kthSmallestInBST.py

# Given a binary search tree, write a function kthSmallest to find the kth smallest element in it.
#
# Note:
# You may assume k is always valid, 1 ≤ k ≤ BST's total elements.
#
# Follow up:
# What if the BST is modified (insert/delete operations) often and you need to find the kth smallest frequently? How would you optimize the kthSmallest routine?

# Definition for a binary tree node.
# class TreeNode(object):
#     def __init__(self, x):
#         self.val = x
#         self.left = None
#         self.right = None

class Solution(object):
    def kthSmallest(self, root, k):
        """
        :type root: TreeNode
        :type k: int
        :rtype: int
        """
        return (self.inorderTraversal(root))[k-1]


    def inorderTraversal(self, root):
        """
        :type root: TreeNode
        :rtype: List[int]
        """
        if not root:
            return []
        return self.inorderTraversal(root.left) + [root.val] + self.inorderTraversal(root.right)