Leetcode #2432: The Employee That Worked on the Longest Task
In this guide, we solve Leetcode #2432 The Employee That Worked on the Longest Task 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
There are n employees, each with a unique id from 0 to n - 1. You are given a 2D integer array logs where logs[i] = [idi, leaveTimei] where: idi is the id of the employee that worked on the ith task, and leaveTimei is the time at which the employee finished the ith task.
Quick Facts
- Difficulty: Easy
- Premium: No
- Tags: Array
Intuition
The constraints allow a direct scan that keeps only the essential state.
By translating the requirements into a clean loop, the logic stays easy to reason about.
Approach
Iterate through the data once, updating the state needed to compute the answer.
Return the final state after the traversal is complete.
Steps:
- Parse the input.
- Iterate and update state.
- Return the computed answer.
Example
Input: n = 10, logs = [[0,3],[2,5],[0,9],[1,15]]
Output: 1
Explanation:
Task 0 started at 0 and ended at 3 with 3 units of times.
Task 1 started at 3 and ended at 5 with 2 units of times.
Task 2 started at 5 and ended at 9 with 4 units of times.
Task 3 started at 9 and ended at 15 with 6 units of times.
The task with the longest time is task 3 and the employee with id 1 is the one that worked on it, so we return 1.
Python Solution
class Solution:
def hardestWorker(self, n: int, logs: List[List[int]]) -> int:
last = mx = ans = 0
for uid, t in logs:
t -= last
if mx < t or (mx == t and ans > uid):
ans, mx = uid, t
last += t
return ans
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.