Add performance benchmarks to the readme about aiofile HOT 7 OPEN

For environment specific libraries like this one, I recommend re-running tests per environment. It would likely require a fairly large text matrix though.

For example, for ReactPy we run each part of our code through IOPS tests. The concept is the same, although we focus on network IO which means we need a live web browser.

Since 99% percent of users only care about read/write performance, your test result matrix might look something like this:

Read

This test repeatedly reads 5MB of binary data from a file, and measures how many reads occurred within 60 seconds (higher is better).

Write

This test repeatedly writes 5MB of binary data to a file, and measures how many writes occurred within 60 seconds (higher is better).

Since I probably don't need to show you how to create the test cases themselves, I'll give some top-level tips.

I recommend reading/writing binary data in order to minimize variables. Also, you should use asyncio.gather to spawn workers. For example...

import asyncio

async def read_binary_test():
  ...

async def main():
  tasks = [read_test() for _ in range(500)]
  await asyncio.gather(*tasks)

if __name__ == "__main__":
  asyncio.run(main())

The write test should make sure to store BINARY_DATA_5MB as a global to avoid reconstructing it every time, which would impact test results

I arbitrarily chose 5MB as a value that gives Python enough "downtime" to actually do something else while IO is being executed.

The test cases should be written to stop recording results after 60 seconds has elapsed.

from aiofile.

The performance actually depends on what underlaying implementation of caio is currently used in the benchmark environment. The linux_aio-based implementation, of course, only for linux this have a better performance.
The thread_aio and python_aio implementations should not show much improvement over aiofiles in the general case, but should be slightly better on POSIX-compatible OSes.

I have no ideas how to make this benchmark fair enough, if you have any share it with me, preferably the code.

from aiofile.

This would be quite valuable.
When starting new project I'm not even sure if I should bother with asyncio .

According to #18 (comment) performance before new implementation was atrocious (i.e. you will be better of having blocking stdlib write/reads most of the time).

#18 (comment) looks like a huge improvement have been achieved, but does not compare against stdlib, which is quite crucial.

As for which interface need the benchmark the most - even doing it for just for linux would be good enough, since most of the applications in which performance is critical, tend to be hosted on servers, which tend to be Linux-based.

I tried rerunning test from the aforementioned comment, but the results look bad. I hope this benchmark is somewhat botched ( I did not try to debug it, just changed it a little to produce table automatically): https://gist.github.com/rooterkyberian/a2c12fc6269c86bcf4e199149eb6b9ec .

Results I got:

Python version: 3.11.6
Platform: Linux-6.5.0-25-generic-x86_64-with-glibc2.35
aiofiles version: 23.2.1
aiofile version: 3.8.8
uvloop version: 0.19.0
aiofile default context <caio.linux_aio_asyncio.AsyncioContext object at 0x7e2eb3ac0f50>

I left it running more than an hour after last result and still nothing, so it seems like either benchmarking script is broken or aiofile (caio backend) is.

from aiofile.