Python Multiprocessing 共享全局值 [英] Python Multiprocessing sharing of global values

问题描述

我想做的是让每个进程都使用全局变量.但我的过程并没有采取全球价值观

What i am trying to do is to make use of global variable by each process. But my process is not taking the global values

import multiprocessing

count = 0 

def smile_detection(thread_name):
    global count

    for x in range(10):
        count +=1
        print thread_name,count

    return count    

x = multiprocessing.Process(target=smile_detection, args=("Thread1",))
y = multiprocessing.Process(target=smile_detection, args=("Thread2",))
x.start()
y.start()

我得到的输出像

Thread1 1
Thread1 2
.
.
Thread1 9
Thread1 10
Thread2 1
Thread2 2
.
.
Thread2 9
Thread2 10

我想要的是

Thread1 1
Thread1 2
.
.
Thread1 9
Thread1 10
Thread2 11
Thread2 12
.
.
Thread2 19
Thread2 20

我必须做什么才能实现这一目标?

What I have to do to achieve this?

推荐答案

与线程不同，由于分叉(或产生)新进程，多处理处理共享状态有点棘手.尤其是在窗户上.要拥有共享对象，请使用 multiprocessing.Array 或 multiprocessing.Value.在数组的情况下，您可以在每个进程中取消引用另一个结构中的内存地址，例如 numpy 数组.在你的情况下，我会做这样的事情:

Unlike threading, multiprocessing is a bit trickier to handle shared state due to forking (or spawning) of a new process. Especially in windows. To have a shared object, use a multiprocessing.Array or multiprocessing.Value. In the case of the array, you can, in each process, dereference its memory address in another structure, e.g an numpy array. In your case, I would do something like this:

import multiprocessing, ctypes

count = multiprocessing.Value(ctypes.c_int, 0)  # (type, init value)

def smile_detection(thread_name, count):

    for x in range(10):
        count.value +=1
        print thread_name,count

    return count    

x = multiprocessing.Process(target=smile_detection, args=("Thread1", count))
y = multiprocessing.Process(target=smile_detection, args=("Thread2", count))
x.start()
y.start()

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