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Given a n-ary tree, find its maximum depth.
The maximum depth is the number of nodes along the longest path from the root node down to the farthest leaf node.
Nary-Tree input serialization is represented in their level order traversal, each group of children is separated by the null value (See examples).
Example 1:
Input: root = [1,null,3,2,4,null,5,6]
Output: 3
Example 2:
Input: root = [1,null,2,3,4,5,null,null,6,7,null,8,null,9,10,null,null,11,null,12,null,13,null,null,14]
Output: 5
Constraints:
[0, 104]
.1000
.public int maxDepth(Node root) {
if(root == null) return 0;
Queue<Node> queue = new LinkedList<>();
queue.offer(root);
int depth = 0;
while(!queue.isEmpty())
{
int size = queue.size();
for(int i = 0; i < size; i++)
{
Node current = queue.poll();
for(Node child: current.children) queue.offer(child);
}
depth++;
}
return depth;
}
class Solution {
public:
int maxDepth(Node* root) {
if (root == nullptr) return 0;
int depth = 0;
for (auto child : root->children) depth = max(depth, maxDepth(child));
return 1 + depth;
}
};
"""
# Definition for a Node.
class Node:
def __init__(self, val, children):
self.val = val
self.children = children
"""
class Solution:
def maxDepth(self, root: 'Node') -> int:
# Base case
if root == None:
return 0
# Depth level of the tree
depth = 0
# Loops through children array
for child in root.children:
# Compares current depth of depth with a new level of depth
# Sets the biggest value to variable depth
depth = max(depth, self.maxDepth(child))
# As going deeper into the tree increases depth by 1
print ('root ' + str(root.val) + ' depth ' + str(depth + 1))
return depth + 1
# So for the first test case it'll look like
# first call is the call with root 1
# depth = 0 -> second call with child 3 ->
# it has 2 children so there'll be two calls from for loop
# call with child 5 -> sets the for loop with child of 5 which is None (Null)
# this call hits base case and returns 0
# the same happens with child 6
# call to child 6 from the for loop -> child of 6 is None -> returns 0
# depth = max(0, 0) -> depth = 0
# return to one level higher -> call to child 5 reaches return statement ->
# depth = 1
# call to child 6 reaches return statement and it returns 1 ->
# current depth is 1 because child 5 set it -> max(1, 1) -> depth = 1
# return to one more level higher
# call to child 3 reaches return statement ->
# depth was equal to 1 now it becomes 2 (depth + 1)
# now it's turn to children 2 and 4 to be called
# the story is exactly the same as with 5 and 6 only depth is now 2 ->
# both 2 and 4 return depth 1 that's why it's rejected by max(2, 1)
# depth remains 2
# and finally everything returns to the very first call with root 1
# it reaches return statement and returns 2+1=3
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