When one thinks of ways of customizing classes at creation time, people probably typically think of metaclasses and class decorators. Metaclasses are at typically viewed as the beginning of class creation while class decorators are at the end. But what you may not know is that there are two other steps in class creation that you can tweak: __prepare__() and __init_subclass__() (added in Python 3.0 and 3.6, respectively).

The __prepare__() hook is used to specify the object used for the class' namespace during construction (the object gets copied into a dict in the end for final storage into __dict__ ). The method is specified on a metaclass and called before __new__() . Historically the __prepare__() method has been used to return OrderedDict so that the definition order of things in a class can be known later on. But since the returned object is used as the class' namespace you can also use it to inject objects to use in your class' definition.

To take an idea from David Beazley, you can abuse __prepare__() so you can define an ABC so that abstractmethod is implicitly available in the class definition.

import abc class DaABC(abc.ABCMeta): @classmethod def __prepare__(metacls, name, bases, **kwargs): return {"abstractmethod": abc.abstractmethod}

Using this metaclass gives you access to abstractmethod without having to get it from abc .

class Foo(metaclass=DaABC): # Notice not `abc.abstractmethod`. @abstractmethod def meth(self): pass

This works because the way classes are created is essentially by taking the class' body and passing it to exec() with the result of calling __prepare__() as the locals.

Another way to tweak class creation is __init_subclass__() . The method gets called when the defining class gets subclassed. It's passed both the subclass and any keyword arguments provided to the class definition line.

To help show a way to use this, I realized that you could abuse variable type annotations to make a "scary" version of Hynek Schlawack's attrs project. Basically the following class automatically defines an __init__() and (optionally) the __repr__() for a class based on variable type annotations.

class ScareHynek: def __init_subclass__(cls, **kwargs): super().__init_subclass__() attrs = tuple(cls.__annotations__.keys()) def __init__(self, *args, **kwargs): # Skimping on the argument-checking because I'm lazy. if len(args) > len(attrs): raise TypeError("too many positional arguments") for attr, val in zip(attrs, args): setattr(self, attr, val) for attr, val in kwargs.items(): if attr not in attrs: raise TypeError("got an unexpected keyword argument {!r}") setattr(self, attr, val) cls.__init__ = __init__ if kwargs.get("repr", True): repr_format = "<" + ", ".join(f"{attr}={{{attr}!r}}" for attr in attrs) + ">" def __repr__(self): all_attrs = self.__class__.__dict__.copy() all_attrs.update(self.__dict__) return repr_format.format_map(all_attrs) cls.__repr__ = __repr__

This then lets you create simple Python objects that you may have created using types.SimpleNamespace instead (aside: please don't abuse collections.namedtuple to make a simple Python object; the class is meant to help porting APIs that return a tuple to a more object-oriented one, so starting with namedtuple means you end up leaking a tuple API that you probably didn't want to begin with).

class Simple(ScareHynek): question: str answer: int = 42 ins = Simple(question="Ultimate Question of Life, The Universe, and Everything") print(repr(ins)) # Prints "# <question='Ultimate Question of Life, The Universe, and Everything', answer=42>"

You can also use keyword arguments to the class definition to skip the __repr__() definition.

class Plain(ScareHynek, repr=False): x: int ins = Plain(42) print(repr(ins)) # Prints "<class_creation.Plain object at 0x100f91198>"

As with all things that tweak class creation, you must be very careful to not abuse this stuff. Adjusting how classes are created can be very difficult to debug and so should only be used when you have a really legitimate use-case. But this stuff is worth knowing about in case you run into code that uses it or you have a real need for it when there are no other reasonable options.