python-fastapi-patterns

Structure a production-ready FastAPI project by separating app setup, shared dependencies, feature routers, services, repositories, and core utilities. Use dependency injection wiring for repositories and services alongside async SQLAlchemy session patterns to maintain a clean architecture.

Pydantic v2 schema design uses request and response models with built-in validation as the single source of truth. FastAPI automatically generates OpenAPI documentation directly from these Pydantic v2 schemas, ensuring clear API contracts without manual specification writing.

Implement JWT authentication in FastAPI using HTTPBearer to securely extract and validate tokens. This approach integrates with FastAPI's dependency injection system to protect endpoints and ensure consistent security practices across your REST API services.

Yes, you can use lifespan startup-shutdown events for managing async endpoints and background tasks in FastAPI. This async-first implementation pattern handles resource initialization and cleanup seamlessly while supporting background task execution.

FastAPI supports custom domain error handlers and request-id middleware for structured request logging. This combination provides middleware-based observability, allowing you to trace requests through your API and handle domain-specific errors consistently.

Test FastAPI services using test-friendly dependency overrides to mock repositories, security, and database sessions. This pattern allows you to isolate endpoint logic and validate behavior without hitting actual external services or JWT authentication layers.