fastapi-patterns

Structure a FastAPI project for production by applying the app factory pattern, modular v1 routers, and Pydantic BaseSettings for configuration management. This approach ensures clean separation of concerns and scalable architecture.

The best way to manage dependency injection in FastAPI is using structured DI patterns for routers, services, and security. This technique centralizes logic and enforces maintainable, reliable API skeletons.

Test async FastAPI endpoints using pytest combined with AsyncClient examples. These testing patterns provide reliable coverage for robust apps handling REST, WebSocket, and background tasks.

Handle FastAPI startup and shutdown lifecycle events properly by implementing app factory and lifespan management. This mechanism creates and boots apps with reliable initialization and teardown processes.

Yes, you can use these FastAPI architecture patterns for WebSocket endpoints and background tasks. The scaffolding supports building robust async APIs that handle real-time and delayed processing use cases.

You need Pydantic BaseSettings for FastAPI configuration management to securely load environment variables and env files. This ensures scalable configurations when migrating Python projects to robust API skeletons.