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Comments sought for PEP 357 --- allowing any object in slice syntax

This post is to gather feedback from the wider community on PEP 357. It
is nearing the acceptance stage and has previously been discussed on
python-dev. This is a chance for the wider Python community to comment
on the proposal.

You will find the PEP attached

PEP: 357
Title: Allowing Any Object to be Used for Slicing
Version: $Revision: 42549 $
Last Modified: $Date: 2006-02-21 21:00:18 -0700 (Tue, 21 Feb 2006) $
Author: Travis Oliphant <ol******@ee.byu.edu>
Status: Draft
Type: Standards Track
Created: 09-Feb-2006
Python-Version: 2.5


This PEP proposes adding an nb_index slot in PyNumberMethods and an
__index__ special method so that arbitrary objects can be used
whenever integers are explicitly needed in Python, such as in slice
syntax (from which the slot gets its name).


Currently integers and long integers play a special role in
slicing in that they are the only objects allowed in slice
syntax. In other words, if X is an object implementing the
sequence protocol, then X[obj1:obj2] is only valid if obj1 and
obj2 are both integers or long integers. There is no way for obj1
and obj2 to tell Python that they could be reasonably used as
indexes into a sequence. This is an unnecessary limitation.

In NumPy, for example, there are 8 different integer scalars
corresponding to unsigned and signed integers of 8, 16, 32, and 64
bits. These type-objects could reasonably be used as integers in
many places where Python expects true integers but cannot inherit from
the Python integer type because of incompatible memory layouts.
There should be some way to be able to tell Python that an object can
behave like an integer.

It is not possible to use the nb_int (and __int__ special method)
for this purpose because that method is used to *coerce* objects
to integers. It would be inappropriate to allow every object that
can be coerced to an integer to be used as an integer everywhere
Python expects a true integer. For example, if __int__ were used
to convert an object to an integer in slicing, then float objects
would be allowed in slicing and x[3.2:5.8] would not raise an error
as it should.


Add an nb_index slot to PyNumberMethods, and a corresponding
__index__ special method. Objects could define a function to place
in the nb_index slot that returns an appropriate C-integer (Py_ssize_t
after PEP 353). This C-integer will be used whenever Python needs
one such as in PySequence_GetSlice, PySequence_SetSlice, and


1) The nb_index slot will have the signature

Py_ssize_t index_func (PyObject *self)

2) The __index__ special method will have the signature

def __index__(self):
return obj

where obj must be either an int or a long.

3) A new C-API function PyNumber_Index will be added with signature

Py_ssize_t PyNumber_Index (PyObject *obj)

which will return obj->ob_type->tp_as_number->nb_index(obj) if it is available.
A -1 will be returned and an exception set on an error.

4) A new operator.index(obj) function will be added that calls
equivalent of obj.__index__() and raises an error if obj does not implement
the special method.

Implementation Plan

1) Add the nb_index slot in object.h and modify typeobject.c to
create the __index__ method

2) Change the ISINT macro in ceval.c to ISINDEX and alter it to
accomodate objects with the index slot defined.

3) Change the _PyEval_SliceIndex function to accomodate objects
with the index slot defined.

4) Change all builtin objects (e.g. lists) that use the as_mapping
slots for subscript access and use a special-check for integers to
check for the slot as well.

5) Add the nb_index slot to integers and long_integers.

6) Add PyNumber_Index C-API to return an integer from any
Python Object that has the nb_index slot.

7) Add the operator.index(x) function.
Discussion Questions


Implementation should not slow down Python because integers and long
integers used as indexes will complete in the same number of
instructions. The only change will be that what used to generate
an error will now be acceptable.

Why not use nb_int which is already there?

The nb_int method is used for coercion and so means something
fundamentally different than what is requested here. This PEP
proposes a method for something that *can* already be thought of as
an integer communicate that information to Python when it needs an
integer. The biggest example of why using nb_int would be a bad
thing is that float objects already define the nb_int method, but
float objects *should not* be used as indexes in a sequence.

Why the name __index__?

Some questions were raised regarding the name __index__ when other
interpretations of the slot are possible. For example, the slot
can be used any time Python requires an integer internally (such
as in "mystring" * 3). The name was suggested by Guido because
slicing syntax is the biggest reason for having such a slot and
in the end no better name emerged. See the discussion thread:
for examples of names that were suggested such as "__discrete__" and

Why return Py_ssize_t from nb_index?

The nb_index slot is primarily intended to return an integer
needed by the sequence interface. In Python 2.5 this is
Py_ssize_t. As this is the primary purpose of the slot, it
makes sense to return the C-integer directly and not wrapped
in a Python int object.

Why can't __index__ return any object with the nb_index method?

This would allow infinite recursion in many different ways that are not
easy to check for. This restriction is similar to the requirement that
__nonzero__ return an int or a bool.

Reference Implementation

Submitted as patch 1436368 to SourceForge.


This document is placed in the public domain

Mar 4 '06 #1
0 1217

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