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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
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