main.py
models.py
routes.py
schemas.py
database.py

app/...

When you first start with FastAPI, it’s tempting to throw everything into a single file — and it works fine… until your app grows. Then suddenly, your codebase becomes spaghetti.

In this post, we’ll go through how to structure a FastAPI project properly, using clean architecture principles that scale easily.

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🚀 Why Project Structure Matters

A good structure makes your project:

• Easier to maintain and scale.
• Easier for new developers to understand.
• Ready for testing, CI/CD, and deployment.

If your FastAPI project looks like this:

main.py
models.py
routes.py
schemas.py
database.py

…it’s time for an upgrade.

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🏗️ Recommended Folder Structure

Here’s a clean, production-ready structure I use for real projects:

app/
├── api/
│   ├── routes/
│   │   ├── users.py
│   │   ├── items.py
│   │   └── __init__.py
│   ├── deps.py
│   ├── __init__.py
│   └── api_v1.py
├── core/
│   ├── config.py
│   ├── security.py
│   └── __init__.py
├── db/
│   ├── base.py
│   ├── session.py
│   └── __init__.py
├── models/
│   ├── user.py
│   ├── item.py
│   └── __init__.py
├── schemas/
│   ├── user.py
│   ├── item.py
│   └── __init__.py
├── services/
│   ├── user_service.py
│   └── __init__.py
├── main.py
└── __init__.py

---

⚙️ Let’s Break It Down

core/

Contains global configurations — environment variables, security settings, and constants.

# app/core/config.py
from pydantic import BaseSettings

class Settings(BaseSettings):
APP_NAME: str = "My FastAPI App"
DATABASE_URL: str

class Config:
env_file = ".env"

settings = Settings()

---

db/

Handles all database setup — connection, session management, and base models.

# app/db/session.py
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from app.core.config import settings

engine = create_engine(settings.DATABASE_URL)
SessionLocal = sessionmaker(bind=engine, autocommit=False, autoflush=False)

---

api/routes/

Organize endpoints by domain — one file per feature.

# app/api/routes/users.py
from fastapi import APIRouter, Depends
from app.schemas.user import User
from app.services.user_service import get_all_users

router = APIRouter(prefix="/users", tags=["users"])

@router.get("/", response_model=list[User])
async def list_users():
return await get_all_users()

---

services/

Business logic lives here — keep it separate from routes.

# app/services/user_service.py
from app.db.session import SessionLocal
from app.models.user import User

async def get_all_users():
db = SessionLocal()
return db.query(User).all()

---

main.py

The entry point that ties everything together.

# app/main.py
from fastapi import FastAPI
from app.api.api_v1 import api_router
from app.core.config import settings

app = FastAPI(title=settings.APP_NAME)
app.include_router(api_router)

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🧠 Tips for Scalable FastAPI Projects

✅ Use Pydantic models for input/output validation ✅ Split logic into layers — routes, services, models ✅ Use dependency injection for clean imports ✅ Add logging early — don’t debug with print() ✅ Separate environment variables from code

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🧰 Example Repository

I’ve uploaded an example of this structure here: 👉 GitHub - fastapi-clean-structure (insert your repo link)

You can clone it, install dependencies, and start your app in seconds:

git clone https://github.com/yourusername/fastapi-clean-structure.git
cd fastapi-clean-structure
poetry install
poetry run uvicorn app.main:app --reload

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🔚 Conclusion

Clean project structure isn’t just about being “organized” — it’s about future-proofing your codebase. FastAPI makes things fast, but structure makes them sustainable.

If you found this useful, drop a ❤️ or follow me — I post about Python, FastAPI, and backend architecture regularly.