Best Time to Buy and Sell Stock

Problem

You are given an array prices where prices[i] is the price of a given stock on the ith day.

You want to maximize your profit by choosing a single day to buy one stock and choosing a different day in the future to sell that stock.

Return the maximum profit you can achieve from this transaction. If you cannot achieve any profit, return 0.

Example 1:

Input: prices = [7,1,5,3,6,4]
Output: 5
Explanation: Buy on day 2 (price = 1) and sell on day 5 (price = 6), profit = 6-1 = 5.
Note that buying on day 2 and selling on day 1 is not allowed because you must buy before you sell.

Example 2:

Input: prices = [7,6,4,3,1]
Output: 0
Explanation: In this case, no transactions are done and the max profit = 0.

Constraints:

  • 1 <= prices.length <= 105
  • 0 <= prices[i] <= 104

Solution

I’m not really sure how this one is considered dynamic programming.

Anyway.

Keep track of the minimum price we’ve seen and the most profit we could have. Go through the array and check if we see a lower price. Update max profit as applicable.

class Solution {
    public int maxProfit(int[] prices) {
        var minPrice = prices[0];
        var maxProfit = 0;

        for (var i : prices) {
            minPrice = Math.min(i, minPrice);
            maxProfit = Math.max(i - minPrice, maxProfit);
        }

        return maxProfit;
    }
}

Recent posts from blogs that I like

Automatically detecting AI text in my browser

Automated AI text detection is currently an underserved niche. The only game in town is Pangram, which does an excellent job but desperately needs more competition. In a few years, I would be surprised if every major social network doesn’t scan new posts1 and comments for AI content in order to tag ...

via Sean Goedecke

Logistician version 1.5 fixes a crashing bug

Version 1.4 can crash when trying to display a Chart view for Signpost or HighVolume log files with less than 6 processes. This update fixes that.

via The Eclectic Light Company

The Pelican comparison grid for Astra is pretty interesting

via Simon Willison