Why I now believe that duck typed metaclasses are impossible in CPython

January 31, 2014

As I mentioned in my entry on fake versus real metaclasses, I've wound up a bit obsessed with the question of whether it's possible to create a fully functional metaclass that doesn't inherit from type. Call this a 'duck typed metaclass' or if you want to be cute, a 'duck typed type' (DTT). As a result of that earlier entry and some additional exploration I now believe that it's impossible.

Let's go back to MetaclassFakeVsReal for a moment and look at the fake metaclass M2:

class M2(object):
   def __new__(self, name, bases, dct):
      print "M2", name
      return type(name, bases, dct)

class C2(object):
   __metaclass__ = M2

class C4(C2):

As we discovered, the problem is that C2 is not an instance of M2 and so (among other things) its subclass C4 will not invoke M2 when it is being created. The real metaclass M1 avoided this problem by instead using type.__new()__ in its __new__ method. So why not work around the problem by making M2 do so too, like this:

class M2(object):
   def __new__(self, name, bases, dct):
      print "M2", name
      return type.__new__(self, name, bases, dct)

Here's why:

TypeError: Error when calling the metaclass bases
    type.__new__(M2): M2 is not a subtype of type

I believe that this is an old friend in a new guise. Instances of M2 would normally be based on the C-level structure for object (since it is a subclass of object), which is not compatible with the C-level type structure that instances of type and its subclasses need to use. So type says 'you cannot do this' and walks away.

Given that we need C2 to be an instance of M2 so that things work right for subclasses of C2 and we can't use type, we can try brute force and fakery:

class M2(object):
   def __new__(self, name, bases, dct):
      print "M2", name
      r = super(M2, self).__new__()
      r.__bases__ = bases
      return r

This looks like it works in that C4 will now get created by M2. However this is an illusion and I'll give you two examples of the ensuing problems, each equally fatal.

Our first problem is creating instances of C2, ie the actual objects that we will want to use in code. Instance creation is fundamentally done by calling C2(), which means that M2 needs a __call__ special method (so that C2, an instance of M2, becomes callable). We'll try a version that delegates all of the work to type:

  def __call__(self, *args, **kwargs):
     print "M2 call", self, args, kwargs
     return type.__call__(self, *args, **kwargs)

Unsurprisingly but unfortunately this doesn't work:

TypeError: descriptor '__call__' requires a 'type' object but received a 'M2'

Okay, fine, we'll try more or less the same trick as before (which is now very dodgy, but ignore that for now):

  def __call__(self, *args, **kwargs):
     print "M2 call", self, args, kwargs
     r = super(M2, self).__new__(self)
     r.__init__(*args, **kwargs)
     return r

You can probably guess what's coming:

TypeError: object.__new__(X): X is not a type object (M2)

We are now well and truly up the creek because classes are the only thing in CPython that can have instances. Classes are instances of type and as we've seen we can't create something that is both an instance of M2 (so that M2 is a real metaclass instead of a fake one) and an instance of type. Classes without instances are obviously not actually functional.

The other problem is that despite how it appears C4 is not actually a subclass of C2 because of course classes are the only thing in CPython that can have subclasses. In specific, attribute lookups on even C4 itself will not look at attributes on C2:

>>> C2.dog = 10
>>> C4.dog
AttributeError: 'M2' object has no attribute 'dog'

The __bases__ attribute that M2.__new__ glued on C4 (and C2) is purely decorative. Again, looking attributes up through the chain of bases (and the entire method resolution order) is something that happens through code that is specific to instances of type. I believe that much of it lives under the C-level function that is type.__getattribute__, but some of it may be even more magically intertwined into the guts of the CPython interpreter than that. And as we've seen, we can't call type.__getattribute__ ourselves unless we have something that is an instance of type.

Note that there is literally no attributes we can set on non-type instances that will change this. On actual instances of type, things like __bases__ and __mro__ are not actual attributes but are instead essentially descriptors that look up and manipulate fields in the C-level type struct. The actual code that does things like attribute lookups uses the C-level struct fields directly, which is one reason it requires genuine type instances; only genuine instances even have those struct fields at the right places in memory.

(Note that attribute inheritance in subclasses is far from the only attribute lookup problem we have. Consider accessing C2.afunction and what you'd get back.)

Either problem is fatal, never mind both of them at once (and note that our M2.__call__ is nowhere near a complete emulation of what type.__call__ actually does). Thus as far as I can tell there is absolutely no way to create a fully functional duck typed metaclass in CPython. To do one you'd need access to the methods and other machinery of type and type reserves that machinery for things that are instances of type (for good reason).

I don't think that there's anything in general Python semantics that require this, so another Python implementation might allow or support enough to enable duck typed metaclasses. What blocks us in CPython is how CPython implements type, object, and various core functionality such as creating instances and doing attribute lookups.

(I tried this with PyPy and it failed with a different set of errors depending on which bits of type I was trying to use. I don't have convenient access to any other Python implementations.)

Written on 31 January 2014.
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Last modified: Fri Jan 31 23:15:29 2014
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