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Optimize asyncio.get_running_loop #100363

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kumaraditya303 opened this issue Dec 20, 2022 · 3 comments
Closed

Optimize asyncio.get_running_loop #100363

kumaraditya303 opened this issue Dec 20, 2022 · 3 comments
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@kumaraditya303
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3.12 expert-asyncio performance Performance or resource usage

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@kumaraditya303
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kumaraditya303 commented Dec 20, 2022 •
edited

asyncio.get_running_loop is one of the most performance critical functions in asyncio. With #66285 the running loop can be reset in the fork handler thereby avoiding the need for the getpid checks. The whole running loop holder object is unnecessary now and adds up unnecessary dependent memory loads.

Benchmark:

import asyncio
from pyperf import Runner

async def main():
    for i in range(10000):
        asyncio.get_running_loop()


runner = Runner()
runner.bench_async_func("main", main)

Result:

Benchmark base patch
main 5.03 ms 328 us: 15.33x faster

The numbers speak for themselves.

Linked PRs
@kumaraditya303 kumaraditya303 added performance Performance or resource usage expert-asyncio 3.12 labels Dec 20, 2022
@kumaraditya303 kumaraditya303 self-assigned this Dec 20, 2022
@bedevere-bot bedevere-bot mentioned this issue Dec 20, 2022
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@gvanrossum
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gvanrossum commented Dec 20, 2022

asyncio.get_running_loop is one of the most performance critical functions in asyncio.

Do you have data about this? Does it show up in profiles of real functions, or do you have call counts or whatever? Usually I imagine the call is followed by a much more expensive computation.

@kumaraditya303
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kumaraditya303 commented Dec 20, 2022

This is based upon call counts and the fact that most functions now internally call this function as loop argument was removed from most asyncio APIs.

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gvanrossum commented Dec 20, 2022

Okay, makes sense.

kumaraditya303 added a commit that referenced this issue Dec 21, 2022
@kumaraditya303
GH-100363: Speed up asyncio.get_running_loop (#100364)
4994f24
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3.12 expert-asyncio performance Performance or resource usage
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