了解 __getattr__ 和 __getattribute__ 之间的区别

发布于 2024-10-04 23:53:38 字数 700 浏览 1 评论 0原文

我试图理解 __getattr__ 和 __getattribute__ 之间的区别,但是,我失败了。

Stack Overflow 问题的答案__getattr____getattribute__ 之间的差异说:

__getattribute__ 在查看实际属性之前被调用 对象,因此可能很难 正确实施。你最终可能会进入 无限递归非常容易。

我完全不知道这意味着什么。

然后它接着说:

您几乎肯定需要__getattr__

为什么?

我读到,如果 __getattribute__ 失败,则会调用 __getattr__ 。那么为什么有两种不同的方法做同样的事情呢?如果我的代码实现了新样式的类,我应该使用什么?

我正在寻找一些代码示例来解决这个问题。我已尽我所能在谷歌上搜索,但我找到的答案并没有彻底讨论这个问题。

如果有任何文档,我准备阅读。

I am trying to understand the difference between __getattr__ and __getattribute__, however, I am failing at it.

The answer to the Stack Overflow question Difference between __getattr__ vs __getattribute__ says:

__getattribute__ is invoked before looking at the actual attributes on
the object, and so can be tricky to
implement correctly. You can end up in
infinite recursions very easily.

I have absolutely no idea what that means.

Then it goes on to say:

You almost certainly want __getattr__.

Why?

I read that if __getattribute__ fails, __getattr__ is called. So why are there two different methods doing the same thing? If my code implements the new style classes, what should I use?

I am looking for some code examples to clear this question. I have Googled to best of my ability, but the answers that I found don't discuss the problem thoroughly.

If there is any documentation, I am ready to read that.

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雨巷深深 2024-10-11 23:53:38

首先是一些基础知识。

对于对象,您需要处理它们的属性。通常,我们使用instance.attribute。有时我们需要更多的控制(当我们事先不知道属性的名称时)。

例如,instance.attribute 将变为 getattr(instance, attribute_name)。使用此模型,我们可以通过以字符串形式提供attribute_name来获取属性。

使用__getattr__

您还可以告诉类如何处理它未显式管理的属性,并通过__getattr__ 方法来执行此操作。

每当您请求尚未定义的属性时,Python 都会调用此方法,以便您可以定义如何处理它。

经典用例:

class A(dict):
    def __getattr__(self, name):
       return self[name]
a = A()
# Now a.somekey will give a['somekey']

注意事项和 __getattribute__ 的使用

如果您需要捕获每个属性,无论它是否存在,请改用 __getattribute__。不同之处在于,仅针对实际不存在的属性调用 __getattr__ 。如果直接设置属性,则引用该属性将检索它,而无需调用 __getattr__ 。

__getattribute__ 始终被调用。

Some basics first.

With objects, you need to deal with their attributes. Ordinarily, we do instance.attribute. Sometimes we need more control (when we do not know the name of the attribute in advance).

For example, instance.attribute would become getattr(instance, attribute_name). Using this model, we can get the attribute by supplying the attribute_name as a string.

Use of __getattr__

You can also tell a class how to deal with attributes which it doesn't explicitly manage and do that via __getattr__ method.

Python will call this method whenever you request an attribute that hasn't already been defined, so you can define what to do with it.

A classic use case:

class A(dict):
    def __getattr__(self, name):
       return self[name]
a = A()
# Now a.somekey will give a['somekey']

Caveats and use of __getattribute__

If you need to catch every attribute regardless whether it exists or not, use __getattribute__ instead. The difference is that __getattr__ only gets called for attributes that don't actually exist. If you set an attribute directly, referencing that attribute will retrieve it without calling __getattr__.

__getattribute__ is called all the times.

谁与争疯 2024-10-11 23:53:38

每当发生属性访问时都会调用 __getattribute__ 。

class Foo(object):
    def __init__(self, a):
        self.a = 1

    def __getattribute__(self, attr):
        try:
            return self.__dict__[attr]
        except KeyError:
            return 'default'
f = Foo(1)
f.a

这将导致无限递归。这里的罪魁祸首是 return self.__dict__[attr] 行。让我们假设(这与事实足够接近)所有属性都存储在 self.__dict__ 中,并且可以通过它们的名称来访问。该行

f.a

尝试访问 fa 属性。这会调用f.__getattribute__('a')__getattribute__ 然后尝试加载 self.__dict____dict__self == f 的一个属性,因此 python 调用 f.__getattribute__('__dict__') ,它再次尝试访问属性 <代码>'__dict__'。这就是无限递归。

如果使用 __getattr__ ,那么

  1. 它永远不会运行,因为 f 有一个 a 属性。
  2. 如果它已经运行(假设您要求 fb),则不会调用它来查找 __dict__,因为它已经存在并且 __getattr__ > 仅当查找属性的所有其他方法均失败时才会调用。

使用 __getattribute__ 编写上述类的“正确”方法是

class Foo(object):
    # Same __init__

    def __getattribute__(self, attr):
        return super().__getattribute__(attr)

super().__getattribute__(attr) 绑定“最近的”的 __getattribute__ 方法' 超类(正式地,类的方法解析顺序中的下一个类,或 MRO)到当前对象 self,然后调用它并让它完成工作。

所有这些麻烦都可以通过使用 __getattr__ 来避免,它让 Python 做正常的事情,直到找不到属性。此时,Python 将控制权交给您的 __getattr__ 方法并让它提出一些建议。

还值得注意的是,您可能会使用 __getattr__ 遇到无限递归。

class Foo(object):
    def __getattr__(self, attr):
        return self.attr

我会把那个作为练习。

__getattribute__ is called whenever an attribute access occurs.

class Foo(object):
    def __init__(self, a):
        self.a = 1

    def __getattribute__(self, attr):
        try:
            return self.__dict__[attr]
        except KeyError:
            return 'default'
f = Foo(1)
f.a

This will cause infinite recursion. The culprit here is the line return self.__dict__[attr]. Let's pretend (It's close enough to the truth) that all attributes are stored in self.__dict__ and available by their name. The line

f.a

attempts to access the a attribute of f. This calls f.__getattribute__('a'). __getattribute__ then tries to load self.__dict__. __dict__ is an attribute of self == f and so python calls f.__getattribute__('__dict__') which again tries to access the attribute '__dict__'. This is infinite recursion.

If __getattr__ had been used instead then

  1. It never would have run because f has an a attribute.
  2. If it had run, (let's say that you asked for f.b) then it would not have been called to find __dict__ because it's already there and __getattr__ is invoked only if all other methods of finding the attribute have failed.

The 'correct' way to write the above class using __getattribute__ is

class Foo(object):
    # Same __init__

    def __getattribute__(self, attr):
        return super().__getattribute__(attr)

super().__getattribute__(attr) binds the __getattribute__ method of the 'nearest' superclass (formally, the next class in the class's Method Resolution Order, or MRO) to the current object self and then calls it and lets that do the work.

All of this trouble is avoided by using __getattr__ which lets Python do it's normal thing until an attribute isn't found. At that point, Python hands control over to your __getattr__ method and lets it come up with something.

It's also worth noting that you can run into infinite recursion with __getattr__.

class Foo(object):
    def __getattr__(self, attr):
        return self.attr

I'll leave that one as an exercise.

你穿错了嫁妆 2024-10-11 23:53:38

我认为其他答案已经很好地解释了 __getattr____getattribute__ 之间的区别,但可能不清楚的一件事是为什么你想要使用 >__getattribute____getattribute__ 的一个很酷的事情是,它本质上允许您在访问类时重载点。这允许您自定义如何在低级别访问属性。例如,假设我想定义一个类,其中所有仅接受 self 参数的方法都被视为属性:

# prop.py
import inspect

class PropClass(object):
    def __getattribute__(self, attr):
        val = super().__getattribute__(attr)
        if callable(val):
            argcount = len(inspect.getargspec(val).args)
            # Account for self
            if argcount == 1:
                return val()
            else:
                return val
        else:
            return val

并且来自交互式解释器:

>>> import prop
>>> class A(prop.PropClass):
...     def f(self):
...             return 1
... 
>>> a = A()
>>> a.f
1

当然这是一个愚蠢的示例,您可能永远不想这样做,但是它向您展示了通过重写 __getattribute__ 可以获得的强大功能。

I think the other answers have done a great job of explaining the difference between __getattr__ and __getattribute__, but one thing that might not be clear is why you would want to use __getattribute__. The cool thing about __getattribute__ is that it essentially allows you to overload the dot when accessing a class. This allows you to customize how attributes are accessed at a low level. For instance, suppose I want to define a class where all methods that only take a self argument are treated as properties:

# prop.py
import inspect

class PropClass(object):
    def __getattribute__(self, attr):
        val = super().__getattribute__(attr)
        if callable(val):
            argcount = len(inspect.getargspec(val).args)
            # Account for self
            if argcount == 1:
                return val()
            else:
                return val
        else:
            return val

And from the interactive interpreter:

>>> import prop
>>> class A(prop.PropClass):
...     def f(self):
...             return 1
... 
>>> a = A()
>>> a.f
1

Of course this is a silly example and you probably wouldn't ever want to do this, but it shows you the power you can get from overriding __getattribute__.

笔芯 2024-10-11 23:53:38

我已经阅读了其他人的精彩解释。但是,我从这个博客 Python 魔法方法和 找到了一个简单的答案__getattr__。以下所有内容均来自那里。

使用 __getattr__ 魔术方法,我们可以拦截不存在的属性查找并执行某些操作,以免失败:

class Dummy(object):

    def __getattr__(self, attr):
        return attr.upper()

d = Dummy()
d.does_not_exist # 'DOES_NOT_EXIST'
d.what_about_this_one  # 'WHAT_ABOUT_THIS_ONE'

但是如果该属性确实存在,则不会调用 __getattr__ :

class Dummy(object):

    def __getattr__(self, attr):
        return attr.upper()

d = Dummy()
d.value = "Python"
print(d.value)  # "Python"

__getattribute____getattr__ 类似,重要的区别是 __getattribute__ 将拦截 EVERY 属性查找,但不会该属性是否存在无关紧要。

class Dummy(object):

    def __getattribute__(self, attr):
        return 'YOU SEE ME?'

d = Dummy()
d.value = "Python"
print(d.value)  # "YOU SEE ME?"

在该示例中,d 对象已经具有属性值。但是当我们尝试访问它时,我们没有得到原始的期望值(“Python”);我们只是得到返回的任何 __getattribute__ 。这意味着我们实际上已经失去了价值属性;它已经变得“遥不可及”。

I have gone through other's excellent explanation. However, I found a simple answer from this blog Python Magic Methods and __getattr__. All the following are from there.

Using the __getattr__ magic method, we can intercept that inexistent attribute lookup and do something so it doesn’t fail:

class Dummy(object):

    def __getattr__(self, attr):
        return attr.upper()

d = Dummy()
d.does_not_exist # 'DOES_NOT_EXIST'
d.what_about_this_one  # 'WHAT_ABOUT_THIS_ONE'

But if the attribute does exist, __getattr__ won’t be invoked:

class Dummy(object):

    def __getattr__(self, attr):
        return attr.upper()

d = Dummy()
d.value = "Python"
print(d.value)  # "Python"

__getattribute__ is similar to __getattr__, with the important difference that __getattribute__ will intercept EVERY attribute lookup, doesn’t matter if the attribute exists or not.

class Dummy(object):

    def __getattribute__(self, attr):
        return 'YOU SEE ME?'

d = Dummy()
d.value = "Python"
print(d.value)  # "YOU SEE ME?"

In that example, the d object already has an attribute value. But when we try to access it, we don’t get the original expected value (“Python”); we’re just getting whatever __getattribute__ returned. It means that we’ve virtually lost the value attribute; it has become “unreachable”.

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