07 python元类编程

property动态属性

根据生日获取年龄案例

@property   把函数编程一个属性，获取值

@类属性函数名.setter 设置一个属性

使用property属性可以获取一个值加入自己的逻辑

from datetime import date, datetime
class User:
    def __init__(self, name, birthday):
        self.name = name
        self.birthday = birthday
        self._age = 0

    @property
    def age(self):
        return datetime.now().year - self.birthday.year

    @age.setter
    def age(self, value):
        self._age = value

if __name__ == "__main__":
    user = User("bobby", date(year=1987, month=1, day=1))
    user.age = 30
    print (user._age)
    print(user.age)

　

输出结果如下　

 

__getattr__、__getattribute__魔法函数

__getattr__   在查找不到属性的时候，python就会调用这个魔法函数，可避免出现报错信息

from datetime import date
class User:
    def __init__(self,info={}):
        self.info = info

    def __getattr__(self, item):
        return self.info[item]

if __name__ == "__main__":
    user = User(info={"company_name":"imooc", "name":"bobby"})
    print(user.name)

 

打印结果如下

 

__getattribute__    对象只要调用属性，无论能否找到这个属性，都会先调用这个魔法函数，比__getattr__的优先级高

from datetime import date
class User:
    def __init__(self,info={}):
        self.info = info

    # def __getattr__(self, item):
    #     return self.info[item]

    def __getattribute__(self, item):
        return "bobby"

if __name__ == "__main__":
    user = User(info={"company_name":"imooc", "name":"bobby"})
    print(user.name)
    print(user.company_name)

　打印结果如下

 

属性描述符和属性查找过程

 在一个类中实现__get__，__set__，__delete__三个之中的任一个方法，那我们就成为这个类为属性描述符

 

案例：验证属性类型，如果类型正确，保存起来；否则，报自定义错误信息

 使用属性描述符后赋值会把值给属性描述符对象，取值也从属性描述符中获取

import numbers

class IntField:  # 整形的属性描述符
    # 数据描述符可按照自定义的逻辑来检查对象
    """
    instance 在这里指的是 user对象
    """
    def __get__(self, instance, owner):
        return self.value

    def __set__(self, instance, value):
        if not isinstance(value, numbers.Integral):
            raise ValueError("int value need")
        if value < 0:
            raise ValueError("positive value need")

        self.value = value

    def __delete__(self, instance):
        pass


class User:
    age = IntField()  # 这里的age是一个属性描述符的对象


if __name__ == "__main__":
    user = User()
    user.age = 30  # 调用上面的__set__函数 ,把值保存在 InField.value= value
    print(user.age)  # 调用上面的__get__函数  ,从IntField中取值

　　

输出结果如下 （如果不是整形会报错）

数据描述符

class IntField:
    #数据描述符
    def __get__(self, instance, owner):
        return self.value
    def __set__(self, instance, value):
        if not isinstance(value, numbers.Integral):
            raise ValueError("int value need")
        if value < 0:
            raise ValueError("positive value need")
        self.value = value
    def __delete__(self, instance):
        pass

非数据描述符

class NonDataIntField:
    #非数据属性描述符
    def __get__(self, instance, owner):
        return self.value　

对象查找一个属性的顺序

user = User(), 那么user.age 顺序如下：

（1）如果“age”是出现在User或其基类的__dict__中， 且age是data descriptor， 那么调用其__get__方法, 否则

（2）如果“age”出现在user的__dict__中， 那么直接返回 obj.__dict__[‘age’]， 否则

（3）如果“age”出现在User或其基类的__dict__中

（3.1）如果age是non-data descriptor，那么调用其__get__方法， 否则

（3.2）返回 __dict__[‘age’]

（4）如果User有__getattr__方法，调用__getattr__方法，否则

（5）抛出AttributeError

 __new__和__init__的区别

 __new__允许在生成类的对象之前添加逻辑，它传进来的参数cls表示类本身，可自定义类的生成过程，返回一个对象

__init__传进来的参数self表示类的对象本身，是用来完善对象的初始化

调用__new__函数生成对象之后，并且__new__方法中要返回对象，才会调用__init__函数

利用__new__生成一个单例

class User:
    _instance = False

    def __new__(cls, *args, **kwargs):
        if not cls._instance:
            cls._instance = super().__new__(cls)
        return cls._instance
    def __init__(self, name):
        self.name = name

if __name__ == "__main__":
    user1 = User(name="bobby1")
    user2 = User(name="bobby2")
    print(id(user1),id(user2))

打印结果如下

自定义元类

 type也可以动态创建类，type('类名'，（继承的类），{属性和方法})

def say(self):
    return "i am user"


class BaseClass:
    def answer(self):
        return "i am baseclass"


USER = type("User", (BaseClass,), {"name": "jack", "age": "14", "say": say})
my_obj = USER()

print(type(my_obj))
print(my_obj.age)
print(my_obj.say())
print(my_obj.answer())

　　

输出结果如下

 

什么是元类？

 元类是创建类的类，比如type，常见的用法是定义一个类来继承type，那么这个新定义的类就是元类python中类的实例化过程

首先找自定义的metaclass, 通过metaclass来创建类对象，如果没有metaclass, 则会使用type来创建类对象

 

class MetaClass(type):
    def __new__(cls, *args, **kwargs):
        return super().__new__(cls, *args, **kwargs)

class User(metaclass=MetaClass):
    def __init__(self, name):
        self.name = name

    def __str__(self):
        return "user"
    
if __name__ == "__main__":
    my_obj = User(name="jack")
    print(my_obj)

　

调试结果如下

通过元类实现orm

使用元类可以实现类型的检查一些值的设定

 用元类模仿django的orm

# 需求
import numbers


class Field:
    pass

class IntField(Field):
    # 数据描述符
    def __init__(self, db_column, min_value=None, max_value=None):
        self._value = None
        self.min_value = min_value
        self.max_value = max_value
        self.db_column = db_column
        if min_value is not None:
            if not isinstance(min_value, numbers.Integral):
                raise ValueError("min_value must be int")
            elif min_value < 0:
                raise ValueError("min_value must be positive int")
        if max_value is not None:
            if not isinstance(max_value, numbers.Integral):
                raise ValueError("max_value must be int")
            elif max_value < 0:
                raise ValueError("max_value must be positive int")
        if min_value is not None and max_value is not None:
            if min_value > max_value:
                raise ValueError("min_value must be smaller than max_value")

    def __get__(self, instance, owner):
        return self._value

    def __set__(self, instance, value):
        if not isinstance(value, numbers.Integral):
            raise ValueError("int value need")
        if value < self.min_value or value > self.max_value:
            raise ValueError("value must between min_value and max_value")
        self._value = value


class CharField(Field):
    def __init__(self, db_column, max_length=None):
        self._value = None
        self.db_column = db_column
        if max_length is None:
            raise ValueError("you must spcify max_lenth for charfiled")
        self.max_length = max_length

    def __get__(self, instance, owner):
        return self._value

    def __set__(self, instance, value):
        if not isinstance(value, str):
            raise ValueError("string value need")
        if len(value) > self.max_length:
            raise ValueError("value len excess len of max_length")
        self._value = value


class ModelMetaClass(type):
    def __new__(cls, name, bases, attrs, **kwargs):
        if name == "BaseModel":
            return super().__new__(cls, name, bases, attrs, **kwargs)
        fields = {}
        for key, value in attrs.items():
            if isinstance(value, Field):
                fields[key] = value
        attrs_meta = attrs.get("Meta", None)
        _meta = {}
        db_table = name.lower()
        if attrs_meta is not None:
            table = getattr(attrs_meta, "db_table", None)
            if table is not None:
                db_table = table
        _meta["db_table"] = db_table
        attrs["_meta"] = _meta
        attrs["fields"] = fields
        del attrs["Meta"]
        return super().__new__(cls, name, bases, attrs, **kwargs)


class BaseModel(metaclass=ModelMetaClass):
    def __init__(self, *args, **kwargs):
        for key, value in kwargs.items():
            setattr(self, key, value)
        return super().__init__()

    def save(self):
        fields = []
        values = []
        for key, value in self.fields.items():
            db_column = value.db_column
            if db_column is None:
                db_column = key.lower()
            fields.append(db_column)
            value = getattr(self, key)
            values.append(str(value))

        sql = "insert {db_table}({fields}) value({values})".format(db_table=self._meta["db_table"],
                                                                   fields=",".join(fields), values=",".join(values))
        pass

class User(BaseModel):
    name = CharField(db_column="name", max_length=10)
    age = IntField(db_column="age", min_value=1, max_value=100)

    class Meta:
        db_table = "user"


if __name__ == "__main__":
    user = User(name="bobby", age=28)
    # user.name = "bobby"
    # user.age = 28
    user.save()

 调试结果如下