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, [email protected] wrote:
Date: Wed, 16 Nov 2016 22:47:39 -0700 From: Charles R Harris<[email protected]> To: numpy-discussion<[email protected]>, SciPy Users List <[email protected]>, SciPy Developers List<[email protected]>, [email protected] 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
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