Showcase Your FastAPI Skills with a GitHub README Badge

Use this markdown in your README:

![FastAPI](https://img.shields.io/badge/FastAPI-009688?style=for-the-badge&logo=fastapi&logoColor=white)

The #009688 is FastAPI's signature teal — matching the teal color used throughout FastAPI's documentation and the auto-generated Swagger UI. The fastapi logo identifier renders FastAPI's logo from Simple Icons. This teal badge stands out clearly in a Python-heavy badge row dominated by blue and yellow badges.

FastAPI proficiency involves Python type annotations, async programming, and API design:

• Path operations: GET/POST/PUT/DELETE endpoints with request/response models using Pydantic
• Dependency injection: FastAPI's Depends() system for authentication, database sessions, rate limiting
• Authentication: JWT with python-jose, OAuth2 with password flow, API key authentication
• Database integration: SQLAlchemy ORM (sync and async), Alembic migrations, Tortoise ORM
• Background tasks: BackgroundTasks for lightweight async jobs, Celery for distributed task queues
• Testing: pytest with httpx.AsyncClient and FastAPI's TestClient
• Deployment: Uvicorn/Gunicorn, Docker, Kubernetes, cloud platforms

FastAPI's automatic OpenAPI documentation is a feature that distinguishes it from Flask — mentioning that your APIs ship with self-documenting Swagger UI signals API design professionalism.

FastAPI appears in multiple Python backend stacks:

• REST API stack: FastAPI + Python + PostgreSQL + Redis + Docker
• AI/ML API stack: FastAPI + Python + OpenAI/Hugging Face + PostgreSQL
• Microservices stack: FastAPI + Docker + Kubernetes + RabbitMQ/Kafka
• Full-stack Python: FastAPI + React/Vue + PostgreSQL + Celery

FastAPI and Django REST Framework are the two dominant Python API frameworks. If you use FastAPI primarily, mentioning when you choose it over DRF (performance requirements, async-first design, smaller APIs) shows architectural judgment. FastAPI is increasingly the default choice for AI/ML model serving due to its async performance and simple deployment model with Uvicorn.

FastAPI projects are Python — your language stats will show Python as the primary language, which is accurate. FastAPI's Pydantic models and type annotations encourage well-structured Python code that is more readable than typical Flask applications.

For pinned repositories, a FastAPI project with well-organized router structure (routers/, models/, schemas/, services/), complete API documentation, database migrations, and Docker deployment configuration is a strong Python backend showcase. Adding a link to the live auto-generated API docs (Swagger UI) from your README allows recruiters to explore the API interactively — a unique advantage that FastAPI provides over other frameworks.