آموزش ماژول multiprocessing – کلاس Lock

import multiprocessing

# shared resource
shared_counter = multiprocessing.Value('i', 0)

def increment_counter(shared_counter):
    for _ in range(100000):
        shared_counter.value += 1

if __name__ == '__main__':
    processes = []
    for _ in range(5):
        p = multiprocessing.Process(target=increment_counter, args=(shared_counter,))
        p.start()
        processes.append(p)

    for p in processes:
        p.join()

    print("Final value of the counter:", shared_counter.value)

import multiprocessing

# shared resource
shared_counter = multiprocessing.Value('i', 0)

def increment_counter(shared_counter):
    for _ in range(100000):
        shared_counter.value += 1

if __name__ == '__main__':
    processes = []
    for _ in range(5):
        p = multiprocessing.Process(target=increment_counter, args=(shared_counter,))
        p.start()
        processes.append(p)

    for p in processes:
        p.join()

    print("Final value of the counter:", shared_counter.value)

import multiprocessing

lock = multiprocessing.Lock()
shared_counter = multiprocessing.Value('i', 0)

def increment_counter(shared_counter, lock):
    lock.acquire()
    for _ in range(100000):
        shared_counter.value += 1
    lock.release()

if __name__ == '__main__':
    processes = []
    for _ in range(5):
        p = multiprocessing.Process(target=increment_counter, args=(shared_counter, lock))
        p.start()
        processes.append(p)

    for p in processes:
        p.join()

    print("Final value of the counter:", shared_counter.value)   # 500000

import multiprocessing

lock = multiprocessing.Lock()
shared_counter = multiprocessing.Value('i', 0)

def increment_counter(shared_counter, lock):
    lock.acquire()
    for _ in range(100000):
        shared_counter.value += 1
    lock.release()

if __name__ == '__main__':
    processes = []
    for _ in range(5):
        p = multiprocessing.Process(target=increment_counter, args=(shared_counter, lock))
        p.start()
        processes.append(p)

    for p in processes:
        p.join()

    print("Final value of the counter:", shared_counter.value)   # 500000

import multiprocessing

lock = multiprocessing.Lock()
shared_counter = multiprocessing.Value('i', 0)

def increment_counter(shared_counter, lock):
    with lock:
        for _ in range(100000):
            shared_counter.value += 1

if __name__ == '__main__':
    processes = []
    for _ in range(5):
        p = multiprocessing.Process(target=increment_counter, args=(shared_counter, lock))
        p.start()
        processes.append(p)

    for p in processes:
        p.join()

    print("Final value of the counter:", shared_counter.value)

import multiprocessing

lock = multiprocessing.Lock()
shared_counter = multiprocessing.Value('i', 0)

def increment_counter(shared_counter, lock):
    with lock:
        for _ in range(100000):
            shared_counter.value += 1

if __name__ == '__main__':
    processes = []
    for _ in range(5):
        p = multiprocessing.Process(target=increment_counter, args=(shared_counter, lock))
        p.start()
        processes.append(p)

    for p in processes:
        p.join()

    print("Final value of the counter:", shared_counter.value)

def increment_counter(shared_counter):
    for _ in range(100000):
        with shared_counter.get_lock():   # Value has its own built-in lock
            shared_counter.value += 1

def increment_counter(shared_counter):
    for _ in range(100000):
        with shared_counter.get_lock():   # Value has its own built-in lock
            shared_counter.value += 1

import multiprocessing

def worker(chunk, success_count, lock):
    local = sum(1 for x in chunk if x % 2 == 0)   # count even numbers (the "work")
    with lock:
        success_count.value += local               # safely add to the shared total

if __name__ == '__main__':
    lock = multiprocessing.Lock()
    success_count = multiprocessing.Value('i', 0)

    data = list(range(100))
    chunks = [data[i::4] for i in range(4)]         # split data into 4 parts

    procs = [multiprocessing.Process(target=worker, args=(c, success_count, lock)) for c in chunks]
    for p in procs: p.start()
    for p in procs: p.join()

    print("total evens found:", success_count.value)   # 50

import multiprocessing

def worker(chunk, success_count, lock):
    local = sum(1 for x in chunk if x % 2 == 0)   # count even numbers (the "work")
    with lock:
        success_count.value += local               # safely add to the shared total

if __name__ == '__main__':
    lock = multiprocessing.Lock()
    success_count = multiprocessing.Value('i', 0)

    data = list(range(100))
    chunks = [data[i::4] for i in range(4)]         # split data into 4 parts

    procs = [multiprocessing.Process(target=worker, args=(c, success_count, lock)) for c in chunks]
    for p in procs: p.start()
    for p in procs: p.join()

    print("total evens found:", success_count.value)   # 50