Leetcode #2226: Maximum Candies Allocated to K Children

In this guide, we solve Leetcode #2226 Maximum Candies Allocated to K Children in Python and focus on the core idea that makes the solution efficient.

You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.

Leetcode

Problem Statement

You are given a 0-indexed integer array candies. Each element in the array denotes a pile of candies of size candies[i].

Quick Facts

Difficulty: Medium
Premium: No
Tags: Array, Binary Search

Intuition

The problem structure suggests a monotonic decision, which makes binary search a natural fit.

By halving the search space each step, we reach the answer efficiently.

Approach

Search either directly on a sorted array or on the answer space using a check function.

Each check is fast, and the logarithmic search keeps the overall runtime low.

Steps:

Define the search bounds.
Check the mid point condition.
Narrow the bounds until convergence.

Example

Input: candies = [5,8,6], k = 3
Output: 5
Explanation: We can divide candies[1] into 2 piles of size 5 and 3, and candies[2] into 2 piles of size 5 and 1. We now have five piles of candies of sizes 5, 5, 3, 5, and 1. We can allocate the 3 piles of size 5 to 3 children. It can be proven that each child cannot receive more than 5 candies.

Python Solution

class Solution:
    def maximumCandies(self, candies: List[int], k: int) -> int:
        l, r = 0, max(candies)
        while l < r:
            mid = (l + r + 1) >> 1
            if sum(x // mid for x in candies) >= k:
                l = mid
            else:
                r = mid - 1
        return l

Complexity

The time complexity is $O(n \times \log M)$ , where $n$ is the length of the array $\text{candies}$ , and $M$ is the maximum value in the array $\text{candies}$ . The space complexity is $O(1)$ .

Edge Cases and Pitfalls

Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.

Summary

This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.

Example

Input: candies = [5,8,6], k = 3
Output: 5
Explanation: We can divide candies[1] into 2 piles of size 5 and 3, and candies[2] into 2 piles of size 5 and 1. We now have five piles of candies of sizes 5, 5, 3, 5, and 1. We can allocate the 3 piles of size 5 to 3 children. It can be proven that each child cannot receive more than 5 candies.

Python Solution

class Solution:
    def maximumCandies(self, candies: List[int], k: int) -> int:
        l, r = 0, max(candies)
        while l < r:
            mid = (l + r + 1) >> 1
            if sum(x // mid for x in candies) >= k:
                l = mid
            else:
                r = mid - 1
        return l

Leetcode #2226: Maximum Candies Allocated to K Children

Problem Statement

Quick Facts

Intuition

Approach

Example

Python Solution

Complexity

Edge Cases and Pitfalls

Summary

Ace your next coding interview

Leetcode #2226: Maximum Candies Allocated to K Children

Problem Statement

Quick Facts

Intuition

Approach

Example

Python Solution

Complexity

Edge Cases and Pitfalls

Summary

Ace your next coding interview