使用多处理写入文件

Writing to a file with multiprocessing(使用多处理写入文件)

问题描述

我在 python 中遇到以下问题.

I'm having the following problem in python.

我需要并行进行一些计算，其结果需要按顺序写入文件中.所以我创建了一个接收 multiprocessing.Queue 和文件句柄的函数，进行计算并将结果打印到文件中:

I need to do some calculations in parallel whose results I need to be written sequentially in a file. So I created a function that receives a multiprocessing.Queue and a file handle, do the calculation and print the result in the file:

import multiprocessing
from multiprocessing import Process, Queue
from mySimulation import doCalculation   

# doCalculation(pars) is a function I must run for many different sets of parameters and collect the results in a file

def work(queue, fh):
while True:
    try:
        parameter = queue.get(block = False)
        result = doCalculation(parameter) 
        print >>fh, string
    except:
        break


if __name__ == "__main__":
    nthreads = multiprocessing.cpu_count()
    fh = open("foo", "w")
    workQueue = Queue()
    parList = # list of conditions for which I want to run doCalculation()
    for x in parList:
        workQueue.put(x)
    processes = [Process(target = writefh, args = (workQueue, fh)) for i in range(nthreads)]
    for p in processes:
       p.start()
    for p in processes:
       p.join()
    fh.close()

但脚本运行后文件最终为空.我试图将 worker() 函数更改为:

But the file ends up empty after the script runs. I tried to change the worker() function to:

def work(queue, filename):
while True:
    try:
        fh = open(filename, "a")
        parameter = queue.get(block = False)
        result = doCalculation(parameter) 
        print >>fh, string
        fh.close()
    except:
        break

并将文件名作为参数传递.然后它按我的意图工作.当我尝试按顺序执行相同的操作时，没有多处理，它也可以正常工作.

and pass the filename as parameter. Then it works as I intended. When I try to do the same thing sequentially, without multiprocessing, it also works normally.

为什么它在第一个版本中不起作用?我看不出问题.

Why it didn't worked in the first version? I can't see the problem.

另外:我可以保证两个进程不会同时尝试写入文件吗?

Also: can I guarantee that two processes won't try to write the file simultaneously?

谢谢.我现在明白了.这是工作版本:

Thanks. I got it now. This is the working version:

import multiprocessing
from multiprocessing import Process, Queue
from time import sleep
from random import uniform

def doCalculation(par):
    t = uniform(0,2)
    sleep(t)
    return par * par  # just to simulate some calculation

def feed(queue, parlist):
    for par in parlist:
            queue.put(par)

def calc(queueIn, queueOut):
    while True:
        try:
            par = queueIn.get(block = False)
            print "dealing with ", par, "" 
            res = doCalculation(par)
            queueOut.put((par,res))
        except:
            break

def write(queue, fname):
    fhandle = open(fname, "w")
    while True:
        try:
            par, res = queue.get(block = False)
            print >>fhandle, par, res
        except:
            break
    fhandle.close()

if __name__ == "__main__":
    nthreads = multiprocessing.cpu_count()
    fname = "foo"
    workerQueue = Queue()
    writerQueue = Queue()
    parlist = [1,2,3,4,5,6,7,8,9,10]
    feedProc = Process(target = feed , args = (workerQueue, parlist))
    calcProc = [Process(target = calc , args = (workerQueue, writerQueue)) for i in range(nthreads)]
    writProc = Process(target = write, args = (writerQueue, fname))


    feedProc.start()
    for p in calcProc:
        p.start()
    writProc.start()

    feedProc.join ()
    for p in calcProc:
        p.join()
    writProc.join ()

推荐答案

你真的应该使用两个队列和三种不同的处理方式.

You really should use two queues and three separate kinds of processing.

1. 将东西放入队列 #1.

1. Put stuff into Queue #1.

从 Queue #1 中取出东西并进行计算，然后将东西放入 Queue #2.您可以拥有其中的许多，因为它们从一个队列中取出并安全地放入另一个队列.

Get stuff out of Queue #1 and do calculations, putting stuff in Queue #2. You can have many of these, since they get from one queue and put into another queue safely.

从 Queue #2 中取出内容并将其写入文件.您必须恰好拥有其中的 1 个，仅此而已.它拥有"文件，保证原子访问，并绝对保证文件被干净和一致地写入.

Get stuff out of Queue #2 and write it to a file. You must have exactly 1 of these and no more. It "owns" the file, guarantees atomic access, and absolutely assures that the file is written cleanly and consistently.

这篇关于使用多处理写入文件的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持编程学习网！