描述符(__get__,__set__,__delete__)

目录

描述符

• 描述符是什么：描述符本质就是一个新式类，在这个新式类中，至少实现了__get__()，__set__()，__delete__()中的一个，这也被称为描述符协议

  • __get__()：调用一个属性时，触发

  • __set__()：为一个属性赋值时，触发

  • __delete__()：采用del删除属性时，触发

• 定义一个描述符

class foo:  # 在python3中foo是新式类，它实现了__get__()，__set__()，__delete__()中的一个三种方法的一个，这个类就被称作一个描述符
    def __get__(self, instance, owner):
        pass

    def __set__(self, instance, value):
        pass

    def __delete__(self, instance):
        pass

描述符的作用

• 描述符是干什么的：描述符的作用是用来代理另外一个类的属性的，必须把描述符定义成这个类的类属性，不能定义到构造函数中

class foo:
    def __get__(self, instance, owner):
        print('触发get')

    def __set__(self, instance, value):
        print('触发set')

    def __delete__(self, instance):
        print('触发delete')


f1 = foo()

• 包含这三个方法的新式类称为描述符，由这个类产生的实例进行属性的调用/赋值/删除，并不会触发这三个方法

f1.name = 'nick'
f1.name
del f1.name

何时，何地，会触发这三个方法的执行

class str:
    """描述符str"""

    def __get__(self, instance, owner):
        print('str调用')

    def __set__(self, instance, value):
        print('str设置...')

    def __delete__(self, instance):
        print('str删除...')


class int:
    """描述符int"""

    def __get__(self, instance, owner):
        print('int调用')

    def __set__(self, instance, value):
        print('int设置...')

    def __delete__(self, instance):
        print('int删除...')


class people:
    name = str()
    age = int()

    def __init__(self, name, age):  # name被str类代理，age被int类代理
        self.name = name
        self.age = age


# 何地？：定义成另外一个类的类属性

# 何时？：且看下列演示

p1 = people('alex', 18)

str设置...
int设置...

• 描述符str的使用

p1.name
p1.name = 'nick'
del p1.name

str调用
str设置...
str删除...

• 描述符int的使用

p1.age
p1.age = 18
del p1.age

int调用
int设置...
int删除...

• 我们来瞅瞅到底发生了什么

print(p1.__dict__)
print(people.__dict__)

{}
{'__module__': '__main__', 'name': <__main__.str object at 0x107a86940>, 'age': <__main__.int object at 0x107a863c8>, '__init__': <function people.__init__ at 0x107ba2ae8>, '__dict__': <attribute '__dict__' of 'people' objects>, '__weakref__': <attribute '__weakref__' of 'people' objects>, '__doc__': none}

• 补充

print(type(p1) == people)  # type(obj)其实是查看obj是由哪个类实例化来的
print(type(p1).__dict__ == people.__dict__)

true
true

两种描述符

数据描述符

• 至少实现了__get__()和__set__()

class foo:
    def __set__(self, instance, value):
        print('set')

    def __get__(self, instance, owner):
        print('get')

非数据描述符

• 没有实现__set__()

class foo:
    def __get__(self, instance, owner):
        print('get')

描述符注意事项

1. 描述符本身应该定义成新式类，被代理的类也应该是新式类

2. 必须把描述符定义成这个类的类属性，不能为定义到构造函数中

3. 要严格遵循该优先级，优先级由高到底分别是

   1.类属性

   2.数据描述符

   3.实例属性

   4.非数据描述符

   5.找不到的属性触发__getattr__()

使用描述符

• 众所周知，python是弱类型语言，即参数的赋值没有类型限制，下面我们通过描述符机制来实现类型限制功能

牛刀小试

class str:
    def __init__(self, name):
        self.name = name

    def __get__(self, instance, owner):
        print('get--->', instance, owner)
        return instance.__dict__[self.name]

    def __set__(self, instance, value):
        print('set--->', instance, value)
        instance.__dict__[self.name] = value

    def __delete__(self, instance):
        print('delete--->', instance)
        instance.__dict__.pop(self.name)


class people:
    name = str('name')

    def __init__(self, name, age, salary):
        self.name = name
        self.age = age
        self.salary = salary


p1 = people('nick', 18, 3231.3)

set---> <__main__.people object at 0x107a86198> nick

• 调用

print(p1.__dict__)

{'name': 'nick', 'age': 18, 'salary': 3231.3}

print(p1.name)

get---> <__main__.people object at 0x107a86198> <class '__main__.people'>
nick

• 赋值

print(p1.__dict__)

{'name': 'nick', 'age': 18, 'salary': 3231.3}

p1.name = 'nicklin'
print(p1.__dict__)

set---> <__main__.people object at 0x107a86198> nicklin
{'name': 'nicklin', 'age': 18, 'salary': 3231.3}

• 删除

print(p1.__dict__)

{'name': 'nicklin', 'age': 18, 'salary': 3231.3}

del p1.name
print(p1.__dict__)

delete---> <__main__.people object at 0x107a86198>
{'age': 18, 'salary': 3231.3}

拔刀相助

class str:
    def __init__(self, name):
        self.name = name

    def __get__(self, instance, owner):
        print('get--->', instance, owner)
        return instance.__dict__[self.name]

    def __set__(self, instance, value):
        print('set--->', instance, value)
        instance.__dict__[self.name] = value

    def __delete__(self, instance):
        print('delete--->', instance)
        instance.__dict__.pop(self.name)


class people:
    name = str('name')

    def __init__(self, name, age, salary):
        self.name = name
        self.age = age
        self.salary = salary


# 疑问：如果我用类名去操作属性呢
try:
    people.name  # 报错，错误的根源在于类去操作属性时，会把none传给instance
except exception as e:
    print(e)

get---> none <class '__main__.people'>
'nonetype' object has no attribute '__dict__'

• 修订__get__方法

class str:
    def __init__(self, name):
        self.name = name

    def __get__(self, instance, owner):
        print('get--->', instance, owner)
        if instance is none:
            return self
        return instance.__dict__[self.name]

    def __set__(self, instance, value):
        print('set--->', instance, value)
        instance.__dict__[self.name] = value

    def __delete__(self, instance):
        print('delete--->', instance)
        instance.__dict__.pop(self.name)


class people:
    name = str('name')

    def __init__(self, name, age, salary):
        self.name = name
        self.age = age
        self.salary = salary


print(people.name)  # 完美，解决

get---> none <class '__main__.people'>
<__main__.str object at 0x107a86da0>

磨刀霍霍

class str:
    def __init__(self, name, expected_type):
        self.name = name
        self.expected_type = expected_type

    def __get__(self, instance, owner):
        print('get--->', instance, owner)
        if instance is none:
            return self
        return instance.__dict__[self.name]

    def __set__(self, instance, value):
        print('set--->', instance, value)
        if not isinstance(value, self.expected_type):  # 如果不是期望的类型，则抛出异常
            raise typeerror('expected %s' % str(self.expected_type))
        instance.__dict__[self.name] = value

    def __delete__(self, instance):
        print('delete--->', instance)
        instance.__dict__.pop(self.name)


class people:
    name = str('name', str)  # 新增类型限制str

    def __init__(self, name, age, salary):
        self.name = name
        self.age = age
        self.salary = salary


try:
    p1 = people(123, 18, 3333.3)  # 传入的name因不是字符串类型而抛出异常
except exception as e:
    print(e)

set---> <__main__.people object at 0x1084cd940> 123
expected <class 'str'>

大刀阔斧

class typed:
    def __init__(self, name, expected_type):
        self.name = name
        self.expected_type = expected_type

    def __get__(self, instance, owner):
        print('get--->', instance, owner)
        if instance is none:
            return self
        return instance.__dict__[self.name]

    def __set__(self, instance, value):
        print('set--->', instance, value)
        if not isinstance(value, self.expected_type):
            raise typeerror('expected %s' % str(self.expected_type))
        instance.__dict__[self.name] = value

    def __delete__(self, instance):
        print('delete--->', instance)
        instance.__dict__.pop(self.name)


class people:
    name = typed('name', str)
    age = typed('name', int)
    salary = typed('name', float)

    def __init__(self, name, age, salary):
        self.name = name
        self.age = age
        self.salary = salary


try:
    p1 = people(123, 18, 3333.3)
except exception as e:
    print(e)

set---> <__main__.people object at 0x1082c7908> 123
expected <class 'str'>

try:
    p1 = people('nick', '18', 3333.3)
except exception as e:
    print(e)

set---> <__main__.people object at 0x1078dd438> nick
set---> <__main__.people object at 0x1078dd438> 18
expected <class 'int'>

p1 = people('nick', 18, 3333.3)

set---> <__main__.people object at 0x1081b3da0> nick
set---> <__main__.people object at 0x1081b3da0> 18
set---> <__main__.people object at 0x1081b3da0> 3333.3

• 大刀阔斧之后我们已然能实现功能了，但是问题是，如果我们的类有很多属性，你仍然采用在定义一堆类属性的方式去实现，low，这时候我需要教你一招：独孤九剑

类的装饰器:无参

def decorate(cls):
    print('类的装饰器开始运行啦------>')
    return cls


@decorate  # 无参：people = decorate(people)
class people:
    def __init__(self, name, age, salary):
        self.name = name
        self.age = age
        self.salary = salary


p1 = people('nick', 18, 3333.3)

类的装饰器开始运行啦------>

类的装饰器:有参

def typeassert(**kwargs):
    def decorate(cls):
        print('类的装饰器开始运行啦------>', kwargs)
        return cls

    return decorate


@typeassert(
    name=str, age=int, salary=float
)  # 有参：1.运行typeassert(...)返回结果是decorate，此时参数都传给kwargs 2.people=decorate(people)
class people:
    def __init__(self, name, age, salary):
        self.name = name
        self.age = age
        self.salary = salary


p1 = people('nick', 18, 3333.3)

类的装饰器开始运行啦------> {'name': <class 'str'>, 'age': <class 'int'>, 'salary': <class 'float'>}

刀光剑影

class typed:
    def __init__(self, name, expected_type):
        self.name = name
        self.expected_type = expected_type

    def __get__(self, instance, owner):
        print('get--->', instance, owner)
        if instance is none:
            return self
        return instance.__dict__[self.name]

    def __set__(self, instance, value):
        print('set--->', instance, value)
        if not isinstance(value, self.expected_type):
            raise typeerror('expected %s' % str(self.expected_type))
        instance.__dict__[self.name] = value

    def __delete__(self, instance):
        print('delete--->', instance)
        instance.__dict__.pop(self.name)


def typeassert(**kwargs):
    def decorate(cls):
        print('类的装饰器开始运行啦------>', kwargs)
        for name, expected_type in kwargs.items():
            setattr(cls, name, typed(name, expected_type))
        return cls

    return decorate


@typeassert(
    name=str, age=int, salary=float
)  # 有参：1.运行typeassert(...)返回结果是decorate，此时参数都传给kwargs 2.people=decorate(people)
class people:
    def __init__(self, name, age, salary):
        self.name = name
        self.age = age
        self.salary = salary


print(people.__dict__)
p1 = people('nick', 18, 3333.3)

类的装饰器开始运行啦------> {'name': <class 'str'>, 'age': <class 'int'>, 'salary': <class 'float'>}
{'__module__': '__main__', '__init__': <function people.__init__ at 0x10797a400>, '__dict__': <attribute '__dict__' of 'people' objects>, '__weakref__': <attribute '__weakref__' of 'people' objects>, '__doc__': none, 'name': <__main__.typed object at 0x1080b2a58>, 'age': <__main__.typed object at 0x1080b2ef0>, 'salary': <__main__.typed object at 0x1080b2c18>}
set---> <__main__.people object at 0x1080b22e8> nick
set---> <__main__.people object at 0x1080b22e8> 18
set---> <__main__.people object at 0x1080b22e8> 3333.3

描述符总结

• 描述符是可以实现大部分python类特性中的底层魔法，包括@classmethod，@staticmethd，@property甚至是__slots__属性

• 描述父是很多高级库和框架的重要工具之一，描述符通常是使用到装饰器或者元类的大型框架中的一个组件.

自定制@property

• 利用描述符原理完成一个自定制@property，实现延迟计算（本质就是把一个函数属性利用装饰器原理做成一个描述符：类的属性字典中函数名为key，value为描述符类产生的对象）

property回顾

class room:
    def __init__(self, name, width, length):
        self.name = name
        self.width = width
        self.length = length

    @property
    def area(self):
        return self.width * self.length


r1 = room('alex', 1, 1)

print(r1.area)

1

自定制property

class lazyproperty:
    def __init__(self, func):
        self.func = func

    def __get__(self, instance, owner):
        print('这是我们自己定制的静态属性，r1.area实际是要执行r1.area()')
        if instance is none:
            return self
        return self.func(instance)  # 此时你应该明白，到底是谁在为你做自动传递self的事情


class room:
    def __init__(self, name, width, length):
        self.name = name
        self.width = width
        self.length = length

    @lazyproperty  # area=lazyproperty(area) 相当于定义了一个类属性,即描述符
    def area(self):
        return self.width * self.length


r1 = room('alex', 1, 1)

print(r1.area)

这是我们自己定制的静态属性，r1.area实际是要执行r1.area()
1

实现延迟计算功能

class lazyproperty:
    def __init__(self, func):
        self.func = func

    def __get__(self, instance, owner):
        print('这是我们自己定制的静态属性，r1.area实际是要执行r1.area()')
        if instance is none:
            return self
        else:
            print('--->')
            value = self.func(instance)
            setattr(instance, self.func.__name__, value)  # 计算一次就缓存到实例的属性字典中
            return value


class room:
    def __init__(self, name, width, length):
        self.name = name
        self.width = width
        self.length = length

    @lazyproperty  # area=lazyproperty(area) 相当于'定义了一个类属性,即描述符'
    def area(self):
        return self.width * self.length


r1 = room('alex', 1, 1)

print(r1.area)  # 先从自己的属性字典找,没有再去类的中找,然后出发了area的__get__方法

这是我们自己定制的静态属性，r1.area实际是要执行r1.area()
--->
1

print(r1.area)  # 先从自己的属性字典找,找到了,是上次计算的结果,这样就不用每执行一次都去计算

1

打破延迟计算

• 一个小的改动，延迟计算的美梦就破碎了

class lazyproperty:
    def __init__(self, func):
        self.func = func

    def __get__(self, instance, owner):
        print('这是我们自己定制的静态属性，r1.area实际是要执行r1.area()')
        if instance is none:
            return self
        else:
            value = self.func(instance)
            instance.__dict__[self.func.__name__] = value
            return value
        # return self.func(instance) # 此时你应该明白,到底是谁在为你做自动传递self的事情
    def __set__(self, instance, value):
        print('hahahahahah')


class room:
    def __init__(self, name, width, length):
        self.name = name
        self.width = width
        self.length = length

    @lazyproperty  # area=lazyproperty(area) 相当于定义了一个类属性,即描述符
    def area(self):
        return self.width * self.length

print(room.__dict__)

{'__module__': '__main__', '__init__': <function room.__init__ at 0x107d53620>, 'area': <__main__.lazyproperty object at 0x107ba3860>, '__dict__': <attribute '__dict__' of 'room' objects>, '__weakref__': <attribute '__weakref__' of 'room' objects>, '__doc__': none}

r1 = room('alex', 1, 1)
print(r1.area)
print(r1.area)
print(r1.area)

这是我们自己定制的静态属性，r1.area实际是要执行r1.area()
1
这是我们自己定制的静态属性，r1.area实际是要执行r1.area()
1
这是我们自己定制的静态属性，r1.area实际是要执行r1.area()
1

print(
    r1.area
)  #缓存功能失效,每次都去找描述符了,为何,因为描述符实现了set方法,它由非数据描述符变成了数据描述符,数据描述符比实例属性有更高的优先级,因而所有的属性操作都去找描述符了

这是我们自己定制的静态属性，r1.area实际是要执行r1.area()
1

自定制@classmethod

class classmethod:
    def __init__(self, func):
        self.func = func

    def __get__(
            self, instance,
            owner):  #类来调用,instance为none,owner为类本身,实例来调用,instance为实例,owner为类本身,
        def feedback():
            print('在这里可以加功能啊...')
            return self.func(owner)

        return feedback


class people:
    name = 'nick'

    @classmethod  # say_hi=classmethod(say_hi)
    def say_hi(cls):
        print('你好啊,帅哥 %s' % cls.name)


people.say_hi()

p1 = people()

在这里可以加功能啊...
你好啊,帅哥 nick

p1.say_hi()

在这里可以加功能啊...
你好啊,帅哥 nick

• 疑问,类方法如果有参数呢,好说,好说

class classmethod:
    def __init__(self, func):
        self.func = func

    def __get__(self, instance, owner
                ):  # 类来调用,instance为none,owner为类本身,实例来调用,instance为实例,owner为类本身,
        def feedback(*args, **kwargs):
            print('在这里可以加功能啊...')
            return self.func(owner, *args, **kwargs)

        return feedback


class people:
    name = 'nick'

    @classmethod  # say_hi=classmethod(say_hi)
    def say_hi(cls, msg):
        print('你好啊,帅哥 %s %s' % (cls.name, msg))


people.say_hi('你是那偷心的贼')

p1 = people()

在这里可以加功能啊...
你好啊,帅哥 nick 你是那偷心的贼

p1.say_hi('你是那偷心的贼')

在这里可以加功能啊...
你好啊,帅哥 nick 你是那偷心的贼

自定制@staticmethod

class staticmethod:
    def __init__(self, func):
        self.func = func

    def __get__(
            self, instance,
            owner):  # 类来调用，instance为none，owner为类本身，实例来调用，instance为实例，owner为类本身
        def feedback(*args, **kwargs):
            print('在这里可以加功能啊...')
            return self.func(*args, **kwargs)

        return feedback


class people:
    @staticmethod  # say_hi = staticmethod(say_hi)
    def say_hi(x, y, z):
        print('------>', x, y, z)


people.say_hi(1, 2, 3)

p1 = people()

在这里可以加功能啊...
------> 1 2 3

p1.say_hi(4, 5, 6)

在这里可以加功能啊...
------> 4 5 6