Comparing
FastAPI framework, high performance, easy to learn, fast to code, ready for production
Python HTTP for Humans
| Metric | fastapi | requests |
|---|---|---|
| Ecosystem | Python | Python |
| Difficulty | Beginner | Beginner |
| Weekly downloads | 0 | 324.9M↑ |
| Latest version | v0.135.2 | v2.33.1 |
| Recipes | 1 | 3↑ |
fastapi only
Shared
requests only
Use FastAPI when building REST or GraphQL APIs in Python, especially when you need async support, automatic OpenAPI/Swagger docs, request validation, or are building microservices. It's the best choice for new Python API projects.
Use requests for any synchronous HTTP work: calling REST APIs, scraping web pages, downloading files, or integrating with webhooks. It's the right default for scripts, CLI tools, and Django/Flask backends that don't need async.
FastAPI is API-only — it has no templating, admin interface, or ORM. For full-stack web apps with server-rendered HTML, Django is better. For tiny internal tools, Flask's smaller learning curve might be preferable.
Avoid requests when you're writing async code — it will block your event loop. Switch to httpx (drop-in async API) or aiohttp for FastAPI backends, async scrapers, or anything running inside asyncio.
fastapi
requests