Python 装饰器详解：@staticmethod 与 @classmethod 的区别与用法：中英双语

缘由：
今天在看Huggingface的源码的时候， https://github.com/huggingface/transformers/blob/v4.47.1/src/transformers/models/auto/configuration_auto.py#L897

对几个装饰器有所疑问，学习一下。

Python 装饰器详解：@staticmethod 与 @classmethod 的区别与用法

在 Python 中，@staticmethod 和 @classmethod 是两种常用的装饰器，用于定义类中的特殊方法。它们允许我们在不创建类实例的情况下访问方法，但具体功能和应用场景有所不同。

本文将详细解析它们的用法、区别，并结合代码示例帮助理解。

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一、装饰器是什么？

在 Python 中，装饰器 是一种用于修改或增强函数、方法或类行为的特殊函数或语法糖。装饰器本质上是一个高阶函数，它接收一个函数或类作为输入，返回一个修改后的函数或类。例如：

def decorator(func):
    def wrapper():
        print("Before function call.")
        func()
        print("After function call.")
    return wrapper

@decorator  # 等价于 say_hello = decorator(say_hello)
def say_hello():
    print("Hello!")

say_hello()

输出：

Before function call.
Hello!
After function call.

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二、@staticmethod —— 静态方法

1. 定义与特点

@staticmethod 将类中的方法定义为静态方法，即不依赖于实例，也不依赖于类本身。因此，它既无法访问实例变量，也无法访问类变量。

2. 使用场景

静态方法通常用于：

1. 逻辑相关，但不依赖类或实例数据的功能。
2. 工具类方法，例如格式转换、数学计算等辅助函数。

3. 示例代码

class MathUtils:
    @staticmethod
    def add(x, y):
        return x + y

    @staticmethod
    def multiply(x, y):
        return x * y

print(MathUtils.add(3, 5))       # 输出: 8
print(MathUtils.multiply(3, 5))  # 输出: 15

分析：

这里的 add 和 multiply 方法不需要访问实例或类属性，因此被定义为静态方法。

调用时可以通过类名直接访问，无需实例化对象：MathUtils.add(3, 5)。

4. 应用场景

1. 辅助函数： 如数学运算、格式转换等。
2. 与类相关的逻辑操作： 无需访问实例属性或类变量的逻辑代码。

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三、@classmethod —— 类方法

1. 定义与特点

@classmethod 将方法定义为类方法，它的第一个参数是类本身 (cls)，而不是实例 (self)。因此，类方法可以访问或修改类属性，但不能直接访问实例属性。

2. 使用场景

类方法通常用于：

1. 操作类变量或类级别的数据。
2. 工厂方法，根据不同需求创建类的实例。
3. 管理类注册机制。

3. 示例代码

class Person:
    count = 0  # 类变量，记录人数

    def __init__(self, name):
        self.name = name
        Person.count += 1

    @classmethod
    def get_count(cls):
        return cls.count

# 创建实例
p1 = Person("Alice")
p2 = Person("Bob")

print(Person.get_count())  # 输出: 2

分析：

get_count 是类方法，使用 cls 访问类变量 count。

通过 Person.get_count() 调用类方法，不需要创建实例。

4. 应用场景

1. 访问类变量： 用于统计类级别的数据，如计数器、共享配置等。
2. 工厂方法： 根据不同的需求动态创建实例。例如：

class Animal:
    def __init__(self, species):
        self.species = species

    @classmethod
    def create_dog(cls):
        return cls("Dog")

    @classmethod
    def create_cat(cls):
        return cls("Cat")

dog = Animal.create_dog()
cat = Animal.create_cat()
print(dog.species)  # 输出: Dog
print(cat.species)  # 输出: Cat

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四、二者对比

特点	@staticmethod	@classmethod
是否绑定实例或类	不绑定实例或类	绑定类 (cls)
能否访问实例属性	否	否
能否访问类变量	否	可以
参数中的特殊符号	无特殊参数	第一个参数是 cls，表示类本身
适合的应用场景	工具函数、辅助计算逻辑	操作类变量、工厂方法、管理类注册等
调用方式	类名或实例均可调用：Class.method()	类名或实例均可调用：Class.method()

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五、示例分析：管理配置注册机制

结合开头提供的代码，以下是示例解析：

class CONFIG_MAPPING:
    _mapping = {}

    @staticmethod
    def register(model_type, config, exist_ok=False):
        # 检查是否已存在
        if model_type in CONFIG_MAPPING._mapping and not exist_ok:
            raise ValueError(f"Model {model_type} already exists!")
        # 注册新配置
        CONFIG_MAPPING._mapping[model_type] = config

    @classmethod
    def get_config(cls, model_type):
        # 使用类方法访问类级变量 _mapping
        if model_type not in cls._mapping:
            raise ValueError(f"Unknown model type: {model_type}")
        return cls._mapping[model_type]

代码解释：

1. register 是一个静态方法，因为它不依赖类或实例变量，仅执行逻辑判断和字典更新。
2. get_config 是一个类方法，允许访问类级别变量 _mapping。即使通过子类调用，也能正确访问。

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六、总结

@staticmethod 用于定义独立于类和实例的逻辑功能，是一种实用工具函数，适合辅助计算和格式转换。

@classmethod 与类绑定，可以访问和修改类变量，适合工厂方法和管理类级别的状态或配置。

它们都属于 Python 的面向对象特性，通过装饰器简化代码设计，提高可维护性和复用性。在实际项目中，应根据需求选择合适的方法定义类型。例如：

不需要访问类或实例数据时，选择 @staticmethod。

需要访问类级变量或动态创建实例时，选择 @classmethod。

英文版

Understanding Python Decorators: @staticmethod vs @classmethod

In Python, decorators like @staticmethod and @classmethod are used to define special types of methods within a class. These methods provide flexibility and allow you to write cleaner, more modular code by specifying how methods behave in relation to the class and its instances.

This blog post will explain the differences between these two decorators, their use cases, and examples to make the concepts clear.

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1. What is a Decorator?

A decorator in Python is a function that modifies the behavior of another function or method. It is often used to add additional functionality without altering the original code. For example:

def decorator(func):
    def wrapper():
        print("Before function call.")
        func()
        print("After function call.")
    return wrapper

@decorator
def say_hello():
    print("Hello!")

say_hello()

Output:

Before function call.
Hello!
After function call.

Here, @decorator modifies the behavior of say_hello. Similarly, @staticmethod and @classmethod are built-in decorators that define specific behaviors for methods in a class.

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2. @staticmethod — Static Methods

Definition and Features:

A static method is defined using the @staticmethod decorator.

It does not depend on instance (self) or class (cls) data.

Static methods act as utility functions related to the class but operate independently of instance or class variables.

Use Cases:

1. Utility functions like calculations or data formatting.
2. Logical operations related to the class that do not require class or instance context.

Example:

class MathUtils:
    @staticmethod
    def add(x, y):
        return x + y

    @staticmethod
    def multiply(x, y):
        return x * y

print(MathUtils.add(3, 5))       # Output: 8
print(MathUtils.multiply(3, 5))  # Output: 15

Explanation:

add and multiply are static methods because they do not rely on any class-level or instance-level variables.

They can be directly called using the class name: MathUtils.add(3, 5).

Key Takeaway:

Static methods are perfect for utility functions that belong to the class logically but do not need access to its attributes or methods.

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3. @classmethod — Class Methods

Definition and Features:

A class method is defined using the @classmethod decorator.

It takes the class (cls) as the first argument instead of the instance (self).

It can access or modify class variables but cannot access instance-specific data.

Use Cases:

1. Access or modify class-level data.
2. Implement factory methods to create instances in a flexible manner.

Example 1 — Class-Level Counter:

class Person:
    count = 0  # Class variable

    def __init__(self, name):
        self.name = name
        Person.count += 1

    @classmethod
    def get_count(cls):
        return cls.count

p1 = Person("Alice")
p2 = Person("Bob")

print(Person.get_count())  # Output: 2

Explanation:

get_count is a class method that accesses the class variable count.

It does not depend on any specific instance but provides information about the class as a whole.

Example 2 — Factory Method:

class Animal:
    def __init__(self, species):
        self.species = species

    @classmethod
    def create_dog(cls):
        return cls("Dog")

    @classmethod
    def create_cat(cls):
        return cls("Cat")

dog = Animal.create_dog()
cat = Animal.create_cat()

print(dog.species)  # Output: Dog
print(cat.species)  # Output: Cat

Explanation:

create_dog and create_cat are factory methods used to create instances of Animal with predefined attributes.

The cls argument ensures the method works correctly even if the class is subclassed.

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4. Key Differences: @staticmethod vs @classmethod

Feature	@staticmethod	@classmethod
Access to instance data	No	No
Access to class data	No	Yes
Requires self or cls	No	Yes (cls is mandatory)
Purpose	Utility methods unrelated to class data	Methods that operate on class-level data
Common Usage	Helper functions (e.g., math calculations)	Factory methods, configuration methods

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5. Example: Configuration Management System

The example below demonstrates how both decorators can be combined in a configuration management system.

class ConfigRegistry:
    _configs = {}

    @staticmethod
    def is_valid_config(config):
        # Check if the config is valid (e.g., a dictionary with certain keys)
        return isinstance(config, dict) and "name" in config and "version" in config

    @classmethod
    def register_config(cls, name, config):
        # Register a configuration for later use
        if not cls.is_valid_config(config):
            raise ValueError("Invalid configuration!")
        cls._configs[name] = config

    @classmethod
    def get_config(cls, name):
        # Retrieve a registered configuration
        if name not in cls._configs:
            raise ValueError(f"No config found for {name}")
        return cls._configs[name]

Key Observations:

Static Method: is_valid_config checks if the configuration is valid without needing any class or instance variables.

Class Methods:

register_config modifies the class variable _configs.

get_config retrieves data stored at the class level.

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6. When to Use Which?

Scenario	Recommended Decorator
Utility methods that are independent of class or instance data	@staticmethod
Methods that operate on or modify class-level data	@classmethod
Factory methods to create instances dynamically	@classmethod
Helper methods for calculations or string manipulations	@staticmethod

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7. Final Thoughts

Both @staticmethod and @classmethod are powerful tools for defining flexible, reusable methods in Python classes.

Use @staticmethod when your method performs operations unrelated to class or instance data.

Use @classmethod when your method needs access to class-level attributes or needs to create instances dynamically.

By understanding these decorators, you can write cleaner, modular, and scalable code, especially for large-scale projects involving configuration management, model registrations, or utility functions.

后记

2024年12月23日14点36分于上海，在GPT4o大模型辅助下完成。

作者：阿正的梦工坊