input: Write a function to solve the knapsack problem using dynamic programming, taking the capacity of the knapsack and a list of item values and weights as input, and returning the maximum value that can be obtained.
  assert knapSack(50, [10, 20, 30], [60, 100, 120], 3)==220
  assert knapSack(10, [1, 2, 3], [10, 15, 40], 3)==65
  assert knapSack(7, [2, 3, 4], [10, 15, 18], 3)==33
  assert knapSack(0, [5, 10, 15], [100, 150, 200], 3)==0
  assert knapSack(100, [30, 20, 50], [100, 200, 150], 3)==350
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]