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speedups for CPU-bound tasks. Here’s an example of using multiprocessing to parallelize a function: import multiprocessing def process_data(data): # CPU-intensive data processing ... if __name__ == '__main__': pool = multiprocessing.Pool() data_chunks = [data[i:i+1000] for i in range(0, len(data),