This page gives you a quick, practical overview of FastAPI—a modern
Python API framework known for speed, type hints, and a great developer experience.
You’ll see where it fits in a production stack and how to start using it today.
In short, the framework sits on ASGI, pairs beautifully with Starlette and Pydantic, and encourages clean,
typed endpoints. Moreover, it auto-generates interactive docs from your route definitions, which helps teams
move from prototype to production with fewer surprises.

If you need to expose your AI or data services quickly, this framework keeps things simple:
define models, add routes, and deploy with an ASGI server. For an end-to-end example, see our guide on
deploying a Python API with Uvicorn and Docker.
In addition, the official documentation covers patterns, security, and performance tuning.

Scroll to the flashcards for a compact refresher. Then, use the links at the end to explore more examples and templates.
pip install fastapi
and add uvicorn[standard]
for a production-grade server.TestClient
with pytest
or unittest
to verify routes and schemas.@app.get()
, @app.post()
, etc., or use APIRouter
modules.StaticFiles
helper.To get started, create a minimal app, add Pydantic models for requests and responses, and enable async where it matters.
Next, containerise with Docker and run behind a process manager such as Gunicorn with Uvicorn workers. Finally, monitor
latency, error rates, and throughput before you scale.
Read our step-by-step guide:
Deploying a Python API with Uvicorn and Docker.
For official tutorials and references, visit the
FastAPI documentation.