
"types" --- Dynamic type creation and names for built-in types
**************************************************************

**Source code:** Lib/types.py

======================================================================

This module defines utility function to assist in dynamic creation of
new types.

It also defines names for some object types that are used by the
standard Python interpreter, but not exposed as builtins like "int" or
"str" are.

Finally, it provides some additional type-related utility classes and
functions that are not fundamental enough to be builtins.


Dynamic Type Creation
=====================

types.new_class(name, bases=(), kwds=None, exec_body=None)

   Creates a class object dynamically using the appropriate metaclass.

   The first three arguments are the components that make up a class
   definition header: the class name, the base classes (in order), the
   keyword arguments (such as "metaclass").

   The *exec_body* argument is a callback that is used to populate the
   freshly created class namespace. It should accept the class
   namespace as its sole argument and update the namespace directly
   with the class contents. If no callback is provided, it has the
   same effect as passing in "lambda ns: ns".

   New in version 3.3.

types.prepare_class(name, bases=(), kwds=None)

   Calculates the appropriate metaclass and creates the class
   namespace.

   The arguments are the components that make up a class definition
   header: the class name, the base classes (in order) and the keyword
   arguments (such as "metaclass").

   The return value is a 3-tuple: "metaclass, namespace, kwds"

   *metaclass* is the appropriate metaclass, *namespace* is the
   prepared class namespace and *kwds* is an updated copy of the
   passed in *kwds* argument with any "'metaclass'" entry removed. If
   no *kwds* argument is passed in, this will be an empty dict.

   New in version 3.3.

See also:

  Customizing class creation
     Full details of the class creation process supported by these
     functions

  **PEP 3115** - Metaclasses in Python 3000
     Introduced the "__prepare__" namespace hook


Standard Interpreter Types
==========================

This module provides names for many of the types that are required to
implement a Python interpreter. It deliberately avoids including some
of the types that arise only incidentally during processing such as
the "listiterator" type.

Typical use of these names is for "isinstance()" or "issubclass()"
checks.

Standard names are defined for the following types:

types.FunctionType
types.LambdaType

   The type of user-defined functions and functions created by
   "lambda"  expressions.

types.GeneratorType

   The type of *generator*-iterator objects, created by generator
   functions.

types.CoroutineType

   The type of *coroutine* objects, created by "async def" functions.

   New in version 3.5.

types.CodeType

   The type for code objects such as returned by "compile()".

types.MethodType

   The type of methods of user-defined class instances.

types.BuiltinFunctionType
types.BuiltinMethodType

   The type of built-in functions like "len()" or "sys.exit()", and
   methods of built-in classes.  (Here, the term "built-in" means
   "written in C".)

class types.ModuleType(name, doc=None)

   The type of *modules*. Constructor takes the name of the module to
   be created and optionally its *docstring*.

   Note: Use "importlib.util.module_from_spec()" to create a new
     module if you wish to set the various import-controlled
     attributes.

   __doc__

      The *docstring* of the module. Defaults to "None".

   __loader__

      The *loader* which loaded the module. Defaults to "None".

      Changed in version 3.4: Defaults to "None". Previously the
      attribute was optional.

   __name__

      The name of the module.

   __package__

      Which *package* a module belongs to. If the module is top-level
      (i.e. not a part of any specific package) then the attribute
      should be set to "''", else it should be set to the name of the
      package (which can be "__name__" if the module is a package
      itself). Defaults to "None".

      Changed in version 3.4: Defaults to "None". Previously the
      attribute was optional.

types.TracebackType

   The type of traceback objects such as found in "sys.exc_info()[2]".

types.FrameType

   The type of frame objects such as found in "tb.tb_frame" if "tb" is
   a traceback object.

types.GetSetDescriptorType

   The type of objects defined in extension modules with
   "PyGetSetDef", such as "FrameType.f_locals" or
   "array.array.typecode".  This type is used as descriptor for object
   attributes; it has the same purpose as the "property" type, but for
   classes defined in extension modules.

types.MemberDescriptorType

   The type of objects defined in extension modules with
   "PyMemberDef", such as "datetime.timedelta.days".  This type is
   used as descriptor for simple C data members which use standard
   conversion functions; it has the same purpose as the "property"
   type, but for classes defined in extension modules.

   **CPython implementation detail:** In other implementations of
   Python, this type may be identical to "GetSetDescriptorType".

class types.MappingProxyType(mapping)

   Read-only proxy of a mapping. It provides a dynamic view on the
   mapping's entries, which means that when the mapping changes, the
   view reflects these changes.

   New in version 3.3.

   key in proxy

      Return "True" if the underlying mapping has a key *key*, else
      "False".

   proxy[key]

      Return the item of the underlying mapping with key *key*.
      Raises a "KeyError" if *key* is not in the underlying mapping.

   iter(proxy)

      Return an iterator over the keys of the underlying mapping.
      This is a shortcut for "iter(proxy.keys())".

   len(proxy)

      Return the number of items in the underlying mapping.

   copy()

      Return a shallow copy of the underlying mapping.

   get(key[, default])

      Return the value for *key* if *key* is in the underlying
      mapping, else *default*.  If *default* is not given, it defaults
      to "None", so that this method never raises a "KeyError".

   items()

      Return a new view of the underlying mapping's items ("(key,
      value)" pairs).

   keys()

      Return a new view of the underlying mapping's keys.

   values()

      Return a new view of the underlying mapping's values.


Additional Utility Classes and Functions
========================================

class types.SimpleNamespace

   A simple "object" subclass that provides attribute access to its
   namespace, as well as a meaningful repr.

   Unlike "object", with "SimpleNamespace" you can add and remove
   attributes.  If a "SimpleNamespace" object is initialized with
   keyword arguments, those are directly added to the underlying
   namespace.

   The type is roughly equivalent to the following code:

      class SimpleNamespace:
          def __init__(self, **kwargs):
              self.__dict__.update(kwargs)

          def __repr__(self):
              keys = sorted(self.__dict__)
              items = ("{}={!r}".format(k, self.__dict__[k]) for k in keys)
              return "{}({})".format(type(self).__name__, ", ".join(items))

          def __eq__(self, other):
              return self.__dict__ == other.__dict__

   "SimpleNamespace" may be useful as a replacement for "class NS:
   pass". However, for a structured record type use "namedtuple()"
   instead.

   New in version 3.3.

types.DynamicClassAttribute(fget=None, fset=None, fdel=None, doc=None)

   Route attribute access on a class to __getattr__.

   This is a descriptor, used to define attributes that act
   differently when accessed through an instance and through a class.
   Instance access remains normal, but access to an attribute through
   a class will be routed to the class's __getattr__ method; this is
   done by raising AttributeError.

   This allows one to have properties active on an instance, and have
   virtual attributes on the class with the same name (see Enum for an
   example).

   New in version 3.4.


Coroutine Utility Functions
===========================

types.coroutine(gen_func)

   This function transforms a *generator* function into a *coroutine
   function* which returns a generator-based coroutine. The generator-
   based coroutine is still a *generator iterator*, but is also
   considered to be a *coroutine* object and is *awaitable*.  However,
   it may not necessarily implement the "__await__()" method.

   If *gen_func* is a generator function, it will be modified in-
   place.

   If *gen_func* is not a generator function, it will be wrapped. If
   it returns an instance of "collections.abc.Generator", the instance
   will be wrapped in an *awaitable* proxy object.  All other types of
   objects will be returned as is.

   New in version 3.5.
