Cookbook: Building a FastAPI Backend

Now that you've mastered the fundamentals of Python, data structures, algorithms, and testing, it is time to build a real-world application. In this cookbook tutorial, we will construct a high-performance REST API backend using FastAPI.

Why FastAPI?

FastAPI is a modern, fast (high-performance) web framework for building APIs with Python 3.8+ based on standard Python type hints.

• Fast: It rivals Node.js and Go in performance.
• Easy: Automatic interactive API documentation.
• Validation: Automatic request body mapping and validation using Pydantic.

1. Setup

First, install FastAPI and an ASGI server, uvicorn.

python -m pip install fastapi uvicorn

Create a new file called main.py.

# non-runnable: requires fastapi
from fastapi import FastAPI

app = FastAPI()

@app.get("/")
def read_root():
    return {"Hello": "World"}

Run your server with:

uvicorn main:app --reload

2. Using Pydantic for Data Validation

FastAPI uses the type hints we covered earlier in the course, together with the Pydantic library, to validate data automatically. Let's create an endpoint that accepts data for a new user.

# non-runnable: requires fastapi
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from typing import Optional

app = FastAPI()

# Database mockup
db = []

# Define standard data schema using Pydantic
class User(BaseModel):
    id: int
    name: str
    age: int
    email: Optional[str] = None

@app.post("/users/")
def create_user(user: User):
    for u in db:
        if u.id == user.id:
            raise HTTPException(status_code=400, detail="User already exists")
    db.append(user)
    return {"status": "success", "user": user}

@app.get("/users/{user_id}", response_model=User)
def read_user(user_id: int):
    for user in db:
        if user.id == user_id:
            return user
    raise HTTPException(status_code=404, detail="User not found")

When someone sends a POST request with missing fields or an age defined as "twenty" instead of 20, FastAPI immediately returns an automatic 422 Unprocessable Entity error. You don't have to write validation code by hand.

3. The Power of Automatic Documentation

Because of the explicit type hints, FastAPI automatically generates two interactive documentation interfaces based on OpenAPI specifications:

• Swagger UI: Found at http://127.0.0.1:8000/docs
• ReDoc: Found at http://127.0.0.1:8000/redoc

Open Swagger UI in your browser to instantly test the endpoints without using Postman or curl.

4. Async Endpoints and Query Parameters

FastAPI is built on ASGI, so a path function can be declared async def. Use it when the handler awaits I/O (a database or an external API) — it lets the server handle other requests while waiting. See the Async / Await tutorial for the underlying concepts.

Function arguments that are not part of the path become query parameters automatically. A parameter with a default is optional; one without is required.

# non-runnable: requires fastapi
from fastapi import FastAPI

app = FastAPI()

@app.get("/search/")
async def search(q: str, limit: int = 10):
    # GET /search/?q=python&limit=5
    return {"query": q, "limit": limit}

Here q is required and limit defaults to 10. FastAPI also validates types: passing limit=abc returns a 422 error.

5. Testing Your API

FastAPI provides a TestClient (built on httpx) so you can test endpoints with pytest — no running server needed. This ties together everything from the testing tutorials.

# non-runnable: requires fastapi
from fastapi.testclient import TestClient
from main import app

client = TestClient(app)

def test_read_root():
    response = client.get("/")
    assert response.status_code == 200
    assert response.json() == {"Hello": "World"}

Conclusion

FastAPI perfectly fuses Python's type annotations and asynchronous capabilities into an enterprise-ready framework. From here, you can connect your FastAPI backend to a real database using an ORM like SQLAlchemy and protect paths using standard OAuth2 security protocols.