anyio

100% same experience. If it were up to me, I'd started with typescript, but the client insisted on using a python stack (landed on FastMCP, FastAPI, PydanticAI). While, `PydanticAI` does the best it can with a limited type system, it just can't match the productivity of typescript. And I still can't believe what a mess async python is. The worst thing we've encountered was a bug from mixing anyio with asyncio which resulted in our ECS container getting it's CPU pinned to 100% [1]. And constantly running into issue with libraries not handling task cancellation properly. I get that python has captured the ML ecosystem, but these agent systems are just API calls and parsing json... [1](https://github.com/agronholm/anyio/issues/884)

The problem, IMO, with asyncio is that its way, way too complicated. In my experience, anyio (https://github.com/agronholm/anyio) provides a much better interface on top of asyncio. And since it can use asyncio as a backend, it maintains compatibility with the asyncio ecosystem. FastAPI, for example, uses anyio. One thing that I don't see being mentioned in any of the threads here talking about green threads is cancellation. A huge benefit, IMO, of anyio is that it makes cancellation really easy to handle. With asyncio, cancellation is pretty hard. And with green threads, cancellation is often impossible.

> it's is quite nice to use, at least compared to what I remember asyncio being like. Yes, I agree. Fairly recently there's been anyio [0], which brings ideas from trio to other async libraries, in particular asyncio. E.g. it has equivalent of trio nurseries (what anyio calls "task groups") for implementing structured concurrency ideas in asyncio environments (saving you from headaches due to having to deal with tasks manually). Very neat way to use trio ideas when stuck on asyncio (e.g. for web apps). :) anyio was also discussed in the latest Python Bytes episode [1]. [0]: https://github.com/agronholm/anyio [1]: https://pythonbytes.fm/episodes/show/197/structured-concurre...