問題描述

我在 python 中遇到以下問題.

I'm having the following problem in python.

我需要并行進行一些計算，其結果需要按順序寫入文件中.所以我創建了一個接收 multiprocessing.Queue 和文件句柄的函數，進行計算并將結果打印到文件中:

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()

但腳本運行后文件最終為空.我試圖將 worker() 函數更改為:

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

并將文件名作為參數傳遞.然后它按我的意圖工作.當我嘗試按順序執行相同的操作時，沒有多處理，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.

為什么它在第一個版本中不起作用?我看不出問題.

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

另外:我可以保證兩個進程不會同時嘗試寫入文件嗎?

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

謝謝.我現在明白了.這是工作版本:

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 ()

推薦答案

你真的應該使用兩個隊列和三種不同的處理方式.

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

1. 將東西放入隊列 #1.

1. Put stuff into Queue #1.

從 Queue #1 中取出東西并進行計算，然后將東西放入 Queue #2.您可以擁有其中的許多，因為它們從一個隊列中取出并安全地放入另一個隊列.

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.

從 Queue #2 中取出內容并將其寫入文件.您必須恰好擁有其中的 1 個，僅此而已.它擁有"文件，保證原子訪問，并絕對保證文件被干凈和一致地寫入.

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.

這篇關于使用多處理寫入文件的文章就介紹到這了，希望我們推薦的答案對大家有所幫助，也希望大家多多支持html5模板網！