Question

我正在使用一个花费太多时间来完成的函数，因为它需要大量输入并使用两个嵌套for循环。

功能代码：

def transform(self, X):
        global brands
        result=[]
        for x in X:
            index=0
            count=0
            for brand in brands:
                all_matches= re.findall(re.escape(brand), x,flags=re.I)
                count_all_match=len(all_matches)
                if(count_all_match>count):
                    count=count_all_match
                    index=brands.index(brand)

            result.append([index])
        return np.array(result)

那么如何更改此函数的代码以便它使用多处理来优化运行时间？

Answer 1

我没有在方法self中看到使用transform。所以我做了一个共同的功能。

import re
import numpy as np

from concurrent.futures import ProcessPoolExecutor

def transformer(x):

    global brands

    index = 0
    count = 0

    for brand in brands:

        all_matches = re.findall(re.escape(brand), x, flags=re.I)

        count_all_match = len(all_matches)

        if count_all_match > count:

            count = count_all_match

            index = brands.index(brand)

    return [index]

def transform(X):

    with ProcessPoolExecutor() as executor:
        result = executor.map(transformer, X)

    return np.array(list(result))

使用多处理在python中实现一个函数

1 个答案: