test

def solve_knapsack(profits, weights, capacity):
  # create a two dimensional array for Memoization, each element is initialized to '-1'
  dp = [[-1 for x in range(capacity+1)] for y in range(len(profits))]
  return knapsack_recursive(dp, profits, weights, capacity, 0)


def knapsack_recursive(dp, profits, weights, capacity, currentIndex):

  # base checks
  if capacity <= 0 or currentIndex >= len(profits):
    return 0

  # if we have already solved a similar problem, return the result from memory
  if dp[currentIndex][capacity] != -1:
    return dp[currentIndex][capacity]

  # recursive call after choosing the element at the currentIndex
  # if the weight of the element at currentIndex exceeds the capacity, we
  # shouldn't process this
  profit1 = 0
  if weights[currentIndex] <= capacity:
    profit1 = profits[currentIndex] + knapsack_recursive(
      dp, profits, weights, capacity - weights[currentIndex], currentIndex + 1)

  # recursive call after excluding the element at the currentIndex
  profit2 = knapsack_recursive(
    dp, profits, weights, capacity, currentIndex + 1)

  dp[currentIndex][capacity] = max(profit1, profit2)
  return dp[currentIndex][capacity]


def main():
  print(solve_knapsack([1, 6, 10, 16], [1, 2, 3, 5], 7))
  print(solve_knapsack([1, 6, 10, 16], [1, 2, 3, 5], 6))


main()