mirror of
https://github.com/youngyangyang04/leetcode-master.git
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Merge pull request #323 from z80160280/master
添加 0226 0101 0104 python版本
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@ -360,6 +360,78 @@ Java:
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Python:
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> 递归法
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```python
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class Solution:
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def isSymmetric(self, root: TreeNode) -> bool:
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if not root:
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return True
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return self.compare(root.left, root.right)
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def compare(self, left, right):
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#首先排除空节点的情况
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if left == None and right != None: return False
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elif left != None and right == None: return False
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elif left == None and right == None: return True
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#排除了空节点,再排除数值不相同的情况
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elif left.val != right.val: return False
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#此时就是:左右节点都不为空,且数值相同的情况
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#此时才做递归,做下一层的判断
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outside = self.compare(left.left, right.right) #左子树:左、 右子树:右
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inside = self.compare(left.right, right.left) #左子树:右、 右子树:左
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isSame = outside and inside #左子树:中、 右子树:中 (逻辑处理)
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return isSame
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```
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> 迭代法: 使用队列
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```python
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import collections
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class Solution:
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def isSymmetric(self, root: TreeNode) -> bool:
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if not root:
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return True
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queue = collections.deque()
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queue.append(root.left) #将左子树头结点加入队列
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queue.append(root.right) #将右子树头结点加入队列
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while queue: #接下来就要判断这这两个树是否相互翻转
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leftNode = queue.popleft()
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rightNode = queue.popleft()
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if not leftNode and not rightNode: #左节点为空、右节点为空,此时说明是对称的
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continue
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#左右一个节点不为空,或者都不为空但数值不相同,返回false
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if not leftNode or not rightNode or leftNode.val != rightNode.val:
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return False
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queue.append(leftNode.left) #加入左节点左孩子
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queue.append(rightNode.right) #加入右节点右孩子
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queue.append(leftNode.right) #加入左节点右孩子
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queue.append(rightNode.left) #加入右节点左孩子
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return True
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```
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> 迭代法:使用栈
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```python
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class Solution:
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def isSymmetric(self, root: TreeNode) -> bool:
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if not root:
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return True
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st = [] #这里改成了栈
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st.append(root.left)
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st.append(root.right)
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while st:
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leftNode = st.pop()
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rightNode = st.pop()
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if not leftNode and not rightNode:
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continue
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if not leftNode or not rightNode or leftNode.val != rightNode.val:
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return False
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st.append(leftNode.left)
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st.append(rightNode.right)
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st.append(leftNode.right)
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st.append(rightNode.left)
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return True
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```
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Go:
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@ -281,6 +281,111 @@ class Solution {
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Python:
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104.二叉树的最大深度
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> 递归法:
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```python
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class Solution:
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def maxDepth(self, root: TreeNode) -> int:
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return self.getDepth(root)
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def getDepth(self, node):
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if not node:
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return 0
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leftDepth = self.getDepth(node.left) #左
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rightDepth = self.getDepth(node.right) #右
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depth = 1 + max(leftDepth, rightDepth) #中
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return depth
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```
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> 递归法;精简代码
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```python
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class Solution:
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def maxDepth(self, root: TreeNode) -> int:
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if not root:
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return 0
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return 1 + max(self.maxDepth(root.left), self.maxDepth(root.right))
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```
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> 迭代法:
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```python
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import collections
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class Solution:
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def maxDepth(self, root: TreeNode) -> int:
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if not root:
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return 0
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depth = 0 #记录深度
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queue = collections.deque()
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queue.append(root)
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while queue:
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size = len(queue)
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depth += 1
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for i in range(size):
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node = queue.popleft()
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if node.left:
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queue.append(node.left)
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if node.right:
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queue.append(node.right)
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return depth
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```
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559.N叉树的最大深度
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> 递归法:
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```python
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class Solution:
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def maxDepth(self, root: 'Node') -> int:
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if not root:
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return 0
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depth = 0
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for i in range(len(root.children)):
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depth = max(depth, self.maxDepth(root.children[i]))
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return depth + 1
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```
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> 迭代法:
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```python
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import collections
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class Solution:
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def maxDepth(self, root: 'Node') -> int:
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queue = collections.deque()
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if root:
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queue.append(root)
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depth = 0 #记录深度
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while queue:
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size = len(queue)
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depth += 1
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for i in range(size):
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node = queue.popleft()
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for j in range(len(node.children)):
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if node.children[j]:
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queue.append(node.children[j])
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return depth
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```
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> 使用栈来模拟后序遍历依然可以
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```python
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class Solution:
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def maxDepth(self, root: 'Node') -> int:
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st = []
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if root:
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st.append(root)
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depth = 0
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result = 0
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while st:
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node = st.pop()
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if node != None:
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st.append(node) #中
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st.append(None)
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depth += 1
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for i in range(len(node.children)): #处理孩子
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if node.children[i]:
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st.append(node.children[i])
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else:
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node = st.pop()
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depth -= 1
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result = max(result, depth)
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return result
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```
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Go:
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@ -230,6 +230,56 @@ class Solution {
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Python:
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> 递归法:前序遍历
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```python
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class Solution:
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def invertTree(self, root: TreeNode) -> TreeNode:
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if not root:
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return None
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root.left, root.right = root.right, root.left #中
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self.invertTree(root.left) #左
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self.invertTree(root.right) #右
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return root
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```
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> 迭代法:深度优先遍历(前序遍历)
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```python
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class Solution:
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def invertTree(self, root: TreeNode) -> TreeNode:
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if not root:
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return root
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st = []
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st.append(root)
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while st:
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node = st.pop()
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node.left, node.right = node.right, node.left #中
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if node.right:
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st.append(node.right) #右
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if node.left:
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st.append(node.left) #左
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return root
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```
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> 迭代法:广度优先遍历(层序遍历)
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```python
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import collections
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class Solution:
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def invertTree(self, root: TreeNode) -> TreeNode:
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queue = collections.deque() #使用deque()
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if root:
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queue.append(root)
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while queue:
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size = len(queue)
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for i in range(size):
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node = queue.popleft()
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node.left, node.right = node.right, node.left #节点处理
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if node.left:
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queue.append(node.left)
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if node.right:
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queue.append(node.right)
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return root
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```
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Go:
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```Go
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func invertTree(root *TreeNode) *TreeNode {
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