如何理解Python的描述符（Descriptor）？

obj.attr

attr

__get__

__set__

__delete__

attr

@property

get_foo()

set_foo()

setter

getter

obj.method()

obj.__dict__

method

method

__get__

obj

self

obj.method

obj.method = 123

obj.__dict__

method

obj.method

123

@property

class DataDescriptor:
    def __get__(self, instance, owner):
        print(f"DataDescriptor __get__ called for {instance}")
        return instance._value if instance else "Class-level data"
    def __set__(self, instance, value):
        print(f"DataDescriptor __set__ called for {instance} with value {value}")
        instance._value = value # 通常将值存储在实例的私有属性中

class NonDataDescriptor:
    def __get__(self, instance, owner):
        print(f"NonDataDescriptor __get__ called for {instance}")
        return "Non-data value from descriptor"

class MyClass:
    data_attr = DataDescriptor()
    non_data_attr = NonDataDescriptor()

    def __init__(self, initial_value):
        self.data_attr = initial_value # 触发DataDescriptor.__set__
        self.instance_specific = "Instance specific value"

print("--- 访问数据描述符 ---")
obj = MyClass(100)
print(f"obj.data_attr: {obj.data_attr}") # 调用DataDescriptor.__get__
obj.data_attr = 200 # 再次调用DataDescriptor.__set__
print(f"obj.data_attr after update: {obj.data_attr}") # 再次调用DataDescriptor.__get__

# 即使我们在实例上设置了一个同名属性，数据描述符依然会优先
obj.__dict__['data_attr'] = "直接设置到实例字典"
print(f"obj.data_attr (after direct dict set): {obj.data_attr}") # 仍然是DataDescriptor.__get__被调用

print("\n--- 访问非数据描述符 ---")
print(f"obj.non_data_attr: {obj.non_data_attr}") # 调用NonDataDescriptor.__get__

# 现在，我们在实例上设置一个同名属性
obj.non_data_attr = "实例覆盖了描述符"
print(f"obj.non_data_attr (after instance override): {obj.non_data_attr}") # 直接从obj.__dict__获取，描述符不再被调用

print(f"MyClass.non_data_attr: {MyClass.non_data_attr}") # 通过类访问，描述符依然有效

__get__

__set__

__delete__

class TypeValidator:
    def __init__(self, expected_type):
        self.expected_type = expected_type
        self._private_name = None # 用于存储属性的实际名称

    def __set_name__(self, owner, name):
        """
        Python 3.6+ 引入的魔法方法，在描述符被赋值给类属性时调用。
        它允许描述符知道它被分配到的属性名称。
        """
        self._private_name = f'_{name}' # 用一个私有名称来存储实际值，避免与描述符自身冲突

    def __get__(self, instance, owner):
        if instance is None:
            return self # 通过类访问时，返回描述符自身
        # 从实例的字典中获取实际存储的值
        return instance.__dict__.get(self._private_name)

    def __set__(self, instance, value):
        if not isinstance(value, self.expected_type):
            raise TypeError(f"属性 '{self._private_name.lstrip('_')}' 期望类型为 {self.expected_type.__name__}, 但得到 {type(value).__name__}")
        # 将验证后的值存储到实例的字典中，使用私有名称
        instance.__dict__[self._private_name] = value

    def __delete__(self, instance):
        if self._private_name in instance.__dict__:
            del instance.__dict__[self._private_name]
        else:
            raise AttributeError(f"属性 '{self._private_name.lstrip('_')}' 未设置")

class User:
    name = TypeValidator(str)
    age = TypeValidator(int)
    email = TypeValidator(str) # 假设邮件也是字符串

    def __init__(self, name, age, email):
        self.name = name   # 触发 TypeValidator.__set__
        self.age = age     # 触发 TypeValidator.__set__
        self.email = email # 触发 TypeValidator.__set__

print("--- 创建一个有效的用户对象 ---")
user1 = User("Alice", 30, "alice@example.com")
print(f"用户1姓名: {user1.name}, 年龄: {user1.age}, 邮箱: {user1.email}")

print("\n--- 尝试设置一个无效类型的值 ---")
try:
    user1.age = "thirty" # 期望引发 TypeError
except TypeError as e:
    print(f"错误: {e}")

print("\n--- 再次检查用户1的年龄，确保未被修改 ---")
print(f"用户1年龄: {user1.age}")

print("\n--- 尝试删除属性 ---")
try:
    del user1.email
    print(f"用户1邮箱删除成功。现在访问: {user1.email}") # 应该返回None或引发AttributeError
except AttributeError as e:
    print(f"错误: {e}")

print("\n--- 通过类访问描述符 ---")
print(User.name) # 应该返回TypeValidator实例

TypeValidator

TypeValidator

User

TypeValidator

User

name

age

__dict__

__get__

__set__