Jaccard algorithms for comparing two strings and return similarity score, Port and refactor https://github.com/aceakash/string-similarity to python

compare-strings.py

def ngram_string(string, n=3, remove_space=False):
    if remove_space:
        string = string.replace(' ', '')

    if len(string) < n:
        return {string: 1}

    ngrams = dict()
    for i in range(len(string)-n+1):
        ngram = string[i:i+n]
        ngrams.setdefault(ngram, 0)
        ngrams[ngram] += 1

    return ngrams


def jaccard_ngrams(first, second):
    intersection = 0
    for ngram in first.keys():
        intersection += min(first.get(ngram, 0), second.get(ngram, 0))
    union = sum(first.values()) + sum(second.values())

    return (2.0 * intersection) / union


def compare_two_strings(first, second, remove_space=False):
    first_ngrams = ngram_string(first, remove_space=remove_space)
    second_ngrams = ngram_string(second, remove_space=remove_space)

    return jaccard_ngrams(first_ngrams, second_ngrams)


def find_best_match(main_string, target_strings):
    ratings = [compare_two_strings(main_string, target_string) for target_string in target_strings]
    best_match_index = target_strings.index(max(ratings))

    return target_strings[best_match_index], ratings[best_match_index]