在Python-3.x中使用最大CPU能力进行多处理

Question

I'm working on human genome which consists of 3.2 billions of characters and i have a list of objects which need to be searched within this data. Something like this:

result_final=[]
objects=['obj1','obj2','obj3',...]

def function(obj):
    result_1=search_in_genome(obj)
    return(result_1)

for item in objects:
    result_2=function(item)
    result_final.append(result_2)

Each object's search within the data takes nearly 30 seconds and i have few thousands of objects. I noticed that while doing this serially just 7% of CPU and 5% of RAM is being used. As i searched, for reducing the computation time i should do parallel computation using queuing , threading or multiprocessing. but they seem complicated for non-experts. could anybody help me how i can code for python to run 10 simultaneous searches and is it possible to make python to use maximum available CPU and RAM for multiprocessing? (I'm using Python33 on windows 7 with 64Gb RAM,COREI7 and 3.5 GH CPU)

Answer 1

You can use the multiprocessing module for this:

from multiprocessing import Pool

objects=['obj1','obj2','obj3',...]

def function(obj):
    result_1=search_in_genome(obj)
    return(result)


if __name__ == "__main__":
    pool = Pool()
    result_final = pool.map(function, objects)

This will allow you to scale the work across all available CPUs on your machine, because processes aren't affected by the GIL. You wouldn't want to run too many more tasks than there are CPUs available. Once you do that, you actually start slowing things down, because then the CPUs have to constantly switch between processes, which has a performance penalty.

Answer 2

Ok I'm not sure of your question, but I would do this (Note that there may be a better solution because I'm not an expert with the Queue Object) :

If you want to multithread your searches :

class myThread (threading.Thread):

    def __init__(self, obj):

        threading.Thread.__init__(self)

        self.result = None

        self.obj = obj

    #Function who is called when you start your Thread
    def run(self)

        #Execute your function here
        self.result = search_in_genome(self.obj)




if __name__ == '__main__':

    result_final=[]
    objects=['obj1','obj2','obj3',...]

    #List of Thread
    listThread = []

    #Count number of potential thread
    allThread = objects.len()
    allThreadDone = 0

    for item in objects:

        #Create one thread
        thread = myThread(item)

        #Launch that Thread
        thread.start()

        #Stock it into the list
        listThread.append(thread)


    while True:

        for thread in listThread:

            #Count number of Thread who are finished
            if thread.result != None:

                #If a Thread is finished, count it
                allThreadDone += 1

        #If all thread are finished, then stop program
        if allThreadDone == allThread:
            break
        #Else initialyse flag to count again
        else:
            allThreadDone = 0

If someone can check and validate this code that would be better. (Sorry for my english btw)