Comparing
High-level concurrency and networking framework on top of asyncio or Trio
FastAPI framework, high performance, easy to learn, fast to code, ready for production
| Metric | anyio | fastapi |
|---|---|---|
| Ecosystem | Python | Python |
| Difficulty | Beginner | Beginner |
| Weekly downloads | 0 | 0↑ |
| Latest version | v4.13.0 | v0.135.2 |
| Recipes | 1 | 1 |
anyio only
Shared
fastapi only
Use anyio when writing an async library or framework that you want to be runtime-agnostic. It's also useful in applications that want trio's structured concurrency model but need to interop with asyncio-based libraries like FastAPI or aiohttp.
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.
For application code that commits to asyncio (e.g. a FastAPI app), using asyncio directly is simpler — there's no need for the compatibility layer. anyio shines at the library level, not the application level.
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.
anyio
fastapi