On Thu, Jun 5, 2014 at 8:58 AM, Todd <[email protected]> wrote:

>
> On 5 Jun 2014 14:28, "David Cournapeau" <[email protected]> wrote:
> >
> >
> >
> >
> > On Thu, Jun 5, 2014 at 9:44 AM, Todd <[email protected]> wrote:
> >>
> >>
> >> On 5 Jun 2014 02:57, "Nathaniel Smith" <[email protected]> wrote:
> >> >
> >> > On Wed, Jun 4, 2014 at 7:18 AM, Travis Oliphant <[email protected]>
> 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?
> >
> >
> > There has been discussions about integrating numpy a long time ago
> (can't find a reference right now), and the consensus was that this was
> possible in its current shape nor advisable. The situation has not changed.
> >
> > Putting something in the stdlib means it basically cannot change
> anymore: API compatibility requirements would be stronger than what we
> provide even now. NumPy is also a large codebase which would need some
> major clean up to be accepted, etc...
> >
> > David
>
> I am not suggesting merging all of numpy, only ndarray and dtype (which I
> know is a huge job itself).  And perhaps not even all of what us currently
> included in those, some methods could be split out to their own functions.
>
> And any numpy 2.0 would also imply a major code cleanup.  So although
> ndarray and dtype are certainly not ready for such a thing right now, if
> you are talking about numpy 2.0 already, perhaps part of that discussion
> could involve a plan to get the code into a state where such a move might
> be plausible.  Even if the merge doesn't actually happen, having the code
> at that quality level would still be a good thing.
>
> I agree that the relationship between numpy and python has not changed
> very much in the last few years, but I think the scientific computing
> landscape is changing.  The latter issue is where my primary concern lies.
>
I don't think it would have any effect on scientific computing users. It
might be useful for other users that occasionally want to do a bit of array
processing.

Scientific users need the extended SciPy stack and not a part of numpy that
can be imported from the standard library.
For example in "Data Science", where I pay more attention and where Python
is getting pretty popular, the usual recommended list requires numpy scipy
and 5 to 10 more python libraries.

Should pandas also go into the python standard library?
Python 3.4 got a statistics library, but I don't think it has any effect on
the potential statsmodels user base.

Josef


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