Leetcode #1845: Seat Reservation Manager
In this guide, we solve Leetcode #1845 Seat Reservation Manager 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
Design a system that manages the reservation state of n seats that are numbered from 1 to n. Implement the SeatManager class: SeatManager(int n) Initializes a SeatManager object that will manage n seats numbered from 1 to n.
Quick Facts
- Difficulty: Medium
- Premium: No
- Tags: Design, Heap (Priority Queue)
Intuition
We need to repeatedly access the smallest or largest element as the input changes.
A heap provides fast insertions and removals while keeping order.
Approach
Push candidates into the heap as you scan, and pop when you need the best element.
Keep the heap size bounded if the problem requires a top-k structure.
Steps:
- Push candidates into a heap.
- Pop the best candidate when needed.
- Maintain heap size or invariants.
Example
Input
["SeatManager", "reserve", "reserve", "unreserve", "reserve", "reserve", "reserve", "reserve", "unreserve"]
[[5], [], [], [2], [], [], [], [], [5]]
Output
[null, 1, 2, null, 2, 3, 4, 5, null]
Explanation
SeatManager seatManager = new SeatManager(5); // Initializes a SeatManager with 5 seats.
seatManager.reserve(); // All seats are available, so return the lowest numbered seat, which is 1.
seatManager.reserve(); // The available seats are [2,3,4,5], so return the lowest of them, which is 2.
seatManager.unreserve(2); // Unreserve seat 2, so now the available seats are [2,3,4,5].
seatManager.reserve(); // The available seats are [2,3,4,5], so return the lowest of them, which is 2.
seatManager.reserve(); // The available seats are [3,4,5], so return the lowest of them, which is 3.
seatManager.reserve(); // The available seats are [4,5], so return the lowest of them, which is 4.
seatManager.reserve(); // The only available seat is seat 5, so return 5.
seatManager.unreserve(5); // Unreserve seat 5, so now the available seats are [5].
Python Solution
class SeatManager:
def __init__(self, n: int):
self.q = list(range(1, n + 1))
def reserve(self) -> int:
return heappop(self.q)
def unreserve(self, seatNumber: int) -> None:
heappush(self.q, seatNumber)
# Your SeatManager object will be instantiated and called as such:
# obj = SeatManager(n)
# param_1 = obj.reserve()
# obj.unreserve(seatNumber)
Complexity
The time complexity is O(n log n). 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.