多进程旧式写法
from multiprocessing import Pool
def f(x):
return x*x if __name__ == '__main__':
p = Pool(5)
print(p.map(f,[1,2,3]))
多进程新式写法
from multiprocessing import Process
def run(num):
print 'this is ',num for i in range(10):
t = Process(target=run,args=(i,))
t.start()
多进程-父子进程
from multiprocessing import Process
import os
def info(title):
print title
print 'module name:',__name__
if hasattr(os,'getppid'):
print 'parent process:',os.getppid() #获取父进程PID
print 'process id:',os.getpid() #获取子进程PID
def f(name):
info('function f') #子进程调用info函数
print 'hello',name
if __name__ == '__main__':
info('main line') #父进程调用info函数
print '---------------'
p = Process(target=f,args=('bob',))
p.start()
p.join()
进程数据共享
from multiprocessing import Process
li = []
def run(num):
li.append(num)
print 'say hi',li for i in range(10):
t = Process(target=run,args=(i,))
t.start() print 'ending',li
进程各自持有一份数据，默认无法共享数据，要使进程间可以共享数据，则
#方法一，Array
from multiprocessing import Process,Array
#创建一个只包含数字类型的一个数组/列表，并且个数不可变
temp = Array('i', [11,22,33,44]) def Foo(i):
temp[i] = 100+i
for item in temp:
print i,'----->',item for i in range(2):
p = Process(target=Foo,args=(i,))
p.start()
#方法二：manage.dict()共享数据
from multiprocessing import Process,Manager
manage = Manager()
dic = manage.dict()
def Foo(i):
dic[i] = 100+i
print dic.values()
for i in range(2):
p = Process(target=Foo,args=(i,))
p.start()
p.join()
#方法，Queue
from multiprocessing import Process,Queue
def f(q,n):
q.put([n,'hello'])
if __name__ == '__main__':
q = Queue()
for i in range(5):
p = Process(target=f,args=(q,i))
p.start()
while True:
print q.get()
#方法4，Manager
from multiprocessing import Process,Manager
def f(d,l):
d[1] = '1'
d['2'] = 2
d[0.25] = None
l.reverse() #反向列表
if __name__ == '__main__':
manager = Manager()
d = manager.dict()
#d = {}
l = manager.list(range(10))
#l = [0,1,2,4,5,6,7,8,9]
p = Process(target=f,args=(d,l))
p.start()
p.join()
print d
print l
进程锁
from multiprocessing import Process, Array, RLock
def Foo(lock,temp,i):
"""
将第0个数加100
"""
lock.acquire() #加锁
temp[0] = 100+i
for item in temp:
print i,'----->',item
lock.release() #解锁 lock = RLock()
temp = Array('i', [11, 22, 33, 44])
for i in range(20):
p = Process(target=Foo,args=(lock,temp,i,))
p.start()
进程池
进程池内部维护一个进程序列，当使用时，则去进程池中获取一个进程，如果进程池序列中没有可供使用的进进程，那么程序就会等待，直到进程池中有可用进程为止。
进程池中有两个方法：
- apply
- apply_async
from multiprocessing import Process,Pool
import time def Foo(i):
time.sleep(2)
return i+100 def Bar(arg):
print arg pool = Pool(5)
#print pool.apply(Foo,(1,))
#print pool.apply_async(func =Foo, args=(1,)).get()
for i in range(10):
pool.apply_async(func=Foo, args=(i,),callback=Bar) print 'end'
pool.close()
pool.join()#进程池中进程执行完毕后再关闭，如果注释，那么程序直接关闭。
from multiprocessing import Pool
import time
def f(x):
print x*x
#time.sleep(2)
return x*x if __name__ == '__main__':
pool = Pool(processes=2) #同时5个进程
res_list = []
for i in range(5):
res = pool.apply_async(f,[i,])
#res = Process(target=f,args=[i,])
print '-----------',i
res_list.append(res)
for r in res_list:
print 'res_list:',r.get()
协程
线程和进程的操作是由程序触发系统接口，最后的执行者是系统；协程的操作则是程序员。
协程存在的意义：对于多线程应用，CPU通过切片的方式来切换线程间的执行，线程切换时需要耗时（保存状态，下次继续）。协程，则只使用一个线程，在一个线程中规定某个代码块执行顺序。
协程的适用场景：当程序中存在大量不需要CPU的操作时（IO），适用于协程；
greenlet
#!/usr/bin/env python
# -*- coding:utf-8 -*- from greenlet import greenlet def test1():
print 12
gr2.switch()
print 34
gr2.switch() def test2():
print 56
gr1.switch()
print 78 gr1 = greenlet(test1)
gr2 = greenlet(test2)
gr1.switch()
gevent
import gevent def foo():
print('Running in foo')
gevent.sleep(0)
print('Explicit context switch to foo again') def bar():
print('Explicit context to bar')
gevent.sleep(0)
print('Implicit context switch back to bar') gevent.joinall([
gevent.spawn(foo),
gevent.spawn(bar),
])
遇到IO操作自动切换：
from gevent import monkey; monkey.patch_all()
import gevent
import urllib2 def f(url):
print('GET: %s' % url)
resp = urllib2.urlopen(url)
data = resp.read()
print('%d bytes received from %s.' % (len(data), url)) gevent.joinall([
gevent.spawn(f, 'https://www.python.org/'),
gevent.spawn(f, 'https://www.yahoo.com/'),
gevent.spawn(f, 'https://github.com/'),
])