python – 如何加速与子进程的通信

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我使用带有线程线程的 Python 2子进程来采用标准输入,使用二进制文件A,B和C进行处理,并将修改后的数据写入标准输出.

这个脚本(我们称之为:A_to_C.py)非常慢,我想学习如何解决它.

一般流程如下:

A_process = subprocess.Popen(['A','-'],stdin=subprocess.PIPE,stdout=subprocess.PIPE)
produce_A_thread = threading.Thread(target=produceA,args=(sys.stdin,A_process.stdin))

B_process = subprocess.Popen(['B',stdout=subprocess.PIPE)
convert_A_to_B_thread = threading.Thread(target=produceB,args=(A_process.stdout,B_process.stdin))

C_process = subprocess.Popen(['C',stdin=subprocess.PIPE)
convert_B_to_C_thread = threading.Thread(target=produceC,args=(B_process.stdout,C_process.stdin)) 

produce_A_thread.start()
convert_A_to_B_thread.start()
convert_B_to_C_thread.start()

produce_A_thread.join()
convert_A_to_B_thread.join()
convert_B_to_C_thread.join()

A_process.wait()
B_process.wait()
C_process.wait()

这个想法是标准输入到A_to_C.py:

> A二进制处理一个标准输入块,并使用函数generateA创建A输出.
> B二进制处理A的标准输出块,并通过函数generateB创建B输出.
> C二进制通过函数produceC处理B的标准输出块,并将C输出写入标准输出.

我用cProfile进行了剖析,几乎所有的时间在这个脚本似乎都花在了获取线程锁.

例如,在测试417s作业中,416s(总运行时的99%)用于获取线程锁:

$python                                                                                                                                                                                                                                         
Python 2.6.6 (r266:84292,Nov 21 2013,10:50:32)                                                                                                                                                                                                                                              
[GCC 4.4.7 20120313 (Red Hat 4.4.7-4)] on linux2                                                                                                                                                                                                                                              
Type "help","copyright","credits" or "license" for more information.                                                                                                                                                                                                                        
>>> import pstats                                                                                                                                                                                                                                                                             
>>> p = pstats.Stats('1.profile')                                                                                                                                                                                                                                                             
>>> p.sort_stats('cumulative').print_stats(10)                                                                                                                                                                                                                                                
Thu Jun 12 22:19:07 2014    1.profile                                                                                                                                                                                                                                                         

         1755 function calls (1752 primitive calls) in 417.203 cpu seconds                                                                                                                                                                                                                    

   Ordered by: cumulative time                                                                                                                                                                                                                                                                
   List reduced from 162 to 10 due to restriction <10>                                                                                                                                                                                                                                        

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)                                                                                                                                                                                                                       
        1    0.020    0.020  417.203  417.203 A_to_C.py:90(<module>)                                                                                                                                                                                  
        1    0.000    0.000  417.123  417.123 A_to_C.py:809(main)                                                                                                                                                                                     
        6    0.000    0.000  416.424   69.404 /foo/python/2.7.3/lib/python2.7/threading.py:234(wait)                                                                                                                                                                         
       32  416.424   13.013  416.424   13.013 {method 'acquire' of 'thread.lock' objects}                                                                                                                                                                                                     
        3    0.000    0.000  416.422  138.807 /foo/python/2.7.3/lib/python2.7/threading.py:648(join)                                                                                                                                                                         
        3    0.000    0.000    0.498    0.166 A_to_C.py:473(which)                                                                                                                                                                                    
       37    0.000    0.000    0.498    0.013 A_to_C.py:475(is_exe)                                                                                                                                                                                   
        3    0.496    0.165    0.496    0.165 {posix.access}                                                                                                                                                                                                                                  
        6    0.000    0.000    0.194    0.032 /foo/python/2.7.3/lib/python2.7/subprocess.py:475(_eintr_retry_call)                                                                                                                                                           
        3    0.000    0.000    0.191    0.064 /foo/python/2.7.3/lib/python2.7/subprocess.py:1286(wait)

我的线程错误我在做什么.Thread和/或subprocess.Popen安排导致这个问题?

解决方法

您对子进程的调用.Popen()隐式指定bufsize的默认值0,这将强制无缓冲的I / O.尝试添加合理的缓冲区大小(4K,16K,甚至1M),看看它是否有所不同.
原文链接:https://www.f2er.com/python/185778.html

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