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Re:Async Python is not faster by throwaway894345 on Friday June 12, 2020 @12:54PM (#23501148)
Double-digit interpreters per host? Where is the expense? Interpreters have a relatively small memory overhead (<10mb). If you're running 100 interpreters per host (you shouldn't be), that's an extra $50/host/year. But you should be running <10/host, so an extra $5/host/year. Not ideal, but not "expensive", and if you care about costs your biggest mistake was using Python in the first place.
Re:Async Python is not faster by Grimm1 on Friday June 12, 2020 @01:00PM (#23501226)
I don't know where you're seeing the < 10mb from the situation I saw they were easily consuming 30mb per interpreter. Even my cursory search around now shows them at roughly 15-20mb so assuming the 30mb Gunicorn was just misconfigured that's still an extra $100 per host using your estimate and what I'm looking at Googling around and across a situation where there are multiple public apis that's adding up pretty quickly.

Another google search shows me Gunicorn, for instance, using high memory on fork isn't exactly uncommon either.

Edit: I reworded some stuff up there and tried to make my point more clear.

Re:Async Python is not faster by throwaway894345 on Friday June 12, 2020 @01:35PM (#23501640)
The interpreter overhead on macos is 7.7mb. I can't speak to gunicorn configuration but it's far from the only game in town.
Re:Async Python is not faster by Grimm1 on Friday June 12, 2020 @01:43PM (#23501692)
Totally fair point, my experience with fork type deploys has only been Gunicorn so I'll take this as a challenge to try some others out.