无法在“ object”类的实例上设置属性

所以，当我在回答 这个问题的时候，我在玩 Python，我发现这是无效的:

o = object()
o.attr = 'hello'

但是，对于从对象继承的任何类，它是有效的:

class Sub(object):
pass


s = Sub()
s.attr = 'hello'

打印 s.attr按预期显示“ hello”。为什么会这样？Python 语言规范中指定了哪些内容不能将属性分配给普通对象？

有关其他变通方法，请参见 如何创建对象并向其添加属性？。

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This is (IMO) one of the fundamental limitations with Python - you can't re-open classes. I believe the actual problem, though, is caused by the fact that classes implemented in C can't be modified at runtime... subclasses can, but not the base classes.

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It's because object is a "type", not a class. In general, all classes that are defined in C extensions (like all the built in datatypes, and stuff like numpy arrays) do not allow addition of arbitrary attributes.

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So, investigating my own question, I discovered this about the Python language: you can inherit from things like int, and you see the same behaviour:

>>> class MyInt(int):
pass


>>> x = MyInt()
>>> print x
0
>>> x.hello = 4
>>> print x.hello
4
>>> x = x + 1
>>> print x
1
>>> print x.hello
Traceback (most recent call last):
File "<interactive input>", line 1, in <module>
AttributeError: 'int' object has no attribute 'hello'

I assume the error at the end is because the add function returns an int, so I'd have to override functions like __add__ and such in order to retain my custom attributes. But this all now makes sense to me (I think), when I think of "object" like "int".

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最佳答案

To support arbitrary attribute assignment, an object needs a __dict__: a dict associated with the object, where arbitrary attributes can be stored. Otherwise, there's nowhere to put new attributes.

An instance of object does not carry around a __dict__ -- if it did, before the horrible circular dependence problem (since dict, like most everything else, inherits from object;-), this would saddle every object in Python with a dict, which would mean an overhead of many bytes per object that currently doesn't have or need a dict (essentially, all objects that don't have arbitrarily assignable attributes don't have or need a dict).

For example, using the excellent pympler project (you can get it via svn from here), we can do some measurements...:

>>> from pympler import asizeof
>>> asizeof.asizeof({})
144
>>> asizeof.asizeof(23)
16

You wouldn't want every int to take up 144 bytes instead of just 16, right?-)

Now, when you make a class (inheriting from whatever), things change...:

>>> class dint(int): pass
...
>>> asizeof.asizeof(dint(23))
184

...the __dict__ is now added (plus, a little more overhead) -- so a dint instance can have arbitrary attributes, but you pay quite a space cost for that flexibility.

So what if you wanted ints with just one extra attribute foobar...? It's a rare need, but Python does offer a special mechanism for the purpose...

>>> class fint(int):
...   __slots__ = 'foobar',
...   def __init__(self, x): self.foobar=x+100
...
>>> asizeof.asizeof(fint(23))
80

...not quite as tiny as an int, mind you! (or even the two ints, one the self and one the self.foobar -- the second one can be reassigned), but surely much better than a dint.

When the class has the __slots__ special attribute (a sequence of strings), then the class statement (more precisely, the default metaclass, type) does not equip every instance of that class with a __dict__ (and therefore the ability to have arbitrary attributes), just a finite, rigid set of "slots" (basically places which can each hold one reference to some object) with the given names.

In exchange for the lost flexibility, you gain a lot of bytes per instance (probably meaningful only if you have zillions of instances gallivanting around, but, there are use cases for that).

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It is simply due to optimization.

Dicts are relatively large.

>>> import sys
>>> sys.getsizeof((lambda:1).__dict__)
140

Most (maybe all) classes that are defined in C do not have a dict for optimization.

If you look at the source code you will see that there are many checks to see if the object has a dict or not.

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As other answerers have said, an object does not have a __dict__. object is the base class of all types, including int or str. Thus whatever is provided by object will be a burden to them as well. Even something as simple as an optional __dict__ would need an extra pointer for each value; this would waste additional 4-8 bytes of memory for each object in the system, for a very limited utility.

Instead of doing an instance of a dummy class, in Python 3.3+, you can (and should) use types.SimpleNamespace for this.

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https://docs.python.org/3/library/functions.html#object :

Note: object does not have a __dict__, so you can’t assign arbitrary attributes to an instance of the object class.


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