[Numpy-discussion] big-bangs versus incremental improvements (was: Re: SciPy 2014 BoF NumPy Participation)

[Todd]

On 5 Jun 2014 02:57, "Nathaniel Smith" <njs at pobox.com> wrote:
>
> On Wed, Jun 4, 2014 at 7:18 AM, Travis Oliphant <travis at continuum.io>
wrote:
> And numpy will be much harder to replace than numeric --
> numeric wasn't the most-imported package in the pythonverse ;-).

If numpy is really such a core part of  python ecosystem, does it really
make sense to keep it as a stand-alone package?  Rather than thinking about
a numpy 2, might it be better to be focusing on getting ndarray and dtype
to a level of quality where acceptance upstream might be plausible?

Matlab and python are no longer the only games in town for scientific
computing anymore.  I worry that the lack of a multidimensional array
literals, not to mention the lack of built-in multidimensional arrays at
all, can only hurt python's attractiveness compared to languages like Julia
long-term.

For people who already know and love python, this doesn't bother us much if
at all.  But thinking of attracting new users long-term, I worry that it
will be harder to convince outsiders that python is really a first-class
scientific computing language when it lacks the key data type for
scientific computing.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20140605/e3c6e7bd/attachment.html>