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Enabled mcpi demo. Added respective documentation
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‎.github/workflows/mcpi_build_test_upload.yml‎

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name: Build-test-upload mcpi package
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on:
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push:
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branches:
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- main
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pull_request:
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env:
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PACKAGE_NAME: mcpi-demo
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MODULE_NAME: mcpi_demo
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jobs:
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build_linux:
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runs-on: ubuntu-20.04
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strategy:
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matrix:
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python: ['3.8', '3.9', '3.10']
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steps:
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- uses: actions/checkout@v3
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with:
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fetch-depth: 0
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- name: Set pkgs_dirs
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run: |
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echo "pkgs_dirs: [~/.conda/pkgs]" >> ~/.condarc
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- name: Cache conda packages
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uses: actions/cache@v3
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env:
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CACHE_NUMBER: 0 # Increase to reset cache
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with:
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path: ~/.conda/pkgs
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key:
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${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-python-${{ matrix.python }}-${{hashFiles('**/meta.yaml') }}
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restore-keys: |
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${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-python-${{ matrix.python }}-
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${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-
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- name: Add conda to system path
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run: echo $CONDA/bin >> $GITHUB_PATH
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- name: Install conda-build
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run: conda install conda-build
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- name: Build conda package
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run: |
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CHANNELS="-c intel -c main --override-channels"
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VERSIONS="--python ${{ matrix.python }}"
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TEST=""
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cd ./demos/mcpi
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conda build $TEST $VERSIONS $CHANNELS conda-recipe
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- name: Upload artifact
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uses: actions/upload-artifact@v3
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with:
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name: ${{ env.PACKAGE_NAME }} ${{ runner.os }} Python ${{ matrix.python }}
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path: /usr/share/miniconda/conda-bld/linux-64/${{ env.PACKAGE_NAME }}-*.tar.bz2
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test_linux:
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needs: build_linux
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runs-on: ${{ matrix.runner }}
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strategy:
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matrix:
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python: ['3.8', '3.9', '3.10']
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experimental: [true]
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runner: [ubuntu-20.04]
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continue-on-error: ${{ matrix.experimental }}
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env:
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CHANNELS: -c dppy/label/dev -c intel -c main --override-channels
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steps:
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- uses: actions/checkout@v3
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with:
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fetch-depth: 0
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- name: Download artifact
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uses: actions/download-artifact@v3
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with:
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name: ${{ env.PACKAGE_NAME }} ${{ runner.os }} Python ${{ matrix.python }}
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- name: Add conda to system path
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run: echo $CONDA/bin >> $GITHUB_PATH
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- name: Install conda-build
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# Needed to be able to run conda index
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run: conda install conda-build
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- name: Create conda channel
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run: |
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mkdir -p $GITHUB_WORKSPACE/channel/linux-64
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# conda index $GITHUB_WORKSPACE/channel || exit 1
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mv ${PACKAGE_NAME}-*.tar.bz2 $GITHUB_WORKSPACE/channel/linux-64 || exit 1
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conda index $GITHUB_WORKSPACE/channel || exit 1
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# Test channel
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conda search $PACKAGE_NAME -c $GITHUB_WORKSPACE/channel --override-channels --info --json > $GITHUB_WORKSPACE/ver.json
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cat ver.json
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- name: Collect dependencies
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run: |
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CHANNELS="-c $GITHUB_WORKSPACE/channel ${{ env.CHANNELS }}"
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conda create -n test-env $PACKAGE_NAME python=${{ matrix.python }} $CHANNELS --only-deps --dry-run > lockfile
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cat lockfile
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- name: Set pkgs_dirs
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run: |
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echo "pkgs_dirs: [~/.conda/pkgs]" >> ~/.condarc
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- name: Cache conda packages
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uses: actions/cache@v3
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env:
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CACHE_NUMBER: 0 # Increase to reset cache
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with:
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path: ~/.conda/pkgs
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key:
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${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-python-${{ matrix.python }}-${{hashFiles('lockfile') }}
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restore-keys: |
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${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-python-${{ matrix.python }}-
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${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-
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- name: Install package
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run: |
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export CHANNELS="-c $GITHUB_WORKSPACE/channel ${{ env.CHANNELS }}"
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conda create -n test-env $PACKAGE_NAME pytest python=${{ matrix.python }} ${CHANNELS}
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. $CONDA/etc/profile.d/conda.sh
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conda activate test-env
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# Test installed packages
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conda list -n test-env
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- name: Run tests
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run: |
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. $CONDA/etc/profile.d/conda.sh
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conda activate test-env
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pushd ./${{ env.MODULE_NAME }}
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pytest
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popd
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upload_linux:
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needs: test_linux
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if: ${{github.ref == 'refs/heads/main' || (startsWith(github.ref, 'refs/heads/release') == true) || github.event_name == 'push' && contains(github.ref, 'refs/tags/')}}
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runs-on: ubuntu-20.04
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strategy:
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matrix:
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python: ['3.8', '3.9', '3.10']
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steps:
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- name: Download artifact
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uses: actions/download-artifact@v3
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with:
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name: ${{ env.PACKAGE_NAME }} ${{ runner.os }} Python ${{ matrix.python }}
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- name: Install anaconda-client
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run: conda install anaconda-client
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- name: Add conda to system path
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run: echo $CONDA/bin >> $GITHUB_PATH
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- name: Upload
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env:
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ANACONDA_TOKEN: ${{ secrets.PYCODDIYTOKEN }}
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run: |
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anaconda --token ${{ env.ANACONDA_TOKEN }} upload --user pycoddiy --label dpep ${PACKAGE_NAME}-*.tar.bz2
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build_windows:
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runs-on: windows-latest
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strategy:
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matrix:
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python: ['3.8', '3.9', '3.10']
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env:
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conda-bld: C:\Miniconda\conda-bld\win-64\
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steps:
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- uses: actions/checkout@v3
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with:
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fetch-depth: 0
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- uses: conda-incubator/setup-miniconda@v2
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with:
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use-only-tar-bz2: true
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auto-activate-base: true
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conda-build-version: "*"
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activate-environment: true
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python-version: ${{ matrix.python }}
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- name: Cache conda packages
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uses: actions/cache@v3
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env:
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CACHE_NUMBER: 0 # Increase to reset cache
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with:
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path: /home/runner/conda_pkgs_dir
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key:
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${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-python-${{ matrix.python }}-${{hashFiles('**/meta.yaml') }}
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restore-keys: |
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${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-python-${{ matrix.python }}-
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${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-
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- name: Build conda package
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run: |
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cd ./demos/mcpi
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conda build --keep-old-work --dirty --no-test --python ${{ matrix.python }} -c intel -c main --override-channels conda-recipe
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- name: Upload artifact
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uses: actions/upload-artifact@v3
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with:
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name: ${{ env.PACKAGE_NAME }} ${{ runner.os }} Python ${{ matrix.python }}
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path: ${{ env.conda-bld }}${{ env.PACKAGE_NAME }}-*.tar.bz2
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test_windows:
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needs: build_windows
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runs-on: ${{ matrix.runner }}
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defaults:
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run:
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shell: cmd /C CALL {0}
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strategy:
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matrix:
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python: ['3.8', '3.9', '3.10']
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experimental: [false]
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runner: [windows-latest]
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continue-on-error: ${{ matrix.experimental }}
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env:
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workdir: '${{ github.workspace }}'
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CHANNELS: -c dppy/label/dev -c intel -c main --override-channels
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steps:
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- name: Checkout sources
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uses: actions/checkout@v3
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with:
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fetch-depth: 0
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- name: Download artifact
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uses: actions/download-artifact@v3
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with:
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name: ${{ env.PACKAGE_NAME }} ${{ runner.os }} Python ${{ matrix.python }}
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- uses: conda-incubator/setup-miniconda@v2
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with:
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use-only-tar-bz2: false
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auto-update-conda: true
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conda-build-version: '*'
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miniconda-version: 'latest'
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activate-environment: test-env
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python-version: ${{ matrix.python }}
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- name: conda info
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shell: cmd /C CALL {0}
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run: |
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conda info
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- name: conda config --show
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shell: cmd /C CALL {0}
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run: |
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conda config --show
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- name: Create conda channel with the artifact bit
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shell: cmd /C CALL {0}
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run: |
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echo ${{ env.workdir }}
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mkdir ${{ env.workdir }}\channel\win-64
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move ${{ env.PACKAGE_NAME }}-*.tar.bz2 ${{ env.workdir }}\channel\win-64
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dir ${{ env.workdir }}\channel\win-64
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- name: Index the channel
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shell: cmd /C CALL {0}
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run: conda index ${{ env.workdir }}\channel
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- name: Collect dependencies
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shell: cmd /C CALL {0}
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run: |
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conda install -n test-env ${{ env.PACKAGE_NAME }} python=${{ matrix.python }} -c ${{ env.workdir }}/channel ${{ env.CHANNELS }} --only-deps --dry-run > lockfile && conda activate test-env
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- name: Display lockfile content
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shell: pwsh
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run: Get-Content -Path .\lockfile
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- name: Cache conda packages
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uses: actions/cache@v3
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env:
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CACHE_NUMBER: 0 # Increase to reset cache
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with:
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path: /home/runner/conda_pkgs_dir
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key:
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${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-python-${{ matrix.python }}-${{hashFiles('lockfile') }}
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restore-keys: |
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${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-python-${{ matrix.python }}-
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${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-
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- name: Install dependencies
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shell: cmd /C CALL {0}
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run: |
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conda install -n test-env ${{ env.PACKAGE_NAME }} pytest python=${{ matrix.python }} -c ${{ env.workdir }}/channel ${{ env.CHANNELS }}
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- name: Install opencl_rt
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shell: cmd /C CALL {0}
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run: conda install -n test-env opencl_rt -c intel --override-channels
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- name: Configure Intel OpenCL CPU RT
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shell: pwsh
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run: |
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$script_path="$env:CONDA_PREFIX\Scripts\set-intel-ocl-icd-registry.ps1"
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&$script_path
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# Check the variable assisting OpenCL CPU driver to find TBB DLLs which are not located where it expects them by default
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$cl_cfg="$env:CONDA_PREFIX\Library\lib\cl.cfg"
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Get-Content -Tail 5 -Path $cl_cfg
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- name: Conda list
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shell: cmd /C CALL {0}
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run: conda list -n test-env
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- name: Run tests
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shell: pwsh
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run: |
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ls
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conda activate test-env
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pushd ./${{ env.MODULE_NAME }}
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pytest
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popd
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upload_windows:
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needs: test_windows
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if: ${{github.ref == 'refs/heads/main' || (startsWith(github.ref, 'refs/heads/release') == true) || github.event_name == 'push' && contains(github.ref, 'refs/tags/')}}
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runs-on: windows-latest
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strategy:
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matrix:
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python: ['3.8', '3.9', '3.10']
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steps:
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- name: Download artifact
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uses: actions/download-artifact@v3
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with:
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name: ${{ env.PACKAGE_NAME }} ${{ runner.os }} Python ${{ matrix.python }}
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- uses: conda-incubator/setup-miniconda@v2
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with:
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auto-activate-base: true
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activate-environment: ""
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- name: Install anaconda-client
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run: conda install anaconda-client
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- name: Upload
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env:
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ANACONDA_TOKEN: ${{ secrets.PYCODDIYTOKEN }}
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run: |
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anaconda --token ${{ env.ANACONDA_TOKEN }} upload --user pycoddiy --label dpep ${{ env.PACKAGE_NAME }}-*.tar.bz2

‎docs/sources/benchmarks.rst‎

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==========
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**Data Parallel Extensions for Python** provide a set of
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`benchmarks<https://github.com/IntelPython/dpbench>`_ illustrating different aspects of
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`benchmarks <https://github.com/IntelPython/dpbench>`_ illustrating different aspects of
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implementing the performant code with Data Parallel Extensions for Python.
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Benchmarks represent some real life numerical problem or some important part (kernel) of real life application.
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Each application/kernel is implemented in several variants (not necessarily all variants):
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all or select benchmarks and variants to evaluate their performance on different hardware.
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For more details please refer to ``dpbench``
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`documentation<https://github.com/IntelPython/dpbench/blob/main/README.md>`_.
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`documentation <https://github.com/IntelPython/dpbench/blob/main/README.md>`_.

‎docs/sources/demos.rst‎

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.. _demos:
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.. include:: ./ext_links.txt
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Demos
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=====
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There are several demo applications illustrating the power of the **Data Parallel Extensions for Python**. They are:
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- `Monte Carlo Pi <https://github.com/IntelPython/DPEP/tree/main/demos/mcpi>`_ -
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The Monte Carlo method to estimate the value of :math:`\pi`.
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- `Mandelbrot Set <https://github.com/IntelPython/DPEP/tree/main/demos/mandelbrot>`_ -
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Visualization of the breathtaking process of diving in the famous Mandelbrot fractal
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- `Game of Life <https://github.com/IntelPython/DPEP/tree/main/demos/game-of-life>`_ -
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Visualization of the life evolution using famous Conway's model
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All demos are located in the `GitHub repository <https://github.com/IntelPython/DPEP/tree/main/demos>`_.
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For more details please refer to the documentation located in the individual demo directory.

‎docs/sources/examples.rst‎

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.. _examples:
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.. include:: ./ext_links.txt
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List of examples
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================
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All examples are located in the `GitHub repository<https://github.com/IntelPython/DPEP/tree/main/examples>`_.
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Examples
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========
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All examples are located in the `GitHub repository <https://github.com/IntelPython/DPEP/tree/main/examples>`_.
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Their names start with the 2-digit number followed by a descriptive name.
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You can run examples in any order, however, if
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you are new to the Data Parallel Extensions for Python, it is recommended to go in the order examples are enumerated.

‎docs/sources/index.rst‎

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examples
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jupyter_notebook
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benchmarks
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demos
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useful_links

‎docs/sources/jupyter_notebook.rst‎

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*********
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Getting started Jupyter* Notebooks illustrating the usage of **Data Parallel Extensions for Python** are located
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in the `GitHub repository<https://github.com/IntelPython/DPEP/tree/main/notebooks>`_
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in the `GitHub repository <https://github.com/IntelPython/DPEP/tree/main/notebooks>`_
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To run the tutorial, in the command line prompt type:
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in the directory where the notebook server was started.
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Navigate to the notebook of your interest and open it in the dashboard.
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For more information please refer to `Jupyter documentation<https://docs.jupyter.org/en/latest/running.html>`_
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For more information please refer to `Jupyter documentation <https://docs.jupyter.org/en/latest/running.html>`_
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.. toctree::
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:maxdepth: 1

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