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)