(config => this._resolvePossibleFunction(config)).filter(Boolean);\n }\n hasContent() {\n return this.getContent().length > 0;\n }\n changeContent(content) {\n this._checkContent(content);\n this._config.content = {\n ...this._config.content,\n ...content\n };\n return this;\n }\n toHtml() {\n const templateWrapper = document.createElement('div');\n templateWrapper.innerHTML = this._maybeSanitize(this._config.template);\n for (const [selector, text] of Object.entries(this._config.content)) {\n this._setContent(templateWrapper, text, selector);\n }\n const template = templateWrapper.children[0];\n const extraClass = this._resolvePossibleFunction(this._config.extraClass);\n if (extraClass) {\n template.classList.add(...extraClass.split(' '));\n }\n return template;\n }\n\n // Private\n _typeCheckConfig(config) {\n super._typeCheckConfig(config);\n this._checkContent(config.content);\n }\n _checkContent(arg) {\n for (const [selector, content] of Object.entries(arg)) {\n super._typeCheckConfig({\n selector,\n entry: content\n }, DefaultContentType);\n }\n }\n _setContent(template, content, selector) {\n const templateElement = SelectorEngine.findOne(selector, template);\n if (!templateElement) {\n return;\n }\n content = this._resolvePossibleFunction(content);\n if (!content) {\n templateElement.remove();\n return;\n }\n if (isElement(content)) {\n this._putElementInTemplate(getElement(content), templateElement);\n return;\n }\n if (this._config.html) {\n templateElement.innerHTML = this._maybeSanitize(content);\n return;\n }\n templateElement.textContent = content;\n }\n _maybeSanitize(arg) {\n return this._config.sanitize ? sanitizeHtml(arg, this._config.allowList, this._config.sanitizeFn) : arg;\n }\n _resolvePossibleFunction(arg) {\n return execute(arg, [this]);\n }\n _putElementInTemplate(element, templateElement) {\n if (this._config.html) {\n templateElement.innerHTML = '';\n templateElement.append(element);\n return;\n }\n templateElement.textContent = element.textContent;\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap tooltip.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$4 = 'tooltip';\nconst DISALLOWED_ATTRIBUTES = new Set(['sanitize', 'allowList', 'sanitizeFn']);\nconst CLASS_NAME_FADE$2 = 'fade';\nconst CLASS_NAME_MODAL = 'modal';\nconst CLASS_NAME_SHOW$2 = 'show';\nconst SELECTOR_TOOLTIP_INNER = '.tooltip-inner';\nconst SELECTOR_MODAL = `.${CLASS_NAME_MODAL}`;\nconst EVENT_MODAL_HIDE = 'hide.bs.modal';\nconst TRIGGER_HOVER = 'hover';\nconst TRIGGER_FOCUS = 'focus';\nconst TRIGGER_CLICK = 'click';\nconst TRIGGER_MANUAL = 'manual';\nconst EVENT_HIDE$2 = 'hide';\nconst EVENT_HIDDEN$2 = 'hidden';\nconst EVENT_SHOW$2 = 'show';\nconst EVENT_SHOWN$2 = 'shown';\nconst EVENT_INSERTED = 'inserted';\nconst EVENT_CLICK$1 = 'click';\nconst EVENT_FOCUSIN$1 = 'focusin';\nconst EVENT_FOCUSOUT$1 = 'focusout';\nconst EVENT_MOUSEENTER = 'mouseenter';\nconst EVENT_MOUSELEAVE = 'mouseleave';\nconst AttachmentMap = {\n AUTO: 'auto',\n TOP: 'top',\n RIGHT: isRTL() ? 'left' : 'right',\n BOTTOM: 'bottom',\n LEFT: isRTL() ? 'right' : 'left'\n};\nconst Default$3 = {\n allowList: DefaultAllowlist,\n animation: true,\n boundary: 'clippingParents',\n container: false,\n customClass: '',\n delay: 0,\n fallbackPlacements: ['top', 'right', 'bottom', 'left'],\n html: false,\n offset: [0, 6],\n placement: 'top',\n popperConfig: null,\n sanitize: true,\n sanitizeFn: null,\n selector: false,\n template: '
' + '
' + '
' + '
',\n title: '',\n trigger: 'hover focus'\n};\nconst DefaultType$3 = {\n allowList: 'object',\n animation: 'boolean',\n boundary: '(string|element)',\n container: '(string|element|boolean)',\n customClass: '(string|function)',\n delay: '(number|object)',\n fallbackPlacements: 'array',\n html: 'boolean',\n offset: '(array|string|function)',\n placement: '(string|function)',\n popperConfig: '(null|object|function)',\n sanitize: 'boolean',\n sanitizeFn: '(null|function)',\n selector: '(string|boolean)',\n template: 'string',\n title: '(string|element|function)',\n trigger: 'string'\n};\n\n/**\n * Class definition\n */\n\nclass Tooltip extends BaseComponent {\n constructor(element, config) {\n if (typeof Popper === 'undefined') {\n throw new TypeError('Bootstrap\\'s tooltips require Popper (https://popper.js.org)');\n }\n super(element, config);\n\n // Private\n this._isEnabled = true;\n this._timeout = 0;\n this._isHovered = null;\n this._activeTrigger = {};\n this._popper = null;\n this._templateFactory = null;\n this._newContent = null;\n\n // Protected\n this.tip = null;\n this._setListeners();\n if (!this._config.selector) {\n this._fixTitle();\n }\n }\n\n // Getters\n static get Default() {\n return Default$3;\n }\n static get DefaultType() {\n return DefaultType$3;\n }\n static get NAME() {\n return NAME$4;\n }\n\n // Public\n enable() {\n this._isEnabled = true;\n }\n disable() {\n this._isEnabled = false;\n }\n toggleEnabled() {\n this._isEnabled = !this._isEnabled;\n }\n toggle() {\n if (!this._isEnabled) {\n return;\n }\n this._activeTrigger.click = !this._activeTrigger.click;\n if (this._isShown()) {\n this._leave();\n return;\n }\n this._enter();\n }\n dispose() {\n clearTimeout(this._timeout);\n EventHandler.off(this._element.closest(SELECTOR_MODAL), EVENT_MODAL_HIDE, this._hideModalHandler);\n if (this._element.getAttribute('data-bs-original-title')) {\n this._element.setAttribute('title', this._element.getAttribute('data-bs-original-title'));\n }\n this._disposePopper();\n super.dispose();\n }\n show() {\n if (this._element.style.display === 'none') {\n throw new Error('Please use show on visible elements');\n }\n if (!(this._isWithContent() && this._isEnabled)) {\n return;\n }\n const showEvent = EventHandler.trigger(this._element, this.constructor.eventName(EVENT_SHOW$2));\n const shadowRoot = findShadowRoot(this._element);\n const isInTheDom = (shadowRoot || this._element.ownerDocument.documentElement).contains(this._element);\n if (showEvent.defaultPrevented || !isInTheDom) {\n return;\n }\n\n // TODO: v6 remove this or make it optional\n this._disposePopper();\n const tip = this._getTipElement();\n this._element.setAttribute('aria-describedby', tip.getAttribute('id'));\n const {\n container\n } = this._config;\n if (!this._element.ownerDocument.documentElement.contains(this.tip)) {\n container.append(tip);\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_INSERTED));\n }\n this._popper = this._createPopper(tip);\n tip.classList.add(CLASS_NAME_SHOW$2);\n\n // If this is a touch-enabled device we add extra\n // empty mouseover listeners to the body's immediate children;\n // only needed because of broken event delegation on iOS\n // https://www.quirksmode.org/blog/archives/2014/02/mouse_event_bub.html\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.on(element, 'mouseover', noop);\n }\n }\n const complete = () => {\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_SHOWN$2));\n if (this._isHovered === false) {\n this._leave();\n }\n this._isHovered = false;\n };\n this._queueCallback(complete, this.tip, this._isAnimated());\n }\n hide() {\n if (!this._isShown()) {\n return;\n }\n const hideEvent = EventHandler.trigger(this._element, this.constructor.eventName(EVENT_HIDE$2));\n if (hideEvent.defaultPrevented) {\n return;\n }\n const tip = this._getTipElement();\n tip.classList.remove(CLASS_NAME_SHOW$2);\n\n // If this is a touch-enabled device we remove the extra\n // empty mouseover listeners we added for iOS support\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.off(element, 'mouseover', noop);\n }\n }\n this._activeTrigger[TRIGGER_CLICK] = false;\n this._activeTrigger[TRIGGER_FOCUS] = false;\n this._activeTrigger[TRIGGER_HOVER] = false;\n this._isHovered = null; // it is a trick to support manual triggering\n\n const complete = () => {\n if (this._isWithActiveTrigger()) {\n return;\n }\n if (!this._isHovered) {\n this._disposePopper();\n }\n this._element.removeAttribute('aria-describedby');\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_HIDDEN$2));\n };\n this._queueCallback(complete, this.tip, this._isAnimated());\n }\n update() {\n if (this._popper) {\n this._popper.update();\n }\n }\n\n // Protected\n _isWithContent() {\n return Boolean(this._getTitle());\n }\n _getTipElement() {\n if (!this.tip) {\n this.tip = this._createTipElement(this._newContent || this._getContentForTemplate());\n }\n return this.tip;\n }\n _createTipElement(content) {\n const tip = this._getTemplateFactory(content).toHtml();\n\n // TODO: remove this check in v6\n if (!tip) {\n return null;\n }\n tip.classList.remove(CLASS_NAME_FADE$2, CLASS_NAME_SHOW$2);\n // TODO: v6 the following can be achieved with CSS only\n tip.classList.add(`bs-${this.constructor.NAME}-auto`);\n const tipId = getUID(this.constructor.NAME).toString();\n tip.setAttribute('id', tipId);\n if (this._isAnimated()) {\n tip.classList.add(CLASS_NAME_FADE$2);\n }\n return tip;\n }\n setContent(content) {\n this._newContent = content;\n if (this._isShown()) {\n this._disposePopper();\n this.show();\n }\n }\n _getTemplateFactory(content) {\n if (this._templateFactory) {\n this._templateFactory.changeContent(content);\n } else {\n this._templateFactory = new TemplateFactory({\n ...this._config,\n // the `content` var has to be after `this._config`\n // to override config.content in case of popover\n content,\n extraClass: this._resolvePossibleFunction(this._config.customClass)\n });\n }\n return this._templateFactory;\n }\n _getContentForTemplate() {\n return {\n [SELECTOR_TOOLTIP_INNER]: this._getTitle()\n };\n }\n _getTitle() {\n return this._resolvePossibleFunction(this._config.title) || this._element.getAttribute('data-bs-original-title');\n }\n\n // Private\n _initializeOnDelegatedTarget(event) {\n return this.constructor.getOrCreateInstance(event.delegateTarget, this._getDelegateConfig());\n }\n _isAnimated() {\n return this._config.animation || this.tip && this.tip.classList.contains(CLASS_NAME_FADE$2);\n }\n _isShown() {\n return this.tip && this.tip.classList.contains(CLASS_NAME_SHOW$2);\n }\n _createPopper(tip) {\n const placement = execute(this._config.placement, [this, tip, this._element]);\n const attachment = AttachmentMap[placement.toUpperCase()];\n return Popper.createPopper(this._element, tip, this._getPopperConfig(attachment));\n }\n _getOffset() {\n const {\n offset\n } = this._config;\n if (typeof offset === 'string') {\n return offset.split(',').map(value => Number.parseInt(value, 10));\n }\n if (typeof offset === 'function') {\n return popperData => offset(popperData, this._element);\n }\n return offset;\n }\n _resolvePossibleFunction(arg) {\n return execute(arg, [this._element]);\n }\n _getPopperConfig(attachment) {\n const defaultBsPopperConfig = {\n placement: attachment,\n modifiers: [{\n name: 'flip',\n options: {\n fallbackPlacements: this._config.fallbackPlacements\n }\n }, {\n name: 'offset',\n options: {\n offset: this._getOffset()\n }\n }, {\n name: 'preventOverflow',\n options: {\n boundary: this._config.boundary\n }\n }, {\n name: 'arrow',\n options: {\n element: `.${this.constructor.NAME}-arrow`\n }\n }, {\n name: 'preSetPlacement',\n enabled: true,\n phase: 'beforeMain',\n fn: data => {\n // Pre-set Popper's placement attribute in order to read the arrow sizes properly.\n // Otherwise, Popper mixes up the width and height dimensions since the initial arrow style is for top placement\n this._getTipElement().setAttribute('data-popper-placement', data.state.placement);\n }\n }]\n };\n return {\n ...defaultBsPopperConfig,\n ...execute(this._config.popperConfig, [defaultBsPopperConfig])\n };\n }\n _setListeners() {\n const triggers = this._config.trigger.split(' ');\n for (const trigger of triggers) {\n if (trigger === 'click') {\n EventHandler.on(this._element, this.constructor.eventName(EVENT_CLICK$1), this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event);\n context.toggle();\n });\n } else if (trigger !== TRIGGER_MANUAL) {\n const eventIn = trigger === TRIGGER_HOVER ? this.constructor.eventName(EVENT_MOUSEENTER) : this.constructor.eventName(EVENT_FOCUSIN$1);\n const eventOut = trigger === TRIGGER_HOVER ? this.constructor.eventName(EVENT_MOUSELEAVE) : this.constructor.eventName(EVENT_FOCUSOUT$1);\n EventHandler.on(this._element, eventIn, this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event);\n context._activeTrigger[event.type === 'focusin' ? TRIGGER_FOCUS : TRIGGER_HOVER] = true;\n context._enter();\n });\n EventHandler.on(this._element, eventOut, this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event);\n context._activeTrigger[event.type === 'focusout' ? TRIGGER_FOCUS : TRIGGER_HOVER] = context._element.contains(event.relatedTarget);\n context._leave();\n });\n }\n }\n this._hideModalHandler = () => {\n if (this._element) {\n this.hide();\n }\n };\n EventHandler.on(this._element.closest(SELECTOR_MODAL), EVENT_MODAL_HIDE, this._hideModalHandler);\n }\n _fixTitle() {\n const title = this._element.getAttribute('title');\n if (!title) {\n return;\n }\n if (!this._element.getAttribute('aria-label') && !this._element.textContent.trim()) {\n this._element.setAttribute('aria-label', title);\n }\n this._element.setAttribute('data-bs-original-title', title); // DO NOT USE IT. Is only for backwards compatibility\n this._element.removeAttribute('title');\n }\n _enter() {\n if (this._isShown() || this._isHovered) {\n this._isHovered = true;\n return;\n }\n this._isHovered = true;\n this._setTimeout(() => {\n if (this._isHovered) {\n this.show();\n }\n }, this._config.delay.show);\n }\n _leave() {\n if (this._isWithActiveTrigger()) {\n return;\n }\n this._isHovered = false;\n this._setTimeout(() => {\n if (!this._isHovered) {\n this.hide();\n }\n }, this._config.delay.hide);\n }\n _setTimeout(handler, timeout) {\n clearTimeout(this._timeout);\n this._timeout = setTimeout(handler, timeout);\n }\n _isWithActiveTrigger() {\n return Object.values(this._activeTrigger).includes(true);\n }\n _getConfig(config) {\n const dataAttributes = Manipulator.getDataAttributes(this._element);\n for (const dataAttribute of Object.keys(dataAttributes)) {\n if (DISALLOWED_ATTRIBUTES.has(dataAttribute)) {\n delete dataAttributes[dataAttribute];\n }\n }\n config = {\n ...dataAttributes,\n ...(typeof config === 'object' && config ? config : {})\n };\n config = this._mergeConfigObj(config);\n config = this._configAfterMerge(config);\n this._typeCheckConfig(config);\n return config;\n }\n _configAfterMerge(config) {\n config.container = config.container === false ? document.body : getElement(config.container);\n if (typeof config.delay === 'number') {\n config.delay = {\n show: config.delay,\n hide: config.delay\n };\n }\n if (typeof config.title === 'number') {\n config.title = config.title.toString();\n }\n if (typeof config.content === 'number') {\n config.content = config.content.toString();\n }\n return config;\n }\n _getDelegateConfig() {\n const config = {};\n for (const [key, value] of Object.entries(this._config)) {\n if (this.constructor.Default[key] !== value) {\n config[key] = value;\n }\n }\n config.selector = false;\n config.trigger = 'manual';\n\n // In the future can be replaced with:\n // const keysWithDifferentValues = Object.entries(this._config).filter(entry => this.constructor.Default[entry[0]] !== this._config[entry[0]])\n // `Object.fromEntries(keysWithDifferentValues)`\n return config;\n }\n _disposePopper() {\n if (this._popper) {\n this._popper.destroy();\n this._popper = null;\n }\n if (this.tip) {\n this.tip.remove();\n this.tip = null;\n }\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Tooltip.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n });\n }\n}\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Tooltip);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap popover.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$3 = 'popover';\nconst SELECTOR_TITLE = '.popover-header';\nconst SELECTOR_CONTENT = '.popover-body';\nconst Default$2 = {\n ...Tooltip.Default,\n content: '',\n offset: [0, 8],\n placement: 'right',\n template: '
' + '
' + '

' + '
' + '
',\n trigger: 'click'\n};\nconst DefaultType$2 = {\n ...Tooltip.DefaultType,\n content: '(null|string|element|function)'\n};\n\n/**\n * Class definition\n */\n\nclass Popover extends Tooltip {\n // Getters\n static get Default() {\n return Default$2;\n }\n static get DefaultType() {\n return DefaultType$2;\n }\n static get NAME() {\n return NAME$3;\n }\n\n // Overrides\n _isWithContent() {\n return this._getTitle() || this._getContent();\n }\n\n // Private\n _getContentForTemplate() {\n return {\n [SELECTOR_TITLE]: this._getTitle(),\n [SELECTOR_CONTENT]: this._getContent()\n };\n }\n _getContent() {\n return this._resolvePossibleFunction(this._config.content);\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Popover.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n });\n }\n}\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Popover);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap scrollspy.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$2 = 'scrollspy';\nconst DATA_KEY$2 = 'bs.scrollspy';\nconst EVENT_KEY$2 = `.${DATA_KEY$2}`;\nconst DATA_API_KEY = '.data-api';\nconst EVENT_ACTIVATE = `activate${EVENT_KEY$2}`;\nconst EVENT_CLICK = `click${EVENT_KEY$2}`;\nconst EVENT_LOAD_DATA_API$1 = `load${EVENT_KEY$2}${DATA_API_KEY}`;\nconst CLASS_NAME_DROPDOWN_ITEM = 'dropdown-item';\nconst CLASS_NAME_ACTIVE$1 = 'active';\nconst SELECTOR_DATA_SPY = '[data-bs-spy=\"scroll\"]';\nconst SELECTOR_TARGET_LINKS = '[href]';\nconst SELECTOR_NAV_LIST_GROUP = '.nav, .list-group';\nconst SELECTOR_NAV_LINKS = '.nav-link';\nconst SELECTOR_NAV_ITEMS = '.nav-item';\nconst SELECTOR_LIST_ITEMS = '.list-group-item';\nconst SELECTOR_LINK_ITEMS = `${SELECTOR_NAV_LINKS}, ${SELECTOR_NAV_ITEMS} > ${SELECTOR_NAV_LINKS}, ${SELECTOR_LIST_ITEMS}`;\nconst SELECTOR_DROPDOWN = '.dropdown';\nconst SELECTOR_DROPDOWN_TOGGLE$1 = '.dropdown-toggle';\nconst Default$1 = {\n offset: null,\n // TODO: v6 @deprecated, keep it for backwards compatibility reasons\n rootMargin: '0px 0px -25%',\n smoothScroll: false,\n target: null,\n threshold: [0.1, 0.5, 1]\n};\nconst DefaultType$1 = {\n offset: '(number|null)',\n // TODO v6 @deprecated, keep it for backwards compatibility reasons\n rootMargin: 'string',\n smoothScroll: 'boolean',\n target: 'element',\n threshold: 'array'\n};\n\n/**\n * Class definition\n */\n\nclass ScrollSpy extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n\n // this._element is the observablesContainer and config.target the menu links wrapper\n this._targetLinks = new Map();\n this._observableSections = new Map();\n this._rootElement = getComputedStyle(this._element).overflowY === 'visible' ? null : this._element;\n this._activeTarget = null;\n this._observer = null;\n this._previousScrollData = {\n visibleEntryTop: 0,\n parentScrollTop: 0\n };\n this.refresh(); // initialize\n }\n\n // Getters\n static get Default() {\n return Default$1;\n }\n static get DefaultType() {\n return DefaultType$1;\n }\n static get NAME() {\n return NAME$2;\n }\n\n // Public\n refresh() {\n this._initializeTargetsAndObservables();\n this._maybeEnableSmoothScroll();\n if (this._observer) {\n this._observer.disconnect();\n } else {\n this._observer = this._getNewObserver();\n }\n for (const section of this._observableSections.values()) {\n this._observer.observe(section);\n }\n }\n dispose() {\n this._observer.disconnect();\n super.dispose();\n }\n\n // Private\n _configAfterMerge(config) {\n // TODO: on v6 target should be given explicitly & remove the {target: 'ss-target'} case\n config.target = getElement(config.target) || document.body;\n\n // TODO: v6 Only for backwards compatibility reasons. Use rootMargin only\n config.rootMargin = config.offset ? `${config.offset}px 0px -30%` : config.rootMargin;\n if (typeof config.threshold === 'string') {\n config.threshold = config.threshold.split(',').map(value => Number.parseFloat(value));\n }\n return config;\n }\n _maybeEnableSmoothScroll() {\n if (!this._config.smoothScroll) {\n return;\n }\n\n // unregister any previous listeners\n EventHandler.off(this._config.target, EVENT_CLICK);\n EventHandler.on(this._config.target, EVENT_CLICK, SELECTOR_TARGET_LINKS, event => {\n const observableSection = this._observableSections.get(event.target.hash);\n if (observableSection) {\n event.preventDefault();\n const root = this._rootElement || window;\n const height = observableSection.offsetTop - this._element.offsetTop;\n if (root.scrollTo) {\n root.scrollTo({\n top: height,\n behavior: 'smooth'\n });\n return;\n }\n\n // Chrome 60 doesn't support `scrollTo`\n root.scrollTop = height;\n }\n });\n }\n _getNewObserver() {\n const options = {\n root: this._rootElement,\n threshold: this._config.threshold,\n rootMargin: this._config.rootMargin\n };\n return new IntersectionObserver(entries => this._observerCallback(entries), options);\n }\n\n // The logic of selection\n _observerCallback(entries) {\n const targetElement = entry => this._targetLinks.get(`#${entry.target.id}`);\n const activate = entry => {\n this._previousScrollData.visibleEntryTop = entry.target.offsetTop;\n this._process(targetElement(entry));\n };\n const parentScrollTop = (this._rootElement || document.documentElement).scrollTop;\n const userScrollsDown = parentScrollTop >= this._previousScrollData.parentScrollTop;\n this._previousScrollData.parentScrollTop = parentScrollTop;\n for (const entry of entries) {\n if (!entry.isIntersecting) {\n this._activeTarget = null;\n this._clearActiveClass(targetElement(entry));\n continue;\n }\n const entryIsLowerThanPrevious = entry.target.offsetTop >= this._previousScrollData.visibleEntryTop;\n // if we are scrolling down, pick the bigger offsetTop\n if (userScrollsDown && entryIsLowerThanPrevious) {\n activate(entry);\n // if parent isn't scrolled, let's keep the first visible item, breaking the iteration\n if (!parentScrollTop) {\n return;\n }\n continue;\n }\n\n // if we are scrolling up, pick the smallest offsetTop\n if (!userScrollsDown && !entryIsLowerThanPrevious) {\n activate(entry);\n }\n }\n }\n _initializeTargetsAndObservables() {\n this._targetLinks = new Map();\n this._observableSections = new Map();\n const targetLinks = SelectorEngine.find(SELECTOR_TARGET_LINKS, this._config.target);\n for (const anchor of targetLinks) {\n // ensure that the anchor has an id and is not disabled\n if (!anchor.hash || isDisabled(anchor)) {\n continue;\n }\n const observableSection = SelectorEngine.findOne(decodeURI(anchor.hash), this._element);\n\n // ensure that the observableSection exists & is visible\n if (isVisible(observableSection)) {\n this._targetLinks.set(decodeURI(anchor.hash), anchor);\n this._observableSections.set(anchor.hash, observableSection);\n }\n }\n }\n _process(target) {\n if (this._activeTarget === target) {\n return;\n }\n this._clearActiveClass(this._config.target);\n this._activeTarget = target;\n target.classList.add(CLASS_NAME_ACTIVE$1);\n this._activateParents(target);\n EventHandler.trigger(this._element, EVENT_ACTIVATE, {\n relatedTarget: target\n });\n }\n _activateParents(target) {\n // Activate dropdown parents\n if (target.classList.contains(CLASS_NAME_DROPDOWN_ITEM)) {\n SelectorEngine.findOne(SELECTOR_DROPDOWN_TOGGLE$1, target.closest(SELECTOR_DROPDOWN)).classList.add(CLASS_NAME_ACTIVE$1);\n return;\n }\n for (const listGroup of SelectorEngine.parents(target, SELECTOR_NAV_LIST_GROUP)) {\n // Set triggered links parents as active\n // With both
    and