15 FastAPI Best Practices For Production

00:00 Introduction to FastAPI Best Practices 00:22 Avoid Async for Blocking Operations 01:24 Use Async Friendly Code 01:46 Avoid Heavy Computation in Endpoints 02:51 FastAPI Dependencies Rules 03:11 Don't Make Users Wait (Background Tasks) 04:00 Don't Expose Swagger/ReDoc in Production 04:22 Create Custom Pydantic Base Model 05:00 Don't Manually Construct Response Models 05:23 Validate with Pydantic, Not Your Code 06:01 Use Dependencies for DB-Based Validation 06:33 Avoid New DB Connections in Every Endpoint 07:27 Use Lifespan Events for Resource Management 08:02 Don't Hardcode Secrets 09:29 Use Structured Logging 11:24 Best Practices for Deploying FastAPI You'll learn how to: ✅ Avoid common async mistakes ✅ Optimize database connections ✅ Handle background tasks the right way ✅ Secure your API in production ✅ Improve performance with structured logging ✅ Deploy FastAPI using Uvicorn + Gunicorn + uvloop ... FastAPI is designed to recognize that {ts:74} you're performing blocking operations within these def endpoints and will intelligently run them in separate threads. This way, {ts:81} your FastAPI application remains responsive. Number two, use async friendly code. To get the most performance out {ts:88} of your FastAPI application, use non-blocking libraries as much as possible so you can declare your endpoints as {ts:94} async endpoints. Use asyncio.sleep instead of time.sleep httpx.AsyncClient instead of the requests module {ts:102} and motor instead of pymongo. I hope you get the idea. Number three, don't do heavy computation {ts:108} in FastAPI endpoints, or you'll block your server. FastAPI is built for I/O-bound workloads. {ts:114} So, avoid processing images or videos or running heavy machine learning models {ts:118} directly in your endpoints. The reason is that your application will be unresponsive for as long {ts:123} as the computation runs. What should you do instead? … {ts:220} limitations: don't use BackgroundTasks for anything requiring guaranteed delivery, retries, or tasks that run for a long duration. {ts:228} For those more robust needs, a dedicated message queue and worker system (like Celery) is still the superior {ts:234} choice. Remember, if your FastAPI process crashes before a background task completes, that task will fail. {ts:240} Number six, don't expose Fastapi Swagger or ReDoc in production unless your API is public-facing. FastAPI automatically generates {ts:248} these docs, which is great during development. But in production, they can reveal {ts:252} endpoints that might still be incomplete or lack proper security. … Don't scatter validation across your route functions with if statements and manual {ts:333} checks. It might seem easier at first, but it quickly turns into a mess. You lose consistent error {ts:339} responses, and clients get cryptic 400s with no clue why their request failed. You end up repeating the