Leetcode #523: Continuous Subarray Sum

In this guide, we solve Leetcode #523 Continuous Subarray Sum 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

Given an integer array nums and an integer k, return true if nums has a good subarray or false otherwise. A good subarray is a subarray where: its length is at least two, and the sum of the elements of the subarray is a multiple of k.

Quick Facts

Difficulty: Medium
Premium: No
Tags: Array, Hash Table, Math, Prefix Sum

Intuition

Fast membership checks and value lookups are the heart of this problem, which makes a hash map the natural choice.

By storing what we have already seen (or counts/indexes), we can answer the question in one pass without backtracking.

Approach

Scan the input once, using the map to detect when the condition is satisfied and to update state as you go.

This keeps the solution linear while remaining easy to explain in an interview setting.

Steps:

Initialize a hash map for seen items or counts.
Iterate through the input, querying/updating the map.
Return the first valid result or the final computed value.

Example

Input: nums = [23,2,4,6,7], k = 6
Output: true
Explanation: [2, 4] is a continuous subarray of size 2 whose elements sum up to 6.

Python Solution

class Solution:
    def checkSubarraySum(self, nums: List[int], k: int) -> bool:
        d = {0: -1}
        s = 0
        for i, x in enumerate(nums):
            s = (s + x) % k
            if s not in d:
                d[s] = i
            elif i - d[s] > 1:
                return True
        return False

Complexity

The time complexity is $O(n)$ , and the space complexity is $O(n)$ , where $n$ is the length of the array $\textit{nums}$ . The space complexity is $O(n)$ , where $n$ is the length of the array $\textit{nums}$ .

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.

Approach

Scan the input once, using the map to detect when the condition is satisfied and to update state as you go.

This keeps the solution linear while remaining easy to explain in an interview setting.

Steps:

Initialize a hash map for seen items or counts.

Iterate through the input, querying/updating the map.

Return the first valid result or the final computed value.

Python Solution

class Solution:
    def checkSubarraySum(self, nums: List[int], k: int) -> bool:
        d = {0: -1}
        s = 0
        for i, x in enumerate(nums):
            s = (s + x) % k
            if s not in d:
                d[s] = i
            elif i - d[s] > 1:
                return True
        return False

Leetcode #523: Continuous Subarray Sum

Problem Statement

Quick Facts

Intuition

Approach

Example

Python Solution

Complexity

Edge Cases and Pitfalls

Summary

Ace your next coding interview

Leetcode #523: Continuous Subarray Sum

Problem Statement

Quick Facts

Intuition

Approach

Example

Python Solution

Complexity

Edge Cases and Pitfalls

Summary

Ace your next coding interview