How can I optimize performance in Python using multiprocessing?

How can I optimize performance in Python using multiprocessing?

You can optimize performance in Python by using the multiprocessing module, which allows you to run multiple processes simultaneously.

What are some common use cases for multiprocessing in Python?

Common use cases include data processing, web scraping, and any CPU-bound tasks that can benefit from parallel execution.

Can you provide a simple example of using multiprocessing?

Sure! Here's a basic example:

import multiprocessing

def square(n):
    return n * n

if __name__ == '__main__':
    with multiprocessing.Pool() as pool:
        results = pool.map(square, [1, 2, 3, 4, 5])
    print(results)

Are there any limitations or challenges with using multiprocessing?

Yes, some challenges include increased memory usage, complexity in debugging, and issues with shared state between processes.