code: def sim(self, src, tar, threshold=0.25, max_mismatches=2):
          
          if tar == src:
              return 1.0
          if not src or not tar:
              return 0.0
  
          mismatches = 0
          ham = Hamming().dist_abs(src, tar, diff_lens=True)
          max_length = max(len(src), len(tar))
          while src and tar and mismatches <= max_mismatches:
              if (
                  max_length < 1
                  or (1 - (max_length - ham) / max_length) <= threshold
              ):
                  return 1.0
              else:
                  mismatches += 1
                  ham -= 1
                  max_length -= 1
  
          if max_length < 1:
              return 1.0
          return 0.0
docs: Return the MLIPNS similarity of two strings.
  
          Parameters
          ----------
          src : str
              Source string for comparison
          tar : str
              Target string for comparison
          threshold : float
              A number [0, 1] indicating the maximum similarity score, below
              which the strings are considered 'similar' (0.25 by default)
          max_mismatches : int
              A number indicating the allowable number of mismatches to remove
              before declaring two strings not similar (2 by default)
  
          Returns
          -------
          float
              MLIPNS similarity
  
          Examples
          --------
          >>> sim_mlipns('cat', 'hat')
          1.0
          >>> sim_mlipns('Niall', 'Neil')
          0.0
          >>> sim_mlipns('aluminum', 'Catalan')
          0.0
          >>> sim_mlipns('ATCG', 'TAGC')
          0.0