如何根据词汇表列表拆分字符串？

Question

给定词汇表列表：

glossaries = ['USA', '34']

目标是使用词汇表中的项目并使用词汇表作为分隔符拆分字符串。例如。给定字符串和词汇表，_isolate_glossaries() 函数：

glossaries = ['USA', '34']
word = '1934USABUSA'
_isolate_glossaries(word, glossaries)

应该输出：

['19', '34', 'USA', 'B', 'USA']

我试过：

def isolate_glossary(word, glossary):
    print(word, glossary)
    # Check that word == glossary and glossary not in word
    if re.match('^{}$'.format(glossary), word) or not re.search(glossary, word):
        return [word]
    else:
        segments = re.split(r'({})'.format(glossary), word)
        segments, ending = segments[:-1], segments[-1] # Remove the last catch with null string.
        return segments

def _isolate_glossaries(word, glossaries):
    word_segments = [word]
    for gloss in glossaries:
        word_segments = [out_segment
                         for segment in word_segments 
                         for out_segment in isolate_glossary(segment, gloss)] 
    return word_segments

它可以工作，但看起来有点太复杂了，无法进行如此多级别的循环和正则表达式拆分。 有没有更好的方法根据词汇表拆分字符串？

Answer 1

要按列表中的项目拆分字符串，动态创建一个正则表达式，包括用竖线分隔的那些项目 | 所有包含在捕获组中（非捕获组不包括项目本身在输出中）：

list = re.split('({})'.format('|'.join(glossaries)), word);
print ([x for x in list if x]) # filter non-word items

见live demo here

如何根据词汇表列表拆分字符串？

How to split strings based on a list of glossaries?

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split

nlp

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