[tooker]

I have a library for doing coordinated async IO in python that addresses some of the scheduling and resource contention issues hinted out in the later part of this post. It's called cellulario in reference to containing async IO mechanics inside a cell wall..

    https://github.com/mayfield/cellulario

And an example of using it to manage a multi-tiered scheme where a first layer of IO requests seeds another layer and then you finally reduce all the responses..

    https://github.com/mayfield/ecmcli/blob/master/ecmcli/api.py#L456

[simonw]

This looks really promising. I've often wanted to be able to do exactly this: run a bunch of async code in the middle of an otherwise synchronous block (classic example: writing a Django view which fires off a bunch of parallel HTTP API requests and continues once all of them have either returned or timed out).

[tooker]

That's almost exactly the use case I began with. It unapologetically requires python 3.5+ but if you're already there I'd be happy to see and support some of your use cases. Hit me up on github if you want to try it and need some guidance (the docs are nonexistent).

[ulyssesv]

Could you please elaborate on why async would be preferred than a task queue solution (would it)?