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refactor: Follow the PEP 585 Typing standard (#439)

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* Follow the PEP 585 Typing standard

* Update list.py
pull/441/head
Yudong Jin 2 years ago committed by GitHub
parent f4e01ea32e
commit 8918ec9079
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GPG Key ID: 4AEE18F83AFDEB23
43 changed files with 256 additions and 342 deletions
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2
codes/python/.gitignore vendored
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@ -1 +1,3 @@
__pycache__
test_all.sh

22
codes/python/chapter_array_and_linkedlist/array.py
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@ -4,11 +4,9 @@ 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 modules import *
import random
def random_access(nums: List[int]) -> int:
def random_access(nums: list[int]) -> int:
""" 随机访问元素 """
# 在区间 [0, len(nums)-1] 中随机抽取一个数字
random_index = random.randint(0, len(nums) - 1)
@ -18,7 +16,7 @@ def random_access(nums: List[int]) -> int:
# 请注意，Python 的 list 是动态数组，可以直接扩展
# 为了方便学习，本函数将 list 看作是长度不可变的数组
def extend(nums: List[int], enlarge: int) -> List[int]:
def extend(nums: list[int], enlarge: int) -> list[int]:
""" 扩展数组长度 """
# 初始化一个扩展长度后的数组
res = [0] * (len(nums) + enlarge)
@ -28,7 +26,7 @@ def extend(nums: List[int], enlarge: int) -> List[int]:
# 返回扩展后的新数组
return res
def insert(nums: List[int], num: int, index: int) -> None:
def insert(nums: list[int], num: int, index: int) -> None:
""" 在数组的索引 index 处插入元素 num """
# 把索引 index 以及之后的所有元素向后移动一位
for i in range(len(nums) - 1, index, -1):
@ -36,13 +34,13 @@ def insert(nums: List[int], num: int, index: int) -> None:
# 将 num 赋给 index 处元素
nums[index] = num
def remove(nums: List[int], index: int) -> None:
def remove(nums: list[int], index: int) -> None:
""" 删除索引 index 处元素 """
# 把索引 index 之后的所有元素向前移动一位
for i in range(index, len(nums) - 1):
nums[i] = nums[i + 1]
def traverse(nums: List[int]) -> None:
def traverse(nums: list[int]) -> None:
""" 遍历数组 """
count = 0
# 通过索引遍历数组
@ -52,7 +50,7 @@ def traverse(nums: List[int]) -> None:
for num in nums:
count += 1
def find(nums: List[int], target: int) -> int:
def find(nums: list[int], target: int) -> int:
""" 在数组中查找指定元素 """
for i in range(len(nums)):
if nums[i] == target:
@ -62,9 +60,9 @@ def find(nums: List[int], target: int) -> int:
""" Driver Code """
if __name__ == "__main__":
""" 初始化数组 """
arr: List[int] = [0] * 5
arr: list[int] = [0] * 5
print("数组 arr =", arr)
nums: List[int] = [1, 3, 2, 5, 4]
nums: list[int] = [1, 3, 2, 5, 4]
print("数组 nums =", nums)
""" 随机访问 """
@ -72,7 +70,7 @@ if __name__ == "__main__":
print("在 nums 中获取随机元素", random_num)
""" 长度扩展 """
nums: List[int] = extend(nums, 3)
nums: list[int] = extend(nums, 3)
print("将数组长度扩展至 8 ，得到 nums =", nums)
""" 插入元素 """

2
codes/python/chapter_array_and_linkedlist/linked_list.py
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@ -23,7 +23,7 @@ def remove(n0: ListNode) -> None:
n1 = P.next
n0.next = n1
def access(head: ListNode, index: int) -> Optional[ListNode]:
def access(head: ListNode, index: int) -> ListNode | None:
""" 访问链表中索引为 index 的结点 """
for _ in range(index):
if not head:

53
codes/python/chapter_array_and_linkedlist/list.py
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@ -4,60 +4,55 @@ 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 modules import *
""" Driver Code """
if __name__ == "__main__":
""" 初始化列表 """
list: List[int] = [1, 3, 2, 5, 4]
print("列表 list =", list)
arr: list[int] = [1, 3, 2, 5, 4]
print("列表 arr =", arr)
""" 访问元素 """
num: int = list[1]
num: int = arr[1]
print("访问索引 1 处的元素，得到 num =", num)
""" 更新元素 """
list[1] = 0
print("将索引 1 处的元素更新为 0 ，得到 list =", list)
arr[1] = 0
print("将索引 1 处的元素更新为 0 ，得到 arr =", arr)
""" 清空列表 """
list.clear()
print("清空列表后 list =", list)
arr.clear()
print("清空列表后 arr =", arr)
""" 尾部添加元素 """
list.append(1)
list.append(3)
list.append(2)
list.append(5)
list.append(4)
print("添加元素后 list =", list)
arr.append(1)
arr.append(3)
arr.append(2)
arr.append(5)
arr.append(4)
print("添加元素后 arr =", arr)
""" 中间插入元素 """
list.insert(3, 6)
print("在索引 3 处插入数字 6 ，得到 list =", list)
arr.insert(3, 6)
print("在索引 3 处插入数字 6 ，得到 arr =", arr)
""" 删除元素 """
list.pop(3)
print("删除索引 3 处的元素，得到 list =", list)
arr.pop(3)
print("删除索引 3 处的元素，得到 arr =", arr)
""" 通过索引遍历列表 """
count: int = 0
for i in range(len(list)):
for i in range(len(arr)):
count += 1
""" 直接遍历列表元素 """
count: int = 0
for n in list:
for n in arr:
count += 1
""" 拼接两个列表 """
list1: List[int] = [6, 8, 7, 10, 9]
list += list1
print("将列表 list1 拼接到 list 之后，得到 list =", list)
arr1: list[int] = [6, 8, 7, 10, 9]
arr += arr1
print("将列表 arr1 拼接到 arr 之后，得到 arr =", arr)
""" 排序列表 """
list.sort()
print("排序列表后 list =", list)
arr.sort()
print("排序列表后 arr =", arr)

44
codes/python/chapter_array_and_linkedlist/my_list.py
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@ -4,16 +4,12 @@ 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 modules import *
class MyList:
""" 列表类简易实现 """
def __init__(self):
""" 构造方法 """
self.__capacity: int = 10 # 列表容量
self.__nums: List[int] = [0] * self.__capacity # 数组（存储列表元素）
self.__nums: my_list[int] = [0] * self.__capacity # 数组（存储列表元素）
self.__size: int = 0 # 列表长度（即当前元素数量）
self.__extend_ratio: int = 2 # 每次列表扩容的倍数
@ -76,7 +72,7 @@ class MyList:
# 更新列表容量
self.__capacity = len(self.__nums)
def to_array(self) -> List[int]:
def to_array(self) -> list[int]:
""" 返回有效长度的列表 """
return self.__nums[:self.__size]
@ -84,35 +80,35 @@ class MyList:
""" Driver Code """
if __name__ == "__main__":
""" 初始化列表 """
list = MyList()
my_list = MyList()
""" 尾部添加元素 """
list.add(1)
list.add(3)
list.add(2)
list.add(5)
list.add(4)
print("列表 list = {} ，容量 = {} ，长度 = {}"
.format(list.to_array(), list.capacity(), list.size()))
my_list.add(1)
my_list.add(3)
my_list.add(2)
my_list.add(5)
my_list.add(4)
print("列表 my_list = {} ，容量 = {} ，长度 = {}"
.format(my_list.to_array(), my_list.capacity(), my_list.size()))
""" 中间插入元素 """
list.insert(6, index=3)
print("在索引 3 处插入数字 6 ，得到 list =", list.to_array())
my_list.insert(6, index=3)
print("在索引 3 处插入数字 6 ，得到 my_list =", my_list.to_array())
""" 删除元素 """
list.remove(3)
print("删除索引 3 处的元素，得到 list =", list.to_array())
my_list.remove(3)
print("删除索引 3 处的元素，得到 my_list =", my_list.to_array())
""" 访问元素 """
num = list.get(1)
num = my_list.get(1)
print("访问索引 1 处的元素，得到 num =", num)
""" 更新元素 """
list.set(0, 1)
print("将索引 1 处的元素更新为 0 ，得到 list =", list.to_array())
my_list.set(0, 1)
print("将索引 1 处的元素更新为 0 ，得到 my_list =", my_list.to_array())
""" 测试扩容机制 """
for i in range(10):
# 在 i = 5 时，列表长度将超出列表容量，此时触发扩容机制
list.add(i)
print("扩容后的列表 list = {} ，容量 = {} ，长度 = {}"
.format(list.to_array(), list.capacity(), list.size()))
my_list.add(i)
print("扩容后的列表 my_list = {} ，容量 = {} ，长度 = {}"
.format(my_list.to_array(), my_list.capacity(), my_list.size()))

12
codes/python/chapter_computational_complexity/leetcode_two_sum.py
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@ -4,11 +4,7 @@ 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 modules import *
def two_sum_brute_force(nums: List[int], target: int) -> List[int]:
def two_sum_brute_force(nums: list[int], target: int) -> list[int]:
""" 方法一：暴力枚举 """
# 两层循环，时间复杂度 O(n^2)
for i in range(len(nums) - 1):
@ -17,7 +13,7 @@ def two_sum_brute_force(nums: List[int], target: int) -> List[int]:
return [i, j]
return []
def two_sum_hash_table(nums: List[int], target: int) -> List[int]:
def two_sum_hash_table(nums: list[int], target: int) -> list[int]:
""" 方法二：辅助哈希表 """
# 辅助哈希表，空间复杂度 O(n)
dic = {}
@ -37,8 +33,8 @@ if __name__ == '__main__':
# ====== Driver Code ======
# 方法一
res: List[int] = two_sum_brute_force(nums, target)
res: list[int] = two_sum_brute_force(nums, target)
print("方法一 res =", res)
# 方法二
res: List[int] = two_sum_hash_table(nums, target)
res: list[int] = two_sum_hash_table(nums, target)
print("方法二 res =", res)

14
codes/python/chapter_computational_complexity/space_complexity.py
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@ -17,7 +17,7 @@ def constant(n: int) -> None:
""" 常数阶 """
# 常量、变量、对象占用 O(1) 空间
a: int = 0
nums: List[int] = [0] * 10000
nums: list[int] = [0] * 10000
node = ListNode(0)
# 循环中的变量占用 O(1) 空间
for _ in range(n):
@ -29,9 +29,9 @@ def constant(n: int) -> None:
def linear(n: int) -> None:
""" 线性阶 """
# 长度为 n 的列表占用 O(n) 空间
nums: List[int] = [0] * n
nums: list[int] = [0] * n
# 长度为 n 的哈希表占用 O(n) 空间
mapp: Dict = {}
mapp = dict[int, str]()
for i in range(n):
mapp[i] = str(i)
@ -44,16 +44,16 @@ def linear_recur(n: int) -> None:
def quadratic(n: int) -> None:
""" 平方阶 """
# 二维列表占用 O(n^2) 空间
num_matrix: List[List[int]] = [[0] * n for _ in range(n)]
num_matrix: list[list[int]] = [[0] * n for _ in range(n)]
def quadratic_recur(n: int) -> int:
""" 平方阶（递归实现） """
if n <= 0: return 0
# 数组 nums 长度为 n, n-1, ..., 2, 1
nums: List[int] = [0] * n
nums: list[int] = [0] * n
return quadratic_recur(n - 1)
def build_tree(n: int) -> Optional[TreeNode]:
def build_tree(n: int) -> TreeNode | None:
""" 指数阶（建立满二叉树） """
if n == 0: return None
root = TreeNode(0)
@ -74,5 +74,5 @@ if __name__ == "__main__":
quadratic(n)
quadratic_recur(n)
# 指数阶
root: Optional[TreeNode] = build_tree(n)
root = build_tree(n)
print_tree(root)

10
codes/python/chapter_computational_complexity/time_complexity.py
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@ -4,10 +4,6 @@ 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 modules import *
def constant(n: int) -> int:
""" 常数阶 """
count: int = 0
@ -23,7 +19,7 @@ def linear(n: int) -> int:
count += 1
return count
def array_traversal(nums: List[int]) -> int:
def array_traversal(nums: list[int]) -> int:
""" 线性阶（遍历数组）"""
count: int = 0
# 循环次数与数组长度成正比
@ -40,7 +36,7 @@ def quadratic(n: int) -> int:
count += 1
return count
def bubble_sort(nums: List[int]) -> int:
def bubble_sort(nums: list[int]) -> int:
""" 平方阶（冒泡排序）"""
count: int = 0 # 计数器
# 外循环：待排序元素数量为 n-1, n-2, ..., 1
@ -120,7 +116,7 @@ if __name__ == "__main__":
count: int = quadratic(n)
print("平方阶的计算操作数量 =", count)
nums: List[int] = [i for i in range(n, 0, -1)] # [n,n-1,...,2,1]
nums: list[int] = [i for i in range(n, 0, -1)] # [n,n-1,...,2,1]
count: int = bubble_sort(nums)
print("平方阶（冒泡排序）的计算操作数量 =", count)

12
codes/python/chapter_computational_complexity/worst_best_time_complexity.py
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@ -4,19 +4,17 @@ 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 modules import *
import random
def random_numbers(n: int) -> List[int]:
def random_numbers(n: int) -> list[int]:
""" 生成一个数组，元素为: 1, 2, ..., n ，顺序被打乱 """
# 生成数组 nums =: 1, 2, 3, ..., n
nums: List[int] = [i for i in range(1, n + 1)]
nums: list[int] = [i for i in range(1, n + 1)]
# 随机打乱数组元素
random.shuffle(nums)
return nums
def find_one(nums: List[int]) -> int:
def find_one(nums: list[int]) -> int:
""" 查找数组 nums 中数字 1 所在索引 """
for i in range(len(nums)):
# 当元素 1 在数组头部时，达到最佳时间复杂度 O(1)
@ -30,7 +28,7 @@ def find_one(nums: List[int]) -> int:
if __name__ == "__main__":
for i in range(10):
n: int = 100
nums: List[int] = random_numbers(n)
nums: list[int] = random_numbers(n)
index: int = find_one(nums)
print("\n数组 [ 1, 2, ..., n ] 被打乱后 =", nums)
print("数字 1 的索引为", index)

4
codes/python/chapter_graph/graph_adjacency_list.py
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@ -10,10 +10,10 @@ from modules import *
class GraphAdjList:
""" 基于邻接表实现的无向图类 """
def __init__(self, edges: List[List[Vertex]]) -> None:
def __init__(self, edges: list[list[Vertex]]) -> None:
""" 构造方法 """
# 邻接表，key: 顶点，value：该顶点的所有邻接顶点
self.adj_list: Dict = {}
self.adj_list = dict[Vertex, Vertex]()
# 添加所有顶点和边
for edge in edges:
self.add_vertex(edge[0])

14
codes/python/chapter_graph/graph_adjacency_matrix.py
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@ -11,14 +11,14 @@ from modules import *
class GraphAdjMat:
""" 基于邻接矩阵实现的无向图类 """
# 顶点列表，元素代表“顶点值”，索引代表“顶点索引”
vertices: List[int] = []
vertices: list[int] = []
# 邻接矩阵，行列索引对应“顶点索引”
adj_mat: List[List[int]] = []
adj_mat: list[list[int]] = []
def __init__(self, vertices: List[int], edges: List[List[int]]) -> None:
def __init__(self, vertices: list[int], edges: list[list[int]]) -> None:
""" 构造方法 """
self.vertices: List[int] = []
self.adj_mat: List[List[int]] = []
self.vertices: list[int] = []
self.adj_mat: list[list[int]] = []
# 添加顶点
for val in vertices:
self.add_vertex(val)
@ -85,8 +85,8 @@ class GraphAdjMat:
if __name__ == "__main__":
""" 初始化无向图 """
# 请注意，edges 元素代表顶点索引，即对应 vertices 元素索引
vertices: List[int] = [1, 3, 2, 5, 4]
edges: List[List[int]] = [[0, 1], [0, 3], [1, 2], [2, 3], [2, 4], [3, 4]]
vertices: list[int] = [1, 3, 2, 5, 4]
edges: list[list[int]] = [[0, 1], [0, 3], [1, 2], [2, 3], [2, 4], [3, 4]]
graph = GraphAdjMat(vertices, edges)
print("\n初始化后，图为")
graph.print()

7
codes/python/chapter_graph/graph_bfs.py
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@ -7,17 +7,18 @@ Author: Krahets (krahets@163.com)
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
from collections import deque
from graph_adjacency_list import GraphAdjList
def graph_bfs(graph: GraphAdjList, start_vet: Vertex) -> List[Vertex]:
def graph_bfs(graph: GraphAdjList, start_vet: Vertex) -> list[Vertex]:
""" 广度优先遍历 BFS """
# 使用邻接表来表示图，以便获取指定顶点的所有邻接顶点
# 顶点遍历序列
res = []
# 哈希表，用于记录已被访问过的顶点
visited = set([start_vet])
visited = set[Vertex]([start_vet])
# 队列用于实现 BFS
que = collections.deque([start_vet])
que = deque[Vertex]([start_vet])
# 以顶点 vet 为起点，循环直至访问完所有顶点
while len(que) > 0:
vet = que.popleft() # 队首顶点出队

6
codes/python/chapter_graph/graph_dfs.py
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@ -9,7 +9,7 @@ sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
from graph_adjacency_list import GraphAdjList
def dfs(graph: GraphAdjList, visited: Set[Vertex], res: List[Vertex], vet: Vertex):
def dfs(graph: GraphAdjList, visited: set[Vertex], res: list[Vertex], vet: Vertex):
""" 深度优先遍历 DFS 辅助函数 """
res.append(vet) # 记录访问顶点
visited.add(vet) # 标记该顶点已被访问
@ -21,12 +21,12 @@ def dfs(graph: GraphAdjList, visited: Set[Vertex], res: List[Vertex], vet: Verte
dfs(graph, visited, res, adjVet)
# 使用邻接表来表示图，以便获取指定顶点的所有邻接顶点
def graph_dfs(graph: GraphAdjList, start_vet: Vertex) -> List[Vertex]:
def graph_dfs(graph: GraphAdjList, start_vet: Vertex) -> list[Vertex]:
""" 深度优先遍历 DFS """
# 顶点遍历序列
res = []
# 哈希表，用于记录已被访问过的顶点
visited = set()
visited = set[Vertex]()
dfs(graph, visited, res, start_vet)
return res

18
codes/python/chapter_hashing/array_hash_map.py
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@ -4,10 +4,6 @@ Created Time: 2022-12-14
Author: msk397 (machangxinq@gmail.com)
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
class Entry:
""" 键值对 int->String """
def __init__(self, key: int, val: str):
@ -19,7 +15,7 @@ class ArrayHashMap:
def __init__(self):
""" 构造方法 """
# 初始化数组，包含 100 个桶
self.buckets: List[Optional[Entry]] = [None] * 100
self.buckets: list[Entry | None] = [None] * 100
def hash_func(self, key: int) -> int:
""" 哈希函数 """
@ -46,25 +42,25 @@ class ArrayHashMap:
# 置为 None ，代表删除
self.buckets[index] = None
def entry_set(self) -> List[Entry]:
def entry_set(self) -> list[Entry]:
""" 获取所有键值对 """
result: List[Entry] = []
result: list[Entry] = []
for pair in self.buckets:
if pair is not None:
result.append(pair)
return result
def key_set(self) -> List[int]:
def key_set(self) -> list[int]:
""" 获取所有键 """
result: List[int] = []
result: list[int] = []
for pair in self.buckets:
if pair is not None:
result.append(pair.key)
return result
def value_set(self) -> List[str]:
def value_set(self) -> list[str]:
""" 获取所有值 """
result: List[str] = []
result: list[str] = []
for pair in self.buckets:
if pair is not None:
result.append(pair.val)

3
codes/python/chapter_hashing/hash_map.py
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@ -8,11 +8,10 @@ import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
""" Driver Code """
if __name__ == "__main__":
""" 初始化哈希表 """
mapp: Dict = {}
mapp = dict[int, str]()
""" 添加操作 """
# 在哈希表中添加键值对 (key, value)

11
codes/python/chapter_heap/heap.py
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@ -4,18 +4,19 @@ Created Time: 2023-02-23
Author: Krahets (krahets@163.com)
"""
import sys
import os.path as osp
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
import heapq
def test_push(heap: List, val: int, flag: int = 1) -> None:
def test_push(heap: list, val: int, flag: int = 1) -> None:
heapq.heappush(heap, flag * val) # 元素入堆
print(f"\n元素 {val} 入堆后")
print_heap([flag * val for val in heap])
def test_pop(heap: List, flag: int = 1) -> None:
def test_pop(heap: list, flag: int = 1) -> None:
val = flag * heapq.heappop(heap) # 堆顶元素出堆
print(f"\n堆顶元素 {val} 出堆后")
print_heap([flag * val for val in heap])
@ -59,7 +60,7 @@ if __name__ == "__main__":
""" 输入列表并建堆 """
# 时间复杂度为 O(n) ，而非 O(nlogn)
min_heap: List[int] = [1, 3, 2, 5, 4]
min_heap: list[int] = [1, 3, 2, 5, 4]
heapq.heapify(min_heap)
print("\n输入列表并建立小顶堆后")
print_heap(min_heap)

2
codes/python/chapter_heap/my_heap.py
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@ -10,7 +10,7 @@ from modules import *
class MaxHeap:
""" 大顶堆 """
def __init__(self, nums: List[int]):
def __init__(self, nums: list[int]):
""" 构造方法 """
# 将列表元素原封不动添加进堆
self.max_heap = nums

10
codes/python/chapter_searching/binary_search.py
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@ -4,11 +4,7 @@ Created Time: 2022-11-26
Author: timi (xisunyy@163.com)
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
def binary_search(nums: List[int], target: int) -> int:
def binary_search(nums: list[int], target: int) -> int:
""" 二分查找（双闭区间） """
# 初始化双闭区间 [0, n-1] ，即 i, j 分别指向数组首元素、尾元素
i, j = 0, len(nums) - 1
@ -23,7 +19,7 @@ def binary_search(nums: List[int], target: int) -> int:
return -1 # 未找到目标元素，返回 -1
def binary_search1(nums: List[int], target: int) -> int:
def binary_search1(nums: list[int], target: int) -> int:
""" 二分查找（左闭右开） """
# 初始化左闭右开 [0, n) ，即 i, j 分别指向数组首元素、尾元素+1
i, j = 0, len(nums)
@ -42,7 +38,7 @@ def binary_search1(nums: List[int], target: int) -> int:
""" Driver Code """
if __name__ == '__main__':
target: int = 6
nums: List[int] = [1, 3, 6, 8, 12, 15, 23, 67, 70, 92]
nums: list[int] = [1, 3, 6, 8, 12, 15, 23, 67, 70, 92]
# 二分查找（双闭区间）
index: int = binary_search(nums, target)

14
codes/python/chapter_searching/hashing_search.py
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@ -8,13 +8,13 @@ import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
def hashing_search_array(mapp: Dict[int, int], target: int) -> int:
def hashing_search_array(mapp: dict[int, int], target: int) -> int:
""" 哈希查找（数组） """
# 哈希表的 key: 目标元素，value: 索引
# 若哈希表中无此 key ，返回 -1
return mapp.get(target, -1)
def hashing_search_linkedlist(mapp: Dict[int, ListNode], target: int) -> Optional[ListNode]:
def hashing_search_linkedlist(mapp: dict[int, ListNode], target: int) -> ListNode | None:
""" 哈希查找（链表） """
# 哈希表的 key: 目标元素，value: 结点对象
# 若哈希表中无此 key ，返回 None
@ -26,18 +26,18 @@ if __name__ == '__main__':
target: int = 3
# 哈希查找（数组）
nums: List[int] = [1, 5, 3, 2, 4, 7, 5, 9, 10, 8]
nums: list[int] = [1, 5, 3, 2, 4, 7, 5, 9, 10, 8]
# 初始化哈希表
mapp: Dict[int, int] = {}
map0 = dict[int, int]()
for i in range(len(nums)):
mapp[nums[i]] = i # key: 元素，value: 索引
index: int = hashing_search_array(mapp, target)
map0[nums[i]] = i # key: 元素，value: 索引
index: int = hashing_search_array(map0, target)
print("目标元素 3 的索引 =", index)
# 哈希查找（链表）
head: ListNode = list_to_linked_list(nums)
# 初始化哈希表
map1: Dict[int, ListNode] = {}
map1 = dict[int, ListNode]()
while head:
map1[head.val] = head # key: 结点值，value: 结点
head = head.next

8
codes/python/chapter_searching/linear_search.py
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@ -8,7 +8,7 @@ import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
def linear_search_array(nums: List[int], target: int) -> int:
def linear_search_array(nums: list[int], target: int) -> int:
""" 线性查找（数组） """
# 遍历数组
for i in range(len(nums)):
@ -16,7 +16,7 @@ def linear_search_array(nums: List[int], target: int) -> int:
return i
return -1 # 未找到目标元素，返回 -1
def linear_search_linkedlist(head: ListNode, target: int) -> Optional[ListNode]:
def linear_search_linkedlist(head: ListNode, target: int) -> ListNode | None:
""" 线性查找（链表） """
# 遍历链表
while head:
@ -31,11 +31,11 @@ if __name__ == '__main__':
target: int = 3
# 在数组中执行线性查找
nums: List[int] = [1, 5, 3, 2, 4, 7, 5, 9, 10, 8]
nums: list[int] = [1, 5, 3, 2, 4, 7, 5, 9, 10, 8]
index: int = linear_search_array(nums, target)
print("目标元素 3 的索引 =", index)
# 在链表中执行线性查找
head: ListNode = list_to_linked_list(nums)
node: Optional[ListNode] = linear_search_linkedlist(head, target)
node: ListNode | None = linear_search_linkedlist(head, target)
print("目标结点值 3 的对应结点对象为", node)

12
codes/python/chapter_sorting/bubble_sort.py
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@ -4,11 +4,7 @@ Created Time: 2022-11-25
Author: timi (xisunyy@163.com)
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
def bubble_sort(nums: List[int]) -> None:
def bubble_sort(nums: list[int]) -> None:
""" 冒泡排序 """
n: int = len(nums)
# 外循环：待排序元素数量为 n-1, n-2, ..., 1
@ -19,7 +15,7 @@ def bubble_sort(nums: List[int]) -> None:
# 交换 nums[j] 与 nums[j + 1]
nums[j], nums[j + 1] = nums[j + 1], nums[j]
def bubble_sort_with_flag(nums: List[int]) -> None:
def bubble_sort_with_flag(nums: list[int]) -> None:
""" 冒泡排序（标志优化） """
n: int = len(nums)
# 外循环：待排序元素数量为 n-1, n-2, ..., 1
@ -37,10 +33,10 @@ def bubble_sort_with_flag(nums: List[int]) -> None:
""" Driver Code """
if __name__ == '__main__':
nums: List[int] = [4, 1, 3, 1, 5, 2]
nums: list[int] = [4, 1, 3, 1, 5, 2]
bubble_sort(nums)
print("排序后数组 nums =", nums)
nums1: List[int] = [4, 1, 3, 1, 5, 2]
nums1: list[int] = [4, 1, 3, 1, 5, 2]
bubble_sort_with_flag(nums1)
print("排序后数组 nums =", nums1)

8
codes/python/chapter_sorting/counting_sort.py
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@ -4,11 +4,7 @@ Created Time: 2023-03-21
Author: Krahets (krahets@163.com)
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
def counting_sort_naive(nums: List[int]) -> None:
def counting_sort_naive(nums: list[int]) -> None:
""" 计数排序 """
# 简单实现，无法用于排序对象
# 1. 统计数组最大元素 m
@ -27,7 +23,7 @@ def counting_sort_naive(nums: List[int]) -> None:
nums[i] = num
i += 1
def counting_sort(nums: List[int]) -> None:
def counting_sort(nums: list[int]) -> None:
""" 计数排序 """
# 完整实现，可排序对象，并且是稳定排序
# 1. 统计数组最大元素 m

8
codes/python/chapter_sorting/insertion_sort.py
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@ -4,11 +4,7 @@ Created Time: 2022-11-25
Author: timi (xisunyy@163.com)
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
def insertion_sort(nums: List[int]) -> None:
def insertion_sort(nums: list[int]) -> None:
""" 插入排序 """
# 外循环：base = nums[1], nums[2], ..., nums[n-1]
for i in range(1, len(nums)):
@ -23,6 +19,6 @@ def insertion_sort(nums: List[int]) -> None:
""" Driver Code """
if __name__ == '__main__':
nums: List[int] = [4, 1, 3, 1, 5, 2]
nums: list[int] = [4, 1, 3, 1, 5, 2]
insertion_sort(nums)
print("排序后数组 nums =", nums)

14
codes/python/chapter_sorting/merge_sort.py
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@ -4,16 +4,12 @@ Created Time: 2022-11-25
Author: timi (xisunyy@163.com)
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
def merge(nums: List[int], left: int, mid: int, right: int) -> None:
def merge(nums: list[int], left: int, mid: int, right: int) -> None:
""" 合并左子数组和右子数组 """
# 左子数组区间 [left, mid]
# 右子数组区间 [mid + 1, right]
# 初始化辅助数组 借助 copy模块
tmp: List[int] = nums[left:right + 1].copy()
# 初始化辅助数组
tmp: list[int] = list(nums[left:right + 1])
# 左子数组的起始索引和结束索引
left_start: int = 0
left_end: int = mid - left
@ -38,7 +34,7 @@ def merge(nums: List[int], left: int, mid: int, right: int) -> None:
nums[k] = tmp[j]
j += 1
def merge_sort(nums: List[int], left: int, right: int) -> None:
def merge_sort(nums: list[int], left: int, right: int) -> None:
""" 归并排序 """
# 终止条件
if left >= right:
@ -53,6 +49,6 @@ def merge_sort(nums: List[int], left: int, right: int) -> None:
""" Driver Code """
if __name__ == '__main__':
nums: List[int] = [ 7, 3, 2, 6, 0, 1, 5, 4 ]
nums: list[int] = [ 7, 3, 2, 6, 0, 1, 5, 4 ]
merge_sort(nums, 0, len(nums) - 1)
print("归并排序完成后 nums =", nums)

24
codes/python/chapter_sorting/quick_sort.py
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@ -4,13 +4,9 @@ Created Time: 2022-11-25
Author: timi (xisunyy@163.com)
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
class QuickSort:
""" 快速排序类 """
def partition(self, nums: List[int], left: int, right: int) -> int:
def partition(self, nums: list[int], left: int, right: int) -> int:
""" 哨兵划分 """
# 以 nums[left] 作为基准数
i, j = left, right
@ -25,7 +21,7 @@ class QuickSort:
nums[i], nums[left] = nums[left], nums[i]
return i # 返回基准数的索引
def quick_sort(self, nums: List[int], left: int, right: int) -> None:
def quick_sort(self, nums: list[int], left: int, right: int) -> None:
""" 快速排序 """
# 子数组长度为 1 时终止递归
if left >= right:
@ -38,7 +34,7 @@ class QuickSort:
class QuickSortMedian:
""" 快速排序类（中位基准数优化）"""
def median_three(self, nums: List[int], left: int, mid: int, right: int) -> int:
def median_three(self, nums: list[int], left: int, mid: int, right: int) -> int:
""" 选取三个元素的中位数 """
# 此处使用异或运算来简化代码
# 异或规则为 0 ^ 0 = 1 ^ 1 = 0, 0 ^ 1 = 1 ^ 0 = 1
@ -48,7 +44,7 @@ class QuickSortMedian:
return mid
return right
def partition(self, nums: List[int], left: int, right: int) -> int:
def partition(self, nums: list[int], left: int, right: int) -> int:
""" 哨兵划分（三数取中值） """
# 以 nums[left] 作为基准数
med: int = self.median_three(nums, left, (left + right) // 2, right)
@ -67,7 +63,7 @@ class QuickSortMedian:
nums[i], nums[left] = nums[left], nums[i]
return i # 返回基准数的索引
def quick_sort(self, nums: List[int], left: int, right: int) -> None:
def quick_sort(self, nums: list[int], left: int, right: int) -> None:
""" 快速排序 """
# 子数组长度为 1 时终止递归
if left >= right:
@ -80,7 +76,7 @@ class QuickSortMedian:
class QuickSortTailCall:
""" 快速排序类（尾递归优化） """
def partition(self, nums: List[int], left: int, right: int) -> int:
def partition(self, nums: list[int], left: int, right: int) -> int:
""" 哨兵划分 """
# 以 nums[left] 作为基准数
i, j = left, right
@ -95,7 +91,7 @@ class QuickSortTailCall:
nums[i], nums[left] = nums[left], nums[i]
return i # 返回基准数的索引
def quick_sort(self, nums: List[int], left: int, right: int) -> None:
def quick_sort(self, nums: list[int], left: int, right: int) -> None:
""" 快速排序（尾递归优化） """
# 子数组长度为 1 时终止
while left < right:
@ -113,16 +109,16 @@ class QuickSortTailCall:
""" Driver Code """
if __name__ == '__main__':
# 快速排序
nums: List[int] = [2, 4, 1, 0, 3, 5]
nums: list[int] = [2, 4, 1, 0, 3, 5]
QuickSort().quick_sort(nums, 0, len(nums) - 1)
print("快速排序完成后 nums =", nums)
# 快速排序（中位基准数优化）
nums1: List[int] = [2, 4, 1, 0, 3, 5]
nums1: list[int] = [2, 4, 1, 0, 3, 5]
QuickSortMedian().quick_sort(nums1, 0, len(nums1) - 1)
print("快速排序（中位基准数优化）完成后 nums =", nums1)
# 快速排序（尾递归优化）
nums2: List[int] = [2, 4, 1, 0, 3, 5]
nums2: list[int] = [2, 4, 1, 0, 3, 5]
QuickSortTailCall().quick_sort(nums2, 0, len(nums2) - 1)
print("快速排序（尾递归优化）完成后 nums =", nums2)

10
codes/python/chapter_stack_and_queue/array_deque.py
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@ -4,17 +4,11 @@ Created Time: 2023-03-01
Author: Krahets (krahets@163.com)
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
class ArrayDeque:
""" 基于环形数组实现的双向队列 """
def __init__(self, capacity: int) -> None:
""" 构造方法 """
self.__nums: List[int] = [0] * capacity
self.__nums: list[int] = [0] * capacity
self.__front: int = 0
self.__size: int = 0
@ -86,7 +80,7 @@ class ArrayDeque:
last = self.index(self.__front + self.__size - 1)
return self.__nums[last]
def to_array(self) -> List[int]:
def to_array(self) -> list[int]:
""" 返回数组用于打印 """
# 仅转换有效长度范围内的列表元素
res = []

10
codes/python/chapter_stack_and_queue/array_queue.py
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@ -4,15 +4,11 @@ Created Time: 2022-12-01
Author: Peng Chen (pengchzn@gmail.com)
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
class ArrayQueue:
""" 基于环形数组实现的队列 """
def __init__(self, size: int) -> None:
""" 构造方法 """
self.__nums: List[int] = [0] * size # 用于存储队列元素的数组
self.__nums: list[int] = [0] * size # 用于存储队列元素的数组
self.__front: int = 0 # 队首指针，指向队首元素
self.__size: int = 0 # 队列长度
@ -51,9 +47,9 @@ class ArrayQueue:
assert not self.is_empty(), "队列为空"
return self.__nums[self.__front]
def to_list(self) -> List[int]:
def to_list(self) -> list[int]:
""" 返回列表用于打印 """
res: List[int] = [0] * self.size()
res: list[int] = [0] * self.size()
j: int = self.__front
for i in range(self.size()):
res[i] = self.__nums[(j % self.capacity())]

8
codes/python/chapter_stack_and_queue/array_stack.py
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@ -4,15 +4,11 @@ Created Time: 2022-11-29
Author: Peng Chen (pengchzn@gmail.com)
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
class ArrayStack:
""" 基于数组实现的栈 """
def __init__(self) -> None:
""" 构造方法 """
self.__stack: List[int] = []
self.__stack: list[int] = []
def size(self) -> int:
""" 获取栈的长度 """
@ -36,7 +32,7 @@ class ArrayStack:
assert not self.is_empty(), "栈为空"
return self.__stack[-1]
def to_list(self) -> List[int]:
def to_list(self) -> list[int]:
""" 返回列表用于打印 """
return self.__stack

35
codes/python/chapter_stack_and_queue/deque.py
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@ -4,42 +4,39 @@ Created Time: 2022-11-29
Author: Peng Chen (pengchzn@gmail.com)
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
from collections import deque
""" Driver Code """
if __name__ == "__main__":
""" 初始化双向队列 """
deque: Deque[int] = collections.deque()
deq: deque[int] = deque()
""" 元素入队 """
deque.append(2) # 添加至队尾
deque.append(5)
deque.append(4)
deque.appendleft(3) # 添加至队首
deque.appendleft(1)
print("双向队列 deque =", deque)
deq.append(2) # 添加至队尾
deq.append(5)
deq.append(4)
deq.appendleft(3) # 添加至队首
deq.appendleft(1)
print("双向队列 deque =", deq)
""" 访问元素 """
front: int = deque[0] # 队首元素
front: int = deq[0] # 队首元素
print("队首元素 front =", front)
rear: int = deque[-1] # 队尾元素
rear: int = deq[-1] # 队尾元素
print("队尾元素 rear =", rear)
""" 元素出队 """
pop_front: int = deque.popleft() # 队首元素出队
pop_front: int = deq.popleft() # 队首元素出队
print("队首出队元素 pop_front =", pop_front)
print("队首出队后 deque =", deque)
pop_rear: int = deque.pop() # 队尾元素出队
print("队首出队后 deque =", deq)
pop_rear: int = deq.pop() # 队尾元素出队
print("队尾出队元素 pop_rear =", pop_rear)
print("队尾出队后 deque =", deque)
print("队尾出队后 deque =", deq)
""" 获取双向队列的长度 """
size: int = len(deque)
size: int = len(deq)
print("双向队列长度 size =", size)
""" 判断双向队列是否为空 """
is_empty: bool = len(deque) == 0
is_empty: bool = len(deq) == 0
print("双向队列是否为空 =", is_empty)

22
codes/python/chapter_stack_and_queue/linkedlist_deque.py
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@ -4,24 +4,20 @@ Created Time: 2023-03-01
Author: Krahets (krahets@163.com)
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
class ListNode:
""" 双向链表结点 """
def __init__(self, val: int) -> None:
""" 构造方法 """
self.val: int = val
self.next: Optional[ListNode] = None # 后继结点引用（指针）
self.prev: Optional[ListNode] = None # 前驱结点引用（指针）
self.next: ListNode | None = None # 后继结点引用（指针）
self.prev: ListNode | None = None # 前驱结点引用（指针）
class LinkedListDeque:
""" 基于双向链表实现的双向队列 """
def __init__(self) -> None:
""" 构造方法 """
self.front: Optional[ListNode] = None # 头结点 front
self.rear: Optional[ListNode] = None # 尾结点 rear
self.front: ListNode | None = None # 头结点 front
self.rear: ListNode | None = None # 尾结点 rear
self.__size: int = 0 # 双向队列的长度
def size(self) -> int:
@ -69,7 +65,7 @@ class LinkedListDeque:
if is_front:
val: int = self.front.val # 暂存头结点值
# 删除头结点
fnext: Optional[ListNode] = self.front.next
fnext: ListNode | None = self.front.next
if fnext != None:
fnext.prev = None
self.front.next = None
@ -78,7 +74,7 @@ class LinkedListDeque:
else:
val: int = self.rear.val # 暂存尾结点值
# 删除尾结点
rprev: Optional[ListNode] = self.rear.prev
rprev: ListNode | None = self.rear.prev
if rprev != None:
rprev.next = None
self.rear.prev = None
@ -102,10 +98,10 @@ class LinkedListDeque:
""" 访问队尾元素 """
return None if self.is_empty() else self.rear.val
def to_array(self) -> List[int]:
def to_array(self) -> list[int]:
""" 返回数组用于打印 """
node: Optional[ListNode] = self.front
res: List[int] = [0] * self.size()
node: ListNode | None = self.front
res: list[int] = [0] * self.size()
for i in range(self.size()):
res[i] = node.val
node = node.next

6
codes/python/chapter_stack_and_queue/linkedlist_queue.py
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@ -12,8 +12,8 @@ class LinkedListQueue:
""" 基于链表实现的队列 """
def __init__(self):
""" 构造方法 """
self.__front: Optional[ListNode] = None # 头结点 front
self.__rear: Optional[ListNode] = None # 尾结点 rear
self.__front: ListNode | None = None # 头结点 front
self.__rear: ListNode | None = None # 尾结点 rear
self.__size: int = 0
def size(self) -> int:
@ -53,7 +53,7 @@ class LinkedListQueue:
return False
return self.__front.val
def to_list(self) -> List[int]:
def to_list(self) -> list[int]:
""" 转化为列表用于打印 """
queue = []
temp = self.__front

6
codes/python/chapter_stack_and_queue/linkedlist_stack.py
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@ -12,7 +12,7 @@ class LinkedListStack:
""" 基于链表实现的栈 """
def __init__(self):
""" 构造方法 """
self.__peek: Optional[ListNode] = None
self.__peek: ListNode | None = None
self.__size: int = 0
def size(self) -> int:
@ -43,9 +43,9 @@ class LinkedListStack:
if not self.__peek: return None
return self.__peek.val
def to_list(self) -> List[int]:
def to_list(self) -> list[int]:
""" 转化为列表用于打印 """
arr: List[int] = []
arr: list[int] = []
node = self.__peek
while node:
arr.append(node.val)

10
codes/python/chapter_stack_and_queue/queue.py
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@ -4,17 +4,15 @@ Created Time: 2022-11-29
Author: Peng Chen (pengchzn@gmail.com)
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
from collections import deque
""" Driver Code """
if __name__ == "__main__":
if __name__ == "__main__":
""" 初始化队列 """
# 在 Python 中，我们一般将双向队列类 deque 看作队列使用
# 虽然 queue.Queue() 是纯正的队列类，但不太好用
que: Deque[int] = collections.deque()
que: deque[int] = deque()
""" 元素入队 """
que.append(1)

7
codes/python/chapter_stack_and_queue/stack.py
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@ -4,16 +4,11 @@ Created Time: 2022-11-29
Author: Peng Chen (pengchzn@gmail.com)
"""
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
""" Driver Code """
if __name__ == "__main__":
""" 初始化栈 """
# Python 没有内置的栈类，可以把 list 当作栈来使用
stack: List[int] = []
stack: list[int] = []
""" 元素入栈 """
stack.append(1)

26
codes/python/chapter_tree/avl_tree.py
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@ -10,27 +10,27 @@ from modules import *
class AVLTree:
""" AVL 树 """
def __init__(self, root: Optional[TreeNode] = None):
def __init__(self, root: TreeNode | None = None):
""" 构造方法 """
self.__root = root
@property
def root(self) -> Optional[TreeNode]:
def root(self) -> TreeNode | None:
return self.__root
def height(self, node: Optional[TreeNode]) -> int:
def height(self, node: TreeNode | None) -> int:
""" 获取结点高度 """
# 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: Optional[TreeNode]):
def __update_height(self, node: TreeNode | None):
""" 更新结点高度 """
# 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: Optional[TreeNode]) -> int:
def balance_factor(self, node: TreeNode | None) -> int:
""" 获取平衡因子 """
# 空结点平衡因子为 0
if node is None:
@ -38,7 +38,7 @@ class AVLTree:
# 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: Optional[TreeNode]) -> Optional[TreeNode]:
def __right_rotate(self, node: TreeNode | None) -> TreeNode | None:
""" 右旋操作 """
child = node.left
grand_child = child.right
@ -51,7 +51,7 @@ class AVLTree:
# 返回旋转后子树的根结点
return child
def __left_rotate(self, node: Optional[TreeNode]) -> Optional[TreeNode]:
def __left_rotate(self, node: TreeNode | None) -> TreeNode | None:
""" 左旋操作 """
child = node.right
grand_child = child.left
@ -64,7 +64,7 @@ class AVLTree:
# 返回旋转后子树的根结点
return child
def __rotate(self, node: Optional[TreeNode]) -> Optional[TreeNode]:
def __rotate(self, node: TreeNode | None) -> TreeNode | None:
""" 执行旋转操作，使该子树重新恢复平衡 """
# 获取结点 node 的平衡因子
balance_factor = self.balance_factor(node)
@ -94,7 +94,7 @@ class AVLTree:
self.__root = self.__insert_helper(self.__root, val)
return self.__root
def __insert_helper(self, node: Optional[TreeNode], val: int) -> TreeNode:
def __insert_helper(self, node: TreeNode | None, val: int) -> TreeNode:
""" 递归插入结点（辅助方法）"""
if node is None:
return TreeNode(val)
@ -111,12 +111,12 @@ class AVLTree:
# 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) -> Optional[TreeNode]:
def remove(self, val: int) -> TreeNode | None:
""" 删除结点 """
self.__root = self.__remove_helper(self.__root, val)
return self.__root
def __remove_helper(self, node: Optional[TreeNode], val: int) -> Optional[TreeNode]:
def __remove_helper(self, node: TreeNode | None, val: int) -> TreeNode | None:
""" 递归删除结点（辅助方法） """
if node is None:
return None
@ -143,7 +143,7 @@ class AVLTree:
# 2. 执行旋转操作，使该子树重新恢复平衡
return self.__rotate(node)
def __get_inorder_next(self, node: Optional[TreeNode]) -> Optional[TreeNode]:
def __get_inorder_next(self, node: TreeNode | None) -> TreeNode | None:
""" 获取中序遍历中的下一个结点（仅适用于 root 有左子结点的情况） """
if node is None:
return None
@ -152,7 +152,7 @@ class AVLTree:
node = node.left
return node
def search(self, val: int) -> Optional[TreeNode]:
def search(self, val: int) -> TreeNode | None:
""" 查找结点 """
cur = self.__root
# 循环查找，越过叶结点后跳出

16
codes/python/chapter_tree/binary_search_tree.py
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@ -11,12 +11,12 @@ from modules import *
class BinarySearchTree:
""" 二叉搜索树 """
def __init__(self, nums: List[int]) -> None:
def __init__(self, nums: list[int]) -> None:
""" 构造方法 """
nums.sort()
self.__root = self.build_tree(nums, 0, len(nums) - 1)
def build_tree(self, nums: List[int], start_index: int, end_index: int) -> Optional[TreeNode]:
def build_tree(self, nums: list[int], start_index: int, end_index: int) -> TreeNode | None:
""" 构建二叉搜索树 """
if start_index > end_index:
return None
@ -30,12 +30,12 @@ class BinarySearchTree:
return root
@property
def root(self) -> Optional[TreeNode]:
def root(self) -> TreeNode | None:
return self.__root
def search(self, num: int) -> Optional[TreeNode]:
def search(self, num: int) -> TreeNode | None:
""" 查找结点 """
cur: Optional[TreeNode] = self.__root
cur: TreeNode | None = self.__root
# 循环查找，越过叶结点后跳出
while cur is not None:
# 目标结点在 cur 的右子树中
@ -49,7 +49,7 @@ class BinarySearchTree:
break
return cur
def insert(self, num: int) -> Optional[TreeNode]:
def insert(self, num: int) -> TreeNode | None:
""" 插入结点 """
# 若树为空，直接提前返回
if self.__root is None:
@ -77,7 +77,7 @@ class BinarySearchTree:
pre.left = node
return node
def remove(self, num: int) -> Optional[TreeNode]:
def remove(self, num: int) -> TreeNode | None:
""" 删除结点 """
# 若树为空，直接提前返回
if self.__root is None:
@ -118,7 +118,7 @@ class BinarySearchTree:
cur.val = tmp
return cur
def get_inorder_next(self, root: Optional[TreeNode]) -> Optional[TreeNode]:
def get_inorder_next(self, root: TreeNode | None) -> TreeNode | None:
""" 获取中序遍历中的下一个结点（仅适用于 root 有左子结点的情况） """
if root is None:
return root

10
codes/python/chapter_tree/binary_tree_bfs.py
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@ -7,15 +7,15 @@ Author: a16su (lpluls001@gmail.com)
import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
from collections import deque
def level_order(root: Optional[TreeNode]) -> List[int]:
def level_order(root: TreeNode | None) -> list[int]:
""" 层序遍历 """
# 初始化队列，加入根结点
queue: Deque[TreeNode] = collections.deque()
queue: deque[TreeNode] = deque()
queue.append(root)
# 初始化一个列表，用于保存遍历序列
res: List[int] = []
res: list[int] = []
while queue:
node: TreeNode = queue.popleft() # 队列出队
res.append(node.val) # 保存结点值
@ -35,6 +35,6 @@ if __name__ == "__main__":
print_tree(root)
# 层序遍历
res: List[int] = level_order(root)
res: list[int] = level_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]

7
codes/python/chapter_tree/binary_tree_dfs.py
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@ -8,8 +8,7 @@ import sys, os.path as osp
sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
from modules import *
def pre_order(root: Optional[TreeNode]) -> None:
def pre_order(root: TreeNode | None) -> None:
""" 前序遍历 """
if root is None:
return
@ -18,7 +17,7 @@ def pre_order(root: Optional[TreeNode]) -> None:
pre_order(root=root.left)
pre_order(root=root.right)
def in_order(root: Optional[TreeNode]) -> None:
def in_order(root: TreeNode | None) -> None:
""" 中序遍历 """
if root is None:
return
@ -27,7 +26,7 @@ def in_order(root: Optional[TreeNode]) -> None:
res.append(root.val)
in_order(root=root.right)
def post_order(root: Optional[TreeNode]) -> None:
def post_order(root: TreeNode | None) -> None:
""" 后序遍历 """
if root is None:
return

16
codes/python/modules/__init__.py
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@ -1,12 +1,8 @@
import copy
import math
import heapq
import queue
import random
import functools
import collections
from typing import Optional, Tuple, List, Dict, DefaultDict, OrderedDict, Set, Deque
# Follow the PEP 585 – Type Hinting Generics In Standard Collections
# https://peps.python.org/pep-0585/
from __future__ import annotations
# Import common libs here to simplify the codes by `from module import *`
from .linked_list import ListNode, list_to_linked_list, linked_list_to_list, get_list_node
from .binary_tree import TreeNode, list_to_tree, tree_to_list, get_tree_node
from .binary_tree import TreweNode, list_to_tree, tree_to_list, get_tree_node
from .vertex import Vertex, vals_to_vets, vets_to_vals
from .print_util import print_matrix, print_linked_list, print_tree, print_dict, print_heap
from .print_util import print_matrix, print_linked_list, print_tree, print_dict, print_heap

31
codes/python/modules/binary_tree.py
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@ -4,25 +4,24 @@ Created Time: 2021-12-11
Author: Krahets (krahets@163.com)
"""
import collections
from typing import List, Deque, Optional
from collections import deque
class TreeNode:
""" Definition for a binary tree node """
def __init__(self, val: int = 0, left: Optional['TreeNode'] = None, right: Optional['TreeNode'] = None):
self.val: int = val # 结点值
self.height: int = 0 # 结点高度
self.left: Optional[TreeNode] = left # 左子结点引用
self.right: Optional[TreeNode] = right # 右子结点引用
def __init__(self, val: int = 0):
self.val: int = val # 结点值
self.height: int = 0 # 结点高度
self.left: TreeNode | None = None # 左子结点引用
self.right: TreeNode | None = None # 右子结点引用
def list_to_tree(arr: List[int]) -> Optional[TreeNode]:
def list_to_tree(arr: list[int]) -> TreeNode | None:
""" Generate a binary tree with a list """
if not arr:
return None
i: int = 0
root = TreeNode(arr[0])
queue: Deque[TreeNode] = collections.deque([root])
queue: deque[TreeNode] = deque([root])
while queue:
node: TreeNode = queue.popleft()
i += 1
@ -38,14 +37,14 @@ def list_to_tree(arr: List[int]) -> Optional[TreeNode]:
return root
def tree_to_list(root: Optional[TreeNode]) -> List[int]:
def tree_to_list(root: TreeNode | None) -> list[int]:
""" Serialize a tree into an array """
if not root: return []
queue: Deque[TreeNode] = collections.deque()
queue: deque[TreeNode] = deque()
queue.append(root)
res: List[int] = []
res: list[int] = []
while queue:
node: Optional[TreeNode] = queue.popleft()
node: TreeNode | None = queue.popleft()
if node:
res.append(node.val)
queue.append(node.left)
@ -53,12 +52,12 @@ def tree_to_list(root: Optional[TreeNode]) -> List[int]:
else: res.append(None)
return res
def get_tree_node(root: Optional[TreeNode], val: int) -> Optional[TreeNode]:
def get_tree_node(root: TreeNode | None, val: int) -> TreeNode | None:
""" Get a tree node with specific value in a binary tree """
if not root:
return
if root.val == val:
return root
left: Optional[TreeNode] = get_tree_node(root.left, val)
right: Optional[TreeNode] = get_tree_node(root.right, val)
left: TreeNode | None = get_tree_node(root.left, val)
right: TreeNode | None = get_tree_node(root.right, val)
return left if left else right

12
codes/python/modules/linked_list.py
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@ -4,15 +4,13 @@ Created Time: 2021-12-11
Author: Krahets (krahets@163.com)
"""
from typing import List, Optional
class ListNode:
""" Definition for a singly-linked list node """
def __init__(self, val: int):
self.val: int = val # 结点值
self.next: Optional[ListNode] = None # 后继结点引用
self.next: ListNode | None = None # 后继结点引用
def list_to_linked_list(arr: List[int]) -> Optional[ListNode]:
def list_to_linked_list(arr: list[int]) -> ListNode | None:
""" Generate a linked list with a list """
dum = head = ListNode(0)
for a in arr:
@ -21,15 +19,15 @@ def list_to_linked_list(arr: List[int]) -> Optional[ListNode]:
head = head.next
return dum.next
def linked_list_to_list(head: Optional[ListNode]) -> List[int]:
def linked_list_to_list(head: ListNode | None) -> list[int]:
""" Serialize a linked list into an array """
arr: List[int] = []
arr: list[int] = []
while head:
arr.append(head.val)
head = head.next
return arr
def get_list_node(head: Optional[ListNode], val: int) -> Optional[ListNode]:
def get_list_node(head: ListNode | None, val: int) -> ListNode | None:
""" Get a list node with specific value from a linked list """
while head and head.val != val:
head = head.next

26
codes/python/modules/print_util.py
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@ -7,33 +7,31 @@ Author: Krahets (krahets@163.com), msk397 (machangxinq@gmail.com)
from .binary_tree import TreeNode, list_to_tree
from .linked_list import ListNode, linked_list_to_list
from typing import List, Optional, Dict
def print_matrix(mat: List[List[int]]) -> None:
def print_matrix(mat: list[list[int]]) -> None:
""" Print a matrix """
s: List[str] = []
s: list[str] = []
for arr in mat:
s.append(' ' + str(arr))
print('[\n' + ',\n'.join(s) + '\n]')
def print_linked_list(head: Optional[ListNode]) -> None:
def print_linked_list(head: ListNode | None) -> None:
""" Print a linked list """
arr: List[int] = linked_list_to_list(head)
arr: list[int] = linked_list_to_list(head)
print(' -> '.join([str(a) for a in arr]))
class Trunk:
def __init__(self, prev: Optional['Trunk'] = None, string: Optional[str] = None) -> None:
self.prev: Optional[Trunk] = prev
self.str: Optional[str] = string
def __init__(self, prev, string: str | None = None) -> None:
self.prev = prev
self.str = string
def show_trunks(p: Optional[Trunk]) -> None:
def show_trunks(p: Trunk | None) -> None:
if p is None:
return
show_trunks(p.prev)
print(p.str, end='')
def print_tree(root: Optional[TreeNode], prev: Optional[Trunk] = None, is_left: bool = False) -> None:
def print_tree(root: TreeNode | None, prev: Trunk | None = None, is_left: bool = False) -> None:
"""
Print a binary tree
This tree printer is borrowed from TECHIE DELIGHT
@ -62,14 +60,14 @@ def print_tree(root: Optional[TreeNode], prev: Optional[Trunk] = None, is_left:
trunk.str = ' |'
print_tree(root.left, trunk, False)
def print_dict(mapp: Dict) -> None:
def print_dict(mapp: dict) -> None:
""" Print a dict """
for key, value in mapp.items():
print(key, '->', value)
def print_heap(heap: List[int]) -> None:
def print_heap(heap: list[int]) -> None:
""" Print a heap both in array and tree representations """
print("堆的数组表示：", heap)
print("堆的树状表示：")
root: Optional[TreeNode] = list_to_tree(heap)
root: TreeNode | None = list_to_tree(heap)
print_tree(root)

6
codes/python/modules/vertex.py
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@ -2,17 +2,15 @@
# Created Time: 2023-02-23
# Author: Krahets (krahets@163.com)
from typing import List
class Vertex:
""" 顶点类 """
def __init__(self, val: int) -> None:
self.val = val
def vals_to_vets(vals: List[int]) -> List['Vertex']:
def vals_to_vets(vals: list[int]) -> list['Vertex']:
""" 输入值列表 vals ，返回顶点列表 vets """
return [Vertex(val) for val in vals]
def vets_to_vals(vets: List['Vertex']) -> List[int]:
def vets_to_vals(vets: list['Vertex']) -> list[int]:
""" 输入顶点列表 vets ，返回值列表 vals """
return [vet.val for vet in vets]

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