@tank/fastapi-mastery

Structure a production-ready FastAPI application by organizing code into separate routers, services, repositories, and shared core utilities. This architecture separates routing from business logic, supports clean application factories, and ensures clear per-request database session management.

Implement JWT authentication in FastAPI by using dependency injection for token-based security, settings, and role checks. Dependencies manage database sessions and authentication, while test-time overrides allow you to mock security layers during testing.

Use async SQLAlchemy 2.0 with Pydantic v2 in FastAPI by applying Pydantic models for field constraints, custom validators, and serialization rules. Async SQLAlchemy handles per-request database session management, while Pydantic manages request validation and error handling.

Yes, you can use FastAPI for SaaS backend deployment with Docker and Kubernetes. Production concerns include container-ready deployment practices, middleware, exception handling, background jobs, WebSockets, and performance tuning to ensure scalable API services.

Yes, FastAPI testing supports dependency overrides for database sessions and authentication. You can use test-time overrides to replace dependencies, enabling isolated unit testing of routing and service layers without hitting actual database or security systems.

Handle error handling and middleware configuration in a FastAPI project by defining centralized exception handlers and configuring middleware within the application factory. This ensures consistent validation, error responses, and request processing across all API endpoints.