input: 
  from typing import List, Tuple
  
  def knapSack(W: int, wt: List[int], val: List[int], n: int) -> int:
      """
      Find the maximum value that can be put in a knapsack of capacity W using dynamic programming.
      
      >>> knapSack(50, [10, 20, 30], [60, 100, 120], 3)
      220
      """
      
      # Base Case 
      if n == 0 or W == 0 : 
          return 0
      
      # If weight of the nth item is more 
      # than Knapsack capacity W, then 
      # this item cannot be included in the optimal solution 
      if (wt[n-1] > W): 
          return knapSack(W, wt, val, n-1) 
      
      # return the maximum of two cases: 
      # (1) nth item included 
      # (2) not included 
      else: 
          return max(val[n-1] + knapSack(W-wt[n-1], wt, val, n-1), 
                      knapSack(W, wt, val, n-1)) 
      
  # end of function knapSack
  
output:     
      dp = [[0 for x in range(W + 1)] for x in range(n + 1)]
      
      # Build table dp[][] in bottom up manner 
      for i in range(n + 1): 
          for w in range(W + 1): 
              if i == 0 or w == 0: 
                  dp[i][w] = 0
              elif wt[i-1] <= w: 
                  dp[i][w] = max(val[i-1] + dp[i-1][w-wt[i-1]],  dp[i-1][w]) 
              else: 
                  dp[i][w] = dp[i-1][w] 
      
      return dp[n][W]
  