python之多线程与多进程
关键词： GIL锁，IO繁忙，线程安全，线程同步，进程池，进程通信，队列
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GIL锁;
全局解释锁，Global Interpretor Lock,
作用:单位时间内只允许一个线程运行。
结果：无法利用多核实现并发功能，cpu繁忙的任务无效甚至效率更低（进程切换需要耗费资源），因此在python中不建议使用多线程，而使用多进程代替 -
cpu繁忙与io繁忙
cpu繁忙：内存操作多
io繁忙：硬盘或其他存储介质读写多，比如各种数据中心，网络存储和云存服务器
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线程同步：
单位时间只能有一个线程访问某个资源
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线程安全：
使用了线程同步，保证资源正确调用
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python实现多进程的方法：
主角：multiprocessing
工具：Process（进程转化为类）, Pool（进程池）, Queue（队列，用于进程通讯）
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初级实现：
class Myprocess(Process): #自定义线程类 def __init__(self, wait_ime): Process.__init__(self) self.wait_ime = wait_ime def run(self):#重写run方法！！！！！！重要 n = 0 while n < 4: print ("subProcess %s run," % os.getpid(), "{0}".format(time.ctime())) time.sleep(self.wait_ime) n += 1 if __name__ == "__main__": p=Myprocess(2) q=Myprocess(0.5) p.start() #启动进程 q.start() p.join() #等待p进程结束，主进程才能往下运行（简称阻塞） q.join() print('结束') -
结果
subProcess 6600 run, Thu Nov 22 16:19:57 2018 # 两个同进程 subProcess 3012 run, Thu Nov 22 16:19:57 2018 subProcess 3012 run, Thu Nov 22 16:19:58 2018 subProcess 3012 run, Thu Nov 22 16:19:58 2018 subProcess 3012 run, Thu Nov 22 16:19:59 2018 subProcess 6600 run, Thu Nov 22 16:19:59 2018 subProcess 6600 run, Thu Nov 22 16:20:01 2018 subProcess 6600 run, Thu Nov 22 16:20:03 2018 结束 -
进程池
def example(wait_ime): n = 0 while n < 4: print ("subProcess %s run," % os.getpid(), "{0}".format(time.ctime())) time.sleep(wait_ime) n += 1 if __name__ == "__main__": pool=Pool(5) for i in (0.1,1.2,0.5): pool.apply_async(example,(i,))#非阻塞模式，不会等一个进程运行完才运行下一个进程 pool.close() pool.join() print('结束') 队列（实现生产者与消费者模式的核心工具）
class MultiProcessProducer(multiprocessing.Process):#生产者类 def __init__(self, num, queue): # 传出队列queue """Constructor""" multiprocessing.Process.__init__(self) self.num = num self.queue = queue def run(self): #存入数字 t1 = time.time() print('producer start ' + str(self.num)) for i in range(1000): self.queue.put((i, self.num)) #插入队列 time.sleep(0.1) print ('producer put', i, self.num) t2 = time.time() print('producer exit ' + str(self.num)) use_time = str(t2 - t1) print('producer ' + str(self.num) + ', \ use_time: '+ use_time) class MultiProcessConsumer(multiprocessing.Process):# 消费者类 def __init__(self, num, queue): """Constructor""" multiprocessing.Process.__init__(self) self.num = num self.queue = queue #传入队列 def run(self): t1 = time.time() print('consumer start ' + str(self.num)) while True: d = self.queue.get() print('get'+str(d)) t2 = time.time() print('consumer exit ' + str(self.num)) print('consumer ' + str(self.num) + ', use time:'+ str(t2 - t1)) def main(): # create queue queue = multiprocessing.Queue() # create processes producer = [] for i in range(5): producer.append(MultiProcessProducer(i, queue)) consumer = [] for i in range(5): consumer.append(MultiProcessConsumer(i, queue)) # start processes for i in range(len(producer)): producer[i].start() for i in range(len(consumer)): consumer[i].start() # wait for processs to exit for i in range(len(producer)): producer[i].join() for i in range(len(consumer)): queue.put(None) for i in range(len(consumer)): consumer[i].join() print('all done finish')
