diff --git a/codes/cpp/chapter_tree/binary_tree_bfs.cpp b/codes/cpp/chapter_tree/binary_tree_bfs.cpp
index eeec2a18e..30c2d6007 100644
--- a/codes/cpp/chapter_tree/binary_tree_bfs.cpp
+++ b/codes/cpp/chapter_tree/binary_tree_bfs.cpp
@@ -15,12 +15,12 @@ vector<int> hierOrder(TreeNode* root) {
     vector<int> vec;
     while (!queue.empty()) {
         TreeNode* node = queue.front();
-        queue.pop();  // 队列出队
-        vec.push_back(node->val);            // 保存结点
+        queue.pop();                 // 队列出队
+        vec.push_back(node->val);    // 保存结点
         if (node->left != nullptr)
-            queue.push(node->left);    // 左子结点入队
+            queue.push(node->left);  // 左子结点入队
         if (node->right != nullptr)
-            queue.push(node->right);   // 右子结点入队
+            queue.push(node->right); // 右子结点入队
     }
     return vec;
 }
diff --git a/codes/go/chapter_computational_complexity/space_complexity.go b/codes/go/chapter_computational_complexity/space_complexity.go
index 77780ae04..eb3ebec97 100644
--- a/codes/go/chapter_computational_complexity/space_complexity.go
+++ b/codes/go/chapter_computational_complexity/space_complexity.go
@@ -42,7 +42,7 @@ func printTree(root *TreeNode) {
 	printTree(root.right)
 }
 
-/* 函数（或称方法）*/
+/* 函数 */
 func function() int {
 	// do something...
 	return 0
diff --git a/codes/python/chapter_tree/avl_tree.py b/codes/python/chapter_tree/avl_tree.py
new file mode 100644
index 000000000..d0ff48cba
--- /dev/null
+++ b/codes/python/chapter_tree/avl_tree.py
@@ -0,0 +1,208 @@
+"""
+File: avl_tree.py
+Created Time: 2022-12-20
+Author: a16su (lpluls001@gmail.com)
+"""
+
+import sys, os.path as osp
+import typing
+
+sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
+from include import *
+
+
+class AVLTree:
+    def __init__(self, root: typing.Optional[TreeNode] = None):
+        self.root = root
+
+    """ 获取结点高度 """
+    def height(self, node: typing.Optional[TreeNode]) -> int:
+        # 空结点高度为 -1 ，叶结点高度为 0
+        if node is not None:
+            return node.height
+        return -1
+
+    """ 更新结点高度 """
+    def __update_height(self, node: TreeNode):
+        # 结点高度等于最高子树高度 + 1
+        node.height = max([self.height(node.left), self.height(node.right)]) + 1
+
+    """ 获取平衡因子 """
+    def balance_factor(self, node: TreeNode) -> int:
+        # 空结点平衡因子为 0
+        if node is None:
+            return 0
+        # 结点平衡因子 = 左子树高度 - 右子树高度
+        return self.height(node.left) - self.height(node.right)
+
+    """ 右旋操作 """
+    def __right_rotate(self, node: TreeNode) -> TreeNode:
+        child = node.left
+        grand_child = child.right
+        # 以 child 为原点，将 node 向右旋转
+        child.right = node
+        node.left = grand_child
+        # 更新结点高度
+        self.__update_height(node)
+        self.__update_height(child)
+        # 返回旋转后子树的根节点
+        return child
+
+    """ 左旋操作 """
+    def __left_rotate(self, node: TreeNode) -> TreeNode:
+        child = node.right
+        grand_child = child.left
+        # 以 child 为原点，将 node 向左旋转
+        child.left = node
+        node.right = grand_child
+        # 更新结点高度
+        self.__update_height(node)
+        self.__update_height(child)
+        # 返回旋转后子树的根节点
+        return child
+
+    """ 执行旋转操作，使该子树重新恢复平衡 """
+    def __rotate(self, node: TreeNode) -> TreeNode:
+        # 获取结点 node 的平衡因子
+        balance_factor = self.balance_factor(node)
+        # 左偏树
+        if balance_factor > 1:
+            if self.balance_factor(node.left) >= 0:
+                # 右旋
+                return self.__right_rotate(node)
+            else:
+                # 先左旋后右旋
+                node.left = self.__left_rotate(node.left)
+                return self.__right_rotate(node)
+        # 右偏树
+        elif balance_factor < -1:
+            if self.balance_factor(node.right) <= 0:
+                # 左旋
+                return self.__left_rotate(node)
+            else:
+                # 先右旋后左旋
+                node.right = self.__right_rotate(node.right)
+                return self.__left_rotate(node)
+        # 平衡树，无需旋转，直接返回
+        return node
+
+    """ 插入结点 """
+    def insert(self, val) -> TreeNode:
+        self.root = self.__insert_helper(self.root, val)
+        return self.root
+
+    """ 递归插入结点（辅助函数）"""
+    def __insert_helper(self, node: typing.Optional[TreeNode], val: int) -> TreeNode:
+        if node is None:
+            return TreeNode(val)
+        # 1. 查找插入位置，并插入结点
+        if val < node.val:
+            node.left = self.__insert_helper(node.left, val)
+        elif val > node.val:
+            node.right = self.__insert_helper(node.right, val)
+        else:
+            # 重复结点不插入，直接返回
+            return node
+        # 更新结点高度
+        self.__update_height(node)
+        # 2. 执行旋转操作，使该子树重新恢复平衡
+        return self.__rotate(node)
+
+    """ 删除结点 """
+    def remove(self, val: int):
+        root = self.__remove_helper(self.root, val)
+        return root
+
+    """ 递归删除结点（辅助函数） """
+    def __remove_helper(self, node: typing.Optional[TreeNode], val: int) -> typing.Optional[TreeNode]:
+        if node is None:
+            return None
+        # 1. 查找结点，并删除之
+        if val < node.val:
+            node.left = self.__remove_helper(node.left, val)
+        elif val > node.val:
+            node.right = self.__remove_helper(node.right, val)
+        else:
+            if node.left is None or node.right is None:
+                child = node.left or node.right
+                # 子结点数量 = 0 ，直接删除 node 并返回
+                if child is None:
+                    return None
+                # 子结点数量 = 1 ，直接删除 node
+                else:
+                    node = child
+            else:  # 子结点数量 = 2 ，则将中序遍历的下个结点删除，并用该结点替换当前结点
+                temp = self.__min_node(node.right)
+                node.right = self.__remove_helper(node.right, temp.val)
+                node.val = temp.val
+        # 更新结点高度
+        self.__update_height(node)
+        # 2. 执行旋转操作，使该子树重新恢复平衡
+        return self.__rotate(node)
+
+    """ 获取最小结点 """
+    def __min_node(self, node: typing.Optional[TreeNode]) -> typing.Optional[TreeNode]:
+        if node is None:
+            return None
+        # 循环访问左子结点，直到叶结点时为最小结点，跳出
+        while node.left is not None:
+            node = node.left
+        return node
+
+    """ 查找结点 """
+    def search(self, val: int):
+        cur = self.root
+        # 循环查找，越过叶结点后跳出
+        while cur is not None:
+            # 目标结点在 root 的右子树中
+            if cur.val < val:
+                cur = cur.right
+            # 目标结点在 root 的左子树中
+            elif cur.val > val:
+                cur = cur.left
+            # 找到目标结点，跳出循环
+            else:
+                break
+        # 返回目标结点
+        return cur
+
+
+""" Driver Code """
+if __name__ == "__main__":
+    def test_insert(tree: AVLTree, val: int):
+        tree.insert(val)
+        print("\n插入结点 {} 后，AVL 树为".format(val))
+        print_tree(tree.root)
+
+    def test_remove(tree: AVLTree, val: int):
+        tree.remove(val)
+        print("\n删除结点 {} 后，AVL 树为".format(val))
+        print_tree(tree.root)
+
+    # 初始化空 AVL 树
+    avl_tree = AVLTree()
+
+    # 插入结点
+    # 请关注插入结点后，AVL 树是如何保持平衡的
+    test_insert(avl_tree, 1)
+    test_insert(avl_tree, 2)
+    test_insert(avl_tree, 3)
+    test_insert(avl_tree, 4)
+    test_insert(avl_tree, 5)
+    test_insert(avl_tree, 8)
+    test_insert(avl_tree, 7)
+    test_insert(avl_tree, 9)
+    test_insert(avl_tree, 10)
+    test_insert(avl_tree, 6)
+
+    # 插入重复结点
+    test_insert(avl_tree, 7)
+
+    # 删除结点
+    # 请关注删除结点后，AVL 树是如何保持平衡的
+    test_remove(avl_tree, 8)  # 删除度为 0 的结点
+    test_remove(avl_tree, 5)  # 删除度为 1 的结点
+    test_remove(avl_tree, 4)  # 删除度为 2 的结点
+
+    result_node = avl_tree.search(7)
+    print("\n查找到的结点对象为 {}，结点值 = {}".format(result_node, result_node.val))
diff --git a/codes/python/chapter_tree/binary_search_tree.py b/codes/python/chapter_tree/binary_search_tree.py
index 0f855f279..23e341854 100644
--- a/codes/python/chapter_tree/binary_search_tree.py
+++ b/codes/python/chapter_tree/binary_search_tree.py
@@ -1,10 +1,167 @@
 """
 File: binary_search_tree.py
-Created Time: 2022-11-25
-Author: Krahets (krahets@163.com)
+Created Time: 2022-12-20
+Author: a16su (lpluls001@gmail.com)
 """
 
 import sys, os.path as osp
+import typing
+
 sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
 from include import *
 
+
+""" 二叉搜索树 """
+class BinarySearchTree:
+    def __init__(self, nums: typing.List[int]) -> None:
+        nums.sort()
+        self.__root = self.build_tree(nums, 0, len(nums) - 1)
+
+    """ 构建二叉搜索树 """
+    def build_tree(self, nums: typing.List[int], start_index: int, end_index: int) -> typing.Optional[TreeNode]:
+        if start_index > end_index:
+            return None
+
+        # 将数组中间结点作为根结点
+        mid = (start_index + end_index) // 2
+        root = TreeNode(nums[mid])
+        # 递归建立左子树和右子树
+        root.left = self.build_tree(nums=nums, start_index=start_index, end_index=mid - 1)
+        root.right = self.build_tree(nums=nums, start_index=mid + 1, end_index=end_index)
+        return root
+
+    @property
+    def root(self) -> typing.Optional[TreeNode]:
+        return self.__root
+
+    """ 查找结点 """
+    def search(self, num: int) -> typing.Optional[TreeNode]:
+        cur = self.root
+        # 循环查找，越过叶结点后跳出
+        while cur is not None:
+            # 目标结点在 root 的右子树中
+            if cur.val < num:
+                cur = cur.right
+            # 目标结点在 root 的左子树中
+            elif cur.val > num:
+                cur = cur.left
+            # 找到目标结点，跳出循环
+            else:
+                break
+        return cur
+
+    """ 插入结点 """
+    def insert(self, num: int) -> typing.Optional[TreeNode]:
+        root = self.root
+        # 若树为空，直接提前返回
+        if root is None:
+            return None
+
+        cur = root
+        pre = None
+
+        # 循环查找，越过叶结点后跳出
+        while cur is not None:
+            # 找到重复结点，直接返回
+            if cur.val == num:
+                return None
+            pre = cur
+
+            if cur.val < num:  # 插入位置在 root 的右子树中
+                cur = cur.right
+            else:  # 插入位置在 root 的左子树中
+                cur = cur.left
+
+        # 插入结点 val
+        node = TreeNode(num)
+        if pre.val < num:
+            pre.right = node
+        else:
+            pre.left = node
+        return node
+
+    """ 删除结点 """
+    def remove(self, num: int) -> typing.Optional[TreeNode]:
+        root = self.root
+        # 若树为空，直接提前返回
+        if root is None:
+            return None
+
+        cur = root
+        pre = None
+
+        # 循环查找，越过叶结点后跳出
+        while cur is not None:
+            # 找到待删除结点，跳出循环
+            if cur.val == num:
+                break
+            pre = cur
+            if cur.val < num:  # 待删除结点在 root 的右子树中
+                cur = cur.right
+            else:  # 待删除结点在 root 的左子树中
+                cur = cur.left
+
+        # 若无待删除结点，则直接返回
+        if cur is None:
+            return None
+
+        # 子结点数量 = 0 or 1
+        if cur.left is None or cur.right is None:
+            # 当子结点数量 = 0 / 1 时， child = null / 该子结点
+            child = cur.left or cur.right
+            # 删除结点 cur
+            if pre.left == cur:
+                pre.left = child
+            else:
+                pre.right = child
+        # 子结点数量 = 2
+        else:
+            # 获取中序遍历中 cur 的下一个结点
+            nex = self.min(cur.right)
+            tmp = nex.val
+            # 递归删除结点 nex
+            self.remove(nex.val)
+            # 将 nex 的值复制给 cur
+            cur.val = tmp
+        return cur
+
+    """ 获取最小结点 """
+    def min(self, root: typing.Optional[TreeNode]) -> typing.Optional[TreeNode]:
+        if root is None:
+            return root
+
+        # 循环访问左子结点，直到叶结点时为最小结点，跳出
+        while root.left is not None:
+            root = root.left
+        return root
+
+
+""" Driver Code """
+if __name__ == "__main__":
+    # 初始化二叉搜索树
+    nums = list(range(1, 16))
+    bst = BinarySearchTree(nums=nums)
+    print("\n初始化的二叉树为\n")
+    print_tree(bst.root)
+
+    # 查找结点
+    node = bst.search(5)
+    print("\n查找到的结点对象为: {}，结点值 = {}".format(node, node.val))
+
+    # 插入结点
+    ndoe = bst.insert(16)
+    print("\n插入结点 16 后，二叉树为\n")
+    print_tree(bst.root)
+
+    # 删除结点
+    bst.remove(1)
+    print("\n删除结点 1 后，二叉树为\n")
+    print_tree(bst.root)
+
+    bst.remove(2)
+    print("\n删除结点 2 后，二叉树为\n")
+    print_tree(bst.root)
+
+    bst.remove(4)
+    print("\n删除结点 4 后，二叉树为\n")
+    print_tree(bst.root)
diff --git a/codes/python/chapter_tree/binary_tree.py b/codes/python/chapter_tree/binary_tree.py
index 81828b5cf..d99026352 100644
--- a/codes/python/chapter_tree/binary_tree.py
+++ b/codes/python/chapter_tree/binary_tree.py
@@ -1,10 +1,40 @@
 """
 File: binary_tree.py
-Created Time: 2022-11-25
-Author: Krahets (krahets@163.com)
+Created Time: 2022-12-20
+Author: a16su (lpluls001@gmail.com)
 """
 
 import sys, os.path as osp
+
 sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
 from include import *
 
+
+""" Driver Code """
+if __name__ == "__main__":
+    """ 初始化二叉树 """
+    # 初始化节点
+    n1 = TreeNode(val=1)
+    n2 = TreeNode(val=2)
+    n3 = TreeNode(val=3)
+    n4 = TreeNode(val=4)
+    n5 = TreeNode(val=5)
+    # 构建引用指向（即指针）
+    n1.left = n2
+    n1.right = n3
+    n2.left = n4
+    n2.right = n5
+    print("\n初始化二叉树\n")
+    print_tree(n1)
+
+    """ 插入与删除结点 """
+    P = TreeNode(0)
+    # 在 n1 -> n2 中间插入节点 P
+    n1.left = P
+    P.left = n2
+    print("\n插入结点 P 后\n")
+    print_tree(n1)
+    # 删除结点
+    n1.left = n2
+    print("\n删除结点 P 后\n");
+    print_tree(n1)
diff --git a/codes/python/chapter_tree/binary_tree_bfs.py b/codes/python/chapter_tree/binary_tree_bfs.py
index 9ae1b3594..0320a08dd 100644
--- a/codes/python/chapter_tree/binary_tree_bfs.py
+++ b/codes/python/chapter_tree/binary_tree_bfs.py
@@ -1,10 +1,42 @@
 """
 File: binary_tree_bfs.py
-Created Time: 2022-11-25
-Author: Krahets (krahets@163.com)
+Created Time: 2022-12-20
+Author: a16su (lpluls001@gmail.com)
 """
 
 import sys, os.path as osp
+import typing
+
 sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
 from include import *
 
+
+""" 层序遍历 """
+def hier_order(root: TreeNode):
+    # 初始化队列，加入根结点
+    queue = collections.deque()
+    queue.append(root)
+    # 初始化一个列表，用于保存遍历序列
+    res = []
+    while queue:
+        node = queue.popleft()       # 队列出队
+        res.append(node.val)         # 保存节点值
+        if node.left is not None:
+            queue.append(node.left)  # 左子结点入队
+        if node.right is not None:
+            queue.append(node.right) # 右子结点入队
+    return res
+
+
+""" Driver Code """
+if __name__ == "__main__":
+    # 初始化二叉树
+    # 这里借助了一个从数组直接生成二叉树的函数
+    root = list_to_tree(arr=[1, 2, 3, 4, 5, 6, 7, None, None, None, None, None, None, None, None])
+    print("\n初始化二叉树\n")
+    print_tree(root)
+
+    # 层序遍历
+    res = hier_order(root)
+    print("\n层序遍历的结点打印序列 = ", res)
+    assert res == [1, 2, 3, 4, 5, 6, 7]
diff --git a/codes/python/chapter_tree/binary_tree_dfs.py b/codes/python/chapter_tree/binary_tree_dfs.py
index f69076a6c..11ee8339c 100644
--- a/codes/python/chapter_tree/binary_tree_dfs.py
+++ b/codes/python/chapter_tree/binary_tree_dfs.py
@@ -1,46 +1,68 @@
 """
 File: binary_tree_dfs.py
-Created Time: 2022-11-25
-Author: Krahets (krahets@163.com)
+Created Time: 2022-12-20
+Author: a16su (lpluls001@gmail.com)
 """
 
 import sys, os.path as osp
+import typing
+
 sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
 from include import *
 
-# 定义一个list数组用来存储遍历的结果
+
+res = []
+
+""" 前序遍历 """
+def pre_order(root: typing.Optional[TreeNode]):
+    if root is None:
+        return
+    # 访问优先级：根结点 -> 左子树 -> 右子树
+    res.append(root.val)
+    pre_order(root=root.left)
+    pre_order(root=root.right)
+
+""" 中序遍历 """
+def in_order(root: typing.Optional[TreeNode]):
+    if root is None:
+        return
+    # 访问优先级：左子树 -> 根结点 -> 右子树
+    in_order(root=root.left)
+    res.append(root.val)
+    in_order(root=root.right)
+
+""" 后序遍历 """
+def post_order(root: typing.Optional[TreeNode]):
+    if root is None:
+        return
+    # 访问优先级：左子树 -> 右子树 -> 根结点
+    post_order(root=root.left)
+    post_order(root=root.right)
+    res.append(root.val)
 
 
-# 前序遍历
-def preorder(root):
-    if root == None:
-        return []
-    
-    # 访问顺序：根结点 -> 左子树 -> 右子树
+""" Driver Code """
+if __name__ == "__main__":
+    # 初始化二叉树
+    # 这里借助了一个从数组直接生成二叉树的函数
+    root = list_to_tree(arr=[1, 2, 3, 4, 5, 6, 7, None, None, None, None, None, None, None, None])
+    print("\n初始化二叉树\n")
+    print_tree(root)
 
-    list.append(root.val)
-    preorder(root.left)
-    preorder(root.right)
+    # 前序遍历
+    res.clear()
+    pre_order(root)
+    print("\n前序遍历的结点打印序列 = ", res)
+    assert res == [1, 2, 4, 5, 3, 6, 7]
 
+    # 中序遍历
+    res.clear()
+    in_order(root)
+    print("\n中序遍历的结点打印序列 = ", res)
+    assert res == [4, 2, 5, 1, 6, 3, 7]
 
-# 中序遍历
-def inorder(root):
-    if root == None:
-        return []
-
-    # 访问顺序：左子树 -> 根结点 -> 右子树
-    
-    inorder(root.left)
-    list.append(root.val)
-    inorder(root.right)
-
-# 后序遍历
-def postorder(root):
-    if root == None:
-        return []
-
-    # 访问顺序：左子树 -> 右子树 -> 根结点
-
-    postorder(root.left)
-    postorder(root.right)
-    list.append(root.val)
+    # 后序遍历
+    res.clear()
+    post_order(root)
+    print("\n后序遍历的结点打印序列 = ", res)
+    assert res == [4, 5, 2, 6, 7, 3, 1]
diff --git a/codes/python/include/binary_tree.py b/codes/python/include/binary_tree.py
index de2569e42..670fd18ce 100644
--- a/codes/python/include/binary_tree.py
+++ b/codes/python/include/binary_tree.py
@@ -10,9 +10,19 @@ class TreeNode:
     """Definition for a binary tree node
     """    
     def __init__(self, val=0, left=None, right=None):
-        self.val = val
-        self.left = left
-        self.right = right
+        self.val = val      # 结点值
+        self.height = 0     # 结点高度
+        self.left = left    # 左子结点引用
+        self.right = right  # 右子结点引用
+
+    def __str__(self):
+        val = self.val
+        left_node_val = self.left.val if self.left else None
+        right_node_val = self.right.val if self.right else None
+        return "<TreeNode: {}, leftTreeNode: {}, rightTreeNode: {}>".format(val, left_node_val, right_node_val)
+
+    __repr__ = __str__
+
 
 def list_to_tree(arr):
     """Generate a binary tree with a list
diff --git a/docs/chapter_computational_complexity/space_complexity.md b/docs/chapter_computational_complexity/space_complexity.md
index 50f2698ff..df5d98f34 100644
--- a/docs/chapter_computational_complexity/space_complexity.md
+++ b/docs/chapter_computational_complexity/space_complexity.md
@@ -38,7 +38,7 @@ comments: true
         Node(int x) { val = x; }
     }
     
-    /* 函数（或称方法） */
+    /* 函数 */
     int function() {
         // do something...
         return 0;
@@ -63,7 +63,7 @@ comments: true
         Node(int x) : val(x), next(nullptr) {}
     };
 
-    /* 函数（或称方法） */
+    /* 函数 */
     int func() {
         // do something...
         return 0;
@@ -87,7 +87,7 @@ comments: true
             self.val = x      # 结点值
             self.next = None  # 指向下一结点的指针（引用）
 
-    """ 函数（或称方法） """
+    """ 函数 """
     def function():
         # do something...
         return 0
@@ -113,7 +113,7 @@ comments: true
         return &Node{val: val}
     }
     
-    /* 函数（或称方法）*/
+    /* 函数 */
     func function() int {
         // do something...
         return 0
@@ -157,7 +157,7 @@ comments: true
         Node(int x) { val = x; }
     }
 
-    /* 函数（或称方法） */
+    /* 函数 */
     int function()
     {
         // do something...
diff --git a/docs/chapter_tree/avl_tree.md b/docs/chapter_tree/avl_tree.md
index 2b1ad08f0..e9a656bed 100644
--- a/docs/chapter_tree/avl_tree.md
+++ b/docs/chapter_tree/avl_tree.md
@@ -48,7 +48,13 @@ G. M. Adelson-Velsky 和 E. M. Landis 在其 1962 年发表的论文 "An algorit
 === "Python"
 
     ```python title="avl_tree.py"
-    
+    """ AVL 树结点类 """
+    class TreeNode:
+        def __init__(self, val=None, left=None, right=None):
+            self.val = val      # 结点值
+            self.height = 0     # 结点高度
+            self.left = left    # 左子结点引用
+            self.right = right  # 右子结点引用
     ```
 
 === "Go"
@@ -115,7 +121,17 @@ G. M. Adelson-Velsky 和 E. M. Landis 在其 1962 年发表的论文 "An algorit
 === "Python"
 
     ```python title="avl_tree.py"
-    
+    """ 获取结点高度 """
+    def height(self, node: typing.Optional[TreeNode]) -> int:
+        # 空结点高度为 -1 ，叶结点高度为 0
+        if node is not None:
+            return node.height
+        return -1
+
+    """ 更新结点高度 """
+    def __update_height(self, node: TreeNode):
+        # 结点高度等于最高子树高度 + 1
+        node.height = max([self.height(node.left), self.height(node.right)]) + 1
     ```
 
 === "Go"
@@ -185,7 +201,13 @@ G. M. Adelson-Velsky 和 E. M. Landis 在其 1962 年发表的论文 "An algorit
 === "Python"
 
     ```python title="avl_tree.py"
-    
+    """ 获取平衡因子 """
+    def balance_factor(self, node: TreeNode) -> int:
+        # 空结点平衡因子为 0
+        if node is None:
+            return 0
+        # 结点平衡因子 = 左子树高度 - 右子树高度
+        return self.height(node.left) - self.height(node.right)
     ```
 
 === "Go"
@@ -281,7 +303,18 @@ AVL 树的独特之处在于「旋转 Rotation」的操作，其可 **在不影
 === "Python"
 
     ```python title="avl_tree.py"
-    
+    """ 右旋操作 """
+    def __right_rotate(self, node: TreeNode) -> TreeNode:
+        child = node.left
+        grand_child = child.right
+        # 以 child 为原点，将 node 向右旋转
+        child.right = node
+        node.left = grand_child
+        # 更新结点高度
+        self.__update_height(node)
+        self.__update_height(child)
+        # 返回旋转后子树的根节点
+        return child
     ```
 
 === "Go"
@@ -363,7 +396,18 @@ AVL 树的独特之处在于「旋转 Rotation」的操作，其可 **在不影
 === "Python"
 
     ```python title="avl_tree.py"
-    
+    """ 左旋操作 """
+    def __left_rotate(self, node: TreeNode) -> TreeNode:
+        child = node.right
+        grand_child = child.left
+        # 以 child 为原点，将 node 向左旋转
+        child.left = node
+        node.right = grand_child
+        # 更新结点高度
+        self.__update_height(node)
+        self.__update_height(child)
+        # 返回旋转后子树的根节点
+        return child
     ```
 
 === "Go"
@@ -485,7 +529,30 @@ AVL 树的独特之处在于「旋转 Rotation」的操作，其可 **在不影
 === "Python"
 
     ```python title="avl_tree.py"
-    
+    """ 执行旋转操作，使该子树重新恢复平衡 """
+    def __rotate(self, node: TreeNode) -> TreeNode:
+        # 获取结点 node 的平衡因子
+        balance_factor = self.balance_factor(node)
+        # 左偏树
+        if balance_factor > 1:
+            if self.balance_factor(node.left) >= 0:
+                # 右旋
+                return self.__right_rotate(node)
+            else:
+                # 先左旋后右旋
+                node.left = self.__left_rotate(node.left)
+                return self.__right_rotate(node)
+        # 右偏树
+        elif balance_factor < -1:
+            if self.balance_factor(node.right) <= 0:
+                # 左旋
+                return self.__left_rotate(node)
+            else:
+                # 先右旋后左旋
+                node.right = self.__right_rotate(node.right)
+                return self.__left_rotate(node)
+        # 平衡树，无需旋转，直接返回
+        return node
     ```
 
 === "Go"
@@ -597,7 +664,27 @@ AVL 树的独特之处在于「旋转 Rotation」的操作，其可 **在不影
 === "Python"
 
     ```python title="avl_tree.py"
-    
+    """ 插入结点 """
+    def insert(self, val) -> TreeNode:
+        self.root = self.__insert_helper(self.root, val)
+        return self.root
+
+    """ 递归插入结点（辅助函数）"""
+    def __insert_helper(self, node: typing.Optional[TreeNode], val: int) -> TreeNode:
+        if node is None:
+            return TreeNode(val)
+        # 1. 查找插入位置，并插入结点
+        if val < node.val:
+            node.left = self.__insert_helper(node.left, val)
+        elif val > node.val:
+            node.right = self.__insert_helper(node.right, val)
+        else:
+            # 重复结点不插入，直接返回
+            return node
+        # 更新结点高度
+        self.__update_height(node)
+        # 2. 执行旋转操作，使该子树重新恢复平衡
+        return self.__rotate(node)
     ```
 
 === "Go"
@@ -717,7 +804,46 @@ AVL 树的独特之处在于「旋转 Rotation」的操作，其可 **在不影
 === "Python"
 
     ```python title="avl_tree.py"
-    
+    """ 删除结点 """
+    def remove(self, val: int):
+        root = self.__remove_helper(self.root, val)
+        return root
+
+    """ 递归删除结点（辅助函数） """
+    def __remove_helper(self, node: typing.Optional[TreeNode], val: int) -> typing.Optional[TreeNode]:
+        if node is None:
+            return None
+        # 1. 查找结点，并删除之
+        if val < node.val:
+            node.left = self.__remove_helper(node.left, val)
+        elif val > node.val:
+            node.right = self.__remove_helper(node.right, val)
+        else:
+            if node.left is None or node.right is None:
+                child = node.left or node.right
+                # 子结点数量 = 0 ，直接删除 node 并返回
+                if child is None:
+                    return None
+                # 子结点数量 = 1 ，直接删除 node
+                else:
+                    node = child
+            else:  # 子结点数量 = 2 ，则将中序遍历的下个结点删除，并用该结点替换当前结点
+                temp = self.min_node(node.right)
+                node.right = self.__remove_helper(node.right, temp.val)
+                node.val = temp.val
+        # 更新结点高度
+        self.__update_height(node)
+        # 2. 执行旋转操作，使该子树重新恢复平衡
+        return self.__rotate(node)
+
+    """ 获取最小结点 """
+    def min_node(self, node: typing.Optional[TreeNode]) -> typing.Optional[TreeNode]:
+        if node is None:
+            return None
+        # 循环访问左子结点，直到叶结点时为最小结点，跳出
+        while node.left is not None:
+            node = node.left
+        return node
     ```
 
 === "Go"
diff --git a/docs/chapter_tree/binary_search_tree.md b/docs/chapter_tree/binary_search_tree.md
index c2551e749..b341e3dc4 100644
--- a/docs/chapter_tree/binary_search_tree.md
+++ b/docs/chapter_tree/binary_search_tree.md
@@ -82,7 +82,21 @@ comments: true
 === "Python"
 
     ```python title="binary_search_tree.py"
-
+    """ 查找结点 """
+    def search(self, num: int) -> typing.Optional[TreeNode]:
+        cur = self.root
+        # 循环查找，越过叶结点后跳出
+        while cur is not None:
+            # 目标结点在 root 的右子树中
+            if cur.val < num:
+                cur = cur.right
+            # 目标结点在 root 的左子树中
+            elif cur.val > num:
+                cur = cur.left
+            # 找到目标结点，跳出循环
+            else:
+                break
+        return cur
     ```
 
 === "Go"
@@ -244,7 +258,35 @@ comments: true
 === "Python"
 
     ```python title="binary_search_tree.py"
+    """ 插入结点 """
+    def insert(self, num: int) -> typing.Optional[TreeNode]:
+        root = self.root
+        # 若树为空，直接提前返回
+        if root is None:
+            return None
 
+        cur = root
+        pre = None
+
+        # 循环查找，越过叶结点后跳出
+        while cur is not None:
+            # 找到重复结点，直接返回
+            if cur.val == num:
+                return None
+            pre = cur
+
+            if cur.val < num:  # 插入位置在 root 的右子树中
+                cur = cur.right
+            else:  # 插入位置在 root 的左子树中
+                cur = cur.left
+
+        # 插入结点 val
+        node = TreeNode(num)
+        if pre.val < num:
+            pre.right = node
+        else:
+            pre.left = node
+        return node
     ```
 
 === "Go"
@@ -525,7 +567,60 @@ comments: true
 === "Python"
 
     ```python title="binary_search_tree.py"
+    """ 删除结点 """
+    def remove(self, num: int) -> typing.Optional[TreeNode]:
+        root = self.root
+        # 若树为空，直接提前返回
+        if root is None:
+            return None
 
+        cur = root
+        pre = None
+
+        # 循环查找，越过叶结点后跳出
+        while cur is not None:
+            # 找到待删除结点，跳出循环
+            if cur.val == num:
+                break
+            pre = cur
+            if cur.val < num:  # 待删除结点在 root 的右子树中
+                cur = cur.right
+            else:  # 待删除结点在 root 的左子树中
+                cur = cur.left
+
+        # 若无待删除结点，则直接返回
+        if cur is None:
+            return None
+
+        # 子结点数量 = 0 or 1
+        if cur.left is None or cur.right is None:
+            # 当子结点数量 = 0 / 1 时， child = null / 该子结点
+            child = cur.left or cur.right
+            # 删除结点 cur
+            if pre.left == cur:
+                pre.left = child
+            else:
+                pre.right = child
+        # 子结点数量 = 2
+        else:
+            # 获取中序遍历中 cur 的下一个结点
+            nex = self.min(cur.right)
+            tmp = nex.val
+            # 递归删除结点 nex
+            self.remove(nex.val)
+            # 将 nex 的值复制给 cur
+            cur.val = tmp
+        return cur
+
+    """ 获取最小结点 """
+    def min(self, root: typing.Optional[TreeNode]) -> typing.Optional[TreeNode]:
+        if root is None:
+            return root
+
+        # 循环访问左子结点，直到叶结点时为最小结点，跳出
+        while root.left is not None:
+            root = root.left
+        return root
     ```
 
 === "Go"
@@ -761,14 +856,14 @@ comments: true
 
 - **查找元素：** 由于数组是无序的，因此需要遍历数组来确定，使用 $O(n)$ 时间；
 - **插入元素：** 只需将元素添加至数组尾部即可，使用 $O(1)$ 时间；
-- **删除元素：** 先查找元素，使用 $O(\log n)$ 时间，再在数组中删除该元素，使用 $O(n)$ 时间；
+- **删除元素：** 先查找元素，使用 $O(n)$ 时间，再在数组中删除该元素，使用 $O(n)$ 时间；
 - **获取最小 / 最大元素：** 需要遍历数组来确定，使用 $O(n)$ 时间；
 
 为了得到先验信息，我们也可以预先将数组元素进行排序，得到一个「排序数组」，此时操作效率为：
 
-- **查找元素：** 由于数组已排序，可以使用二分查找，使用 $O(\log n)$ 时间；
-- **插入元素：** 为了保持数组是有序的，需插入到数组某位置，平均使用 $O(n)$ 时间；
-- **删除元素：** 与无序数组中的情况相同，使用 $O(n)$ 时间；
+- **查找元素：** 由于数组已排序，可以使用二分查找，平均使用 $O(\log n)$ 时间；
+- **插入元素：** 先查找插入位置，使用 $O(\log n)$ 时间，再插入到指定位置，使用 $O(n)$ 时间；
+- **删除元素：** 先查找元素，使用 $O(\log n)$ 时间，再在数组中删除该元素，使用 $O(n)$ 时间；
 - **获取最小 / 最大元素：** 数组头部和尾部元素即是最小和最大元素，使用 $O(1)$ 时间；
 
 观察发现，无序数组和有序数组中的各项操作的时间复杂度是“偏科”的，即有的快有的慢；**而二叉搜索树的各项操作的时间复杂度都是对数阶，在数据量 $n$ 很大时有巨大优势**。
diff --git a/docs/chapter_tree/binary_tree.md b/docs/chapter_tree/binary_tree.md
index 9fc818128..07e311551 100644
--- a/docs/chapter_tree/binary_tree.md
+++ b/docs/chapter_tree/binary_tree.md
@@ -35,7 +35,7 @@ comments: true
     ```python title=""
     """ 链表结点类 """
     class TreeNode:
-        def __init__(self, val=0, left=None, right=None):
+        def __init__(self, val=None, left=None, right=None):
             self.val = val      # 结点值
             self.left = left    # 左子结点指针
             self.right = right  # 右子结点指针
@@ -44,13 +44,13 @@ comments: true
 === "Go"
 
     ```go title=""
-    """ 链表结点类 """
+    // 链表结点类
     type TreeNode struct {
         Val   int
         Left  *TreeNode
         Right *TreeNode
     }
-    """ 结点初始化方法 """
+    // 结点初始化方法
     func NewTreeNode(v int) *TreeNode {
         return &TreeNode{
             Left:  nil,
@@ -175,7 +175,18 @@ comments: true
 === "Python"
 
     ```python title="binary_tree.py"
-    
+    """ 初始化二叉树 """
+    # 初始化节点
+    n1 = TreeNode(val=1)
+    n2 = TreeNode(val=2)
+    n3 = TreeNode(val=3)
+    n4 = TreeNode(val=4)
+    n5 = TreeNode(val=5)
+    # 构建引用指向（即指针）
+    n1.left = n2
+    n1.right = n3
+    n2.left = n4
+    n2.right = n5
     ```
 
 === "Go"
@@ -284,7 +295,13 @@ comments: true
 === "Python"
 
     ```python title="binary_tree.py"
-    
+    """ 插入与删除结点 """
+    p = TreeNode(0)
+    # 在 n1 -> n2 中间插入结点 P
+    n1.left = p
+    p.left = n2
+    # 删除节点 P
+    n1.left = n2
     ```
 
 === "Go"
@@ -437,7 +454,7 @@ comments: true
 === "Python"
 
     ```python title=""
-    “”“ 二叉树的数组表示 ”“”
+    """ 二叉树的数组表示 """
     # 直接使用 None 来表示空位
     tree = [1, 2, 3, 4, None, 6, 7, 8, 9, None, None, 12, None, None, 15]
     ```
@@ -453,7 +470,7 @@ comments: true
     ```js title=""
     /* 二叉树的数组表示 */
     // 直接使用 null 来表示空位
-    let tree = [1, 2, 3, 4, 5, 6, 7, null, null, null, null, null, null, null, null]
+    let tree = [1, 2, 3, 4, null, 6, 7, 8, 9, null, null, 12, null, null, 15];
     ```
 
 === "TypeScript"
@@ -461,7 +478,7 @@ comments: true
     ```typescript title=""
     /* 二叉树的数组表示 */
     // 直接使用 null 来表示空位
-    let tree = [1, 2, 3, 4, 5, 6, 7, null, null, null, null, null, null, null, null]
+    let tree: (number | null)[] = [1, 2, 3, 4, null, 6, 7, 8, 9, null, null, 12, null, null, 15];
     ```
 
 === "C"
diff --git a/docs/chapter_tree/binary_tree_traversal.md b/docs/chapter_tree/binary_tree_traversal.md
index 971d24cc5..f46348412 100644
--- a/docs/chapter_tree/binary_tree_traversal.md
+++ b/docs/chapter_tree/binary_tree_traversal.md
@@ -51,12 +51,12 @@ comments: true
         vector<int> vec;
         while (!queue.empty()) {
             TreeNode* node = queue.front();
-            queue.pop();  // 队列出队
-            vec.push_back(node->val);            // 保存结点
+            queue.pop();                 // 队列出队
+            vec.push_back(node->val);    // 保存结点
             if (node->left != nullptr)
-                queue.push(node->left);    // 左子结点入队
+                queue.push(node->left);  // 左子结点入队
             if (node->right != nullptr)
-                queue.push(node->right);   // 右子结点入队
+                queue.push(node->right); // 右子结点入队
         }
         return vec;
     }
@@ -65,7 +65,21 @@ comments: true
 === "Python"
 
     ```python title="binary_tree_bfs.py"
-    
+    """ 层序遍历 """
+    def hier_order(root: TreeNode):
+        # 初始化队列，加入根结点
+        queue = collections.deque()
+        queue.append(root)
+        # 初始化一个列表，用于保存遍历序列
+        res = []
+        while queue:
+            node = queue.popleft()       # 队列出队
+            res.append(node.val)         # 保存节点值
+            if node.left is not None:
+                queue.append(node.left)  # 左子结点入队
+            if node.right is not None:
+                queue.append(node.right) # 右子结点入队
+        return res
     ```
 
 === "Go"
@@ -256,7 +270,32 @@ comments: true
 === "Python"
 
     ```python title="binary_tree_dfs.py"
-    
+    """ 前序遍历 """
+    def pre_order(root: typing.Optional[TreeNode]):
+        if root is None:
+            return
+        # 访问优先级：根结点 -> 左子树 -> 右子树
+        res.append(root.val)
+        pre_order(root=root.left)
+        pre_order(root=root.right)
+
+    """ 中序遍历 """
+    def in_order(root: typing.Optional[TreeNode]):
+        if root is None:
+            return
+        # 访问优先级：左子树 -> 根结点 -> 右子树
+        in_order(root=root.left)
+        res.append(root.val)
+        in_order(root=root.right)
+
+    """ 后序遍历 """
+    def post_order(root: typing.Optional[TreeNode]):
+        if root is None:
+            return
+        # 访问优先级：左子树 -> 右子树 -> 根结点
+        post_order(root=root.left)
+        post_order(root=root.right)
+        res.append(root.val)
     ```
 
 === "Go"
@@ -402,7 +441,6 @@ comments: true
         postOrder(root.right);
         list.Add(root.val);
     }
-    
     ```
 
 !!! note
diff --git a/docs/chapter_tree/summary.md b/docs/chapter_tree/summary.md
index 7edfbad71..a46a253f9 100644
--- a/docs/chapter_tree/summary.md
+++ b/docs/chapter_tree/summary.md
@@ -15,4 +15,4 @@ comments: true
 - 前序、中序、后序遍历是深度优先搜索，体现着“走到头、再回头继续”的回溯遍历方式，通常使用递归实现。
 - 二叉搜索树是一种高效的元素查找数据结构，查找、插入、删除操作的时间复杂度皆为 $O(\log n)$ 。二叉搜索树退化为链表后，各项时间复杂度劣化至 $O(n)$ ，因此如何避免退化是非常重要的课题。
 - AVL 树又称平衡二叉搜索树，其通过旋转操作，使得在不断插入与删除结点后，仍然可以保持二叉树的平衡（不退化）。
-- AVL 树的旋转操作分为右旋、左旋、先右旋后左旋、先左旋后右旋。在插入或删除结点后，AVL 树会从底置顶地执行旋转操作，使树恢复平衡。
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+- AVL 树的旋转操作分为右旋、左旋、先右旋后左旋、先左旋后右旋。在插入或删除结点后，AVL 树会从底置顶地执行旋转操作，使树恢复平衡。