装饰器模式、策略模式和回调模式。

下面我将提供三种设计模式的Python实现示例：装饰器模式、策略模式和回调模式。

1. 装饰器模式

装饰器模式允许我们向一个对象添加新的功能，同时不改变其结构。在Python中，装饰器通常是一个函数，它接受一个函数作为参数并返回一个新的函数。

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()  # 输出: Something is happening before... Hello! ...after the function is called.

2. 策略模式

策略模式定义了一系列算法，并将每一个算法封装起来，使它们可以互换。策略模式让算法独立于使用它的客户端。

from abc import ABC, abstractmethod

class Strategy(ABC):
    @abstractmethod
    def execute(self):
        pass

class ConcreteStrategyA(Strategy):
    def execute(self):
        return "Executed strategy A"

class ConcreteStrategyB(Strategy):
    def execute(self):
        return "Executed strategy B"

class Context:
    def __init__(self, strategy: Strategy):
        self.strategy = strategy

    def set_strategy(self, strategy: Strategy):
        self.strategy = strategy

    def do_operation(self):
        return self.strategy.execute()

# 使用策略模式
context = Context(ConcreteStrategyA())
print(context.do_operation())  # 输出: Executed strategy A

context.set_strategy(ConcreteStrategyB())
print(context.do_operation())  # 输出: Executed strategy B

3. 回调函数

回调模式允许一个函数作为参数传递给另一个函数，然后在某个点被调用。这在事件处理、异步编程等领域非常常见。

def callback_function(data):
    print(f"Callback received data: {data}")

def function_with_callback(data, callback):
    print("Function is processing data.")
    # 模拟数据处理
    processed_data = data + " and processed it."
    callback(processed_data)

function_with_callback("Function received", callback_function)
# 输出: Function is processing data. Callback received data: Function received and processed it.

在上述示例中，callback_function 是一个回调函数，它被作为参数传递给 function_with_callback 函数，并在数据处理完成后被调用。