Leetcode #2054: Two Best Non-Overlapping Events
In this guide, we solve Leetcode #2054 Two Best Non-Overlapping Events 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 a 0-indexed 2D integer array of events where events[i] = [startTimei, endTimei, valuei]. The ith event starts at startTimei and ends at endTimei, and if you attend this event, you will receive a value of valuei.
Quick Facts
- Difficulty: Medium
- Premium: No
- Tags: Array, Binary Search, Dynamic Programming, Sorting, Heap (Priority Queue)
Intuition
The problem structure suggests a monotonic decision, which makes binary search a natural fit.
By halving the search space each step, we reach the answer efficiently.
Approach
Search either directly on a sorted array or on the answer space using a check function.
Each check is fast, and the logarithmic search keeps the overall runtime low.
Steps:
- Define the search bounds.
- Check the mid point condition.
- Narrow the bounds until convergence.
Example
Input: events = [[1,3,2],[4,5,2],[2,4,3]]
Output: 4
Explanation: Choose the green events, 0 and 1 for a sum of 2 + 2 = 4.
Python Solution
class Solution:
def maxTwoEvents(self, events: List[List[int]]) -> int:
events.sort()
n = len(events)
f = [events[-1][2]] * n
for i in range(n - 2, -1, -1):
f[i] = max(f[i + 1], events[i][2])
ans = 0
for _, e, v in events:
idx = bisect_right(events, e, key=lambda x: x[0])
if idx < n:
v += f[idx]
ans = max(ans, v)
return ans
Complexity
The time complexity is , and the space complexity is . 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.