hello-algo/codes/python/chapter_tree/binary_search_tree.py

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"""
File: binary_search_tree.py
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Created Time: 2022-12-20
Author: a16su (lpluls001@gmail.com)
"""
import sys, os.path as osp
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import typing
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from include import *
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""" 二叉搜索树 """
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class BinarySearchTree:
def __init__(self, nums: typing.List[int]) -> None:
nums.sort()
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self.__root = self.build_tree(nums, 0, len(nums) - 1)
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""" 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
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# 将数组中间结点作为根结点
mid = (start_index + end_index) // 2
root = TreeNode(nums[mid])
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# 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
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@property
def root(self) -> typing.Optional[TreeNode]:
return self.__root
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""" 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
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""" 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
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""" 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
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""" 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
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")
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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")
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print_tree(bst.root)
# 删除结点
bst.remove(1)
print("\n删除结点 1 后,二叉树为\n")
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print_tree(bst.root)
bst.remove(2)
print("\n删除结点 2 后,二叉树为\n")
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print_tree(bst.root)
bst.remove(4)
print("\n删除结点 4 后,二叉树为\n")
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print_tree(bst.root)