python-peps/pep-0447.txt

PEP: 447
Title: Add __locallookup__ method to metaclass
Version: $Revision$
Last-Modified: $Date$
Author: Ronald Oussoren <ronaldoussoren@mac.com>
Status: Draft
Type: Standards Track
Content-Type: text/x-rst
Created: 12-Jun-2013
Post-History: 2-Jul-2013, 15-Jul-2013, 29-Jul-2013


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 ``__locallookup__`` method to
a metaclass that can be used to override this behavior.

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.__locallookup__(name)
             except AttributeError:
                 pass

         return NotFound


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.

The ``__locallookup__`` 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.

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.


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 ``__locallookup__``, 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.

In Python code
--------------

A meta type can define a method ``__locallookup__`` that is called during
attribute resolution by both ``super.__getattribute__``
and ``object.__getattribute``::

    class MetaType(type):
        def __locallookup__(cls, name):
            try:
                return cls.__dict__[name]
            except KeyError:
                raise AttributeError(name) from None

The ``__locallookup__`` 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 ``__locallookup__``,
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 __locallookup__(cls, name):
            return cls.__dict__[name.upper()]

    class SillyObject (metaclass=UpperCaseAccess):
        def m(self):
            return 42

        def M(self):
            return "fourtytwo"

    obj = SillyObject()
    assert obj.m() == "fortytwo"


In C code
---------

A new slot ``tp_locallookup`` is added to the ``PyTypeObject`` struct, this
slot corresponds to the ``__locallookup__`` method on `type`_.

The slot has the following prototype::

    PyObject* (*locallookupfunc)(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).

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 ``__locallookup__`` 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 ``__locallookup__`` 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.

The attribute lookup cache in ``Objects/typeobject.c`` is disabled for classes
that have a metaclass that overrides ``__locallookup__``, because using the
cache might not be valid for such classes.

Performance impact
------------------

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 an 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`_.


References
==========

* `Issue 18181`_ contains a prototype implementation

Copyright
=========

This document has been placed in the public domain.

.. _`Issue 18181`: http://bugs.python.org/issue18181

.. _`super class`: http://docs.python.org/3/library/functions.html#super

.. _`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