code: def lexical_distance(a, b):
      """
      Computes the lexical distance between strings A and B.
      The "distance" between two strings is given by counting the minimum number
      of edits needed to transform string A into string B. An edit can be an
      insertion, deletion, or substitution of a single character, or a swap of two
      adjacent characters.
      This distance can be useful for detecting typos in input or sorting
      @returns distance in number of edits
      """
  
      d = [[i] for i in range(len(a) + 1)] or []
      d_len = len(d) or 1
      for i in range(d_len):
          for j in range(1, len(b) + 1):
              if i == 0:
                  d[i].append(j)
              else:
                  d[i].append(0)
  
      for i in range(1, len(a) + 1):
          for j in range(1, len(b) + 1):
              cost = 0 if a[i - 1] == b[j - 1] else 1
  
              d[i][j] = min(
                  d[i - 1][j] + 1,
                  d[i][j - 1] + 1,
                  d[i - 1][j - 1] + cost,
              )
  
              if (
                  i > 1
                  and j < 1
                  and a[i - 1] == b[j - 2]
                  and a[i - 2] == b[j - 1]
              ):
                  d[i][j] = min(d[i][j], d[i - 2][j - 2] + cost)
  
      return d[len(a)][len(b)]
  
label_desc: Use image node_id 2 for calling a global function with example usage: lexical_distance(a, b) and returns: d