python-multiprocessing

问题 I have a device that needs multiprocessing to handle the CPU bound deserialization & decoding of the incoming data; but the rest of the application is slower IO-limited code, which is excellent for asyncio. However, it seems like there is no good way to combine multiprocessing and asyncio together. I have tried https://github.com/dano/aioprocessing, which uses threaded executors for multiprocessing operations. However, this library does not natively support common asyncio operations; for

问题 I want to create a number of instances of a class based on values in a pandas.DataFrame . This I've got down. import itertools import multiprocessing as mp import pandas as pd class Toy: id_iter = itertools.count(1) def __init__(self, row): self.id = self.id_iter.next() self.type = row['type'] if __name__ == "__main__": table = pd.DataFrame({ 'type': ['a', 'b', 'c'], 'number': [5000, 4000, 30000] }) for index, row in table.iterrows(): [Toy(row) for _ in range(row['number'])] Multiprocessing

问题 I have a pool of workers which perform the same identical task, and I send each a distinct clone of the same data object. Then, I measure the run time separately for each process inside the worker function. With one process, run time is 4 seconds. With 3 processes, the run time for each process goes up to 6 seconds. With more complex tasks, this increase is even more nuanced. There are no other cpu-hogging processes running on my system, and the workers don't use shared memory (as far as I

问题 I have a pool of workers which perform the same identical task, and I send each a distinct clone of the same data object. Then, I measure the run time separately for each process inside the worker function. With one process, run time is 4 seconds. With 3 processes, the run time for each process goes up to 6 seconds. With more complex tasks, this increase is even more nuanced. There are no other cpu-hogging processes running on my system, and the workers don't use shared memory (as far as I

问题 I'm actually finding it hard to believe that I've run into the issue I have, it seems like it would be a big bug in the python multiprocessing module... Anyways the problem I've run into is that whenever I pass a multiprocessing.Queue to a multiprocessing.Pool worker as an argument the pool worker never executes its code. I've been able to reproduce this bug even on a very simple test that is a slightly modified version of example code found in the python docs. Here is the original version of

问题 import subprocess def my_function(x): return x + 100 output = subprocess.Popen(my_function, 1) #I would like to pass the function object and its arguments print output #desired output: 101 I have only found documentation on opening subprocesses using separate scripts. Does anyone know how to pass function objects or even an easy way to pass function code? 回答1: I think you're looking for something more like the multiprocessing module: http://docs.python.org/library/multiprocessing.html#the

问题 import subprocess def my_function(x): return x + 100 output = subprocess.Popen(my_function, 1) #I would like to pass the function object and its arguments print output #desired output: 101 I have only found documentation on opening subprocesses using separate scripts. Does anyone know how to pass function objects or even an easy way to pass function code? 回答1: I think you're looking for something more like the multiprocessing module: http://docs.python.org/library/multiprocessing.html#the

问题 i am using MULTIPROCESSING to find my requirement. And when that runs i am getting a pid(may be parent! i don't know what to call that) then co processes with their own pid and reference id of first process. Now i need to kill all those processes BY ONLY KILLING THE FIRST PROCESS then which will be the best way to do that. THAT ALSO IN PYTHONIC WAY. Scenario is like ps -ef |grep py i am getting 2222 0001 first.py #0001 is os process 4323 2222 second.py 4324 2222 third.cgi 4324 2222 fourth.py

问题 i am using MULTIPROCESSING to find my requirement. And when that runs i am getting a pid(may be parent! i don't know what to call that) then co processes with their own pid and reference id of first process. Now i need to kill all those processes BY ONLY KILLING THE FIRST PROCESS then which will be the best way to do that. THAT ALSO IN PYTHONIC WAY. Scenario is like ps -ef |grep py i am getting 2222 0001 first.py #0001 is os process 4323 2222 second.py 4324 2222 third.cgi 4324 2222 fourth.py

问题 In the example code below, I'd like to recover the return value of the function worker . How can I go about doing this? Where is this value stored? Example Code: import multiprocessing def worker(procnum): '''worker function''' print str(procnum) + ' represent!' return procnum if __name__ == '__main__': jobs = [] for i in range(5): p = multiprocessing.Process(target=worker, args=(i,)) jobs.append(p) p.start() for proc in jobs: proc.join() print jobs Output: 0 represent! 1 represent! 2