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Merge pull request #75 from pyansys/feat/unit-tests
Solving workflow issues: vale, pre-commit
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.github/workflows/ci_cd.yml

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runs-on: ubuntu-latest
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steps:
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- name: PyAnsys code style checks
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uses: pyansys/actions/code-style@v2
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uses: pyansys/actions/code-style@v3
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with:
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python-version: ${{ env.MAIN_PYTHON_VERSION }}
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# docs-style:
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# name: Documentation Style Check
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# runs-on: ubuntu-latest
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# steps:
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# - uses: actions/checkout@v3
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# - name: Running Vale
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# uses: errata-ai/vale-action@reviewdog
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# env:
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# GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}
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# with:
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# files: doc
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# reporter: github-pr-check
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# level: error
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# filter_mode: nofilter
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# fail_on_error: true
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# vale_flags: "--config=doc/.vale.ini"
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docs-style:
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name: Documentation Style Check
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runs-on: ubuntu-latest
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steps:
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- name: PyAnsys documentation style checks
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uses: pyansys/actions/doc-style@v3
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with:
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token: ${{ secrets.GITHUB_TOKEN }}
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smoke-tests:
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name: Build and Smoke tests
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fail-fast: false
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matrix:
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os: [windows-latest, ubuntu-latest]
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python-version: ['3.7', '3.8', '3.9', '3.10']
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python-version: ['3.7', '3.8', '3.9', '3.10'] #, '3.11'] # --> At some point we should include Py3.11
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steps:
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- name: Build wheelhouse and perform smoke test
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uses: pyansys/actions/build-wheelhouse@v2
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uses: pyansys/actions/build-wheelhouse@v3
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with:
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library-name: ${{ env.PACKAGE_NAME }}
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library-namespace: ${{ env.PACKAGE_NAMESPACE }}
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docs:
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name: Documentation
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runs-on: ubuntu-latest
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# needs: [docs-style]
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needs: [docs-style]
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steps:
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- uses: actions/checkout@v3
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runs-on: ubuntu-latest
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steps:
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- name: Build library source and wheel artifacts
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uses: pyansys/actions/build-library@v2
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uses: pyansys/actions/build-library@v3
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with:
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library-name: ${{ env.PACKAGE_NAME }}
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python-version: ${{ env.MAIN_PYTHON_VERSION }}
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runs-on: ubuntu-latest
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steps:
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- name: Release to GitHub
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uses: pyansys/actions/release-github@v2
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uses: pyansys/actions/release-github@v3
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with:
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library-name: ${{ env.PACKAGE_NAME }}
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needs: [docs]
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steps:
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- name: Deploy the latest documentation
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uses: pyansys/actions/doc-deploy-dev@v2
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uses: pyansys/actions/doc-deploy-dev@v3
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with:
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cname: ${{ env.DOCUMENTATION_CNAME }}
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token: ${{ secrets.GITHUB_TOKEN }}
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needs: [release]
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steps:
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- name: Deploy the stable documentation
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uses: pyansys/actions/doc-deploy-stable@v2
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uses: pyansys/actions/doc-deploy-stable@v3
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with:
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cname: ${{ env.DOCUMENTATION_CNAME }}
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token: ${{ secrets.GITHUB_TOKEN }}

.pre-commit-config.yaml

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repos:
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- repo: https://github.com/psf/black
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rev: 22.10.0
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rev: 23.1.0
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hooks:
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- id: black
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args:
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- --max-line-length=120
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- repo: https://github.com/pycqa/isort
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rev: 5.10.1
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rev: 5.12.0
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hooks:
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- id: isort
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args:

doc/source/API/index.rst

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=============
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This section describes PyDyna core classes, methods, and functions
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for Dyna apps and modules. Use the search feature or click links
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for LS-Dyna apps and modules. Use the search feature or click links
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to view API documentation.
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.. toctree::

doc/source/API/pre.rst

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PyDyna-pre APIs
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================
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===============
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The PyDyna-pre API includes classes for apps and modules.
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.. currentmodule:: ansys.dyna.core
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Getting Started
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Getting started
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===============
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Installation
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~~~~~~~~~~~~
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This package is not yet available on PyPI, so for now the only real
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option is for you to download the code from GitHub:
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.. code::
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git clone https://github.com/pyansys/pyDyna
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and copy the required files
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and copy the required files.

doc/source/Resources/User_Guide.rst

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User Guide
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User guide
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----------
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There are 3 related packages here, all under the ansys/dyna/ directory.
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There are 3 related packages here, all under the ``ansys/dyna`` directory.
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PyDyna-pre provides interface to create DYNA input deck.
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PyDyna-solver contains code for interfacing with the LS-DYNA solver directly.
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As LS-DYNA is primarily a batch solver with very limited interactive
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capabilities, the code here is similarly limited. The target
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use case is that LS-DYNA will be running in a container environment
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such as Docker or Kubernetes. The code here then allows for pushing
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capabilities, the code here is similarly limited. The target
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use case is that LS-DYNA is running in a container environment
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such as Docker or Kubernetes. The code here then allows for pushing
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input files to the container, starting LS-DYNA and monitoring its
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progress, and retrieving results files.
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The Data Processing Framework (DPF) is designed to provide numerical
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simulation users/engineers with a toolbox for accessing and
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transforming simulation data. DPF can access data from solver result
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files as well as several neutral formats (csv, hdf5, vtk,
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files as well as several neutral formats (``.csv``, ``.hdf5``, ``.vtk``,
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etc.). Various operators are available allowing the manipulation and
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the transformation of this data.
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The Python `ansys-dpf-post` package provides a simplified Python
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interface to DPF, thus enabling rapid postprocessing without ever
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leaving a Python environment.
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leaving a Python environment.
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Visit the [DPF-Post Documentation](https://postdocs.pyansys.com) for a
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Visit the `DPF-Post Documentation <https://post.docs.pyansys.com>`_ for a
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detailed description of the package
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.. toctree::

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