python - 将multiprocessing.Queue转储到列表中

我希望将multiprocessing.Queue转储到列表中。为此，我编写了以下函数:

import Queue

def dump_queue(queue):
    """
    Empties all pending items in a queue and returns them in a list.
    """
    result = []

    # START DEBUG CODE
    initial_size = queue.qsize()
    print("Queue has %s items initially." % initial_size)
    # END DEBUG CODE

    while True:
        try:
            thing = queue.get(block=False)
            result.append(thing)
        except Queue.Empty:

            # START DEBUG CODE
            current_size = queue.qsize()
            total_size = current_size + len(result)
            print("Dumping complete:")
            if current_size == initial_size:
                print("No items were added to the queue.")
            else:
                print("%s items were added to the queue." % \
                      (total_size - initial_size))
            print("Extracted %s items from the queue, queue has %s items \
            left" % (len(result), current_size))
            # END DEBUG CODE

            return result

但是由于某种原因，它不起作用。

观察以下shell session :

>>> import multiprocessing
>>> q = multiprocessing.Queue()
>>> for i in range(100):
...     q.put([range(200) for j in range(100)])
...
>>> q.qsize()
100
>>> l=dump_queue(q)
Queue has 100 items initially.
Dumping complete:
0 items were added to the queue.
Extracted 1 items from the queue, queue has 99 items left
>>> l=dump_queue(q)
Queue has 99 items initially.
Dumping complete:
0 items were added to the queue.
Extracted 3 items from the queue, queue has 96 items left
>>> l=dump_queue(q)
Queue has 96 items initially.
Dumping complete:
0 items were added to the queue.
Extracted 1 items from the queue, queue has 95 items left
>>>

这里发生了什么事？为什么不是所有物品都被丢弃？

最佳答案

试试这个:

import Queue
import time

def dump_queue(queue):
    """
    Empties all pending items in a queue and returns them in a list.
    """
    result = []

    for i in iter(queue.get, 'STOP'):
        result.append(i)
    time.sleep(.1)
    return result

import multiprocessing
q = multiprocessing.Queue()
for i in range(100):
    q.put([range(200) for j in range(100)])
q.put('STOP')
l=dump_queue(q)
print len(l)

多处理队列具有一个内部缓冲区，该缓冲区具有一个供稿器线程，该线程可以将工作从缓冲区中取出，并将其刷新到管道中。如果不是所有的对象都被刷新，我会看到一个情况，即过早引发了Empty。使用哨兵指示队列结束是安全的(并且是可靠的)。同样，使用iter(get，sentinel)习惯比依赖Empty更好。

我不喜欢由于刷新时间而将其清空(我添加了time.sleep(.1)来允许上下文切换到供稿器线程，您可能不需要它，没有它就可以工作-这是一种习惯释放GIL)。