I have a Python script that performs several tasks that can be executed in parallel. Currently, I’m using the multiprocessing.Pool to manage these tasks, but I was wondering if there’s a more automatic way to implement multiprocessing in Python without manually setting up and managing pools.

Here is a simplified version of my current approach:

from multiprocessing import Pool

def task(x):
    return x * x

if __name__ == "__main__":
    inputs = [1, 2, 3, 4, 5]
    with Pool(4) as p:
        results = p.map(task, inputs)
    print(results)

This works fine, but I want to know if there’s a way to automate the multiprocessing setup. Ideally, I’m looking for a solution where I don’t have to explicitly create and manage the Pool object. Is there a library or a pattern that abstracts this process?

Any advice or examples would be greatly appreciated. Thank you!