multiprocessing

问题 How do you use the fork() command in such a way that you can spawn 10 processes and have them do a small task concurrently. Concurrent is the operative word, many places that show how to use fork only use one call to fork() in their demos. I thought you would use some kind of for loop but i tried and it seems in my tests that the fork()'s are spawning a new process, doing work, then spawning a new process. So they appear to be running sequentially but how can I fork concurrently and have 10

问题 I'm trying out a code snippet from the standard python documentation to learn how to use the multiprocessing module. The code is pasted at the end of this message. I'm using Python 2.7.1 on Ubuntu 11.04 on a quad core machine (which according to the system monitor gives me eight cores due to hyper threading) Problem: All workload seems to be scheduled to just one core, which gets close to 100% utilization, despite the fact that several processes are started. Occasionally all workload migrates

问题 I am following this book http://doughellmann.com/pages/python-standard-library-by-example.html Along with some online references. I have some algorithm setup for multiprocessing where i have a large array of dictionaries and do some calculation. I use multiprocessing to divide the indexes on which the calculations are done on the dictionary. To make the question more general, I replaced the algorithm with just some array of return values. From finding information online and other SO, I think

问题 I am following this book http://doughellmann.com/pages/python-standard-library-by-example.html Along with some online references. I have some algorithm setup for multiprocessing where i have a large array of dictionaries and do some calculation. I use multiprocessing to divide the indexes on which the calculations are done on the dictionary. To make the question more general, I replaced the algorithm with just some array of return values. From finding information online and other SO, I think

问题 Why in the example below myFunct() is not printing any messages is supposed to when it is ran by 'multiprocessing'? And how to solve it? import multiprocessing as mp poolDict=mp.Manager().dict() def myFunct(arg): print 'myFunct():', arg for i in range(110): for n in range(500000): pass poolDict[arg]=i print 'myFunct(): completed', arg, poolDict from multiprocessing import Pool pool = Pool(processes=2) myArgsList=['arg1','arg2','arg3'] pool.map_async( myFunct, myArgsList) print 'completed' 回答1

问题 I have a Q's for awk processing, i got a file below cat test.txt /home/shhh/ abc.c /home/shhh/2/ def.c gthjrjrdj.c /kernel/sssh sarawtera.c wrawrt.h wearwaerw.h My goal is to make a full path from splitting sentences into /home/jhyoon/abc.c . This is the command I got from someone: cat test.txt | awk '/^\/.*/{path=$0}/^[a-zA-Z]/{printf("%s/%s\n",path,$0);}' It works, but I do not understand well about how do make interpret it step by step. Could you teach me how do I make interpret it? Result

问题 In Python 3 I need to have a Pool of processes in which, asynchronously, apply multiple workers. The problem is that I need to "send" workers to the Pool from a series of separate Python processes . So, all the worker should be executed in the same Pool instance . N.B. The objective is to process a lot of data without use all the computer resources. Having the following multi.py example code: import multiprocessing from time import sleep def worker(x): sleep(5) return x*x if __name__ == "_

问题 In Python 3 I need to have a Pool of processes in which, asynchronously, apply multiple workers. The problem is that I need to "send" workers to the Pool from a series of separate Python processes . So, all the worker should be executed in the same Pool instance . N.B. The objective is to process a lot of data without use all the computer resources. Having the following multi.py example code: import multiprocessing from time import sleep def worker(x): sleep(5) return x*x if __name__ == "_

问题 import multiprocessing from multiprocessing import Pool from source.RUN import* def func(r,grid,pos,h): return r,grid,pos,h p = multiprocessing.Pool() # Creates a pool with as many workers as you have CPU cores results = [] if __name__ == '__main__': for i in pos[-1]<2: results.append(Pool.apply_async(LISTE,(r,grid,pos[i,:],h))) p.close() p.join() for result in results: print('liste', result.get()) I want to create Pool for (LISTE,(r,grid,pos[i,:],h)) process and i is in pos which is variable

问题 I am trying to write a Python model which is capable of doing some processing in a PostgreSQL database using the multi-threading module and peewee. In single core mode the code works, however, when I try to run the code with multiple cores I am running into a SSL error. I would like to post the structure of my model in the hope that somebody can advice how to set of my model in a proper way. Currently, I have chosen to use an object oriented approach in which I make one connection which is