[SciPy-dev] A proposal for dtype/dtypedescr in numpy objects

Francesc Altet faltet at carabos.com
Thu Jan 5 15:40:57 CST 2006


Hi,

In my struggle for getting consistent behaviours with data types, I've
ended with a new proposal for treating them. The basic thing is that I
suggest to deprecate .dtype as being a first-class attribute and
replace it instead by the descriptor type container, which I find
quite more useful for end users. The current .dtype type will be still
accessible (mainly for developers) but buried in .dtype.type.

Briefly stated:

current             proposed
=======             ========
.dtypedescr     --> moved into .dtype
.dtype          --> moved into .dtype.type
.dtype.dtypestr --> moved into .dtype.str
                    new .dtype.name

What is achieved with that? Well, not much, except easy of use and
type comparison correctness. For example, with the next setup:

>>> import numpy
>>> a=numpy.arange(10,dtype='i')
>>> b=numpy.arange(10,dtype='l')

we have currently:

>>> a.dtype
<type 'int32_arrtype'>
>>> a.dtypedescr
dtypedescr('<i4')
>>> a.dtypedescr.dtypestr
'<i4'
>>> a.dtype.__name__[:-8]
'int32'
>>> a.dtype == b.dtype
False

With the new proposal, we would have:

>>> a.dtype.type
<type 'int32_arrtype'>
>>> a.dtype
dtype('<i4')
>>> a.dtype.str
'<i4'
>>> a.dtype.name
'int32'
>>> a.dtype == b.dtype
True

The advantages of the new proposal are:

- No more .dtype and .dtypedescr lying together, just current
  .dtypedescr renamed to .dtype. I think that current .dtype does not
  provide more useful information than current .dtypedesc, and giving
  it a shorter name than .dtypedescr seems to indicate that it is more
  useful to users (and in my opinion, it isn't).

- Current .dtype is still accessible, but specifying and extra name in
  path: .dtype.type (can be changed into .dtype.type_ or
  whatever). This should be useful mainly for developers.

- Added a useful dtype(descr).name so that one can quickly access to
  the type name.

- Comparison between data types works as it should now (without having
  to create a metaclass for PyType_Type).

Drawbacks:

- Backward incompatible change. However, provided the advantages are
  desirable, I think it is better changing now than later.

- I don't specially like the string representation for the new .dtype
  class. For example, I'd find dtype('Int32') much better than
  dtype('<i4'). However, this would represent more changes in the
  code, but they can be made later on (much less disruptive than the
  proposed change).

- Some other issues that I'm not aware of.


I'm attaching the patch for latest SVN. Once applied (please, pay
attention to the "XXX" signs in patched code), it passes all tests.
However, it may remain some gotchas (specially those cases that are
not checked in current tests). In case you are considering this change
to check in, please, tell me and I will revise much more carefully the
patch. If don't, never mind, it has been a good learning experience
anyway.

Uh, sorry for proposing this sort of things in the hours previous to a
public release of numpy.

-- 
>0,0<   Francesc Altet     http://www.carabos.com/
V   V   Cárabos Coop. V.   Enjoy Data
 "-"


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