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

Question

Jupyter 笔记本

我基本上正在使用多处理模块，我仍在学习多处理的功能。我正在使用 Dusty Phillips 的书，这段代码属于它。

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(不在 jupyter 笔记本上)我看到以下内容

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？

Answer 1

似乎 Jupyter 笔记本中的问题与不同 ide 中的问题是设计功能。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

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笔记本中我写了以下几行

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