#!/bin/env python
# -*- coding: utf-8 -*-
#filename: peartest.py
import threading, signal
is_exit = False
def doStress(i, cc):
global is_exit
idx = i
while not is_exit:
if (idx print "thread[%d]: idx=%d"%(i, idx)
idx = idx + cc
else:
break
print "thread[%d] complete."%i
def handler(signum, frame):
global is_exit
is_exit = True
print "receive a signal %d, is_exit = %d"%(signum, is_exit)
if __name__ == "__main__":
signal.signal(signal.SIGINT, handler)
signal.signal(signal.SIGTERM, handler)
cc = 5
for i in range(cc):
t = threading.Thread(target=doStress, args=(i,cc))
t.start()
上面是一个模拟程序,并不真正向服务发送请求,而代之以在一千万以内,每个线程每隔并发数个(cc个)打印一个整数。很明显,当所有线程都完成自己的任务后,进程会正常退出。但如果我们中途想退出(试想一个压力测试程序,在中途已经发现了问题,需要停止测试),该肿么办?你当然可以用ps查找到进程号,然后kill -9杀掉,但这样太繁琐了,捕捉Ctrl+C是最自然的想法。上面示例程序中已经捕捉了这个信号,并修改全局变量is_exit,线程中会检测这个变量,及时退出。
但事实上这个程序并不work,当你按下Ctrl+C时,程序照常运行,并无任何响应。网上搜了一些资料,明白是python的子线程如果不是daemon的话,主线程是不能响应任何中断的。但设为daemon后主线程会随之退出,接着整个进程很快就退出了,所以还需要在主线程中检测各个子线程的状态,直到所有子线程退出后自己才退出,因此上例29行之后的代码可以修改为:
threads=[]
for i in range(cc):
t = threading.Thread(target=doStress, args=(i, cc))
t.setDaemon(True)
threads.append(t)
t.start()
for i in range(cc):
threads[i].join()
重新试一下,问题依然没有解决,进程还是没有响应Ctrl+C,这是因为join()函数同样会waiting在一个锁上,使主线程无法捕获信号。因此继续修改,调用线程的isAlive()函数判断线程是否完成:
while 1:
alive = False
for i in range(cc):
alive = alive or threads[i].isAlive()
if not alive:
break
这样修改后,程序完全按照预想运行了:可以顺利的打印每个线程应该打印的所有数字,也可以中途用Ctrl+C终结整个进程。完整的代码如下:
#!/bin/env python
# -*- coding: utf-8 -*-
#filename: peartest.py
import threading, signal
is_exit = False
def doStress(i, cc):
global is_exit
idx = i
while not is_exit:
if (idx print "thread[%d]: idx=%d"%(i, idx)
idx = idx + cc
else:
break
if is_exit:
print "receive a signal to exit, thread[%d] stop."%i
else:
print "thread[%d] complete."%i
def handler(signum, frame):
global is_exit
is_exit = True
print "receive a signal %d, is_exit = %d"%(signum, is_exit)
if __name__ == "__main__":
signal.signal(signal.SIGINT, handler)
signal.signal(signal.SIGTERM, handler)
cc = 5
threads = []
for i in range(cc):
t = threading.Thread(target=doStress, args=(i,cc))
t.setDaemon(True)
threads.append(t)
t.start()
while 1:
alive = False
for i in range(cc):
alive = alive or threads[i].isAlive()
if not alive:
break
其实,如果用python写一个服务,也需要这样,因为负责服务的那个线程是永远在那里接收请求的,不会退出,而如果你想用Ctrl+C杀死整个服务,跟上面的压力测试程序是一个道理。总结一下,python多线程中要响应Ctrl+C的信号以杀死整个进程,需要:
1.把所有子线程设为Daemon;
2.使用isAlive()函数判断所有子线程是否完成,而不是在主线程中用join()函数等待完成;
3.写一个响应Ctrl+C信号的函数,修改全局变量,使得各子线程能够检测到,并正常退出。

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