code: def dist_levenshtein(src, tar, mode='lev', cost=(1, 1, 1, 1)):
      
      return Levenshtein().dist(src, tar, mode, cost)
docs: Return the normalized Levenshtein distance between two strings.
  
      This is a wrapper of :py:meth:`Levenshtein.dist`.
  
      Parameters
      ----------
      src : str
          Source string for comparison
      tar : str
          Target string for comparison
      mode : str
          Specifies a mode for computing the Levenshtein distance:
  
              - ``lev`` (default) computes the ordinary Levenshtein distance, in
                which edits may include inserts, deletes, and substitutions
              - ``osa`` computes the Optimal String Alignment distance, in which
                edits may include inserts, deletes, substitutions, and
                transpositions but substrings may only be edited once
  
      cost : tuple
          A 4-tuple representing the cost of the four possible edits: inserts,
          deletes, substitutions, and transpositions, respectively (by default:
          (1, 1, 1, 1))
  
      Returns
      -------
      float
          The Levenshtein distance between src & tar
  
      Examples
      --------
      >>> round(dist_levenshtein('cat', 'hat'), 12)
      0.333333333333
      >>> round(dist_levenshtein('Niall', 'Neil'), 12)
      0.6
      >>> dist_levenshtein('aluminum', 'Catalan')
      0.875
      >>> dist_levenshtein('ATCG', 'TAGC')
      0.75