Jupyter notebook 永远不会使用多处理(Python 3)完成处理

问题描述

我基本上在使用多处理模块，我还在学习多处理的功能.我正在使用 Dusty Phillips 的书，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(不是 jupyter notebook)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不会结束运行?

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，我已将函数编码到名为 defs.py 的文件中

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

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