python 多线程和多进程

在python中，多线程的使用还是比较多的，记录一下class继承的实现方法

• 多线程

class mythread(threading.Thread):
    def __init__(self,i):
        threading.Thread.__init__(self)
        self.i = i
    def run(self):
        for j in range(10000):
            print self.i

if __name__ == '__main__':
    threads = []
    for i in range(5):
        t = mythread(i)
        t.start()
        if threading.activeCount()>2:#让线程数不大于2
            for t in threads:
                t.join()
    for t in thread:
        t.join()

当然，可以使用lock=threading.RLock() #需要的话使用这个进行锁，lock.acquire()与lock.release()包住次只允许一个线程操作的地方。多线程有些时候不能提高程序的执行效率，主要限制为python的机制GIL将线程有效地限制到一个核中。详细http://www.cnblogs.com/mindsbook/archive/2009/10/15/thread-safety-and-GIL.html

• 多进程

import multiprocessing
class proc(multiprocessing.Process):
    def __init__(self,i):
        multiprocessing.Process.__init__(self)
        self.t = i
    def run(self):
        for i in range(10000):
            print self.t,
if __name__ == '__main__':
    jobs = []
    for i in range(7):
        p = proc(i)
        p.start()
        jobs.append(p)
        print multiprocessing.active_children()
        if len(multiprocessing.active_children())>1:
            for j in jobs:
                j.join()
    for j in jobs:
        j.join()
    print "over"

锁

import threading
import Queue
class procg(threading.Thread):
    def __init__(self,queue,lockname,i):
        threading.Thread.__init__(self)
        self.queue = queue
        self.lock = lockname
        self.num = i
    def run(self):
        import time
        i = 0
        while(i<500):
            self.lock.acquire()
            if not self.queue.empty():
                data = self.queue.get()
                print 'get '+ self.num +': '+str(data)
                self.lock.release()
                for j in range(100000):
                    i = i
                i += 1
            else:
                self.lock.release()

class proc(threading.Thread):
    def __init__(self,queue,lockname):
        threading.Thread.__init__(self)
        self.queue = queue
        self.lock = lockname
    def run(self):
        import time
        i = 0
        while(i<1000):
            self.lock.acquire()
            self.queue.put(i)
            print "put " + str(i)
            self.lock.release()
            for j in range(100000):
                i = i
            i += 1


if __name__ == '__main__':
    jobs = []
    queue = Queue.Queue()
    queueLock = threading.Lock()
    p = proc(queue,queueLock)
    p.start()
    jobs.append(p)
    g1 = procg(queue,queueLock,'1')
    g1.start()
    jobs.append(g1)
    g2 = procg(queue,queueLock,'2')
    g2.start()
    jobs.append(g2)
    for j in jobs:
        j.join()
    print "over"

详情参考 http://outofmemory.cn/code-snippet/2267/Python-duojincheng-multiprocessing-usage-example与http://bofang.iteye.com/blog/1684345