Jupyter 笔记本永远不会使用多处理(Python 3)完成处理 [英] Jupyter notebook never finishes processing using multiprocessing (Python 3)

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本文介绍了Jupyter 笔记本永远不会使用多处理(Python 3)完成处理的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我基本上在使用多处理模块,我仍在学习多处理的功能.我正在使用 Dusty Phillips 的这本书,这段代码属于它.

I am using multiprocessing module basically, I am still learning the capabilities of multiprocessing. I am using the book by Dusty Phillips and this code belongs to it.

import multiprocessing  
import random
from multiprocessing.pool import Pool

def prime_factor(value):
    factors = []
    for divisor in range(2, value-1):
        quotient, remainder = divmod(value, divisor)
        if not remainder:
            factors.extend(prime_factor(divisor))
            factors.extend(prime_factor(quotient))
            break
        else:
            factors = [value]
    return factors

if __name__ == '__main__':
    pool = Pool()
    to_factor = [ random.randint(100000, 50000000) for i in range(20)]
    results = pool.map(prime_factor, to_factor)
    for value, factors in zip(to_factor, results):
        print("The factors of {} are {}".format(value, factors))

在 Windows PowerShell 上(不是在 jupyter 笔记本上)我看到以下内容

On the Windows PowerShell (not on jupyter notebook) I see the following

Process SpawnPoolWorker-5:
Process SpawnPoolWorker-1:
AttributeError: Can't get attribute 'prime_factor' on <module '__main__' (built-in)>

我不知道为什么单元格永远运行不完?

I do not know why the cell never ends running?

推荐答案

看来 Jupyter notebook 和不同 ide 的问题是设计特性.因此,我们必须将函数 (prime_factor) 写入不同的文件并导入模块.此外,我们必须注意调整.例如,就我而言,我已将函数编码到一个名为 defs.py

It seems that the problem in Jupyter notebook as in different ide is the design feature. Therefore, we have to write the function (prime_factor) into a different file and import the module. Furthermore, we have to take care of the adjustments. For example, in my case, I have coded the function into a file known as defs.py

def prime_factor(value):
    factors = []
    for divisor in range(2, value-1):
        quotient, remainder = divmod(value, divisor)
        if not remainder:
            factors.extend(prime_factor(divisor))
            factors.extend(prime_factor(quotient))
            break
        else:
            factors = [value]
    return factors

然后在 jupyter notebook 中我写了以下几行

Then in the jupyter notebook I wrote the following lines

import multiprocessing  
import random
from multiprocessing import Pool
import defs



if __name__ == '__main__':
    pool = Pool()
    to_factor = [ random.randint(100000, 50000000) for i in range(20)]
    results = pool.map(defs.prime_factor, to_factor)
    for value, factors in zip(to_factor, results):
        print("The factors of {} are {}".format(value, factors))

这解决了我的问题

这篇关于Jupyter 笔记本永远不会使用多处理(Python 3)完成处理的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

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