#from concurrent.futures import ProcessPoolExecutor
from concurrent.futures import ThreadPoolExecutor

import time

values = range(1,9999)

def dissect1(qq):
    adding    = sum(list1[qq:qq+100000])
    averaging = adding / len(list1[qq:qq+100000]) 
    return adding,averaging

def dissect2(qq):
    adding = sum(list2[qq:qq+100000])
    averaging = adding / len(list2[qq:qq+100000])
    return adding,averaging

    list1 = range(0, 99999999) # Two copies to speed things up?
    list2 = range(0, 99999999) # Two copies to speed things up?

if __name__ == '__main__':
    result1 = []
    result2 = []
    tic = time.time()

    with ThreadPoolExecutor(max_workers=8) as exe:
        result = exe.map(dissect1,range(1,5000))

    with ThreadPoolExecutor(max_workers=8) as exe:
        result2 = exe.map(dissect2,range(5000,9999))

    toc = time.time()
    print(f'Parallel execution, completed in {toc - tic} seconds')

    for v in values:
        a,b = dissect1(v)  

    tac = time.time()
    print(f'Serial execution, completed in {tac - toc} seconds')

Both parallel and serial execution resulted in about 27 seconds of run time. Why is this so?

Parallel execution, completed in 27.91899013519287 seconds

Serial execution, completed in 27.62840223312378 seconds