Python thread pool similar to the multiprocessing Pool?

Question

Is there a Pool class for worker threads, similar to the multiprocessing module's Pool class?

I like for example the easy way to parallelize a map function

def long_running_func(p):
    c_func_no_gil(p)

p = multiprocessing.Pool(4)
xs = p.map(long_running_func, range(100))

however I would like to do it without the overhead of creating new processes.

I know about the GIL. However, in my usecase, the function will be an IO-bound C function for which the python wrapper will release the GIL before the actual function call.

Do I have to write my own threading pool?

Answer 1

There is no built in thread based pool. However, it can be very quick to implement a producer/consumer queue with the Queue class.

Answer 2

The overhead of creating the new processes is minimal, especially when it's just 4 of them. I doubt this is a performance hot spot of your application. Keep it simple, optimize where you have to and where profiling results point to.

Answer 3

Here's something that looks promising over in the Python Cookbook:

Recipe 576519: Thread pool with same API as (multi)processing.Pool (Python)

Answer 4

I just found out that there actually is a thread-based Pool interface in the multiprocessing module, however it is hidden somewhat and not properly documented.

It can be imported via

from multiprocessing.pool import ThreadPool

It is implemented using a dummy Process class wrapping a python thread. This thread-based Process class can be found in multiprocessing.dummy which is mentioned briefly in the docs. This dummy module supposedly provides the whole multiprocessing interface based on threads.