Python 多线程4-死锁
死锁
在线程间共享多个资源的时候,如果两个线程分别占有一部分资源并且同时等待对方的资源,就会造成死锁。尽管死锁很少发生,但一旦发生就会造成应用的停止响应。下面看一个死锁的例子:
# encoding: UTF-8
import threading
import time
class MyThread(threading.Thread):
def do1(self):
global resA, resB
if mutexA.acquire():
msg = self.name+' got resA'
print msg
if mutexB.acquire(1):
msg = self.name+' got resB'
print msg
mutexB.release()
mutexA.release()
def do2(self):
global resA, resB
if mutexB.acquire():
msg = self.name+' got resB'
print msg
if mutexA.acquire(1):
msg = self.name+' got resA'
print msg
import threading
import time
class MyThread(threading.Thread):
def run(self):
global num
time.sleep(1)
if mutex.acquire(1):
num = num+1
msg = self.name+' set num to '+str(num)
print msg
mutex.acquire()
mutex.release()
mutex.release()
num = 0
mutex = threading.Lock()
def test():
for i in range(5):
t = MyThread()
t.start()
if __name__ == '__main__':
test()
mutexA.release() mutexB.release() def run(self): self.do1() self.do2() resA = 0 resB = 0 mutexA = threading.Lock() mutexB = threading.Lock() def test(): for i in range(5): t = MyThread() t.start() if __name__ == '__main__': test()
更简单的死锁情况是一个线程“迭代”请求同一个资源,直接就会造成死锁:
为了支持在同一线程中多次请求同一资源,python提供了“可重入锁”:threading.RLock。RLock内部维护着一个Lock和一个counter变量,counter记录了acquire的次数,从而使得资源可以被多次require。直到一个线程所有的acquire都被release,其他的线程才能获得资源。上面的例子如果使用RLock代替Lock,则不会发生死锁:
import threading
import time
class MyThread(threading.Thread):
def run(self):
global num
time.sleep(1)
if mutex.acquire(1):
num = num+1
msg = self.name+' set num to '+str(num)
print msg
mutex.acquire()
mutex.release()
mutex.release()
num = 0
mutex = threading.RLock()
def test():
for i in range(5):
t = MyThread()
t.start()
if __name__ == '__main__':
test()
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