How can I optimize performance in Python using parallel programming?

How can I optimize performance in Python using parallel programming?

You can use libraries like multiprocessing or concurrent.futures to run tasks in parallel. Would you like an example?

Yes, please provide an example using the multiprocessing library.

Sure! Here's a simple example:

import multiprocessing

def square(n):
    return n * n

if __name__ == '__main__':
    with multiprocessing.Pool() as pool:
        results = pool.map(square, range(10))
    print(results)

This will compute the square of numbers from 0 to 9 in parallel.

What are the benefits of using parallel programming in Python?

The main benefits include improved performance, especially for CPU-bound tasks, and better resource utilization. It can significantly reduce execution time for large computations.