types
--- Dynamic type creation and names for built-in typesSource code: Lib/types.py
[UNKNOWN NODE transition]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.
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.
Changed in version 3.6: The default value for the namespace
element of the returned
tuple has changed. Now an insertion-order-preserving mapping is
used when the metaclass does not have a __prepare__
method,
See also
- Metaclasses
- Full details of the class creation process supported by these functions
- PEP 3115 - Metaclasses in Python 3000
- Introduced the
__prepare__
namespace hook
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.AsyncGeneratorType
The type of asynchronous generator-iterator objects, created by asynchronous generator functions.
New in version 3.6.
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.
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.
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.