How to Configure GitHub Actions CI for Python Using Poetry on Multiple Versions 🚀
Learn how to set up a robust GitHub Actions CI pipeline for your Python project using Poetry, testing across multiple Python versions to ensure compatibility and reliability.
Continuous Integration (CI) is a critical part of any modern software development workflow. If you’re managing dependencies and environments with Poetry, this guide will help you configure a robust GitHub Actions CI pipeline for your Python project across multiple Python versions. For a practical example, you can refer to the actual code in this GitHub repository: jdevto/python-poetry-hello. 🎉
Why Poetry for Python Projects? 🐍
Poetry simplifies Python dependency management and packaging. It provides:
- A clear
pyproject.tomlfile for dependencies and project metadata. - A virtual environment management system.
- Commands to build, publish, and manage dependencies.
Configuring GitHub Actions for Python Using Poetry on Multiple Versions
Below is a complete GitHub Actions workflow configuration to automate your CI pipeline with Poetry across Python versions 3.9 to 3.13. This example includes three types of triggers: on push to the main branch, on pull requests, and on a scheduled daily cron job. You can adjust these triggers to suit your own requirements.
name: ci
on:
push:
branches:
- main
pull_request:
schedule:
- cron: 0 12 * * *
workflow_dispatch:
jobs:
test:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ['3.9', '3.10', '3.11', '3.12', '3.13']
fail-fast: false
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
- name: Install Poetry
run: |
curl -sSL https://install.python-poetry.org | python3 -
echo "PATH=$HOME/.local/bin:$PATH" >> $GITHUB_ENV
- name: Install dependencies with Poetry
run: |
cd hello-world
poetry install --with dev
- name: Set PYTHONPATH to include the source directory
run: echo "PYTHONPATH=$PWD/hello-world" >> $GITHUB_ENV
- name: Run tests
run: |
cd hello-world
poetry run pytest --cov=hello-world --cov-report=term-missing
Key Steps in the Workflow
1. Checkout Code
The actions/checkout@v4 action fetches your code from the repository so it can be used in subsequent steps.
2. Set Up Python
The actions/setup-python@v4 action installs the specified Python versions using a matrix strategy, enabling tests to run on multiple Python versions.
3. Install Poetry
The script installs the latest version of Poetry using its official installation method and ensures it’s added to the PATH.
4. Install Dependencies
poetry install --with dev installs all the project’s dependencies, including development dependencies.
5. Set PYTHONPATH
The PYTHONPATH environment variable is configured to include the src directory, enabling proper module imports during testing.
6. Run Tests
poetry run pytest runs the tests defined in your project, with coverage reporting enabled via --cov=src --cov-report=term-missing.
Enhancements
1. Add Caching for Dependencies
To speed up your workflow, you can cache Poetry dependencies:
- name: Cache Poetry dependencies
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: ${{ runner.os }}-poetry-${{ hashFiles('poetry.lock') }}
restore-keys: |
${{ runner.os }}-poetry-
Add this step before installing dependencies to skip re-installing dependencies if nothing has changed.
Conclusion
By configuring this GitHub Actions workflow, you can automate testing across multiple Python versions and ensure that your Python project using Poetry is always in top shape. This setup includes steps to install dependencies, run tests, and even cache dependencies for faster builds. 🚀
If you have any questions or suggestions, feel free to share! 🙌 For more inspiration and a working example, visit the GitHub repository: jdevto/python-poetry-hello.
Top comments (0)