This guide explains how to split tuples in Python across multiple processes, allowing for efficient parallel processing when working with large datasets.
Python, tuples, multiprocessing, parallel processing, data splitting
import multiprocessing
def process_tuple(tup):
# Add your processing logic here
return sum(tup)
if __name__ == '__main__':
tuples = [(1, 2), (3, 4), (5, 6), (7, 8)]
# Create a pool of processes
with multiprocessing.Pool(processes=4) as pool:
results = pool.map(process_tuple, tuples)
print(results) # Output: [3, 7, 11, 15]
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