Problem Description

You are given an array prices where prices[i] is the price of a given stock on the i-th` 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.

My Idea

The idea here is to implement the sliding window approach, where our window starts at the lowest possible price to buy and slides to the right, searching for the highest price to sell at.

My solution

# Time Complexity: O(n)
def maxProfit(prices: list[int]) -> int:
    l = 0
    r = l+1
    maxProfit = 0
    while r < len(prices):
        if prices[r] < prices[l]:
            l = r
            r += 1
        else:
            maxProfit = max(maxProfit,prices[r]-prices[l])
            r += 1
    return maxProfit