comefrom: <qiyuangong>072_Edit_Distance_1.py
code: def minDistance( word1, word2):
      ls_1, ls_2 = len(word1), len(word2)
      dp = [[0] * (ls_2 + 1) for _ in range(ls_1 + 1)]
      for i in range(1, ls_1 + 1):
          dp[i][0] = i
      for j in range(1, ls_2 + 1):
          dp[0][j] = j
      for i in range(1, ls_1 + 1):
          for j in range(1, ls_2 + 1):
              if word1[i - 1] == word2[j - 1]:
                  dp[i][j] = dp[i - 1][j - 1]
              else:
                  dp[i][j] = min(dp[i - 1][j - 1] + 1,
                                 dp[i][j - 1] + 1,
                                 dp[i - 1][j] + 1)
      return dp[ls_1][ls_2]
masked: def sample_funcname ( var_0 , var_1 ) :
      var_3 , var_4 = len ( var_0 ) , len ( var_1 )
      var_9 = [ [ 0 ] * ( var_4 + 1 ) for var_7 in range ( var_3 + 1 ) ]
      for var_10 in range ( 1 , var_3 + 1 ) :
          var_9 [ var_10 ] [ 0 ] = var_10
      for var_11 in range ( 1 , var_4 + 1 ) :
          var_9 [ 0 ] [ var_11 ] = var_11
      for var_10 in range ( 1 , var_3 + 1 ) :
          for var_11 in range ( 1 , var_4 + 1 ) :
              if var_0 [ var_10 - 1 ] == var_1 [ var_11 - 1 ] :
                  var_9 [ var_10 ] [ var_11 ] = var_9 [ var_10 - 1 ] [ var_11 - 1 ]
              else :
                  var_9 [ var_10 ] [ var_11 ] = min ( var_9 [ var_10 - 1 ] [ var_11 - 1 ] + 1 , var_9 [ var_10 ] [ var_11 - 1 ] + 1 , var_9 [ var_10 - 1 ] [ var_11 ] + 1 )
      return var_9 [ var_3 ] [ var_4 ]
  