Python CI Workflow with pytest

Python CI with GitHub Actions

A robust Python CI workflow validates code quality with linting and runs the test suite on every push. This workflow uses actions/setup-python to install a specific Python version and leverages pip caching for faster dependency installation.

Workflow YAML

name: Python CI

on:
  push:
    branches:
      - main
  pull_request:
    branches:
      - main

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
        uses: actions/checkout@v4

      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          python-version: '3.12'
          cache: 'pip'

      - name: Install dependencies
        run: |
          python -m pip install --upgrade pip
          pip install -r requirements.txt

      - name: Lint with flake8
        run: |
          pip install flake8
          flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics

      - name: Test with pytest
        run: |
          pip install pytest pytest-cov
          pytest --cov=src --cov-report=xml

      - name: Upload coverage
        uses: actions/upload-artifact@v4
        with:
          name: coverage-report
          path: coverage.xml

How It Works

1. Python setup: actions/setup-python@v5 installs the specified Python version and adds it to PATH. The cache: 'pip' option caches the pip download cache automatically.
2. Dependency installation: Always upgrade pip first, then install from requirements.txt. For projects using pyproject.toml, replace with pip install -e ".[dev]".
3. Linting: Flake8 checks for syntax errors and undefined names first (the most critical checks), then optionally run full style checks.
4. Testing: Pytest with coverage generates both terminal output and an XML report for CI integration.

Tips for Python CI

• Pin your Python version (e.g., 3.12) rather than using 3.x to avoid unexpected breakage.
• Use pip install -r requirements.txt for reproducible builds, or pip install -e ".[test]" for package projects.
• Consider adding mypy for type checking in projects using type hints.