Narcissistic number with multi-processing and memoization

# Video Channel: youtube.com/beapythondev
# My Blog : https://beapython.dev

import time
from multiprocessing import Pool, cpu_count

def is_narc(s,e, memo_table):
    to_return = []
    for i in range(s,e):
        # Mike also pointed we save cycles by storing the length as a variable
        str_i = str(i)
        len_i = len(str_i)
        if (i == sum(memo_table[len_i-1][int(d)] for d in str_i)):
            to_return.append(i)
    return to_return

if __name__ == '__main__':
    t_start = time.time()

    # Credit to Mike Kerry for idea to memoize the calculation of the powers before hand
    #
    # @Stefan for modifying code to pass this to the processes so it only needs to calculate
    # once
    memo_table = [[i ** j for i in range(10)] for j in range(1,10)]

    l = 10 # Left start index
    ws = 25000 # Window size
    results = []

    # Initialize p_size equal to max threads on your hardware
    p_size = cpu_count()

    with Pool(p_size) as p:
        while len(results) < 15:
            # launching multiple evaluations asynchronously *may* use more processes
            multiple_results = [p.apply_async(is_narc, (l + (ws * i), l+(ws*(i+1)), memo_table)) for i in range(p_size)]
            [results.extend(r) for r in [res.get(timeout=1) for res in multiple_results]]
            l += (ws * p_size)

    print(results)
    print(f"Processing time = {time.time() - t_start}")