Title: Allowing Any Object to be Used for Slicing
Author: Travis Oliphant <firstname.lastname@example.org>
Type: Standards Track
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 a Python integer
(either an int or a long). This integer can
then be appropriately converted to a Py_ssize_t value whenever
Python needs one such as in PySequence_GetSlice,
PySequence_SetSlice, and PySequence_DelSlice.
1) The nb_index slot will have the following signature
PyObject *index_func (PyObject *self)
The returned object must be a Python IntType or
Python LongType. NULL should be returned on
error with an appropriate error set.
2) The __index__ special method will have the signature
where obj must be either an int or a long.
3) 3 new abstract C-API functions will be added
a) The first checks to see if the object supports the index
slot and if it is filled in.
This will return true if the object defines the nb_index
b) The second is a simple wrapper around the nb_index call that
raises PyExc_TypeError if the call is not available or if it
doesn't return an int or long. Because the
PyIndex_Check is performed inside the PyNumber_Index call
you can call it directly and manage any error rather than
check for compatibility first.
PyObject *PyNumber_Index (PyObject *obj)
c) The third call helps deal with the common situation of
actually needing a Py_ssize_t value from the object to use for
indexing or other needs.
Py_ssize_t PyNumber_AsSsize_t(PyObject *obj, PyObject *exc)
The function calls the nb_index slot of obj if it is
available and then converts the returned Python integer into
a Py_ssize_t value. If this goes well, then the value is
returned. The second argument allows control over what
happens if the integer returned from nb_index cannot fit
into a Py_ssize_t value.
If exc is NULL, then the returnd value will be clipped to
PY_SSIZE_T_MAX or PY_SSIZE_T_MIN depending on whether the
nb_index slot of obj returned a positive or negative
integer. If exc is non-NULL, then it is the error object
that will be set to replace the PyExc_OverflowError that was
raised when the Python integer or long was converted to Py_ssize_t.
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.
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 accommodate 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
(which just return themselves)
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.
8) Alter arrayobject.c and mmapmodule.c to use the new C-API for their
sub-scripting and other needs.
9) Add unit-tests
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 PyObject * from nb_index?
Intially Py_ssize_t was selected as the return type for the
nb_index slot. However, this led to an inability to track and
distinguish overflow and underflow errors without ugly and brittle
hacks. As the nb_index slot is used in at least 3 different ways
in the Python core (to get an integer, to get a slice end-point,
and to get a sequence index), there is quite a bit of flexibility
needed to handle all these cases. The importance of having the
necessary flexibility to handle all the use cases is critical.
For example, the initial implementation that returned Py_ssize_t for
nb_index led to the discovery that on a 32-bit machine with >=2GB of RAM
s = 'x' * (2**100) works but len(s) was clipped at 2147483647.
Several fixes were suggested but eventually it was decided that
nb_index needed to return a Python Object similar to the nb_int
and nb_long slots in order to handle overflow correctly.
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.
Submitted as patch 1436368 to SourceForge.
This document is placed in the public domain.