1. 装饰器(Decorators)

装饰器是Python的高级特性,用于修改函数行为而无需改变其源代码。常见用法包括日志记录、权限验证等。

Python_decorator
示例: ```python def my_decorator(func): def wrapper(): print("装饰器前置操作") func() print("装饰器后置操作") return wrapper

@my_decorator def say_hello(): print("Hello")

say_hello()

🔗 [了解更多装饰器进阶用法](/Community/Tutorials/PythonDecorators)

## 2. 生成器(Generators)
生成器通过`yield`关键字实现,可高效处理大数据集。  
<center><img src="https://cloud-image.ullrai.com/q/Python_generator/" alt="Python_generator"/></center>  
示例:  
```python
def count_up_to(n):
    count = 1
    while count <= n:
        yield count
        count += 1

for number in count_up_to(5):
    print(number)

🔍 探索生成器与迭代器的区别

3. 上下文管理器(Context Managers)

使用with语句管理资源,确保文件正确关闭或数据库连接释放。

Python_context_manager
示例: ```python with open("file.txt", "r") as f: content = f.read() print(content) ``` 📌 [查看上下文管理器实战案例](/Community/Tutorials/PythonContext)

4. 元编程(Metaprogramming)

通过type()元类实现动态创建类与对象。

Python_metaprogramming
示例: ```python class Meta(type): def __new__(cls, name, bases, dct): print("元类创建类") return super().__new__(cls, name, bases, dct)

class MyClass(metaclass=Meta): pass

💡 [深入元编程原理与应用](/Community/Tutorials/PythonMetaprogramming)

## 5. 异步编程(Async Programming)
使用`async/await`实现非阻塞I/O操作,提升程序性能。  
<center><img src="https://cloud-image.ullrai.com/q/Python_async/" alt="Python_async"/></center>  
示例:  
```python
import asyncio

async def my_async_function():
    await asyncio.sleep(1)
    print("异步任务完成")

asyncio.run(my_async_function())

📚 异步编程与协程详解