Algorithm Notes
Summary: Climbing Stairs — notes not yet curated.
Time: Estimate via loops/recurrences; common classes: O(1), O(log n), O(n), O(n log n), O(n^2)
Space: Count auxiliary structures and recursion depth.
Tip: See the Big-O Guide for how to derive bounds and compare trade-offs.
Big-O Guide
Source
"""
Climbing Stairs
TODO: Add problem description
"""
from src.interview_workbook.leetcode._registry import register_problem
from src.interview_workbook.leetcode._types import Category, Difficulty
class Solution:
def solve(self, *args) -> int:
"""Return the number of distinct ways to climb n stairs (1 or 2 steps at a time)."""
if not args:
return 0
n = args[0]
if n <= 2:
return n
prev, curr = 1, 2
for _ in range(3, n + 1):
prev, curr = curr, prev + curr
return curr
def demo():
"""Run a demo for the Climbing Stairs problem."""
solver = Solution()
n = 5
result = solver.solve(n)
return str(result)
register_problem(
id=70,
slug="climbing_stairs",
title="Climbing Stairs",
category=Category.DP_1D,
difficulty=Difficulty.EASY,
tags=["math", "dynamic_programming"],
url="https://leetcode.com/problems/climbing-stairs/",
notes="",
)