KISS == Keep It Simple,Stupid
不论什么，坚持简单的过程/原理/结构/代码，就是自在！
现在小白想使用多线程来提高查询的速度，就用threading模块了！
# -*- coding: utf-8 -*-
import os
import time
from threading import Thread
from configparser import RawConfigParser as rcp
class grepIt(Thread):
def __init__(self, cdcfile, keyword):
Thread.__init__(self)
self.cdcf = cdcfile
self.keyw = keyword.upper()
self.report = ""
def run(self):
if self.cdcf.endswith('.ini'):
self.report = marklni(self.cdcf, self.keyw)
def marklni(cdcfile, keyword):
"""配置文件模式匹配函数
"""
report = ""
keyw = keyword.upper()
cfg = rcp()
cfg.read(cdcfile)
nodelist = cfg.sections()
nodelist.remove("Comment")
nodelist.remove("Info")
for node in nodelist:
if keyw in node.upper():
print(node)
report += "\n %s" % node
continue
else:
for item in cfg.items(node):
if keyw in item[0].upper():
report += "\n %s\%s" % (node, item)
return report
def grepSearch(cdcpath, keyword):
"""多线程群体搜索函数
"""
begin = time.time()
filelist = os.listdir(cdcpath)
# 用于记录发起的搜索线程
searchlist = []
for cdcf in filelist:
pathcdcf = "%s\%s" % (cdcpath, cdcf)
#print(pathcdcf)
# 初始化线程对象
current = grepIt(pathcdcf, keyword)
# 追加记录线程队列
searchlist.append(current)
# 发动线程处理
current.start()
for searcher in searchlist:
searcher.join()
print("Search from", searcher.cdcf, "out", searcher.report)
print("usage %s s" % (time.time() - begin))
if __name__ == "__main__":
grepSearch("F:\\back", "images")
针对执行效率的重构，就像玩头脑急转弯，只要充分直觉地分析运行时的整体软件行为，很容易确定瓶颈。
对问题有了准确的理解后，再向行者请教时便有了确切方向，进而容易获得有效的提示。
小练习：
利用Lock和RLock实现线程间的简单同步，使得10个线程对同一共享变量进行递增操作，使用加锁机制保证变量结果的正确
# -*- coding: utf-8 -*-
import threading, time
class mythread(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
def run(self):
global n
if lock.acquire():
print('Thread:',n)
n += 1
lock.release()
n = 0
t = []
lock = threading.Lock()
for i in range(10):
my = mythread()
t.append(my)
for i in range(10):
t[i].start()
for i in range(10):
t[i].join()运行结果如下：
Thread: 0 Thread: 1 Thread: 2 Thread: 3 Thread: 4 Thread: 5 Thread: 6 Thread: 7 Thread: 8 Thread: 9
原文地址：http://blog.51cto.com/9473774/2091399
