python中的多线程其实并不是真正的多线程,如果想要充分地使用多核CPU资源,在python中大部分情况需要使用多进程。python提供了非常好用的多进程包Multiprocessing,只需要定义一个函数,python会完成其它所有事情。借助这个包,可以轻松完成从单进程到并发执行的转换。multiprocessing支持子进程、通信和共享数据、执行不同形式的同步,提供了Process、Queue、Pipe、LocK等组件
一、Process
语法:Process([group[,target[,name[,args[,kwargs]]]]])
参数含义:target表示调用对象;args表示调用对象的位置参数元祖;kwargs表示调用对象的字典。name为别名,groups实际上不会调用。
方法:is_alive():
join(timeout):
run():
start():
terminate():
属性:authkey、daemon(要通过start()设置)、exitcode(进程在运行时为None、如果为-N,表示被信号N结束)、name、pid。其中daemon是父进程终止后自动终止,且自己不能产生新的进程,必须在start()之前设置。
1.创建函数,并将其作为单个进程
from multiprocessing import Process def func(name): print("%s曾经是好人"%name) if __name__ == "__main__": p = Process(target=func,args=('kebi',)) p.start() #start()通知系统开启这个进程
2.创建函数并将其作为多个进程
from multiprocessing import Process import random,time def hobby_motion(name): print('%s喜欢运动'% name) time.sleep(random.randint(1,3)) def hobby_game(name): print('%s喜欢游戏'% name) time.sleep(random.randint(1,3)) if __name__ == "__main__": p1 = Process(target=hobby_motion,args=('付婷婷',)) p2 = Process(target=hobby_game,args=('科比',)) p1.start() p2.start()
执行结果:
付婷婷喜欢运动 科比喜欢游戏
3.将进程定义为类(开启进程的另一种方法,并不是很常用)
from multiprocessing import Process class MyProcess(Process): def __init__(self,name): super().__init__() self.name = name def run(self): #start()时,run自动调用,而且此处只能定义为run。 print("%s曾经是好人"%self.name) if __name__ == "__main__": p = MyProcess('kebi') p.start() #将Process当作父类,并且自定义一个函数。
4.daemon程序对比效果
不加daemon属性
import time def func(name): print("work start:%s"% time.ctime()) time.sleep(2) print("work end:%s"% time.ctime()) if __name__ == "__main__": p = Process(target=func,args=('kebi',)) p.start() print("this is over") #执行结果 this is over work start:Thu Nov 30 16:12:00 2017 work end:Thu Nov 30 16:12:02 2017
加上daemon属性
from multiprocessing import Process import time def func(name): print("work start:%s"% time.ctime()) time.sleep(2) print("work end:%s"% time.ctime()) if __name__ == "__main__": p = Process(target=func,args=('kebi',)) p.daemon = True #父进程终止后自动终止,不能产生新进程,必须在start()之前设置 p.start() print("this is over") #执行结果 this is over
设置了daemon属性又想执行完的方法:
import time def func(name): print("work start:%s"% time.ctime()) time.sleep(2) print("work end:%s"% time.ctime()) if __name__ == "__main__": p = Process(target=func,args=('kebi',)) p.daemon = True p.start() p.join() #执行完前面的代码再执行后面的 print("this is over") #执行结果 work start:Thu Nov 30 16:18:39 2017 work end:Thu Nov 30 16:18:41 2017 this is over
5.join():上面的代码执行完毕之后,才会执行后i面的代码。
先看一个例子:
from multiprocessing import Process import time,os,random def func(name,hour): print("A lifelong friend:%s,%s"% (name,os.getpid())) time.sleep(hour) print("Good bother:%s"%name) if __name__ == "__main__": p = Process(target=func,args=('kebi',2)) p1 = Process(target=func,args=('maoxian',1)) p2 = Process(target=func,args=('xiaoniao',3)) p.start() p1.start() p2.start() print("this is over")
执行结果:
this is over #最后执行,最先打印,说明start()只是开启进程,并不是说一定要执行完 A lifelong friend:kebi,12048 A lifelong friend:maoxian,8252 A lifelong friend:xiaoniao,6068 Good bother:maoxian #最先打印,第二位执行 Good bother:kebi Good bother:xiaoniao
添加join()
from multiprocessing import Process import time,os,random def func(name,hour): print("A lifelong friend:%s,%s"% (name,os.getpid())) time.sleep(hour) print("Good bother:%s"%name) start = time.time() if __name__ == "__main__": p = Process(target=func,args=('kebi',2)) p1 = Process(target=func,args=('maoxian',1)) p2 = Process(target=func,args=('xiaoniao',3)) p.start() p.join() #上面的代码执行完毕之后,再执行后面的 p1.start() p1.join() p2.start() p2.join() print("this is over") print(time.time() - start) #执行结果 A lifelong friend:kebi,14804 Good bother:kebi A lifelong friend:maoxian,11120 Good bother:maoxian A lifelong friend:xiaoniao,10252 #每个进程执行完了,才会执行下一个 Good bother:xiaoniao this is over 6.497815370559692 #2+1+3+主程序执行时间
改变一下位置
from multiprocessing import Process import time,os,random def func(name,hour): print("A lifelong friend:%s,%s"% (name,os.getpid())) time.sleep(hour) print("Good bother:%s"%name) start = time.time() if __name__ == "__main__": p = Process(target=func,args=('kebi',2)) p1 = Process(target=func,args=('maoxian',1)) p2 = Process(target=func,args=('xiaoniao',3)) p.start() p1.start() p2.start() p.join() #需要2秒 p1.join() #到这时已经执行完 p2.join() #已经执行了2秒,还要1秒 print("this is over") print(time.time() - start) #执行结果 A lifelong friend:kebi,13520 A lifelong friend:maoxian,11612 A lifelong friend:xiaoniao,17064 #几乎是同时开启执行 Good bother:maoxian Good bother:kebi Good bother:xiaoniao this is over 3.273620367050171 #以最长时间的为主
6.其它属性和方法
from multiprocessing import Process import time def func(name): print("work start:%s"% time.ctime()) time.sleep(2) print("work end:%s"% time.ctime()) if __name__ == "__main__": p = Process(target=func,args=('kebi',)) p.start() p.terminate() #将进程杀死,而且必须放在start()后面,与daemon的功能类似 #执行结果 this is over
from multiprocessing import Process import time def func(name): print("work start:%s"% time.ctime()) time.sleep(2) print("work end:%s"% time.ctime()) if __name__ == "__main__": p = Process(target=func,args=('kebi',)) # p.daemon = True print(p.is_alive()) p.start() print(p.name) #获取进程的名字 print(p.pid) #获取进程的pid print(p.is_alive()) #判断进程是否存在 print("this is over")
来源:https://www.cnblogs.com/xxpythonxx/p/12150385.html