Add typing annotations to Python codes. (#411)

codes/python/chapter_computational_complexity/leetcode_two_sum.py

@@ -14,7 +14,7 @@ def two_sum_brute_force(nums: List[int], target: int) -> List[int]:
     for i in range(len(nums) - 1):
         for j in range(i + 1, len(nums)):
             if nums[i] + nums[j] == target:
-                return i, j
+                return [i, j]
     return []
 
 def two_sum_hash_table(nums: List[int], target: int) -> List[int]:
@@ -24,7 +24,7 @@ def two_sum_hash_table(nums: List[int], target: int) -> List[int]:
     # 单层循环，时间复杂度 O(n)
     for i in range(len(nums)):
         if target - nums[i] in dic:
-            return dic[target - nums[i]], i
+            return [dic[target - nums[i]], i]
         dic[nums[i]] = i
     return []
 
@@ -37,8 +37,8 @@ if __name__ == '__main__':
     
     # ====== Driver Code ======
     # 方法一
-    res = 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 = 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

@@ -8,52 +8,52 @@ import sys, os.path as osp
 sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
 from modules import *
 
-def function():
+def function() -> int:
     """ 函数 """
     # do something
     return 0
 
-def constant(n):
+def constant(n: int) -> None:
     """ 常数阶 """
     # 常量、变量、对象占用 O(1) 空间
-    a = 0
-    nums = [0] * 10000
+    a: int = 0
+    nums: List[int] = [0] * 10000
     node = ListNode(0)
     # 循环中的变量占用 O(1) 空间
     for _ in range(n):
-        c = 0
+        c: int = 0
     # 循环中的函数占用 O(1) 空间
     for _ in range(n):
         function()
 
-def linear(n):
+def linear(n: int) -> None:
     """ 线性阶 """
     # 长度为 n 的列表占用 O(n) 空间
-    nums = [0] * n
+    nums: List[int] = [0] * n
     # 长度为 n 的哈希表占用 O(n) 空间
-    mapp = {}
+    mapp: Dict = {}
     for i in range(n):
         mapp[i] = str(i)
 
-def linear_recur(n):
+def linear_recur(n: int) -> None:
     """ 线性阶（递归实现） """
     print("递归 n =", n)
     if n == 1: return
     linear_recur(n - 1)
 
-def quadratic(n):
+def quadratic(n: int) -> None:
     """ 平方阶 """
     # 二维列表占用 O(n^2) 空间
-    num_matrix = [[0] * n for _ in range(n)]
+    num_matrix: List[List[int]] = [[0] * n for _ in range(n)]
 
-def quadratic_recur(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 = [0] * n
+    nums: List[int] = [0] * n
     return quadratic_recur(n - 1)
 
-def build_tree(n):
+def build_tree(n: int) -> Optional[TreeNode]:
     """ 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 = build_tree(n)
+    root: Optional[TreeNode] = build_tree(n)
     print_tree(root)

codes/python/chapter_computational_complexity/time_complexity.py

@@ -8,56 +8,57 @@ import sys, os.path as osp
 sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
 from modules import *
 
-def constant(n):
+def constant(n: int) -> int:
     """ 常数阶 """
-    count = 0
-    size = 100000
+    count: int = 0
+    size: int = 100000
     for _ in range(size):
         count += 1
     return count
 
-def linear(n):
+def linear(n: int) -> int:
     """ 线性阶 """
-    count = 0
+    count: int = 0
     for _ in range(n):
         count += 1
     return count
 
-def array_traversal(nums):
+def array_traversal(nums: List[int]) -> int:
     """ 线性阶（遍历数组）"""
-    count = 0
+    count: int = 0
     # 循环次数与数组长度成正比
     for num in nums:
         count += 1
     return count
 
-def quadratic(n):
+def quadratic(n: int) -> int:
     """ 平方阶 """
-    count = 0
+    count: int = 0
     # 循环次数与数组长度成平方关系
     for i in range(n):
         for j in range(n):
             count += 1
     return count
 
-def bubble_sort(nums):
+def bubble_sort(nums: List[int]) -> int:
     """ 平方阶（冒泡排序）"""
-    count = 0  # 计数器
+    count: int = 0  # 计数器
     # 外循环：待排序元素数量为 n-1, n-2, ..., 1
     for i in range(len(nums) - 1, 0, -1):
         # 内循环：冒泡操作
         for j in range(i):
             if nums[j] > nums[j + 1]:
                 # 交换 nums[j] 与 nums[j + 1]
-                tmp = nums[j]
+                tmp: int = nums[j]
                 nums[j] = nums[j + 1]
                 nums[j + 1] = tmp
                 count += 3  # 元素交换包含 3 个单元操作
     return count
 
-def exponential(n):
+def exponential(n: int) -> int:
     """ 指数阶（循环实现）"""
-    count, base = 0, 1
+    count: int = 0
+    base: int = 1
     # cell 每轮一分为二，形成数列 1, 2, 4, 8, ..., 2^(n-1)
     for _ in range(n):
         for _ in range(base):
@@ -66,37 +67,37 @@ def exponential(n):
     # count = 1 + 2 + 4 + 8 + .. + 2^(n-1) = 2^n - 1
     return count
 
-def exp_recur(n):
+def exp_recur(n: int) -> int:
     """ 指数阶（递归实现）"""
     if n == 1: return 1
     return exp_recur(n - 1) + exp_recur(n - 1) + 1
 
-def logarithmic(n):
+def logarithmic(n: float) -> int:
     """ 对数阶（循环实现）"""
-    count = 0
+    count: int = 0
     while n > 1:
         n = n / 2
         count += 1
     return count
 
-def log_recur(n):
+def log_recur(n: float) -> int:
     """ 对数阶（递归实现）"""
     if n <= 1: return 0
     return log_recur(n / 2) + 1
 
-def linear_log_recur(n):
+def linear_log_recur(n: float) -> int:
     """ 线性对数阶 """
     if n <= 1: return 1
-    count = linear_log_recur(n // 2) + \
-            linear_log_recur(n // 2)
+    count: int = linear_log_recur(n // 2) + \
+                 linear_log_recur(n // 2)
     for _ in range(n):
         count += 1
     return count
 
-def factorial_recur(n):
+def factorial_recur(n: int) -> int:
     """ 阶乘阶（递归实现）"""
     if n == 0: return 1
-    count = 0
+    count: int = 0
     # 从 1 个分裂出 n 个
     for _ in range(n):
         count += factorial_recur(n - 1)
@@ -109,32 +110,32 @@ if __name__ == "__main__":
     n = 8
     print("输入数据大小 n =", n)
 
-    count = constant(n)
+    count: int = constant(n)
     print("常数阶的计算操作数量 =", count)
 
-    count = linear(n)
+    count: int = linear(n)
     print("线性阶的计算操作数量 =", count)
-    count = array_traversal([0] * n)
+    count: int = array_traversal([0] * n)
     print("线性阶（遍历数组）的计算操作数量 =", count)
 
-    count = quadratic(n)
+    count: int = quadratic(n)
     print("平方阶的计算操作数量 =", count)
-    nums = [i for i in range(n, 0, -1)]  # [n,n-1,...,2,1]
-    count = bubble_sort(nums)
+    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)
 
-    count = exponential(n)
+    count: int = exponential(n)
     print("指数阶（循环实现）的计算操作数量 =", count)
-    count = exp_recur(n)
+    count: int = exp_recur(n)
     print("指数阶（递归实现）的计算操作数量 =", count)
 
-    count = logarithmic(n)
+    count: int = logarithmic(n)
     print("对数阶（循环实现）的计算操作数量 =", count)
-    count = log_recur(n)
+    count: int = log_recur(n)
     print("对数阶（递归实现）的计算操作数量 =", count)
 
-    count = linear_log_recur(n)
+    count: int = linear_log_recur(n)
     print("线性对数阶（递归实现）的计算操作数量 =", count)
 
-    count = factorial_recur(n)
+    count: int = factorial_recur(n)
     print("阶乘阶（递归实现）的计算操作数量 =", count)

codes/python/chapter_computational_complexity/worst_best_time_complexity.py

@@ -8,15 +8,15 @@ import sys, os.path as osp
 sys.path.append(osp.dirname(osp.dirname(osp.abspath(__file__))))
 from modules import *
 
-def random_numbers(n):
+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 = [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):
+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)
@@ -29,8 +29,8 @@ def find_one(nums):
 """ Driver Code """
 if __name__ == "__main__":
     for i in range(10):
-        n = 100
-        nums = random_numbers(n)
-        index = find_one(nums)
+        n: int = 100
+        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)