Have you used shared global memory when organizing multi-process applications?

Yes, when organizing multiprocess applications in Python, I used shared memory segments with the multiprocessing module. Specifically, for data exchange between processes, I used the multiprocessing.Value or multiprocessing.Array classes, which allow creating objects in shared memory.

This is especially useful when you need to avoid redundant data copying between processes and ensure synchronized access through locks (Lock).

An example of using a shared integer value:

from multiprocessing import Process, Value, Lock

def worker(shared_num, lock):
    with lock:
        shared_num.value += 1

if __name__ == '__main__':
    lock = Lock()
    shared_num = Value('i', 0)  # 'i' - integer type
    processes = [Process(target=worker, args=(shared_num, lock)) for _ in range(5)]

    for p in processes:
        p.start()
    for p in processes:
        p.join()

    print(f'Final value: {shared_num.value}')

Thus, shared memory segments allow efficient coordination of state between processes without the need for external message exchange systems.