Building a FastAPI Backend: Getting Started

FastAPI has become my go-to framework for building Python APIs. It's fast, modern, and comes with automatic API documentation out of the box.

Why FastAPI?

Here are the main reasons I choose FastAPI for backend projects:

• Performance: Built on Starlette and Pydantic, it's one of the fastest Python frameworks
• Type Safety: Full Python type hints support with automatic validation
• Auto Documentation: Swagger UI and ReDoc generated automatically
• Modern Python: Async/await support for concurrent operations
• Developer Experience: Excellent error messages and autocomplete

Basic Setup

First, install FastAPI and Uvicorn:

pip install fastapi uvicorn[standard]

Create a simple API:

from fastapi import FastAPI

app = FastAPI()

@app.get("/")
async def root():
    return {"message": "Hello World"}

@app.get("/items/{item_id}")
async def read_item(item_id: int, q: str = None):
    return {"item_id": item_id, "q": q}

Run the server:

uvicorn main:app --reload

Visit http://localhost:8000/docs to see the automatic API documentation.

Project Structure

For production apps, I organize projects like this:

app/
├── main.py
├── models/
│   └── user.py
├── schemas/
│   └── user.py
├── routers/
│   └── users.py
├── database.py
└── config.py

Next Steps

In the next post, I'll cover:

• Database integration with SQLAlchemy
• Authentication with JWT tokens
• Request validation with Pydantic
• Error handling and middleware
• Testing with pytest

Stay tuned!