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

* Follow the PEP 585 Typing standard

* Update list.py

codes/python/chapter_computational_complexity/leetcode_two_sum.py

@@ -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)

codes/python/chapter_computational_complexity/space_complexity.py

@@ -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)

codes/python/chapter_computational_complexity/time_complexity.py

@@ -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)
 

codes/python/chapter_computational_complexity/worst_best_time_complexity.py

@@ -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)