Since the NumPy API is forwards compatible, you should use the oldest version of NumPy you would like to support to build your wheels with. The wheels will then work with any future NumPy versions. On Fri, Nov 18, 2016 at 9:30 AM Peter Cock <p.j.a.cock@googlemail.com> wrote:
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?
Thanks
Peter
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@scipy.org wrote:
Date: Wed, 16 Nov 2016 22:47:39 -0700 From: Charles R Harris<charlesr.harris@gmail.com> To: numpy-discussion<numpy-discussion@scipy.org>, SciPy Users List <scipy-user@scipy.org>, SciPy Developers List<scipy-dev@scipy.org>, python-announce-list@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,
On Thu, Nov 17, 2016 at 11:24 PM, Matti Picus <matti.picus@gmail.com> wrote: this
is a milestone for PyPy's C-API compatibility layer.
Thanks to all,
Chuck
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