29.7. abc — Abstract Base Classes — Python 3.6.6 documentation

# 29.7. `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, is it hashable or 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 not supported. 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, ...):
              ...
          @classmethod
          @abstractmethod
          def my_abstract_classmethod(cls, ...):
              ...
          @staticmethod
          @abstractmethod
          def my_abstract_staticmethod(...):
              ...

          @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, ...):
              ...

`@``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(...):
              ...

`@``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.

Footnotes

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