python-expert

FastAPI with Pydantic models enforces type safety at request and response boundaries. Define Pydantic models for your data schemas, use them as FastAPI endpoint parameters, and the framework automatically validates incoming data, serializes responses, and generates OpenAPI documentation.

Dependency injection decouples components and improves testability. FastAPI's built-in DI system, Flask extensions, and Django's service layer patterns let you inject database connections, configuration, or business logic into handlers. This enables clean architecture and easier mocking in tests.

Async background tasks offload long-running operations from request handlers. FastAPI supports BackgroundTasks, while Django and Flask use Celery or similar task queues. Queue work asynchronously, monitor completion, and separate API response time from task execution.

ORM optimization reduces N+1 queries and database load. Use select_related and prefetch_related in Django, eager loading in SQLAlchemy, and query indexing across all frameworks. Profile queries, batch operations, and cache results to improve API response time.

Custom exception handlers transform application errors into meaningful HTTP responses. Define exception classes, attach them to handlers in FastAPI or Flask, and return structured error payloads with status codes. This improves debugging and client integration.

FastAPI prioritizes async-first design and automatic validation; Flask offers minimal overhead and flexibility; Django provides batteries-included ORM and admin. Choose FastAPI for performance-critical APIs, Flask for lightweight services, Django for monolithic applications with built-in features.