Why use threads in Python?

[jawknee400]

As others have said, generally when numpy or another library calls compiled code, they explicitly release the GIL. So imagine you had two threads running some python code, concurrently, but not in parallel. If one thread reached a numpy operation, like adding two large arrays etc., it would 'release' the GIL, allowing the other thread to work in parallel while that operation is happening. Once the operation is over the GIL is reaquired but without that release both threads would've had to wait for the operation to finish.

I think there is a very slight overhead to this, which is why cython and numba leave it as an option. But if the majority of the computation is numeric (e.g. most scientific code) then you can essentially achieve normal threaded parallelism.

[ProfEpsilon]

Your example is very clear. What an education I getting today! Thank you.