如何在python中运行并行程序

Question

I have a python script to run a few external commands using the os.subprocess module. But one of these steps takes a huge time and so I would like to run it separately. I need to launch them, check they are finished and then execute the next command which is not parallel. My code is something like this:

nproc = 24 
for i in xrange(nproc):
    #Run program in parallel

#Combine files generated by the parallel step
for i in xrange(nproc):
    handle = open('Niben_%s_structures' % (zfile_name), 'w')
    for i in xrange(nproc):
        for zline in open('Niben_%s_file%d_structures' % (zfile_name,i)):handle.write(zline)
    handle.close()

#Run next step
cmd = 'bowtie-build -f Niben_%s_precursors.fa bowtie-index/Niben_%s_precursors' % (zfile_name,zfile_name)

Answer 1

For your example, you just want to shell out in parallel - you don't need threads for that.

Use the Popen constructor in the subprocess module: http://docs.python.org/library/subprocess.htm

Collect the Popen instances for each process you spawned and then wait() for them to finish:

procs = []
for i in xrange(nproc):
    procs.append(subprocess.Popen(ARGS_GO_HERE)) #Run program in parallel
for p in procs:
    p.wait()

You can get away with this (as opposed to using the multiprocessing or threading modules), since you aren't really interested in having these interoperate - you just want the os to run them in parallel and be sure they are all finished when you go to combine the results...

Answer 2

Running things in parallel can also be implemented using multiple processes in Python. I had written a blog post on this topic a while ago, you can find it here

http://multicodecjukebox.blogspot.de/2010/11/parallelizing-multiprocessing-commands.html

Basically, the idea is to use "worker processes" which independently retrieve jobs from a queue and then complete these jobs.

Works quite well in my experience.

Answer 3

You can do it using threads. This is very short and (not tested) example with very ugly if-else on what you are actually doing in the thread, but you can write you own worker classes..

import threading

class Worker(threading.Thread):
    def __init__(self, i):
        self._i = i
        super(threading.Thread,self).__init__()

    def run(self):
        if self._i == 1:
            self.result = do_this()
        elif self._i == 2:
            self.result = do_that()

threads = []
nproc = 24 
for i in xrange(nproc):
    #Run program in parallel        
    w = Worker(i)
    threads.append(w)
    w.start()
    w.join()

# ...now all threads are done

#Combine files generated by the parallel step
for i in xrange(nproc):
    handle = open('Niben_%s_structures' % (zfile_name), 'w')
    ...etc...