How do I chunk lists in Python across multiple processes?

In Python, you can efficiently chunk lists and process them across multiple processes using the `multiprocessing` library. This can enhance performance when dealing with large datasets by distributing the workload across multiple CPU cores.

Keywords: Python, chunking lists, multiprocessing, parallel processing, performance optimization
Description: This guide demonstrates how to split a list into smaller chunks and process those chunks in parallel using Python’s multiprocessing capabilities, making it ideal for handling large lists or datasets.

Below is an example of how you can implement list chunking across multiple processes:

<?php import multiprocessing # Function to process a chunk of data def process_chunk(chunk): # Replace with your processing logic return sum(chunk) # Function to create chunks def chunk_list(data, chunk_size): for i in range(0, len(data), chunk_size): yield data[i:i + chunk_size] if __name__ == "__main__": data = [i for i in range(100000)] # Example dataset chunk_size = 1000 # Example chunk size chunks = list(chunk_list(data, chunk_size)) with multiprocessing.Pool() as pool: results = pool.map(process_chunk, chunks) total = sum(results) print("Total:", total) ?>

Keywords: Python chunking lists multiprocessing parallel processing performance optimization

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