[IPython-dev] Options for cloud-based Jupyterhub for Python training?

[Signell, Richard]

We would be fine with Python 2 and Jupyter in
https://cloud.sagemath.com would be fine if those packages were
installed for all projects.

But some of those packages are tough to build, and getting the right
versions that all play nice together is tricky.   That's why we have
our conda channel.   We have put a lot of effort into that.    Do you
have the ability to install from the binstar.org/ioos channel?

We don't need heavy duty computational facilities.   This is mostly
about accessing and visualizing met/ocean data.

On Wed, Apr 22, 2015 at 5:20 PM, William Stein <wstein at gmail.com> wrote:
> On Wed, Apr 22, 2015 at 2:14 PM, Signell, Richard <rsignell at usgs.gov> wrote:
>> William,
>>
>> I mean a python environment with these packages installed from our
>> binstar channel (http://conda.binstar.org):
>>
>> iris
>> mpld3
>> pyoos
>> pandas
>> folium
>> rdflib
>> geojson
>> requests
>> ipython-notebook
>> xlrd
>> mplleaflet
>> oceans
>> qrcode
>> utilities
>
> Does Python 2 versus Python 3 matter?
>
> Also, if you've tried Jupyter in https://cloud.sagemath.com, would it
> be sufficient to meet your needs if it had the above packages
> installed for all projects?
>
> Also, how powerful of computing facilities would be required?
>
>>
>> On Wed, Apr 22, 2015 at 5:09 PM, William Stein <wstein at gmail.com> wrote:
>>> On Wed, Apr 22, 2015 at 2:06 PM, Signell, Richard <rsignell at usgs.gov> wrote:
>>>> Jupyterhub folks,
>>>>
>>>> We are looking for solutions for one week of Python training for about
>>>> 50 met-ocean students at the NSF-funded Unidata Program Center in
>>>> Boulder (in June).  And we are thinking Jupyterhub on the cloud.
>>>>
>>>> We know that Software Carpentry favors students to install on their
>>>> own laptops, but we are leaning toward a cloud solution to demonstrate
>>>> the advantages of computing close to large met-ocean datasets.  And we
>>>> could also set up a common environment with packages used in the
>>>> met-ocean community (e.g. http://conda.binstar.org/ioos).
>>>>
>>>> We read this article
>>>> https://developer.rackspace.com/blog/deploying-jupyterhub-for-education/
>>>> which is similar to what we would like to set up, but the setup
>>>> sounded rather harrowing.
>>>>
>>>> Are there other solutions that would take less setup, yet allow us a
>>>> multi-user notebook login with cloud resources with a shared custom
>>>> env?
>>>
>>> Could you elaborate on what you mean by "a shared custom environment".
>>> https://cloud.sagemath.com, which I run, is zero setup, and can easily
>>> handle the load of 50 people (we often have 600-700 simultaneous
>>> users).   However, there's no notion of shared custom environment, so
>>> it might not work at all for you.
>>>
>>>  -- William
>>>
>>>>
>>>> Thanks,
>>>> Rich
>>>>
>>>> --
>>>> Dr. Richard P. Signell   (508) 457-2229
>>>> USGS, 384 Woods Hole Rd.
>>>> Woods Hole, MA 02543-1598
>>>> _______________________________________________
>>>> IPython-dev mailing list
>>>> IPython-dev at scipy.org
>>>> http://mail.scipy.org/mailman/listinfo/ipython-dev
>>>
>>>
>>>
>>> --
>>> William (http://wstein.org)
>>> _______________________________________________
>>> IPython-dev mailing list
>>> IPython-dev at scipy.org
>>> http://mail.scipy.org/mailman/listinfo/ipython-dev
>>
>>
>>
>> --
>> Dr. Richard P. Signell   (508) 457-2229
>> USGS, 384 Woods Hole Rd.
>> Woods Hole, MA 02543-1598
>> _______________________________________________
>> IPython-dev mailing list
>> IPython-dev at scipy.org
>> http://mail.scipy.org/mailman/listinfo/ipython-dev
>
>
>
> --
> William (http://wstein.org)
> _______________________________________________
> IPython-dev mailing list
> IPython-dev at scipy.org
> http://mail.scipy.org/mailman/listinfo/ipython-dev



-- 
Dr. Richard P. Signell   (508) 457-2229
USGS, 384 Woods Hole Rd.
Woods Hole, MA 02543-1598