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 fromABC
avoiding sometimes confusing metaclass usage, for example:from abc import ABC class MyABC(ABC): pass
Note that the type of
ABC
is stillABCMeta
, therefore inheriting fromABC
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 usingABCMeta
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 viasuper()
). [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 theget_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 callregister()
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
orNotImplemented
. If it returnsTrue
, the subclass is considered a subclass of this ABC. If it returnsFalse
, the subclass is not considered a subclass of this ABC, even if it would normally be one. If it returnsNotImplemented
, 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. Theget_iterator()
method is also part of theMyIterable
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 aMyIterable
too.Finally, the last line makes
Foo
a virtual subclass ofMyIterable
, 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 makeget_iterator
available as a method ofFoo
, 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 fromABCMeta
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. Theabstractmethod()
only affects subclasses derived using regular inheritance; “virtual subclasses” registered with the ABC’sregister()
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 beTrue
if any of the methods used to compose the descriptor are abstract. For example, Python’s built-inproperty
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
withabstractmethod()
, making this decorator redundant.A subclass of the built-in
classmethod()
, indicating an abstract classmethod. Otherwise it is similar toabstractmethod()
.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
withabstractmethod()
, making this decorator redundant.A subclass of the built-in
staticmethod()
, indicating an abstract staticmethod. Otherwise it is similar toabstractmethod()
.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()
andproperty.deleter()
withabstractmethod()
, 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