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Comment by noident | Hacker News Reader

> It got me wondering if it was actually possible to make Python’s async event loop work with multiple threads.

There is built-in support for this. Take a look at loop.run_in_executor. You can await something scheduled in a separate Thread/ProcessPoolExecutor.

Granted, this is different than making the async library end-to-end multi-threaded as you seem to be trying to do, but it does seem worth mentioning in this context. You _can_ have async and multiple threads at the same time!

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run_in_executor is pretty powerful for running sync code in async code, but my use case was more making async code utlize the cpu better. I think, just using run_in_executor would add a lot of complication and changes to how you use async await. But great point none the less!

I've had plenty of success using run_in_executor in production. You basically just use the decorator, and it mostly just works.

Which decorator?

I went back to look at some of the old code as my memory was hazy. It was tornado's implementation of the run_on_executor method that we used, which is used as a decorator.

https://www.tornadoweb.org/en/stable/concurrent.html#tornado...

> but my use case was more making async code utlize the cpu better

But run_in_executor achieves that as well! If you use no-GIL Python and a thread pool (or GIL Python with a Process pool), you will utilize more CPU cores.

run_in_executor that can be spelled as asyncio.to_thread() won't help utilizing cpu for pure Python code. It may help with blocking I/O, or cpu-heavy C extensions that release GIL. Otherwise, you have to utilize different processes to take full advantage of cpus (there are also subinterpreters (same process, separate GILs) but that exotic).

>run_in_executor that can be spelled as asyncio.to_thread() won't help utilizing cpu for pure Python code

That isn't true. If you use a ProcessPoolExecutor as the target instead of the default executor, you will use multiple processes in pure Python code.

the default executor must be ThreadPoolExecutor. But you are right you can pass ProcessPoolExecutor too.

https://docs.python.org/3/library/asyncio-eventloop.html#asy...

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