Before abc was introduced you would see this frequently.

class Base(object):
    def go(self):
        raise NotImplementedError("Please Implement this method")


class Specialized(Base):
    def go(self):
        print "Consider me implemented"

Python actually does have abstract classes with abstact methods:

>>> import abc
>>> 
>>> class IFoo(object):
...     __metaclass__ = abc.ABCMeta
...     
...     @abc.abstractmethod
...     def foo(self):
...         pass
... 
>>> foo = IFoo()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: Cant instantiate abstract class IFoo with abstract methods foo
>>> class FooDerived(IFoo):
...     pass
... 
>>> foo = FooDerived()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: Cant instantiate abstract class FooDerived with abstract methods foo
>>> class FooImplements(FooDerived):
...     def foo(self):
...         print "foo'ed"
... 
>>> foo = FooImplements()
>>> foo.foo()
foo'ed
>>> 

On the other hand, the fundamental question of "is this pythonic" is a bit harder to say. If your intent is to provide the abstract base class so that you can later check to make sure that values inherit from it, then no, that's not particularly pythonic, even though it's possible to make arbitrary types abstract subclasses of your baseclass. On the other hand, it's perfectly fine to provide an abstract baseclass that implements some functionality based upon the implementation provided in concrete subclasses. For example, collections.Sequence and collections.Mapping do just this for list like and dict like classes; subclasses can provide __getitem__ and can get __contains__ and others for free.

For certain, you should never use assert() except to document the expectations of code; If it's actually possible for the assert to fail, you shouldn't be using an assert. Optimized python (python -O script.py) does not check assertions.

Edit: more exposition:

If you are checking the type of a value:

def foo(bar):
    if not isinstance(bar, AbstractBaz):
        raise ValueError, ("bar must be an instance of AbstractBaz, "
                           "got %s" % type(bar))

If for some reason you can't use @abstractmethod, but still want that effect, you should raise NotImplementedError. You might want to do this because you actually do want instances of that class, some of which might not need to implement optional functionality. You still should account for the possibility that the function was called through super(). To a first approximation, that might look like this.

class Foo(object):
    def bar(self, baz):
        if self.bar.im_func == Foo.bar.im_func:
            raise NotImplementedError, "Subclasses must implement bar"

It's worse than you think. Abstract methods are tracked by name only, so you don't even have to make quack a method in order to instantiate the child class.

class SurrealDuck(Quacker):
    quack = 3

d = SurrealDuck()
print d.quack   # Shows 3

There is nothing in the system that enforces that quack is even a callable object, let alone one whose arguments match the abstract method's original. At best, you could subclass ABCMeta and add code yourself to compare type signatures in the child to the originals in the parent, but this would be nontrivial to implement.

(Currently, marking something as "abstract" essentially just adds the name to a frozen set attribute in the parent (Quacker.__abstractmethods__). Making a class instantiable is as simple as setting this attribute to an empty iterable, which is useful for testing.)

You can't do what you want with just ABCMeta. ABC enforcement doesn't do any type checking, only the presence of an attribute with the correct name is enforced.

Take for example:

>>> from abc import ABCMeta, abstractmethod, abstractproperty
>>> class Abstract(object):
...     __metaclass__ = ABCMeta
...     @abstractmethod
...     def foo(self): pass
...     @abstractproperty
...     def bar(self): pass
... 
>>> class Concrete(Abstract):
...     foo = 'bar'
...     bar = 'baz'
... 
>>> Concrete()
<__main__.Concrete object at 0x104b4df90>

I was able to construct Concrete() even though both foo and bar are simple attributes.

The ABCMeta metaclass only tracks how many objects are left with the __isabstractmethod__ attribute being true; when creating a class from the metaclass (ABCMeta.__new__ is called) the cls.__abstractmethods__ attribute is then set to a frozenset object with all the names that are still abstract.

type.__new__ then tests for that frozenset and throws a TypeError if you try to create an instance.

You'd have to produce your own __new__ method here; subclass ABCMeta and add type checking in a new __new__ method. That method should look for __abstractmethods__ sets on the base classes, find the corresponding objects with the __isabstractmethod__ attribute in the MRO, then does typechecking on the current class attributes.

This'd mean that you'd throw the exception when defining the class, not an instance, however. For that to work you'd add a __call__ method to your ABCMeta subclass and have that throw the exception based on information gathered by your own __new__ method about what types were wrong; a similar two-stage process as what ABCMeta and type.__new__ do at the moment. Alternatively, update the __abstractmethods__ set on the class to add any names that were implemented but with the wrong type and leave it to type.__new__ to throw the exception.

The following implementation takes that last tack; add names back to __abstractmethods__ if the implemented type doesn't match (using a mapping):

from types import FunctionType

class ABCMetaTypeCheck(ABCMeta):
    _typemap = {  # map abstract type to expected implementation type
        abstractproperty: property,
        abstractstatic: staticmethod,
        # abstractmethods return function objects
        FunctionType: FunctionType,
    }
    def __new__(mcls, name, bases, namespace):
        cls = super(ABCMetaTypeCheck, mcls).__new__(mcls, name, bases, namespace)
        wrong_type = set()
        seen = set()
        abstractmethods = cls.__abstractmethods__
        for base in bases:
            for name in getattr(base, "__abstractmethods__", set()):
                if name in seen or name in abstractmethods:
                    continue  # still abstract or later overridden
                value = base.__dict__.get(name)  # bypass descriptors
                if getattr(value, "__isabstractmethod__", False):
                    seen.add(name)
                    expected = mcls._typemap[type(value)]
                    if not isinstance(namespace[name], expected):
                        wrong_type.add(name)
        if wrong_type:
            cls.__abstractmethods__ = abstractmethods | frozenset(wrong_type)
        return cls

With this metaclass you get your expected output:

>>> class Abstract(object):
...     __metaclass__ = ABCMetaTypeCheck
...     @abstractmethod
...     def foo(self): pass
...     @abstractproperty
...     def bar(self): pass
...     @abstractstatic
...     def baz(): pass
... 
>>> class ConcreteWrong(Abstract):
...     foo = 'bar'
...     bar = 'baz'
...     baz = 'spam'
... 
>>> ConcreteWrong()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: Can't instantiate abstract class ConcreteWrong with abstract methods bar, baz, foo
>>> 
>>> class ConcreteCorrect(Abstract):
...     def foo(self): return 'bar'
...     @property
...     def bar(self): return 'baz'
...     @staticmethod
...     def baz(): return  'spam'
... 
>>> ConcreteCorrect()
<__main__.ConcreteCorrect object at 0x104ce1d10>