input: Write a function to find the maximum value that can be put in a knapsack using dynamic programming. The function should take the capacity of the knapsack, a list of item values, and a list of item weights, and return the maximum value.
  
  def knapSack(W, wt, val):
      n = len(val)
      dp = [[0 for _ in range(W + 1)] for _ in range(n + 1)]
      
      for i in range(1, n + 1):
          for w in range(1, W + 1):
              if 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]
  
  assert knapSack(50, [10, 20, 30], [60, 100, 120]) == 220
  assert knapSack(10, [5, 4, 6, 3], [10, 40, 30, 50]) == 90
  assert knapSack(2, [1, 1], [2, 1]) == 3
  assert knapSack(0, [10, 20], [60, 100]) == 0
  assert knapSack(100, [], []) == 0
output: def knapSack(W, wt, val):
      n = len(val)
      dp = [[0 for _ in range(W + 1)] for _ in range(n + 1)]
      
      for i in range(1, n + 1):
          for w in range(1, W + 1):
              if 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]