Re: [Numpy-discussion] Dropping Python 3.4 support for NumPy 1.16

It was a small task. I created a PR for it here . Feel free to merge after CI passes or close. Hameer Abbasi Sent from Astro for Mac On 14. Jun 2018 at 22:50, Marten van Kerkwijk wrote: It seems everyone is in favour -

Re: [Numpy-discussion] Circle CI moving from 1.0 to 2.0

Hi Matti, It seems the CircleCI config is already on Version 2.0. See here, notice the 2.0 in front of every successful build. https://circleci.com/gh/numpy/numpy I can also see that some failed builds have 1.0 in front of them... But this shouldn't happen. Most likely this is a CircleCI issue,

[Numpy-discussion] Circle CI moving from 1.0 to 2.0

I stumbled across this notice (only seems to appear in a failed build) "This project is currently running on CircleCI 1.0 which will no longer be supported after August 31, 2018. Please start migrating this project to CircleCI 2.0 ." Here is the

Re: [Numpy-discussion] Dropping Python 3.4 support for NumPy 1.16

It is a welcome thing to see Python 2.7 support disappearing. Dropping 3.4 support in new releases sounds like a great idea as well. NumPy was originally pitched as a Python 3 thing... Travis On Thu, Jun 14, 2018, 12:52 PM Marten van Kerkwijk < m.h.vankerkw...@gmail.com> wrote: > It seems

Re: [Numpy-discussion] Dropping Python 3.4 support for NumPy 1.16

It seems everyone is in favour - anybody in for making a PR reducing the travis testing accordingly? (It seems a bit of overkill more generally - would be good to reduce the kWhr footprint a little...) -- Marten ___ NumPy-Discussion mailing list

Re: [Numpy-discussion] Updated 1.15.0 release notes

Indeed, we do something similar in astropy, with a pre-release failure being considered breakage (rather than ignorable as for -dev): https://github.com/astropy/astropy/blob/master/.travis.yml#L142 ​-- Marten ___ NumPy-Discussion mailing list

Re: [Numpy-discussion] Updated 1.15.0 release notes

Hi Nathan, One very helpful think you could do, is add a Travis-CI matrix entry where you are testing against the latest numpy nightly builds. I got a bit lost in your tox setup, but the basic idea is that, for one test entry, you add the following flags to pip: -f