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For solving a task with high performance requirements, is it preferable to use multiprocessing or multithreading?

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Answer from AI

For high-performance tasks in Python, it is often preferable to use multiprocessing. This is because the Global Interpreter Lock (GIL) restricts the concurrent execution of threads within a single process, especially for CPU-intensive tasks.

Multiprocessing allows running multiple processes, each with its own Python interpreter, effectively utilizing multiple CPU cores.

If the task involves input/output (I/O), multithreading can be more efficient, but for computationally heavy operations — multiprocessing is better.

Example of using the multiprocessing module:

from multiprocessing import Pool

def f(x):
    return x * x

with Pool(4) as p:
    print(p.map(f, [1, 2, 3, 4]))

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