[Python] Why is there not much speedup when using parallel processing during bubble sort?

I want to compare the effect of multiprocessing for bubble sort.

Let us consider first the original one without multiprocessing:

import multiprocessing
import random
import time
import numpy as np

def bubble_sort(array):
check = True
while check == True:
check = False
for i in range(len(array) - 1):
if array > array[i + 1]:
check = True
temp = array
array = array[i + 1]
array[i + 1] = temp
print("Array sorted: ", array)

if __name__ == "__main__":
array = np.random.randint(0, 1000, 10000)
start = time.time()
bubble_sort(array)
print("Time taken: ", time.time() - start)


The result is:

Array sorted: [ 0 0 0 ... 999 999 999]
Time taken: 25.157966375350952


Now with multiprocessing:

if __name__ == "__main__":
array = np.random.randint(0, 1000, 10000)
p = multiprocessing.Process(target=bubble_sort, args=(array,))
start = time.time()
p.start()
p.join()
print("Time taken: ",time.time()-start)


The result is:

Array sorted: [ 0 0 0 ... 999 999 999]
Time taken: 24.962100744247437


There is only one second difference, am I missing something?

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