Python怎么计算字符串相似度

计算字符串相似度可以使用一些算法，常用的算法包括编辑距离算法（Levenshtein Distance）、Jaccard相似度等。

以下是使用编辑距离算法计算字符串相似度的示例代码：

def levenshtein_distance(s1, s2):     if len(s1) < len(s2):         return levenshtein_distance(s2, s1)      if len(s2) == 0:         return len(s1)      previous_row = range(len(s2) + 1)     for i, c1 in enumerate(s1):         current_row = [i + 1]         for j, c2 in enumerate(s2):             insertions = previous_row[j + 1] + 1             deletions = current_row[j] + 1             substitutions = previous_row[j] + (c1 != c2)             current_row.append(min(insertions, deletions, substitutions))         previous_row = current_row      return previous_row[-1]  def similarity(s1, s2):     max_length = max(len(s1), len(s2))     distance = levenshtein_distance(s1, s2)     similarity = 1 - distance / max_length     return similarity  s1 = "hello" s2 = "hallo" similarity_score = similarity(s1, s2) print(f"The similarity score between '{s1}' and '{s2}' is {similarity_score}") 

这段代码会计算字符串 “hello” 和 “hallo” 之间的相似度，输出结果为：

The similarity score between 'hello' and 'hallo' is 0.8 

你可以根据需要修改代码来计算其他字符串的相似度。