Leetcode #442: Find All Duplicates in an Array
In this guide, we solve Leetcode #442 Find All Duplicates in 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
Given an integer array nums of length n where all the integers of nums are in the range [1, n] and each integer appears at most twice, return an array of all the integers that appears twice. You must write an algorithm that runs in O(n) time and uses only constant auxiliary space, excluding the space needed to store the output Example 1: Input: nums = [4,3,2,7,8,2,3,1] Output: [2,3] Example 2: Input: nums = [1,1,2] Output: [1] Example 3: Input: nums = [1] Output: [] Constraints: n == nums.length 1 <= n <= 105 1 <= nums[i] <= n Each element in nums appears once or twice.
Quick Facts
- Difficulty: Medium
- Premium: No
- Tags: Array, Hash Table, Sorting
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 = [4,3,2,7,8,2,3,1]
Output: [2,3]
Python Solution
class Solution:
def findDuplicates(self, nums: List[int]) -> List[int]:
for i in range(len(nums)):
while nums[i] != nums[nums[i] - 1]:
nums[nums[i] - 1], nums[i] = nums[i], nums[nums[i] - 1]
return [v for i, v in enumerate(nums) if v != i + 1]
Complexity
The time complexity is O(n). The space complexity is O(n).
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.