N 叉树的层序遍历
给定一个 N 叉树,返回其节点值的层序遍历。(即从左到右,逐层遍历)。
树的序列化输入是用层序遍历,每组子节点都由 null 值分隔(参见示例)。
示例 1:

输入:root = [1,null,3,2,4,null,5,6]
输出:[[1],[3,2,4],[5,6]]
示例 2:

输入: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]
输出:[[1],[2,3,4,5],[6,7,8,9,10],[11,12,13],[14]]
提示:
- 树的高度不会超过
1000 - 树的节点总数在
[0, 10^4]之间
Python:
#BFS
"""
# Definition for a Node.
class Node:
def __init__(self, val=None, children=None):
self.val = val
self.children = children
"""
class Solution:
def levelOrder(self, root: 'Node') -> List[List[int]]:
if not root:
return []
out = []
q = deque([root])
while q:
level_values = []
level_size = len(q)
for _ in range(level_size):
node = q.popleft()
level_values.append(node.val)
q.extend(node.children)
out.append(level_values)
return out
#DFS
"""
# Definition for a Node.
class Node:
def __init__(self, val=None, children=None):
self.val = val
self.children = children
"""
class Solution:
def levelOrder(self, root: 'Node') -> List[List[int]]:
out = []
def dfs(node, depth):
if not node:
return
if depth == len(out):
out.append([])
out[depth].append(node.val)
for child in node.children:
dfs(child, depth + 1)
dfs(root, 0)
return out
Go:
//BFS
/**
* Definition for a Node.
* type Node struct {
* Val int
* Children []*Node
* }
*/
func levelOrder(root *Node) (out [][]int) {
if root == nil {
return
}
q := []*Node{root}
for len(q) > 0 {
var tmp []int
l := len(q)
for i := 0; i < l; i++ {
node := q[i]
tmp = append(tmp, node.Val)
for _, v := range node.Children {
q = append(q, v)
}
}
q = q[l:]
out = append(out, tmp)
}
return
}
//DFS
/**
* Definition for a Node.
* type Node struct {
* Val int
* Children []*Node
* }
*/
func levelOrder(root *Node) (out [][]int) {
var dfs func(*Node, int)
dfs = func(node *Node, depth int) {
if node == nil {
return
}
if depth == len(out) {
out = append(out, []int{})
}
out[depth] = append(out[depth], node.Val)
for _, v := range node.Children {
dfs(v, depth+1)
}
}
dfs(root, 0)
return
}
//BFS
func levelOrder(root *Node) (ans [][]int) {
if root == nil {
return
}
q := []*Node{root}
for q != nil {
level := []int{}
tmp := q
q = nil
for _, node := range tmp {
level = append(level, node.Val)
q = append(q, node.Children...)
}
ans = append(ans, level)
}
return
}
在每个树行中找最大值
给定一棵二叉树的根节点 root ,请找出该二叉树中每一层的最大值。
示例1:

输入: root = [1,3,2,5,3,null,9]
输出: [1,3,9]
示例2:
输入: root = [1,2,3]
输出: [1,3]
提示:
- 二叉树的节点个数的范围是
[0,104] -2^31 <= Node.val <= 2^31 - 1
Python:
# BFS
# 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 largestValues(self, root: Optional[TreeNode]) -> List[int]:
if not root:
return []
out = []
q = [root]
while q:
tmp = q.copy()
maximum = tmp[0].val
q = []
for node in tmp:
if node.val > maximum:
maximum = node.val
if node.left:
q.append(node.left)
if node.right:
q.append(node.right)
out.append(maximum)
return out
# DFS
# 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 largestValues(self, root: Optional[TreeNode]) -> List[int]:
def dfs(node, depth):
if not node:
return
if depth == len(out):
out.append(node.val)
else:
if node.val > out[depth]:
out[depth] = node.val
dfs(node.left, depth + 1)
dfs(node.right, depth + 1)
out = []
dfs(root, 0)
return out
Go:
//BFS
/**
* Definition for a binary tree node.
* type TreeNode struct {
* Val int
* Left *TreeNode
* Right *TreeNode
* }
*/
func largestValues(root *TreeNode) (out []int) {
if root == nil {
return nil
}
q := []*TreeNode{root}
for len(q) > 0 {
tmp := q
max := tmp[0].Val
q = nil
for _, node := range tmp {
if node.Val > max {
max = node.Val
}
if node.Left != nil {
q = append(q, node.Left)
}
if node.Right != nil {
q = append(q, node.Right)
}
}
out = append(out, max)
}
return
}
//DFS
/**
* Definition for a binary tree node.
* type TreeNode struct {
* Val int
* Left *TreeNode
* Right *TreeNode
* }
*/
func largestValues(root *TreeNode) (out []int) {
var dfs func(*TreeNode, int)
dfs = func(node *TreeNode, depth int) {
if node == nil {
return
}
if depth == len(out) {
out = append(out, node.Val)
} else {
if node.Val > out[depth] {
out[depth] = node.Val
}
}
dfs(node.Left, depth+1)
dfs(node.Right, depth+1)
}
dfs(root, 0)
return
}
填充每个节点的下一个右侧节点指针
给定一个 完美二叉树 ,其所有叶子节点都在同一层,每个父节点都有两个子节点。二叉树定义如下:
struct Node {
int val;
Node *left;
Node *right;
Node *next;
}
填充它的每个 next 指针,让这个指针指向其下一个右侧节点。如果找不到下一个右侧节点,则将 next 指针设置为 NULL。
初始状态下,所有 next 指针都被设置为 NULL。
示例 1:

输入:root = [1,2,3,4,5,6,7]
输出:[1,#,2,3,#,4,5,6,7,#]
解释:给定二叉树如图 A 所示,你的函数应该填充它的每个 next 指针,以指向其下一个右侧节点,如图 B 所示。序列化的输出按层序遍历排列,同一层节点由 next 指针连接,'#' 标志着每一层的结束。
示例 2:
输入:root = []
输出:[]
提示:
- 树中节点的数量在
[0, 212 - 1]范围内 -1000 <= node.val <= 1000
Python:
#官方解法
class Solution:
def connect(self, root: 'Node') -> 'Node':
if not root:
return root
# 从根节点开始
leftmost = root
while leftmost.left:
# 遍历这一层节点组织成的链表,为下一层的节点更新 next 指针
head = leftmost
while head:
# CONNECTION 1
head.left.next = head.right
# CONNECTION 2
if head.next:
head.right.next = head.next.left
# 指针向后移动
head = head.next
# 去下一层的最左的节点
leftmost = leftmost.left
return root
#官方解法,BFS
import collections
class Solution:
def connect(self, root: 'Node') -> 'Node':
if not root:
return root
# 初始化队列同时将第一层节点加入队列中,即根节点
Q = collections.deque([root])
# 外层的 while 循环迭代的是层数
while Q:
# 记录当前队列大小
size = len(Q)
# 遍历这一层的所有节点
for i in range(size):
# 从队首取出元素
node = Q.popleft()
# 连接
if i < size - 1:
node.next = Q[0]
# 拓展下一层节点
if node.left:
Q.append(node.left)
if node.right:
Q.append(node.right)
# 返回根节点
return root
#BFS,本人解法
class Solution:
def connect(self, root: 'Optional[Node]') -> 'Optional[Node]':
if root is None:
return root
q = [root]
def insert(arr, node):
l = len(arr)
if l != 0:
arr[-1].next = node
arr.append(node)
return arr
arr.append(node)
return arr
while len(q) > 0:
tmp = q
q = []
for node in tmp:
if node.left:
q = insert(q, node.left)
q = insert(q, node.right)
return root
#DFS,本人解法
class Solution:
def connect(self, root: 'Node') -> 'Node':
arr = []
def dfs(node, level):
nonlocal arr
if node is None:
return
if level == len(arr):
arr.append([])
if len(arr[level]) > 0:
arr[level][-1].next = node
arr[level].append(node)
dfs(node.left, level + 1)
dfs(node.right, level + 1)
dfs(root, 0)
return root
Go:
//官方解法
func connect(root *Node) *Node {
if root == nil {
return root
}
// 每次循环从该层的最左侧节点开始
for leftmost := root; leftmost.Left != nil; leftmost = leftmost.Left {
// 通过 Next 遍历这一层节点,为下一层的节点更新 Next 指针
for node := leftmost; node != nil; node = node.Next {
// 左节点指向右节点
node.Left.Next = node.Right
// 右节点指向下一个左节点
if node.Next != nil {
node.Right.Next = node.Next.Left
}
}
}
// 返回根节点
return root
}
//BFS,官方解法
func connect(root *Node) *Node {
if root == nil {
return root
}
// 初始化队列同时将第一层节点加入队列中,即根节点
queue := []*Node{root}
// 循环迭代的是层数
for len(queue) > 0 {
tmp := queue
queue = nil
// 遍历这一层的所有节点
for i, node := range tmp {
// 连接
if i+1 < len(tmp) {
node.Next = tmp[i+1]
}
// 拓展下一层节点
if node.Left != nil {
queue = append(queue, node.Left)
queue = append(queue, node.Right)
}
}
}
// 返回根节点
return root
}
//BFS,本人解法
/**
* Definition for a Node.
* type Node struct {
* Val int
* Left *Node
* Right *Node
* Next *Node
* }
*/
func connect(root *Node) *Node {
if root == nil {
return root
}
q := []*Node{root}
insert := func(arr []*Node, node *Node) []*Node {
l := len(arr)
if l != 0 {
arr[l-1].Next = node
arr = append(arr, node)
return arr
}
// node.Next = nil
arr = append(arr, node)
return arr
}
for len(q) > 0 {
tmp := q
q = nil
for _, node := range tmp {
if node.Left != nil {
q = insert(q, node.Left)
q = insert(q, node.Right)
}
}
}
return root
}
//DFS,本人解法
/**
* Definition for a Node.
* type Node struct {
* Val int
* Left *Node
* Right *Node
* Next *Node
* }
*/
func connect(root *Node) *Node {
var arr [][]*Node
var dfs func(*Node, int)
dfs = func(node *Node, level int) {
if node == nil {
return
}
if level == len(arr) {
arr = append(arr, []*Node{})
}
if len(arr[level]) > 0 {
arr[level][len(arr[level])-1].Next = node
}
arr[level] = append(arr[level], node)
dfs(node.Left, level+1)
dfs(node.Right, level+1)
}
dfs(root, 0)
return root
}
填充每个节点的下一个右侧节点指针 II
给定一个二叉树:
struct Node {
int val;
Node *left;
Node *right;
Node *next;
}
填充它的每个 next 指针,让这个指针指向其下一个右侧节点。如果找不到下一个右侧节点,则将 next 指针设置为 NULL 。
初始状态下,所有 next 指针都被设置为 NULL 。
示例 1:

输入:root = [1,2,3,4,5,null,7]
输出:[1,#,2,3,#,4,5,7,#]
解释:给定二叉树如图 A 所示,你的函数应该填充它的每个 next 指针,以指向其下一个右侧节点,如图 B 所示。序列化输出按层序遍历顺序(由 next 指针连接),'#' 表示每层的末尾。
示例 2:
输入:root = []
输出:[]
提示:
- 树中的节点数在范围
[0, 6000]内 -100 <= Node.val <= 100
Python:
#BFS
class Solution:
def connect(self, root: 'Node') -> 'Node':
if not root:
return root
# 初始化队列同时将第一层节点加入队列中,即根节点
Q = collections.deque([root])
# 外层的 while 循环迭代的是层数
while Q:
# 记录当前队列大小
size = len(Q)
# 遍历这一层的所有节点
for i in range(size):
# 从队首取出元素
node = Q.popleft()
# 连接
if i < size - 1:
node.next = Q[0]
# 拓展下一层节点
if node.left:
Q.append(node.left)
if node.right:
Q.append(node.right)
# 返回根节点
return root
#BFS,与上题类似
class Solution:
def connect(self, root: 'Optional[Node]') -> 'Optional[Node]':
if root is None:
return root
q = [root]
def insert(arr, node):
l = len(arr)
if l != 0:
arr[-1].next = node
arr.append(node)
return arr
arr.append(node)
return arr
while len(q) > 0:
tmp = q
q = []
for node in tmp:
if node.left:
q = insert(q, node.left)
if node.right:
q = insert(q, node.right)
return root
"""
# Definition for a Node.
class Node:
def __init__(self, val: int = 0, left: 'Node' = None, right: 'Node' = None, next: 'Node' = None):
self.val = val
self.left = left
self.right = right
self.next = next
"""
#DFS,与上题类似
class Solution:
def connect(self, root: 'Node') -> 'Node':
arr = []
def dfs(node, level):
nonlocal arr
if node is None:
return
if level == len(arr):
arr.append([])
if len(arr[level]) > 0:
arr[level][-1].next = node
arr[level].append(node)
dfs(node.left, level + 1)
dfs(node.right, level + 1)
dfs(root, 0)
return root
Go:
//跟上题解法类似,BFS
/**
* Definition for a Node.
* type Node struct {
* Val int
* Left *Node
* Right *Node
* Next *Node
* }
*/
func connect(root *Node) *Node {
if root == nil {
return root
}
// 初始化队列同时将第一层节点加入队列中,即根节点
queue := []*Node{root}
// 循环迭代的是层数
for len(queue) > 0 {
tmp := queue
queue = nil
// 遍历这一层的所有节点
for i, node := range tmp {
// 连接
if i+1 < len(tmp) {
node.Next = tmp[i+1]
}
// 拓展下一层节点
if node.Left != nil {
queue = append(queue, node.Left)
}
if node.Right != nil {
queue = append(queue, node.Right)
}
}
}
// 返回根节点
return root
}
//BFS
func connect(root *Node) *Node {
if root == nil {
return root
}
q := []*Node{root}
insert := func(arr []*Node, node *Node) []*Node {
l := len(arr)
if l != 0 {
arr[l-1].Next = node
arr = append(arr, node)
return arr
}
// node.Next = nil
arr = append(arr, node)
return arr
}
for len(q) > 0 {
tmp := q
q = nil
for _, node := range tmp {
if node.Left != nil {
q = insert(q, node.Left)
}
if node.Right != nil {
q = insert(q, node.Right)
}
}
}
return root
}
//与上题类似,DFS同样适用
func connect(root *Node) *Node {
var arr [][]*Node
var dfs func(*Node, int)
dfs = func(node *Node, level int) {
if node == nil {
return
}
if level == len(arr) {
arr = append(arr, []*Node{})
}
if len(arr[level]) > 0 {
arr[level][len(arr[level])-1].Next = node
}
arr[level] = append(arr[level], node)
dfs(node.Left, level+1)
dfs(node.Right, level+1)
}
dfs(root, 0)
return root
}
二叉树的最大深度
给定一个二叉树 root ,返回其最大深度。
二叉树的 最大深度 是指从根节点到最远叶子节点的最长路径上的节点数。
示例 1:

输入:root = [3,9,20,null,null,15,7]
输出:3
示例 2:
输入:root = [1,null,2]
输出:2
提示:
- 树中节点的数量在
[0, 10^4]区间内。 -100 <= Node.val <= 100
Python:
#官方解法,DFS
class Solution:
def maxDepth(self, root):
if root is None:
return 0
else:
left_height = self.maxDepth(root.left)
right_height = self.maxDepth(root.right)
return max(left_height, right_height) + 1
#本人解法,BFS
class Solution:
def maxDepth(self, root: Optional[TreeNode]) -> int:
if not root:
return 0
max_depth = 0
queue = collections.deque([root])
while queue:
size = len(queue)
for _ in range(size):
node = queue.popleft()
if node.left:
queue.append(node.left)
if node.right:
queue.append(node.right)
max_depth += 1
return max_depth
##本人解法,DFS
# 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 maxDepth(self, root: Optional[TreeNode]) -> int:
def dfs(node: TreeNode, depth: int) -> None:
nonlocal max_depth
if not node:
return
if depth > max_depth:
max_depth = depth
dfs(node.left, depth + 1)
dfs(node.right, depth + 1)
max_depth = 0
dfs(root, 1)
return max_depth
Go:
//官方解法,DFS
func maxDepth(root *TreeNode) int {
if root == nil {
return 0
}
return max(maxDepth(root.Left), maxDepth(root.Right)) + 1
}
func max(a, b int) int {
if a > b {
return a
}
return b
}
//DFS,本人解法
/**
* Definition for a binary tree node.
* type TreeNode struct {
* Val int
* Left *TreeNode
* Right *TreeNode
* }
*/
func maxDepth(root *TreeNode) int {
var dfs func(*TreeNode, int)
max := 0
dfs = func(node *TreeNode, depth int) {
if node == nil {
return
}
if depth > max {
max = depth
}
dfs(node.Left, depth+1)
dfs(node.Right, depth+1)
}
dfs(root, 1)
return max
}
//本人解法,BFS
func maxDepth(root *TreeNode) (max int) {
if root == nil {
return
}
q := []*TreeNode{root}
for len(q) > 0 {
tmp := q
q = nil
for _, node := range tmp {
if node.Left != nil {
q = append(q, node.Left)
}
if node.Right != nil {
q = append(q, node.Right)
}
}
max++
}
return
}
二叉树的最小深度
给定一个二叉树,找出其最小深度。
最小深度是从根节点到最近叶子节点的最短路径上的节点数量。
**说明:**叶子节点是指没有子节点的节点。
示例 1:

输入:root = [3,9,20,null,null,15,7]
输出:2
示例 2:
输入:root = [2,null,3,null,4,null,5,null,6]
输出:5
提示:
- 树中节点数的范围在
[0, 10^5]内 -1000 <= Node.val <= 1000
Python:
#DFS
# 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 minDepth(self, root: Optional[TreeNode]) -> int:
def dfs(node, depth):
if node is None:
return depth - 1
if node.left is None and node.right is None:
return depth
left = dfs(node.left, depth + 1)
right = dfs(node.right, depth + 1)
if node.left is None:
return right
if node.right is None:
return left
return min(left, right)
return dfs(root, 1)
# 本人解法,BFS
# 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 minDepth(self, root: Optional[TreeNode]) -> int:
if not root:
return 0
min_depth = 0
queue = deque([root])
while queue:
size = len(queue)
min_depth += 1
for _ in range(size):
node = queue.popleft()
if not node.left and not node.right:
return min_depth
if node.left:
queue.append(node.left)
if node.right:
queue.append(node.right)
return min_depth
Go:
//本人解法,BFS
func minDepth(root *TreeNode) (min int) {
if root == nil {
return 0
}
q := []*TreeNode{root}
for len(q) > 0 {
tmp := q
q = nil
min++
for _, node := range tmp {
if node.Left == nil && node.Right == nil {
return
}
if node.Left != nil {
q = append(q, node.Left)
}
if node.Right != nil {
q = append(q, node.Right)
}
}
}
return
}
//本人解法,DFS
func minDepth(root *TreeNode) int {
var dfs func(*TreeNode, int) int
dfs = func(node *TreeNode, depth int) int {
if node == nil {
return depth - 1
}
if node.Left == nil && node.Right == nil {
return depth
}
left := dfs(node.Left, depth+1)
right := dfs(node.Right, depth+1)
if node.Left == nil {
return right
}
if node.Right == nil {
return left
}
return min(left, right)
}
return dfs(root, 1)
}
func min(a, b int) int {
if a < b {
return a
}
return b
}
//注意,考虑一个只有左子节点的节点。在这种情况下,node.Left != nil 和 node.Right == nil。如果我们删除了这两行代码,那么函数将返回 min(left, right),即 min(depth of left subtree, 0),结果将是0,这是不正确的。正确的行为是返回右子树(即左子树)的深度,因为这是唯一存在的子树。因此,这两行代码确保了函数在处理只有一个子节点的节点时的正确行为。如果删除它们,函数将无法正确处理这种情况。