Explore diverse LeetCode solutions in Python, C++, JavaScript, SQL, and TypeScript. Ideal for interview prep, learning, and code practice in multiple programming languages. Github Repo Link
Given the root
of a binary tree, determine if it is a valid binary search tree (BST).
A valid BST is defined as follows:
- The left subtree of a node contains only nodes with keys less than the node’s key.
- The right subtree of a node contains only nodes with keys greater than the node’s key.
- Both the left and right subtrees must also be binary search trees.
Example 1:
Input: root = [2,1,3] Output: true
Example 2:
Input: root = [5,1,4,null,null,3,6] Output: false Explanation: The root node's value is 5 but its right child's value is 4.
Constraints:
- The number of nodes in the tree is in the range
[1, 104]
. -231 <= Node.val <= 231 - 1
內容目錄
TogglePython
# time complexixty: O(n)
# space complexity: O(n)
import math
from typing import Optional
class TreeNode:
def __init__(self, val=0, left=None, right=None):
self.val = val
self.left = left
self.right = right
class Solution:
def isValidBST(self, root: Optional[TreeNode]) -> bool:
def dfs(node: Optional[TreeNode], low=-math.inf, high=math.inf):
if node is None:
return True
if node.val <= low:
return False
if node.val >= high:
return False
return dfs(node.left, low, node.val) and dfs(node.right, node.val, high)
return dfs(root)
class Solution:
def isValidBST(self, root: Optional[TreeNode]) -> bool:
prev = [-math.inf]
def dfs(node: Optional[TreeNode], prev):
if not node:
return True
if not dfs(node.left, prev):
return False
if node.val <= prev[0]:
return False
prev[0] = node.val
return dfs(node.right, prev)
return dfs(root, prev)
root1 = TreeNode(2)
root1.left = TreeNode(1)
root1.right = TreeNode(3)
print(Solution().isValidBST(root1))
root2 = TreeNode(5)
root2.left = TreeNode(1)
root2.right = TreeNode(4)
root2.right.left = TreeNode(3)
root2.right.right = TreeNode(6)
print(Solution().isValidBST(root2))