Introduction
Descriptors (descriptors) are a profound but important black magic in the Python language. They are widely used in the kernel of the Python language. Proficiency in descriptors will benefit Python programmers. Toolbox adds an extra trick. In this article, I will describe the definition of descriptors and some common scenarios, and at the end of the article I will add __getattr__, __getattribute__, and __getitem__, three magic methods that also involve attribute access.
Definition of descriptor
descr__get__(self,?obj,?objtype=None)?-->?value descr.__set__(self,?obj,?value)?-->?None descr.__delete__(self,?obj)?-->?None
As long as an object attribute (object attribute) defines any one of the above three methods, then this class can be called a descriptor class.
Descriptor Basics
In the following example we create a RevealAcess class and implement the __get__ method. Now this class can be called a descriptor class.
class?RevealAccess(object):
????def?__get__(self,?obj,?objtype):
????????print('self?in?RevealAccess:?{}'.format(self))
????????print('self:?{}\nobj:?{}\nobjtype:?{}'.format(self,?obj,?objtype))
class?MyClass(object):
????x?=?RevealAccess()
????def?test(self):
????????print('self?in?MyClass:?{}'.format(self))
EX1 instance attribute
Next let’s take a look at the meaning of each parameter of the __get__ method. In the following example, self is the instance x of the RevealAccess class, and obj is the MyClass class. Instance m, objtype, as the name suggests, is the MyClass class itself. As can be seen from the output statement, m.x access descriptor x will call the __get__ method.
>>>?m?=?MyClass() >>>?m.test() self?in?MyClass:?<__main__.MyClass object at 0x7f19d4e42160> >>>?m.x self?in?RevealAccess:?<__main__.RevealAccess object at 0x7f19d4e420f0> self:?<__main__.RevealAccess object at 0x7f19d4e420f0> obj:?<__main__.MyClass object at 0x7f19d4e42160> objtype:?<class '__main__.MyClass'>
EX2 class attribute
If you access attribute x directly through the class, then the obj connection is directly None, which is easier to understand because there is no instance of MyClass.
>>>?MyClass.x self?in?RevealAccess:?<__main__.RevealAccess object at 0x7f53651070f0> self:?<__main__.RevealAccess object at 0x7f53651070f0> obj:?None objtype:?<class '__main__.MyClass'>
The principle of descriptor
Descriptor trigger
In the above example, we enumerated the usage of descriptors from the perspective of instance attributes and class attributes. Below we Let’s carefully analyze the internal principle:
If you access instance attributes, it is equivalent to calling object.__getattribute__(), which translates obj.d into type(obj ).__dict__['d'].__get__(obj, type(obj)).
If you are accessing a class attribute, it is equivalent to calling type.__getattribute__(), which translates cls.d into cls.__dict__['d'].__get__( None, cls), converted into Python code is:
def?__getattribute__(self,?key): ????"Emulate?type_getattro()?in?Objects/typeobject.c" ????v?=?object.__getattribute__(self,?key) ????if?hasattr(v,?'__get__'): ????????return?v.__get__(None,?self) ????return?v
Let’s briefly talk about the __getattribute__ magic method. This method will be called unconditionally when we access the attributes of an object. Details I will make an additional supplement at the end of the article about the details such as the difference between __getattr and __getitem__, but we will not delve into it for now.
Descriptor priority
First of all, descriptors are divided into two types:
If an object defines both __get__() and __set__ () method, this descriptor is called a data descriptor.
If an object only defines the __get__() method, this descriptor is called a non-data descriptor.
There are four situations when we access properties:
data descriptor
instance dict
non-data descriptor
__getattr__()
Their priority The size is:
data?descriptor?>?instance?dict?>?non-data?descriptor?>?__getattr__()
What does this mean? That is to say, if data descriptor->d and instance attribute->d with the same name appear in the instance object obj, when obj.d accesses attribute d, Python will call it because the data descriptor has a higher priority. type(obj).__dict__['d'].__get__(obj, type(obj)) instead of calling obj.__dict__['d']. But if the descriptor is a non-data descriptor, Python will call obj.__dict__['d'].
Property
Defining a descriptor class every time a descriptor is used seems very cumbersome. Python provides a concise way to add data descriptors to properties.
property(fget=None,?fset=None,?fdel=None,?doc=None)?->?property?attribute
fget, fset and fdel are the getter, setter and deleter methods of the class respectively. We use the following example to illustrate how to use Property:
class?Account(object): ????def?__init__(self): ????????self._acct_num?=?None ????def?get_acct_num(self): ????????return?self._acct_num ????def?set_acct_num(self,?value): ????????self._acct_num?=?value ????def?del_acct_num(self): ????????del?self._acct_num ????acct_num?=?property(get_acct_num,?set_acct_num,?del_acct_num,?'_acct_num?property.')
If acct is an instance of Account, acct.acct_num will call the getter, acct.acct_num = value will call the setter, and del acct_num.acct_num will call deleter.
>>>?acct?=?Account() >>>?acct.acct_num?=?1000 >>>?acct.acct_num 1000
Python also provides the @property decorator, which can be used to create properties for simple application scenarios. A property object has getter, setter and delete decorator methods, which can be used to create a copy of the property through the accessor function of the corresponding decorated function.
class?Account(object): ????def?__init__(self): ????????self._acct_num?=?None ????@property ?????#?the?_acct_num?property.?the?decorator?creates?a?read-only?property ????def?acct_num(self): ????????return?self._acct_num ????@acct_num.setter ????#?the?_acct_num?property?setter?makes?the?property?writeable ????def?set_acct_num(self,?value): ????????self._acct_num?=?value ????@acct_num.deleter ????def?del_acct_num(self): ????????del?self._acct_num
If you want the property to be read-only, just remove the setter method.
Create descriptors at runtime
We can add property attributes at runtime:
class?Person(object):
????def?addProperty(self,?attribute):
????????#?create?local?setter?and?getter?with?a?particular?attribute?name
????????getter?=?lambda?self:?self._getProperty(attribute)
????????setter?=?lambda?self,?value:?self._setProperty(attribute,?value)
????????#?construct?property?attribute?and?add?it?to?the?class
????????setattr(self.__class__,?attribute,?property(fget=getter,?\
????????????????????????????????????????????????????fset=setter,?\
????????????????????????????????????????????????????doc="Auto-generated?method"))
????def?_setProperty(self,?attribute,?value):
????????print("Setting:?{}?=?{}".format(attribute,?value))
????????setattr(self,?'_'?+?attribute,?value.title())
????def?_getProperty(self,?attribute):
????????print("Getting:?{}".format(attribute))
????????return?getattr(self,?'_'?+?attribute)
>>>?user?=?Person()
>>>?user.addProperty('name')
>>>?user.addProperty('phone')
>>>?user.name?=?'john?smith'
Setting:?name?=?john?smith
>>>?user.phone?=?'12345'
Setting:?phone?=?12345
>>>?user.name
Getting:?name
'John?Smith'
>>>?user.__dict__
{'_phone':?'12345',?'_name':?'John?Smith'}
Static methods and class methods
We can use descriptors To simulate the implementation of @staticmethod and @classmethod in Python. Let’s first browse the following table:
| Called from an Object | Called from a Class | |
|---|---|---|
| f(obj, *args) | f(*args) | |
| f(*args) | f(*args) | |
| f(type(obj), *args) | f(klass, *args) |
| Transformation | Called from an Object | Called from a Class |
|---|---|---|
| function | f(obj, *args) | f(*args) |
| staticmethod | f(*args) | f(*args) |
| classmethod | f(type(obj), *args) | f(klass, *args) |
靜態(tài)方法
對(duì)于靜態(tài)方法f。c.f和C.f是等價(jià)的，都是直接查詢object.__getattribute__(c, ‘f’)或者object.__getattribute__(C, ’f‘)。靜態(tài)方法一個(gè)明顯的特征就是沒(méi)有self變量。
靜態(tài)方法有什么用呢？假設(shè)有一個(gè)處理專(zhuān)門(mén)數(shù)據(jù)的容器類(lèi)，它提供了一些方法來(lái)求平均數(shù)，中位數(shù)等統(tǒng)計(jì)數(shù)據(jù)方式，這些方法都是要依賴(lài)于相應(yīng)的數(shù)據(jù)的。但是類(lèi)中可能還有一些方法，并不依賴(lài)這些數(shù)據(jù)，這個(gè)時(shí)候我們可以將這些方法聲明為靜態(tài)方法，同時(shí)這也可以提高代碼的可讀性。
使用非數(shù)據(jù)描述符來(lái)模擬一下靜態(tài)方法的實(shí)現(xiàn)：
class?StaticMethod(object): ????def?__init__(self,?f): ????????self.f?=?f ????def?__get__(self,?obj,?objtype=None): ????????return?self.f
我們來(lái)應(yīng)用一下：
class?MyClass(object): ????@StaticMethod ????def?get_x(x): ????????return?x print(MyClass.get_x(100))??#?output:?100
類(lèi)方法
Python的@classmethod和@staticmethod的用法有些類(lèi)似，但是還是有些不同，當(dāng)某些方法只需要得到類(lèi)的引用而不關(guān)心類(lèi)中的相應(yīng)的數(shù)據(jù)的時(shí)候就需要使用classmethod了。
使用非數(shù)據(jù)描述符來(lái)模擬一下類(lèi)方法的實(shí)現(xiàn)：
class?ClassMethod(object): ????def?__init__(self,?f): ????????self.f?=?f ????def?__get__(self,?obj,?klass=None): ????????if?klass?is?None: ????????????klass?=?type(obj) ????????def?newfunc(*args): ????????????return?self.f(klass,?*args) ????????return?newfunc
其他的魔術(shù)方法
首次接觸Python魔術(shù)方法的時(shí)候，我也被__get__, __getattribute__, __getattr__, __getitem__之間的區(qū)別困擾到了，它們都是和屬性訪問(wèn)相關(guān)的魔術(shù)方法，其中重寫(xiě)__getattr__，__getitem__來(lái)構(gòu)造一個(gè)自己的集合類(lèi)非常的常用，下面我們就通過(guò)一些例子來(lái)看一下它們的應(yīng)用。
__getattr__
Python默認(rèn)訪問(wèn)類(lèi)/實(shí)例的某個(gè)屬性都是通過(guò)__getattribute__來(lái)調(diào)用的，__getattribute__會(huì)被無(wú)條件調(diào)用，沒(méi)有找到的話就會(huì)調(diào)用__getattr__。如果我們要定制某個(gè)類(lèi)，通常情況下我們不應(yīng)該重寫(xiě)__getattribute__，而是應(yīng)該重寫(xiě)__getattr__，很少看見(jiàn)重寫(xiě)__getattribute__的情況。
從下面的輸出可以看出，當(dāng)一個(gè)屬性通過(guò)__getattribute__無(wú)法找到的時(shí)候會(huì)調(diào)用__getattr__。
In?[1]:?class?Test(object):
????...:?????def?__getattribute__(self,?item):
????...:?????????print('call?__getattribute__')
????...:?????????return?super(Test,?self).__getattribute__(item)
????...:?????def?__getattr__(self,?item):
????...:?????????return?'call?__getattr__'
????...:
In?[2]:?Test().a
call?__getattribute__
Out[2]:?'call?__getattr__'
應(yīng)用
對(duì)于默認(rèn)的字典，Python只支持以obj['foo']形式來(lái)訪問(wèn)，不支持obj.foo的形式，我們可以通過(guò)重寫(xiě)__getattr__讓字典也支持obj['foo']的訪問(wèn)形式，這是一個(gè)非常經(jīng)典常用的用法：
class?Storage(dict): ????""" ????A?Storage?object?is?like?a?dictionary?except?`obj.foo`?can?be?used ????in?addition?to?`obj['foo']`. ????""" ????def?__getattr__(self,?key): ????????try: ????????????return?self[key] ????????except?KeyError?as?k: ????????????raise?AttributeError(k) ????def?__setattr__(self,?key,?value): ????????self[key]?=?value ????def?__delattr__(self,?key): ????????try: ????????????del?self[key] ????????except?KeyError?as?k: ????????????raise?AttributeError(k) ????def?__repr__(self): ????????return?'<Storage ' + dict.__repr__(self) + '>'
我們來(lái)使用一下我們自定義的加強(qiáng)版字典：
>>>?s?=?Storage(a=1) >>>?s['a'] 1 >>>?s.a 1 >>>?s.a?=?2 >>>?s['a'] 2 >>>?del?s.a >>>?s.a ... AttributeError:?'a'
__getitem__
getitem用于通過(guò)下標(biāo)[]的形式來(lái)獲取對(duì)象中的元素，下面我們通過(guò)重寫(xiě)__getitem__來(lái)實(shí)現(xiàn)一個(gè)自己的list。
class?MyList(object): ????def?__init__(self,?*args): ????????self.numbers?=?args ????def?__getitem__(self,?item): ????????return?self.numbers[item] my_list?=?MyList(1,?2,?3,?4,?6,?5,?3) print?my_list[2]
這個(gè)實(shí)現(xiàn)非常的簡(jiǎn)陋，不支持slice和step等功能，請(qǐng)讀者自行改進(jìn)，這里我就不重復(fù)了。
應(yīng)用
下面是參考requests庫(kù)中對(duì)于__getitem__的一個(gè)使用，我們定制了一個(gè)忽略屬性大小寫(xiě)的字典類(lèi)。
程序有些復(fù)雜，我稍微解釋一下：由于這里比較簡(jiǎn)單，沒(méi)有使用描述符的需求，所以使用了@property裝飾器來(lái)代替，lower_keys的功能是將實(shí)例字典中的鍵全部轉(zhuǎn)換成小寫(xiě)并且存儲(chǔ)在字典self._lower_keys中。重寫(xiě)了__getitem__方法，以后我們?cè)L問(wèn)某個(gè)屬性首先會(huì)將鍵轉(zhuǎn)換為小寫(xiě)的方式，然后并不會(huì)直接訪問(wèn)實(shí)例字典，而是會(huì)訪問(wèn)字典self._lower_keys去查找。賦值/刪除操作的時(shí)候由于實(shí)例字典會(huì)進(jìn)行變更，為了保持self._lower_keys和實(shí)例字典同步，首先清除self._lower_keys的內(nèi)容，以后我們重新查找鍵的時(shí)候再調(diào)用__getitem__的時(shí)候會(huì)重新新建一個(gè)self._lower_keys。
class?CaseInsensitiveDict(dict): ????@property ????def?lower_keys(self): ????????if?not?hasattr(self,?'_lower_keys')?or?not?self._lower_keys: ????????????self._lower_keys?=?dict((k.lower(),?k)?for?k?in?self.keys()) ????????return?self._lower_keys ????def?_clear_lower_keys(self): ????????if?hasattr(self,?'_lower_keys'): ????????????self._lower_keys.clear() ????def?__contains__(self,?key): ????????return?key.lower()?in?self.lower_keys ????def?__getitem__(self,?key): ????????if?key?in?self: ????????????return?dict.__getitem__(self,?self.lower_keys[key.lower()]) ????def?__setitem__(self,?key,?value): ????????dict.__setitem__(self,?key,?value) ????????self._clear_lower_keys() ????def?__delitem__(self,?key): ????????dict.__delitem__(self,?key) ????????self._lower_keys.clear() ????def?get(self,?key,?default=None): ????????if?key?in?self: ????????????return?self[key] ????????else: ????????????return?default
我們來(lái)調(diào)用一下這個(gè)類(lèi)：
>>>?d?=?CaseInsensitiveDict()
>>>?d['ziwenxie']?=?'ziwenxie'
>>>?d['ZiWenXie']?=?'ZiWenXie'
>>>?print(d)
{'ZiWenXie':?'ziwenxie',?'ziwenxie':?'ziwenxie'}
>>>?print(d['ziwenxie'])
ziwenxie
#?d['ZiWenXie']?=>?d['ziwenxie']
>>>?print(d['ZiWenXie'])
ziwenxie
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