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pre-PEP generic objects

I promised I'd put together a PEP for a 'generic object' data type for
Python 2.5 that allows one to replace __getitem__ style access with
dotted-attribute style access (without declaring another class). Any
comments would be appreciated!

Thanks!

Steve

----------------------------------------------------------------------
Title: Generic Object Data Type
Version: $Revision: 1.0 $
Last-Modified: $Date: 2004/11/29 16:00:00 $
Author: Steven Bethard <st************ @gmail.com>
Status: Draft
Type: Standards Track
Content-Type: text/x-rst
Created: 29-Nov-2004
Python-Version: 2.5
Post-History: 29-Nov-2004
Abstract
========

This PEP proposes a standard library addition to support the simple
creation of 'generic' objects which can be given named attributes
without the need to declare a class. Such attribute-value mappings are
intended to complement the name-value mappings provided by Python's
builtin dict objects.
Motivation
==========

Python's dict objects provide a simple way of creating anonymous
name-value mappings. These mappings use the __getitem__ protocol to
access the value associated with a name, so that code generally appears
like::

mapping['name']

Occasionally, a programmer may decide that dotted-attribute style access
is more appropriate to the domain than __getitem__ style access, and
that their mapping should be accessed like::

mapping.name

Currently, if a Python programmer makes this design decision, they are
forced to declare a new class, and then build instances of this class.
When no methods are to be associated with the attribute-value mappings,
declaring a new class can be overkill. This PEP proposes adding a
simple type to the standard library that can be used to build such
attribute-value mappings.

Providing such a type allows the Python programmer to determine which
type of mapping is most appropriate to their domain and apply this
choice with minimal effort. Some of the suggested uses include:
Returning Named Results
-----------------------

It is often appropriate for a function that returns multiple items to
give names to the different items returned. The type suggested in this
PEP provides a simple means of doing this that allows the returned
values to be accessed in the usual attribute-style access::
def f(x): ... return Bunch(double=2* x, squared=x**2)
... y = f(10)
y.double 20 y.squared 100
Representing Hierarchical Data
------------------------------

The type suggested in this PEP also allows a simple means of
representing hierarchical data that allows attribute-style access::
x = Bunch(spam=Bunc h(rabbit=1, badger=[2, 3, 4]), ham='neewom')
x.spam.badger [2, 3, 4] x.ham 'neewom'
Rationale
=========

As Bunch objects are intended primarily to replace simple classes,
simple Bunch construction was a primary concern. As such, the Bunch
constructor supports creation from keyword arguments, dicts, and
sequences of (attribute, value) pairs::
Bunch(eggs=1, spam=2, ham=3) Bunch(eggs=1, ham=3, spam=2) Bunch({'eggs':1 , 'spam':2, 'ham':3}) Bunch(eggs=1, ham=3, spam=2) Bunch([('eggs',1), ('spam',2), ('ham',3)]) Bunch(eggs=1, ham=3, spam=2)

To allow attribute-value mappings to be easily combined, the update
method of Bunch objects supports similar arguments.

If Bunch objects are used to represent hierarchical data, comparison of
such objects becomes a concern. For this reason, Bunch objects support
object equality::
x = Bunch(parrot=Bu nch(lumberjack= True, spam=42), peng='shrub')
y = Bunch(peng='shr ub', parrot=Bunch(sp am=42, lumberjack=True ))
z = Bunch(parrot=Bu nch(lumberjack= True), peng='shrub')
x == y True x == z False

Additionally, to allow users of the Bunch type to convert other
hierarchical data into Bunch objects, a frommapping classmethod is
supported. This can be used, for example, to convert an XML DOM tree
into a tree of nested Bunch objects::
import xml.dom.minidom
def getitems(elemen t): ... if not isinstance(elem ent, xml.dom.minidom .Element):
... raise TypeError('item s only retrievable from Elements')
... if element.attribu tes:
... for key, value in element.attribu tes.items():
... yield key, value
... children = {}
... for child in element.childNo des:
... if child.nodeType == xml.dom.minidom .Node.TEXT_NODE :
... text_list = children.setdef ault('text', [])
... text_list.appen d(child.nodeVal ue)
... else:
... children.setdef ault(child.node Name, []).append(
... Bunch.frommappi ng(child, getitems=getite ms))
... for name, child_list in children.items( ):
... yield name, child_list
... doc = xml.dom.minidom .parseString("" "\ ... <xml>
... <a attr_a="1">
... a text 1
... <b attr_b="2" />
... <b attr_b="3"> b text </b>
... a text 2
... </a>
... <c attr_c="4"> c text </c>
... </xml>""") b = Bunch.frommappi ng(doc.document Element, getitems=getite ms)
b.a[0].b[1] Bunch(attr_b=u' 3', text=[u' b text '])

Note that support for the various mapping methods, e.g.
__(get|set|del) item__, __len__, __iter__, __contains__, items, keys,
values, etc. was intentionally omitted as these methods did not seem to
be necessary for the core uses of an attribute-value mapping. If such
methods are truly necessary for a given use case, this may suggest that
a dict object is a more appropriate type for that use.
Reference Implementation
=============== =========

(This will be replaced with a link to a SF patch when I think I've
made all the necessary corrections)::

import operator as _operator

class Bunch(object):
"""Bunch([bunch|dict|seq], **kwds) -> new bunch with specified
attributes

The new Bunch object's attributes are initialized from (if
provided) either another Bunch object's attributes, a
dictionary, or a sequence of (name, value) pairs, then from the
name=value pairs in the keyword argument list.

Example Usage: Bunch(eggs=1, spam=2, ham=3) Bunch(eggs=1, ham=3, spam=2) Bunch({'eggs':1 , 'spam':2, 'ham':3}) Bunch(eggs=1, ham=3, spam=2) Bunch([('eggs',1), ('spam',2), ('ham',3)]) Bunch(eggs=1, ham=3, spam=2) Bunch(Bunch(egg s=1, spam=2), ham=3) Bunch(eggs=1, ham=3, spam=2)
"""

def __init__(self, *args, **kwds):
"""Initiali zes a Bunch instance."""
self.update(*ar gs, **kwds)

def __eq__(self, other):
"""x.__eq__ (y) <==> x == y"""
return (isinstance(oth er, self.__class__)
and self.__dict__ == other.__dict__)

def __repr__(self):
"""x.__repr __() <==> repr(x)

If all attribute values in this bunch (and any nested
bunches) are reproducable with eval(repr(x)), then the Bunch
object is also reproducable for eval(repr(x)).
"""
return '%s(%s)' % (self.__class__ .__name__,
', '.join('%s=%r' % (k, v)
for k, v
in self.__dict__.i tems()))

def update(self, *args, **kwds):
"""update([bunch|dict|seq], **kwds) -> None

Updates a Bunch object's attributes from (if provided)
either another Bunch object's attributes, a dictionary, or a
sequence of (name, value) pairs, then from the name=value
pairs in the keyword argument list.
"""
if len(args) == 1:
other, = args
if isinstance(othe r, self.__class__) :
other = other.__dict__
try:
self.__dict__.u pdate(other)
except TypeError:
raise TypeError('cann ot update Bunch with %s' %
type(other).__n ame__)
elif len(args) != 0:
raise TypeError('expe cted 1 argument, got %i' %
len(args))
self.__dict__.u pdate(kwds)

@classmethod
def frommapping(cls , mapping, getitems=None):
"""Create a Bunch object from a (possibly nested) mapping.

Note that, unlike the Bunch constructor, frommapping
recursively converts all mappings to bunches.

Example Usage: Bunch.frommappi ng({'eggs':1,

... 'spam':{'ham':2 , 'badger':3}})
Bunch(eggs=1, spam=Bunch(ham= 2, badger=3))

Keyword Arguments:
mapping -- a mapping object
getitems -- a function that takes the mapping as a parameter
and returns an iterable of (key, value) pairs. If not
provided, the items method on the mapping object will be
used, or (key, mapping[key]) values will be generated if
the mapping object does not provide an items method.

Note that getitems will be applied recursively to each value
in the mapping. It should raise a TypeError if it is
applied to an object for which it cannot produce
(key, value) pairs.
"""
# determine which items() method to use
if getitems is None:
try:
getitems = type(mapping).i tems
except AttributeError:
getitems = _items
# build the Bunch from the mapping, recursively
result = cls()
for key, value in getitems(mappin g):
try:
value = cls.frommapping (value, getitems=getite ms)
except TypeError:
pass
setattr(result, key, value)
return result
def _items(mapping) :
"""Produces (key, value) pairs from a mapping object.

Intended for use with mapping objects that do not supply an
items method.
"""
for key in mapping:
yield key, mapping[key]
Open Issues
===========
What should the type be named? Some suggestions include 'Bunch',
'Record' and 'Struct'.

Where should the type be placed? The current suggestion is the
collections module.
References
==========

...
Local Variables:
mode: indented-text
indent-tabs-mode: nil
sentence-end-double-space: t
fill-column: 70
End:
Jul 18 '05
49 2915
Nick Craig-Wood wrote:
class Hash:
def __init__(self, **kwargs):
for key,value in kwargs.items():
setattr(self, key, value)
def __getitem__(sel f, x):
return getattr(self, x)
def __setitem__(sel f, x, y):
setattr(self, x, y)


You can simplify this:
class Hash(object):
def __init__(self, **kwargs):
for key,value in kwargs.items():
setattr(self, key, value)
__getitem__ = getattr
__setitem__ = setattr

--Scott David Daniels
Sc***********@A cm.Org
Jul 18 '05 #11
Scott David Daniels wrote:
Nick Craig-Wood wrote:
class Hash:
def __init__(self, **kwargs):
for key,value in kwargs.items():
setattr(self, key, value)
def __getitem__(sel f, x):
return getattr(self, x)
def __setitem__(sel f, x, y):
setattr(self, x, y)

You can simplify this:
class Hash(object):
def __init__(self, **kwargs):
for key,value in kwargs.items():
setattr(self, key, value)
__getitem__ = getattr
__setitem__ = setattr


Oh, I guess I should mention that Hash actually does something Bunch is
not intended to -- it supports __getitem__ style access in addition to
dotted-attribute (__getattr__) style access. Bunch is intended only to
support dotted-attribute style access, though it does support the
one-way conversion of a mapping object to a Bunch.

Steve
Jul 18 '05 #12
[Scott David Daniels]
You can simplify this:
class Hash(object):
def __init__(self, **kwargs):
for key,value in kwargs.items():
setattr(self, key, value)


Might it be:

def __init__(self, **kwargs):
self.__dict__.u pdate(kwargs)

--
François Pinard http://pinard.progiciels-bpi.ca
Jul 18 '05 #13
Steven Bethard wrote:
Peter Otten wrote:
Steven Bethard wrote:
def __eq__(self, other):
"""x.__eq__ (y) <==> x == y"""
return (isinstance(oth er, self.__class__)
and self.__dict__ == other.__dict__)
This results in an asymmetry:

[snip]

Whether this is intended, I don't know. If someone can enlighten me...

Unintended.
Oops, I meant CPython's rich comparison, not your __eq__() implementation.
I'll switch to
self.__class__ == other.__class__
or
type(self) == type(other)
Any preference?


Normally none of them. The former if hard pressed because all old-style
classes have the same type(). But it doesn't really matter here.

Peter

Jul 18 '05 #14
Peter Otten wrote:
Steven Bethard wrote:
def __eq__(self, other):
"""x.__eq__ (y) <==> x == y"""
return (isinstance(oth er, self.__class__)
and self.__dict__ == other.__dict__)

This results in an asymmetry:
from bunch import Bunch
class B(Bunch): pass ...B().__eq__( Bunch()) FalseBunch().__e q__(B()) True

With indirect use of __eq__() this puzzling behaviour disappears:
B() == Bunch() FalseBunch() == B()

False

Whether this is intended, I don't know. If someone can enlighten me...


It does look like it's at least documented:

http://docs.python.org/ref/comparisons.html
"The operators <, >, ==, >=, <=, and != compare the values of two
objects. The objects need not have the same type. If both are numbers,
they are converted to a common type. Otherwise, objects of different
types always compare unequal, and are ordered consistently but arbitrarily."

This sounds like using "==" makes a guarantee that objects of different
types will compare unequal, while my __eq__ method (using isinstance)
did not make this guarantee.

I tried to check the C code to verify this (that different classes are
guaranteed to be unequal) but rich comparisons make that code pretty
complicated.

Steve
Jul 18 '05 #15

"Steven Bethard" <st************ @gmail.com> wrote in message
def __eq__(self, other):
"""x.__eq__ (y) <==> x == y"""
return (isinstance(oth er, self.__class__)
Since an instance of a subclass is an instance of a parent class, but not
vice versa, I believe you introduce here the assymetry you verify below.
and self.__dict__ == other.__dict__)

This results in an asymmetry:
>from bunch import Bunch
>class B(Bunch): pass

...
>B().__eq__ (Bunch())

False
>Bunch().__ eq__(B())

True


Terry J. Reedy

Jul 18 '05 #16
Terry Reedy wrote:
"Steven Bethard" <st************ @gmail.com> wrote in message
>>>def __eq__(self, other): """x.__eq__ (y) <==> x == y"""
return (isinstance(oth er, self.__class__)

Since an instance of a subclass is an instance of a parent class, but not
vice versa, I believe you introduce here the assymetry you verify below.


Yes, the asymmetry is due to isinstance.

I believe what Peter Otten was pointing out is that calling __eq__ is
not the same as using ==, presumably because the code for == checks the
types of the two objects and returns False if they're different before
the __eq__ code ever gets called.

Steve
Jul 18 '05 #17
Steven Bethard <st************ @gmail.com> wrote:
Nick Craig-Wood wrote:
Steven Bethard <st************ @gmail.com> wrote:
I promised I'd put together a PEP for a 'generic object' data type for
Python 2.5 that allows one to replace __getitem__ style access with
dotted-attribute style access (without declaring another class). Any
comments would be appreciated!
My experience from using this is that whenever I used Hash(), I found
that later on in the refinement of the conversion it became its own
class.


This has also generally been my experience, though I'm not sure it's as
true for the XML DOM to Bunch translation. Did you use Hash() in the
same way for hierarchical data?


Hash() got nested yes, but not in a general purpose structure like
your XML example.
So my take on the matter is that this encourages perl style
programming (just ram it in a hash, and write lots of functions acting
on it) rather than creating a specific class for the job which is dead
easy in python anyway and to which you can attach methods etc.


You'll note that the (pre-)PEP explicitly notes that this object is
intended only for use when no methods are associated with the attributes:

"When no methods are to be associated with the attribute-value mappings,
declaring a new class can be overkill."

I do understand your point though -- people might not use Bunch in the
way it's intended. Of course, those same people can already do the same
thing with a dict instead (e.g. write a bunch of functions to handle a
certain type of dict). If someone wants to write Perl in Python,
there's not much we can really do to stop them...


No there isn't ;-)

The above does make it a lot more convenient though blob['foo'] is
rather difficult to type compared to blob.foo!

--
Nick Craig-Wood <ni**@craig-wood.com> -- http://www.craig-wood.com/nick
Jul 18 '05 #18
Scott David Daniels <Sc***********@ Acm.Org> wrote:
Nick Craig-Wood wrote:
class Hash:
def __init__(self, **kwargs):
for key,value in kwargs.items():
setattr(self, key, value)
def __getitem__(sel f, x):
return getattr(self, x)
def __setitem__(sel f, x, y):
setattr(self, x, y)


You can simplify this:
class Hash(object):
def __init__(self, **kwargs):
for key,value in kwargs.items():
setattr(self, key, value)
__getitem__ = getattr
__setitem__ = setattr


That doesn't work unfortunately.. .
class Hash(object): .... def __init__(self, **kwargs):
.... for key,value in kwargs.items():
.... setattr(self, key, value)
.... __getitem__ = getattr
.... __setitem__ = setattr
.... h=Hash(a=1,b=2)
h.a 1 h['a'] Traceback (most recent call last):
File "<stdin>", line 1, in ?
TypeError: getattr expected at least 2 arguments, got 1


I'm not exactly sure why though!
--
Nick Craig-Wood <ni**@craig-wood.com> -- http://www.craig-wood.com/nick
Jul 18 '05 #19
Nick Craig-Wood wrote:
Scott David Daniels <Sc***********@ Acm.Org> wrote:
Nick Craig-Wood wrote:
> class Hash:
> def __init__(self, **kwargs):
> for key,value in kwargs.items():
> setattr(self, key, value)
> def __getitem__(sel f, x):
> return getattr(self, x)
> def __setitem__(sel f, x, y):
> setattr(self, x, y)


You can simplify this:
class Hash(object):
def __init__(self, **kwargs):
for key,value in kwargs.items():
setattr(self, key, value)
__getitem__ = getattr
__setitem__ = setattr


That doesn't work unfortunately.. .
class Hash(object): ... def __init__(self, **kwargs):
... for key,value in kwargs.items():
... setattr(self, key, value)
... __getitem__ = getattr
... __setitem__ = setattr
... h=Hash(a=1,b=2)
h.a 1 h['a'] Traceback (most recent call last):
File "<stdin>", line 1, in ?
TypeError: getattr expected at least 2 arguments, got 1


I'm not exactly sure why though!


Functions written in Python have a __get__ attribute while builtin functions
(implemented in C) don't. Python-coded functions therefore automatically
act as descriptors while builtins are just another attribute. See

http://mail.python.org/pipermail/pyt...ay/219424.html

for a strange example.

Peter
Jul 18 '05 #20

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