python多线程写文件问题_许多线程在Python中同时写入日志文件

I am writing a script to retrieve WMI info from many computers at the same time then write this info in a text file:

f = open("results.txt", 'w+') ## to clean the results file before the start

def filesize(asset):

f = open("results.txt", 'a+')

c = wmi.WMI(asset)

wql = 'SELECT FileSize,Name FROM CIM_DataFile where (Drive="D:" OR Drive="E:") and Caption like "%file%"'

for item in c.query(wql):

print >> f, item.Name.split("\")[2].strip().upper(), str(item.FileSize)

class myThread (threading.Thread):

def __init__(self,name):

threading.Thread.__init__(self)

self.name = name

def run(self):

pythoncom.CoInitialize ()

print "Starting " + self.name

filesize(self.name)

print "Exiting " + self.name

thread1 = myThread('10.24.2.31')

thread2 = myThread('10.24.2.32')

thread3 = myThread('10.24.2.33')

thread4 = myThread('10.24.2.34')

thread1.start()

thread2.start()

thread3.start()

thread4.start()

The problem is that all threads writing at the same time.

解决方案

You can simply create your own locking mechanism to ensure that only one thread is ever writing to a file.

import threading

lock = threading.Lock()

def write_to_file(f, text, file_size):

lock.acquire() # thread blocks at this line until it can obtain lock

# in this section, only one thread can be present at a time.

print >> f, text, file_size

lock.release()

def filesize(asset):

f = open("results.txt", 'a+')

c = wmi.WMI(asset)

wql = 'SELECT FileSize,Name FROM CIM_DataFile where (Drive="D:" OR Drive="E:") and Caption like "%file%"'

for item in c.query(wql):

write_to_file(f, item.Name.split("\")[2].strip().upper(), str(item.FileSize))

You may want to consider placing the lock around the entire for loop for item in c.query(wql): to allow each thread to do a larger chunk of work before releasing the lock.

相关文章

文章浏览阅读1.8k次,点赞63次,收藏54次。Linux下的目录权限...
文章浏览阅读1.6k次,点赞44次,收藏38次。关于Qt的安装、Wi...
本文介绍了使用shell脚本编写一个 Hello
文章浏览阅读1.5k次,点赞37次,收藏43次。【Linux】初识Lin...
文章浏览阅读3k次,点赞34次,收藏156次。Linux超详细笔记,...
文章浏览阅读6.8k次,点赞109次,收藏114次。【Linux】 Open...