python 多线程编程

[TheBigFish]

python 多线程编程

使用回调方式

import time
def countdown(n):
    while n > 0:
        print('T-minus', n)
        n -= 1
        time.sleep(5)

# Create and launch a thread
from threading import Thread
t = Thread(target=countdown, args=(10,))
t.start()

使用继承方式

from threading import Thread

class CountdownTask:
    def __init__(self):
        self._running = True

    def terminate(self):
        self._running = False

    def run(self, n):
        while self._running and n > 0:
            print('T-minus', n)
            n -= 1
            time.sleep(5)

c = CountdownTask()
t = Thread(target=c.run, args=(10,))
t.start()
c.terminate() # Signal termination
t.join()      # Wait for actual termination (if needed)

注意使用变量 self._running 退出线程的方式

使用 Queue 进行线程间通信

import Queue
import threading
import time

task_queue = Queue.Queue()


class ThreadTest(threading.Thread):
    def __init__(self, queue):
        threading.Thread.__init__(self)
        self.queue = queue

    def run(self):
        while True:
            msg = self.queue.get()
            print(msg)
            time.sleep(0.1)
            self.queue.task_done()


def main():
    start = time.time()
    # populate queue with data
    for i in range(100):
        task_queue.put("message")

    # spawn a pool of threads, and pass them queue instance
    for i in range(5):
        t = ThreadTest(task_queue)
        t.setDaemon(True)
        t.start()

    # wait on the queue until everything has been processed
    task_queue.join()
    print "Elapsed Time: {}".format(time.time() - start)


if __name__ == "__main__":
    main()

setDaemon 设置为 True, run 函数中不需要退出，主线程结束后所有子线程退出
如果 setDaemon 设置为 False,则改为

def run(self):
    while not self.queue.empty():
        msg = self.queue.get()
        print(msg)
        time.sleep(0.1)
        self.queue.task_done()

并且在主函数结束前 join 所有线程

注意

• 向队列中添加数据项时并不会复制此数据项，线程间通信实际上是在线程间传递对象引用。如果你担心对象的共享状态，那你最好只传递不可修改的数据结构（如：整型、字符串或者元组）或者一个对象的深拷贝。

    from queue import Queue
    from threading import Thread
    import copy
  
    # A thread that produces data
    def producer(out_q):
        while True:
            # Produce some data
            ...
            out_q.put(copy.deepcopy(data))
  
    # A thread that consumes data
    def consumer(in_q):
        while True:
            # Get some data
            data = in_q.get()
            # Process the data
            ...

• q.qsize() ， q.full() ， q.empty() 等实用方法可以获取一个队列的当前大小和状态。但要注意，这些方法都不是线程安全的。可能你对一个队列使用 empty() 判断出这个队列为空，但同时另外一个线程可能已经向这个队列中插入一个数据项。

参考

• python3-cookbook Chapter 12 'Concurrency-Starting and Stopping Threads'

• Practical threaded programming with Python