
"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 following class:

class 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 ABCMeta

         class MyABC(metaclass=ABCMeta):
             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.

   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(metaclass=ABCMeta):

          @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 decorators:

@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(metaclass=ABCMeta):
          @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.

@abc.abstractclassmethod

   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(metaclass=ABCMeta):
          @classmethod
          @abstractmethod
          def my_abstract_classmethod(cls, ...):
              ...

   New in version 3.2.

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

@abc.abstractstaticmethod

   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(metaclass=ABCMeta):
          @staticmethod
          @abstractmethod
          def my_abstract_staticmethod(...):
              ...

   New in version 3.2.

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

@abc.abstractproperty(fget=None, fset=None, fdel=None, doc=None)

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

   Using this function 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
   properties can be called using any of the normal 'super' call
   mechanisms.

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

      class C(metaclass=ABCMeta):
          @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(metaclass=ABCMeta):
          @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):
              ...

   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.

-[ Footnotes ]-

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