Develop Reference

How to define enum values that are functions?

I have a situation where I need to enforce and give the user the option of one of a number of select functions, to be passed in as an argument to another function:
I really want to achieve something like the following:
from enum import Enum
#Trivial Function 1
def functionA():
pass
#Trivial Function 2
def functionB():
pass
#This is not allowed (as far as i can tell the values should be integers)
#But pseudocode for what I am after
class AvailableFunctions(Enum):
OptionA = functionA
OptionB = functionB
So the following can be executed:
def myUserFunction(theFunction = AvailableFunctions.OptionA):
#Type Check
assert isinstance(theFunction,AvailableFunctions)
#Execute the actual function held as value in the enum or equivalent
return theFunction.value()

Your assumption is wrong. Values can be arbitrary, they are not limited to integers. From the documentation:
The examples above use integers for enumeration values. Using integers
is short and handy (and provided by default by the Functional API),
but not strictly enforced. In the vast majority of use-cases, one
doesn’t care what the actual value of an enumeration is. But if the
value is important, enumerations can have arbitrary values.
However the issue with functions is that they are considered to be method definitions instead of attributes!
In [1]: from enum import Enum
In [2]: def f(self, *args):
...: pass
...:
In [3]: class MyEnum(Enum):
...: a = f
...: def b(self, *args):
...: print(self, args)
...:
In [4]: list(MyEnum) # it has no values
Out[4]: []
In [5]: MyEnum.a
Out[5]: <function __main__.f>
In [6]: MyEnum.b
Out[6]: <function __main__.MyEnum.b>
You can work around this by using a wrapper class or just functools.partial or (only in Python2) staticmethod:
from functools import partial
class MyEnum(Enum):
OptionA = partial(functionA)
OptionB = staticmethod(functionB)
Sample run:
In [7]: from functools import partial
In [8]: class MyEnum2(Enum):
...: a = partial(f)
...: def b(self, *args):
...: print(self, args)
...:
In [9]: list(MyEnum2)
Out[9]: [<MyEnum2.a: functools.partial(<function f at 0x7f4130f9aae8>)>]
In [10]: MyEnum2.a
Out[10]: <MyEnum2.a: functools.partial(<function f at 0x7f4130f9aae8>)>
Or using a wrapper class:
In [13]: class Wrapper:
...: def __init__(self, f):
...: self.f = f
...: def __call__(self, *args, **kwargs):
...: return self.f(*args, **kwargs)
...:
In [14]: class MyEnum3(Enum):
...: a = Wrapper(f)
...:
In [15]: list(MyEnum3)
Out[15]: [<MyEnum3.a: <__main__.Wrapper object at 0x7f413075b358>>]
Also note that if you want you can define the __call__ method in your enumeration class to make the values callable:
In [1]: from enum import Enum
In [2]: def f(*args):
...: print(args)
...:
In [3]: class MyEnum(Enum):
...: a = partial(f)
...: def __call__(self, *args):
...: self.value(*args)
...:
In [5]: MyEnum.a(1,2,3) # no need for MyEnum.a.value(1,2,3)
(1, 2, 3)

Since Python 3.11 there is much more concise and understandable way. member and nonmember functions were added to enum among other improvements, so you can now do the following:
from enum import Enum, member
def fn(x):
print(x)
class MyEnum(Enum):
meth = fn
mem = member(fn)
#classmethod
def this_is_a_method(cls):
print('No, still not a member')
def this_is_just_function():
print('No, not a member')
#member
def this_is_a_member(x):
print('Now a member!', x)
And now
>>> list(MyEnum)
[<MyEnum.mem: <function fn at ...>>, <MyEnum.this_is_a_member: <function MyEnum.this_is_a_member at ...>>]
>>> MyEnum.meth(1)
1
>>> MyEnum.mem(1)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: 'MyEnum' object is not callable
>>> MyEnum.mem.value(1)
1
>>> MyEnum.this_is_a_method()
No, still not a member
>>> MyEnum.this_is_just_function()
No, not a member
>>> MyEnum.this_is_a_member()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: 'MyEnum' object is not callable
>>> MyEnum.this_is_a_member.value(1)
Now a member! 1

Another less clunky solution is to put the functions in a tuple. As Bakuriu mentioned, you may want to make the enum callable.
from enum import Enum
def functionA():
pass
def functionB():
pass
class AvailableFunctions(Enum):
OptionA = (functionA,)
OptionB = (functionB,)
def __call__(self, *args, **kwargs):
self.value[0](*args, **kwargs)
Now you can use it like this:
AvailableFunctions.OptionA() # calls functionA

In addition to the answer of Bakuriu... If you use the wrapper approach like above you loose information about the original function like __name__, __repr__
and so on after wrapping it. This will cause problems for example if you want to use sphinx for generation of source code documentation. Therefore add the following to your wrapper class.
class wrapper:
def __init__(self, function):
self.function = function
functools.update_wrapper(self, function)
def __call__(self,*args, **kwargs):
return self.function(*args, **kwargs)
def __repr__(self):
return self.function.__repr__()

Building on top of #bakuriu's approach, I just want to highlight that we can also use dictionaries of multiple functions as values and have a broader polymorphism, similar to enums in Java. Here is a fictitious example to show what I mean:
from enum import Enum, unique
#unique
class MyEnum(Enum):
test = {'execute': lambda o: o.test()}
prod = {'execute': lambda o: o.prod()}
def __getattr__(self, name):
if name in self.__dict__:
return self.__dict__[name]
elif not name.startswith("_"):
value = self.__dict__['_value_']
return value[name]
raise AttributeError(name)
class Executor:
def __init__(self, mode: MyEnum):
self.mode = mode
def test(self):
print('test run')
def prod(self):
print('prod run')
def execute(self):
self.mode.execute(self)
Executor(MyEnum.test).execute()
Executor(MyEnum.prod).execute()
Obviously, the dictionary approach provides no additional benefit when there is only a single function, so use this approach when there are multiple functions. Ensure that the keys are uniform across all values as otherwise, the usage won't be polymorphic.
The __getattr__ method is optional, it is only there for syntactic sugar (i.e., without it, mode.execute() would become mode.value['execute']().
Since dictionaries can't be made readonly, using namedtuple would be better and require only minor changes to the above.
from enum import Enum, unique
from collections import namedtuple
EnumType = namedtuple("EnumType", "execute")
#unique
class MyEnum(Enum):
test = EnumType(lambda o: o.test())
prod = EnumType(lambda o: o.prod())
def __getattr__(self, name):
if name in self.__dict__:
return self.__dict__[name]
elif not name.startswith("_"):
value = self.__dict__['_value_']
return getattr(value, name)
raise AttributeError(name)

What is the hidden argument being passed to my `MethodType`?

I recently came across this recipe for making a "weakmethod" and thought it was the bees' knees; but there seems to be a mystery argument being passed to the resulting MethodType function that i can't seem to find:
from weakref import proxy
from types import MethodType
class Foo(object):
def __getattribute__(self, name):
if name.startswith('foo_'):
return MethodType(super(Foo, self).__getattribute__(name), proxy(self), self.__class__)
else:
return super(Foo, self).__getattribute__(name)
class Bar(Foo):
def my_func(self, a, b):
print a, b
def foo_my_func(self, a, b):
print 'FF Victory Theme'
>>> bar = Bar()
>>> bar.my_func(1, 2)
1 2
>>> weakmethod = bar.foo_my_func
>>> weakmethod(2, 3) # Or `bar.foo_my_func(2, 3)`
Traceback (most recent call last):
File "<pyshell#160>", line 1, in <module>
weakmethod(2, 3)
TypeError: foo_my_func() takes exactly 3 arguments (4 given)
What is this 4th argument that's being passed?

You used super(Foo, self).__getattribute__(name) to access the foo_my_func method. This already returns a MethodType object. You then wrap this object again.
So your returned object passes in proxy(self) to the wrapped method, which passes in another self argument. You started with a, b, and end up with self, proxy(self), a, b.
The recipe you linked to uses a decorator instead; this decorator is executed at class definition time, and wraps the function object. It is itself a descriptor, so it handles all the wrapping directly.
You'll want to either unwrap the result of super(Foo, self).__getattribute__(name) or don't use __getattribute__ at all.
Unwrapping can be done with accessing the __func__ attribute on a method:
class Foo(object):
def __getattribute__(self, name):
attr = super(Foo, self).__getattribute__(name)
if name.startswith('foo_'):
return MethodType(attr.__func__, proxy(self), self.__class__)
return attr
Not using __getattribute__ is done by just accessing the __dict__ mapping on the class directly:
class Foo(object):
def __getattribute__(self, name):
if name.startswith('foo_'):
for cls in type(self).__mro__:
if name in cls.__dict__:
return MethodType(cls.__dict__[name], proxy(self), self.__class__)
return super(Foo, self).__getattribute__(name)
where type(self).__mro__ lets you iterate over the class and it's base classes in method resolution order to manually search for the method.

Abstract attribute (not property)?

What's the best practice to define an abstract instance attribute, but not as a property?
I would like to write something like:
class AbstractFoo(metaclass=ABCMeta):
#property
#abstractmethod
def bar(self):
pass
class Foo(AbstractFoo):
def __init__(self):
self.bar = 3
Instead of:
class Foo(AbstractFoo):
def __init__(self):
self._bar = 3
#property
def bar(self):
return self._bar
#bar.setter
def setbar(self, bar):
self._bar = bar
#bar.deleter
def delbar(self):
del self._bar
Properties are handy, but for simple attribute requiring no computation they are an overkill. This is especially important for abstract classes which will be subclassed and implemented by the user (I don't want to force someone to use #property when he just could have written self.foo = foo in the __init__).
Abstract attributes in Python question proposes as only answer to use #property and #abstractmethod: it doesn't answer my question.
The ActiveState recipe for an abstract class attribute via AbstractAttribute may be the right way, but I am not sure. It also only works with class attributes and not instance attributes.

A possibly a bit better solution compared to the accepted answer:
from better_abc import ABCMeta, abstract_attribute # see below
class AbstractFoo(metaclass=ABCMeta):
#abstract_attribute
def bar(self):
pass
class Foo(AbstractFoo):
def __init__(self):
self.bar = 3
class BadFoo(AbstractFoo):
def __init__(self):
pass
It will behave like this:
Foo() # ok
BadFoo() # will raise: NotImplementedError: Can't instantiate abstract class BadFoo
# with abstract attributes: bar
This answer uses same approach as the accepted answer, but integrates well with built-in ABC and does not require boilerplate of check_bar() helpers.
Here is the better_abc.py content:
from abc import ABCMeta as NativeABCMeta
class DummyAttribute:
pass
def abstract_attribute(obj=None):
if obj is None:
obj = DummyAttribute()
obj.__is_abstract_attribute__ = True
return obj
class ABCMeta(NativeABCMeta):
def __call__(cls, *args, **kwargs):
instance = NativeABCMeta.__call__(cls, *args, **kwargs)
abstract_attributes = {
name
for name in dir(instance)
if getattr(getattr(instance, name), '__is_abstract_attribute__', False)
}
if abstract_attributes:
raise NotImplementedError(
"Can't instantiate abstract class {} with"
" abstract attributes: {}".format(
cls.__name__,
', '.join(abstract_attributes)
)
)
return instance
The nice thing is that you can do:
class AbstractFoo(metaclass=ABCMeta):
bar = abstract_attribute()
and it will work same as above.
Also one can use:
class ABC(ABCMeta):
pass
to define custom ABC helper. PS. I consider this code to be CC0.
This could be improved by using AST parser to raise earlier (on class declaration) by scanning the __init__ code, but it seems to be an overkill for now (unless someone is willing to implement).
2021: typing support
You can use:
from typing import cast, Any, Callable, TypeVar
R = TypeVar('R')
def abstract_attribute(obj: Callable[[Any], R] = None) -> R:
_obj = cast(Any, obj)
if obj is None:
_obj = DummyAttribute()
_obj.__is_abstract_attribute__ = True
return cast(R, _obj)
which will let mypy highlight some typing issues
class AbstractFooTyped(metaclass=ABCMeta):
#abstract_attribute
def bar(self) -> int:
pass
class FooTyped(AbstractFooTyped):
def __init__(self):
# skipping assignment (which is required!) to demonstrate
# that it works independent of when the assignment is made
pass
f_typed = FooTyped()
_ = f_typed.bar + 'test' # Mypy: Unsupported operand types for + ("int" and "str")
FooTyped.bar = 'test' # Mypy: Incompatible types in assignment (expression has type "str", variable has type "int")
FooTyped.bar + 'test' # Mypy: Unsupported operand types for + ("int" and "str")
and for the shorthand notation, as suggested by #SMiller in the comments:
class AbstractFooTypedShorthand(metaclass=ABCMeta):
bar: int = abstract_attribute()
AbstractFooTypedShorthand.bar += 'test' # Mypy: Unsupported operand types for + ("int" and "str")

Just because you define it as an abstractproperty on the abstract base class doesn't mean you have to make a property on the subclass.
e.g. you can:
In [1]: from abc import ABCMeta, abstractproperty
In [2]: class X(metaclass=ABCMeta):
...: #abstractproperty
...: def required(self):
...: raise NotImplementedError
...:
In [3]: class Y(X):
...: required = True
...:
In [4]: Y()
Out[4]: <__main__.Y at 0x10ae0d390>
If you want to initialise the value in __init__ you can do this:
In [5]: class Z(X):
...: required = None
...: def __init__(self, value):
...: self.required = value
...:
In [6]: Z(value=3)
Out[6]: <__main__.Z at 0x10ae15a20>
Since Python 3.3 abstractproperty is deprecated. So Python 3 users should use the following instead:
from abc import ABCMeta, abstractmethod
class X(metaclass=ABCMeta):
#property
#abstractmethod
def required(self):
raise NotImplementedError

If you really want to enforce that a subclass define a given attribute, you can use metaclasses:
class AbstractFooMeta(type):
def __call__(cls, *args, **kwargs):
"""Called when you call Foo(*args, **kwargs) """
obj = type.__call__(cls, *args, **kwargs)
obj.check_bar()
return obj
class AbstractFoo(object):
__metaclass__ = AbstractFooMeta
bar = None
def check_bar(self):
if self.bar is None:
raise NotImplementedError('Subclasses must define bar')
class GoodFoo(AbstractFoo):
def __init__(self):
self.bar = 3
class BadFoo(AbstractFoo):
def __init__(self):
pass
Basically the meta class redefine __call__ to make sure check_bar is called after the init on an instance.
GoodFoo()  # ok
BadFoo ()  # yield NotImplementedError

As Anentropic said, you don't have to implement an abstractproperty as another property.
However, one thing all answers seem to neglect is Python's member slots (the __slots__ class attribute). Users of your ABCs required to implement abstract properties could simply define them within __slots__ if all that's needed is a data attribute.
So with something like,
class AbstractFoo(abc.ABC):
__slots__ = ()
bar = abc.abstractproperty()
Users can define sub-classes simply like,
class Foo(AbstractFoo):
__slots__ = 'bar', # the only requirement
# define Foo as desired
def __init__(self):
self.bar = ...
Here, Foo.bar behaves like a regular instance attribute, which it is, just implemented differently. This is simple, efficient, and avoids the #property boilerplate that you described.
This works whether or not ABCs define __slots__ at their class' bodies. However, going with __slots__ all the way not only saves memory and provides faster attribute accesses but also gives a meaningful descriptor instead of having intermediates (e.g. bar = None or similar) in sub-classes.1
A few answers suggest doing the "abstract" attribute check after instantiation (i.e. at the meta-class __call__() method) but I find that not only wasteful but also potentially inefficient as the initialization step could be a time-consuming one.
In short, what's required for sub-classes of ABCs is to override the relevant descriptor (be it a property or a method), it doesn't matter how, and documenting to your users that it's possible to use __slots__ as implementation for abstract properties seems to me as the more adequate approach.
1 In any case, at the very least, ABCs should always define an empty __slots__ class attribute because otherwise sub-classes are forced to have __dict__ (dynamic attribute access) and __weakref__ (weak reference support) when instantiated. See the abc or collections.abc modules for examples of this being the case within the standard library.

The problem isn't what, but when:
from abc import ABCMeta, abstractmethod
class AbstractFoo(metaclass=ABCMeta):
#abstractmethod
def bar():
pass
class Foo(AbstractFoo):
bar = object()
isinstance(Foo(), AbstractFoo)
#>>> True
It doesn't matter that bar isn't a method! The problem is that __subclasshook__, the method of doing the check, is a classmethod, so only cares whether the class, not the instance, has the attribute.
I suggest you just don't force this, as it's a hard problem. The alternative is forcing them to predefine the attribute, but that just leaves around dummy attributes that just silence errors.

I've searched around for this for awhile but didn't see anything I like. As you probably know if you do:
class AbstractFoo(object):
#property
def bar(self):
raise NotImplementedError(
"Subclasses of AbstractFoo must set an instance attribute "
"self._bar in it's __init__ method")
class Foo(AbstractFoo):
def __init__(self):
self.bar = "bar"
f = Foo()
You get an AttributeError: can't set attribute which is annoying.
To get around this you can do:
class AbstractFoo(object):
#property
def bar(self):
try:
return self._bar
except AttributeError:
raise NotImplementedError(
"Subclasses of AbstractFoo must set an instance attribute "
"self._bar in it's __init__ method")
class OkFoo(AbstractFoo):
def __init__(self):
self._bar = 3
class BadFoo(AbstractFoo):
pass
a = OkFoo()
b = BadFoo()
print a.bar
print b.bar # raises a NotImplementedError
This avoids the AttributeError: can't set attribute but if you just leave off the abstract property all together:
class AbstractFoo(object):
pass
class Foo(AbstractFoo):
pass
f = Foo()
f.bar
You get an AttributeError: 'Foo' object has no attribute 'bar' which is arguably almost as good as the NotImplementedError. So really my solution is just trading one error message from another .. and you have to use self._bar rather than self.bar in the init.

Following https://docs.python.org/2/library/abc.html you could do something like this in Python 2.7:
from abc import ABCMeta, abstractproperty
class Test(object):
__metaclass__ = ABCMeta
#abstractproperty
def test(self): yield None
def get_test(self):
return self.test
class TestChild(Test):
test = None
def __init__(self, var):
self.test = var
a = TestChild('test')
print(a.get_test())

Can Python classes have members that are accessible, but not from an instance of the class?

So I don't come from a computer science background and I am having trouble googling/SO searching on the right terms to answer this question. If I have a Python class with a class variable objects like so:
class MyClass(object):
objects = None
pass
MyClass.objects = 'test'
print MyClass.objects # outputs 'test'
a = MyClass()
print a.objects # also outputs 'test'
both the class and instances of the class will have access to the objects variable. I understand that I can change the instance value like so:
a.objects = 'bar'
print a.objects # outputs 'bar'
print MyClass.objects # outputs 'test'
but is it possible to have a class variable in Python that is accessible to users of the class (i.e. not just from within the class) but not accessible to the instances of that class? I think this is called a private member or static member in other languages?

Python is designed to allow instances of a class to access that class's attributes through the instance.
This only goes one level deep, so you can use a metaclass:
class T(type):
x = 5
class A(object):
__metaclass__ = T
Note that the metaclass syntax is different in Python 3. This works:
>>> A.x
5
>>> A().x
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'A' object has no attribute 'x'
It doesn't prevent you setting the attribute on instances of the class, though; to prevent that you'd have to play with __setattr__ magic method:
class A(object):
x = 1
def __getattribute__(self, name):
if name == 'x':
raise AttributeError
return super(A, self).__getattribute__(name)
def __setattr__(self, name, value):
if name == 'x':
raise AttributeError
return super(A, self).__setattr__(name, value)
def __delattr__(self, name):
if name == 'x':
raise AttributeError
return super(A, self).__delattr__(name)

The simplest way of achieving it is to use a descriptor. Descriptors are the thing meant for giving a higher level of control over attribute access. For example:
class ClassOnly(object):
def __init__(self, name, value):
self.name = name
self.value = value
def __get__(self, inst, cls):
if inst is not None:
msg = 'Cannot access class attribute {} from an instance'.format(self.name)
raise AttributeError(msg)
return self.value
class A(object):
objects = ClassOnly('objects', [])
Used as:
In [11]: a = A()
In [12]: a.objects
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-12-24afc67fd0ba> in <module>()
----> 1 a.objects
<ipython-input-9-db6510cd313b> in __get__(self, inst, cls)
5 def __get__(self, inst, cls):
6 if inst is not None:
----> 7 raise AttributeError('Cannot access class attribute {} from an instance'.format(self.name))
8 return self.value
AttributeError: Cannot access class attribute objects from an instance
In [13]: A.objects
Out[13]: []

If you want there to be a "single source of truth" for objects, you could make it a mutable type:
class MyClass(object):
objects = []
With immutable types, the fact that each instance starts out with the same reference from MyClass is irrelevant, as the first time that attribute is changed for the instance, it becomes "disconnected" from the class's value.
However, if the attribute is mutable, changing it in an instance changes it for the class and all other instances of the class:
>>> MyClass.objects.append(1)
>>> MyClass.objects
[1]
>>> a = MyClass()
>>> a.objects
[1]
>>> a.objects.append(2)
>>> a.objects
[1, 2]
>>> MyClass.objects
[1, 2]
In Python, nothing is really "private", so you can't really prevent the instances from accessing or altering objects (in that case, is it an appropriate class attribute?), but it is conventional to prepend names with an underscore if you don't ordinarily want them to be accessed directly: _objects.
One way to actually protect objects from instance access would be to override __getattribute__:
def __getattribute__(self, name):
if name == "objects":
raise AttributeError("Do not access 'objects' though MyClass instances.")
return super(MyClass, self).__getattribute__(name)
>>> MyClass.objects
[1]
>>> a.objects
...
AttributeError: Do not access 'objects' though MyClass instances.

No, you can't (EDIT: you can't in a way that is completely unaccessible, like in Java or C++).
You can do this, if you like:
class MyClass(object):
objects = None
pass
MyClass_objects = 'test'
print MyClass_objects # outputs 'test'
a = MyClass()
print a.objects # outputs 'None'
or this:
in your_module.py:
objects = 'test'
class MyClass(object):
objects = None
pass
in yourapp.py:
import your_module
print your_module.objects # outputs 'test'
a = your_module.MyClass()
print a.objects # outputs 'None'
the reason is:
When you create an instance of some class there is nothing to prevent
you from poking around inside and using various internal, private
methods that are (a) necessary for the class to function, BUT (b) not
intended for direct use/access.
Nothing is really private in python. No class or class instance can
keep you away from all what's inside (this makes introspection
possible and powerful). Python trusts you. It says "hey, if you want
to go poking around in dark places, I'm gonna trust that you've got a
good reason and you're not making trouble."
Karl Fast

Remove attribute from subclass in Python

Is there any way to remove an attribute from a subclass that is present in the parent?
In the following example
class A(object):
foo = 1
bar = 2
class B(A):
pass
# <desired code here>
b = B()
assert hasattr(b, 'bar') == False
Is there any code we can write to make the assertion pass?

class A(object):
foo = 1
bar = 2
class B(A):
#property
def bar(self):
raise AttributeError
>>> b = B()
>>> b.bar
Traceback (most recent call last):
File "<pyshell#17>", line 1, in <module>
b.bar
File "<pyshell#15>", line 4, in bar
raise AttributeError
AttributeError

This works for me whe I don't want a specific attribute ('bar' in this case) to be listed in dir(A).
class A(object):
foo = 1
bar = 2
class B(A):
def ___init__(self):
self.delete()
def delete(self):
delattr(self, 'bar')
Basically, create a method (delete) in the subclass B that deletes that attribute and put that in the constructor.

Yes, using the magic of descriptors. See my blog post about it. Short version:
class nosubclasses(object):
def __init__(self, f, cls):
self.f = f
self.cls = cls
def __get__(self, obj, type=None):
if type == self.cls:
if hasattr(self.f, '__get__'):
return self.f.__get__(obj, type)
return self.f
raise AttributeError
Example:
In [2]: class MyClass(object):
...: x = 1
...:
In [3]: MyClass.x = nosubclasses(MyClass.x, MyClass)
In [4]: class MySubclass(MyClass):
...: pass
...:
In [5]: MyClass.x
Out[5]: 1
In [6]: MyClass().x
Out[6]: 1
In [80]: MySubclass.x
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-80-2b2f456dd101> in <module>()
----> 1 MySubclass.x
<ipython-input-51-7fe1b5063367> in __get__(self, obj, type)
8 return self.f.__get__(obj, type)
9 return self.f
---> 10 raise AttributeError
AttributeError:
In [81]: MySubclass().x
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-81-93764eeb9948> in <module>()
----> 1 MySubclass().x
<ipython-input-51-7fe1b5063367> in __get__(self, obj, type)
8 return self.f.__get__(obj, type)
9 return self.f
---> 10 raise AttributeError
AttributeError:
But as the commenter #delnan pointed out, this violates the Liskov substitutability principle. The motivation in my blog post was warranted, because the attribute did not describe the object itself. But in general, this breaks the whole point of being able to subclass in the first place, which is really the whole point of having classes at all.
By the way, the difference between my answer and #jamylak's is that in #jamylak's answer, attributes are removed on a per-subclass basis. If you made a class C(A), it would still have the bar attribute. In my answer, the class itself (well, actually the attribute), disallows subclasses from having the attribute, so that in one fell swoop, all subclasses don't have it.