使用多线程的方式
1、 函数式：使用threading模块threading.Thread(e.g target name parameters)
import time,threading
def loop():
print("thread %s is running..." % threading.current_thread().name)
n = 0
while n < 5:
n += 1
print("thread %s is running... n = %s" % (threading.current_thread().name,str(n)))
time.sleep(1)
print("thread %s is over..." % threading.current_thread().name) print("thread %s is running..." % threading.current_thread().name) ts = []
for i in range(5):
t = threading.Thread(target = loop, name = 'loopThread '+ str(i))
t.start()
ts.append(t)
for t in ts:
t.join()
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 = 1
thread loopThread 1 is running...
thread loopThread 1 is running... n = 1
thread loopThread 2 is running...
thread loopThread 2 is running... n = 1
thread loopThread 0 is running... n = 2
thread loopThread 1 is running... n = 2
thread loopThread 2 is running... n = 2
thread loopThread 0 is running... n = 3
thread loopThread 1 is running... n = 3
thread loopThread 2 is running... n = 3
thread loopThread 0 is running... n = 4
thread loopThread 1 is running... n = 4
thread loopThread 2 is running... n = 4
thread loopThread 0 is running... n = 5
thread loopThread 1 is running... n = 5
thread loopThread 2 is running... n = 5
thread 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
import time,threading
class threadTest(threading.Thread):
def __init__(self,tname):
threading.Thread.__init__(self)
self.name = tname
def run(self):
print("thread %s is running..." % threading.current_thread().name)
n = 0
while n < 5:
n += 1
print("thread %s is running... n = %s" % (threading.current_thread().name,str(n)))
time.sleep(1)
print("thread %s is over..." % threading.current_thread().name)
print("thread %s is running..." % threading.current_thread().name) for i in range(3):
t = threadTest('t' + str(i))
t.start()
t.join()
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 = 1
thread t0 is running... n = 2
thread t0 is running... n = 3
thread t0 is running... n = 4
thread t0 is running... n = 5
thread t0 is over...
thread t1 is running...
thread t1 is running... n = 1
thread t1 is running... n = 2
thread t1 is running... n = 3
thread t1 is running... n = 4
thread t1 is running... n = 5
thread t1 is over...
thread t2 is running...
thread t2 is running... n = 1
thread t2 is running... n = 2
thread t2 is running... n = 3
thread t2 is running... n = 4
thread t2 is running... n = 5
thread 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”
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 threading total = 0
lock = threading.Lock()
def change(n):
global total
total += n
total -= n def 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