ProcessPoolExecutor 和 Lock in Python

Question

我正在尝试将 concurrent.futures.ProcessPoolExecutor 与锁一起使用，但出现运行时间错误。（如果相关的话，我正在研究 Windows）

这是我的代码：

import multiprocessing
from concurrent.futures import ProcessPoolExecutor

import time


def f(i, lock):
    with lock:
        print(i, 'hello')
        time.sleep(1)
        print(i, 'world')


def main():
    lock = multiprocessing.Lock()
    pool = ProcessPoolExecutor()
    futures = [pool.submit(f, num, lock) for num in range(3)]
    for future in futures:
        future.result()


if __name__ == '__main__':
    main()

这是我得到的错误：

    Traceback (most recent call last):
  File "F:\WinPython-64bit-3.4.3.2\python-3.4.3.amd64\Lib\multiprocessing\queues.py", line 242, in _feed
    obj = ForkingPickler.dumps(obj)
  File "F:\WinPython-64bit-3.4.3.2\python-3.4.3.amd64\Lib\multiprocessing\reduction.py", line 50, in dumps
    cls(buf, protocol).dump(obj)
  File "F:\WinPython-64bit-3.4.3.2\python-3.4.3.amd64\Lib\multiprocessing\synchronize.py", line 102, in __getstate__
    context.assert_spawning(self)
  File "F:\WinPython-64bit-3.4.3.2\python-3.4.3.amd64\Lib\multiprocessing\context.py", line 347, in assert_spawning
    ' through inheritance' % type(obj).__name__
RuntimeError: Lock objects should only be shared between processes through inheritance

奇怪的是，如果我用 multiprocessing.Process 编写相同的代码，一切正常：

import multiprocessing

import time


def f(i, lock):
    with lock:
        print(i, 'hello')
        time.sleep(1)
        print(i, 'world')


def main():
    lock = multiprocessing.Lock()
    processes = [multiprocessing.Process(target=f, args=(i, lock)) for i in range(3)]
    for process in processes:
        process.start()
    for process in processes:
        process.join()



if __name__ == '__main__':
    main()

这行得通，我得到：

1 hello
1 world
0 hello
0 world
2 hello
2 world

Answer 1

您需要使用 Manager 并使用 Manager.Lock() 代替：

import multiprocessing
from concurrent.futures import ProcessPoolExecutor

import time

def f(i, lock):
    with lock:
        print(i, 'hello')
        time.sleep(1)
        print(i, 'world')

def main():
    pool = ProcessPoolExecutor()
    m = multiprocessing.Manager()
    lock = m.Lock()
    futures = [pool.submit(f, num, lock) for num in range(3)]
    for future in futures:
        future.result()


if __name__ == '__main__':
    main()

结果：

% python locks.py
0 hello
0 world
1 hello
1 world
2 hello
2 world

Answer 2

我试验了它按预期工作的代码。我的理解是Manager.Lock() returns获取句柄（即multiprocessing.managers.AcquirerProxy）。当它与关键字 "with" 一起使用时，它实际上锁定了除当前处理器之外的所有处理器，以便 "with" 范围内的代码片段就像在单个处理中一样.

ProcessPoolExecutor 和 Lock in Python

ProcessPoolExecutor and Lock in Python

python

concurrency

locking

multiprocessing

pool