How can I optimize parallel code in Python?

How can I optimize parallel code in Python?

You can optimize parallel code in Python by using libraries like multiprocessing or concurrent.futures. What specific task are you trying to parallelize?

I'm working on a data processing task that involves large datasets.

For large datasets, consider using the multiprocessing library to distribute the workload across multiple CPU cores. Have you tried using it yet?

Not yet, can you provide a simple example?

Sure! Here's a basic example using multiprocessing:

import multiprocessing

def process_data(data):
    # Your data processing logic here
    return data * 2

if __name__ == '__main__':
    data = [1, 2, 3, 4, 5]
    with multiprocessing.Pool() as pool:
        results = pool.map(process_data, data)
    print(results)