[IPython-dev] Docker IPython

[Brian Granger]

I think a more useful way of approaching this would be to ask the
following: what layers of docker images are useful? Here are some
ideas:

Base: ipython and its deps, installed using system packages or pip
Base+SciPy: Base plus the extended scipy stack installed using system
packages or pip
Base+R kernel
Base+Julia kernel
...
Conda/Anaconda version: ipython and deps installed using conda. We
should talk to Continuum about this

Question, do docker images have ways of pulling from multiple parents?

Cheers,

Brian

On Tue, Aug 5, 2014 at 9:34 PM, Geoff Oxberry <goxberry at gmail.com> wrote:
> In case chiming in matters, I'm vehemently opposed to conda in a base image,
> because I think conda would be a great package manager if it didn't try to
> do too much (as of Anaconda 1.9, it was also managing Python version, and
> managing/creating virtualenvs). If it's in an "extended" derivative image,
> that's fine by me. I agree that pip is more standard, and conda is good for
> installing things (and only good for installing things).
>
>
> On Tue, Aug 5, 2014 at 6:40 PM, Dave Hirschfeld <dave.hirschfeld at gmail.com>
> wrote:
>>
>> Fernando Perez <fperez.net <at> gmail.com> writes:
>>
>> >
>> >
>> >
>> > On Tue, Aug 5, 2014 at 11:11 AM, Thomas Kluyver <takowl <at> gmail.com>
>> wrote:If you call it scipystack, please put Sympy and nose in as well - a
>> long and heated discussion last year settled on a core set of packages
>> that distributions describing themselves as shipping the Scipy Stack
>> should include:http://www.scipy.org/stackspec.html
>> >
>> >
>> > +1. Let's use the 'scipy stack' term as per the above.
>> >
>> >
>> >
>> >
>> > I actually would vote for the 'extended' stack, that includes a few
>> packages that in the real world lots of people do use/need, like
>> sklearn/image. Here's a slightly outdated version of that:
>> >
>> >
>> > https://speakerdeck.com/fperez/pydata-2013-keynote-ipython-and-friends?
>> slide=8
>> >
>> >
>> > Today I'd probably drop Mayav/PyTables (too specialized) but add
>> Seaborn (lightweight, easy, plays beautifully with pandas).
>> >
>> > That would make a very compelling image out of the box, with minimal
>> additional complexity (while there's extension code in those, none of
>> them are harder than scipy itself).
>> >
>> >
>> >
>> >
>> > Cheers,
>> >
>> > f-- Fernando Perez ( <at> fperez_org; http://fperez.org)
>>
>> PyTables could be handy as it's an optional dependency for pandas which
>> IIUC allows you to store pandas objects in hdf5 via the HDFStore which is
>> becoming a very common way to store pandas objects.
>>
>> -Dave
>>
>>
>>
>>
>> _______________________________________________
>> IPython-dev mailing list
>> IPython-dev at scipy.org
>> http://mail.scipy.org/mailman/listinfo/ipython-dev
>
>
>
>
> --
> Geoffrey Oxberry, Ph.D., E.I.T.
> goxberry at gmail.com
>
> _______________________________________________
> IPython-dev mailing list
> IPython-dev at scipy.org
> http://mail.scipy.org/mailman/listinfo/ipython-dev
>



-- 
Brian E. Granger
Cal Poly State University, San Luis Obispo
@ellisonbg on Twitter and GitHub
bgranger at calpoly.edu and ellisonbg at gmail.com