X multi-process

#!/usr/bin/env Python3

#-*-Coding:utf-8-*-

‘‘‘

From multiprocessing import Process

Import OS

#子进程要执行的代码

def run_proc (name):

Print (' Run child process%s (%s) ... '% (Name,os.getpid ()))

If __name__== ' __main__ ':

Print (' Parent process%s. '% Os.getpid ())

P=process (target=run_proc,args= (' Test ',))

Print (' child process'll start. ')

P.start ()

P.join ()

Print (' Child process End ')

‘‘‘

#执行结果如下

‘‘‘

Parent process 4152.

Child process would start.

Run Child Process Test (10456) ...

Child process End

‘‘‘

#创建子进程时, you only need to pass in a parameter that executes functions and functions, create a process instance, and start with the start () method, so that the creation process is simpler than fork ().

The #join () method can wait for the child process to end before it continues to run, typically for inter-process synchronization.

‘‘‘

From multiprocessing import Pool

Import OS, Time,random

def long_time_task (name):

Print (' Run task%s (%s) ... '% (Name,os.getpid ()))

Start=time.time ()

Time.sleep (Random.random ())

End=time.time ()

Print (' Task%s runs%0.2f seconds. '% (name, (End-start)))

If __name__== ' __main__ ':

Print (' Parent process%s. '% Os.getpid ())

P=pool (4)

For I in range (5):

P.apply_async (long_time_task,args= (i,))

Print (' wainting for all subprocesses done ... ')

P.close ()

P.join ()

Print (' All subprocesses-done ... ')

‘‘‘

#执行结果如下

‘‘‘

Parent process 9508.

Wainting-subprocesses done ...

Run Task 0 (5084) ...

Run Task 1 (8540) ...

Run Task 2 (6500) ...

Run Task 3 (4756) ...

Task 1 runs 0.78 seconds.

Run Task 4 (8540) ...

Task 4 runs 0.93 seconds.

Task 0 runs 1.92 seconds.

Task 3 runs 2.49 seconds.

Task 2 runs 2.75 seconds.

All subprocesses-Done ...

‘‘‘

The #对POOL对象调用join () method waits for all child processes to complete, must call Close () before calling join (), and cannot continue adding a new process after calling Close ().

#请注意输出的结果, Task 0,1,2,3 is executed immediately, and task 4 waits for the previous task to complete before it executes, because the default size of the pool is 4 on this computer, so at the same time

#执行4个进程. This is a design restriction by the pool and is not a limitation of the operating system. If you change to: P=pool (5), you can run 5 processes at a time.

#由于POOL的默认大小是CPU的核数, if you unfortunately have a 8-core CPU, you will have to submit at least 9 sub-processes to see the wait effect above.

#子进程

#很多时候, a child process is not itself, but an external process. After we have created the child process, we also need to control the input and output of the child process.

The #subprocess module allows us to start a subprocess very conveniently and then control its input and output.

#下面演示如何在Python代码中运行命令nslookup www.python.org, this is the same effect as the command runs directly:

‘‘‘

Import subprocess

Print (' $nslookup www.python.org ')

R=subprocess.call ([' Nslookup ', ' www.python.org '])

Print (' Exit code: ', R)

‘‘‘

#执行结果如下:

‘‘‘

$nslookup www.python.org

Server: dc.gticom.cn

address:172.18.5.251

Non-authoritative response:

Name: python.map.fastly.net

addresses:2a04:4e42:11::223

151.101.72.223

Aliases:www.python.org

Exit code:0

‘‘‘

#如果子进程还需要输入, you can enter by using the Communicate () method:

‘‘‘

Import subprocess

Print (' $ Nslookup ')

P= subprocess. Popen ([' Nslookup '],stdin=subprocess. Pipe,stdout=subprocess. Pipe,stderr=subprocess. PIPE)

Output,err = P.communicate (b ' Set q=mx\npython.org\nexit\n ')

Print (Output.decode (' Utf-8 '))

Print (' Exit code: ', P.returncode)

‘‘‘

#上面的代码相当于在命令行执行命令nslookup, and then manually enter:

‘‘‘

Set Q=MX

python.org

Exit

‘‘‘

#上述代码未运行出来, don't bother.

#进程间通信

#Python multiprocessing Module wraps the underlying mechanism, providing queue, pipes, and many other ways to exchange data.

#以Queue为例, create two child processes in the parent process, one to write data to the queue, and one to read the data from the queue:

#队列是线程间最常用的交换数据的形式. The queue module is a module that provides queued operations.

From multiprocessing import Process,queue

Import Os,time,random

#写数据进程执行的代码

def write (q):

Print (' Process to write:%s '%os.getpid ())

For value in [' A ', ' B ', ' C ']:

Print (' Put%s to queue ... '% value)

Q.put (value) # calls the object's put () method to insert a project at the end of the queue.

Time.sleep (Random.random ()) # Time.sleep (n) postpones the call thread's run, indicating that the process is suspended for n seconds. The random.random is used to generate a random floating-point number between the interval [0,1].

#读数据进程执行的代码:

def read (q):

Print (' Process to read:%s '% os.getpid ())

While True:

Value=q.get (True) # calls the Get () method of the queue object, deletes from the team header and returns an item.

Print (' Get%s from queue. '% value)

If __name__== ' __main__ ':

#父进程创建Queue, and pass to each child process:

Q=queue ()

Pw=process (target=write,args= (q,))

Pr=process (target=read,args= (q,))

#启动子进程pw, write:

Pw.start ()

#启动子进程pr, read:

Pr.start ()

#等待pw结束:

The Pw.join () #join () method can wait for the child process to end before continuing to run, typically for inter-process synchronization.

#pr process is a dead loop, unable to wait for its end, only forcibly terminates:

Pr.terminate ()

#Process, create the class of the process: process ([Group[,target[,name[,args[,kwargs]]]), target indicates the calling object (typically the function name),

#args表示调用对象的位置参数 (Typically, a function's entry) tuple. The Kwargs represents the dictionary of the calling object. Name is an alias. Group is not actually used.

#输出结果如下:

‘‘‘

Process to write:7952

Put A to queue ...

Process to read:13656

Get A from queue.

Put B to queue ...

Get B from the queue.

Put C to queue ...

Get C from queue.

‘‘‘

# under Unix/linux, the multiprocessing module encapsulates the fork () call, so we don't need to focus on the details of the fork (). Because Windows does not have a fork call, multiprocessing needs to ' emulate ' out

#fork的效果, all Python objects of the parent process must be pickle serialized and then passed to the child process, so if multiprocessing fails in Windows downgrade, consider whether the pickle failed.

#在Unix/linux, you can use the fork () call to implement multiple processes.

#要实现跨平台的多进程, you can use the Multiprocessing module

#进程间通信是通过Queue, pipes and other implementations.

X multi-process