import multiprocessing
from functools import partial
data_list = [1, 2, 3, 4]
def prod_xy(x,y):
return x * y
def parallel_runs(data_list):
pool = multiprocessing.Pool(processes=4)
prod_x=partial(prod_xy, y=10) # prod_x has only one argument x (y is fixed to 10)
result_list = pool.map(prod_x, data_list)
print(result_list)
if __name__ == '__main__':
parallel_runs(data_list)