[IPython-dev] Multi-user IPython Notebook

[MinRK]

The authentication is customizable. I wrote the OAuth example as a test
case for this customizability. Anything that takes a username and password
should be quite simple. We are still working on what the API should be, but
it works right now. It is not planned, however, for JupyterHub to support
Windows at all.

-MinRK


On Fri, Oct 3, 2014 at 1:11 PM, Brian Granger <ellisonbg at gmail.com> wrote:

> No but we are accepting PRs!
>
> On Fri, Oct 3, 2014 at 1:09 PM, Kenneth Tran <one at kentran.net> wrote:
> > Are there any instructions on how to get JupyterHub work on Windows using
> > Active Directory or using Online Microsoft accounts?
> >
> > Fernando mentioned that we can plug-in a custom authenticator (or
> something
> > like this). I want to know more details.
> >
> > Thanks.
> > -Ken
> >
> >
> > On Fri, Oct 3, 2014 at 11:57 AM, Brian Granger <ellisonbg at gmail.com>
> wrote:
> >>
> >> (Kyle, working at Rackspace, might not volunteer this information in
> >> this context)
> >>
> >> I highly recommend looking at Rackspace's OnMetal Servers for
> >> performance critical things that you want to cost contain.
> >>
> >> Cheers,
> >>
> >> Brian
> >>
> >> On Fri, Oct 3, 2014 at 11:18 AM, ssanderson <ssanderson at quantopian.com>
> >> wrote:
> >> > Kyle,
> >> >
> >> > Currently we're spinning up new containers manually over SSH using
> >> > Fabric.
> >> > The container we're running is conceptually pretty similar to the
> >> > scipyserver container in  docker-notebook
> >> > <https://github.com/ipython/docker-notebook>  .  At the moment we're
> not
> >> > doing any sort of proxying, so each single user server just gets its
> own
> >> > unique URL and password, which is supplied to its user.
> >> >
> >> > As far as how many containers we run per host, we're still playing
> >> > around
> >> > with different instance types and resource limits, so we haven't
> settled
> >> > on
> >> > a specific number.  One of the challenges for us is that different
> >> > research
> >> > activities have radically different performance profiles.  For
> example,
> >> > querying historical financial data is mostly IO-bound, analyses of
> large
> >> > datasets are often constrained by RAM, and backtesting with in-memory
> >> > data
> >> > is primarily CPU-bound (in my dream world, we can farm out the
> CPU-bound
> >> > tasks to pool of worker containers using IPython Parallel, but that's
> a
> >> > ways
> >> > off).   That said, I think our current ballpark is to run on the order
> >> > of 10
> >> > containers per host.
> >> >
> >> >
> >> >
> >> > --
> >> > View this message in context:
> >> >
> http://python.6.x6.nabble.com/Multi-user-IPython-Notebook-tp5073520p5073582.html
> >> > Sent from the IPython - Development mailing list archive at
> Nabble.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
> >> _______________________________________________
> >> IPython-dev mailing list
> >> IPython-dev at scipy.org
> >> http://mail.scipy.org/mailman/listinfo/ipython-dev
> >
> >
> >
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> > 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
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