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Re:Making 1M requests with Python-aiohttp by tooker on Saturday April 23, 2016 @01:13PM (#11556383)
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
Re:Making 1M requests with Python-aiohttp by simonw on Saturday April 23, 2016 @02:46PM (#11556821)
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).
Re:Making 1M requests with Python-aiohttp by tooker on Saturday April 23, 2016 @03:13PM (#11556985)
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).
Re:Making 1M requests with Python-aiohttp by ulyssesv on Saturday April 23, 2016 @10:49PM (#11558351)
Could you please elaborate on why async would be preferred than a task queue solution (would it)?