python-testing

You can write pytest tests for FastAPI endpoints by using AsyncClient for async HTTP requests, applying pytest.mark.asyncio, and overriding FastAPI dependencies. Reusable conftest.py fixtures handle DB setup via Testcontainers for real PostgreSQL integration testing.

Structuring reusable pytest fixtures involves creating a conftest.py file to manage service wiring and database setup. Using Testcontainers provides a real PostgreSQL instance for repository-level integration tests, ensuring persistent behavior validation without manual mock databases.

Mock external dependencies in async Python tests by applying AsyncMock and patch. This isolates external service calls, while pytest.raises validates failure paths and exception assertions, ensuring your test suite accurately captures error handling.

Yes, you can use Testcontainers to run pytest integration tests against a real PostgreSQL database. This approach validates actual persistence behavior at the repository level, providing reliable integration testing without maintaining manual database mocks.

Measure code coverage and separate tests by applying clear pytest markers for integration separation. Standardize coverage commands to generate reports, running unit and integration tests independently to ensure precise coverage tracking for your Python application.