# Python函数教程
# =============
# 1. 函数的基本定义和调用
# --------------------
# 定义一个简单的函数
def greet():
print("Hello, World!")
# 调用函数
greet()
# 2. 带参数的函数
# -------------
# 带位置参数的函数
def greet_person(name):
print(f"Hello, {name}!")
greet_person("Alice")
# 带多个参数的函数
def add_numbers(a, b):
return a + b
result = add_numbers(5, 3)
print(f"5 + 3 = {result}")
# 3. 默认参数
# ----------
def greet_with_title(name, title="Mr."):
print(f"Hello, {title} {name}!")
greet_with_title("Smith") # 使用默认title
greet_with_title("Smith", "Dr.") # 覆盖默认title
# 4. 关键字参数
# ------------
def describe_pet(animal_type, pet_name):
print(f"I have a {animal_type} named {pet_name}.")
# 使用位置参数
describe_pet("dog", "Buddy")
# 使用关键字参数
describe_pet(pet_name="Whiskers", animal_type="cat")
# 5. 可变参数
# ----------
# *args - 接收任意数量的位置参数
def make_pizza(*toppings):
print("Making a pizza with the following toppings:")
for topping in toppings:
print(f"- {topping}")
make_pizza("pepperoni")
make_pizza("mushrooms", "green peppers", "extra cheese")
# **kwargs - 接收任意数量的关键字参数
def build_profile(first, last, **user_info):
profile = {}
profile['first_name'] = first
profile['last_name'] = last
for key, value in user_info.items():
profile[key] = value
return profile
user_profile = build_profile('albert', 'einstein',
location='princeton',
field='physics')
print(user_profile)
# 6. 解包参数 (* 和 **)
# -------------------
a = [1, 2, 3]
b = {'a': 1, 'b': 2}
print(*a) # 解包列表作为位置参数
# 使用 ** 解包字典作为关键字参数
def my_function(a, b, c):
print(f"a={a}, b={b}, c={c}")
params = {'a': 1, 'b': 2, 'c': 3}
my_function(**params) # 将字典解包为关键字参数
# 7. Lambda函数（匿名函数）
# ---------------------
# 简单的lambda函数
square = lambda x: x ** 2
print(f"Square of 5: {square(5)}")
# 在高阶函数中使用lambda
numbers = [1, 2, 3, 4, 5]
squared_numbers = list(map(lambda x: x**2, numbers))
print(f"Squared numbers: {squared_numbers}")
# 8. 作用域和全局变量
# ----------------
# 全局变量
counter = 0
def increment():
global counter # 声明使用全局变量
counter += 1
return counter
print(f"Counter before: {counter}")
print(f"Counter after increment: {increment()}")
# 9. 文档字符串
# ------------
def factorial(n):
"""
计算n的阶乘
Args:
n (int): 需要计算阶乘的非负整数
Returns:
int: n的阶乘值
Raises:
ValueError: 当n为负数时抛出异常
"""
if n < 0:
raise ValueError("Factorial is not defined for negative numbers")
if n == 0 or n == 1:
return 1
result = 1
for i in range(2, n+1):
result *= i
return result
print(f"Factorial of 5: {factorial(5)}")
# 10. 函数装饰器基础
# ----------------
def my_decorator(func):
def wrapper():
print("Something is happening before the function is called.")
func()
print("Something is happening after the function is called.")
return wrapper
@my_decorator
def say_hello():
print("Hello!")
say_hello()
# 11. 递归函数
# ----------
# 添加记忆化版本的斐波那契函数
def fibonacci_memo(n, memo={}):
"""
使用记忆化技术计算斐波那契数列的第n项
避免重复计算，提高效率
Args:
n (int): 斐波那契数列的索引
memo (dict): 存储已计算结果的字典
Returns:
int: 斐波那契数列第n项的值
"""
# 如果已经计算过，直接返回结果
if n in memo:
return memo[n]
# 基础情况
if n <= 1:
return n
# 递归计算并存储结果
memo[n] = fibonacci_memo(n-1, memo) + fibonacci_memo(n-2, memo)
return memo[n]
# 使用装饰器实现记忆化功能
def memoize(func):
cache = {}
def wrapper(n):
if n not in cache:
cache[n] = func(n)
return cache[n]
return wrapper
@memoize
def fibonacci_decorated(n):
"""使用装饰器实现记忆化的斐波那契函数"""
if n <= 1:
return n
else:
return fibonacci_decorated(n-1) + fibonacci_decorated(n-2)
print(f"Fibonacci sequence (first 10 terms) using memoization:")
for i in range(10):
print(f"F({i}) = {fibonacci_memo(i)}")
print(f"\nFibonacci sequence (first 10 terms) using decorator:")
for i in range(10):
print(f"F({i}) = {fibonacci_decorated(i)}")
# 原始版本（保留作对比）
def fibonacci(n):
"""计算斐波那契数列的第n项"""
if n <= 1:
return n
else:
return fibonacci(n-1) + fibonacci(n-2)
print(f"Fibonacci sequence (first 10 terms):")
for i in range(10):
print(f"F({i}) = {fibonacci(i)}")
