python多线程编程-白红宇

Python多线程编程中常用方法：

1、join()方法：如果一个线程或者在函数执行的过程中调用另一个线程，并且希望待其完成操作后才能执行，那么在调用线程的时就可以使用被调线程的join方法join([timeout]) timeout：可选参数，线程运行的最长时间

2、isAlive()方法：查看线程是否还在运行

3、getName()方法：获得线程名

4、setDaemon()方法：主线程退出时，需要子线程随主线程退出，则设置子线程的setDaemon()

Python线程同步：

（1）Thread的Lock和RLock实现简单的线程同步：

import threadingimport timeclass mythread(threading.Thread):    def __init__(self,threadname):        threading.Thread.__init__(self,name=threadname)    def run(self):        global x        lock.acquire()        for i in range(3):            x = x+1        time.sleep(1)        print x        lock.release()if __name__ == '__main__':    lock = threading.RLock()    t1 = []    for i in range(10):        t = mythread(str(i))        t1.append(t)    x = 0    for i in t1:        i.start()

（2）使用条件变量保持线程同步：

# coding=utf-8import threadingclass Producer(threading.Thread):    def __init__(self,threadname):        threading.Thread.__init__(self,name=threadname)    def run(self):        global x        con.acquire()        if x == 10000:            con.wait()             pass        else:            for i in range(10000):                x = x+1                con.notify()        print x        con.release()class Consumer(threading.Thread):    def __init__(self,threadname):        threading.Thread.__init__(self,name=threadname)    def run(self):        global x        con.acquire()        if x == 0:            con.wait()            pass        else:            for i in range(10000):                x = x-1            con.notify()        print x        con.release()if __name__ == '__main__':    con = threading.Condition()    x = 0    p = Producer('Producer')    c = Consumer('Consumer')    p.start()    c.start()    p.join()    c.join()    print x

（3）使用队列保持线程同步：

# coding=utf-8import threadingimport Queueimport timeimport randomclass Producer(threading.Thread):    def __init__(self,threadname):        threading.Thread.__init__(self,name=threadname)    def run(self):        global     queue        i = random.randint(1,5)        queue.put(i)        print self.getName(),' put %d to queue' %(i)        time.sleep(1)class Consumer(threading.Thread):    def __init__(self,threadname):        threading.Thread.__init__(self,name=threadname)    def run(self):        global     queue        item = queue.get()        print self.getName(),' get %d from queue' %(item)        time.sleep(1)if __name__ == '__main__':    queue = Queue.Queue()    plist = []    clist = []    for i in range(3):        p = Producer('Producer'+str(i))        plist.append(p)    for j in range(3):        c = Consumer('Consumer'+str(j))        clist.append(c)    for pt in plist:        pt.start()        pt.join()    for ct in clist:        ct.start()        ct.join()

生产者消费者模式的另一种实现：

# coding=utf-8import timeimport threadingimport Queueclass Consumer(threading.Thread):    def __init__(self, queue):        threading.Thread.__init__(self)        self._queue = queue    def run(self):        while True:            # queue.get() blocks the current thread until an item is retrieved.            msg = self._queue.get()            # Checks if the current message is the "quit"            if isinstance(msg, str) and msg == 'quit':                # if so, exists the loop                break            # "Processes" (or in our case, prints) the queue item            print "I'm a thread, and I received %s!!" % msg        # Always be friendly!        print 'Bye byes!'class Producer(threading.Thread):    def __init__(self, queue):        threading.Thread.__init__(self)        self._queue = queue    def run(self):        # variable to keep track of when we started        start_time = time.time()        # While under 5 seconds..        while time.time() - start_time < 5:            # "Produce" a piece of work and stick it in the queue for the Consumer to process            self._queue.put('something at %s' % time.time())            # Sleep a bit just to avoid an absurd number of messages            time.sleep(1)        # This the "quit" message of killing a thread.        self._queue.put('quit')if __name__ == '__main__':    queue = Queue.Queue()    consumer = Consumer(queue)    consumer.start()    producer1 = Producer(queue)    producer1.start()

使用线程池（Thread pool）+同步队列（Queue）的实现方式：

# A more realistic thread pool example# coding=utf-8import time import threading import Queue import urllib2 class Consumer(threading.Thread):     def __init__(self, queue):        threading.Thread.__init__(self)        self._queue = queue      def run(self):        while True:             content = self._queue.get()             if isinstance(content, str) and content == 'quit':                break            response = urllib2.urlopen(content)        print 'Bye byes!' def Producer():    urls = [        'http://www.python.org', 'http://www.yahoo.com'        'http://www.scala.org', 'http://cn.bing.com'        # etc..     ]    queue = Queue.Queue()    worker_threads = build_worker_pool(queue, 4)    start_time = time.time()    # Add the urls to process    for url in urls:         queue.put(url)      # Add the 'quit' message    for worker in worker_threads:        queue.put('quit')    for worker in worker_threads:        worker.join()     print 'Done! Time taken: {}'.format(time.time() - start_time) def build_worker_pool(queue, size):    workers = []    for _ in range(size):        worker = Consumer(queue)        worker.start()         workers.append(worker)    return workers if __name__ == '__main__':    Producer()

另一个使用线程池+Map的实现：

import urllib2 from multiprocessing.dummy import Pool as ThreadPool  urls = [    'http://www.python.org',     'http://www.python.org/about/',    'http://www.python.org/doc/',    'http://www.python.org/download/',    'http://www.python.org/community/'    ] # Make the Pool of workerspool = ThreadPool(4) # Open the urls in their own threads# and return the resultsresults = pool.map(urllib2.urlopen, urls)#close the pool and wait for the work to finish pool.close() pool.join()

参考：

http://blog.jobbole.com/58700/

本文转自阿凡卢博客园博客，原文链接：http://www.cnblogs.com/luxiaoxun/p/3827022.html，如需转载请自行联系原作者