Which modules in the Python standard library are used for organizing parallel code execution?

The following modules are used in the Python standard library for organizing parallel code execution:

• threading — for creating and managing threads. Suitable for tasks with a large number of I/O operations.
• multiprocessing — for running multiple processes, which allows bypassing the GIL limitation and efficiently utilizing multiple CPU cores.
• concurrent.futures — a high-level interface for working with threads (ThreadPoolExecutor) and processes (ProcessPoolExecutor).

Example of using concurrent.futures for parallel function execution:

import concurrent.futures

def task(n):
    return n * n

with concurrent.futures.ThreadPoolExecutor() as executor:
    results = list(executor.map(task, range(5)))

print(results)  # [0, 1, 4, 9, 16]