How do I deduplicate sets in Python across multiple processes?

In Python, deduplicating sets across multiple processes can be accomplished using the `multiprocessing` module. This allows different processes to work independently and then combine the results at the end to form a unique set of data.

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This guide provides an example of how to deduplicate sets in Python effectively using multiprocessing to ensure that unique elements are collected from multiple processes.

import multiprocessing def deduplicate_chunks(chunk): return set(chunk) if __name__ == '__main__': data = [1, 2, 2, 3, 4, 5, 5, 6, 7] chunk_size = 3 # Splitting data into chunks for processing chunks = [data[i:i + chunk_size] for i in range(0, len(data), chunk_size)] with multiprocessing.Pool(processes=3) as pool: # Deduplicate each chunk in a separate process results = pool.map(deduplicate_chunks, chunks) # Combine the results into a single set unique_set = set().union(*results) print(unique_set) # Output: {1, 2, 3, 4, 5, 6, 7}

deduplicate sets Python multiprocessing process unique data

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