from concurrent.futures import ProcessPoolExecutor
import random
from typing import List

def merge_sort(lst: List[int]) -> List[int]:          # no executor parameter!
    if len(lst) <= 1:
        return lst
    middle = len(lst) // 2
    # These run in separate processes → no shared thread pool problem
    left = merge_sort(lst[:middle])
    right = merge_sort(lst[middle:])
    return merge(left, right)

def merge(left: List[int], right: List[int]) -> List[int]:
    res = []
    i = j = 0
    while i < len(left) and j < len(right):
        if left[i] <= right[j]:
            res.append(left[i])
            i += 1
        else:
            res.append(right[j])
            j += 1
    res.extend(left[i:])
    res.extend(right[j:])
    return res

RANGE = 10_000
cpu_num = 10
def main():
    data = [random.randint(0, 100) for _ in range(RANGE)]
    sorted_data = []
    ranges = [i for i in range(RANGE // cpu_num, RANGE, RANGE // 100)]
    with ProcessPoolExecutor() as executor:
        for pos_range in ranges:
            sorted_data.append(executor.submit(merge_sort, data[:pos_range]).result())

    while len(sorted_data) > 1:
        new_sorted_data = []
        for i in range(0, len(sorted_data), 2):
            if 
            res = merge(sorted_data[i], sorted_data[i+1])
            new_sorted_data.append(res)

    print(len(sorted_data))

if __name__ == "__main__":      # important on Windows/macOS
        main()