How do I sort sets in Python across multiple processes?

Sorting sets in Python across multiple processes can be efficiently achieved using the `multiprocessing` library. This allows you to take advantage of multiple CPU cores to perform sorting operations in parallel, especially useful for large datasets.

Python, sorting sets, multiprocessing, parallel processing, multi-core, performance optimization
This document explains how to sort sets in Python using multiprocessing for improved performance, particularly when dealing with large datasets. 

import multiprocessing

def sort_set(shared_set):
    """Function to sort the set"""
    sorted_list = sorted(shared_set)
    return sorted_list

if __name__ == '__main__':
    # Create a set of numbers
    number_set = {5, 1, 3, 7, 4, 6, 2}
    
    # Wrap the set for processing
    with multiprocessing.Pool(processes=multiprocessing.cpu_count()) as pool:
        # Call the sorting function in parallel
        sorted_results = pool.map(sort_set, [number_set])
    
    # Print the sorted results
    print(sorted_results)

Python sorting sets multiprocessing parallel processing multi-core performance optimization

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