7 FastAPI Pitfalls I Faced Building Real Projects

FastAPI is fast, modern, and powerful — but it’s not foolproof. I learned that the hard way, in production.

7 FastAPI Pitfalls I Faced Building Real Projects

After building multiple real-world apps with FastAPI, I ran into tricky pitfalls that docs don’t warn you about. Here are 7 hard-earned lessons to save you time (and headaches).

…and how you can avoid them before they cost you time and sanity.

When I first discovered FastAPI, I was blown away. Type hints, automatic docs, and blazing speed? Count me in.

But like any framework, the honeymoon phase wears off when you start using it in real-world projects.

In this post, I’ll share 7 pitfalls I ran into while building production-grade APIs with FastAPI — along with the lessons I learned (sometimes the hard way).

If you’re using FastAPI or planning to, this might save you a few late nights.

1. Overusing Depends() Without Understanding It

FastAPI’s Depends() is a magic wand—but it can turn into a curse if you don’t understand dependency injection well.

In my early projects, I used Depends() for everything—DB sessions, auth, configs. But then I started hitting issues with nested dependencies and hard-to-debug behavior.

Use Depends() thoughtfully. Understand that dependencies are functions, not just configuration tools. If a dependency does too much (e.g., DB + auth + logging), refactor.

Use Annotated from Python 3.9+ to make your dependencies more readable:

from typing import Annotated 
 
user: Annotated[User, Depends(get_current_user)]

2. Relying Too Heavily on Pydantic Models for Business Logic

I was so excited about Pydantic’s validation that I started putting all logic into models — default values, type coercion, even computations. It felt clean… until it wasn’t.

The problem? Pydantic models are meant for validation and parsing — not for housing your app’s logic.

Keep validation in models, but put logic in services. Otherwise, you’ll mix concerns and create spaghetti.

3. Blocking Code in Asynchronous Routes

I thought just adding async def made my API asynchronous. Turns out, calling blocking functions (like time.sleep() or synchronous DB calls) inside async routes blocks the entire event loop.

Don’t use async def unless you’re actually calling non-blocking code (like an async DB driver or HTTP client). Otherwise, it’s just adding overhead.

Use this rule of thumb:

• Sync code → use def
• Async I/O → use async def

4. Poor Error Handling with Background Tasks

FastAPI makes background tasks look effortless, but here’s the kicker: if a background task fails, you won’t see the error unless you explicitly log or monitor it.

I learned this the hard way after a task silently failed and a user’s action never completed.

Wrap background tasks in try/except blocks and always log exceptions:

def my_background_task(): 
    try: 
        # task logic 
    except Exception as e: 
        logger.exception("Background task failed: %s", e)

And for mission-critical tasks? Consider Celery or RQ instead.

5. Ignoring Middleware Until It’s Too Late

Middleware seems like an advanced topic — until you need custom logging, request tracing, or response transformation.

I once tried bolting on middleware after building out 90% of the app. Refactoring was painful.

Plan middleware early. Add logging, request IDs, or CORS handling upfront. It’s easier to do it early than retrofitting later.

6. Auto Docs Becoming a Crutch

FastAPI’s OpenAPI docs are fantastic, but I made the mistake of relying on them for everything.

I skipped proper API documentation thinking, “Hey, the Swagger UI is good enough!”

Wrong.

Docs are for humans. Auto-generated docs help, but you still need human-friendly explanations for endpoints, error messages, and request flows. Invest time in writing clear API docs for your team or external users.

7. No Clear Project Structure

FastAPI is unopinionated. That’s great for flexibility — but also dangerous for beginners.

My first project had routes, models, and logic scattered everywhere.

As it grew, so did the chaos.

Adopt a clear structure early on. Here’s one I like:

/app 
  /api 
    /v1 
      routes.py 
      schemas.py 
      dependencies.py 
  /core 
    config.py 
    security.py 
  /services 
    user_service.py 
  /models 
    user.py

You’ll thank yourself when the app crosses 10k+ lines.

How to Structure Your FastAPI Projects (The Right Way)

Master the art of structuring FastAPI apps like a pro — whether you’re building APIs solo or scaling with a team.

Final Thoughts

FastAPI is incredible. It’s become my go-to for building APIs fast. But no tool is perfect out of the box — and even great frameworks have sharp edges.

If you’re just starting out or scaling your FastAPI project, keep these pitfalls in mind. Avoiding them might just save you a weekend (or two).

Have you faced similar struggles with FastAPI?
I’d love to hear your lessons in the comments

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