i would like to compare to each other python's multithreading and multiprocessing, here is example of multithreading : import numpy as np import threading import time def calc_squares(numbers): for n in numbers: time.sleep(3) print(f'Square of {n} is {n**2}\n') def calc_cubes(numbers): for n in numbers: time.sleep(3) print(f'cube of {n} is {n**3}\n') arr =[2,3,4,5] start =time.time() th1 =threading.Thread(target=calc_squares,args=(arr,)) th2 =threading.Thread(target=calc_cubes,args=(arr,)) th1.start() th2.start() th1.join() th2.join() # calc_squares(arr) # calc_cubes(arr) print(f'time taken is {time.time()-start}') this algorithm takes apprximately 12 second,no let us consider multiprocessing : import numpy as np import threading import time import multiprocessing def calc_squares(numbers): for n in numbers: time.sleep(3) print(f'Square of {n} is {n**2}\n') def calc_cubes(numbers): for n in numbers: time.sleep(3) print(f'cube of {n} is {n**3}\n') if __name__=="__main__": arr =[2,3,4,5] start =time.time() th1 =multiprocessing.Process(target=calc_squares,args=(arr,)) th2 =multiprocessing.Process(target=calc_cubes,args=(arr,)) th1.start() th2.start() th1.join() th2.join() # calc_squares(arr) # calc_cubes(arr) print(f'time taken is {time.time()-start}') result is same : Square of 2 is 4 cube of 2 is 8 Square of 3 is 9 cube of 3 is 27 Square of 4 is 16 cube of 4 is 64 Square of 5 is 25 cube of 5 is 125 time taken is 12.206198692321777 so my question : for such task is there any difference multithreading is used or multiprocessing? Continue reading...
