<p>Given the <code>root</code> of a binary search tree, and an integer <code>k</code>, return <em>the</em> <code>k<sup>th</sup></code> <em>smallest value (<strong>1-indexed</strong>) of all the values of the nodes in the tree</em>.</p>

<p>&nbsp;</p>
<p><strong class="example">Example 1:</strong></p>
<img alt="" src="https://assets.leetcode.com/uploads/2021/01/28/kthtree1.jpg" style="width: 212px; height: 301px;" />
<pre>
<strong>Input:</strong> root = [3,1,4,null,2], k = 1
<strong>Output:</strong> 1
</pre>

<p><strong class="example">Example 2:</strong></p>
<img alt="" src="https://assets.leetcode.com/uploads/2021/01/28/kthtree2.jpg" style="width: 382px; height: 302px;" />
<pre>
<strong>Input:</strong> root = [5,3,6,2,4,null,null,1], k = 3
<strong>Output:</strong> 3
</pre>

<p>&nbsp;</p>
<p><strong>Constraints:</strong></p>

<ul>
	<li>The number of nodes in the tree is <code>n</code>.</li>
	<li><code>1 &lt;= k &lt;= n &lt;= 10<sup>4</sup></code></li>
	<li><code>0 &lt;= Node.val &lt;= 10<sup>4</sup></code></li>
</ul>

<p>&nbsp;</p>
<p><strong>Follow up:</strong> If the BST is modified often (i.e., we can do insert and delete operations) and you need to find the kth smallest frequently, how would you optimize?</p>

# 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:
        """
        inorder traversal
        left -> root -> right

        dfs, as we want to start from the leftmost path
        iterative dfs using stack
        """
        self.nodes = []
        def dfs(node):
            if not node:
                return None
            dfs(node.left)
            self.nodes.append(node.val)
            dfs(node.right)
        dfs(root)
        return self.nodes[k - 1]


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