ANN: scikit-image 0.10.0

[Matthew Brett]

On Monday, June 2, 2014 4:05:03 PM UTC-7, Stéfan van der Walt wrote:
>
> On Tue, Jun 3, 2014 at 1:01 AM, Michael Aye <kmicha... at gmail.com 
> <javascript:>> wrote: 
> > I just went through a quite painful learning process with all this, 
> because 
> > the docs are quite scattered, with lots of old stuff mixed in. So I'd 
> like 
> > to comment, in case you don't insist on the Travis build machinery to be 
> > MacPython (is that even possible, as Travis runs on Linux?), to speed 
> things 
> > up IMMENSELY over using pip for requirements install, one can use conda 
> for 
> > the env setup in Travis. It speeds things up, because pip doesn't store 
> > binaries and instead spends a lot of time compiling things (or so it 
> says 
> > here: http://sburns.org/2014/03/28/faster-travis-builds.html). Find the 
> > instructions on how to setup Travis with conda in that link, I tried it 
> and 
> > it works fine here. 
> > I did one thing different compared to that blog entry though: In the 
> travis 
> > yaml I prefer to "script: python setup.py develop && python setup.py 
> test", 
> > because that way I don't get a useless test run in case the develop 
> install 
> > fails due to a bug. 
>
> This works great--I've used that approach for our Windows buildbot too. 
>
> On Linux, since we have apt-get, it's less of an issue, even though we 
> currently build Matplotlib from source to get the latest version. 
>

Some of us are building wheels for the travis linux machines too - see for 
example:

https://github.com/matthew-brett/nipy/blob/12f96d576be0b7c841a65b095ae0b70a22b36d2b/.travis.yml#L20

That gives me the latest released version of matplotlib.  The wheels are 
pretty easy to build too, just create a vagrant virtual machine, and you're 
ready to go:

https://gist.github.com/matthew-brett/714b50bd3159d416981a

Cheers,

Matthew

 
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