Leetcode #2386: Find the K-Sum of an Array
In this guide, we solve Leetcode #2386 Find the K-Sum of an Array 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.
Problem Statement
You are given an integer array nums and a positive integer k. You can choose any subsequence of the array and sum all of its elements together.
Quick Facts
- Difficulty: Hard
- Premium: No
- Tags: Array, Sorting, Heap (Priority Queue)
Intuition
We need to repeatedly access the smallest or largest element as the input changes.
A heap provides fast insertions and removals while keeping order.
Approach
Push candidates into the heap as you scan, and pop when you need the best element.
Keep the heap size bounded if the problem requires a top-k structure.
Steps:
- Push candidates into a heap.
- Pop the best candidate when needed.
- Maintain heap size or invariants.
Example
Input: nums = [2,4,-2], k = 5
Output: 2
Explanation: All the possible subsequence sums that we can obtain are the following sorted in decreasing order:
6, 4, 4, 2, 2, 0, 0, -2.
The 5-Sum of the array is 2.
Python Solution
class Solution:
def kSum(self, nums: List[int], k: int) -> int:
mx = 0
for i, x in enumerate(nums):
if x > 0:
mx += x
else:
nums[i] = -x
nums.sort()
h = [(0, 0)]
for _ in range(k - 1):
s, i = heappop(h)
if i < len(nums):
heappush(h, (s + nums[i], i + 1))
if i:
heappush(h, (s + nums[i] - nums[i - 1], i + 1))
return mx - h[0][0]
Complexity
The time complexity is , where is the length of the array . The space complexity is .
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.