input: Write a function to solve the 0-1 Knapsack problem using dynamic programming. The function should return the maximum value that can be obtained with a given weight capacity. The function should take in the maximum weight capacity, the list of weights, and the list of values for the items.
  assert knapSack(50, [10, 20, 30], [60, 100, 120], 3) == 220
  assert knapSack(10, [5, 4, 6, 3], [10, 40, 30, 50], 4) == 90
  assert knapSack(7, [1, 3, 4, 5], [1, 4, 5, 7], 4) == 9
  assert knapSack(5, [1, 2, 3], [6, 10, 12], 3) == 16
  assert knapSack(0, [10, 20, 30], [60, 100, 120], 3) == 0
output: def knapSack(W, wt, val, n):
      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]