add binary_tree and avl_tree python code

pull/138/head
a16su 2 years ago
parent 2a1bb23990
commit 9eac1275f6
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@ -0,0 +1,281 @@
import sys, os.path as osp
import typing
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from include import *
class AVLTreeNode:
def __init__(
self,
val=None,
height: int = 0,
left: typing.Optional["AVLTreeNode"] = None,
right: typing.Optional["AVLTreeNode"] = None,
):
self.val = val
self.height = height
self.left = left
self.right = right
def __str__(self):
val = self.val
left_val = self.left.val if self.left else None
right_val = self.right.val if self.right else None
return "<AVLTreeNode: {}, leftAVLTreeNode: {}, rightAVLTreeNode: {}>".format(
val, left_val, right_val
)
class AVLTree:
def __init__(self, root: typing.Optional[AVLTreeNode] = None):
self.root = root
@staticmethod
def height(node: typing.Optional[AVLTreeNode]) -> int:
"""
获取结点高度
Args:
node:起始结点
Returns: 高度 or -1
"""
# 空结点高度为 -1 ,叶结点高度为 0
if node is not None:
return node.height
return -1
def __update_height(self, node: AVLTreeNode):
"""
更新结点高度
Args:
node: 要更新高度的结点
Returns: None
"""
# 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
def balance_factor(self, node: AVLTreeNode) -> int:
"""
获取结点平衡因子
Args:
node: 要获取平衡因子的结点
Returns: 平衡因子
"""
# 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)
def __right_rotate(self, node: AVLTreeNode) -> AVLTreeNode:
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
def __left_rotate(self, node: AVLTreeNode) -> AVLTreeNode:
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
def rotate(self, node: AVLTreeNode):
"""
执行旋转操作使该子树重新恢复平衡
Args:
node: 要旋转的根结点
Returns: 旋转后的根结点
"""
# 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
def insert(self, val) -> AVLTreeNode:
"""
插入结点
Args:
val: 结点的值
Returns:
node: 插入结点后的根结点
"""
self.root = self.insert_helper(self.root, val)
return self.root
def insert_helper(
self, node: typing.Optional[AVLTreeNode], val: int
) -> AVLTreeNode:
"""
递归插入结点辅助函数
Args:
node: 要插入的根结点
val: 要插入的结点的值
Returns: 插入结点后的根结点
"""
if node is None:
return AVLTreeNode(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)
def remove(self, val: int):
"""
删除结点
Args:
val: 要删除的结点的值
Returns:
"""
root = self.remove_helper(self.root, val)
return root
def remove_helper(
self, node: typing.Optional[AVLTreeNode], val: int
) -> typing.Optional[AVLTreeNode]:
"""
递归删除结点辅助函数
Args:
node: 删除的起始结点
val: 要删除的结点的值
Returns: 删除目标结点后的起始结点
"""
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)
def min_node(
self, node: typing.Optional[AVLTreeNode]
) -> typing.Optional[AVLTreeNode]:
# 获取最小结点
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
def search(self, val: int):
cur = self.root
while cur is not None:
if cur.val < val:
cur = cur.right
elif cur.val > val:
cur = cur.left
else:
break
return cur
if __name__ == "__main__":
def test_insert(tree: AVLTree, val: int):
tree.insert(val)
print("\n插入结点 {}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 {}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))

@ -1,10 +1,173 @@
'''
"""
File: binary_search_tree.py
Created Time: 2022-11-25
Author: Krahets (krahets@163.com)
'''
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from include import *
class BinarySearchTree:
"""
二叉搜索树
"""
def __init__(self, nums) -> None:
nums.sort()
self.__root = self.buildTree(nums, 0, len(nums) - 1)
def buildTree(self, nums, start_index, end_index):
if start_index > end_index:
return None
mid = (start_index + end_index) // 2
root = TreeNode(nums[mid])
root.left = self.buildTree(
nums=nums, start_index=start_index, end_index=mid - 1
)
root.right = self.buildTree(nums=nums, start_index=mid + 1, end_index=end_index)
return root
def get_root(self):
return self.__root
def search(self, num):
"""
查找结点
"""
cur = self.get_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
def insert(self, num):
"""
插入结点
"""
root = self.get_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
def remove(self, num):
"""
删除结点
"""
root = self.get_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
def min(self, root):
"""
获取最小结点
"""
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
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.get_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.get_root())
# 删除结点
bst.remove(1)
print("\n删除结点 1 后,二叉树为\n")
print_tree(bst.get_root())
bst.remove(2)
print("\n删除结点 2 后,二叉树为\n")
print_tree(bst.get_root())
bst.remove(4)
print("\n删除结点 4 后,二叉树为\n")
print_tree(bst.get_root())

@ -1,10 +1,38 @@
'''
"""
File: binary_tree.py
Created Time: 2022-11-25
Author: Krahets (krahets@163.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)
n1.left = n2
n1.right = n3
n2.left = n4
n2.right = n5
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_tree(n1)
# 删除结点
n1.left = n2
print_tree(n1)

@ -1,10 +1,45 @@
'''
"""
File: binary_tree_bfs.py
Created Time: 2022-11-25
Author: Krahets (krahets@163.com)
'''
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from include import *
def hierOrder(root):
# 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
result = []
while queue:
# 队列出队
node = queue.popleft()
# 保存节点值
result.append(node.val)
if node.left is not None:
# 左子结点入队
queue.append(node.left)
if node.right is not None:
# 右子结点入队
queue.append(node.right)
return result
""" 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
result = hierOrder(root)
print("\n层序遍历的结点打印序列 = ", result)
assert result == [1, 2, 3, 4, 5, 6, 7]

@ -1,10 +1,80 @@
'''
"""
File: binary_tree_dfs.py
Created Time: 2022-11-25
Author: Krahets (krahets@163.com)
'''
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from include import *
result = []
def preOrder(root):
"""
前序遍历二叉树
"""
if root is None:
return
# 访问优先级:根结点 -> 左子树 -> 右子树
result.append(root.val)
preOrder(root=root.left)
preOrder(root=root.right)
def inOrder(root):
"""
中序遍历二叉树
"""
if root is None:
return
# 访问优先级:左子树 -> 根结点 -> 右子树
inOrder(root=root.left)
result.append(root.val)
inOrder(root=root.right)
def postOrder(root):
"""
后序遍历二叉树
"""
if root is None:
return
# 访问优先级:左子树 -> 右子树 -> 根结点
postOrder(root=root.left)
postOrder(root=root.right)
result.append(root.val)
""" 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)
# 前序遍历
result = []
preOrder(root)
print("\n前序遍历的结点打印序列 = ", result)
assert result == [1, 2, 4, 5, 3, 6, 7]
# 中序遍历
result = []
inOrder(root)
print("\n中序遍历的结点打印序列 = ", result)
assert result == [4, 2, 5, 1, 6, 3, 7]
# 后序遍历
result = []
postOrder(root)
print("\n后序遍历的结点打印序列 = ", result)
assert result == [4, 5, 2, 6, 7, 3, 1]

@ -9,7 +9,7 @@ import collections
class TreeNode:
"""Definition for a binary tree node
"""
def __init__(self, val=0, left=None, right=None):
def __init__(self, val=None, left=None, right=None):
self.val = val
self.left = left
self.right = right

@ -48,7 +48,24 @@ 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"
class AVLTreeNode:
def __init__(
self,
val=None,
height: int = 0,
left: typing.Optional["AVLTreeNode"] = None,
right: typing.Optional["AVLTreeNode"] = None
):
self.val = val
self.height = height
self.left = left
self.right = right
def __str__(self):
val = self.val
left_val = self.left.val if self.left else None
right_val = self.right.val if self.right else None
return "<AVLTreeNode: {}, leftAVLTreeNode: {}, rightAVLTreeNode: {}>".format(val, left_val, right_val)
```
=== "Go"
@ -108,7 +125,31 @@ 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"
def height(node: typing.Optional[AVLTreeNode]) -> int:
"""
获取结点高度
Args:
node:起始结点
Returns: 高度 or -1
"""
# 空结点高度为 -1 ,叶结点高度为 0
if node is not None:
return node.height
return -1
def update_height(node: AVLTreeNode):
"""
更新结点高度
Args:
node: 要更新高度的结点
Returns: None
"""
# 结点高度等于最高子树高度 + 1
node.height = max([height(node.left), height(node.right)]) + 1
```
=== "Go"
@ -166,7 +207,20 @@ 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"
def balance_factor(node: AVLTreeNode) -> int:
"""
获取结点平衡因子
Args:
node: 要获取平衡因子的结点
Returns: 平衡因子
"""
# 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 height(node.left) - height(node.right)
```
=== "Go"
@ -255,7 +309,17 @@ 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"
def rightRotate(node: AVLTreeNode):
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
update_height(node)
update_height(child)
# 返回旋转后子树的根节点
return child
```
=== "Go"
@ -323,7 +387,17 @@ 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"
def leftRotate(node: AVLTreeNode):
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
update_height(node)
update_height(child)
# 返回旋转后子树的根节点
return child
```
=== "Go"
@ -432,7 +506,37 @@ 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"
def rotate(node: AVLTreeNode):
"""
执行旋转操作,使该子树重新恢复平衡
Args:
node: 要旋转的根结点
Returns: 旋转后的根结点
"""
# 获取结点 node 的平衡因子
factor = balance_factor(node)
# 左偏树
if factor > 1:
if balance_factor(node.left) >= 0:
# 右旋
return right_rotate(node)
else:
# 先左旋后右旋
node.left = left_rotate(node.left)
return right_rotate(node)
# 右偏树
elif factor < -1:
if balance_factor(node.right) <= 0:
# 左旋
return left_rotate(node)
else:
# 先右旋后左旋
node.right = right_rotate(node.right)
return left_rotate(node)
# 平衡树,无需旋转,直接返回
return node
```
=== "Go"
@ -507,7 +611,42 @@ 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"
def insert(val) -> AVLTreeNode:
"""
插入结点
Args:
val: 结点的值
Returns:
node: 插入结点后的根结点
"""
root = insert_helper(root, val)
return root
def insert_helper(node: typing.Optional[AVLTreeNode], val: int) -> AVLTreeNode:
"""
递归插入结点(辅助函数)
Args:
node: 要插入的根结点
val: 要插入的结点的值
Returns: 插入结点后的根结点
"""
if node is None:
return AVLTreeNode(val)
# 1. 查找插入位置,并插入结点
if val < node.val:
node.left = insert_helper(node.left, val)
elif val > node.val:
node.right = 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
update_height(node)
# 2. 执行旋转操作,使该子树重新恢复平衡
return rotate(node)
```
=== "Go"
@ -604,7 +743,62 @@ 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"
def remove(val: int):
"""
删除结点
Args:
val: 要删除的结点的值
Returns:
"""
root = remove_helper(root, val)
return root
def remove_helper(node: typing.Optional[AVLTreeNode], val: int) -> typing.Optional[AVLTreeNode]:
"""
递归删除结点(辅助函数)
Args:
node: 删除的起始结点
val: 要删除的结点的值
Returns: 删除目标结点后的起始结点
"""
if node is None:
return None
# 1. 查找结点,并删除之
if val < node.val:
node.left = remove_helper(node.left, val)
elif val > node.val:
node.right = 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 = min_node(node.right)
node.right = remove_helper(node.right, temp.val)
node.val = temp.val
# 更新结点高度
update_height(node)
# 2. 执行旋转操作,使该子树重新恢复平衡
return rotate(node)
def min_node(node: typing.Optional[AVLTreeNode]) -> typing.Optional[AVLTreeNode]:
# 获取最小结点
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"

@ -82,6 +82,23 @@ comments: true
=== "Python"
```python title="binary_search_tree.py"
def search(self, num):
"""
查找结点
"""
cur = self.get_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
```
@ -228,7 +245,37 @@ comments: true
=== "Python"
```python title="binary_search_tree.py"
def insert(self, num):
"""
插入结点
"""
root = self.get_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: # root
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"
@ -483,7 +530,64 @@ comments: true
=== "Python"
```python title="binary_search_tree.py"
def remove(self, num):
"""
删除结点
"""
root = self.get_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: # root
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
def min(self, root):
"""
获取最小结点
"""
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"

@ -33,9 +33,9 @@ comments: true
=== "Python"
```python title=""
""" 链表结点类 """
class TreeNode:
def __init__(self, val=0, left=None, right=None):
""" 链表结点类 """
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
@ -190,7 +190,18 @@ 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"
@ -288,7 +299,13 @@ 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"
@ -406,7 +423,24 @@ comments: true
=== "Python"
```python title="binary_tree_bfs.py"
def hierOrder(root):
# 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
result = []
while queue:
# 队列出队
node = queue.popleft()
# 保存节点值
result.append(node.val)
if node.left is not None:
# 左子结点入队
queue.append(node.left)
if node.right is not None:
# 右子结点入队
queue.append(node.right)
return result
```
=== "Go"
@ -578,7 +612,43 @@ comments: true
=== "Python"
```python title="binary_tree_dfs.py"
def preOrder(root):
"""
前序遍历二叉树
"""
if root is None:
return
# 访问优先级:根结点 -> 左子树 -> 右子树
result.append(root.val)
preOrder(root=root.left)
preOrder(root=root.right)
def inOrder(root):
"""
中序遍历二叉树
"""
if root is None:
return
# 访问优先级:左子树 -> 根结点 -> 右子树
inOrder(root=root.left)
result.append(root.val)
inOrder(root=root.right)
def postOrder(root):
"""
后序遍历二叉树
"""
if root is None:
return
# 访问优先级:左子树 -> 右子树 -> 根结点
postOrder(root=root.left)
postOrder(root=root.right)
result.append(root.val)
```
=== "Go"

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