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Does the final decorator help in preventing method overriding?

I am trying to create a final method in my class, where I want that it cannot be overridden by any sub-class, just like when creating a final class using final decorator which cannot be inherited.
from final_class import final
class Dummy:
def show(self):
print("show id running from dummy")
#final
def display(self):
print("display from dummy")
class Demo(Dummy):
def show(self):
print("show from demo")
def display(self):
print("display from demo")
d = Demo()
d.display()
I think we should get an error when accessing the display method from Demo, but when I run the program it gives "display from demo".
So what am I missing? I have checked final annotation and decorators in python3.8 but it talks about typechecking in typing packages while I was trying it from the final_class package.

As seem in the comments, the 3rd party library final_class.final is one thing: a class decorator that will prevent, at runtime, that a class is further inherited, anf typing.final which ships with Python, and is intended to decorate both classes and methods, but which has no enforcing behavior during program execution - it will, instead, make any compliant static analysis tool to raise an error in the type-checking stage.
It is, due to Python flexibility and dynamism, possible to create a final decorator for methods that will be enforced at runtime: i.e. whenever a subclass is created overriding a method marked as final in the inheritance chain, a RuntimeError, or other custom error can be raised.
The idea is that whenever a new class is created, both methods on the metaclass and the __init_subclass__ method of the bases is called - so, if one wants to create a custom metaclass or custom base-class to be used along with such a #final decorator, it should be something more or less straightforward.
What would be less straightforward would be such a decorator that would work regardless of an specific base class or custom-metaclass - and this also can be done: by injecting in the class being constructed an __init_subclass__ method which will perform a check of violation of the final clause.
The complicated part is to co-exist with eventual pre-existing __init_subclass__ methods which also need to be called, either on the same class or in any superclass, as well as emulate the working of super(), since we are creating a method outside the class body. The decorator code can inspect the context from which its called and inject a __init_subclass__ there, taking some care:
import sys
def final(method):
f = sys._getframe().f_back
_init_subclass_meth = "super"
def __init_subclass__(cls, *args, **kw):
# all of these are readonly, so nonlocal is optional:
# nonlocal final_methods, _init_subclass_meth, _original_init_subclass, __init_subclass__
# In a normal __init_subclass__, one can know about the class in which
# a method is declared, and call super(), via the `__class__`
# magic variable. But that won't work for a method defined
# outside the class and inkected in it.
# the line bellow should retrieve the equivalent to __class__
current_class = next(supercls for supercls in cls.__mro__ if getattr(supercls.__dict__.get("__init_subclass__", None), "__func__", None) is __init_subclass__)
for meth_name in cls.__dict__:
if meth_name in final_methods:
raise RuntimeError(f"Final method {meth_name} is redeclared in subclass {cls.__name__} from {current_class.__name__}")
if _init_subclass_meth == "wrap":
return _original_init_subclass(cls, *args, **kwd)
return super(current_class, None).__init_subclass__(*args, **kw)
__init_subclass__._final_mark = True
if "__init_subclass__" in f.f_locals and not getattr(f.f_locals["__init_subclass__"], "_final_mark", False):
_init_subclass_meth = "wrap"
_original_init_subclass = f.f_locals["__init_subclass__"]
# locals assignment: will work in this case because the caller context
# is a class body, inside which `f_locals` refers usually to a
# plain dict (unless a custom metaclass changed it).
# This normally would not work (= no effect) in an ordinary frame,
# represnting a plain function or method in execution:
f.f_locals["__init_subclass__"] = __init_subclass__
final_methods = f.f_locals.setdefault("_final_methods", set())
final_methods.add(method.__name__)
return method
class A:
#final
def b(self):
print("final b")
And this will raise an error:
class B(A):
def b(self):
# RuntimeError expected
...

Enforce/Define python classes with only the specified attributes [duplicate]

I have two classes that are supposed to implement the same test cases for two independent libraries (let's call them LibA and LibB). So far I define the test methods to be implemented in an abstract base class which ensures that both test classes implement all desired tests:
from abc import ABC, abstractmethod
class MyTests(ABC):
#abstractmethod
def test_foo(self):
pass
class TestsA(MyTests):
def test_foo(self):
pass
class TestsB(MyTests):
def test_foo(self):
pass
This works as expected, but what may still happen is that someone working on LibB accidentally adds a test_bar() method to TestB instead of the base class. The missing test_bar() in the TestA class would go unnoticed in that case.
Is there a way to prohibit the addition of new methods to an (abstract) base class? The objective is to force the addition of new methods to happen in the base class and thus force the implementation of new methods in all derived classes.

Yes. It can be done through a metaclass, or from Python 3.6 onwards, with a check in __init_subclass__ of the baseclass.
__init_sublass__ is a special method called by the language each time a subclass is instantiated. So it can check if the new class have any method that is not present in any of the superclasses and raise a TypeError when the subclass is declared. (__init_subclass__ is converted to a classmethod automatically)
class Base(ABC):
...
def __init_subclass__(cls, *args, **kw):
super().__init_subclass__(*args, **kw)
# By inspecting `cls.__dict__` we pick all methods declared directly on the class
for name, attr in cls.__dict__.items():
attr = getattr(cls, name)
if not callable(attr):
continue
for superclass in cls.__mro__[1:]:
if name in dir(superclass):
break
else:
# method not found in superclasses:
raise TypeError(f"Method {name} defined in {cls.__name__} does not exist in superclasses")
Note that unlike the TypeError raised by non-implemented abstractmethods, this error is raised at class declaration time, not class instantiation time. If the later is desired, you have to use a metaclass and move the check to its __call__ method - however that complicates things, as if one method is created in an intermediate class, that was never instantiated, it won't raise when the method is available in the leaf subclass. I guess what you need is more along the code above.

What are the differences between a `classmethod` and a metaclass method?

In Python, I can create a class method using the #classmethod decorator:
>>> class C:
... #classmethod
... def f(cls):
... print(f'f called with cls={cls}')
...
>>> C.f()
f called with cls=<class '__main__.C'>
Alternatively, I can use a normal (instance) method on a metaclass:
>>> class M(type):
... def f(cls):
... print(f'f called with cls={cls}')
...
>>> class C(metaclass=M):
... pass
...
>>> C.f()
f called with cls=<class '__main__.C'>
As shown by the output of C.f(), these two approaches provide similar functionality.
What are the differences between using #classmethod and using a normal method on a metaclass?

As classes are instances of a metaclass, it is not unexpected that an "instance method" on the metaclass will behave like a classmethod.
However, yes, there are differences - and some of them are more than semantic:
The most important difference is that a method in the metaclass is not "visible" from a class instance. That happens because the attribute lookup in Python (in a simplified way - descriptors may take precedence) search for an attribute in the instance - if it is not present in the instance, Python then looks in that instance's class, and then the search continues on the superclasses of the class, but not on the classes of the class. The Python stdlib make use of this feature in the abc.ABCMeta.register method.
That feature can be used for good, as methods related with the class themselves are free to be re-used as instance attributes without any conflict (but a method would still conflict).
Another difference, though obvious, is that a method declared in the metaclass can be available in several classes, not otherwise related - if you have different class hierarchies, not related at all in what they deal with, but want some common functionality for all classes, you'd have to come up with a mixin class, that would have to be included as base in both hierarchies (say for including all classes in an application registry). (NB. the mixin may sometimes be a better call than a metaclass)
A classmethod is a specialized "classmethod" object, while a method in the metaclass is an ordinary function.
So, it happens that the mechanism that classmethods use is the "descriptor protocol". While normal functions feature a __get__ method that will insert the self argument when they are retrieved from an instance, and leave that argument empty when retrieved from a class, a classmethod object have a different __get__, that will insert the class itself (the "owner") as the first parameter in both situations.
This makes no practical differences most of the time, but if you want access to the method as a function, for purposes of adding dynamically adding decorator to it, or any other, for a method in the metaclass meta.method retrieves the function, ready to be used, while you have to use cls.my_classmethod.__func__ to retrieve it from a classmethod (and then you have to create another classmethod object and assign it back, if you do some wrapping).
Basically, these are the 2 examples:
class M1(type):
def clsmethod1(cls):
pass
class CLS1(metaclass=M1):
pass
def runtime_wrap(cls, method_name, wrapper):
mcls = type(cls)
setattr(mcls, method_name, wrapper(getatttr(mcls, method_name)))
def wrapper(classmethod):
def new_method(cls):
print("wrapper called")
return classmethod(cls)
return new_method
runtime_wrap(cls1, "clsmethod1", wrapper)
class CLS2:
#classmethod
def classmethod2(cls):
pass
def runtime_wrap2(cls, method_name, wrapper):
setattr(cls, method_name, classmethod(
wrapper(getatttr(cls, method_name).__func__)
)
)
runtime_wrap2(cls1, "clsmethod1", wrapper)
In other words: apart from the important difference that a method defined in the metaclass is visible from the instance and a classmethod object do not, the other differences, at runtime will seem obscure and meaningless - but that happens because the language does not need to go out of its way with special rules for classmethods: Both ways of declaring a classmethod are possible, as a consequence from the language design - one, for the fact that a class is itself an object, and another, as a possibility among many, of the use of the descriptor protocol which allows one to specialize attribute access in an instance and in a class:
The classmethod builtin is defined in native code, but it could just be coded in pure python and would work in the exact same way. The 5 line class bellow can be used as a classmethod decorator with no runtime differences to the built-in #classmethod" at all (though distinguishable through introspection such as calls toisinstance, and evenrepr` of course):
class myclassmethod:
def __init__(self, func):
self.__func__ = func
def __get__(self, instance, owner):
return lambda *args, **kw: self.__func__(owner, *args, **kw)
And, beyond methods, it is interesting to keep in mind that specialized attributes such as a #property on the metaclass will work as specialized class attributes, just the same, with no surprising behavior at all.

When you phrase it like you did in the question, the #classmethod and metaclasses may look similar but they have rather different purposes. The class that is injected in the #classmethod's argument is usually used for constructing an instance (i.e. an alternative constructor). On the other hand, the metaclasses are usually used to modify the class itself (e.g. like what Django does with its models DSL).
That is not to say that you can't modify the class inside a classmethod. But then the question becomes why didn't you define the class in the way you want to modify it in the first place? If not, it might suggest a refactor to use multiple classes.
Let's expand the first example a bit.
class C:
#classmethod
def f(cls):
print(f'f called with cls={cls}')
Borrowing from the Python docs, the above will expand to something like the following:
class ClassMethod(object):
"Emulate PyClassMethod_Type() in Objects/funcobject.c"
def __init__(self, f):
self.f = f
def __get__(self, obj, klass=None):
if klass is None:
klass = type(obj)
def newfunc(*args):
return self.f(klass, *args)
return newfunc
class C:
def f(cls):
print(f'f called with cls={cls}')
f = ClassMethod(f)
Note how __get__ can take either an instance or the class (or both), and thus you can do both C.f and C().f. This is unlike the metaclass example you give which will throw an AttributeError for C().f.
Moreover, in the metaclass example, f does not exist in C.__dict__. When looking up the attribute f with C.f, the interpreter looks at C.__dict__ and then after failing to find, looks at type(C).__dict__ (which is M.__dict__). This may matter if you want the flexibility to override f in C, although I doubt this will ever be of practical use.

In your example, the difference would be in some other classes that will have M set as their metaclass.
class M(type):
def f(cls):
pass
class C(metaclass=M):
pass
class C2(metaclass=M):
pass
C.f()
C2.f()
class M(type):
pass
class C(metaclass=M):
#classmethod
def f(cls):
pass
class C2(metaclass=M):
pass
C.f()
# C2 does not have 'f'
Here is more on metaclasses
What are some (concrete) use-cases for metaclasses?

Both #classmethod and Metaclass are different.
Everything in python is an object. Every thing means every thing.
What is Metaclass ?
As said every thing is an object. Classes are also objects in fact classes are instances of other mysterious objects formally called as meta-classes. Default metaclass in python is "type" if not specified
By default all classes defined are instances of type.
Classes are instances of Meta-Classes
Few important points are to understand metioned behaviour
As classes are instances of meta classes.
Like every instantiated object, like objects(instances) get their attributes from class. Class will get it's attributes from Meta-Class
Consider Following Code
class Meta(type):
def foo(self):
print(f'foo is called self={self}')
print('{} is instance of {}: {}'.format(self, Meta, isinstance(self, Meta)))
class C(metaclass=Meta):
pass
C.foo()
Where,
class C is instance of class Meta
"class C" is class object which is instance of "class Meta"
Like any other object(instance) "class C" has access it's attributes/methods defined in it's class "class Meta"
So, decoding "C.foo()" . "C" is instance of "Meta" and "foo" is method calling through instance of "Meta" which is "C".
First argument of method "foo" is reference to instance not class unlike "classmethod"
We can verify as if "class C" is instance of "Class Meta
isinstance(C, Meta)
What is classmethod?
Python methods are said to be bound. As python imposes the restriction that method has to be invoked with instance only.
Sometimes we might want to invoke methods directly through class without any instance (much like static members in java) with out having to create any instance.By default instance is required to call method. As a workaround python provides built-in function classmethod to bind given method to class instead of instance.
As class methods are bound to class. It takes at least one argument which is reference to class itself instead of instance (self)
if built-in function/decorator classmethod is used. First argument
will be reference to class instead of instance
class ClassMethodDemo:
#classmethod
def foo(cls):
print(f'cls is ClassMethodDemo: {cls is ClassMethodDemo}')
As we have used "classmethod" we call method "foo" without creating any instance as follows
ClassMethodDemo.foo()
Above method call will return True. Since first argument cls is indeed reference to "ClassMethodDemo"
Summary:
Classmethod's receive first argument which is "a reference to class(traditionally referred as cls) itself"
Methods of meta-classes are not classmethods. Methods of Meta-classes receive first argument which is "a reference to instance(traditionally referred as self) not class"

Implementing an abstract class with a class method doesn't raise an exception

I am attempting to implement a method as both an abstract method and as a class method but it doesn't feel like any of the benefits of an abstract class are gained when doing so.
For example:
from abc import ABC, abstractmethod
class BasePipeline(ABC):
#classmethod
#abstractmethod
def consume_frame(cls):
pass
#abstractmethod
def consume_frame_two(self):
pass
class AnotherSubclass(BasePipeline):
#classmethod
def does_nothing(cls):
a = 1 + 1
# Call it.
AnotherSubclass.consume_frame()
This doesn't raise any exception and does not error out. I'd expect for it to say something along the lines of: consume_frame_two is not implemented and consume_frame is not implemented.
Not sure what the intended behavior is or if I'm just doing something wrong. I'd like for AnotherSubclass.consume_frame() to raise an exception if it isn't properly implemented as a class method.

Your code doesn't try to create an instance of the AnotherSubclass class. All it does is access the implementation of a classmethod that is marked as abstract. Python's ABC abstract classes are not intended to prevent that kind of access.
The abc module is intended to help you define a protocol or interface, a base class that sets expectations as to what attributes must be present on concrete objects that should be considered the same.
To that end, all that you can do with an ABC subclass is prevent instances to be created of any class in the class hierarchy that has at least one abstractmethod or abstractproperty attribute. From the #abc.abstractmethod() documentation:
A class that has a metaclass derived from ABCMeta cannot be instantiated unless all of its abstract methods and properties are overridden.
Any abstractmethod-decorated method can still be called; there is no mechanism to prevent this and it is actually a specific goal of the module that concrete implementations can use super().name() to access the implementation of an abstractmethod object. From the same source:
The abstract methods can be called using any of the normal ‘super’ call mechanisms
and
Note: Unlike Java abstract methods, these abstract methods may have an implementation. This implementation can be called via the super() mechanism from the class that overrides it. This could be useful as an end-point for a super-call in a framework that uses cooperative multiple-inheritance.
Any other attributes of the class can be used just the same as on other classes, including classmethod objects.
Under the covers, each ABCMeta metaclass gives each class you create with it a __abstractmethods__ attribute, which is a frozenset object with the names of any attribute on the class that has the __isabstractmethod__ attribute set to True, subclasses only have to use the same name as a parent abstract method object, setting it to an attribute that doesn't have __isabstractmethod__ set to true to remove that name from the set for that class. Python will then raise an exception when you try to create an instance of a class whose __abstractmethods__ is not empty.
If you need to lock down your class definitions further, then you'll have to come up with our own metaclass or other mechanism to implement those rules. For example, you could wrap classobject attributes in your own descriptor object that prevents calling a classmethod bound to a class with a non-empty __abstractmethods__ attribute.

Can one declare an abstract exception in Python?

I would like to declare a hierarchy of user-defined exceptions in Python. However, I would like my top-level user-defined class (TransactionException) to be abstract. That is, I intend TransactionException to specify methods that its subclasses are required to define. However, TransactionException should never be instantiated or raised.
I have the following code:
from abc import ABCMeta, abstractmethod
class TransactionException(Exception):
__metaclass__ = ABCMeta
#abstractmethod
def displayErrorMessage(self):
pass
However, the above code allows me to instantiate TransactionException...
a = TransactionException()
In this case a is meaningless, and should instead draw an exception. The following code removes the fact that TransactionException is a subclass of Exception...
from abc import ABCMeta, abstractmethod
class TransactionException():
__metaclass__ = ABCMeta
#abstractmethod
def displayErrorMessage(self):
pass
This code properly prohibits instantiation but now I cannot raise a subclass of TransactionException because it's not an Exception any longer.
Can one define an abstract exception in Python? If so, how? If not, why not?
NOTE: I'm using Python 2.7, but will happily accept an answer for Python 2.x or Python 3.x.

There's a great answer on this topic by Alex Martelli here. In essence, it comes down how the object initializers (__init__) of the various base classes (object, list, and, I presume, Exception) behave when abstract methods are present.
When an abstract class inherits from object (which is the default, if no other base class is given), its __init__ method is set to that of object's, which performs the heavy-lifting in checking if all abstract methods have been implemented.
If the abstract class inherits from a different base class, it will get that class' __init__ method. Other classes, such as list and Exception, it seems, do not check for abstract method implementation, which is why instantiating them is allowed.
The other answer provides a suggested workaround for this. Of course, another option that you have is simply to accept that the abstract class will be instantiable, and try to discourage it.

class TransactionException(Exception):
def __init__(self, *args, **kwargs):
raise NotImplementedError('you should not be raising this')
class EverythingLostException(TransactionException):
def __init__(self, msg):
super(TransactionException, self).__init__(msg)
try:
raise EverythingLostException('we are doomed!')
except TransactionException:
print 'check'
try:
raise TransactionException('we are doomed!')
except TransactionException:
print 'oops'

My implementation for an abstract exception class, in which the children of the class work out of the box.
class TransactionException(Exception):
def __init__(self):
self._check_abstract_initialization(self)
#staticmethod
def _check_abstract_initialization(self):
if type(self) == TransactionException:
raise NotImplementedError("TransactionException should not be instantiated directly")
class AnotherException(TransactionException):
pass
TransactionException() # NotImplementedError: TransactionException should not be instantiated directly
AnotherException # passes

Here's a helper function that can be used in such scenario:
def validate_abstract_methods(obj):
abstract_methods = []
for name in dir(obj):
value = getattr(obj, name, None)
if value is not None and getattr(value, '__isabstractmethod__', False):
abstract_methods.append(name)
if abstract_methods:
abstract_methods.sort()
raise TypeError(f"Can't instantiate abstract class {obj.__class__.__name__} with abstract methods {', '.join(abstract_methods)}")
This function roughly does the same thing as abc.ABC class - you just need to call it from your class' __init__ method.