input: from typing import List, Tuple
  
  def knapSack(W: int, wt: List[int], val: List[int], n: int) -> int:
      """ Finds the maximum value that can be put in a knapsack of capacity W, given a list of items
      with their respective values and weights.
      >>> 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))
output:     
      # Using dynamic programming to optimize the solution
      dp = [[0 for _ in range(W + 1)] for _ in range(n + 1)]
      
      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]
  