本文理论上对multiprocessing.dummy的Pool同样有效。
python2.x中multiprocessing提供的基于函数进程池，join后陷入内核态，按下ctrl+c不能停止所有的进程并退出。即必须ctrl+z后找到残留的子进程，把它们干掉。先看一段ctrl+c无效的代码：
#!/usr/bin/env python
import multiprocessing
import os
import time
def do_work(x):
print 'Work Started: %s' % os.getpid()
time.sleep(10)
return x * x
def main():
pool = multiprocessing.Pool(4)
try:
result = pool.map_async(do_work, range(8))
pool.close()
pool.join()
print result
except KeyboardInterrupt:
print 'parent received control-c'
pool.terminate()
pool.join()
if __name__ == "__main__":
main()这段代码运行后，按^c一个进程也杀不掉，最后会残留包括主进程在内共5个进程(1+4)，kill掉主进程能让其全部退出。很明显，使用进程池时KeyboardInterrupt不能被进程捕捉。解决方法有两种。
方案一
下面这段是python源码里multiprocessing下的pool.py中的一段，ApplyResult就是Pool用来保存函数运行结果的类
class ApplyResult(object):
def __init__(self, cache, callback):
self._cond = threading.Condition(threading.Lock())
self._job = job_counter.next()
self._cache = cache
self._ready = False
self._callback = callback
cache[self._job] = self而下面这段代码也是^c无效的代码
if __name__ == '__main__':
import threading
cond = threading.Condition(threading.Lock())
cond.acquire()
cond.wait()
print "done"很明显，threading.Condition(threading.Lock())对象无法接收KeyboardInterrupt，但稍微修改一下，给cond.wait()一个timeout参数即可，这个timeout可以在map_async后用get传递，把
result = pool.map_async(do_work, range(4))改为
result = pool.map_async(do_work, range(4)).get(1)就能成功接收^c了，get里面填1填99999还是0xffff都行
方案二
另一种方法当然就是自己写进程池了，需要使用队列，贴一段代码感受下
#!/usr/bin/env python
import multiprocessing, os, signal, time, Queue
def do_work():
print 'Work Started: %d' % os.getpid()
time.sleep(2)
return 'Success'
def manual_function(job_queue, result_queue):
signal.signal(signal.SIGINT, signal.SIG_IGN)
while not job_queue.empty():
try:
job = job_queue.get(block=False)
result_queue.put(do_work())
except Queue.Empty:
pass
#except KeyboardInterrupt: pass
def main():
job_queue = multiprocessing.Queue()
result_queue = multiprocessing.Queue()
for i in range(6):
job_queue.put(None)
workers = []
for i in range(3):
tmp = multiprocessing.Process(target=manual_function,
args=(job_queue, result_queue))
tmp.start()
workers.append(tmp)
try:
for worker in workers:
worker.join()
except KeyboardInterrupt:
print 'parent received ctrl-c'
for worker in workers:
worker.terminate()
worker.join()
while not result_queue.empty():
print result_queue.get(block=False)
if __name__ == "__main__":
main()方案三
使用一个全局变量eflag作标识，让SIG_INT信号绑定一个处理函数，在其中对eflag的值更改，线程的函数中以eflag的值判定作为while的条件，把语句写在循环里，老实说这个方案虽然可以用，但是简直太差劲。线程肯定是可行的，进程应该还需要单独共享变量，非常不推荐的方式
常见的错误方案
这个必须要提一下，我发现segmentfault上都有人被误导了
理论上，在Pool初始化时传递一个initializer函数，让子进程忽略SIGINT信号，也就是^c，然后Pool进行terminate处理。代码
#!/usr/bin/env python
import multiprocessing
import os
import signal
import time
def init_worker():
signal.signal(signal.SIGINT, signal.SIG_IGN)
def run_worker(x):
print "child: %s" % os.getpid()
time.sleep(20)
return x * x
def main():
pool = multiprocessing.Pool(4, init_worker)
try:
results = []
print "Starting jobs"
for x in range(8):
results.append(pool.apply_async(run_worker, args=(x,)))
time.sleep(5)
pool.close()
pool.join()
print [x.get() for x in results]
except KeyboardInterrupt:
print "Caught KeyboardInterrupt, terminating workers"
pool.terminate()
pool.join()
if __name__ == "__main__":
main()然而这段代码只有在运行在time.sleep(5)处的时候才能用ctrl+c中断，即前5s你按^c有效，一旦pool.join()后则完全无效！
建议
先确认是否真的需要用到多进程，如果是IO多的程序建议用多线程或协程，计算特别多则用多进程。如果非要用多进程，可以利用Python3的concurrent.futures包(python2.x也能装)，编写更加简单易用的多线程/多进程代码，其使用和Java的concurrent框架有些相似.
经过亲自验证，ProcessPoolExecutor是没有^c的问题的，要用多进程建议使用它
参考
http://bryceboe.com/2010/08/26/python-multiprocessing-and-keyboardinterrupt/#georges
http://stackoverflow.com/questions/1408356/keyboard-interrupts-with-pythons-multiprocessing-pool#comment12678760_6191991