Leetcode #230: Kth Smallest Element in a BST
In this guide, we solve Leetcode #230 Kth Smallest Element in a BST 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 the root of a binary search tree, and an integer k, return the kth smallest value (1-indexed) of all the values of the nodes in the tree. Example 1: Input: root = [3,1,4,null,2], k = 1 Output: 1 Example 2: Input: root = [5,3,6,2,4,null,null,1], k = 3 Output: 3 Constraints: The number of nodes in the tree is n.
Quick Facts
- Difficulty: Medium
- Premium: No
- Tags: Tree, Depth-First Search, Binary Search Tree, Binary Tree
Intuition
We need to explore a structure deeply before backing up, which suits DFS.
DFS keeps local context on the call stack and is easy to implement recursively.
Approach
Define a recursive DFS that carries the necessary state.
Combine child results as the recursion unwinds.
Steps:
- Define a recursive DFS with state.
- Visit children and combine results.
- Return the final aggregation.
Example
Input: root = [3,1,4,null,2], k = 1
Output: 1
Python Solution
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, val=0, left=None, right=None):
# self.val = val
# self.left = left
# self.right = right
class Solution:
def kthSmallest(self, root: Optional[TreeNode], k: int) -> int:
stk = []
while root or stk:
if root:
stk.append(root)
root = root.left
else:
root = stk.pop()
k -= 1
if k == 0:
return root.val
root = root.right
Complexity
The time complexity is O(V+E). The space complexity is O(V).
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.