multiprocessing Pool example

sum_square_Pool.py

## Credit to LucidProgramming https://www.youtube.com/watch?v=u2jTn-Gj2Xw for the walkthrough.  My changes weren't terribly significant.  

import os # to get core count on machine
import time  # to time the duration

from multiprocessing import Pool  # to instantiate a Pool of workers to distribute the process across the cores in CPU


def sum_square(number):
    s=0
    for i in range(1, number + 1):
        s += i * i
    return s


def sum_square_with_mp(numbers):
    """Call sum_square using multiprocessing"""
    start_time = time.time()

    p = Pool(os.cpu_count() - 1)  # instatiate Pool object, but use n - 1 cores
    result_multi = p.map(sum_square, numbers)  # map maps the function onto the cores

    p.close()
    p.join()
    
    end_time = time.time() - start_time
    print(f"Processing {len(numbers):,} numbers took {end_time:,.4f} seconds using multiprocessing\nfinal result [-1] = {result_multi[-1]:,}\n")

    
def sum_square_no_mp(numbers):
    """Call sum_square using for loop on single core"""
    start_time = time.time()
    
    result_serial = []
    for i in numbers:
        result_serial.append(sum_square(i))

    end_time = time.time() - start_time
    print(f"Processing {len(numbers):,} numbers took {end_time:,.4f} seconds using serial processing\nfinal result [-1] = {result_serial[-1]:,}")

    
if __name__ == '__main__':    
    numbers = range(7_500)   ## range needs to be large enough to cross inflection point where Pool() results in time savings.
    sum_square_with_mp(numbers)
    sum_square_no_mp(numbers)