[Numpy-discussion] NumPy 1.16.0rc2 released

Hi All, On behalf of the NumPy team I'm pleased to announce the release of NumPy 1.16.0rc2. This is the last NumPy release to support Python 2.7 and will be maintained as a long term release with bug fixes until 2020. This release has seen a lot of refactoring and features many bug fixes, improve

Re: [Numpy-discussion] Ia `-fno-strict-aliasing` still required?

On Fri, Jan 4, 2019 at 1:14 PM Nathaniel Smith wrote: > This is a pretty good article on what -fno-strict-aliasing actually does: > https://blog.regehr.org/archives/1307 > > That was pretty much as I recalled. I'm guessing that what changed for NumPy was going to separate compilation and the wide

Re: [Numpy-discussion] Ia `-fno-strict-aliasing` still required?

This is a pretty good article on what -fno-strict-aliasing actually does: https://blog.regehr.org/archives/1307 -n On Fri, Jan 4, 2019, 09:36 Charles R Harris Hi All, > > Just asking if the `-fno-strict-aliasing` flag is still required for gcc. > Supposedly `-fstrict-aliasing` is enabled by defa

Re: [Numpy-discussion] Adding more detailed exception types to numpy

Since numpy generally does not expose parts as modules, I think a separate namespace for the exceptions makes sense. I prefer `np.exceptions` over `np.errors`. It might still make sense for that namespace to import from the different parts, i.e., also have `np.core.exceptions`, np.polynomial.excep

Re: [Numpy-discussion] Ia `-fno-strict-aliasing` still required?

On Fri, Jan 4, 2019 at 11:26 AM Neal Becker wrote: > Define "doing fine", does it pass all tests? > Yes. Chuck ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion

Re: [Numpy-discussion] Ia `-fno-strict-aliasing` still required?

Define "doing fine", does it pass all tests? On Fri, Jan 4, 2019 at 12:36 PM Charles R Harris wrote: > Hi All, > > Just asking if the `-fno-strict-aliasing` flag is still required for gcc. > Supposedly `-fstrict-aliasing` is enabled by default with optimization > levels >= `-O2` and that used to

[Numpy-discussion] Ia `-fno-strict-aliasing` still required?

Hi All, Just asking if the `-fno-strict-aliasing` flag is still required for gcc. Supposedly `-fstrict-aliasing` is enabled by default with optimization levels >= `-O2` and that used to result in errors. However, I have noticed that numpy wheels are being built without the `-fno-strict-aliasing` f

Re: [Numpy-discussion] Adding more detailed exception types to numpy

On Fri, Jan 4, 2019 at 8:18 AM Eric Wieser wrote: > PR #12593 adds a handful of > new exception types for . Some consequences of this change are that: > >1. The string formatting is moved to python, allowing us to give >better error messages wit

[Numpy-discussion] Adding more detailed exception types to numpy

PR #12593 adds a handful of new exception types for . Some consequences of this change are that: 1. The string formatting is moved to python, allowing us to give better error messages without a lot of work 2. The formatting is dispatched lazily,

Re: [Numpy-discussion] Debugging NumPy development build in conda environment

On 4/1/19 3:34 pm, Lars Grueter wrote: Unfortunately the last two commands stopped working out of the blue with my existing environment and fail with RuntimeError: Broken toolchain: cannot link a simple C program The compiler error is a few lines above this (copied below). When I have got

Re: [Numpy-discussion] Debugging NumPy development build in conda environment

> On Friday, Jan 04, 2019 at 2:44 PM, Lars Grueter (mailto:la...@mailbox.org)> wrote: > Dear devs, > > If this is the wrong place for this kind of question I apologize and > feel free to ignore this or point me to the right place. > > I'm using the conda package manager for my development environm

[Numpy-discussion] Debugging NumPy development build in conda environment

Dear devs, If this is the wrong place for this kind of question I apologize and feel free to ignore this or point me to the right place. I'm using the conda package manager for my development environment which used to work just fine with these steps: > conda create -n dev-numpy python=3.7 numpy