使用多处理从队列中读取

Posted 2023-02-16

【中文标题】使用多处理从队列中读取

【英文标题】：Using multiprocessing to read from a queue

【发布时间】：2020-12-03 00:48:59

【问题描述】：

这是我使用 Python 多处理填充队列并从队列中读取的代码：

from multiprocessing import Lock, Process, Queue, Pool

import time
from random import randint

def add_to_queue(tasks_to_accomplish, name):
    while True:
        random_int = randint(0, 22)
        print('name', name , "adding" , random_int)
        tasks_to_accomplish.put(random_int)
        time.sleep(2)

def read_from_queue(tasks_to_accomplish, name):
    while True:
        item = tasks_to_accomplish.get()
        print('name' , name , item)

        time.sleep(.01)


if __name__ == '__main__':
    tasks_to_accomplish = Queue()

    p = Process(target=add_to_queue, args=(tasks_to_accomplish, "p"))
    p.start()

    p2 = Process(target=read_from_queue, args=(tasks_to_accomplish, "p2"))
    p2.start()
    p3 = Process(target=read_from_queue, args=(tasks_to_accomplish, "p3"))
    p3.start()

    p.join()
    p2.join()
    p3.join()

代码会无限执行，这里是部分输出：

name p adding 3
name p2 3
name p adding 4
name p3 4
name p adding 0
name p2 0
name p adding 22
name p3 22
name p adding 2
name p2 2
name p adding 13
name p3 13
name p adding 0
name p2 0
name p adding 14
name p3 14
name p adding 20
name p2 20
name p adding 4
name p3 4

从队列中读取所用时间为 0.01 秒：time.sleep(.01)。但是 p2 和 p3 进程似乎没有在 0.01 秒内读取线程，因为很明显它们阻塞了超过 0.01 秒。我是否正确实现了从队列中读取的进程线程？

【问题讨论】：

您每 2 秒才将一个项目添加到队列中。由于读取队列阻塞直到数据可用，读取线程将阻塞直到新数据到达。这需要 2 秒。阅读器中的sleep 可能毫无意义，因为阅读器总是阻塞get() 方法，直到有新项目可用。

【参考方案1】：

正如 Daniel 指出的那样，Queue.get() 将在默认情况下阻塞直到数据可用。

您可以使用q.get(block=True) 来更改它，尽管这会raise an exception：

name p adding 12
name p2 12
Process Process-6:
Traceback (most recent call last):
  File "/home/user/.pyenv/versions/3.8.0/lib/python3.8/multiprocessing/process.py", line 313, in _bootstrap
    self.run()
  File "/home/user/.pyenv/versions/3.8.0/lib/python3.8/multiprocessing/process.py", line 108, in run
    self._target(*self._args, **self._kwargs)
  File "<ipython-input-2-4e6d57c64980>", line 15, in read_from_queue
    item = tasks_to_accomplish.get(block=False)
  File "/home/user/.pyenv/versions/3.8.0/lib/python3.8/multiprocessing/queues.py", line 110, in get
    raise Empty
_queue.Empty
Process Process-5:
Traceback (most recent call last):
  File "/home/user/.pyenv/versions/3.8.0/lib/python3.8/multiprocessing/process.py", line 313, in _bootstrap
    self.run()
  File "/home/user/.pyenv/versions/3.8.0/lib/python3.8/multiprocessing/process.py", line 108, in run
    self._target(*self._args, **self._kwargs)
  File "<ipython-input-2-4e6d57c64980>", line 15, in read_from_queue
    item = tasks_to_accomplish.get(block=False)
  File "/home/user/.pyenv/versions/3.8.0/lib/python3.8/multiprocessing/queues.py", line 110, in get
    raise Empty
_queue.Empty
name p adding 2
name p adding 12
name p adding 14
name p adding 21
name p adding 9
name p adding 13

您需要：

def read_from_queue(tasks_to_accomplish, name):
    while True:
        try:
            item = tasks_to_accomplish.get(block=False)
        except:
            print('no data for', name)
        else:
            print('name' , name , item)
    
        time.sleep(.01)

得到：

name p adding 0
name p2 0
no data for p3
no data for p3
no data for p2
no data for p2
no data for p3
no data for p2
no data for p3
# about 350 more entries like this
name p adding 5
no data for p2
name p3 5
no data for p2
no data for p3
no data for p3
no data for p2
no data for p3
# ...

除非您需要在读取之间做一些工作，否则我会说是的，您已经正确实现了读取过程（并且您可以在读取时安全地删除对 sleep 的调用）。