Python's async ecosystem has matured significantly, with frameworks like FastAPI becoming production staples. Async excels for I/O-bound workloads—API calls, database queries, file operations—common in AI applications making multiple LLM API calls concurrently.
Framework Selection
FastAPI provides automatic documentation, type validation, and excellent developer experience. Starlette offers lower-level control as FastAPI's foundation. Django gains async capabilities incrementally, suitable for existing Django projects. Choose based on project requirements and team familiarity.
- FastAPI suits new API projects needing rapid development with modern features
- Starlette provides flexibility when FastAPI's opinions don't fit
- Django async views work within existing Django projects
- Use async database drivers like asyncpg for PostgreSQL
- Consider Uvicorn or Hypercorn as ASGI servers for production
Async Patterns
Proper async usage requires understanding event loop behavior. Avoid blocking calls that stall async benefits. Use asyncio.gather for concurrent operations. Implement proper error handling since exceptions in async code behave differently. Test async endpoints thoroughly.