pathos_multiprocessing_pool_parallel_map_with_lambda_support.py

1from pathos.multiprocessing import ProcessingPool as Pool
2
3# Define a simple function to parallelize
4def add(x, y):
5    return x + y
6
7# Initialize the pool with 4 workers
8pool = Pool(nodes=4)
9
10# Map the function over two lists of arguments
11# This illustrates pathos's ability to handle multiple arguments and lambdas easily
12results = pool.map(add, [1, 2, 3], [4, 5, 6])
13print(f"Standard function results: {results}")
14
15# Pathos can also serialize lambdas, which the standard multiprocessing library cannot
16squared = pool.map(lambda x: x**2, [1, 2, 3, 4])
17print(f"Lambda function results: {squared}")