Thank you Chuck!
04.10.2016 5:15 пользователь "Charles R Harris"
написал:
> *Hi All,*
>
> I'm pleased to announce the release of Numpy 1.11.2. This release
> supports Python 2.6 - 2.7, and 3.2 - 3.5 and fixes bugs and regressions
> found in Numpy 1.11.1. Wheels for
Note that numpy does store some larger arrays already, in the fft
module. (In fact, this was a cache of unlimited size until #7686.) It
might not be bad if the same cache were used more generally.
That said, if newer versions of python are offering ways of doing this
better, maybe that is the
On Mon, Oct 3, 2016 at 7:15 PM, Charles R Harris
wrote:
> Hi All,
>
> I'm pleased to announce the release of Numpy 1.11.2. This release supports
> Python 2.6 - 2.7, and 3.2 - 3.5 and fixes bugs and regressions found in
> Numpy 1.11.1. Wheels for Linux, Windows, and OSX
On Sun, Oct 2, 2016 at 5:53 PM, Vincent Davis
wrote:
> +1, I am very skeptical of anything on SourceForge, it negatively impacts
> my opinion of any project that requires me to download from sourceforge.
>
>
> On Saturday, October 1, 2016, Charles R Harris
Mon, 03 Oct 2016 15:07:28 -0400, Benjamin Root kirjoitti:
> With regards to arguments about holding onto large arrays, I would like
> to emphasize that my original suggestion mentioned weakref'ed numpy
> arrays.
> Essentially, the idea is to claw back only the raw memory blocks during
> that limbo
With regards to arguments about holding onto large arrays, I would like to
emphasize that my original suggestion mentioned weakref'ed numpy arrays.
Essentially, the idea is to claw back only the raw memory blocks during
that limbo period between discarding the numpy array python object and when
On 03.10.2016 20:23, Chris Barker wrote:
>
>
> On Mon, Oct 3, 2016 at 3:16 AM, Julian Taylor
> >
> wrote:
>
> the problem with this approach is that we don't really want numpy
> hogging on to hundreds of megabytes of
On Mon, Oct 3, 2016 at 3:16 AM, Julian Taylor wrote:
> the problem with this approach is that we don't really want numpy
> hogging on to hundreds of megabytes of memory by default so it would
> need to be a user option.
>
indeed -- but one could set an LRU cache
Hi all,
I'm happy to announce pandas 0.19.0 has been released.
This is a major release from 0.18.1 and includes a number of API changes,
several new features, enhancements, and performance improvements along with
a large number of bug fixes. See the Whatsnew