"""
0742. Closest Leaf in a Binary Tree
Medium

Given a binary tree where every node has a unique value, and a target key k, find the value of the nearest leaf node to target k in the tree.

Here, nearest to a leaf means the least number of edges travelled on the binary tree to reach any leaf of the tree. Also, a node is called a leaf if it has no children.

In the following examples, the input tree is represented in flattened form row by row. The actual root tree given will be a TreeNode object.

Example 1:

Input:
root = [1, 3, 2], k = 1
Diagram of binary tree:
          1
         / \
        3   2

Output: 2 (or 3)

Explanation: Either 2 or 3 is the nearest leaf node to the target of 1.
Example 2:

Input:
root = [1], k = 1
Output: 1

Explanation: The nearest leaf node is the root node itself.
Example 3:

Input:
root = [1,2,3,4,null,null,null,5,null,6], k = 2
Diagram of binary tree:
             1
            / \
           2   3
          /
         4
        /
       5
      /
     6

Output: 3
Explanation: The leaf node with value 3 (and not the leaf node with value 6) is nearest to the node with value 2.
Note:
root represents a binary tree with at least 1 node and at most 1000 nodes.
Every node has a unique node.val in range [1, 1000].
There exists some node in the given binary tree for which node.val == k.

"""
# 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 findClosestLeaf(self, root: TreeNode, k: int) -> int:
        # 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 findClosestLeaf(self, root: TreeNode, k: int) -> int:
        graph, leaves = collections.defaultdict(list), set()
        def traverse(node):
            if not node:
                return
            if not node.left and not node.right:
                leaves.add(node.val)
                return
            if node.left:
                graph[node.val].append(node.left.val)
                graph[node.left.val].append(node.val)
                traverse(node.left)
            if node.right:
                graph[node.val].append(node.right.val)
                graph[node.right.val].append(node.val)
                traverse(node.right)
        traverse(root)
        queue = [k]
        while len(queue):
            next_queue = []
            for node in queue:
                if node in leaves:
                    return node
                next_queue += graph.pop(node, [])
            queue = next_queue

"""
0742. Closest Leaf in a Binary Tree
Medium

Given a binary tree where every node has a unique value, and a target key k, find the value of the nearest leaf node to target k in the tree.

Here, nearest to a leaf means the least number of edges travelled on the binary tree to reach any leaf of the tree. Also, a node is called a leaf if it has no children.

In the following examples, the input tree is represented in flattened form row by row. The actual root tree given will be a TreeNode object.

Example 1:

Input:
root = [1, 3, 2], k = 1
Diagram of binary tree:
          1
         / \
        3   2

Output: 2 (or 3)

Explanation: Either 2 or 3 is the nearest leaf node to the target of 1.
Example 2:

Input:
root = [1], k = 1
Output: 1

Explanation: The nearest leaf node is the root node itself.
Example 3:

Input:
root = [1,2,3,4,null,null,null,5,null,6], k = 2
Diagram of binary tree:
             1
            / \
           2   3
          /
         4
        /
       5
      /
     6

Output: 3
Explanation: The leaf node with value 3 (and not the leaf node with value 6) is nearest to the node with value 2.
Note:
root represents a binary tree with at least 1 node and at most 1000 nodes.
Every node has a unique node.val in range [1, 1000].
There exists some node in the given binary tree for which node.val == k.

"""
# 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 findClosestLeaf(self, root: TreeNode, k: int) -> int:
        # 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 findClosestLeaf(self, root: TreeNode, k: int) -> int:
        graph, leaves = collections.defaultdict(list), set()
        def traverse(node):
            if not node:
                return
            if not node.left and not node.right:
                leaves.add(node.val)
                return
            if node.left:
                graph[node.val].append(node.left.val)
                graph[node.left.val].append(node.val)
                traverse(node.left)
            if node.right:
                graph[node.val].append(node.right.val)
                graph[node.right.val].append(node.val)
                traverse(node.right)
        traverse(root)
        queue = [k]
        while len(queue):
            next_queue = []
            for node in queue:
                if node in leaves:
                    return node
                next_queue += graph.pop(node, [])
            queue = next_queue

0742. Closest Leaf in a Binary Tree Medium  Given a binary tree where every node has a unique value, and a target key k, find the value of the nearest leaf node to target k in the tree.  Here, nearest to a leaf means the least number of edges travelled on the binary tree to reach any leaf of the tree. Also, a node is called a leaf if it has no children.  In the following examples, the input tree is represented in flattened form row by row. The actual root tree given will be a TreeNode object.  Example 1:  Input: root = [1, 3, 2], k = 1 Diagram of binary tree:           1          / \         3   2  Output: 2 (or 3)  Explanation: Either 2 or 3 is the nearest leaf node to the target of 1. Example 2:  Input: root = [1], k = 1 Output: 1  Explanation: The nearest leaf node is the root node itself. Example 3:  Input: root = [1,2,3,4,null,null,null,5,null,6], k = 2 Diagram of binary tree:              1             / \            2   3           /          4         /        5       /      6  Output: 3 Explanation: The leaf node with value 3 (and not the leaf node with value 6) is nearest to the node with value 2. Note: root represents a binary tree with at least 1 node and at most 1000 nodes. Every node has a unique node.val in range [1, 1000]. There exists some node in the given binary tree for which node.val == k. # 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 # 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