【leetcode】104. 二叉树的最大深度(python)递归 _深度优先 + 非递归_广度优先

【leetcode】104. 二叉树的最大深度(python)递归 _深度优先 + 非递归_广度优先_第1张图片

方法一:递归 (DFS)

# Definition for a binary tree node.
# class TreeNode(object):
#     def __init__(self, val=0, left=None, right=None):
#         self.val = val
#         self.left = left
#         self.right = right
class Solution(object):
    def maxDepth(self, root):
        """
        :type root: TreeNode
        :rtype: int
        """
        if root is None:
            return 0
        nl = self.maxDepth(root.left)
        nr = self.maxDepth(root.right)
        return max(nl, nr) + 1

方法二:非递归(广度优先,层次遍历)

实现1:用collections中的队列

# Definition for a binary tree node.
# class TreeNode(object):
#     def __init__(self, val=0, left=None, right=None):
#         self.val = val
#         self.left = left
#         self.right = right

# 非递归  层次遍历(广度优先)   queue
import collections

class Solution(object):
    def maxDepth(self, root):
        if not root:
            return 0
        que = collections.deque()
        que.append(root)
        high = 0
        while que:
            cur_len = len(que)
            for i in range(cur_len):
                tmp = que.popleft()
                if tmp.left:
                    que.append(tmp.left)
                if tmp.right:
                    que.append(tmp.right)
            high += 1
        return high

实现2:直接用list

# Definition for a binary tree node.
# class TreeNode(object):
#     def __init__(self, val=0, left=None, right=None):
#         self.val = val
#         self.left = left
#         self.right = right

# 非递归  层次遍历(广度优先)   queue
class Solution(object):
    def maxDepth(self, root):
        if not root:
            return 0
        que = [root]    # 用list也可
        high = 0
        while que:
            cur_len = len(que)
            for i in range(cur_len):
                tmp = que.pop(0)
                if tmp.left:
                    que.append(tmp.left)
                if tmp.right:
                    que.append(tmp.right)
            high += 1
        return high

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