Python's flexibility is a gift and a trap. These practices keep production codebases maintainable as teams and features grow.
Structure and tooling
- Clear project layout with domain-oriented modules
- Dependency management with poetry/pip-tools and lockfiles
- Formatting and linting — ruff/black — enforced in CI
- Type hints everywhere; mypy or pyright in CI
Testing
pytest with fixtures, coverage on critical paths, and factory-based test data. For APIs, test happy path, validation, auth, and permissions. Tests are the contract that lets you refactor safely.
Performance
- Avoid N+1 queries — use select_related/prefetch_related or explicit joins
- Cache hot paths (Redis) and paginate large responses
- Use async where IO-bound; offload heavy work to Celery
- Profile before optimizing — measure, don't guess
Security
Keep secrets in environment vaults, validate all input, use parameterized queries, apply rate limits, and keep dependencies patched. Review permissions on multi-tenant data to prevent IDOR.
"Readable, tested Python is cheaper to run than clever Python. Optimize for the next engineer."