abc — Abstract Base Classes¶

Source code: Lib/abc.py

This module provides the infrastructure for defining abstract base classes (ABCs) in Python, as outlined in PEP 3119; see the PEP for why this was added to Python. (See also PEP 3141 and the numbers module regarding a type hierarchy for numbers based on ABCs.)

The collections module has some concrete classes that derive from ABCs; these can, of course, be further derived. In addition, the collections.abc submodule has some ABCs that can be used to test whether a class or instance provides a particular interface, for example, if it is hashable or if it is a mapping.

This module provides the metaclass ABCMeta for defining ABCs and a helper class ABC to alternatively define ABCs through inheritance:

class abc.ABC¶

A helper class that has ABCMeta as its metaclass. With this class, an abstract base class can be created by simply deriving from ABC avoiding sometimes confusing metaclass usage, for example:

from abc import ABC

class MyABC(ABC):
    pass

Note that the type of ABC is still ABCMeta, therefore inheriting from ABC requires the usual precautions regarding metaclass usage, as multiple inheritance may lead to metaclass conflicts. One may also define an abstract base class by passing the metaclass keyword and using ABCMeta directly, for example:

from abc import ABCMeta

class MyABC(metaclass=ABCMeta):
    pass

New in version 3.4.

class abc.ABCMeta¶

Metaclass for defining Abstract Base Classes (ABCs).

Use this metaclass to create an ABC. An ABC can be subclassed directly, and then acts as a mix-in class. You can also register unrelated concrete classes (even built-in classes) and unrelated ABCs as “virtual subclasses” – these and their descendants will be considered subclasses of the registering ABC by the built-in issubclass() function, but the registering ABC won’t show up in their MRO (Method Resolution Order) nor will method implementations defined by the registering ABC be callable (not even via super()). 1

Classes created with a metaclass of ABCMeta have the following method:

register(subclass)¶

Register subclass as a “virtual subclass” of this ABC. For example:

from abc import ABC

class MyABC(ABC):
    pass

MyABC.register(tuple)

assert issubclass(tuple, MyABC)
assert isinstance((), MyABC)

Changed in version 3.3: Returns the registered subclass, to allow usage as a class decorator.

Changed in version 3.4: To detect calls to register(), you can use the get_cache_token() function.

You can also override this method in an abstract base class:

__subclasshook__(subclass)¶

(Must be defined as a class method.)

Check whether subclass is considered a subclass of this ABC. This means that you can customize the behavior of issubclass further without the need to call register() on every class you want to consider a subclass of the ABC. (This class method is called from the __subclasscheck__() method of the ABC.)

This method should return True, False or NotImplemented. If it returns True, the subclass is considered a subclass of this ABC. If it returns False, the subclass is not considered a subclass of this ABC, even if it would normally be one. If it returns NotImplemented, the subclass check is continued with the usual mechanism.

For a demonstration of these concepts, look at this example ABC definition:

class Foo:
    def __getitem__(self, index):
        ...
    def __len__(self):
        ...
    def get_iterator(self):
        return iter(self)

class MyIterable(ABC):

    @abstractmethod
    def __iter__(self):
        while False:
            yield None

    def get_iterator(self):
        return self.__iter__()

    @classmethod
    def __subclasshook__(cls, C):
        if cls is MyIterable:
            if any("__iter__" in B.__dict__ for B in C.__mro__):
                return True
        return NotImplemented

MyIterable.register(Foo)

The ABC MyIterable defines the standard iterable method, __iter__(), as an abstract method. The implementation given here can still be called from subclasses. The get_iterator() method is also part of the MyIterable abstract base class, but it does not have to be overridden in non-abstract derived classes.

The __subclasshook__() class method defined here says that any class that has an __iter__() method in its __dict__ (or in that of one of its base classes, accessed via the __mro__ list) is considered a MyIterable too.

Finally, the last line makes Foo a virtual subclass of MyIterable, even though it does not define an __iter__() method (it uses the old-style iterable protocol, defined in terms of __len__() and __getitem__()). Note that this will not make get_iterator available as a method of Foo, so it is provided separately.

The abc module also provides the following decorator:

@abc.abstractmethod¶

A decorator indicating abstract methods.

Using this decorator requires that the class’s metaclass is ABCMeta or is derived from it. A class that has a metaclass derived from ABCMeta cannot be instantiated unless all of its abstract methods and properties are overridden. The abstract methods can be called using any of the normal ‘super’ call mechanisms. abstractmethod() may be used to declare abstract methods for properties and descriptors.

Dynamically adding abstract methods to a class, or attempting to modify the abstraction status of a method or class once it is created, are only supported using the update_abstractmethods() function. The abstractmethod() only affects subclasses derived using regular inheritance; “virtual subclasses” registered with the ABC’s register() method are not affected.

When abstractmethod() is applied in combination with other method descriptors, it should be applied as the innermost decorator, as shown in the following usage examples:

class C(ABC):
    @abstractmethod
    def my_abstract_method(self, arg1):
        ...
    @classmethod
    @abstractmethod
    def my_abstract_classmethod(cls, arg2):
        ...
    @staticmethod
    @abstractmethod
    def my_abstract_staticmethod(arg3):
        ...

    @property
    @abstractmethod
    def my_abstract_property(self):
        ...
    @my_abstract_property.setter
    @abstractmethod
    def my_abstract_property(self, val):
        ...

    @abstractmethod
    def _get_x(self):
        ...
    @abstractmethod
    def _set_x(self, val):
        ...
    x = property(_get_x, _set_x)

In order to correctly interoperate with the abstract base class machinery, the descriptor must identify itself as abstract using __isabstractmethod__. In general, this attribute should be True if any of the methods used to compose the descriptor are abstract. For example, Python’s built-in property does the equivalent of:

class Descriptor:
    ...
    @property
    def __isabstractmethod__(self):
        return any(getattr(f, '__isabstractmethod__', False) for
                   f in (self._fget, self._fset, self._fdel))

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.

The abc module also supports the following legacy decorators:

@abc.abstractclassmethod¶

New in version 3.2.

Deprecated since version 3.3: It is now possible to use classmethod with abstractmethod(), making this decorator redundant.

A subclass of the built-in classmethod(), indicating an abstract classmethod. Otherwise it is similar to abstractmethod().

This special case is deprecated, as the classmethod() decorator is now correctly identified as abstract when applied to an abstract method:

class C(ABC):
    @classmethod
    @abstractmethod
    def my_abstract_classmethod(cls, arg):
        ...

@abc.abstractstaticmethod¶

New in version 3.2.

Deprecated since version 3.3: It is now possible to use staticmethod with abstractmethod(), making this decorator redundant.

A subclass of the built-in staticmethod(), indicating an abstract staticmethod. Otherwise it is similar to abstractmethod().

This special case is deprecated, as the staticmethod() decorator is now correctly identified as abstract when applied to an abstract method:

class C(ABC):
    @staticmethod
    @abstractmethod
    def my_abstract_staticmethod(arg):
        ...

@abc.abstractproperty¶

Deprecated since version 3.3: It is now possible to use property, property.getter(), property.setter() and property.deleter() with abstractmethod(), making this decorator redundant.

A subclass of the built-in property(), indicating an abstract property.

This special case is deprecated, as the property() decorator is now correctly identified as abstract when applied to an abstract method:

class C(ABC):
    @property
    @abstractmethod
    def my_abstract_property(self):
        ...

The above example defines a read-only property; you can also define a read-write abstract property by appropriately marking one or more of the underlying methods as abstract:

class C(ABC):
    @property
    def x(self):
        ...

    @x.setter
    @abstractmethod
    def x(self, val):
        ...

If only some components are abstract, only those components need to be updated to create a concrete property in a subclass:

class D(C):
    @C.x.setter
    def x(self, val):
        ...

The abc module also provides the following functions:

abc.get_cache_token()¶

Returns the current abstract base class cache token.

The token is an opaque object (that supports equality testing) identifying the current version of the abstract base class cache for virtual subclasses. The token changes with every call to ABCMeta.register() on any ABC.

New in version 3.4.

abc.update_abstractmethods(cls)¶

A function to recalculate an abstract class’s abstraction status. This function should be called if a class’s abstract methods have been implemented or changed after it was created. Usually, this function should be called from within a class decorator.

Returns cls, to allow usage as a class decorator.

If cls is not an instance of ABCMeta, does nothing.

Note

This function assumes that cls’s superclasses are already updated. It does not update any subclasses.

New in version 3.10.

Footnotes

1

C++ programmers should note that Python’s virtual base class concept is not the same as C++’s.