code: def dist_abs(
          self, src, tar, qval=2, pval=1, normalized=False, alphabet=None
      ):
          
          q_src, q_tar = self._get_qgrams(src, tar, qval)
          diffs = ((q_src - q_tar) + (q_tar - q_src)).values()
  
          normalizer = 1
          if normalized:
              totals = (q_src + q_tar).values()
              if alphabet is not None:
                  # noinspection PyTypeChecker
                  normalizer = (
                      alphabet if isinstance(alphabet, Number) else len(alphabet)
                  )
              elif pval == 0:
                  normalizer = len(totals)
              else:
                  normalizer = sum(_ ** pval for _ in totals) ** (1 / pval)
  
          if len(diffs) == 0:
              return 0.0
          if pval == float('inf'):
              # Chebyshev distance
              return max(diffs) / normalizer
          if pval == 0:
              # This is the l_0 "norm" as developed by David Donoho
              return len(diffs) / normalizer
          return sum(_ ** pval for _ in diffs) ** (1 / pval) / normalizer
docs: Return the Minkowski distance (:math:`L^p`-norm) of two strings.
  
          Parameters
          ----------
          src : str
              Source string (or QGrams/Counter objects) for comparison
          tar : str
              Target string (or QGrams/Counter objects) for comparison
          qval : int
              The length of each q-gram; 0 for non-q-gram version
          pval : int or float
              The :math:`p`-value of the :math:`L^p`-space
          normalized : bool
              Normalizes to [0, 1] if True
          alphabet : collection or int
              The values or size of the alphabet
  
          Returns
          -------
          float
              The Minkowski distance
  
          Examples
          --------
          >>> cmp = Minkowski()
          >>> cmp.dist_abs('cat', 'hat')
          4.0
          >>> cmp.dist_abs('Niall', 'Neil')
          7.0
          >>> cmp.dist_abs('Colin', 'Cuilen')
          9.0
          >>> cmp.dist_abs('ATCG', 'TAGC')
          10.0