questions (& answers) about object, type, builtin types, class, metaclass and __getattribute__

[Stephen Hansen]

On 8/22/11 3:02 AM, Amirouche B. wrote:
> A) type vs object
> -----------------
> 
> 1) object is the base object, it has no bases : len(object.__bases__)
> == 0
> 2) every object in python inherit object :
> any_object_except_object.__bases__[-1] is object

Not exactly. Python has two somewhat different object models, "old style
classes" and "new style classes", with slightly different behavior and
internal structure.

   class Foo: pass

is an "old-style class", dated back to Python's ancient past. This all
relates to the fact that 'type' and 'class' used to be two pretty
different things, where one was something you mostly did only in C, and
one was something you did (mostly) only in Python. They are largely the
same now.

> 3) object's type is type : object.__class__ is type
> 4) type parent object is object : type.__bases__ == (object,)

Saying "type" and "parent" and the like for new-style classes is
something of a misnomer. For "type" and "object", these things aren't
constructed like this.

What you have here is technically true if you go poke at it in the
interpreter, but it doesn't really /mean/ anything because its not how
these objects came to be and is circular and a bit confusing. These
fundamental objects are created special.


> B) type vs metaclass
> --------------------
> 
> 1) type is the first metaclass ?

Type is the basic, default "metaclass", yes. A metaclass is a callable
that constructs class objects.

> 2) type is its own metaclass : type(type) is type ?

Only in a purely theoretical way. It doesn't actually mean anything;
moreover, type(something) is NOT how you determine somethings metaclass.
Its how you determine somethings type.

The two concepts may be very distinct. Lots of things don't have
metaclasses.

> 3) object's metaclass is type ?

Again, only theoretically.

> 4) other metaclasses *MUST* inherit type ?

Absolutely not. Any callable can be a metaclasss. Despite its name, it
doesn't have to be itself a class or anything. Just something you can
call with er, 3 (I forget exactly) arguments, and which returns a
constructed class object.

> 5) type(any_object) == last_metaclass_..., which is, most of the time,
> type ?

Not necessarily at all. In fact, there is no way I'm aware of to
determine if a metaclass was involved in a classes construction unless
said metaclass wants to provide such a mechanism.

Metaclasses are kind of a  hack. They are a way to hook into the class
construction that's normally done and do something, anything you want,
(even hijack the whole procedure and NOT construct a class at all, but
play a song if you want) before its all finished.

For example, this is a metaclass I've used:

    PageTypes = {}

    class _PageRegistration(type):
        def __new__(cls, name, bases, dct):
            klass = type.__new__(cls, name, bases, dct)
            typename = name[:-9].lower()
            if not typename:
                typename = None

            PageTypes[typename] = klass
            klass.Type = typename

            return klass

    class QueuePage(sc.SizedPanel):
        __metaclass__ = _PageRegistration

Note, the fact that my _PageRegistration metaclass inherits is itself a
class which inherits from type is just one convenient way to write
metaclasses. It could as simply have been just a function.

Metaclasses are somewhat poorly named in that they are really, "creation
hooks".

> C) type vs class
> ----------------
> 
> 1) Type is the metaclass of most classes

Yes and no. Yes, in that most classes are created using the default
mechanism inside CPython. The class body is executed in a scope, the
resulting dictionary is bound to a new class object, bases and the like
are set, and such.

No in that it really just, IIUC, skips the whole "metaclass" part of the
process because this 'default mechanism' doesn't need to call out into
other code to do its job. At least, I think-- May be wrong here,
metaclasses are something of a dark voodoo and I'm not 100% entirely
familiar with the internal workings of CPython.

But functionally, a metaclass is the chunk of code responsible for the
actual physical construction of the class object.

> 2) The class statement::
> 
>     class MyClass(object):
>         attribute = 1
> 
>         def method(self):
>             pass
> 
>    translates to::
> 
>     MyClass = type('MyClass', (object,), {'attribute': 1, 'method':
> def method: pass })

Translates to, I don't know about that. Is functionally equivalent, yes.
It is more or less what happens.

> 3) Instantiation of any class ``MyClass(*args, **kwargs)`` translates
> to::
> 
>     type(MyClass).__call__(MyClass, *args, **kwargs)
> 
>    This is due to __getattribute__ algorithm (see E)
> 4) It's in type.__call__ that happens calls to __new__ and __init__

Again, "translates to" is suggesting "this is what happens when you do
X", which I don't know if is strictly true. CPython inside may be
optimizing this whole process. Especially when it comes to "magic
methods", __x__ and the like -- CPython rarely uses __get*_ for those.
It just calls the methods directly on the class object.

What you're doing here is functionally equivalent to what CPython does,
but it may take a more direct route to get there. CPython has the
advantage of not being Python and having direct access to internals.

> 5) 3) => classes are instance of type
> 
> 6) Since type.__call__ is used to instantiate instance of instance of
> type
>    (rephrased: __call__ is used to instantiate classes) where is the
> code which
>    is executed when we write ``type(myobject)`` or ``type('MyClass',
> bases, attributes)``
>    __getattribute__ resolution algorithm (see E) tells me that it
> should be type.__call__
>    but type.__call__ is already used to class instatiation.

Python callables can have more then one argument, and more then one
behavior, and can choose to do more then one thing based on the number
of arguments.

They don't have overloading, but they can do it themselves.

You've already proven that, and you already know that -- you're sorta
over-complicating this :)

You said:

    MyClass = type('MyClass', (object,), {'attribute': 1, 'method': def
method: pass })

Type.__call__ does both.

> C') class vs class instances aka. objects
> -----------------------------------------
> 
> 1) A class type is a metaclass : issubclass(type(MyClass), type),
>    MyClass.__class__ == type(MyClass)

An old-style classe's type is classobj. A new-style class's type is
type. It may or may not be a "metaclass". type(foo) is not defined as
'the metaclass of foo', but 'the type of foo'. It often is the same
thing, since most of the time type(myclass) is "type" itself and "type"
is the default "metaclass". But mixing up the two concepts isn't really
very helpful.

> 2) An object type is a class : most of the time
> isinstance(type(my_object), type)
>    generally issubclass(type(type(my_object)), type)

Generally.

> D) builtin types
> ----------------
> 
> 1) builtin types are their own metaclass ?

Builtin types are constructed by the interpreter, and may or may not
involve themselves with the class/type hierarchy. Even when they do,
they may only do so partially.

> 2) why function builtin type can not be subclassed ?

Because functions are not classes. They're discrete things of their own.
That a function object has a __class__ attribute is an example of a
builtin partially involving itself in the class/type hierarchy, largely
just for introspection purposes-- since functions are first-class
citizens, you need to be able to pass it around and test to determine
what one thing or another actually is.

Now, functions ARE indeed PyObjects, the internal CPython representation
of an object, of which all things are. But that's not really the same
thing as ultimately inheriting from and involving itself in "object" and
types/classes.

> 3) how does builtin function type relate to callable objects ?

It doesn't, really.

> 4) int(1) is the same as int.__call__(1), since type(int) is type,
> shouldn't int(1)
>    translates to type.__call__(int, 1) ?

You're overly focused on __call__, for one thing. For another, no, I'm
not sure why you think one should "translate" to another (again: just
because you've got the basic relationship of the meta-parts of Python
down pat, doesn't mean Python internals actually goes through all those
actual steps when doing things).

int(1) translates into:

    int.__call__(1)
    int_inst = int.__new__(1)

More or less. Now, "int" is itself a "class" (type), so it was, itself,
constructed by a call to type (well, "type"'s internal C version of
itself, Py_TYPE).

type, the metaclass or class-constructor version, is only called to
create /classes/, at class-creation-time. After "int" itself exists, its
no longer involved.

int has its own __new__ that's used to construct actual instances of
itself. type is now out of the picture.

> 
> 
> E) __getattribute__
> -------------------
> 
> 1) ``my_object.attribute`` always translates to
> ``my_object.__getattribute__('attribute')``

No. __getattribute__ is a mechanism to hook into the attribute fetching
mechanism. (As is __getattr__). It is NOT always invoked.

Especially in the case of __*__ attributes, which by and large bypass
such hooks, as the CPython internals is calling those functions directly
on the class instances themselves.

> 2) Is the following algorithm describing __getattribute__ correct 

This is broadly incorrect because it implies that __getattribute__ is an
internal protocol that Python uses for attribute-resolution, which is
simply untrue. Its a method you may define on new style classes which,
if present, is called when an attribute is requested from an object (but
NOT in the case of __*__ methods, usually, which are obtained internally
by a direct struct access, i.e., mytype->tp_new gets mytype.__new__).

If no such attribute exists, it goes along to do its default
attribute-resolution process, including the descriptor protocol and dict
checking and the like.

__getattribute__ is an optional hook that you can define which allows a
Python class to /bypass/ the normal mechanism for normal (non-magic)
attributes.

If you're asking what the normal mechanism is, its broadly:

 - Check to see if the object's base-classes have a descriptor of the
attributes name. If so, call that.
 - Check to see if the object's instance dict has an attribute of the
name. If so, return that.
 - Check to see if the object's base-classes have an attribute of the name.

More or less. I think. I'm probably leaving something out there.

-- 

   Stephen Hansen
   ... Also: Ixokai
   ... Mail: me+list/python (AT) ixokai (DOT) io
   ... Blog: http://meh.ixokai.io/

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