original_docstring: 
      Measure the similarity between two strings using Levenshtein distance, which
      gives the minimum number of character insertions, deletions, and substitutions
      needed to change one string into the other.
  
      Args:
          str1
          str2
  
      Returns:
          Similarity between ``str1`` and ``str2`` in the interval [0.0, 1.0],
          where larger values correspond to more similar strings
      
docstring: Measure the similarity between two strings using Levenshtein distance, which
  gives the minimum number of character insertions, deletions, and substitutions
  needed to change one string into the other.
  
  str1
  str2
  
  
docstring_tokens: Measure the similarity between two strings using Levenshtein distance which gives the minimum number of character insertions deletions and substitutions needed to change one string into the other . str1 str2
code: def levenshtein(str1: str, str2: str) -> float:
      """
      Measure the similarity between two strings using Levenshtein distance, which
      gives the minimum number of character insertions, deletions, and substitutions
      needed to change one string into the other.
  
      Args:
          str1
          str2
  
      Returns:
          Similarity between ``str1`` and ``str2`` in the interval [0.0, 1.0],
          where larger values correspond to more similar strings
      """
      distance = _levenshtein(str1, str2)
      max_len = max(len(str1), len(str2))
      try:
          return 1.0 - (distance / max_len)
      except ZeroDivisionError:
          return 0.0
code_tokens: def levenshtein ( str1 : str , str2 : str ) -> float : distance = _levenshtein ( str1 , str2 ) max_len = max ( len ( str1 ) , len ( str2 ) ) try : return 1.0 - ( distance / max_len ) except ZeroDivisionError : return 0.0
short_docstring: Measure the similarity between two strings using Levenshtein distance, which
  gives the minimum number of character insertions, deletions, and substitutions
  needed to change one string into the other.
short_docstring_tokens: Measure the similarity between two strings using Levenshtein distance which gives the minimum number of character insertions deletions and substitutions needed to change one string into the other .
comment: """
      Measure the similarity between two strings using Levenshtein distance, which
      gives the minimum number of character insertions, deletions, and substitutions
      needed to change one string into the other.
  
      Args:
          str1
          str2
  
      Returns:
          Similarity between ``str1`` and ``str2`` in the interval [0.0, 1.0],
          where larger values correspond to more similar strings
      """