content: package LeetCode.Easy.BestTimeToBuyAndSellStock_II;
  
  /*
    122. Best Time to Buy and Sell Stock II
  
    Say you have an array prices for which the ith element is the price of a given stock on day i.
  
    Design an algorithm to find the maximum profit. You may complete as many transactions as you like (i.e., buy one and sell one share of the stock multiple times).
  
    Note: You may not engage in multiple transactions at the same time (i.e., you must sell the stock before you buy again).
  
    Example 1:
    Input: [7,1,5,3,6,4]
    Output: 7
    Explanation: Buy on day 2 (price = 1) and sell on day 3 (price = 5), profit = 5-1 = 4.
    Then buy on day 4 (price = 3) and sell on day 5 (price = 6), profit = 6-3 = 3.
  
    Example 2:
    Input: [1,2,3,4,5]
    Output: 4
    Explanation: Buy on day 1 (price = 1) and sell on day 5 (price = 5), profit = 5-1 = 4.
    Note that you cannot buy on day 1, buy on day 2 and sell them later, as you are
    engaging multiple transactions at the same time. You must sell before buying again.
  
    Example 3:
    Input: [7,6,4,3,1]
    Output: 0
    Explanation: In this case, no transaction is done, i.e. max profit = 0.
  
  
    Constraints:
    1 <= prices.length <= 3 * 10 ^ 4
    0 <= prices[i] <= 10 ^ 4
  */
  
  public class Solution {
    public int maxProfit(int[] prices) {
      int profit = 0;
  
      for (int i = 0; i < prices.length - 1; ++i)
        // If the selling price is greater
        // than cost price, keep on adding
        // the profit
        if (prices[i] < prices[i + 1]) profit += prices[i + 1] - prices[i];
  
      return profit;
    }
  
    public static void main(String[] args) {
      Solution solution = new Solution();
  
      // should be 7
      System.out.println(solution.maxProfit(new int[] {7, 1, 5, 3, 6, 4}));
  
      // should be 4
      System.out.println(solution.maxProfit(new int[] {1, 2, 3, 4, 5}));
  
      // should be 0
      System.out.println(solution.maxProfit(new int[] {7, 6, 4, 3, 1}));
    }
  }
  