Python多线程同步Lock、RLock、Semaphore、Event实例
一、多线程同步
由于CPython的python解释器在单线程模式下执行，所以导致python的多线程在很多的时候并不能很好地发挥多核cpu的资源。大部分情况都推荐使用多进程。
python的多线程的同步与其他语言基本相同，主要包含：
Lock & RLock ：用来确保多线程多共享资源的访问。
Semaphore ： 用来确保一定资源多线程访问时的上限，例如资源池。
Event : 是最简单的线程间通信的方式，一个线程可以发送信号，其他的线程接收到信号后执行操作。
二、实例
1）Lock & RLock
Lock对象的状态可以为locked和unlocked
使用acquire()设置为locked状态；
使用release()设置为unlocked状态。
如果当前的状态为unlocked，则acquire()会将状态改为locked然后立即返回。当状态为locked的时候，acquire()将被阻塞直到另一个线程中调用release()来将状态改为unlocked，然后acquire()才可以再次将状态置为locked。
Lock.acquire(blocking=True, timeout=-1),blocking参数表示是否阻塞当前线程等待，timeout表示阻塞时的等待时间 。如果成功地获得lock，则acquire()函数返回True，否则返回False，timeout超时时如果还没有获得lock仍然返回False。
实例：(确保只有一个线程可以访问共享资源)
import threading
import time
num = 0
lock = threading.Lock()
def func(st):
global num
print (threading.currentThread().getName() + ' try to acquire the lock')
if lock.acquire():
print (threading.currentThread().getName() + ' acquire the lock.' )
print (threading.currentThread().getName() +" :%s" % str(num) )
num += 1
time.sleep(st)
print (threading.currentThread().getName() + ' release the lock.' )
lock.release()
t1 = threading.Thread(target=func, args=(8,))
t2 = threading.Thread(target=func, args=(4,))
t3 = threading.Thread(target=func, args=(2,))
t1.start()
t2.start()
t3.start()
结果：
RLock与Lock的区别是：RLock中除了状态locked和unlocked外还记录了当前lock的owner和递归层数，使得RLock可以被同一个线程多次acquire()。
2）Semaphore
Semaphore管理一个内置的计数器，
每当调用acquire()时内置计数器-1；
调用release() 时内置计数器+1；
计数器不能小于0；当计数器为0时，acquire()将阻塞线程直到其他线程调用release()。
实例：(同时只有2个线程可以获得semaphore,即可以限制最大连接数为2)：
import threading
import time
semaphore = threading.Semaphore(2)
def func():
if semaphore.acquire():
for i in range(5):
print (threading.currentThread().getName() + ' get semaphore')
semaphore.release()
print (threading.currentThread().getName() + ' release semaphore')
for i in range(4):
t1 = threading.Thread(target=func)
t1.start()
结果：
3) Event
Event内部包含了一个标志位，初始的时候为false。
可以使用使用set()来将其设置为true；
或者使用clear()将其从新设置为false；
可以使用is_set()来检查标志位的状态；
另一个最重要的函数就是wait(timeout=None)，用来阻塞当前线程，直到event的内部标志位被设置为true或者timeout超时。如果内部标志位为true则wait()函数理解返回。
实例： (线程间相互通信)
import logging
import threading
import time
logging.basicConfig(level=logging.DEBUG,
format="(%(threadName)-10s : %(message)s",
)
def wait_for_event_timeout(e, t):
"""Wait t seconds and then timeout"""
while not e.isSet():
logging.debug("wait_for_event_timeout starting")
event_is_set = e.wait(t)
logging.debug("event set: %s" % event_is_set)
if event_is_set:
logging.debug("processing event")
else:
logging.debug("doing other work")
e = threading.Event()
t2 = threading.Thread(name="nonblock",
target=wait_for_event_timeout,args=(e, 2))
t2.start()
logging.debug("Waiting before calling Event.set()")
time.sleep(7)
e.set()
logging.debug("Event is set")
运行结果：
三、其他
1） 线程局部变量
线程局部变量的值是跟线程相关的，区别与全局的变量。使用非常简单如下：
mydata = threading.local()
mydata.x = 1
2）对Lock，semaphore，condition等使用with关键字代替手动调用acquire()和release()。
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