input: Write a function to calculate the maximum possible revenue from the items with given weights and values using the knapsack problem approach. The function should accept a list of weights and a corresponding list of values, and it should return the maximum possible revenue given a specific capacity of the knapsack. If the weights or values lists are empty, the function should return 0.
  
  def knapsack(weights, values, W):
      n = len(weights)
      if n == 0 or len(values) != n:
          return 0
      
      K = [[0 for x in range(W+1)] for x in range(n+1)]
      
      for i in range(n+1):
          for w in range(W+1):
              if i==0 or w==0:
                  K[i][w] = 0
              elif weights[i-1] <= w:
                  K[i][w] = max(values[i-1] + K[i-1][w-weights[i-1]],  K[i-1][w])
              else:
                  K[i][w] = K[i-1][w]
      
      return K[n][W]
  
  assert knapsack([2, 1, 3], [4, 2, 3], 5) == 7
  assert knapsack([2, 3, 4], [3, 4, 5], 5) == 7
  assert knapsack([1, 2, 3], [6, 10, 12], 3) == 22
  assert knapsack([], [], 5) == 0
  assert knapsack([1, 3, 4], [1, 2, 6], 8) == 9
  
output: def knapsack(weights, values, W):
      n = len(weights)
      if n == 0 or len(values) != n:
          return 0
      
      K = [[0 for x in range(W+1)] for x in range(n+1)]
      
      for i in range(n+1):
          for w in range(W+1):
              if i==0 or w==0:
                  K[i][w] = 0
              elif weights[i-1] <= w:
                  K[i][w] = max(values[i-1] + K[i-1][w-weights[i-1]],  K[i-1][w])
              else:
                  K[i][w] = K[i-1][w]
      
      return K[n][W]