[Numpy-discussion] NumPy 1.12.0b1 released

Peter Cock p.j.a.cock at googlemail.com
Fri Nov 18 09:30:33 EST 2016

I have a related question to Matti's,

Do you have any recommendations for building standard wheels
for 3rd party Python libraries which use both the NumPy Python
and C API?

e.g. Do we need to do anything special given the NumPy C API
itself is versioned? Does it matter compiler chain should we use?



On Thu, Nov 17, 2016 at 11:24 PM, Matti Picus <matti.picus at gmail.com> wrote:
> Congrats to all on the release.Two questions:
> Is there a guide to building standard wheels for NumPy?
> Assuming I can build standardized PyPy 2.7 wheels for Ubuntu, Win32 and
> OSX64, how can I get them blessed and uploaded to PyPI?
> Matti
> On 17/11/16 07:47, numpy-discussion-request at scipy.org wrote:
>> Date: Wed, 16 Nov 2016 22:47:39 -0700
>> From: Charles R Harris<charlesr.harris at gmail.com>
>> To: numpy-discussion<numpy-discussion at scipy.org>, SciPy Users List
>>         <scipy-user at scipy.org>,  SciPy Developers
>> List<scipy-dev at scipy.org>,
>>         python-announce-list at python.org
>> Subject: [Numpy-discussion] NumPy 1.12.0b1 released.
>> Hi All,
>> I'm pleased to annouce the release of NumPy 1.12.0b1. This release
>> supports  Python 2.7 and 3.4 - 3.6 and is the result of 388 pull requests
>> submitted by 133 contributors. It is quite sizeable and rather than put
>> the
>> release notes inline I've attached them as a file and they may also be
>> viewed at Github<https://github.com/numpy/numpy/releases/tag/v1.12.0b1>.
>> Zip files and tarballs may also be found the Github link. Wheels and
>> source
>> archives may be downloaded from PyPI, which is the recommended method.
>> This release is a large collection of fixes, enhancements, and
>> improvements
>> and it is difficult to select just a few as highlights. However, the
>> following enhancements may be of particular interest
>>     - Order of operations in ``np.einsum`` now can be optimized for large
>>     speed improvements.
>>     - New ``signature`` argument to ``np.vectorize`` for vectorizing with
>>     core dimensions.
>>     - The ``keepdims`` argument was added to many functions.
>>     - Support for PyPy 2.7 v5.6.0 has been added. While not complete, this
>>     is a milestone for PyPy's C-API compatibility layer.
>> Thanks to all,
>> Chuck
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at scipy.org
> https://mail.scipy.org/mailman/listinfo/numpy-discussion

More information about the NumPy-Discussion mailing list