PEP-574 isn't on the roadmap (yet!), but I think we would clearly welcome
it. Like all NumPy improvements, it would need to implemented by an
interested party.
On Mon, Jun 4, 2018 at 1:52 AM Antoine Pitrou wrote:
>
> Hi,
>
> Do you plan to consider trying to add PEP 574 / pickle5 support? There's
Hi,
Do you plan to consider trying to add PEP 574 / pickle5 support? There's
an implementation ready (and a PyPI backport) that you can play with.
https://www.python.org/dev/peps/pep-0574/
PEP 574 implicits targets Numpy arrays as one of its primary producers,
since Numpy arrays is how large sc
On Thu, May 31, 2018 at 5:50 PM, Matti Picus wrote:
> At the recent NumPy sprint at BIDS (thanks to those who made the trip) we
> spent some time brainstorming about a roadmap for NumPy, in the spirit of
> similar work that was done for Jupyter. The idea is that a document with
> wide community a
I like the idea of a random/controversial ideas section.
On Fri, Jun 1, 2018 at 12:11 PM, Ralf Gommers wrote:
>
>
> On Fri, Jun 1, 2018 at 9:57 AM, Stefan van der Walt
> wrote:
>>
>> Hi Ralf,
>>
>> On Thu, 31 May 2018 21:57:06 -0700, Ralf Gommers wrote:
>> > - "internal refactorings": MaskedArra
On Fri, Jun 1, 2018 at 9:57 AM, Stefan van der Walt
wrote:
> Hi Ralf,
>
> On Thu, 31 May 2018 21:57:06 -0700, Ralf Gommers wrote:
> > - "internal refactorings": MaskedArray yes, but the other ones no.
> > numpy.distutils and f2py are very hard to test, a big refactor pretty
> much
> > guarantees
While we are in the crazy wish-list: having dtypes that are universal
enough for pandas to use them and export their columns with them would be
my crazy wish. I hope that it would help adding more uniform support for
things like categorical variables in the pydata ecosystem.
Gaël
_
I would love to see gufuncs become more general. Specifically I would like
an optional prologue and epilogue function. The prologue could potentially
1) inspect parameterized dtypes 2) kwargs 3) set non-trivial output array
sizes 4) initialize data structures 5) defer processing to other functions
On Fri, Jun 1, 2018 at 9:46 AM, Chris Barker wrote:
> numpy is also quite a bit slower than raw python for math with (very)
> small arrays:
>
doing a bit more experimentation, the advantage is with pure python for
over 10 elements (I got bored...). but I noticed that the time for numpy
computati
Hi Ralf,
On Thu, 31 May 2018 21:57:06 -0700, Ralf Gommers wrote:
> - "internal refactorings": MaskedArray yes, but the other ones no.
> numpy.distutils and f2py are very hard to test, a big refactor pretty much
> guarantees breakage. there's also not much need for refactoring, because
> those thin
On Fri, Jun 1, 2018 at 4:43 AM, Marten van Kerkwijk <
m.h.vankerkw...@gmail.com> wrote:
> one thing that always slightly annoyed me is that numpy math is way
> slower for scalars than python math
>
numpy is also quite a bit slower than raw python for math with (very) small
arrays:
In [31]: % t
On Fri, Jun 1, 2018, 11:27 Todd wrote:
>
>
> On Thu, May 31, 2018, 19:50 Matti Picus wrote:
>
>> At the recent NumPy sprint at BIDS (thanks to those who made the trip)
>> we spent some time brainstorming about a roadmap for NumPy, in the
>> spirit of similar work that was done for Jupyter. The i
On Thu, May 31, 2018, 19:50 Matti Picus wrote:
> At the recent NumPy sprint at BIDS (thanks to those who made the trip)
> we spent some time brainstorming about a roadmap for NumPy, in the
> spirit of similar work that was done for Jupyter. The idea is that a
> document with wide community accept
Hi Matti,
Thanks for sharing the roadmap. Overall, it looks very nice. A practical
question is on whether you want input via the mailing list, or should one
just edit the wiki and add questions or so?
As the roadmap mentioned interaction with python proper (and a possible
PEP): one thing that alw
On Thu, May 31, 2018 at 4:50 PM, Matti Picus wrote:
> At the recent NumPy sprint at BIDS (thanks to those who made the trip) we
> spent some time brainstorming about a roadmap for NumPy, in the spirit of
> similar work that was done for Jupyter. The idea is that a document with
> wide community a
At the recent NumPy sprint at BIDS (thanks to those who made the trip)
we spent some time brainstorming about a roadmap for NumPy, in the
spirit of similar work that was done for Jupyter. The idea is that a
document with wide community acceptance can guide the work of the
full-time developer(s)
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