fastapi-patterns

An opinionated directory layout organizes routes, Pydantic models, and dependencies separately to ensure a maintainable and scalable FastAPI codebase as the application grows.

Implement dependency injection in FastAPI by defining reusable functions for common operations like database sessions. This pattern decouples business logic from endpoints, making Python web service code cleaner and easier to test.

FastAPI handles asynchronous programming using async endpoints for non-blocking I/O operations. It supports background tasks to offload long-running processes, ensuring efficient API request handling without delaying client responses.

Yes, you can use WebSockets in a FastAPI application to support real-time communication. This pattern allows maintaining persistent client connections for instant data streaming alongside standard HTTP API endpoints.

You test FastAPI applications with httpx by simulating asynchronous HTTP requests against your API endpoints. This pattern provides comprehensive coverage for validating route behavior, data serialization, and response schemas.

Yes, Pydantic models are needed in FastAPI to define clear request and response schemas. They handle automatic data validation and serialization, ensuring type-safe API design and robust backend operations.