Format python codes with black. (#453)

codes/python/chapter_computational_complexity/leetcode_two_sum.py

@@ -4,8 +4,9 @@ Created Time: 2022-11-25
 Author: Krahets (krahets@163.com)
 """
 
+
 def two_sum_brute_force(nums: list[int], target: int) -> list[int]:
-    """ 方法一：暴力枚举 """
+    """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):
         for j in range(i + 1, len(nums)):
@@ -13,8 +14,9 @@ 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]:
-    """ 方法二：辅助哈希表 """
+    """方法二：辅助哈希表"""
     # 辅助哈希表，空间复杂度 O(n)
     dic = {}
     # 单层循环，时间复杂度 O(n)
@@ -26,11 +28,11 @@ def two_sum_hash_table(nums: list[int], target: int) -> list[int]:
 
 
 """ Driver Code """
-if __name__ == '__main__':
+if __name__ == "__main__":
     # ======= Test Case =======
-    nums = [2,7,11,15]
+    nums = [2, 7, 11, 15]
     target = 9
-    
+
     # ====== Driver Code ======
     # 方法一
     res: list[int] = two_sum_brute_force(nums, target)

codes/python/chapter_computational_complexity/space_complexity.py

@@ -5,16 +5,19 @@ 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 function() -> int:
-    """ 函数 """
+    """函数"""
     # do something
     return 0
 
+
 def constant(n: int) -> None:
-    """ 常数阶 """
+    """常数阶"""
     # 常量、变量、对象占用 O(1) 空间
     a: int = 0
     nums: list[int] = [0] * 10000
@@ -26,8 +29,9 @@ def constant(n: int) -> None:
     for _ in range(n):
         function()
 
+
 def linear(n: int) -> None:
-    """ 线性阶 """
+    """线性阶"""
     # 长度为 n 的列表占用 O(n) 空间
     nums: list[int] = [0] * n
     # 长度为 n 的哈希表占用 O(n) 空间
@@ -35,27 +39,34 @@ def linear(n: int) -> None:
     for i in range(n):
         mapp[i] = str(i)
 
+
 def linear_recur(n: int) -> None:
-    """ 线性阶（递归实现） """
+    """线性阶（递归实现）"""
     print("递归 n =", n)
-    if n == 1: return
+    if n == 1:
+        return
     linear_recur(n - 1)
 
+
 def quadratic(n: int) -> None:
-    """ 平方阶 """
+    """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)]
 
+
 def quadratic_recur(n: int) -> int:
-    """ 平方阶（递归实现） """
-    if n <= 0: return 0
+    """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
     return quadratic_recur(n - 1)
 
+
 def build_tree(n: int) -> TreeNode | None:
-    """ 指数阶（建立满二叉树） """
-    if n == 0: return None
+    """指数阶（建立满二叉树）"""
+    if n == 0:
+        return None
     root = TreeNode(0)
     root.left = build_tree(n - 1)
     root.right = build_tree(n - 1)

codes/python/chapter_computational_complexity/time_complexity.py

@@ -4,31 +4,35 @@ Created Time: 2022-11-25
 Author: Krahets (krahets@163.com)
 """
 
+
 def constant(n: int) -> int:
-    """ 常数阶 """
+    """常数阶"""
     count: int = 0
     size: int = 100000
     for _ in range(size):
         count += 1
     return count
 
+
 def linear(n: int) -> int:
-    """ 线性阶 """
+    """线性阶"""
     count: int = 0
     for _ in range(n):
         count += 1
     return count
 
+
 def array_traversal(nums: list[int]) -> int:
-    """ 线性阶（遍历数组）"""
+    """线性阶（遍历数组）"""
     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: int) -> int:
-    """ 平方阶 """
+    """平方阶"""
     count: int = 0
     # 循环次数与数组长度成平方关系
     for i in range(n):
@@ -36,8 +40,9 @@ def quadratic(n: int) -> int:
             count += 1
     return count
 
+
 def bubble_sort(nums: list[int]) -> int:
-    """ 平方阶（冒泡排序）"""
+    """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
     for i in range(len(nums) - 1, 0, -1):
@@ -51,8 +56,9 @@ def bubble_sort(nums: list[int]) -> int:
                 count += 3  # 元素交换包含 3 个单元操作
     return count
 
+
 def exponential(n: int) -> int:
-    """ 指数阶（循环实现）"""
+    """指数阶（循环实现）"""
     count: int = 0
     base: int = 1
     # cell 每轮一分为二，形成数列 1, 2, 4, 8, ..., 2^(n-1)
@@ -63,36 +69,44 @@ def exponential(n: int) -> int:
     # count = 1 + 2 + 4 + 8 + .. + 2^(n-1) = 2^n - 1
     return count
 
+
 def exp_recur(n: int) -> int:
-    """ 指数阶（递归实现）"""
-    if n == 1: return 1
+    """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: float) -> int:
-    """ 对数阶（循环实现）"""
+    """对数阶（循环实现）"""
     count: int = 0
     while n > 1:
         n = n / 2
         count += 1
     return count
 
+
 def log_recur(n: float) -> int:
-    """ 对数阶（递归实现）"""
-    if n <= 1: return 0
+    """对数阶（递归实现）"""
+    if n <= 1:
+        return 0
     return log_recur(n / 2) + 1
 
+
 def linear_log_recur(n: float) -> int:
-    """ 线性对数阶 """
-    if n <= 1: return 1
-    count: int = linear_log_recur(n // 2) + \
-                 linear_log_recur(n // 2)
+    """线性对数阶"""
+    if n <= 1:
+        return 1
+    count: int = linear_log_recur(n // 2) + linear_log_recur(n // 2)
     for _ in range(n):
         count += 1
     return count
 
+
 def factorial_recur(n: int) -> int:
-    """ 阶乘阶（递归实现）"""
-    if n == 0: return 1
+    """阶乘阶（递归实现）"""
+    if n == 0:
+        return 1
     count: int = 0
     # 从 1 个分裂出 n 个
     for _ in range(n):

codes/python/chapter_computational_complexity/worst_best_time_complexity.py

@@ -6,16 +6,18 @@ Author: Krahets (krahets@163.com)
 
 import random
 
+
 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)]
     # 随机打乱数组元素
     random.shuffle(nums)
     return nums
 
+
 def find_one(nums: list[int]) -> int:
-    """ 查找数组 nums 中数字 1 所在索引 """
+    """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)
         # 当元素 1 在数组尾部时，达到最差时间复杂度 O(n)