Question

我需要通过套接字接收连接，读取输入数据，进行艰难和长时间的计算，然后发送答案。同时查询可能很多（即100）我明白了，因为GIL我不能使用普通线程，并尝试使用C ++与boost：threads和boost：python，并在每个线程中运行python的子解释器。但无论如何，它并没有同时100％利用所有核心。

所以我决定使用多处理，但创建一个静态计数池，用于通过队列为这些请求提供服务。这样，我们不会浪费时间来分叉一个过程，并且我们不会同时拥有100个或更多的进程，只有静态计数。

我是Python新手，主要是我使用C ++

所以现在我有了这段代码，但它没有用。连接打开并立即关闭，我不知道为什么：

#!/usr/bin/env python   
import os
import sys
import SocketServer
import Queue
import time
import socket
import multiprocessing
from multiprocessing.reduction import reduce_handle
from multiprocessing.reduction import rebuild_handle 

class MultiprocessWorker(multiprocessing.Process):

    def __init__(self, sq):

        self.SLEEP_INTERVAL = 1

        # base class initialization
        multiprocessing.Process.__init__(self)

        # job management stuff
        self.socket_queue = sq
        self.kill_received = False

    def run(self):
        while not self.kill_received:
            try:     
                h = self.socket_queue.get_nowait()          
                fd=rebuild_handle(h)
                client_socket=socket.fromfd(fd,socket.AF_INET,socket.SOCK_STREAM)
                #client_socket.send("hellofromtheworkerprocess\r\n")
                received = client_socket.recv(1024)
                print "Recieved on client: ",received
                client_socket.close()

            except Queue.Empty:
                pass

            #Dummy timer
            time.sleep(self.SLEEP_INTERVAL)

class MyTCPHandler(SocketServer.BaseRequestHandler):
    """
    The RequestHandler class for our server.

    It is instantiated once per connection to the server, and must
    override the handle() method to implement communication to the
    client.
    """

    def handle(self):
        # self.request is the TCP socket connected to the client
        #self.data = self.request.recv(1024).strip()
        #print "{} wrote:".format(self.client_address[0])
        #print self.data
        # just send back the same data, but upper-cased
        #self.request.sendall(self.data.upper())

        #Either pipe it to worker directly like this
        #pipe_to_worker.send(h) #instanceofmultiprocessing.Pipe
        #or use a Queue :)

        h = reduce_handle(self.request.fileno())
        socket_queue.put(h)


if __name__ == "__main__":

    #Mainprocess
    address =  ('localhost', 8082)
    server = SocketServer.TCPServer(address, MyTCPHandler)
    socket_queue = multiprocessing.Queue()

    for i in range(5):
        worker = MultiprocessWorker(socket_queue)
        worker.start()

    try:
        server.serve_forever()
    except KeyboardInterrupt:
        sys.exit(0)

Answer 1

你有没有理由不使用

def reduce_socket(s):
    ...

def rebuild_socket(ds):
    ...

好像你可以这样做：

import copyreg
copyreg.pickle(type(socket.socket), reduce_socket, rebuild_socket)

然后将套接字传递给队列。

这些是建议。他们有帮助吗？

Answer 2

试试这个：

def handle(self):
    h = reduce_handle(self.request.fileno())
    socket_queue.put(h)
    self.request.close()

请注意 self.request.close（）添加。

Python socket多工作池的工人

2 个答案: