Python 3.6.5 Documentation >  "abc" — Abstract Base Classes

"abc" — Abstract Base Classes
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**Source code:** Lib/abc.py

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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.