views:

176

answers:

5

So, I was playing around with Python while answering this question, and I discovered that this is not valid:

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

due to an AttributeError: 'object' object has no attribute 'attr'. However, with any class inherited from object, it is valid:

class Sub(object):
    pass

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

Printing s.attr displays 'hello' as expected. Why is this the case? What in the Python language specification specifies that you can't assign attributes to vanilla objects?

A: 

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.

Peter
+1  A: 

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.

Ryan
But object() is an object, just like Sub() is an object. My understanding is that both s and o are objects. So what is the fundamental difference between s and o? Is it that one is an instantiated type and the other is an instantiated class?
Smashery
Bingo. That's exactly the issue.
Ryan
A: 

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".

Smashery
+14  A: 

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).

Alex Martelli
+2  A: 

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.

Unknown