1028. Recover a Tree From Preorder Traversal

Problem

We run a preorder depth-first search (DFS) on the root of a binary tree.

At each node in this traversal, we output D dashes (where D is the depth of this node), then we output the value of this node. If the depth of a node is D, the depth of its immediate child is D + 1. The depth of the root node is 0.

If a node has only one child, that child is guaranteed to be the left child.

Given the output traversal of this traversal, recover the tree and return its root.

https://leetcode.com/problems/recover-a-tree-from-preorder-traversal/

Example 1:

Input: traversal = "1-2--3--4-5--6--7"
Output: [1,2,5,3,4,6,7]

Example 2:

Input: traversal = "1-2--3---4-5--6---7"
Output: [1,2,5,3,null,6,null,4,null,7]

Example 3:

Input: traversal = "1-401--349---90--88"
Output: [1,401,null,349,88,90]

Constraints:

The number of nodes in the original tree is in the range [1, 1000].
1 <= Node.val <= 10⁹

Test Cases

# 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 recoverFromPreorder(self, traversal: str) -> Optional[TreeNode]:

solution_test.py

import pytest

import os
import sys
sys.path.append(os.path.dirname(os.path.dirname(__file__)))
from _utils.binary_tree import print_tree
from solution import Solution

null = None


@pytest.mark.parametrize('traversal, expected', [
    ("1-2--3--4-5--6--7", [1,2,5,3,4,6,7]),
    ("1-2--3---4-5--6---7", [1,2,5,3,null,6,null,4,null,7]),
    ("1-401--349---90--88", [1,401,null,349,88,90]),
])
@pytest.mark.parametrize('sol', [Solution()])
def test_solution(sol, traversal, expected):
    root = sol.recoverFromPreorder(traversal)
    res = print_tree(root)
    assert res == expected

Thoughts

先对 traversal 字符串做预处理，把信息解析出来，得到一个数组，数组中每一项是个二元组即 (level, val)，其中 val 就是对应的数字，level 是数字前边 - 的个数（即对应节点在二叉树的深度）。最简单的办法就是直接按 - 把 traversal 分段，除了第一个数字之外，每个数字左边的空字符串数量即为 level - 1。也可以像 224. Basic Calculator 那样写一个专门的 tokenizer，用移动下标进行处理。

在构造二叉树的时候，用一个栈记录下从根节点到新节点的路径，以便能够快速回退到某个祖先节点。根据路径的长度（栈中节点的个数）可以知道栈顶节点在二叉树中的深度，对于从 traversal 解析到的下一对 (level, val)，如果 level 小于路径长度，则把多余的节点依次弹出，直到栈顶节点的深度是 level - 1，此即新节点的父节点。因为题目限定，如果只有一个子节点，该子节点为左子节点，所以只需要判断栈顶节点是否有左子节点，以此来确定新节点是添加到哪里。

时间复杂度 O(n)，空间复杂度 O(n)（主要是处理 traversal 用的，如果不用 split 而是完全流式处理，可以用 O(1) 空间完成 traversal 处理，而总的空间复杂度为 O(h)，其中 h 是二叉树的深度）。

Code

solution.py

from typing import Iterable, Optional


# 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 recoverFromPreorder(self, traversal: str) -> Optional[TreeNode]:
        stack = [] # path from root to current node
        for level, val in self.tokenize(traversal):
            while len(stack) > level:
                stack.pop()

            node = TreeNode(val)
            if stack:
                parent = stack[-1]
                if parent.left is None:
                    parent.left = node
                else:
                    parent.right = node

            stack.append(node)

        return stack[0]

    def tokenize(self, traversal: str) -> Iterable[tuple[int, int]]:
        level = 0
        for part in traversal.split('-'):
            if not part:
                level += 1
            else:
                yield level, int(part)
                level = 1

Test cases for solution inner methods:

solution_inner_test.py

import pytest

from solution import Solution


@pytest.mark.parametrize('traversal, expected', [
    ("1-2--3--4-5--6--7", [(0,1), (1,2), (2,3), (2,4), (1,5), (2,6), (2,7)]),
    ("1-2--3---4-5--6---7", [(0,1), (1,2), (2,3), (3,4), (1,5), (2,6), (3,7)]),
    ("1-401--349---90--88", [(0,1), (1,401), (2,349), (3,90), (2,88)]),
])
@pytest.mark.parametrize('sol', [Solution()])
def test_solution(sol, traversal, expected):
    res = sol.tokenize(traversal)
    assert list(res) == expected

本文引用
- 224. Basic Calculator

本文除了题目描述（Problem）部分之外，其他内容由 Calf 原创，采用 CC BY-NC-SA 4.0 许可协议，转载请注明出处。