多线程
协程
IO模型
多线程
进程:是资源单位 进程之前是竞争关系 线程:是资源CPU计算单位 线程之间是协作关系 线程两个特点:1、线程的创建开销小,速度快。 2、1个进程下的多个线程之间共享名称空间或资源。 注:Linux系统下,子进程会复制父进程的状态。
#线程的PID与主进程PID一致 from threading import Thread from multiprocessing import Process import os def task(): print('%s is running' %os.getpid()) if __name__ == '__main__': t1=Thread(target=task,) t2=Thread(target=task,) # t1=Process(target=task,) # t2=Process(target=task,) t1.start() t2.start() print('主',os.getpid())
#多线程共享一个进程内的资源 from threading import Thread from multiprocessing import Process n=100 def work(): global n n=0 if __name__ == '__main__': # p=Process(target=work,) # p.start() # p.join() # print('主',n) t=Thread(target=work,) t.start() t.join() print('主',n)
#开启线程的两种方式 #开启线程的方式一:使用替换threading模块提供的Thread from threading import Thread from multiprocessing import Process def task(): print('is running') if __name__ == '__main__': t=Thread(target=task,) # t=Process(target=task,) t.start() print('主') #开启线程的方式二:自定义类,继承Thread from threading import Thread from multiprocessing import Process class MyThread(Thread): def __init__(self,name): super().__init__() self.name=name def run(self): print('%s is running' %self.name) if __name__ == '__main__': t=MyThread('egon') # t=Process(target=task,) t.start() print('主')
#多线程共享同一进程内地址空间的练习 #三个任务,一个接收用户输入,一个将用户输入的内容格式化成大写,一个将格式化后的结果存入文件 from threading import Thread msg_l=[] format_l=[] def talk(): while True: msg=input('>>: ').strip() msg_l.append(msg) def format(): while True: if msg_l: data=msg_l.pop() format_l.append(data.upper()) def save(): while True: if format_l: data=format_l.pop() with open('db.txt','a') as f: f.write('%s ' %data) if __name__ == '__main__': t1=Thread(target=talk) t2=Thread(target=format) t3=Thread(target=save) t1.start() t2.start() t3.start()
#Thread对象其他相关的属性或方法 from threading import Thread,activeCount,enumerate,current_thread import time def task(): print('%s is running' %current_thread().getName()) time.sleep(2) if __name__ == '__main__': t=Thread(target=task,) t.start() t.join() print(t.is_alive()) 无join()返回True,有join()返回FALSE print(t.getName()) 获取线程名 print(enumerate()) 当前活跃的线程信息/对象 print('主') print(activeCount()) 返回活跃的线程个数
#current_thread的用法 返回当前进程信息 from threading import Thread,activeCount,enumerate,current_thread from multiprocessing import Process import time def task(): print('%s is running' %current_thread().getName()) time.sleep(2) if __name__ == '__main__': p=Process(target=task) p.start() print(current_thread()) #有MainThread主进程对象信息 from threading import Thread,activeCount,enumerate,current_thread from multiprocessing import Process import time def task(): print('%s is running' %current_thread().getName()) time.sleep(2) if __name__ == '__main__': t1=Thread(target=task) t2=Thread(target=task) t3=Thread(target=task) t1.start() t2.start() t3.start() print(current_thread()) #强调:主线程从执行层面上代表了其所在进程的执行过程
#先看:守护进程 from multiprocessing import Process import time def task1(): print('123') time.sleep(1) print('123done') def task2(): print('456') time.sleep(10) print('456done') if __name__ == '__main__': p1=Process(target=task1) p2=Process(target=task2) p1.daemon = True p1.start() p2.start() print('主') ‘’‘主 456 456done’‘’ #再看:守护线程 from threading import Thread import time def task1(): print('123') time.sleep(10) print('123done') def task2(): print('456') time.sleep(1) print('456done') if __name__ == '__main__': t1=Thread(target=task1) t2=Thread(target=task2) t1.daemon=True t1.start() t2.start() print('主') ‘’‘123 456 主 456done’‘’
#Python GIL(Global Interpreter Lock) 全局解释器锁 #注意的点: #1.线程抢的是GIL锁,GIL锁相当于执行权限,拿到执行权限后才能拿到互斥锁Lock,其他线程也可以抢到GIL,但如果发现Lock仍然没有被释放则阻塞,即便是拿到执行权限GIL也要立刻交出来 #2.join是等待所有,即整体串行,而锁只是锁住修改共享数据的部分,即部分串行,要想保证数据安全的根本原理在于让并发变成串行,join与互斥锁都可以实现,毫无疑问,互斥锁的部分串行效率要更高 from threading import Thread n=100 def task(): print('is running') if __name__ == '__main__': t1=Thread(target=task,) t2=Thread(target=task,) t3=Thread(target=task,) # t=Process(target=task,) t1.start() t2.start() t3.start() print('主') #线程的互斥锁 from threading import Thread,Lock import time n=100 def work(): global n mutex.acquire() temp=n time.sleep(0.1) n=temp-1 mutex.release() if __name__ == '__main__': mutex=Lock() l=[] start=time.time() for i in range(100): t=Thread(target=work) l.append(t) t.start() for t in l: t.join() print('run time:%s value:%s' %(time.time()-start,n)) #互斥锁与join的区别 #join from threading import Thread,Lock import time n=100 def work(): time.sleep(0.05) global n temp=n time.sleep(0.1) n=temp-1 if __name__ == '__main__': start=time.time() for i in range(100): t=Thread(target=work) t.start() t.join() print('run time:%s value:%s' %(time.time()-start,n #多进程: #优点:可以利用多核优势 #缺点:开销大 #多线程: #优点:开销小 #缺点:不能利用多核优势 from threading import Thread from multiprocessing import Process import time #计算密集型 def work(): res=1 for i in range(100000000): res+=i if __name__ == '__main__': p_l=[] start=time.time() for i in range(4): # p=Process(target=work) #6.7473859786987305 p=Thread(target=work) #24.466399431228638 p_l.append(p) p.start() for p in p_l: p.join() print(time.time()-start) from threading import Thread from multiprocessing import Process import time #IO密集型 def work(): time.sleep(2) if __name__ == '__main__': p_l=[] start=time.time() for i in range(400): # p=Process(target=work) #12.104692220687866 p=Thread(target=work) #2.038116455078125 p_l.append(p) p.start() for p in p_l: p.join() print(time.time()-start) #死锁现象 from threading import Thread,Lock,RLock import time mutexA=Lock() mutexB=Lock() class Mythread(Thread): def run(self): self.f1() self.f2() def f1(self): mutexA.acquire() print('