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Leetcode #1372: Longest ZigZag Path in a Binary Tree

In this guide, we solve Leetcode #1372 Longest ZigZag Path in a Binary Tree in Python and focus on the core idea that makes the solution efficient.

You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.

Leetcode

Problem Statement

You are given the root of a binary tree. A ZigZag path for a binary tree is defined as follow: Choose any node in the binary tree and a direction (right or left).

Quick Facts

  • Difficulty: Medium
  • Premium: No
  • Tags: Tree, Depth-First Search, Dynamic Programming, Binary Tree

Intuition

The problem breaks into overlapping subproblems, so caching results prevents exponential repetition.

A carefully chosen DP state captures exactly what we need to build the final answer.

Approach

Define the DP state and recurrence, then compute states in the correct order.

Optionally compress space once the recurrence is clear.

Steps:

  • Choose a DP state definition.
  • Write the recurrence and base cases.
  • Compute states in the correct order.

Example

Input: root = [1,null,1,1,1,null,null,1,1,null,1,null,null,null,1] Output: 3 Explanation: Longest ZigZag path in blue nodes (right -> left -> right).

Python Solution

# 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 longestZigZag(self, root: TreeNode) -> int: def dfs(root, l, r): if root is None: return nonlocal ans ans = max(ans, l, r) dfs(root.left, r + 1, 0) dfs(root.right, 0, l + 1) ans = 0 dfs(root, 0, 0) return ans

Complexity

The time complexity is O(n·m) (typical). The space complexity is O(n·m) or optimized.

Edge Cases and Pitfalls

Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.

Summary

This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.


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