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Creation of pipeline to publish dts python package to pypi (#43)
* Creating of pipeline to publish dts python package to pypi Signed-off-by: Ryan Lettieri <[email protected]> * Upgrading version of durabletask-azuremanaged from 0.1b1 to 0.1 Signed-off-by: Ryan Lettieri <[email protected]> * Updating versioning on packages Signed-off-by: Ryan Lettieri <[email protected]> * Incrementing version to allign with pypi Signed-off-by: Ryan Lettieri <[email protected]> * Adressing majority of first round of feedback Signed-off-by: Ryan Lettieri <[email protected]> * Updating pipeline to have linting Signed-off-by: Ryan Lettieri <[email protected]> * Updating versions in pyproject.toml Signed-off-by: Ryan Lettieri <[email protected]> * Updating working dirs in yml Signed-off-by: Ryan Lettieri <[email protected]> * Adding requirements.txt Signed-off-by: Ryan Lettieri <[email protected]> * Moving durabletask tests into specific dir and more Signed-off-by: Ryan Lettieri <[email protected]> * Fixing more paths Signed-off-by: Ryan Lettieri <[email protected]> * ATtemptign to ignore durabletask-azuremanaged folder Signed-off-by: Ryan Lettieri <[email protected]> * installing dts dependencies Signed-off-by: Ryan Lettieri <[email protected]> * Changing path for requirements.txt Signed-off-by: Ryan Lettieri <[email protected]> * Moving init.py Signed-off-by: Ryan Lettieri <[email protected]> * Updating readme and some tests Signed-off-by: Ryan Lettieri <[email protected]> * Running all dts tests in publish pipeline Signed-off-by: Ryan Lettieri <[email protected]> * Removing PYTHONPATH and installing regular deps Signed-off-by: Ryan Lettieri <[email protected]> * Adding timeout to dts orchestration e2e test Signed-off-by: Ryan Lettieri <[email protected]> * Removing suspend and continue as new tests from dts Signed-off-by: Ryan Lettieri <[email protected]> * Removing raise event timeout tests Signed-off-by: Ryan Lettieri <[email protected]> * Only runnign publish on tag push Signed-off-by: Ryan Lettieri <[email protected]> * Changing dts action to run on tag creation Signed-off-by: Ryan Lettieri <[email protected]> * Updating tag name Signed-off-by: Ryan Lettieri <[email protected]> * Adressing review feedback Signed-off-by: Ryan Lettieri <[email protected]> * Fixing run requirements in actions and adding exit-zero Signed-off-by: Ryan Lettieri <[email protected]> * Update .github/workflows/publish-dts-sdk.yml --------- Signed-off-by: Ryan Lettieri <[email protected]> Co-authored-by: Bernd Verst <[email protected]>
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‎.github/workflows/pr-validation.yml

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# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
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# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python
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name: Build Validation
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on:
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push:
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branches: [ "main" ]
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pull_request:
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branches: [ "main" ]
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merge_group:
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jobs:
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build:
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runs-on: ubuntu-latest
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strategy:
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fail-fast: false
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matrix:
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python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v5
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with:
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python-version: ${{ matrix.python-version }}
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install flake8 pytest
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pip install -r requirements.txt
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- name: Lint with flake8
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run: |
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flake8 . --count --show-source --statistics --exit-zero
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- name: Pytest unit tests
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run: |
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pytest -m "not e2e" --verbose
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# Sidecar for running e2e tests requires Go SDK
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- name: Install Go SDK
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uses: actions/setup-go@v5
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with:
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go-version: 'stable'
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# Install and run the durabletask-go sidecar for running e2e tests
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- name: Pytest e2e tests
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run: |
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go install github.com/microsoft/durabletask-go@main
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durabletask-go --port 4001 &
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pytest -m "e2e" --verbose
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# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
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# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python
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name: Build Validation
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on:
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push:
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branches: [ "main" ]
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pull_request:
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branches: [ "main" ]
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merge_group:
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jobs:
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build:
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runs-on: ubuntu-latest
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strategy:
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fail-fast: false
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matrix:
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python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v5
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with:
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python-version: ${{ matrix.python-version }}
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- name: Install durabletask dependencies
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run: |
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python -m pip install --upgrade pip
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pip install flake8 pytest
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pip install -r requirements.txt
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- name: Install durabletask-azuremanaged dependencies
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working-directory: examples/dts
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run: |
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python -m pip install --upgrade pip
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pip install -r requirements.txt
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- name: Lint with flake8
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run: |
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flake8 . --count --show-source --statistics --exit-zero
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- name: Pytest unit tests
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working-directory: tests/durabletask
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run: |
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pytest -m "not e2e and not dts" --verbose
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# Sidecar for running e2e tests requires Go SDK
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- name: Install Go SDK
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uses: actions/setup-go@v5
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with:
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go-version: 'stable'
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# Install and run the durabletask-go sidecar for running e2e tests
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- name: Pytest e2e tests
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working-directory: tests/durabletask
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run: |
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go install github.com/microsoft/durabletask-go@main
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durabletask-go --port 4001 &
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pytest -m "e2e and not dts" --verbose

‎.github/workflows/publish-dts-sdk.yml

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name: Publish Durable Task Scheduler to PyPI
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on:
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push:
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branches:
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- "main"
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tags:
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- "azuremanaged-v*" # Only run for tags starting with "azuremanaged-v"
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pull_request:
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branches:
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- "main"
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jobs:
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lint:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python 3.12
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uses: actions/setup-python@v5
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with:
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python-version: 3.12
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- name: Install dependencies
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working-directory: durabletask-azuremanaged
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run: |
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python -m pip install --upgrade pip
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pip install setuptools wheel tox
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pip install flake8
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- name: Run flake8 Linter
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working-directory: durabletask-azuremanaged
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run: flake8 .
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run-docker-tests:
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env:
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EMULATOR_VERSION: "v0.0.5" # Define the variable
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needs: lint
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runs-on: ubuntu-latest
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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- name: Pull Docker image
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run: docker pull mcr.microsoft.com/dts/dts-emulator:$EMULATOR_VERSION
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- name: Run Docker container
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run: |
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docker run --name dtsemulator -d -p 8080:8080 mcr.microsoft.com/dts/dts-emulator:$EMULATOR_VERSION
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- name: Wait for container to be ready
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run: sleep 10 # Adjust if your service needs more time to start
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- name: Set environment variables
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run: |
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echo "TASKHUB=default" >> $GITHUB_ENV
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echo "ENDPOINT=http://localhost:8080" >> $GITHUB_ENV
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- name: Install durabletask dependencies
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run: |
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python -m pip install --upgrade pip
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pip install flake8 pytest
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pip install -r requirements.txt
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- name: Install durabletask-azuremanaged dependencies
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working-directory: examples/dts
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run: |
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python -m pip install --upgrade pip
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pip install -r requirements.txt
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- name: Run the tests
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working-directory: tests/durabletask-azuremanaged
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run: |
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pytest -m "dts" --verbose
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publish:
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if: startsWith(github.ref, 'refs/tags/azuremanaged-v') # Only run if a matching tag is pushed
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needs: run-docker-tests
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runs-on: ubuntu-latest
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steps:
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- name: Checkout code
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uses: actions/checkout@v4
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- name: Extract version from tag
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run: echo "VERSION=${GITHUB_REF#refs/tags/azuremanaged-v}" >> $GITHUB_ENV # Extract version from the tag
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- name: Set up Python
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uses: actions/setup-python@v5
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with:
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python-version: "3.12" # Adjust Python version as needed
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install build twine
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- name: Build package from directory durabletask-azuremanaged
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working-directory: durabletask-azuremanaged
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run: |
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python -m build
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- name: Check package
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working-directory: durabletask-azuremanaged
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run: |
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twine check dist/*
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- name: Publish package to PyPI
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env:
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TWINE_USERNAME: __token__
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TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN_AZUREMANAGED }} # Store your PyPI API token in GitHub Secrets
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working-directory: durabletask-azuremanaged
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run: |
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twine upload dist/*

‎durabletask-azuremanaged/pyproject.toml

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[project]
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name = "durabletask.azuremanaged"
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version = "0.1b1"
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version = "0.1.2"
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description = "Extensions for the Durable Task Python SDK for integrating with the Durable Task Scheduler in Azure"
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keywords = [
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"durable",

‎examples/dts/README.md

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## Prerequisites
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All the examples assume that you have a Durable Task Scheduler taskhub created.
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There are 2 separate ways to run an example:
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1. Using the emulator.
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2. Using a real scheduler and taskhub.
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All the examples by defualt assume that you have a Durable Task Scheduler taskhub created.
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## Running with a scheduler and taskhub resource
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The simplest way to create a taskhub is by using the az cli commands:
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1. Create a scheduler:
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1. Grant yourself the `Durable Task Data Contributor` role over your scheduler
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## Running with the emulator
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The emulator is a simulation of a scheduler and taskhub. It is the 'backend' of the durabletask-azuremanaged system packaged up into an easy to use docker container. For these steps, it is assumed that you are using port 8080.
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In order to use the emulator for the examples, perform the following steps:
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1. Install docker if it is not already installed.
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2. Pull down the docker image for the emulator:
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`docker pull mcr.microsoft.com/dts/dts-emulator:v0.0.4`
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3. Run the emulator and wait a few seconds for the container to be ready:
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`docker run --name dtsemulator -d -p 8080:8080 mcr.microsoft.com/dts/dts-emulator:v0.0.4`
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4. Set the environment variables that are referenced and used in the examples:
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1. If you are using windows powershell:
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`$env:TASKHUB="default"`
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`$env:ENDPOINT="http://localhost:8080"`
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2. If you are using bash:
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`export TASKHUB=default`
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`export ENDPOINT=http://localhost:8080`
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5. Finally, edit the examples to change the `token_credential` input of both the `DurableTaskSchedulerWorker` and `DurableTaskSchedulerClient` to a value of `None`
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## Running the examples
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Now, you can simply execute any of the examples in this directory using `python3`:

‎examples/dts/requirements.txt

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autopep8
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grpcio>=1.60.0 # 1.60.0 is the version introducing protobuf 1.25.X support, newer versions are backwards compatible
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protobuf
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azure-identity
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durabletask-azuremanaged
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durabletask

‎pyproject.toml

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[project]
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name = "durabletask"
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version = "0.2b1"
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version = "0.2.0"
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description = "A Durable Task Client SDK for Python"
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keywords = [
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"durable",

‎tests/durabletask-azuremanaged/__init__.py

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‎tests/durabletask-azuremanaged/test_dts_activity_sequence.py

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"""End-to-end sample that demonstrates how to configure an orchestrator
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that calls an activity function in a sequence and prints the outputs."""
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import os
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from durabletask import client, task
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from durabletask.azuremanaged.client import DurableTaskSchedulerClient
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from durabletask.azuremanaged.worker import DurableTaskSchedulerWorker
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import pytest
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pytestmark = pytest.mark.dts
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def hello(ctx: task.ActivityContext, name: str) -> str:
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"""Activity function that returns a greeting"""
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return f'Hello {name}!'
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def sequence(ctx: task.OrchestrationContext, _):
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"""Orchestrator function that calls the 'hello' activity function in a sequence"""
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# call "hello" activity function in a sequence
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result1 = yield ctx.call_activity(hello, input='Tokyo')
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result2 = yield ctx.call_activity(hello, input='Seattle')
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result3 = yield ctx.call_activity(hello, input='London')
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# return an array of results
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return [result1, result2, result3]
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# Read the environment variable
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taskhub_name = os.getenv("TASKHUB")
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# Check if the variable exists
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if taskhub_name:
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print(f"The value of TASKHUB is: {taskhub_name}")
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else:
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print("TASKHUB is not set. Please set the TASKHUB environment variable to the name of the taskhub you wish to use")
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print("If you are using windows powershell, run the following: $env:TASKHUB=\"<taskhubname>\"")
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print("If you are using bash, run the following: export TASKHUB=\"<taskhubname>\"")
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exit()
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# Read the environment variable
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endpoint = os.getenv("ENDPOINT")
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# Check if the variable exists
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if endpoint:
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print(f"The value of ENDPOINT is: {endpoint}")
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else:
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print("ENDPOINT is not set. Please set the ENDPOINT environment variable to the endpoint of the scheduler")
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print("If you are using windows powershell, run the following: $env:ENDPOINT=\"<schedulerEndpoint>\"")
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print("If you are using bash, run the following: export ENDPOINT=\"<schedulerEndpoint>\"")
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exit()
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# configure and start the worker
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with DurableTaskSchedulerWorker(host_address=endpoint, secure_channel=True,
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taskhub=taskhub_name, token_credential=None) as w:
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w.add_orchestrator(sequence)
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w.add_activity(hello)
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w.start()
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# Construct the client and run the orchestrations
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c = DurableTaskSchedulerClient(host_address=endpoint, secure_channel=True,
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taskhub=taskhub_name, token_credential=None)
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instance_id = c.schedule_new_orchestration(sequence)
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state = c.wait_for_orchestration_completion(instance_id, timeout=60)
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if state and state.runtime_status == client.OrchestrationStatus.COMPLETED:
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print(f'Orchestration completed! Result: {state.serialized_output}')
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elif state:
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print(f'Orchestration failed: {state.failure_details}')

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