How do I merge sets in Python across multiple processes?

In Python, merging sets across multiple processes can be accomplished using the `multiprocessing` module, specifically with `Pool` or `Process`. This allows you to distribute the task of merging sets efficiently across different CPU cores.

keywords: merge sets, multiprocessing, Python, set operations, parallel processing
description: Learn how to merge sets in Python across multiple processes using the multiprocessing module for efficient parallel processing.
# This example demonstrates merging sets using multiprocessing in Python. import multiprocessing def merge_sets(sets): # Merge all sets in the list result = set() for s in sets: result.update(s) return result if __name__ == "__main__": # Sample sets to merge sets_to_merge = [set([1, 2, 3]), set([2, 3, 4]), set([5, 6])] # Create a pool of worker processes with multiprocessing.Pool(processes=3) as pool: # Map the merge_sets function to the sets merged_results = pool.map(merge_sets, [sets_to_merge[i:i + 1] for i in range(len(sets_to_merge))]) # Final merge of results from all processes final_merged_set = set() for result in merged_results: final_merged_set.update(result) print("Merged Set:", final_merged_set)

keywords: merge sets multiprocessing Python set operations parallel processing

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