Keeping your projects nice and clean — Jan Musílek

Python Testing Automation

Learn best practices for maintaining clean Python projects using autoformatters, code checks, and CI tools. Tips for efficient development and team collaboration.

Key takeaways

Use autoformatters to maintain consistent code style and save cognitive effort
- Don’t waste time arguing about specific formatting - let tools handle it
- Code review improves code quality and serves as bidirectional mentorship between junior and senior developers
- Set up continuous integration to enforce code quality checks
Use pre-commit hooks to catch issues before code reaches the server
Key tools recommended:
- Black or Ruff for autoformatting
- Flake8 for linting
- Bandit for security checks
- Pydoc style for docstring formatting
- MyPy for type checking
Keep tool configurations simple - start with defaults and build up gradually
Store project configuration in pyproject.toml
Automate manual tasks where possible
Don’t run formatting in CI - do it locally during development
Maintain consistency across projects to improve collaboration
Consider “bus factor” - ensure multiple team members can maintain the codebase
Keep dependencies and tools up to date but pin versions to avoid breaking changes
Use tools that provide autofix capabilities to save time on manual corrections

Keeping your projects nice and clean — Jan Musílek

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