Fastapi
by fastapi
Modern Python API Framework with Auto-Generated Docs
Build production-ready REST APIs with automatic OpenAPI documentation, type validation, and async support in minimal code.
- 94,253+ GitHub stars
- Built with Python
- Automatic OpenAPI and JSON Schema generation with interactive documentation
- MIT License license
About This Project
FastAPI revolutionizes Python web development by combining modern Python type hints with automatic API documentation generation. Built on top of Starlette and Pydantic, it delivers exceptional performance comparable to Node.js and Go while maintaining Python's simplicity and readability.
The framework automatically generates interactive API documentation (Swagger UI and ReDoc) directly from your code annotations, eliminating the tedious manual documentation process. Every endpoint is validated at runtime using Pydantic models, catching errors early and providing clear error messages to API consumers.
Performance meets developer experience: FastAPI leverages Python's async/await syntax for handling concurrent requests efficiently, making it ideal for I/O-bound applications. The framework's intelligent editor support provides autocomplete and inline error detection, dramatically reducing development time and bugs.
With built-in dependency injection, OAuth2 authentication, CORS middleware, and WebSocket support, FastAPI provides everything needed to build enterprise-grade APIs without wrestling with boilerplate code or configuration files.
Key Features
- Automatic OpenAPI and JSON Schema generation with interactive documentation
- Built-in data validation using Python type hints and Pydantic models
- High-performance async request handling with Starlette foundation
- Editor support with autocomplete and type checking in IDEs
- Dependency injection system for clean, testable code architecture
How You Can Use It
Building microservices architectures with automatic service documentation
Creating data-driven REST APIs with real-time validation and serialization
Developing machine learning model serving endpoints with async request handling
Prototyping and deploying production APIs with minimal boilerplate code
Who Is This For?
Python developers building REST APIs, backend engineers transitioning to async frameworks, data scientists deploying ML models, and teams requiring auto-generated API documentation