Develop Reference

Define a #property and #classproperty with the same name (Python, Django)

Background
The Django LiveServerTestCase class has a live_server_url method with a #classproperty decorator. (django.utils.functional.classproperty.) The class starts its test server before any tests run, and thus knows the test server's URL before any tests run.
I have a similar MyTestCase class that has a live_server_url #property. It starts a new test server before each test, and thus its live_server_url property can't be a #classproperty because it doesn't know its port until it is instantiated.
To make the API for both consistent, so that all the test utility functions etc. in the code base can be used with both classes, the tests could be written to never reference live_server_url in setUpClass(), before all the tests run. But this would slow down many tests.
Instead, I want MyTestCase.live_server_url to raise a helpful error if it is referenced from the class object rather than an instance object.
Since MyTestCase.live_server_url is a #property, MyTestCase().live_server_url returns a string, but MyTestCase.live_server_url returns a property object. This causes cryptic errors like "TypeError: unsupported operand type(s) for +: 'property' and 'str'".
Actual question
If I could define a #classproperty and #property on the same class, then I would define a MyTestCase.live_server_url #classproperty that raises an error with a helpful message like "live_server_url can only be called on an instance of MyTestCase, not on the MyTestCase class".
But when you define 2 methods with the same name in a Python class then the earlier one gets discarded, so I can't do that.
How can I make the behavior of MyTestCase.live_server_url different depending on whether it is called on the class or on an instance?

One option might be to use a metaclass. (Example)
But since I read that metaclasses should usually be avoided, here is what I did:
from django.utils.functional import classproperty
class MyTestCase(TransactionTestCase):
def __getattribute__(self, attr: str):
if attr == 'live_server_url':
return "http://%s:%s" % (self.host, self._port)
return super().__getattribute__(attr)
#classproperty
def live_server_url(self):
raise ValueError('live_server_url can only be called on an instance of MyTestCase, not on the MyTestCase class')
MyTestCase().live_server_url calls __getattribute__().
MyTestCase.live_server_url calls the #classproperty definition of live_server_url.

Just subclass property and implement __get__ to raise on error if it is not accessed through an instance :
class OnlyInstanceProperty(property):
def __get__(self, obj, objtype=None):
if obj is None:
raise ValueError('live_server_url can only be called on an instance of MyTestCase, not on the MyTestCase class')
return super().__get__(obj, objtype)
Perhaps you can come up with a better name for it. But in any case, you can then use it like so:
class MyTestClass:
def __init__(self):
self.host = "foo"
self._port = "bar"
#OnlyInstanceProperty
def live_server_url(self):
return "http://%s:%s" % (self.host, self._port)
Then:
print(MyTestClass.live_server_url) # http://foo:bar
print(MyTestClass.live_server_url) # ValueError: live_server_url can only be called on an instance of MyTestCase, not on the MyTestCase class
And it will work like any other property, so you can use live_server_url.setter and live_server_url.deleter
If you are unfamiliar with __get__, read this HOWTO and it should tell you all you need to know about descriptors, which are an intermediate/advanced Python technique. The descriptor protocol is behind a lot of seemingly magical behavior, and that HOWTO shows you how various things like classmethod, staticmethod, property could be implemented in pure python using the descriptor protocol.
Note, you don't have to inherit from property, a simple bespoke (albeit tightly coupled) approach could be something like:
class LiveServerUrl:
def __get__(self, obj, objtype=None):
if obj is None:
raise ValueError('live_server_url can only be called on an instance of MyTestCase, not on the MyTestCase class')
return "http://%s:%s" % (obj.host, obj._port)
class MyTestClass:
live_server_url = LiveServerUrl()
def __init__(self):
self.host = "foo"
self._port = "bar"

Why are properties class attributes in Python?

I'm reading Fluent Python chapter 19 > A Proper Look at Properties, and I'm confused about the following words:
Properties are always class attributes, but they actually manage attribute access in the instances of the class.
The example code is:
class LineItem:
def __init__(self, description, weight, price):
self.description = description
self.weight = weight # <1>
self.price = price
def subtotal(self):
return self.weight * self.price
#property # <2>
def weight(self): # <3>
return self.__weight # <4>
#weight.setter # <5>
def weight(self, value):
if value > 0:
self.__weight = value # <6>
else:
raise ValueError('value must be > 0') # <7>
From my previous experiences, class attributes are belong to the class itself and shared by all the instances. But here, weight, the property, is an instance method and the value returned by it is different between instances. How is it eligible to be a class attribute? Doesn't it that all the class attributes should be the same for any instances?
I think I misunderstand something, so I hope to get a correct explanation. Thanks!

A distinction is made because when you define a #property on a class, that property object becomes an attribute on the class. Whereas when you define attributes against an instance of your class (in your __init__ method), that attribute only exists against that object. This might be confusing if you do:
>>> dir(LineItem)
['__class__', ..., '__weakref__', 'subtotal', 'weight']
>>> item = LineItem("an item", 3, 1.12)
>>> dir(item)
['__class__', ..., '__weakref__', 'description', 'price', 'subtotal', 'weight']
Notice how both subtotal and weight exist as attributes on your class.
I think it's also worth noting that when you define a class, code under that class is executed. This includes defining variables (which then become class attributes), defining functions, and anything else.
>>> import requests
>>> class KindOfJustANamespace:
... text = requests.get("https://example.com").text
... while True:
... break
... for x in range(2):
... print(x)
...
0
1
>>> KindOfJustANamespace.text
'<!doctype html>\n<html>\n<head>\n <title>Example Domain...'
A #decorator is just "syntactic sugar". Meaning #property over a function if the same as function = property(function). This applies to functions defined inside a class as well, but now the function is part of the class's namespace.
class TestClass:
#property
def foo(self):
return "foo"
# ^ is the same as:
def bar(self):
return "bar"
bar = property(bar)
A good explanation of property in Python can be found here: https://stackoverflow.com/a/17330273/7220776

From my previous experiences, class attributes are belong to the class itself and shared by all the instances.
That's right.
But here, weight, the property, is an instance method
No, it's a property object. When you do:
#decorator
def func():
return 42
it's actually syntactic sugar for
def func():
return 42
func = decorator(func)
IOW the def statement is executed, the function object created, but instead of beeing bound to it's name, it's passed to the decorator callable, and the name is bound to whatever decorator() returned.
In this case the decorator is the property class itself, so the weight attribute is a property instance. You can check this out by yourself by inspecting LineItem.weight (which will return the property object itself).
and the value returned by it is different between instances.
Well yes of course, how is this surprising ? LineItem.subtotal is a class attribute also (like all methods), yet it returns values from the instance it's called on (which is passed to the function as the self param).
How is it eligible to be a class attribute? Doesn't it that all the class attributes should be the same for any instances?
The class attributes ARE the same for all instances of a class, yes. There's only one single subtotal function for all instances of LineItem.
A property is mainly a shortcut to make a function (or a pair of functions if you specify a setter) look like it's a plain attribute, so when you type mylinitem.weight, what is really executed is LineItem.weight.fget(mylineitem), where fget is the getter function you decorated with #property. The mechanism behind this is known as the "descriptor protocol", which is also used to turn mylineitem.subtotal() into LineItem.subtotal(mylineitem) (python functions implement the descriptor protocol to return "method" objects, which are themselves wrappers around the function and the current instance and insert the instance as first argument to the function call).
So it's not suprising that properties are class attributes - you only need one property instance to "serve" all instances of the class -, and moreover, properties - like all descriptors FWIW - MUST actually be class attributes to work as expected, since the descriptor protocol is only invoked on class attributes (there's no use case for a "per instance" computed attribute since the function in charge of the "computation" will get the instance as parameter).

I finally understand the descriptor and property concept through Simeon Franklin's excellent presentation, the following contents can be seen as a summary on his lecture notes. Thanks to him!
To understand properties, you first need to understand descriptors, because a property is implemented by a descriptor and python's decorator syntactic sugar. Don't worry, it's not that difficult.
What is a descriptor:
a descriptor is any object that implements at least one of methods named __get__(), __set__(), and __delete__().
Descriptor can be divided into two categories:
A data descriptor implements both __get__() and __set__().
A non-data descriptor implements only __get__().
According to python's HowTo:
a descriptor is an object attribute with “binding behavior”, one whose attribute access has been overridden by methods in the descriptor protocol.
Then what is the descriptor protocol? Basically speaking, it's just says that when Python interpreter comes across an attribute access like obj.attr，it will search in some order to resolve this .attr , and if this attr is a descriptor attribute, then this descriptor will take some precedence in this specific order and this attribute access will be translated into a method call on this descriptor according to the descriptor protocol, possibly shadowing a namesake instance attribute or class attribute. More concretely, if attr is a data descriptor, then obj.attr will be translated into the calling result of this descriptor's __get__ method; if attr is not a data descriptor and is an instance attribute, this instance attribute will be matched; if attr is not in above, and it is a non-data descriptor, we get the calling result of this non-data descriptor's __get__ method. Full rules on attribute resolution can be found here .
Now let's talk about property. If you have looked at Python' descriptor HowTo, you can find a pure Python version implementation of property:
class Property(object):
"Emulate PyProperty_Type() in Objects/descrobject.c"
def __init__(self, fget=None, fset=None, fdel=None, doc=None):
self.fget = fget
self.fset = fset
self.fdel = fdel
if doc is None and fget is not None:
doc = fget.__doc__
self.__doc__ = doc
def __get__(self, obj, objtype=None):
if obj is None:
return self
if self.fget is None:
raise AttributeError("unreadable attribute")
return self.fget(obj)
def __set__(self, obj, value):
if self.fset is None:
raise AttributeError("can't set attribute")
self.fset(obj, value)
def __delete__(self, obj):
if self.fdel is None:
raise AttributeError("can't delete attribute")
self.fdel(obj)
def getter(self, fget):
return type(self)(fget, self.fset, self.fdel, self.__doc__)
def setter(self, fset):
return type(self)(self.fget, fset, self.fdel, self.__doc__)
def deleter(self, fdel):
return type(self)(self.fget, self.fset, fdel, self.__doc__)
Apparently，property is a data descriptor!
#property just uses python's decorator syntactic sugar.
#property
def attr(self):
pass
is equivalent to:
attr = property(attr)
So, attr is no longer an instance method as I posted in thie question, but is translated into a class attribute by the decorator syntactic sugar as the author said. It's a descriptor object attribute.
How is it eligible to be a class attribute?
OK, we solved it now.
Then:
Doesn't it that all the class attributes should be the same for any instances?
No!
I steal an example from Simeon Franklin's excellent presentation .
>>> class MyDescriptor(object):
... def __get__(self, obj, type):
... print self, obj, type
... def __set__(self, obj, val):
... print "Got %s" % val
...
>>> class MyClass(object):
... x = MyDescriptor() # Attached at class definition time!
...
>>> obj = MyClass()
>>> obj.x # a function call is hiding here
<...MyDescriptor object ...> <....MyClass object ...> <class '__main__.MyClass'>
>>>
>>> MyClass.x # and here!
<...MyDescriptor object ...> None <class '__main__.MyClass'>
>>>
>>> obj.x = 4 # and here
Got 4
Pay attention to obj.x and its output. The second element in its output is <....MyClass object ...> . It's the specific instance obj . Shortly speaking, because this attribute access has been translated into a __get__ method call, and this __get__ method get the specific instance argument as its method signature descr.__get__(self, obj, type=None) demands, it can return different values according to which instance it is been called by.
Note: my English explanation maybe not clear enough, so I highly recommend you to look at Simeon Franklin's notes and Python's descriptor HowTo.

You didn't misunderstand. Don't worry, just read on. It will become clear in the next chapter.
The same book explains in chapter 20 that they can be a class attributes because of the descriptor protocol. The documentation explains how properties are implemented as descriptors.
As you see from the example, properties are really class attributes (methods). When called, they get a reference to the instance, and writes/reads to its underlying __dict__.

I think the example is wrong, the init shoul look like this:
def __init__(self, description, weight, price):
self.description = description
self.__weight = weight # <1>
self.__price = price
self.__weight and self.__price are the internal attributes hidden in the class by the properties

How to create an abstract class attribute (potentially read-only)

I have spent a lot of time researching this, but none of the answers seem to work how I would like.
I have an abstract class with a class attribute I want each subclass to be forced to implement
class AbstractFoo():
forceThis = 0
So that when I do this
class RealFoo(AbstractFoo):
pass
it throws an error telling me it can't create the class until I implement forceThis.
How can I do that?
(I don't want the attribute to be read-only, but if that's the only solution, I'll accept it.)
For a class method, I've discovered I can do
from abc import ABCMeta, abstractmethod
class AbstractFoo(metaclass=ABCMeta):
#classmethod
#abstractmethod
def forceThis():
"""This must be implemented"""
so that
class RealFoo(AbstractFoo):
pass
at least throws the error TypeError: Can't instantiate abstract class EZ with abstract methods forceThis
(Although it doesn't force forceThis to be a class method.)
How can I get a similar error to pop up for the class attribute?

You can do this by defining your own metaclass. Something like:
class ForceMeta(type):
required = ['foo', 'bar']
def __new__(mcls, name, bases, namespace):
cls = super().__new__(mcls, name, bases, namespace)
for prop in mcls.required:
if not hasattr(cls, prop):
raise NotImplementedError('must define {}'.format(prop))
return cls
Now you can use this as the metaclass of your own classes:
class RequiredClass(metaclass=ForceMeta):
foo = 1
which will raise the error 'must define bar'.

I came up with a solution based on those posted earlier. (Thank you #Daniel Roseman and #martineau)
I created a metaclass called ABCAMeta (the last 'A' stands for 'Attributes').
The class has two ways of working.
A class which just uses ABCAMeta as a metaclass must have a property called required_attributes which should contain a list of the names of all the attributes you want to require on future subclasses of that class
A class whose parent's metaclass is ABCAMeta must have all the required attributes specified by its parent class(es).
For example:
class AbstractFoo(metaclass=ABCAMeta):
required_attributes = ['force_this']
class RealFoo(AbstractFoo):
pass
will throw an error:
NameError: Class 'RealFoo' has not implemented the following attributes: 'force_this'
Exactly how I wanted.
from abc import ABCMeta
class NoRequirements(RuntimeError):
def __init__(self, message):
RuntimeError.__init__(self, message)
class ABCAMeta(ABCMeta):
def __init__(mcls, name, bases, namespace):
ABCMeta.__init__(mcls, name, bases, namespace)
def __new__(mcls, name, bases, namespace):
def get_requirements(c):
"""c is a class that should have a 'required_attributes' attribute
this function will get that list of required attributes or
raise a NoRequirements error if it doesn't find one.
"""
if hasattr(c, 'required_attributes'):
return c.required_attributes
else:
raise NoRequirements(f"Class '{c.__name__}' has no 'required_attributes' property")
cls = super().__new__(mcls, name, bases, namespace)
# true if no parents of the class being created have ABCAMeta as their metaclass
basic_metaclass = True
# list of attributes the class being created must implement
# should stay empty if basic_metaclass stays True
reqs = []
for parent in bases:
parent_meta = type(parent)
if parent_meta==ABCAMeta:
# the class being created has a parent whose metaclass is ABCAMeta
# the class being created must contain the requirements of the parent class
basic_metaclass=False
try:
reqs.extend(get_requirements(parent))
except NoRequirements:
raise
# will force subclasses of the created class to define
# the attributes listed in the required_attributes attribute of the created class
if basic_metaclass:
get_requirements(cls) # just want it to raise an error if it doesn't have the attributes
else:
missingreqs = []
for req in reqs:
if not hasattr(cls, req):
missingreqs.append(req)
if len(missingreqs)!=0:
raise NameError(f"Class '{cls.__name__}' has not implemented the following attributes: {str(missingreqs)[1:-1]}")
return cls
Any suggestions for improvement are welcome in the comments.

Although you can do something very similar with a metaclass, as illustrated in #Daniel Roseman's answer, it can also be done with a class decorator. A couple of advantages they have are that errors will occur when the class is defined, instead of when an instance of one is created, and the syntax for specifying them is the same in both Python 2 and 3. Some folks also find them simpler and easier to understand.
def check_reqs(cls):
requirements = 'must_have',
missing = [req for req in requirements if not hasattr(cls, req)]
if missing:
raise NotImplementedError(
'class {} did not define required attribute{} named {}'.format(
cls.__name__, 's' if len(missing) > 1 else '',
', '.join('"{}"'.format(name) for name in missing)))
return cls
#check_reqs
class Foo(object): # OK
must_have = 42
#check_reqs
class Bar(object): # raises a NotImplementedError
pass

How to make a class attribute exclusive to the super class

I have a master class for a planet:
class Planet:
def __init__(self,name):
self.name = name
(...)
def destroy(self):
(...)
I also have a few classes that inherit from Planet and I want to make one of them unable to be destroyed (not to inherit the destroy function)
Example:
class Undestroyable(Planet):
def __init__(self,name):
super().__init__(name)
(...)
#Now it shouldn't have the destroy(self) function
So when this is run,
Undestroyable('This Planet').destroy()
it should produce an error like:
AttributeError: Undestroyable has no attribute 'destroy'

The mixin approach in other answers is nice, and probably better for most cases. But nevertheless, it spoils part of the fun - maybe obliging you to have separate planet-hierarchies - like having to live with two abstract classes each ancestor of "destroyable" and "non-destroyable".
First approach: descriptor decorator
But Python has a powerful mechanism, called the "descriptor protocol", which is used to retrieve any attribute from a class or instance - it is even used to ordinarily retrieve methods from instances - so, it is possible to customize the method retrieval in a way it checks if it "should belong" to that class, and raise attribute error otherwise.
The descriptor protocol mandates that whenever you try to get any attribute from an instance object in Python, Python will check if the attribute exists in that object's class, and if so, if the attribute itself has a method named __get__. If it has, __get__ is called (with the instance and class where it is defined as parameters) - and whatever it returns is the attribute. Python uses this to implement methods: functions in Python 3 have a __get__ method that when called, will return another callable object that, in turn, when called will insert the self parameter in a call to the original function.
So, it is possible to create a class whose __get__ method will decide whether to return a function as a bound method or not depending on the outer class been marked as so - for example, it could check an specific flag non_destrutible. This could be done by using a decorator to wrap the method with this descriptor functionality
class Muteable:
def __init__(self, flag_attr):
self.flag_attr = flag_attr
def __call__(self, func):
"""Called when the decorator is applied"""
self.func = func
return self
def __get__(self, instance, owner):
if instance and getattr(instance, self.flag_attr, False):
raise AttributeError('Objects of type {0} have no {1} method'.format(instance.__class__.__name__, self.func.__name__))
return self.func.__get__(instance, owner)
class Planet:
def __init__(self, name=""):
pass
#Muteable("undestroyable")
def destroy(self):
print("Destroyed")
class BorgWorld(Planet):
undestroyable = True
And on the interactive prompt:
In [110]: Planet().destroy()
Destroyed
In [111]: BorgWorld().destroy()
...
AttributeError: Objects of type BorgWorld have no destroy method
In [112]: BorgWorld().destroy
AttributeError: Objects of type BorgWorld have no destroy method
Perceive that unlike simply overriding the method, this approach raises the error when the attribute is retrieved - and will even make hasattr work:
In [113]: hasattr(BorgWorld(), "destroy")
Out[113]: False
Although, it won't work if one tries to retrieve the method directly from the class, instead of from an instance - in that case the instance parameter to __get__ is set to None, and we can't say from which class it was retrieved - just the owner class, where it was declared.
In [114]: BorgWorld.destroy
Out[114]: <function __main__.Planet.destroy>
Second approach: __delattr__ on the metaclass:
While writting the above, it occurred me that Pythn does have the __delattr__ special method. If the Planet class itself implements __delattr__ and we'd try to delete the destroy method on specifc derived classes, it wuld nt work: __delattr__ gards the attribute deletion of attributes in instances - and if you'd try to del the "destroy" method in an instance, it would fail anyway, since the method is in the class.
However, in Python, the class itself is an instance - of its "metaclass". That is usually type . A proper __delattr__ on the metaclass of "Planet" could make possible the "disinheitance" of the "destroy" method by issuing a `del UndestructiblePlanet.destroy" after class creation.
Again, we use the descriptor protocol to have a proper "deleted method on the subclass":
class Deleted:
def __init__(self, cls, name):
self.cls = cls.__name__
self.name = name
def __get__(self, instance, owner):
raise AttributeError("Objects of type '{0}' have no '{1}' method".format(self.cls, self.name))
class Deletable(type):
def __delattr__(cls, attr):
print("deleting from", cls)
setattr(cls, attr, Deleted(cls, attr))
class Planet(metaclass=Deletable):
def __init__(self, name=""):
pass
def destroy(self):
print("Destroyed")
class BorgWorld(Planet):
pass
del BorgWorld.destroy
And with this method, even trying to retrieve or check for the method existense on the class itself will work:
In [129]: BorgWorld.destroy
...
AttributeError: Objects of type 'BorgWorld' have no 'destroy' method
In [130]: hasattr(BorgWorld, "destroy")
Out[130]: False
metaclass with a custom __prepare__ method.
Since metaclasses allow one to customize the object that contains the class namespace, it is possible to have an object that responds to a del statement within the class body, adding a Deleted descriptor.
For the user (programmer) using this metaclass, it is almost the samething, but for the del statement been allowed into the class body itself:
class Deleted:
def __init__(self, name):
self.name = name
def __get__(self, instance, owner):
raise AttributeError("No '{0}' method on class '{1}'".format(self.name, owner.__name__))
class Deletable(type):
def __prepare__(mcls,arg):
class D(dict):
def __delitem__(self, attr):
self[attr] = Deleted(attr)
return D()
class Planet(metaclass=Deletable):
def destroy(self):
print("destroyed")
class BorgPlanet(Planet):
del destroy
(The 'deleted' descriptor is the correct form to mark a method as 'deleted' - in this method, though, it can't know the class name at class creation time)
As a class decorator:
And given the "deleted" descriptor, one could simply inform the methods to be removed as a class decorator - there is no need for a metaclass in this case:
class Deleted:
def __init__(self, cls, name):
self.cls = cls.__name__
self.name = name
def __get__(self, instance, owner):
raise AttributeError("Objects of type '{0}' have no '{1}' method".format(self.cls, self.name))
def mute(*methods):
def decorator(cls):
for method in methods:
setattr(cls, method, Deleted(cls, method))
return cls
return decorator
class Planet:
def destroy(self):
print("destroyed")
#mute('destroy')
class BorgPlanet(Planet):
pass
Modifying the __getattribute__ mechanism:
For sake of completeness - what really makes Python reach methods and attributes on the super-class is what happens inside the __getattribute__ call. n the object version of __getattribute__ is where the algorithm with the priorities for "data-descriptor, instance, class, chain of base-classes, ..." for attribute retrieval is encoded.
So, changing that for the class is an easy an unique point to get a "legitimate" attribute error, without need for the "non-existent" descritor used on the previous methods.
The problem is that object's __getattribute__ does not make use of type's one to search the attribute in the class - if it did so, just implementing the __getattribute__ on the metaclass would suffice. One have to do that on the instance to avoid instance lookp of an method, and on the metaclass to avoid metaclass look-up. A metaclass can, of course, inject the needed code:
def blocker_getattribute(target, attr, attr_base):
try:
muted = attr_base.__getattribute__(target, '__muted__')
except AttributeError:
muted = []
if attr in muted:
raise AttributeError("object {} has no attribute '{}'".format(target, attr))
return attr_base.__getattribute__(target, attr)
def instance_getattribute(self, attr):
return blocker_getattribute(self, attr, object)
class M(type):
def __init__(cls, name, bases, namespace):
cls.__getattribute__ = instance_getattribute
def __getattribute__(cls, attr):
return blocker_getattribute(cls, attr, type)
class Planet(metaclass=M):
def destroy(self):
print("destroyed")
class BorgPlanet(Planet):
__muted__=['destroy'] # or use a decorator to set this! :-)
pass

If Undestroyable is a unique (or at least unusual) case, it's probably easiest to just redefine destroy():
class Undestroyable(Planet):
# ...
def destroy(self):
cls_name = self.__class__.__name__
raise AttributeError("%s has no attribute 'destroy'" % cls_name)
From the point of view of the user of the class, this will behave as though Undestroyable.destroy() doesn't exist … unless they go poking around with hasattr(Undestroyable, 'destroy'), which is always a possibility.
If it happens more often that you want subclasses to inherit some properties and not others, the mixin approach in chepner's answer is likely to be more maintainable. You can improve it further by making Destructible an abstract base class:
from abc import abstractmethod, ABCMeta
class Destructible(metaclass=ABCMeta):
#abstractmethod
def destroy(self):
pass
class BasePlanet:
# ...
pass
class Planet(BasePlanet, Destructible):
def destroy(self):
# ...
pass
class IndestructiblePlanet(BasePlanet):
# ...
pass
This has the advantage that if you try to instantiate the abstract class Destructible, you'll get an error pointing you at the problem:
>>> Destructible()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: Can't instantiate abstract class Destructible with abstract methods destroy
… similarly if you inherit from Destructible but forget to define destroy():
class InscrutablePlanet(BasePlanet, Destructible):
pass
>>> InscrutablePlanet()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: Can't instantiate abstract class InscrutablePlanet with abstract methods destroy

Rather than remove an attribute that is inherited, only inherit destroy in the subclasses where it is applicable, via a mix-in class. This preserves the correct "is-a" semantics of inheritance.
class Destructible(object):
def destroy(self):
pass
class BasePlanet(object):
...
class Planet(BasePlanet, Destructible):
...
class IndestructiblePlanet(BasePlanet): # Does *not* inherit from Destructible
...
You can provide suitable definitions for destroy in any of Destructible, Planet, or any class that inherits from Planet.

Metaclasses and descriptor protocols are fun, but perhaps overkill. Sometimes, for raw functionality, you can't beat good ole' __slots__.
class Planet(object):
def __init__(self, name):
self.name = name
def destroy(self):
print("Boom! %s is toast!\n" % self.name)
class Undestroyable(Planet):
__slots__ = ['destroy']
def __init__(self,name):
super().__init__(name)
print()
x = Planet('Pluto') # Small, easy to destroy
y = Undestroyable('Jupiter') # Too big to fail
x.destroy()
y.destroy()
Boom! Pluto is toast!
Traceback (most recent call last):
File "planets.py", line 95, in <module>
y.destroy()
AttributeError: destroy

You cannot inherit only a portion of a class. Its all or nothing.
What you can do is to put the destroy function in a second level of the class, such you have the Planet-class without the destry-function, and then you make a DestroyablePlanet-Class where you add the destroy-function, which all the destroyable planets use.
Or you can put a flag in the construct of the Planet-Class which determines if the destroy function will be able to succeed or not, which is then checked in the destroy-function.

How to access the subclasses of a class as properties?

So I have a .py file containing a class where its subclasses can be accessed as properties. All these subclasses are defined beforehand. I also need all the subclasses to have the same ability (having their own subclasses be accessible as properties). The biggest problem I've been facing is that I don't know how to access the current class within my implementation of __getattr__(), so that'd be a good place to start.
Here's some Python+Pseudocode with what I've tried so far. I'm pretty sure it won't work since __getattr__() seems to be only working with instances of a class. If that is case, sorry, I am not as familiar with OOP in Python as I would like.
class A(object):
def __getattr__(self, name):
subclasses = [c.__name__ for c in current_class.__subclasses__()]
if name in subclasses:
return name
raise AttributeError

If I've understood your question properly, you can do what you want by using a custom metaclass that adds a classmethod to its instances. Here's an example:
class SubclassAttributes(type):
def __getattr__(cls, name): # classmethod of instances
for subclass in cls.__subclasses__():
if subclass.__name__ == name:
return subclass
else:
raise TypeError('Class {!r} has no subclass '
'named {!r}'.format(cls.__name__, name))
class Base(object):
__metaclass__ = SubclassAttributes # Python 2 metaclass syntax
#class Base(object, metaclass=SubclassAttributes): # Python 3 metaclass syntax
# """ nothing to see here """
class Derived1(Base): pass
class Derived2(Base): pass
print(Base.Derived1) # -> <class '__main__.Derived1'>
print(Base.Derived2) # -> <class '__main__.Derived2'>
print(Base.Derived3) # -> TypeError: Class 'Base' has no subclass named 'Derived3'
For something that works in both Python 2 and 3, define the class as shown below. Derives Base from a class that has SubclassAttributes as its metaclass. The is similar to what the six module's with_metaclass() function does:
class Base(type.__new__(type('TemporaryMeta', (SubclassAttributes,), {}),
'TemporaryClass', (), {})): pass

class A(object):
def __getattr__(self, key):
for subclass in self.__class__.__subclasses__():
if (subclass.__name__ == key):
return subclass
raise AttributeError, key
Out of curiosity, what is this designed to be used for?

>>> class A(object):
... pass
...
>>> foo = A()
>>> foo.__class__
<class '__main__.A'>