python多线程限制并发数示例

#coding: utf-8
#!/usr/bin/env python
import Queue
import threading
import time

prolock = threading.Lock()

# 定义同时队列数
queue = Queue.Queue(maxsize=10)

# 定义任务初值值及最大值
taskidx = 0
maxidx = 100

# 生成任务列表
def taskList():
    task = []
    for i in range(100):
        task.append("task" + str(i))
    return task


# 把任务放入队列中
class Producer(threading.Thread):
    def __init__(self, name, queue):
        self.__name = name
        self.__queue = queue
        super(Producer, self).__init__()

    def run(self):
        while True:
            global taskidx, prolock, maxidx
            time.sleep(4)
            prolock.acquire()
            print 'Producer name: %s' % (self.__name)
            if maxidx == taskidx:
                prolock.release()
                break
            ips = taskList()
            ip = ips[taskidx]
            self.__queue.put(ip)
            taskidx = taskidx + 1
            prolock.release()



# 线程处理任务
class Consumer(threading.Thread):
    def __init__(self, name, queue):
        self.__name = name
        self.__queue = queue
        super(Consumer, self).__init__()

    def run(self):
        while True:
            ip = self.__queue.get()
            print 'Consumer name: %s' % (self.__name)
            consumer_process(ip)
            self.__queue.task_done()

def consumer_process(ip):
    time.sleep(1)
    print ip


def startProducer(thread_num):
    t_produce = []
    for i in range(thread_num):
        p = Producer("producer"+str(i), queue)
        p.setDaemon(True)
        p.start()
        t_produce.append(p)
    return t_produce


def startConsumer(thread_num):
    t_consumer = []
    for i in range(thread_num):
        c = Consumer("Consumer"+str(i), queue)
        c.setDaemon(True)
        c.start()
        t_consumer.append(c)
    return t_consumer

def main():
    t_produce = startProducer(3)
    t_consumer = startConsumer(5)

    # 确保所有的任务都生成
    for p in t_produce:
        p.join()

    # 等待处理完所有任务
    queue.join()


if __name__ == '__main__':
    main()
    print '------end-------'

一般生成任务都会比较快，可以使用单线程来生成任务，示例如下：

#coding: utf-8
#!/usr/bin/env python
import Queue
import threading
import time

# 定义同时处理任务数
queue = Queue.Queue(maxsize=3)

# 生成任务列表
def taskList():
    task = []
    for i in range(100):
        task.append("task" + str(i))
    return task


# 把任务放入队列中
class Producer(threading.Thread):
    def __init__(self, name, queue):
        self.__name = name
        self.__queue = queue
        super(Producer, self).__init__()

    def run(self):
        for ip in taskList():
            self.__queue.put(ip)


# 线程处理任务
class Consumer(threading.Thread):
    def __init__(self, name, queue):
        self.__name = name
        self.__queue = queue
        super(Consumer, self).__init__()

    def run(self):
        while True:
            ip = self.__queue.get()
            print 'Consumer name: %s' % (self.__name)
            consumer_process(ip)
            self.__queue.task_done()

def consumer_process(ip):
    time.sleep(1)
    print ip


def startConsumer(thread_num):
    t_consumer = []
    for i in range(thread_num):
        c = Consumer(i, queue)
        c.setDaemon(True)
        c.start()
        t_consumer.append(c)
    return t_consumer

def main():
    p = Producer("Producer task0", queue)
    p.setDaemon(True)
    p.start()
    startConsumer(9)

    # 确保所有的任务都生成
    p.join()

    # 等待处理完所有任务
    queue.join()



if __name__ == '__main__':
    main()
    print '------end-------'