```python

# 函数式编程利器：lambda、map和filter提升代码简洁性

# lambda表达式：创建匿名函数

square = lambda x: x 2

is_even = lambda x: x % 2 == 0

# 传统方式 vs lambda方式

def square_def(x):

return x 2

numbers = [1, 2, 3, 4, 5]

# 使用map进行数据转换

squared_numbers = list(map(lambda x: x 2, numbers))

# 等价于：[x2 for x in numbers]

# 使用filter进行数据筛选

even_numbers = list(filter(lambda x: x % 2 == 0, numbers))

# 等价于：[x for x in numbers if x % 2 == 0]

# 组合使用map和filter

squared_evens = list(map(lambda x: x 2,

filter(lambda x: x % 2 == 0, numbers)))

# 处理字符串数据

words = ['hello', 'world', 'python', 'functional']

capitalized_words = list(map(lambda word: word.upper(), words))

# 复杂数据处理

data = [{'name': 'Alice', 'age': 25},

{'name': 'Bob', 'age': 30},

{'name': 'Charlie', 'age': 35}]

# 提取年龄大于28的人名

names_over_28 = list(map(lambda person: person['name'],

filter(lambda person: person['age'] > 28, data)))

# 数学运算示例

import math

points = [(1, 2), (3, 4), (5, 6)]

distances = list(map(lambda point: math.sqrt(point[0]2 + point[1]2), points))

# 多参数lambda与map

add_numbers = lambda x, y: x + y

list1 = [1, 2, 3]

list2 = [4, 5, 6]

sums = list(map(add_numbers, list1, list2))

# 条件过滤的复杂示例

mixed_data = [1, 'hello', 3.14, 42, 'world', 2.71]

integers_only = list(filter(lambda x: isinstance(x, int), mixed_data))

# 性能优化：使用生成器表达式

large_numbers = range(1000000)

even_squares_gen = map(lambda x: x 2,

filter(lambda x: x % 2 == 0, large_numbers))

# 实际应用：数据清洗

raw_data = [' hello ', ' WORLD ', ' PYTHON ']

cleaned_data = list(map(lambda s: s.strip().lower(), raw_data))

# 函数组合

def compose(f, g):

return lambda x: f(g(x))

to_upper = lambda s: s.upper()

add_exclamation = lambda s: s + '!'

shout = compose(to_upper, add_exclamation)

# 使用示例

result = list(map(shout, ['hello', 'world']))

```