> Multiprocessing on Python works great and isn’t even very hard if you use say async_apply with a Pool.

Multiprocessing works great if you don't really need a shared memory space for your task. If it's very loosely coupled, that's fine.

But if you use something that can benefit from real threading, Python clamps you to about 1.5-2.5 cores worth of throughput very often.

There's a serialization overhead both on dispatch and return that makes multiprocessing in Python unsuitable for some problems that would otherwise be solved well with threads in other languages.

Unless you don't need to change your code.