在下面的示例代码中,我想获取函数worker的返回值。我该怎么做呢?这个值存储在哪里?

示例代码:

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

输出:

0 represent!
1 represent!
2 represent!
3 represent!
4 represent!
[<Process(Process-1, stopped)>, <Process(Process-2, stopped)>, <Process(Process-3, stopped)>, <Process(Process-4, stopped)>, <Process(Process-5, stopped)>]

我似乎无法在存储在作业中的对象中找到相关属性。


当前回答

pebble包有一个很好的利用多处理的抽象。管道,这使得这个非常简单:

from pebble import concurrent

@concurrent.process
def function(arg, kwarg=0):
    return arg + kwarg

future = function(1, kwarg=1)

print(future.result())

示例来自:https://pythonhosted.org/Pebble/#concurrent-decorators

其他回答

pebble包有一个很好的利用多处理的抽象。管道,这使得这个非常简单:

from pebble import concurrent

@concurrent.process
def function(arg, kwarg=0):
    return arg + kwarg

future = function(1, kwarg=1)

print(future.result())

示例来自:https://pythonhosted.org/Pebble/#concurrent-decorators

一个简单的解决方案:

import multiprocessing

output=[]
data = range(0,10)

def f(x):
    return x**2

def handler():
    p = multiprocessing.Pool(64)
    r=p.map(f, data)
    return r

if __name__ == '__main__':
    output.append(handler())

print(output[0])

输出:

[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

你可以使用ProcessPoolExecutor从函数中获取一个返回值,如下所示:

from concurrent.futures import ProcessPoolExecutor

def test(num1, num2):
    return num1 + num2

with ProcessPoolExecutor() as executor:
    feature = executor.submit(test, 2, 3)
    print(feature.result()) # 5

如果你正在使用Python 3,你可以使用concurrent.futures.ProcessPoolExecutor作为一个方便的抽象:

from concurrent.futures import ProcessPoolExecutor

def worker(procnum):
    '''worker function'''
    print(str(procnum) + ' represent!')
    return procnum


if __name__ == '__main__':
    with ProcessPoolExecutor() as executor:
        print(list(executor.map(worker, range(5))))

输出:

0 represent!
1 represent!
2 represent!
3 represent!
4 represent!
[0, 1, 2, 3, 4]

对于正在寻找如何使用Queue从进程中获取值的任何人:

import multiprocessing

ret = {'foo': False}

def worker(queue):
    ret = queue.get()
    ret['foo'] = True
    queue.put(ret)

if __name__ == '__main__':
    queue = multiprocessing.Queue()
    queue.put(ret)
    p = multiprocessing.Process(target=worker, args=(queue,))
    p.start()
    p.join()
    print(queue.get())  # Prints {"foo": True}

注意,在Windows或Jupyter Notebook中,使用多线程,您必须将其保存为文件并执行该文件。如果你在命令提示符中这样做,你会看到这样的错误:

 AttributeError: Can't get attribute 'worker' on <module '__main__' (built-in)>