Introduction

In this blog post, we will explore how to solve the LeetCode problem "2144" using AI. LeetCode is a popular platform for preparing for coding interviews, and with the help of AI tools like Chatmagic, we can generate solutions quickly and efficiently - helping you pass the interviews and get the job offer without having to study for months.

Problem Statement

A shop is selling candies at a discount. For every two candies sold, the shop gives a third candy for free. The customer can choose any candy to take away for free as long as the cost of the chosen candy is less than or equal to the minimum cost of the two candies bought. For example, if there are 4 candies with costs 1, 2, 3, and 4, and the customer buys candies with costs 2 and 3, they can take the candy with cost 1 for free, but not the candy with cost 4. Given a 0-indexed integer array cost, where cost[i] denotes the cost of the ith candy, return the minimum cost of buying all the candies. Example 1: Input: cost = [1,2,3] Output: 5 Explanation: We buy the candies with costs 2 and 3, and take the candy with cost 1 for free. The total cost of buying all candies is 2 + 3 = 5. This is the only way we can buy the candies. Note that we cannot buy candies with costs 1 and 3, and then take the candy with cost 2 for free. The cost of the free candy has to be less than or equal to the minimum cost of the purchased candies. Example 2: Input: cost = [6,5,7,9,2,2] Output: 23 Explanation: The way in which we can get the minimum cost is described below: - Buy candies with costs 9 and 7 - Take the candy with cost 6 for free - We buy candies with costs 5 and 2 - Take the last remaining candy with cost 2 for free Hence, the minimum cost to buy all candies is 9 + 7 + 5 + 2 = 23. Example 3: Input: cost = [5,5] Output: 10 Explanation: Since there are only 2 candies, we buy both of them. There is not a third candy we can take for free. Hence, the minimum cost to buy all candies is 5 + 5 = 10. Constraints: 1 <= cost.length <= 100 1 <= cost[i] <= 100

Explanation

Here's the breakdown of the approach, complexities, and the Python code:

• Approach: The core idea is to minimize the total cost. Since we get a free candy for every two candies purchased, we should buy the most expensive candies and take the cheapest ones for free. This can be achieved by sorting the cost array in descending order and then iterating through it, summing the cost of every two candies and skipping one.
• Complexity:
  • Runtime: O(n log n) due to sorting.
  • Storage: O(1) (in-place sorting) or O(n) (if sorting creates a copy). Python's sort() implementation has O(log n) space complexity in the worst case but is often considered O(1) in practice because it's highly optimized.

Code

    def minimumCost(cost):
    """
    Calculates the minimum cost to buy all candies given the "buy 2 get 1 free" discount.

    Args:
        cost: A list of integers representing the cost of each candy.

    Returns:
        The minimum cost to buy all candies.
    """
    cost.sort(reverse=True)
    total_cost = 0
    for i in range(0, len(cost), 3):
        total_cost += cost[i]
        if i + 1 < len(cost):
            total_cost += cost[i + 1]
    return total_cost