python queue & multiprocessing queue: how they behave?

痞子三分冷 提交于 2019-12-17 23:29:56

问题


This sample code works (I can write something in the file):

from multiprocessing import Process, Queue

queue = Queue()
def _printer(self, queue):
    queue.put("hello world!!")

def _cmdDisp(self, queue):
    f = file("Cmd.log", "w")
    print >> f, queue.get()
    f.close()

instead this other sample not: (errormsg: 'module' object is not callable)

import Queue

queue = Queue()
def _printer(self, queue):
    queue.put("hello world!!")

def _cmdDisp(self, queue):
    f = file("Cmd.log", "w")
    print >> f, queue.get()
    f.close()

this other sample not (I cannot write something in the file):

import Queue

queue = Queue.Queue()
def _printer(self, queue):
    queue.put("hello world!!")

def _cmdDisp(self, queue):
    f = file("Cmd.log", "w")
    print >> f, queue.get()
    f.close()

Can someone explain the differences? and the right to do?


回答1:


For your second example, you already gave the explanation yourself---Queue is a module, which cannot be called.

For the third example: I assume that you use Queue.Queue together with multiprocessing. A Queue.Queue will not be shared between processes. If the Queue.Queue is declared before the processes then each process will receive a copy of it which is then independent of every other process. Items placed in the Queue.Queue by the parent before starting the children will be available to each child. Items placed in the Queue.Queue by the parent after starting the child will only be available to the parent. Queue.Queue is made for data interchange between different threads inside the same process (using the threading module). The multiprocessing queues are for data interchange between different Python processes. While the API looks similar (it's designed to be that way), the underlying mechanisms are fundamentally different.

  • multiprocessing queues exchange data by pickling (serializing) objects and sending them through pipes.
  • Queue.Queue uses a data structure that is shared between threads and locks/mutexes for correct behaviour.


来源:https://stackoverflow.com/questions/925100/python-queue-multiprocessing-queue-how-they-behave

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