Dynamically adding __slots__ to an imported class [duplicate]

Question

Suppose I have a class with __slots__

class A:
    __slots__ = ['x']

a = A()
a.x = 1   # works fine
a.y = 1   # AttributeError (as expected)

Now I am going to change __slots__ of A.

A.__slots__.append('y')
print(A.__slots__)   # ['x', 'y']
b = A()
b.x = 1   # OK
b.y = 1   # AttributeError (why?)

b was created after __slots__ of A had changed, so Python, in principle, could allocate memory for b.y. Why it didn't?

How to properly modify __slots__ of a class, so that new instances have the modified attributes?

Answer 1

You cannot dynamically alter the __slots__ attribute after creating the class, no. That's because the value is used to create special descriptors for each slot. From the __slots__ documentation:

__slots__ are implemented at the class level by creating descriptors (Implementing Descriptors) for each variable name. As a result, class attributes cannot be used to set default values for instance variables defined by __slots__; otherwise, the class attribute would overwrite the descriptor assignment.

You can see the descriptors in the class __dict__:

>>> class A:
...     __slots__ = ['x']
... 
>>> A.__dict__
mappingproxy({'__module__': '__main__', '__doc__': None, 'x': <member 'x' of 'A' objects>, '__slots__': ['x']})
>>> A.__dict__['x']
<member 'x' of 'A' objects>
>>> a = A()
>>> A.__dict__['x'].__get__(a, A)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: x
>>> A.__dict__['x'].__set__(a, 'foobar')
>>> A.__dict__['x'].__get__(a, A)
'foobar'
>>> a.x
'foobar'

You cannot yourself create these additional descriptors. Even if you could, you cannot allocate more memory space for the extra slot references on the instances produced for this class, as that's information stored in the C struct for the class, and not in a manner accessible to Python code.

That's all because __slots__ is only an extension of the low-level handling of the elements that make up Python instances to Python code; the __dict__ and __weakref__ attributes on regular Python instances were always implemented as slots:

>>> class Regular: pass
... 
>>> Regular.__dict__['__dict__']
<attribute '__dict__' of 'Regular' objects>
>>> Regular.__dict__['__weakref__']
<attribute '__weakref__' of 'Regular' objects>
>>> r = Regular()
>>> Regular.__dict__['__dict__'].__get__(r, Regular) is r.__dict__
True

All the Python developers did here was extend the system to add a few more of such slots using arbitrary names, with those names taken from the __slots__ attribute on the class being created, so that you can save memory; dictionaries take more memory than simple references to values in slots do. By specifying __slots__ you disable the __dict__ and __weakref__ slots, unless you explicitly include those in the __slots__ sequence.

The only way to extend slots then is to subclass; you can dynamically create a subclass with the type() function or by using a factory function:

def extra_slots_subclass(base, *slots):
    class ExtraSlots(base):
        __slots__ = slots
    ExtraSlots.__name__ = base.__name__
    return ExtraSlots

Answer 2

It appears to me a type turns __slots__ into a tuple as one of it's first orders of action. It then stores the tuple on the extended type object. Since beneath it all, the python is looking at a tuple, there is no way to mutate it. Indeed, I'm not even sure you can access it unless you pass a tuple in to the instance in the first place.

The fact that the original object that you set still remains as an attribute on the type is (perhaps) just a convenience for introspection.

You can't modify __slots__ and expect to have that show up somewhere (and really -- from a readability perspective, You probably don't really want to do that anyway, right?)...

Of course, you can always subclass to extend the slots:

>>> class C(A):
...   __slots__ = ['z']
... 
>>> c = C()
>>> c.x = 1
>>> c.z = 1