hello-algo/codes/python/chapter_tree/binary_search_tree.py
2023-10-14 21:54:47 +08:00

145 lines
4.2 KiB
Python

"""
File: binary_search_tree.py
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 modules import *
class BinarySearchTree:
"""二叉搜索树"""
def __init__(self):
"""构造方法"""
# 初始化空树
self._root = None
def get_root(self) -> TreeNode | None:
"""获取二叉树根节点"""
return self._root
def search(self, num: int) -> TreeNode | None:
"""查找节点"""
cur = self._root
# 循环查找,越过叶节点后跳出
while cur is not None:
# 目标节点在 cur 的右子树中
if cur.val < num:
cur = cur.right
# 目标节点在 cur 的左子树中
elif cur.val > num:
cur = cur.left
# 找到目标节点,跳出循环
else:
break
return cur
def insert(self, num: int):
"""插入节点"""
# 若树为空,则初始化根节点
if self._root is None:
self._root = TreeNode(num)
return
# 循环查找,越过叶节点后跳出
cur, pre = self._root, None
while cur is not None:
# 找到重复节点,直接返回
if cur.val == num:
return
pre = cur
# 插入位置在 cur 的右子树中
if cur.val < num:
cur = cur.right
# 插入位置在 cur 的左子树中
else:
cur = cur.left
# 插入节点
node = TreeNode(num)
if pre.val < num:
pre.right = node
else:
pre.left = node
def remove(self, num: int):
"""删除节点"""
# 若树为空,直接提前返回
if self._root is None:
return
# 循环查找,越过叶节点后跳出
cur, pre = self._root, None
while cur is not None:
# 找到待删除节点,跳出循环
if cur.val == num:
break
pre = cur
# 待删除节点在 cur 的右子树中
if cur.val < num:
cur = cur.right
# 待删除节点在 cur 的左子树中
else:
cur = cur.left
# 若无待删除节点,则直接返回
if cur is None:
return
# 子节点数量 = 0 or 1
if cur.left is None or cur.right is None:
# 当子节点数量 = 0 / 1 时, child = null / 该子节点
child = cur.left or cur.right
# 删除节点 cur
if cur != self._root:
if pre.left == cur:
pre.left = child
else:
pre.right = child
else:
# 若删除节点为根节点,则重新指定根节点
self._root = child
# 子节点数量 = 2
else:
# 获取中序遍历中 cur 的下一个节点
tmp: TreeNode = cur.right
while tmp.left is not None:
tmp = tmp.left
# 递归删除节点 tmp
self.remove(tmp.val)
# 用 tmp 覆盖 cur
cur.val = tmp.val
"""Driver Code"""
if __name__ == "__main__":
# 初始化二叉搜索树
bst = BinarySearchTree()
nums = [8, 4, 12, 2, 6, 10, 14, 1, 3, 5, 7, 9, 11, 13, 15]
# 请注意,不同的插入顺序会生成不同的二叉树,该序列可以生成一个完美二叉树
for num in nums:
bst.insert(num)
print("\n初始化的二叉树为\n")
print_tree(bst.get_root())
# 查找节点
node = bst.search(7)
print("\n查找到的节点对象为: {},节点值 = {}".format(node, node.val))
# 插入节点
bst.insert(16)
print("\n插入节点 16 后,二叉树为\n")
print_tree(bst.get_root())
# 删除节点
bst.remove(1)
print("\n删除节点 1 后,二叉树为\n")
print_tree(bst.get_root())
bst.remove(2)
print("\n删除节点 2 后,二叉树为\n")
print_tree(bst.get_root())
bst.remove(4)
print("\n删除节点 4 后,二叉树为\n")
print_tree(bst.get_root())