FastAPI: Why It's Our Go-To Choice for Python Backend Development

Introduction

Choosing the right framework can make or break your backend development project. After years of working with various Python frameworks, FastAPI has become our go-to choice for building APIs. Here's why—and why you should consider it for your next project.

What Is FastAPI?

FastAPI is a modern, high-performance web framework for building APIs with Python 3.7+. Created by Sebastián Ramírez, it's designed to be easy to use while delivering exceptional performance.

Key characteristics:

• Fast: On par with NodeJS and Go
• Fast to code: 200-300% faster development speed
• Fewer bugs: Reduces developer-induced errors by ~40%
• Intuitive: Great editor support and autocomplete
• Easy: Designed to be easy to use and learn
• Standards-based: Based on OpenAPI and JSON Schema

Why FastAPI Stands Out

1. Exceptional Performance

FastAPI is one of the fastest Python frameworks available, thanks to:

• Starlette for the web parts
• Pydantic for data validation
• Async support out of the box

Benchmark comparison (requests/second):

2. Automatic Documentation

FastAPI automatically generates interactive API documentation:

• Swagger UI: Available at /docs
• ReDoc: Available at /redoc

No extra configuration needed—just write your code and documentation is generated automatically.

3. Type Hints and Validation

Python type hints aren't just for documentation—FastAPI uses them for:

• Request validation
• Response serialisation
• Editor autocomplete
• Automatic documentation

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class Item(BaseModel):
    name: str
    price: float
    is_offer: bool = False

@app.post("/items/")
async def create_item(item: Item):
    return {"item_name": item.name, "item_price": item.price}

This simple code:

• Validates that "name" is a string
• Validates that "price" is a float
• Sets default for "is_offer"
• Returns appropriate errors for invalid data
• Documents everything automatically

4. Async Support

FastAPI is built for async from the ground up:

@app.get("/async-data")
async def get_async_data():
    data = await fetch_from_database()
    external = await call_external_api()
    return {"data": data, "external": external}

This allows handling thousands of concurrent requests efficiently—essential for modern web applications.

5. Dependency Injection

FastAPI's dependency injection system is powerful yet simple:

from fastapi import Depends

async def get_current_user(token: str = Depends(oauth2_scheme)):
    user = await verify_token(token)
    return user

@app.get("/users/me")
async def read_users_me(current_user: User = Depends(get_current_user)):
    return current_user

Benefits:

• Clean, reusable code
• Easy testing (just override dependencies)
• Automatic handling of nested dependencies

Real-World Use Cases

API Development

FastAPI excels at building:

• RESTful APIs
• GraphQL endpoints (with Strawberry)
• WebSocket applications
• Microservices

Machine Learning APIs

Many ML teams choose FastAPI because:

• Easy integration with NumPy, Pandas, TensorFlow
• Async handling for long-running predictions
• Automatic data validation
• Clear documentation for model endpoints

Microservices

FastAPI's lightweight nature makes it perfect for:

• Docker containers
• Kubernetes deployments
• Serverless functions
• Event-driven architectures

FastAPI vs Other Frameworks

FastAPI vs Flask

Choose FastAPI when: You need performance, modern features, and automatic documentation.

Choose Flask when: You prefer maximum flexibility or have existing Flask expertise.

FastAPI vs Django REST Framework

Choose FastAPI when: Building APIs/microservices and need performance.

Choose Django REST when: You need admin panels, ORM, and full-stack features.

Getting Started with FastAPI

Installation

pip install fastapi uvicorn[standard]

Your First 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 It

uvicorn main:app --reload

Visit:

• API: http://localhost:8000
• Docs: http://localhost:8000/docs

Best Practices

Project Structure

app/
├── __init__.py
├── main.py           # FastAPI app instance
├── config.py         # Settings and configuration
├── routers/          # API route modules
│   ├── __init__.py
│   ├── users.py
│   └── items.py
├── models/           # Database models
├── schemas/          # Pydantic schemas
├── services/         # Business logic
└── utils/            # Utility functions

Use Routers for Organisation

# routers/users.py
from fastapi import APIRouter

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

@router.get("/")
async def get_users():
    return []

# main.py
from fastapi import FastAPI
from routers import users

app = FastAPI()
app.include_router(users.router)

Environment Configuration

from pydantic_settings import BaseSettings

class Settings(BaseSettings):
    app_name: str = "My API"
    debug: bool = False
    database_url: str

    class Config:
        env_file = ".env"

settings = Settings()

Conclusion

FastAPI represents the best of modern Python web development: high performance, developer productivity, and clean, maintainable code. Whether you're building a simple API or a complex microservices architecture, FastAPI provides the tools you need to succeed.

At Codevex, we've used FastAPI to build everything from simple contact form backends to complex AI-powered APIs. Its combination of speed, ease of use, and modern features makes it our framework of choice.

Ready to build your next API with FastAPI? Contact us to discuss your project.