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【python，threading】python多线程
使用多线程的方式
1、 函数式：使用threading模块threading.Thread(e.g target name parameters)
1 import time,threading 2 def loop(): 3 print("thread %s is running..." % threading.current_thread().name) 4 n = 0 5 while n < 5: 6 n += 1 7 print("thread %s is running... n = %s" % (threading.current_thread().name,str(n))) 8 time.sleep(1) 9 print("thread %s is over..." % threading.current_thread().name) 10 11 print("thread %s is running..." % threading.current_thread().name) 12 13 ts = []14 for i in range(5):15 t = threading.Thread(target = loop, name = ‘loopThread ‘+ str(i))16 t.start()17 ts.append(t)18 for t in ts:19 t.join()20 print("thread %s is over..." % threading.current_thread().name)
多线程的输出：
thread MainThread is running...thread loopThread 0 is running...thread loopThread 0 is running... n = 1thread loopThread 1 is running...thread loopThread 1 is running... n = 1thread loopThread 2 is running...thread loopThread 2 is running... n = 1thread loopThread 0 is running... n = 2thread loopThread 1 is running... n = 2thread loopThread 2 is running... n = 2thread loopThread 0 is running... n = 3thread loopThread 1 is running... n = 3thread loopThread 2 is running... n = 3thread loopThread 0 is running... n = 4thread loopThread 1 is running... n = 4thread loopThread 2 is running... n = 4thread loopThread 0 is running... n = 5thread loopThread 1 is running... n = 5thread loopThread 2 is running... n = 5thread loopThread 0 is over...thread loopThread 1 is over...thread loopThread 2 is over...thread MainThread is over...
python中得thread的一些机制和C/C++不同：在C/C++中，主线程结束后，其子线程会默认被主线程kill掉。而在python中，主线程结束后，会默认等待子线程结束后，主线程才退出。
python对于thread的管理中有两个函数：join和setDaemon
join：如在一个线程B中调用threada.join()，则threada结束后，线程B才会接着threada.join()往后运行。
setDaemon：主线程A启动了子线程B，调用b.setDaemaon(True)，则主线程结束时，会把子线程B也杀死。【此段内容摘录自junshao90的博客】
2. 使用面向对象方式。创建子类继承自threading.Thread，需overwrite run方法
1 import time,threading 2 class threadTest(threading.Thread): 3 def __init__(self,tname): 4 threading.Thread.__init__(self) 5 self.name = tname 6 def run(self): 7 print("thread %s is running..." % threading.current_thread().name) 8 n = 0 9 while n < 5:10 n += 111 print("thread %s is running... n = %s" % (threading.current_thread().name,str(n))) 12 time.sleep(1)13 print("thread %s is over..." % threading.current_thread().name) 14 print("thread %s is running..." % threading.current_thread().name) 15 16 for i in range(3):17 t = threadTest(‘t‘ + str(i))18 t.start()19 t.join()20 print("thread %s is over..." % threading.current_thread().name)
运行输出：
thread MainThread is running...thread t0 is running...thread t0 is running... n = 1thread t0 is running... n = 2thread t0 is running... n = 3thread t0 is running... n = 4thread t0 is running... n = 5thread t0 is over...thread t1 is running...thread t1 is running... n = 1thread t1 is running... n = 2thread t1 is running... n = 3thread t1 is running... n = 4thread t1 is running... n = 5thread t1 is over...thread t2 is running...thread t2 is running... n = 1thread t2 is running... n = 2thread t2 is running... n = 3thread t2 is running... n = 4thread t2 is running... n = 5thread t2 is over...thread MainThread is over...
3. lock
多线程和多进程最大的不同在于，多进程中，同一个变量，各自有一份拷贝存在于每个进程中，互不影响。
而多线程中，所有变量都由所有线程共享，所以，任何一个变量都可以被任何一个线程修改，因此，线程之间共享数据最大的危险在于多个线程同时改一个变量，把 内容给改乱了。
lock 对象：
acquire()：负责取得一个锁。如果没有线程正持有锁，acquire方法会立刻得到锁。否则，它闲意态等锁被释放。一旦acquire()返回，调用它的线程就持有锁。
release(): 释放锁。如果有其他线程正等待这个锁(通过acquire())，当release()被效用的时候，它们中的一个线程就会
被唤醒
以下内容摘自“廖雪峰的官方网站”
http://www.liaoxuefeng.com/wiki/001374738125095c955c1e6d8bb493182103fac9270762a000/001386832360548a6491f20c62d427287739fcfa5d5be1f000
balance为共享资源，多进程同时执行，一定概率结果为balance != 0[详细描述见原文]def change_it(n): # 先存后取，结果应该为0: global balance balance = balance + n balance = balance - n
使用threading.Lock()
import threadingtotal = 0lock = threading.Lock()def change(n): global total total += n total -= ndef run_thread(n): lock.acquire() for i in range(100000): change(n) lock.release() t1 = threading.Thread(target = run_thread, args=(5,))t2 = threading.Thread(target = run_thread, args=(8,))t1.start()t2.start()t1.join()t2.join()print(total)
4. 其他详细关于对进程的资料可参考
解决共享资源问题的：条件变量，同步队列
Vamei的博客Python标准库08 多线程与同步 (threading包)
片片灵感的博客Python多线程学习
【python，threading】python多线程