How can I improve the performance of my Python application using multiprocessing?

How can I improve the performance of my Python application using multiprocessing?

You can improve performance by using the multiprocessing module to run tasks in parallel, which utilizes multiple CPU cores.

What are some common pitfalls when using multiprocessing?

Common pitfalls include issues with shared state, increased complexity in debugging, and overhead from process creation.

Can you give me an example of using multiprocessing in Python?

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, [1, 2, 3, 4, 5])
    print(results)

How does the Pool class work in the multiprocessing module?

The Pool class allows you to create a pool of worker processes. You can then use methods like map to distribute tasks across these workers.