python_multiprocessing []

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==== using pool ====
Goal: Run two functions in parallel. The second function should start irrespective of whether the first one finished or not.

<code>
$ cat use_pool.py
from multiprocessing import Pool
from time import sleep

def square(x):
    res = x*x
    print('square(', x, ') = ', res)
    # artificially increase the runtime of the function
    sleep(10)
    return res

def cube(x):
    res = x**3
    print('cube(', x, ') = ', res)
    # artificially increase the runtime of the function
    sleep(10)
    return res

if __name__ == '__main__':
    num_workers = 2
    pool = Pool(num_workers)
    funcs = [square, cube]
    token = 2
    tasks = [pool.apply_async(func, (token,))
             for func in funcs]
    [task.get() for task in tasks]
</code>

<code>
$ python use_pool.py
square( 2 ) =  4
cube( 2 ) =  8
</code>

<code>
$ python --version
Python 3.9.4
</code>

tags | run processes in parallel

==== links I came across ====
  * https://docs.python.org/3/library/multiprocessing.html