在Python中,我见过许多调用多处理的例子,但目标只是打印一些东西。我有一个场景,目标返回2个变量,我稍后需要用到它们。例如:
def foo(some args):
a = someObject
b = someObject
return a,b
p1=multiprocess(target=foo,args(some args))
p2=multiprocess(target=foo,args(some args))
p3=multiprocess(target=foo,args(some args))
这次又是什么?我可以执行.start和.join,但是如何检索各个结果呢?我需要捕获我执行的所有作业的返回值a,b,然后处理它。
发布于 2012-05-29 19:15:28
是的,当然--你可以使用很多方法。最简单的方法之一是共享Queue
。请看这里的示例:http://eli.thegreenplace.net/2012/01/16/python-parallelizing-cpu-bound-tasks-with-multiprocessing/
发布于 2012-05-29 19:19:42
我直接从文档中复制这个例子,因为我不能给你一个直接的链接。请注意,它会打印出done_queue的结果,但您可以使用它做任何您喜欢的事情。
#
# Simple example which uses a pool of workers to carry out some tasks.
#
# Notice that the results will probably not come out of the output
# queue in the same in the same order as the corresponding tasks were
# put on the input queue. If it is important to get the results back
# in the original order then consider using `Pool.map()` or
# `Pool.imap()` (which will save on the amount of code needed anyway).
#
# Copyright (c) 2006-2008, R Oudkerk
# All rights reserved.
#
import time
import random
from multiprocessing import Process, Queue, current_process, freeze_support
#
# Function run by worker processes
#
def worker(input, output):
for func, args in iter(input.get, 'STOP'):
result = calculate(func, args)
output.put(result)
#
# Function used to calculate result
#
def calculate(func, args):
result = func(*args)
return '%s says that %s%s = %s' % \
(current_process().name, func.__name__, args, result)
#
# Functions referenced by tasks
#
def mul(a, b):
time.sleep(0.5*random.random())
return a * b
def plus(a, b):
time.sleep(0.5*random.random())
return a + b
#
#
#
def test():
NUMBER_OF_PROCESSES = 4
TASKS1 = [(mul, (i, 7)) for i in range(20)]
TASKS2 = [(plus, (i, 8)) for i in range(10)]
# Create queues
task_queue = Queue()
done_queue = Queue()
# Submit tasks
for task in TASKS1:
task_queue.put(task)
# Start worker processes
for i in range(NUMBER_OF_PROCESSES):
Process(target=worker, args=(task_queue, done_queue)).start()
# Get and print results
print 'Unordered results:'
for i in range(len(TASKS1)):
print '\t', done_queue.get()
# Add more tasks using `put()`
for task in TASKS2:
task_queue.put(task)
# Get and print some more results
for i in range(len(TASKS2)):
print '\t', done_queue.get()
# Tell child processes to stop
for i in range(NUMBER_OF_PROCESSES):
task_queue.put('STOP')
if __name__ == '__main__':
freeze_support()
test()
发布于 2012-05-29 19:40:37
它不会在windows上工作,但这是我的多进程函数装饰器,它返回一个队列,您可以从队列中轮询和收集返回的数据
import os
from Queue import Queue
from multiprocessing import Process
def returning_wrapper(func, *args, **kwargs):
queue = kwargs.get("multiprocess_returnable")
del kwargs["multiprocess_returnable"]
queue.put(func(*args, **kwargs))
class Multiprocess(object):
"""Cute decorator to run a function in multiple processes."""
def __init__(self, func):
self.func = func
self.processes = []
def __call__(self, *args, **kwargs):
num_processes = kwargs.get("multiprocess_num_processes", 2) # default to two processes.
return_obj = kwargs.get("multiprocess_returnable", Queue()) # default to stdlib Queue
kwargs["multiprocess_returnable"] = return_obj
for i in xrange(num_processes):
pro = Process(target=returning_wrapper, args=tuple([self.func] + list(args)), kwargs=kwargs)
self.processes.append(pro)
pro.start()
return return_obj
@Multiprocess
def info():
print 'module name:', __name__
print 'parent process:', os.getppid()
print 'process id:', os.getpid()
return 4 * 22
data = info()
print data.get(False)
https://stackoverflow.com/questions/10797998
复制相似问题