python-patterns

Choosing between FastAPI, Django, and Flask depends on your project needs. FastAPI offers speed and async capabilities, Django provides batteries-included features, and Flask allows lightweight flexibility for custom project structures.

Use asynchronous programming in Python for I/O-bound tasks to handle concurrent operations efficiently. Use synchronous programming for CPU-bound tasks where processing logic requires blocking execution until completion.

The best way to use type hints with Pydantic involves applying them for data validation and clarity. Pydantic enforces type hints at runtime, ensuring robust data parsing and maintainable Python application code.

Structure a large Python application by following modular organization principles. Separating concerns into distinct directories for routes, models, and services ensures maintainable code across small, medium, and large project scales.

FastAPI is optimized for asynchronous I/O-bound tasks rather than CPU-bound tasks. For heavy CPU-bound processing, synchronous paradigms or Django's synchronous architecture may be more appropriate to prevent event loop blocking.