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10 Async Pitfalls in FastAPI and How to Avoid Them
Mastering Asynchronous Code in FastAPI: Avoid These Common Traps That Slow Down Your App
Struggling with async in FastAPI? This guide uncovers 10 critical async mistakes that silently hurt performance — and how to fix them for smoother, faster APIs.
Introduction: The FastAPI Speed Trap
FastAPI promises lightning-fast performance — but only if you use async the right way. Many developers, especially those new to asynchronous Python, dive in excited by the non-blocking magic, only to find their APIs sluggish, buggy, or worse — completely broken under load.
I’ve been there.
In my early projects, I assumed slapping async on a function was all it took to unlock performance. I was wrong. FastAPI's performance edge heavily depends on correct async usage—and it’s easy to get it wrong.
If you’re building real-time APIs, handling high-concurrency workloads, or just want to avoid unnecessary slowdowns, this article is for you.
Here are the 10 most common async mistakes developers make in FastAPI — and exactly how to fix them.
