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Python Code Samples

Medium snippets you can copy, study, and run in the browser editor.

3 matches
Concurrency & performance medium

How to Share Memory Between Processes in Python with multiprocessing.Value and Array

Share a numeric value and a list-like array across multiple Python processes using multiprocessing.Value and multiprocessing.Array, with each process modifying the same memory.

multiprocessing shared-memory concurrency
Python
import multiprocessing

def worker(shared_value, shared_array, index):
    shared_value.value += 10
    shared_array[index] = shared_array[index] * 2

if __name__ == "__main__":
    shared_value = multiprocessing.Value("i", 5)
    shared_array = multiprocessing.Array("i", [1, 2, 3, 4, 5])

    processes = []
    for i…
13 0 Open
Concurrency & performance medium

How to Use ProcessPoolExecutor for CPU Parallel Map in Python

Run a function over a sequence of inputs in parallel across multiple CPU cores with ProcessPoolExecutor.map.

concurrency processpoolexecutor parallelism
Python
from concurrent.futures import ProcessPoolExecutor
import math

def compute_square(num):
    return num * num

def is_prime(n):
    if n < 2:
        return False
    for i in range(2, int(math.sqrt(n)) + 1):
        if n % i == 0:
            return False
    return True

if __name__ == "__main__":
    numbers = rang…
11 0 Open
Concurrency & performance medium

How to Use multiprocessing Pool map and starmap in Python

Parallelize functions over iterables with Pool.map, and unpack multiple arguments via Pool.starmap.

multiprocessing parallelism pool
Python
from multiprocessing import Pool


def square(x):
    return x * x


def add_and_multiply(a, b, c):
    return (a + b) * c


if __name__ == "__main__":
    numbers = [1, 2, 3, 4, 5]
    with Pool(processes=2) as pool:
        squares = pool.map(square, numbers)
        print(f"squares: {squares}")

        starmap_arg…
14 0 Open

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