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PEP: 447
Title: Add __getdescriptor__ method to metaclass
Author: Ronald Oussoren <ronaldoussoren@mac.com>
Status: Deferred
Type: Standards Track
Content-Type: text/x-rst
Created: 12-Jun-2013
Post-History: 02-Jul-2013, 15-Jul-2013, 29-Jul-2013, 22-Jul-2015
Abstract
========
Currently ``object.__getattribute__`` and ``super.__getattribute__`` peek
in the ``__dict__`` of classes on the MRO for a class when looking for
an attribute. This PEP adds an optional ``__getdescriptor__`` method to
a metaclass that replaces this behavior and gives more control over attribute
lookup, especially when using a `super`_ object.
That is, the MRO walking loop in ``_PyType_Lookup`` and
``super.__getattribute__`` gets changed from::
def lookup(mro_list, name):
for cls in mro_list:
if name in cls.__dict__:
return cls.__dict__
return NotFound
to::
def lookup(mro_list, name):
for cls in mro_list:
try:
return cls.__getdescriptor__(name)
except AttributeError:
pass
return NotFound
The default implementation of ``__getdescriptor__`` looks in the class
dictionary::
class type:
def __getdescriptor__(cls, name):
try:
return cls.__dict__[name]
except KeyError:
raise AttributeError(name) from None
PEP Status
==========
This PEP is deferred until someone has time to update this PEP and push it forward.
Rationale
=========
It is currently not possible to influence how the `super class`_ looks
up attributes (that is, ``super.__getattribute__`` unconditionally
peeks in the class ``__dict__``), and that can be problematic for
dynamic classes that can grow new methods on demand, for example dynamic
proxy classes.
The ``__getdescriptor__`` method makes it possible to dynamically add
attributes even when looking them up using the `super class`_.
The new method affects ``object.__getattribute__`` (and
`PyObject_GenericGetAttr`_) as well for consistency and to have a single
place to implement dynamic attribute resolution for classes.
Background
----------
The current behavior of ``super.__getattribute__`` causes problems for
classes that are dynamic proxies for other (non-Python) classes or types,
an example of which is `PyObjC`_. PyObjC creates a Python class for every
class in the Objective-C runtime, and looks up methods in the Objective-C
runtime when they are used. This works fine for normal access, but doesn't
work for access with `super`_ objects. Because of this PyObjC currently
includes a custom `super`_ that must be used with its classes, as well as
completely reimplementing `PyObject_GenericGetAttr`_ for normal attribute
access.
The API in this PEP makes it possible to remove the custom `super`_ and
simplifies the implementation because the custom lookup behavior can be
added in a central location.
.. note::
`PyObjC`_ cannot precalculate the contents of the class ``__dict__``
because Objective-C classes can grow new methods at runtime. Furthermore,
Objective-C classes tend to contain a lot of methods while most Python
code will only use a small subset of them, this makes precalculating
unnecessarily expensive.
The superclass attribute lookup hook
====================================
Both ``super.__getattribute__`` and ``object.__getattribute__`` (or
`PyObject_GenericGetAttr`_ and in particular ``_PyType_Lookup`` in C code)
walk an object's MRO and currently peek in the class' ``__dict__`` to look up
attributes.
With this proposal both lookup methods no longer peek in the class ``__dict__``
but call the special method ``__getdescriptor__``, which is a slot defined
on the metaclass. The default implementation of that method looks
up the name the class ``__dict__``, which means that attribute lookup is
unchanged unless a metatype actually defines the new special method.
Aside: Attribute resolution algorithm in Python
-----------------------------------------------
The attribute resolution process as implemented by ``object.__getattribute__``
(or ``PyObject_GenericGetAttr`` in CPython's implementation) is fairly
straightforward, but not entirely so without reading C code.
The current CPython implementation of object.__getattribute__ is basically
equivalent to the following (pseudo-) Python code (excluding some house
keeping and speed tricks)::
def _PyType_Lookup(tp, name):
mro = tp.mro()
assert isinstance(mro, tuple)
for base in mro:
assert isinstance(base, type)
# PEP 447 will change these lines:
try:
return base.__dict__[name]
except KeyError:
pass
return None
class object:
def __getattribute__(self, name):
assert isinstance(name, str)
tp = type(self)
descr = _PyType_Lookup(tp, name)
f = None
if descr is not None:
f = descr.__get__
if f is not None and descr.__set__ is not None:
# Data descriptor
return f(descr, self, type(self))
dict = self.__dict__
if dict is not None:
try:
return self.__dict__[name]
except KeyError:
pass
if f is not None:
# Non-data descriptor
return f(descr, self, type(self))
if descr is not None:
# Regular class attribute
return descr
raise AttributeError(name)
class super:
def __getattribute__(self, name):
assert isinstance(name, unicode)
if name != '__class__':
starttype = self.__self_type__
mro = startype.mro()
try:
idx = mro.index(self.__thisclass__)
except ValueError:
pass
else:
for base in mro[idx+1:]:
# PEP 447 will change these lines:
try:
descr = base.__dict__[name]
except KeyError:
continue
f = descr.__get__
if f is not None:
return f(descr,
None if (self.__self__ is self.__self_type__) else self.__self__,
starttype)
else:
return descr
return object.__getattribute__(self, name)
This PEP should change the dict lookup at the lines starting at "# PEP 447" with
a method call to perform the actual lookup, making is possible to affect that
lookup both for normal attribute access and access through the `super proxy`_.
Note that specific classes can already completely override the default
behaviour by implementing their own ``__getattribute__`` slot (with or without
calling the super class implementation).
In Python code
--------------
A meta type can define a method ``__getdescriptor__`` that is called during
attribute resolution by both ``super.__getattribute__``
and ``object.__getattribute``::
class MetaType(type):
def __getdescriptor__(cls, name):
try:
return cls.__dict__[name]
except KeyError:
raise AttributeError(name) from None
The ``__getdescriptor__`` method has as its arguments a class (which is an
instance of the meta type) and the name of the attribute that is looked up.
It should return the value of the attribute without invoking descriptors,
and should raise `AttributeError`_ when the name cannot be found.
The `type`_ class provides a default implementation for ``__getdescriptor__``,
that looks up the name in the class dictionary.
Example usage
.............
The code below implements a silly metaclass that redirects attribute lookup to
uppercase versions of names::
class UpperCaseAccess (type):
def __getdescriptor__(cls, name):
try:
return cls.__dict__[name.upper()]
except KeyError:
raise AttributeError(name) from None
class SillyObject (metaclass=UpperCaseAccess):
def m(self):
return 42
def M(self):
return "fortytwo"
obj = SillyObject()
assert obj.m() == "fortytwo"
As mentioned earlier in this PEP a more realistic use case of this
functionality is a ``__getdescriptor__`` method that dynamically populates the
class ``__dict__`` based on attribute access, primarily when it is not
possible to reliably keep the class dict in sync with its source, for example
because the source used to populate ``__dict__`` is dynamic as well and does
not have triggers that can be used to detect changes to that source.
An example of that are the class bridges in PyObjC: the class bridge is a
Python object (class) that represents an Objective-C class and conceptually
has a Python method for every Objective-C method in the Objective-C class.
As with Python it is possible to add new methods to an Objective-C class, or
replace existing ones, and there are no callbacks that can be used to detect
this.
In C code
---------
A new type flag ``Py_TPFLAGS_GETDESCRIPTOR`` with value ``(1UL << 11)`` that
indicates that the new slot is present and to be used.
A new slot ``tp_getdescriptor`` is added to the ``PyTypeObject`` struct, this
slot corresponds to the ``__getdescriptor__`` method on `type`_.
The slot has the following prototype::
PyObject* (*getdescriptorfunc)(PyTypeObject* cls, PyObject* name);
This method should lookup *name* in the namespace of *cls*, without looking at
superclasses, and should not invoke descriptors. The method returns ``NULL``
without setting an exception when the *name* cannot be found, and returns a
new reference otherwise (not a borrowed reference).
Classes with a ``tp_getdescriptor`` slot must add ``Py_TPFLAGS_GETDESCRIPTOR``
to ``tp_flags`` to indicate that new slot must be used.
Use of this hook by the interpreter
-----------------------------------
The new method is required for metatypes and as such is defined on ``type_``.
Both ``super.__getattribute__`` and
``object.__getattribute__``/`PyObject_GenericGetAttr`_
(through ``_PyType_Lookup``) use the this ``__getdescriptor__`` method when
walking the MRO.
Other changes to the implementation
-----------------------------------
The change for `PyObject_GenericGetAttr`_ will be done by changing the private
function ``_PyType_Lookup``. This currently returns a borrowed reference, but
must return a new reference when the ``__getdescriptor__`` method is present.
Because of this ``_PyType_Lookup`` will be renamed to ``_PyType_LookupName``,
this will cause compile-time errors for all out-of-tree users of this
private API.
For the same reason ``_PyType_LookupId`` is renamed to ``_PyType_LookupId2``.
A number of other functions in typeobject.c with the same issue do not get
an updated name because they are private to that file.
The attribute lookup cache in ``Objects/typeobject.c`` is disabled for classes
that have a metaclass that overrides ``__getdescriptor__``, because using the
cache might not be valid for such classes.
Impact of this PEP on introspection
===================================
Use of the method introduced in this PEP can affect introspection of classes
with a metaclass that uses a custom ``__getdescriptor__`` method. This section
lists those changes.
The items listed below are only affected by custom ``__getdescriptor__``
methods, the default implementation for ``object`` won't cause problems
because that still only uses the class ``__dict__`` and won't cause visible
changes to the visible behaviour of the ``object.__getattribute__``.
* ``dir`` might not show all attributes
As with a custom ``__getattribute__`` method `dir()`_ might not see all
(instance) attributes when using the ``__getdescriptor__()`` method to
dynamically resolve attributes.
The solution for that is quite simple: classes using ``__getdescriptor__``
should also implement `__dir__()`_ if they want full support for the builtin
`dir()`_ function.
* ``inspect.getattr_static`` might not show all attributes
The function ``inspect.getattr_static`` intentionally does not invoke
``__getattribute__`` and descriptors to avoid invoking user code during
introspection with this function. The ``__getdescriptor__`` method will also
be ignored and is another way in which the result of ``inspect.getattr_static``
can be different from that of ``builtin.getattr``.
* ``inspect.getmembers`` and ``inspect.classify_class_attrs``
Both of these functions directly access the class __dict__ of classes along
the MRO, and hence can be affected by a custom ``__getdescriptor__`` method.
Code with a custom ``__getdescriptor__`` method that want to play nice with
these methods also needs to ensure that the ``__dict__`` is set up correctly
when that is accessed directly by Python code.
Note that ``inspect.getmembers`` is used by ``pydoc`` and hence this can
affect runtime documentation introspection.
* Direct introspection of the class ``__dict__``
Any code that directly access the class ``__dict__`` for introspection
can be affected by a custom ``__getdescriptor__`` method, see the previous
item.
Performance impact
==================
**WARNING**: The benchmark results in this section are old, and will be updated
when I've ported the patch to the current trunk. I don't expect significant
changes to the results in this section.
Micro benchmarks
----------------
`Issue 18181`_ has a micro benchmark as one of its attachments
(`pep447-micro-bench.py`_) that specifically tests the speed of attribute
lookup, both directly and through super.
Note that attribute lookup with deep class hierarchies is significantly slower
when using a custom ``__getdescriptor__`` method. This is because the
attribute lookup cache for CPython cannot be used when having this method.
Pybench
-------
The pybench output below compares an implementation of this PEP with the
regular source tree, both based on changeset a5681f50bae2, run on an idle
machine and Core i7 processor running Centos 6.4.
Even though the machine was idle there were clear differences between runs,
I've seen difference in "minimum time" vary from -0.1% to +1.5%, with similar
(but slightly smaller) differences in the "average time" difference.
::
-------------------------------------------------------------------------------
PYBENCH 2.1
-------------------------------------------------------------------------------
* using CPython 3.4.0a0 (default, Jul 29 2013, 13:01:34) [GCC 4.4.7 20120313 (Red Hat 4.4.7-3)]
* disabled garbage collection
* system check interval set to maximum: 2147483647
* using timer: time.perf_counter
* timer: resolution=1e-09, implementation=clock_gettime(CLOCK_MONOTONIC)
-------------------------------------------------------------------------------
Benchmark: pep447.pybench
-------------------------------------------------------------------------------
Rounds: 10
Warp: 10
Timer: time.perf_counter
Machine Details:
Platform ID: Linux-2.6.32-358.114.1.openstack.el6.x86_64-x86_64-with-centos-6.4-Final
Processor: x86_64
Python:
Implementation: CPython
Executable: /tmp/default-pep447/bin/python3
Version: 3.4.0a0
Compiler: GCC 4.4.7 20120313 (Red Hat 4.4.7-3)
Bits: 64bit
Build: Jul 29 2013 14:09:12 (#default)
Unicode: UCS4
-------------------------------------------------------------------------------
Comparing with: default.pybench
-------------------------------------------------------------------------------
Rounds: 10
Warp: 10
Timer: time.perf_counter
Machine Details:
Platform ID: Linux-2.6.32-358.114.1.openstack.el6.x86_64-x86_64-with-centos-6.4-Final
Processor: x86_64
Python:
Implementation: CPython
Executable: /tmp/default/bin/python3
Version: 3.4.0a0
Compiler: GCC 4.4.7 20120313 (Red Hat 4.4.7-3)
Bits: 64bit
Build: Jul 29 2013 13:01:34 (#default)
Unicode: UCS4
Test minimum run-time average run-time
this other diff this other diff
-------------------------------------------------------------------------------
BuiltinFunctionCalls: 45ms 44ms +1.3% 45ms 44ms +1.3%
BuiltinMethodLookup: 26ms 27ms -2.4% 27ms 27ms -2.2%
CompareFloats: 33ms 34ms -0.7% 33ms 34ms -1.1%
CompareFloatsIntegers: 66ms 67ms -0.9% 66ms 67ms -0.8%
CompareIntegers: 51ms 50ms +0.9% 51ms 50ms +0.8%
CompareInternedStrings: 34ms 33ms +0.4% 34ms 34ms -0.4%
CompareLongs: 29ms 29ms -0.1% 29ms 29ms -0.0%
CompareStrings: 43ms 44ms -1.8% 44ms 44ms -1.8%
ComplexPythonFunctionCalls: 44ms 42ms +3.9% 44ms 42ms +4.1%
ConcatStrings: 33ms 33ms -0.4% 33ms 33ms -1.0%
CreateInstances: 47ms 48ms -2.9% 47ms 49ms -3.4%
CreateNewInstances: 35ms 36ms -2.5% 36ms 36ms -2.5%
CreateStringsWithConcat: 69ms 70ms -0.7% 69ms 70ms -0.9%
DictCreation: 52ms 50ms +3.1% 52ms 50ms +3.0%
DictWithFloatKeys: 40ms 44ms -10.1% 43ms 45ms -5.8%
DictWithIntegerKeys: 32ms 36ms -11.2% 35ms 37ms -4.6%
DictWithStringKeys: 29ms 34ms -15.7% 35ms 40ms -11.0%
ForLoops: 30ms 29ms +2.2% 30ms 29ms +2.2%
IfThenElse: 38ms 41ms -6.7% 38ms 41ms -6.9%
ListSlicing: 36ms 36ms -0.7% 36ms 37ms -1.3%
NestedForLoops: 43ms 45ms -3.1% 43ms 45ms -3.2%
NestedListComprehensions: 39ms 40ms -1.7% 39ms 40ms -2.1%
NormalClassAttribute: 86ms 82ms +5.1% 86ms 82ms +5.0%
NormalInstanceAttribute: 42ms 42ms +0.3% 42ms 42ms +0.0%
PythonFunctionCalls: 39ms 38ms +3.5% 39ms 38ms +2.8%
PythonMethodCalls: 51ms 49ms +3.0% 51ms 50ms +2.8%
Recursion: 67ms 68ms -1.4% 67ms 68ms -1.4%
SecondImport: 41ms 36ms +12.5% 41ms 36ms +12.6%
SecondPackageImport: 45ms 40ms +13.1% 45ms 40ms +13.2%
SecondSubmoduleImport: 92ms 95ms -2.4% 95ms 98ms -3.6%
SimpleComplexArithmetic: 28ms 28ms -0.1% 28ms 28ms -0.2%
SimpleDictManipulation: 57ms 57ms -1.0% 57ms 58ms -1.0%
SimpleFloatArithmetic: 29ms 28ms +4.7% 29ms 28ms +4.9%
SimpleIntFloatArithmetic: 37ms 41ms -8.5% 37ms 41ms -8.7%
SimpleIntegerArithmetic: 37ms 41ms -9.4% 37ms 42ms -10.2%
SimpleListComprehensions: 33ms 33ms -1.9% 33ms 34ms -2.9%
SimpleListManipulation: 28ms 30ms -4.3% 29ms 30ms -4.1%
SimpleLongArithmetic: 26ms 26ms +0.5% 26ms 26ms +0.5%
SmallLists: 40ms 40ms +0.1% 40ms 40ms +0.1%
SmallTuples: 46ms 47ms -2.4% 46ms 48ms -3.0%
SpecialClassAttribute: 126ms 120ms +4.7% 126ms 121ms +4.4%
SpecialInstanceAttribute: 42ms 42ms +0.6% 42ms 42ms +0.8%
StringMappings: 94ms 91ms +3.9% 94ms 91ms +3.8%
StringPredicates: 48ms 49ms -1.7% 48ms 49ms -2.1%
StringSlicing: 45ms 45ms +1.4% 46ms 45ms +1.5%
TryExcept: 23ms 22ms +4.9% 23ms 22ms +4.8%
TryFinally: 32ms 32ms -0.1% 32ms 32ms +0.1%
TryRaiseExcept: 17ms 17ms +0.9% 17ms 17ms +0.5%
TupleSlicing: 49ms 48ms +1.1% 49ms 49ms +1.0%
WithFinally: 48ms 47ms +2.3% 48ms 47ms +2.4%
WithRaiseExcept: 45ms 44ms +0.8% 45ms 45ms +0.5%
-------------------------------------------------------------------------------
Totals: 2284ms 2287ms -0.1% 2306ms 2308ms -0.1%
(this=pep447.pybench, other=default.pybench)
A run of the benchmark suite (with option "-b 2n3") also seems to indicate that
the performance impact is minimal::
Report on Linux fangorn.local 2.6.32-358.114.1.openstack.el6.x86_64 #1 SMP Wed Jul 3 02:11:25 EDT 2013 x86_64 x86_64
Total CPU cores: 8
### call_method_slots ###
Min: 0.304120 -> 0.282791: 1.08x faster
Avg: 0.304394 -> 0.282906: 1.08x faster
Significant (t=2329.92)
Stddev: 0.00016 -> 0.00004: 4.1814x smaller
### call_simple ###
Min: 0.249268 -> 0.221175: 1.13x faster
Avg: 0.249789 -> 0.221387: 1.13x faster
Significant (t=2770.11)
Stddev: 0.00012 -> 0.00013: 1.1101x larger
### django_v2 ###
Min: 0.632590 -> 0.601519: 1.05x faster
Avg: 0.635085 -> 0.602653: 1.05x faster
Significant (t=321.32)
Stddev: 0.00087 -> 0.00051: 1.6933x smaller
### fannkuch ###
Min: 1.033181 -> 0.999779: 1.03x faster
Avg: 1.036457 -> 1.001840: 1.03x faster
Significant (t=260.31)
Stddev: 0.00113 -> 0.00070: 1.6112x smaller
### go ###
Min: 0.526714 -> 0.544428: 1.03x slower
Avg: 0.529649 -> 0.547626: 1.03x slower
Significant (t=-93.32)
Stddev: 0.00136 -> 0.00136: 1.0028x smaller
### iterative_count ###
Min: 0.109748 -> 0.116513: 1.06x slower
Avg: 0.109816 -> 0.117202: 1.07x slower
Significant (t=-357.08)
Stddev: 0.00008 -> 0.00019: 2.3664x larger
### json_dump_v2 ###
Min: 2.554462 -> 2.609141: 1.02x slower
Avg: 2.564472 -> 2.620013: 1.02x slower
Significant (t=-76.93)
Stddev: 0.00538 -> 0.00481: 1.1194x smaller
### meteor_contest ###
Min: 0.196336 -> 0.191925: 1.02x faster
Avg: 0.196878 -> 0.192698: 1.02x faster
Significant (t=61.86)
Stddev: 0.00053 -> 0.00041: 1.2925x smaller
### nbody ###
Min: 0.228039 -> 0.235551: 1.03x slower
Avg: 0.228857 -> 0.236052: 1.03x slower
Significant (t=-54.15)
Stddev: 0.00130 -> 0.00029: 4.4810x smaller
### pathlib ###
Min: 0.108501 -> 0.105339: 1.03x faster
Avg: 0.109084 -> 0.105619: 1.03x faster
Significant (t=311.08)
Stddev: 0.00022 -> 0.00011: 1.9314x smaller
### regex_effbot ###
Min: 0.057905 -> 0.056447: 1.03x faster
Avg: 0.058055 -> 0.056760: 1.02x faster
Significant (t=79.22)
Stddev: 0.00006 -> 0.00015: 2.7741x larger
### silent_logging ###
Min: 0.070810 -> 0.072436: 1.02x slower
Avg: 0.070899 -> 0.072609: 1.02x slower
Significant (t=-191.59)
Stddev: 0.00004 -> 0.00008: 2.2640x larger
### spectral_norm ###
Min: 0.290255 -> 0.299286: 1.03x slower
Avg: 0.290335 -> 0.299541: 1.03x slower
Significant (t=-572.10)
Stddev: 0.00005 -> 0.00015: 2.8547x larger
### threaded_count ###
Min: 0.107215 -> 0.115206: 1.07x slower
Avg: 0.107488 -> 0.115996: 1.08x slower
Significant (t=-109.39)
Stddev: 0.00016 -> 0.00076: 4.8665x larger
The following not significant results are hidden, use -v to show them:
call_method, call_method_unknown, chaos, fastpickle, fastunpickle, float, formatted_logging, hexiom2, json_load, normal_startup, nqueens, pidigits, raytrace, regex_compile, regex_v8, richards, simple_logging, startup_nosite, telco, unpack_sequence.
Alternative proposals
=====================
``__getattribute_super__``
--------------------------
An earlier version of this PEP used the following static method on classes::
def __getattribute_super__(cls, name, object, owner): pass
This method performed name lookup as well as invoking descriptors and was
necessarily limited to working only with ``super.__getattribute__``.
Reuse ``tp_getattro``
---------------------
It would be nice to avoid adding a new slot, thus keeping the API simpler and
easier to understand. A comment on `Issue 18181`_ asked about reusing the
``tp_getattro`` slot, that is super could call the ``tp_getattro`` slot of all
methods along the MRO.
That won't work because ``tp_getattro`` will look in the instance
``__dict__`` before it tries to resolve attributes using classes in the MRO.
This would mean that using ``tp_getattro`` instead of peeking the class
dictionaries changes the semantics of the `super class`_.
Alternative placement of the new method
---------------------------------------
This PEP proposes to add ``__getdescriptor__`` as a method on the metaclass.
An alternative would be to add it as a class method on the class itself
(similar to how ``__new__`` is a `staticmethod`_ of the class and not a method
of the metaclass).
The advantage of using a method on the metaclass is that will give an error
when two classes on the MRO have different metaclasses that may have different
behaviors for ``__getdescriptor__``. With a normal classmethod that problem
would pass undetected while it might cause subtle errors when running the code.
History
=======
* 23-Jul-2015: Added type flag ``Py_TPFLAGS_GETDESCRIPTOR`` after talking
with Guido.
The new flag is primarily useful to avoid crashing when loading an extension
for an older version of CPython and could have positive speed implications
as well.
* Jul-2014: renamed slot to ``__getdescriptor__``, the old name didn't
match the naming style of other slots and was less descriptive.
Discussion threads
==================
* The initial version of the PEP was send with
Message-ID `<75030FAC-6918-4E94-95DA-67A88D53E6F5@mac.com>`_
* Further discussion starting at a message with
Message-ID `<5BB87CC4-F31B-4213-AAAC-0C0CE738460C@mac.com>`_
* And more discussion starting at message with
Message-ID `<00AA7433-C853-4101-9718-060468EBAC54@mac.com>`_
References
==========
* `Issue 18181`_ contains an out of date prototype implementation
Copyright
=========
This document has been placed in the public domain.
.. _`<75030FAC-6918-4E94-95DA-67A88D53E6F5@mac.com>`: http://marc.info/?l=python-dev&m=137510220928964&w=2
.. _`<5BB87CC4-F31B-4213-AAAC-0C0CE738460C@mac.com>`: https://mail.python.org/pipermail/python-ideas/2014-July/028420.html
.. _`<00AA7433-C853-4101-9718-060468EBAC54@mac.com>`: https://mail.python.org/pipermail/python-dev/2013-July/127321.html
.. _`Issue 18181`: http://bugs.python.org/issue18181
.. _`super class`: http://docs.python.org/3/library/functions.html#super
.. _`super proxy`: http://docs.python.org/3/library/functions.html#super
.. _`super`: http://docs.python.org/3/library/functions.html#super
.. _`dir()`: http://docs.python.org/3/library/functions.html#dir
.. _`staticmethod`: http://docs.python.org/3/library/functions.html#staticmethod
.. _`__dir__()`: https://docs.python.org/3/reference/datamodel.html#object.__dir__
.. _`NotImplemented`: http://docs.python.org/3/library/constants.html#NotImplemented
.. _`PyObject_GenericGetAttr`: http://docs.python.org/3/c-api/object.html#PyObject_GenericGetAttr
.. _`type`: http://docs.python.org/3/library/functions.html#type
.. _`AttributeError`: http://docs.python.org/3/library/exceptions.html#AttributeError
.. _`PyObjC`: http://pyobjc.sourceforge.net/
.. _`classmethod`: http://docs.python.org/3/library/functions.html#classmethod
.. _`pep447-micro-bench.py`: http://bugs.python.org/file40013/pep447-micro-bench.py
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