What is FastAPI?

Definition

FastAPI is an open-source Python web framework designed for building RESTful APIs quickly and efficiently. Created by Sebastián Ramírez and first released in 2018, it has rapidly become one of the most popular Python frameworks, rivaling Flask and Django for API development.

FastAPI is built on top of Starlette (for web handling) and Pydantic (for data validation). It uses Python 3.7+ type hints as its core mechanism for request validation, serialization, and automatic API documentation.

Key Features

• Automatic validation: Request parameters, bodies, and headers are validated automatically using Pydantic models and Python type hints.
• Auto-generated docs: Interactive Swagger UI and ReDoc documentation are generated automatically from your code.
• Async support: Native support for async/await syntax, making it ideal for I/O-bound operations like database queries and HTTP calls.
• Dependency injection: A powerful, declarative dependency injection system that handles authentication, database sessions, and shared logic.
• High performance: One of the fastest Python frameworks available, comparable to Node.js and Go frameworks in benchmarks.
• Standards-based: Fully compatible with OpenAPI (Swagger) and JSON Schema standards.

When to Use FastAPI

FastAPI excels in several scenarios:

• Microservices: Its lightweight nature and async support make it perfect for microservice architectures.
• Data-heavy APIs: Pydantic integration provides robust data validation with minimal boilerplate.
• Real-time applications: WebSocket support and async capabilities suit real-time features.
• ML/AI serving: Popular choice for serving machine learning models via REST APIs.
• Rapid prototyping: Type hints and auto-docs speed up development significantly.

Consider alternatives like Django if you need a full-featured web framework with admin panels, ORM, and template rendering built in.

How FastAPI Works

FastAPI operates on the ASGI (Asynchronous Server Gateway Interface) specification. When a request arrives, the framework:

1. Routes the request to the appropriate path operation function
2. Resolves all dependencies declared in the function signature
3. Validates and deserializes request data using Pydantic models
4. Executes the handler function (sync or async)
5. Serializes the response and sends it back

The framework runs on an ASGI server like Uvicorn or Hypercorn, which handles the low-level async event loop.

Code Example

from fastapi import FastAPI, Depends, HTTPException
from pydantic import BaseModel

app = FastAPI()

class UserCreate(BaseModel):
    name: str
    email: str
    age: int | None = None

@app.post("/users/", status_code=201)
async def create_user(user: UserCreate):
    # Validation happens automatically via Pydantic
    return {"message": f"User {user.name} created", "data": user}

Frequently Asked Questions

Is FastAPI better than Flask?

FastAPI and Flask serve different needs. FastAPI provides built-in validation, async support, and auto-generated documentation, making it ideal for modern API development. Flask is more flexible and has a larger ecosystem of extensions. For new API projects, FastAPI is generally the better choice due to its developer experience and performance.

Is FastAPI production-ready?

Yes. FastAPI is used in production by companies like Microsoft, Uber, Netflix, and many others. It has a mature ecosystem, extensive documentation, and a growing community. It's actively maintained and follows semantic versioning.

Does FastAPI support WebSockets?

Yes, FastAPI has native WebSocket support through Starlette. You can create WebSocket endpoints alongside regular HTTP endpoints in the same application.