python-patterns

Choosing between FastAPI and Django depends on your project context. Use FastAPI for API-first services requiring async execution, or Django if you need built-in admin features and team familiarity for full-stack web apps.

Use async for I/O-bound workloads like API calls or database operations, and sync for CPU-bound work. Applying async concurrency rules correctly prevents common execution bottlenecks and improves API responsiveness.

A maintainable Python project structure applies type hinting strategy and Pydantic for validation. Organizing code for scalability ensures clarity and testability across API-first services and background workers.

Yes, you need Pydantic for validation in FastAPI. It provides a type-hinting strategy that ensures correctness in validation-heavy systems, automatically validating incoming API requests and data models.

Async concurrency for background workers handles I/O-bound tasks efficiently. By applying async execution rules, you prevent common concurrency mistakes and improve workload throughput for background operations.

Using async for CPU-bound work limits performance because it blocks the event loop. You should not use async for heavy processing; instead, apply sync execution to ensure correct CPU utilization and avoid concurrency mistakes.