7. Multi-process development

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1. Multi-process

Multi-Process Official documentation

Https://docs.python.org/2/library/multiprocessing.html

"Multi-process"

Example 1:

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!/usr/bin/env python#coding:utf-8from multiprocessing import pooldef f (x):     return x*x                 #返回自乘值if  __name__ ==  ' __main__ ':     p = pool (5)                #定义5个进程      print  (P.map (f,[1,2,3]))   #调用f函数, send 1,2.3 to X, let them squared Example 2: (This script can only be used under Linux to produce effects) #多进程使用方法: #!/usr/bin/ env python#coding:utf-8from multiprocessing import processimport osimport  Timedef info (title):    print title    print  ' module  name: ', __name__    if hasattr (os,  ' getppid '):         print  ' parent process: ',  os.getppid ()      # Output parent Process Id    time.sleeP (3)     print  ' Process id: ',  os.getpid ()                 #输出子进程IDdef  f (name):     info (' Function f ')     print  ' hellow ',nameif __name__ ==  ' __main__ ':     info (' main line ')     print  '---------------'      p = process (target=f,args= (' Bob ',))     p.start ()      p.join ()

Usage: How many cores the CPU uses, or 1 time times the number of CPU cores

Multi-process use and multi-threaded use of different points (this script can only run under Linux) [[email protected] opt]# cat pro.py #!/usr/bin/env python#coding:utf-8from Multiprocessing Import Processimport threadingdef run (info_list,n): Info_list.append (n) Print info_listinfo=[]for I In range: p = Process (Target=run,args=[info,i]) #多进程独享内存, 10 process P.start () print '---------threding-----' info=[ ]for i in range: P = Threading. Thread (Target=run,args=[info,i]) #多线程共享内存, 10 Threads P.start ()

Memory synchronization method between processes: (memory sharing first method)

[Email protected] opt]# vim multiprocess.py #!/usr/bin/env python#coding:utf-8from multiprocessing Import Process,queu Edef f (q,n): Q.put ([N, ' hello ']) print q.get () print q.get () if __name__ = = ' __main__ ': q = Queue () q.put (' DD d ') for I in range (5): p = Process (target=f,args= (q,i)) P.start () while True:print Q.get ()

The second method of memory sharing

#!/usr/bin/env python#coding:utf-8from multiprocessing Import Process, Value, Arraydef f (N, a): N.value = 3.1415927 For I in range (Len (a)): a[i] =-a[i]if __name__ = = ' __main__ ': num = Value (' d ', 0.0) arr = Array (' I ', range (1 0)) p = Process (target=f, args= (num, arr)) P.start () p.join () Print num.value print arr[:]

Third method of memory sharing (recommended, more supported types)

#!/usr/bin/env python#coding:utf-8from multiprocessing Import process,managerdef F (d,l): d[1] = ' 1 ' #给字典赋值 d[2 ] = ' 2 ' d[0.25] = None l.reverse #把列表反向输出if __name__ = = ' __main__ ': Manger = Manager () d = manger.dict ( ) #获取字典, empty dictionary L = manger.list (range) #获取列表 p = Process (Target=f, args= (d,l)) P.start () P.join () print D Print L

Multi-process through pool, process pool (not commonly used)

#!/usr/bin/env python#coding:utf-8from multiprocessing Import poolimport timedef f (x): Print x*x time.sleep (2) Re    Turn X*xpool = Pool (processes=5) #每次跑5个进程res_list = []for i in range: res = Pool.apply_async (f, [I,]) #定义十个进程 #res = Process (Target=f, Args[i,]) #上面那一句相当于这一句的意思 #print '----: ', I res_list.append (res) for R in RES_LIST:PR int R.get () #print Pool.map (F.range (10))

#进程生成线程

#!/usr/bin/env python#coding:utf-8from multiprocessing import poolimport timedef  f (x):    info_list = []    for i in  Range () 5:        t = threading. Thread (Target =t_func,args=[info_list,i])         t.start () pool  = pool (processes=5)    #每次跑5个进程res_list  = []for i in range (10):     res = pool.apply_async (F, [i,])    #定义十个进程       #res  = process (Target=f, args[i,])    #上面那一句相当于这一句的意思      print  '----: ', I    res_list.append (res) for r in res_list:        print r.get (timeout=1) #print  pool.map (F.range (10)) 1, creating a process program from  Multiprocessing import processimport threadingimPort timedef foo (i):    print  ' Say hi ', Ifor i in range ( ):     p = process (target=foo,args= (i,))     p.start ()

2. Data sharing between processes

The default holds one copy of each

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#!/usr/bin/env python#coding:utf-8from multiprocessing Import processfrom multiprocessing import Managerimport Timeli =    []def Foo (i): Li.append (i) print ' Say hi ', Li for I in range: p = Process (target=foo,args= (i,)) P.start () Print Li

Data sharing between processes can be accomplished through a special data structure

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#方法一, arrayfrom multiprocessing Import process,arraytemp = Array (' i ', [11,22,33,44]) def Foo (i): temp[i] = 100+i for I Tem in Temp:print I, '-----> ', itemfor I in range (2): P = Process (target=foo,args= (i,)) P.start () P.join ()

#方法二: Manage.dict () shared data

From multiprocessing Import process,managermanage = 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 ()

#方法三: Manage. Namespace () Sharing data

From multiprocessing Import process,managermanage = Manager () namespace = manage.  Namespace () namespace.x = [11,22,33]def Foo (i,dic): namespace.x = [11,22,33,i] Print namespacefor i in range (2): P = Process (target=foo,args= (i,namespace)) P.start () P.join ()

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7. Multi-process development