python multiprocessing pool how can I know when all the workers in the pool have finished

Title: A Guide to Python Multiprocessing Pool: Monitoring Worker Completion
Introduction:
Python's multiprocessing module provides a convenient way to parallelize your code and leverage multiple CPU cores. One of the key components of this module is the multiprocessing pool, which allows you to distribute tasks across a pool of worker processes. In this tutorial, we will explore how to use a multiprocessing pool and how to determine when all the workers in the pool have completed their tasks.
Putting it all together:
This example demonstrates the basic usage of a multiprocessing pool and how to determine when all the workers in the pool have finished their tasks. Adjust the number of worker processes (num_workers) and the tasks according to your specific use case.
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