实现数据模型的类型约束

在这个问题中，你需要在对某些实例属性赋值时进行检查。 所以你要自定义属性赋值函数，这种情况下最好使用描述器。

下面的代码使用描述器实现了一个系统类型和赋值验证框架：

# Base class. Uses a descriptor to set a value
class Descriptor:
    def __init__(self, name=None, **opts):
        self.name = name
        for key, value in opts.items():
            setattr(self, key, value)

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


# Descriptor for enforcing types
class Typed(Descriptor):
    expected_type = type(None)

    def __set__(self, instance, value):
        if not isinstance(value, self.expected_type):
            raise TypeError('expected ' + str(self.expected_type))
        super().__set__(instance, value)


# Descriptor for enforcing values
class Unsigned(Descriptor):
    def __set__(self, instance, value):
        if value < 0:
            raise ValueError('Expected >= 0')
        super().__set__(instance, value)


class MaxSized(Descriptor):
    def __init__(self, name=None, **opts):
        if 'size' not in opts:
            raise TypeError('missing size option')
        super().__init__(name, **opts)

    def __set__(self, instance, value):
        if len(value) >= self.size:
            raise ValueError('size must be < ' + str(self.size))
        super().__set__(instance, value)
这些类就是你要创建的数据模型或类型系统的基础构建模块。 下面就是我们实际定义的各种不同的数据类型：

class Integer(Typed):
    expected_type = int

class UnsignedInteger(Integer, Unsigned):
    pass

class Float(Typed):
    expected_type = float

class UnsignedFloat(Float, Unsigned):
    pass

class String(Typed):
    expected_type = str

class SizedString(String, MaxSized):
    pass
然后使用这些自定义数据类型，我们定义一个类：

class Stock:
    # Specify constraints
    name = SizedString('name', size=8)
    shares = UnsignedInteger('shares')
    price = UnsignedFloat('price')

    def __init__(self, name, shares, price):
        self.name = name
        self.shares = shares
        self.price = price
然后测试这个类的属性赋值约束，可发现对某些属性的赋值违法了约束是不合法的：

>>> s.name
'ACME'
>>> s.shares = 75
>>> s.shares = -10
Traceback (most recent call last):
    File "<stdin>", line 1, in <module>
    File "example.py", line 17, in __set__
        super().__set__(instance, value)
    File "example.py", line 23, in __set__
        raise ValueError('Expected >= 0')
ValueError: Expected >= 0
>>> s.price = 'a lot'
Traceback (most recent call last):
    File "<stdin>", line 1, in <module>
    File "example.py", line 16, in __set__
        raise TypeError('expected ' + str(self.expected_type))
TypeError: expected <class 'float'>
>>> s.name = 'ABRACADABRA'
Traceback (most recent call last):
    File "<stdin>", line 1, in <module>
    File "example.py", line 17, in __set__
        super().__set__(instance, value)
    File "example.py", line 35, in __set__
        raise ValueError('size must be < ' + str(self.size))
ValueError: size must be < 8
>>>
还有一些技术可以简化上面的代码，其中一种是使用类装饰器：

# Class decorator to apply constraints
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

# Example
@check_attributes(name=SizedString(size=8),
                  shares=UnsignedInteger,
                  price=UnsignedFloat)
class Stock:
    def __init__(self, name, shares, price):
        self.name = name
        self.shares = shares
        self.price = price
另外一种方式是使用元类：

# A metaclass that applies checking
class checkedmeta(type):
    def __new__(cls, clsname, bases, methods):
        # Attach attribute names to the descriptors
        for key, value in methods.items():
            if isinstance(value, Descriptor):
                value.name = key
        return type.__new__(cls, clsname, bases, methods)

# Example
class Stock2(metaclass=checkedmeta):
    name = SizedString(size=8)
    shares = UnsignedInteger()
    price = UnsignedFloat()

    def __init__(self, name, shares, price):
        self.name = name
        self.shares = shares
        self.price = price