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Leetcode #15: 3Sum

In this guide, we solve Leetcode #15 3Sum 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, return all the triplets [nums[i], nums[j], nums[k]] such that i != j, i != k, and j != k, and nums[i] + nums[j] + nums[k] == 0. Notice that the solution set must not contain duplicate triplets.

Quick Facts

  • Difficulty: Medium
  • Premium: No
  • Tags: Array, Two Pointers, Sorting

Intuition

The constraints hint that we can reason about two ends of the data at once, which is perfect for a two-pointer scan.

Moving one pointer at a time keeps the invariant intact and avoids nested loops.

Approach

Place pointers at the left and right ends and move them based on the comparison or target condition.

This yields a clean linear pass after any required sorting.

Steps:

  • Set left and right pointers.
  • Move a pointer based on the condition.
  • Update the best answer while scanning.

Example

Input: nums = [-1,0,1,2,-1,-4] Output: [[-1,-1,2],[-1,0,1]] Explanation: nums[0] + nums[1] + nums[2] = (-1) + 0 + 1 = 0. nums[1] + nums[2] + nums[4] = 0 + 1 + (-1) = 0. nums[0] + nums[3] + nums[4] = (-1) + 2 + (-1) = 0. The distinct triplets are [-1,0,1] and [-1,-1,2]. Notice that the order of the output and the order of the triplets does not matter.

Python Solution

class Solution: def threeSum(self, nums: List[int]) -> List[List[int]]: nums.sort() n = len(nums) ans = [] for i in range(n - 2): if nums[i] > 0: break if i and nums[i] == nums[i - 1]: continue j, k = i + 1, n - 1 while j < k: x = nums[i] + nums[j] + nums[k] if x < 0: j += 1 elif x > 0: k -= 1 else: ans.append([nums[i], nums[j], nums[k]]) j, k = j + 1, k - 1 while j < k and nums[j] == nums[j - 1]: j += 1 while j < k and nums[k] == nums[k + 1]: k -= 1 return ans

Complexity

The time complexity is O(n2)O(n^2)O(n2), 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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