Python之描述器

1.描述器的表现

用到三个魔术方法，__get__(), __set__(), __delete__()
方法签名如下
object.__get__(self,instance,owner)
object.__set__(self,instance,value)
object.__delete(self,instance)
self指代当前实例，调用者
instance是owner的实例
owner是属性的所输的类

#描述器A调用并赋值给了类B的属性，当调用类B或者实例b时，去类A执行__get__()函数，类调用instance返回none，实例调用返回实例
#执行顺序和类，实例字典无关
class A:
    def __init__(self):
        print(2,'A init')
    def __set__(self, instance, value):
        print(3,self,instance,value)
    def __get__(self, instance, owner): #return值，将会影响b.x or B.x的调用属性
        print(4,self,instance,owner)

class B:
    x = A()
    def __init__(self):
        print(1,'B init')

b = B()  #output 2->1
b.x   #output 4 <__main__.A object at 0x047B09D0> <__main__.B object at 0x047BB350> <class '__main__.B'>
B.x   #output 4 <__main__.A object at 0x047B09D0> None <class '__main__.B'>
此时访问b.x.a1  B.x.a1都会报错 AttributeError:Nonetype
问题出在__get__的返回值，修改为 return self 返回A的实例就具备了a1属性 返回正常

class B:
    x = A()
    def __init__(self):
        self.b1 = A()
        print(1,'B init')

b = B()  #output 2->1
print(b.b1) #output <__main__.A object at 0x03000990> 没有触发__get__的打印
从运行结果可以看出，只有类属性是类的实例才行

2.描述其的定义

python中，一个类实现了__get__,__set__.__delete__的三个方法中的任意一个就是描述器
1.如果仅仅实现了__get__.就是非数据描述器 non-data descriptor
2.同时实现了__get__,__set__,就是数据描述器，data descriptor
如果一个类的类属性，设置为描述器，那么这个类被称为owner属主，method也是类的属性

class A:
    def __init__(self):
        self.a1 = 'a1'
        print(2,'A init')

    def __get__(self, instance, owner):
        print(4,self,instance,owner)
        return self

class B:
    x = A()
    def __init__(self):
        self.x = 'b1'   #如果描述器定义了__set__,此时b1就是value
        print(1,'B init')

b = B()  #output 2->1
print(B.x) #output 4  <__main__.A object at 0x04EEB350> None <class '__main__.B'> ;;;; return <__main__.A object at 0x02E8B350>
print(B.x.a1) #output 4  <__main__.A object at 0x02E8B350> None <class '__main__.B'> ;;;;return a1
print(b.x)  #return b1 访问到了实例的属性，而不是描述器
print(b.x.a1) #AttributeError 'str object has no Attribute
在非数据描述器中，owner实例的属性 会被实例调用，而不是访问__get__描述器

#添加了set方法 对比上个代码，；数据描述器
class A:
    def __init__(self):
        self.a1 = 'a1'
        print(2,'A init')
    def __set__(self, instance, value):  #当定义了set魔术方法后，B实例定义的实例属性self.x = 'b1 不会在写进实例字典，而是调用set方法
        print(3,self,instance,value)
        # instance.__dict__['x']=value
    def __get__(self, instance, owner): #return值，将会影响b.x or B.x的调用属性
        print(4,self,instance,owner)
        # return instance.__dict__['x']
        return self
class B:
    x = A()
    def __init__(self):
        print(1,'B init')
        print("+++++++++++++++++++++++")
        self.x = 'b1'
        print("+++++++++++++++++++++++")

b = B()  #output 2->1->+ ->3-> + ；；实例化时候，self.x = 'b1'调用了set方法
print(b.x.a1)  #return a1 直接调用get
b.x = 100       #return a1 直接调用set
print(b.__dict__)  #实例字典为空
print(B.__dict__)

总结：实例的__dict__优先于非数据描述器；；；数据描述器优先于实例__dict__

2.1描述器查找顺序和__dict__的关系

class A:
    def __init__(self):
        self.a1 = 'a1'
        print(2,'A init')
    def __set__(self, instance, value):
        print(3,self,instance,value)
        self.data = value
        print(self.data)
    def __get__(self, instance, owner):
        print(4,self,instance,owner)
        return self
class B:
    x = A()
    def __init__(self):
        print(1,'B init')
        self.x = 'b.x'
        self.y = 'b.y'
        self.z = 'b.z'


b = B()  #output 2->1->+ ->3-> + ；；实例化时候，self.x = 'b1'调用了set方法
print(b.y) #return b.y
print(b.x)
print(B.__dict__)
print(b.__dict__)#output {'y': 'b.y', 'z': 'b.z'}  ;;;self.x 这里的x是x = A()所以调用set方法，而self.y self.z追加到字典

2.3练习

from functools import  partial
class StaticMethod:
    def __init__(self,fn):
        self.fn = fn
    def __get__(self, instance, owner):
        return self.fn
class ClassMethod:
    def __init__(self,fn):
        self.fn = fn
    def __get__(self, instance, owner):
        # return self.fn(instance)
        return partial(self.fn,instance)
class Test:
    @StaticMethod  #st = staticmethod(st) 去调用__get__方法时，不用在考虑这个Test类了 装饰器到描述器执行，调用时加（）就返回值
    def st(): #st = return self.fn   
        print('st')
    @ClassMethod
    def ct(cls):    #ct = return self.fn(instance)
        print('ct')
t = Test()
Test.st()
t.st()
t.ct()
Test.ct()

class Typed:
    def __init__(self,name,type):
        self.name = name
        self.type = type

    def __set__(self, instance, value):
        if not  isinstance(value,self.type):
            raise TypeError(value)
        instance.__dict__[self.name]=value

    def __get__(self, instance, owner):
        if instance is  not None:
            return instance.__dict__[self.name]
        return self
class Person:
    name = Typed('name',str)   # 1  演变其他的基础
    age = Typed('age',int)
    def __init__(self,name:str,age:int):
        self.name = name       # 2
        self.age = age

p = Person('tom',21)
print(p.__dict__)       #output {'name': 'tom', 'age': 21}
print(p.age)            #output 21
print(Person.age.name)  #output age
print(Person.name.name) #output name
print(Typed.__dict__)
print(Person.__dict__)
# 1-->类属性调用了类实例，2-->有set，此处调用set方法，因为数据描述器，所以字典为空，自己追加字典值，
#get也需要从字典中获取值

import inspect
class Typed:
    def __init__(self,name,type):
        self.name = name
        self.type = type

    def __set__(self, instance, value):
        if not  isinstance(value,self.type):
            raise TypeError(value)
        instance.__dict__[self.name]=value

    def __get__(self, instance, owner):
        if instance is  not None:
            return instance.__dict__[self.name]
        return self

def typeassert(cls):
    parmas = inspect.signature(cls).parameters
    for k,v in parmas.items():
        if v.annotation != v.empty:
            setattr(cls,k,Typed(v,v.annotation))
    return cls
@typeassert
class Person:
    def __init__(self,name:str,age:int):
        self.name = name       # 2
        self.age = age

p = Person('tom',21)