数据模型的类型的约束

基于描述符建立数据模型实现赋值验证框架

在实例属性的获取和设定方面，前面已经提过可以使用property和描述符实现

1、创建数据模型的基础构建模块

class Descriptor:
    def __init__(self, name=None, **opts):
        self.name = name
        for key, val in opts.items():
            setattr(self, key, val)

    def __set__(self, instance, value):
        instance.__dict__[self.name] = value


class Typed(Descriptor):
    expected_type = type(None)

    def __set__(self, instance, value):
        if not isinstance(value, self.expected_type):
            raise TypeError("expect:{}".format(self.expected_type))
        super().__set__(instance, value)


class Unsigned(Descriptor):
    def __set__(self, instance, value):
        if value < 0:
            raise ValueError("expect > 0")
        super().__set__(instance, value)

接着

2、定义不同的数据类型

class Interger(Typed):
    expected_type = int


class Float(Typed):
    expected_type = float


class String(Typed):
    expected_type = str

接着

3、介入类装饰器

def check_attributes(**kwargs):
    def decorate(cls):
        for key, value in kwargs.items():
            if isinstance(value, Descriptor):
                value.name = key
                setattr(cls, key, value)
            else:
                setattr(cls, key, value(key))
        return cls

    return decorate

最后

4、应用

@check_attributes(
    name=String,
    age=Interger
)
class Valley:

    def __init__(self):
        self.name = "g"
        self.age = 26


if __name__ == '__main__':
    print(Valley().__dict__)

整合

class Descriptor:
    def __init__(self, name=None, **opts):
        self.name = name
        for key, val in opts.items():
            setattr(self, key, val)

    def __set__(self, instance, value):
        instance.__dict__[self.name] = value


class Typed(Descriptor):
    expected_type = type(None)

    def __set__(self, instance, value):
        if not isinstance(value, self.expected_type):
            raise TypeError("expect:{}".format(self.expected_type))
        super().__set__(instance, value)


class Unsigned(Descriptor):
    def __set__(self, instance, value):
        if value < 0:
            raise ValueError("expect > 0")
        super().__set__(instance, value)


class Interger(Typed):
    expected_type = int


class Float(Typed):
    expected_type = float


class String(Typed):
    expected_type = str


def check_attributes(**kwargs):
    def decorate(cls):
        for key, value in kwargs.items():
            if isinstance(value, Descriptor):
                value.name = key
                setattr(cls, key, value)
            else:
                setattr(cls, key, value(key))
        return cls

    return decorate


@check_attributes(
    name=String,
    age=Interger
)
class Valley:

    def __init__(self):
        self.name = "g"
        self.age = 26


if __name__ == '__main__':
    print(Valley().__dict__)

这一块还是要好好琢磨琢磨