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add python threading examples and intros for lec 18 spoc discuss

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From:
- http://www.laurentluce.com/posts/python-threads-synchronization-locks-rlocks-semaphores-conditions-events-and-queues/
- http://yoyzhou.github.io/blog/2013/02/28/python-threads-synchronization-locks/
- http://blog.chinaunix.net/uid-429659-id-3186991.html
- http://blog.csdn.net/yidangui/article/details/8707187
- http://blog.csdn.net/yidangui/article/details/8707205
- http://blog.csdn.net/yidangui/article/details/8707209
- http://blog.csdn.net/yidangui/article/details/8707197
## threads: Python threads synchronization: Locks, RLocks, Semaphores, Conditions, Events and Queues.
### threading简介
python是支持多线程的，并且是native的线程。主要是通过thread和threading这两个模块来实现的。
#### 实现模块
- thread：多线程的底层支持模块，一般不建议使用；
- threading：对thread进行了封装，将一些线程的操作对象化。
#### threading模块
- Timer与Thread类似，但要等待一段时间后才开始运行；
- Lock 锁原语，这个我们可以对全局变量互斥时使用；
- RLock 可重入锁，使单线程可以再次获得已经获得的锁；
- Condition 条件变量，能让一个线程停下来，等待其他线程满足某个“条件”；
- Event 通用的条件变量。多个线程可以等待某个事件发生，在事件发生后，所有的线程都被激活；
- Semaphore为等待锁的线程提供一个类似“等候室”的结构；
- BoundedSemaphore 与semaphore类似，但不允许超过初始值；
- Queue：实现了多生产者（Producer）、多消费者（Consumer）的队列，支持锁原语，能够在多个线程之间提供很好的同步支持。
thread是比较底层的模块，threading是对thread做了一些包装的，可以更加方便的被使用。创建thread的方式有：
- 第一种方式:创建一个threading.Thread()的实例对象，给它一个函数。在它的初始化函数（__init__）中将可调用对象作为参数传入
- 第二种方式:创建一个threading.Thread的实例，传给它一个可调用类对象，类中使用__call__()函数调用函数
- 第三种方式:是通过继承Thread类，重写它的run方法；
第一种和第三种常用。
第一种方式举例：
```
#coding=utf-8
import threading
def thread_fun(num):
for n in range(0, int(num)):
print " I come from %s, num: %s" %( threading.currentThread().getName(), n)
def main(thread_num):
thread_list = list();
# 先创建线程对象
for i in range(0, thread_num):
thread_name = "thread_%s" %i
thread_list.append(threading.Thread(target = thread_fun, name = thread_name, args = (20,)))
# 启动所有线程
for thread in thread_list:
thread.start()
# 主线程中等待所有子线程退出
for thread in thread_list:
thread.join()
if __name__ == "__main__":
main(3)
```
第三种方式举例1：
```
#!/usr/bin/env python
import threading
import time
count=1
class KissThread(threading.Thread):
def run(self):
global count
print "Thread # %s:Pretending to do stuff" % count
count+=1
time.sleep(2)
print "done with stuff"
for t in range(5):
KissThread().start()
```
第三种方式举例2：
```
import threading
class MyThread(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
def run(self):
print "I am %s" % (self.name)
if __name__ == "__main__":
for i in range(0, 5):
my_thread = MyThread()
my_thread.start()
```
### Thread类常用方法
#### getName(self)
返回线程的名字
#### setName方法
可以指定每一个thread的name
```
def __init__(self):
threading.Thread.__init__(self)
self.setName("new" + self.name)
```
#### isAlive(self)
布尔标志，表示这个线程是否还在运行中
#### isDaemon(self)
返回线程的daemon标志
#### run(self)
定义线程的功能函数
#### start方法
启动线程
#### join方法
join方法原型如下，这个方法是用来程序挂起，直到线程结束，如果给出timeout，则最多阻塞timeout秒
```
def join(self, timeout=None):
```
#### setDaemon方法
当我们在程序运行中，执行一个主线程，如果主线程又创建一个子线程，主线程和子线程就分兵两路，当主线程完成想退出时，会检验子线程是否完成。如果子线程未完成，则主线程会等待子线程完成后再退出。但是有时候我们需要的是，只要主线程完成了，不管子线程是否完成，都要和主线程一起退出，这时就可以用setDaemon方法，并设置其参数为True。
### Queue提供的类
- Queue队列
- LifoQueue后入先出（LIFO）队列
- PriorityQueue 优先队列
### 互斥锁
Python编程中，引入了对象互斥锁的概念，来保证共享数据操作的完整性。每个对象都对应于一个可称为" 互斥锁" 的标记，这个标记用来保证在任一时刻，只能有一个线程访问该对象。在Python中我们使用threading模块提供的Lock类。添加一个互斥锁变量mutex = threading.Lock()，然后在争夺资源的时候之前我们会先抢占这把锁mutex.acquire()，对资源使用完成之后我们在释放这把锁mutex.release()。
当一个线程调用Lock对象的acquire()方法获得锁时，这把锁就进入“locked”状态。因为每次只有一个线程可以获得锁，所以如果此时另一个线程试图获得这个锁，该线程就会变为同步阻塞状态。直到拥有锁的线程调用锁的release()方法释放锁之后，该锁进入“unlocked”状态。线程调度程序从处于同步阻塞状态的线程中选择一个来获得锁，并使得该线程进入运行（running）状态。
```
import threading
import time
counter = 0
mutex = threading.Lock()
class MyThread(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
def run(self):
global counter, mutex
time.sleep(1);
if mutex.acquire():
counter += 1
print "I am %s, set counter:%s" % (self.name, counter)
mutex.release()
if __name__ == "__main__":
for i in range(0, 100):
my_thread = MyThread()
my_thread.start()
```
### Condition条件变量
Python提供的Condition对象提供了对复杂线程同步问题的支持。Condition被称为条件变量，除了提供与Lock类似的acquire和release方法外，还提供了wait和notify方法。使用Condition的主要方式为：线程首先acquire一个条件变量，然后判断一些条件。如果条件不满足则wait；如果条件满足，进行一些处理改变条件后，通过notify方法通知其他线程，其他处于wait状态的线程接到通知后会重新判断条件。不断的重复这一过程，从而解决复杂的同步问题。
另外：Condition对象的构造函数可以接受一个Lock/RLock对象作为参数，如果没有指定，则Condition对象会在内部自行创建一个RLock；除了notify方法外，Condition对象还提供了notifyAll方法，可以通知waiting池中的所有线程尝试acquire内部锁。由于上述机制，处于waiting状态的线程只能通过notify方法唤醒，所以notifyAll的作用在于防止有线程永远处于沉默状态。
#### “生产者-消费者”模型
代码中主要实现了生产者和消费者线程，双方将会围绕products来产生同步问题，首先是2个生成者生产products ，而接下来的4个消费者将会消耗products.
实现举例：
```
#coding=utf-8
#!/usr/bin/env python
import threading
import time
condition = threading.Condition()
products = 0
class Producer(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
def run(self):
global condition, products
while True:
if condition.acquire():
if products < 10:
products += 1;
print "Producer(%s):deliver one, now products:%s" %(self.name, products)
condition.notify()
else:
print "Producer(%s):already 10, stop deliver, now products:%s" %(self.name, products)
condition.wait();
condition.release()
time.sleep(1)
class Consumer(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
def run(self):
global condition, products
while True:
if condition.acquire():
if products > 1:
products -= 1
print "Consumer(%s):consume one, now products:%s" %(self.name, products)
condition.notify()
else:
print "Consumer(%s):only 1, stop consume, products:%s" %(self.name, products)
condition.wait();
condition.release()
time.sleep(2)
if __name__ == "__main__":
for p in range(0, 2):
p = Producer()
p.start()
for c in range(0, 4):
c = Consumer()
c.start()
```
### 信号量semaphore
semaphore是一个变量，控制着对公共资源或者临界区的访问。信号量维护着一个计数器，指定可同时访问资源或者进入临界区的线程数。每次有一个线程获得信号量时，计数器-1。若计数器为0，其他线程就停止访问信号量，直到另一个线程释放信号量。
```
#coding=utf-8
import threading
import random
import time
class SemaphoreThread(threading.Thread):
"""class using semaphore"""
availableTables=['A','B','C','D','E']
def __init__(self,threadName,semaphore):
"""initialize thread"""
threading.Thread.__init__(self,name=threadName)
self.sleepTime=random.randrange(1,6)
#set the semaphore as a data attribute of the class
self.threadSemaphore=semaphore
def run(self):
"""Print message and release semaphore"""
#acquire the semaphore
self.threadSemaphore.acquire()
#remove a table from the list
table=SemaphoreThread.availableTables.pop()
print "%s entered;seated at table %s." %(self.getName(),table),
print SemaphoreThread.availableTables
time.sleep(self.sleepTime)
#free a table
print " %s exiting;freeing table %s." %(self.getName(),table),
SemaphoreThread.availableTables.append(table)
print SemaphoreThread.availableTables
#release the semaphore after execution finishes
self.threadSemaphore.release()
threads=[] #list of threads
#semaphore allows five threads to enter critical section
threadSemaphore=threading.Semaphore(len(SemaphoreThread.availableTables))
#创建一个threading.Semaphore对象，他最多允许5个线程访问临界区。
#Semaphore类的一个对象用计数器跟踪获取和释放信号量的线程数量。
#create ten threads
for i in range(1,11):
threads.append(SemaphoreThread("thread"+str(i),threadSemaphore))
#创建一个列表，该列表由SemaphoreThread对象构成，start方法开始列表中的每个线程
#start each thread
for thread in threads:
thread.start()
```
SemaphoreThread类的每个对象代表饭馆里的一个客人。类属性availableTables跟踪饭馆中可用的桌子。
信号量有个内建的计数器，用于跟踪他的acquire和release方法调用的次数。内部计数器的初始值可作为参数传给Semaphore构造函数。默认值为1.计数器大于0，Semaphore的acquire方法就为线程获得信号量，并计数器自减。
### 死锁现象
所谓死锁： 是指两个或两个以上的进程在执行过程中，因争夺资源而造成的一种互相等待的现象，若无外力作用，它们都将无法推进下去。此时称系统处于死锁状态或系统产生了死锁，这些永远在互相等待的进程称为死锁进程。 由于资源占用是互斥的，当某个进程提出申请资源后，使得有关进程在无外力协助下，永远分配不到必需的资源而无法继续运行，这就产生了一种特殊现象死锁。
```
import threading
counterA = 0
counterB = 0
mutexA = threading.Lock()
mutexB = threading.Lock()
class MyThread(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
def run(self):
self.fun1()
self.fun2()
def fun1(self):
global mutexA, mutexB
if mutexA.acquire():
print "I am %s , get res: %s" %(self.name, "ResA")
if mutexB.acquire():
print "I am %s , get res: %s" %(self.name, "ResB")
mutexB.release()
mutexA.release()
def fun2(self):
global mutexA, mutexB
if mutexB.acquire():
print "I am %s , get res: %s" %(self.name, "ResB")
if mutexA.acquire():
print "I am %s , get res: %s" %(self.name, "ResA")
mutexA.release()
mutexB.release()
if __name__ == "__main__":
for i in range(0, 100):
my_thread = MyThread()
my_thread.start()
```

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#coding=utf-8
import threading
def thread_fun(num):
for n in range(0, int(num)):
print " I come from %s, num: %s" %( threading.currentThread().getName(), n)
def main(thread_num):
thread_list = list();
# 先创建线程对象
for i in range(0, thread_num):
thread_name = "thread_%s" %i
thread_list.append(threading.Thread(target = thread_fun, name = thread_name, args = (20,)))
# 启动所有线程
for thread in thread_list:
thread.start()
# 主线程中等待所有子线程退出
for thread in thread_list:
thread.join()
if __name__ == "__main__":
main(3)

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related_info/lab7/semaphore_condition/thr-ex1.py View File

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#!/bin/env python
# -*- coding: utf-8 -*-
#filename: peartest.py
import threading, signal
is_exit = False
def doStress(i, cc):
global is_exit
idx = i
while not is_exit:
if (idx < 10000000):
print "thread[%d]: idx=%d"%(i, idx)
idx = idx + cc
else:
break
if is_exit:
print "receive a signal to exit, thread[%d] stop."%i
else:
print "thread[%d] complete."%i
def handler(signum, frame):
global is_exit
is_exit = True
print "receive a signal %d, is_exit = %d"%(signum, is_exit)
if __name__ == "__main__":
signal.signal(signal.SIGINT, handler)
signal.signal(signal.SIGTERM, handler)
cc = 5
threads = []
for i in range(cc):
t = threading.Thread(target=doStress, args=(i,cc))
t.setDaemon(True)
threads.append(t)
t.start()
while 1:
alive = False
for i in range(cc):
alive = alive or threads[i].isAlive()
if not alive:
break

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related_info/lab7/semaphore_condition/thr-ex2.py View File

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#!/usr/bin/env python
import threading
import time
count=1
class KissThread(threading.Thread):
def run(self):
global count
print "Thread # %s:Pretending to do stuff" % count
count+=1
time.sleep(2)
print "done with stuff"
for t in range(5):
KissThread().start()

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related_info/lab7/semaphore_condition/thr-ex3.py View File

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#coding=utf-8
#!/usr/bin/env python
import subprocess
from threading import Thread
from Queue import Queue
num_thread=3 #定义线程的数量
queue=Queue() #创建队列实例
ips=['192.168.1.100','192.168.1.110','192.168.1.120','192.168.1.130','192.168.1.200']
def pinger(i,q):
while True:
ip=q.get() #获取Queue队列传过来的ip，队列使用队列实例queue.put(ip)传入ip，通过q.get() 获得
print "Thread %s:Pinging %s" %(i,ip)
ret=subprocess.call("ping -c 1 %s" % ip,shell=True,stdout=open('/dev/null','w'),stderr=subprocess.STDOUT)
#调用子进程执行命令，获取退出状态。不能使用subprocess.Popen也可以
if ret==0:
print "%s:is alive" % ip
else:
print "%s:did not respond" % ip
q.task_done() #告诉queue.join()已完成队列中提取元组的工作
for i in range(num_thread):#各线程开始工作
worker=Thread(target=pinger,args=(i,queue)) #创建一个threading.Thread()的实例，给它一个函数以及函数的参数
worker.setDaemon(True) #在start方法被调用之前如果没有进行设置，程序会不定期挂起。
worker.start() #开始线程的工作，没有设置程序会挂起，不会开始线程的工作，因为pinger程序是while True循环
for ip in ips:
queue.put(ip) #将IP放入队列中。函数中使用q.get(ip)获取
print "Main Thread Waiting"
queue.join() #防止主线程在其他线程获得机会完成队列中任务之前从程序中退出。
print "Done"

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import threading
class MyThread(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
def run(self):
print "I am %s" % (self.name)
if __name__ == "__main__":
for i in range(0, 5):
my_thread = MyThread()
my_thread.start()

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related_info/lab7/semaphore_condition/thr-ex5.py View File

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#coding=utf-8
#!/usr/bin/env python
import threading
import time
condition = threading.Condition()
products = 0
class Producer(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
def run(self):
global condition, products
while True:
if condition.acquire():
if products < 10:
products += 1;
print "Producer(%s):deliver one, now products:%s" %(self.name, products)
condition.notify()
else:
print "Producer(%s):already 10, stop deliver, now products:%s" %(self.name, products)
condition.wait();
condition.release()
time.sleep(2)
class Consumer(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
def run(self):
global condition, products
while True:
if condition.acquire():
if products > 1:
products -= 1
print "Consumer(%s):consume one, now products:%s" %(self.name, products)
condition.notify()
else:
print "Consumer(%s):only 1, stop consume, products:%s" %(self.name, products)
condition.wait();
condition.release()
time.sleep(2)
if __name__ == "__main__":
for p in range(0, 2):
p = Producer()
p.start()
for c in range(0, 10):
c = Consumer()
c.start()

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import threading
import time
counter = 0
mutex = threading.Lock()
class MyThread(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
def run(self):
global counter, mutex
time.sleep(1);
if mutex.acquire():
counter += 1
print "I am %s, set counter:%s" % (self.name, counter)
mutex.release()
if __name__ == "__main__":
for i in range(0, 100):
my_thread = MyThread()
my_thread.start()

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related_info/lab7/semaphore_condition/thr-ex7.py View File

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#coding=utf-8
import threading
import random
import time
class SemaphoreThread(threading.Thread):
"""classusing semaphore"""
availableTables=['A','B','C','D','E']
def __init__(self,threadName,semaphore):
"""initialize thread"""
threading.Thread.__init__(self,name=threadName)
self.sleepTime=random.randrange(1,6)
#set the semaphore as a data attribute of the class
self.threadSemaphore=semaphore
def run(self):
"""Print message and release semaphore"""
#acquire the semaphore
self.threadSemaphore.acquire()
#remove a table from the list
table=SemaphoreThread.availableTables.pop()
print "%s entered;seated at table %s." %(self.getName(),table),
print SemaphoreThread.availableTables
time.sleep(self.sleepTime)
#free a table
print " %s exiting;freeing table %s." %(self.getName(),table),
SemaphoreThread.availableTables.append(table)
print SemaphoreThread.availableTables
#release the semaphore after execution finishes
self.threadSemaphore.release()
threads=[] #list of threads
#semaphore allows five threads to enter critical section
threadSemaphore=threading.Semaphore(len(SemaphoreThread.availableTables))
#创建一个threading.Semaphore对象，他最多允许5个线程访问临界区。
#Semaphore类的一个对象用计数器跟踪获取和释放信号机的线程数量。
#create ten threads
for i in range(1,11):
threads.append(SemaphoreThread("thread"+str(i),threadSemaphore))
#创建一个列表，该列表由SemaphoreThread对象构成，start方法开始列表中的每个线程
#start each thread
for thread in threads:
thread.start()

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import threading
counterA = 0
counterB = 0
mutexA = threading.Lock()
mutexB = threading.Lock()
class MyThread(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
def run(self):
self.fun1()
self.fun2()
def fun1(self):
global mutexA, mutexB
if mutexA.acquire():
print "I am %s , get res: %s" %(self.name, "ResA")
if mutexB.acquire():
print "I am %s , get res: %s" %(self.name, "ResB")
mutexB.release()
mutexA.release()
def fun2(self):
global mutexA, mutexB
if mutexB.acquire():
print "I am %s , get res: %s" %(self.name, "ResB")
if mutexA.acquire():
print "I am %s , get res: %s" %(self.name, "ResA")
mutexA.release()
mutexB.release()
if __name__ == "__main__":
for i in range(0, 100):
my_thread = MyThread()
my_thread.start()

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