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Leetcode #2587: Rearrange Array to Maximize Prefix Score

In this guide, we solve Leetcode #2587 Rearrange Array to Maximize Prefix Score 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 nums. You can rearrange the elements of nums to any order (including the given order).

Quick Facts

  • Difficulty: Medium
  • Premium: No
  • Tags: Greedy, Array, Prefix Sum, Sorting

Intuition

A locally optimal choice leads to a globally optimal result for this structure.

That means we can commit to decisions as we scan without backtracking.

Approach

Sort or preprocess if needed, then repeatedly take the best available local choice.

Maintain the minimal state necessary to validate the greedy decision.

Steps:

  • Sort or preprocess as needed.
  • Iterate and pick the best local option.
  • Track the current solution.

Example

Input: nums = [2,-1,0,1,-3,3,-3] Output: 6 Explanation: We can rearrange the array into nums = [2,3,1,-1,-3,0,-3]. prefix = [2,5,6,5,2,2,-1], so the score is 6. It can be shown that 6 is the maximum score we can obtain.

Python Solution

class Solution: def maxScore(self, nums: List[int]) -> int: nums.sort(reverse=True) s = 0 for i, x in enumerate(nums): s += x if s <= 0: return i return len(nums)

Complexity

The time complexity is O(n×log⁡n)O(n \times \log n)O(n×logn), and the space complexity is O(log⁡n)O(\log n)O(logn). The space complexity is O(log⁡n)O(\log n)O(logn).

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.


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