How do I reduce dicts in Python across multiple processes?

Python, reduce dicts, multiprocessing, parallel processing, optimization

This document provides an example of how to reduce dictionaries in Python across multiple processes, improving efficiency and performance in data processing tasks.

# Example in Python
import multiprocessing

# Function to reduce dictionaries
def reduce_dicts(dicts):
    result = {}
    for d in dicts:
        for key, value in d.items():
            if key in result:
                result[key] += value
            else:
                result[key] = value
    return result

if __name__ == "__main__":
    # Sample data
    dict_list = [
        {'a': 1, 'b': 2},
        {'a': 2, 'b': 3},
        {'a': 3, 'c': 4}
    ]

    # Create a pool of processes
    with multiprocessing.Pool(processes=4) as pool:
        # Split dicts into chunks and process in parallel
        chunk_size = len(dict_list) // 4
        chunks = [dict_list[i:i + chunk_size] for i in range(0, len(dict_list), chunk_size)]
        
        # Map reduce function to the chunks
        results = pool.map(reduce_dicts, chunks)

        # Combine the results
        final_result = reduce_dicts(results)
        print(final_result)  # Output: {'a': 6, 'b': 5, 'c': 4}
        

Python reduce dicts multiprocessing parallel processing optimization