[IPython-dev] Docker IPython

[Tyler Erickson]

On Mon, Aug 4, 2014 at 10:33 PM, Kyle Kelley <rgbkrk at gmail.com> wrote:

> Tyler,
>
> Taking in everyones comments and my opinion as a not-quite-sysadmin:
>
> Base image, ipython/notebook, will
>
> * have just the ipython notebook essentials
> * up to date (as of image build) version of pip (or conda... plead for one
> or the other please!)
>

conda, please :)


> * be installed for all users (all users inside the container)
>   * This means that any images inheriting from it can set up their own
> user setup, install more packages
>

Sounds fine to me.


> * default cmd that runs the notebook server with some default parameters
>   * This can be overwritten by a Dockerfile that uses FROM ipython/notebook
>
> My personal take on this is that we could have an ipy user, with notebooks
> at /home/ipy/notebooks.
>

Sounds reasonable. I have no strong opinion.


> Derivative image, ipython/scipystack (please suggest other names), could be
>
> * numpy
> * scipy
> * matplotlib
> * pandas
> * scikit-learn
>

I would be happy with that list.

Cheers,
Tyler



> For an IHaskell base image, I'd prefer the namespace to actually be
> jupyter/ihaskell in the long run.
>
> There may come a time when we want multiple kernels in one container.
> After all, have you seen what you can do with the current master branch?
>
>
>
>
> Including all the kernels (and stacks) will make a hefty docker image
> though, so I won't progress down that path just yet.
>
>
>
> On Mon, Aug 4, 2014 at 4:52 PM, Tyler Erickson <tylere at google.com> wrote:
>
>> Kyle,
>>
>> I think having an official base Docker instance will be quite useful,
>> especially for running workshops.
>>
>> I added comments for my particular use case below.
>>
>> On Fri, Aug 1, 2014 at 6:54 PM, Kyle Kelley <rgbkrk at gmail.com> wrote:
>>
>>> Earlier this week we released an experimental base Docker image for the
>>> IPython notebook:
>>>
>>> https://registry.hub.docker.com/u/ipython/notebook/
>>>
>>> As well as a Docker image for the notebook viewer (which will be used in
>>> production soon):
>>>
>>> https://registry.hub.docker.com/u/ipython/nbviewer/
>>>
>>> Yay!
>>>
>>> Several folks have reached out about these images, and I'd like to get a
>>> conversation started amongst those that want to build from a common base.
>>> There are, after all, a *lot* of ipython images up on Docker already.
>>> Additionally, there is a LONG thread on the software carpentry mailing list
>>>
>>> There are some open questions from me:
>>>
>>> * Who should the user be inside the container?
>>>   * Should they be able to install more packages?
>>>
>>
>>  I don't think the user accessing the instance needs to be able to
>> install custom packages. (It would be nice this functionality was
>> available, but it is not critical for running workshops.)
>>
>> However, administrators need to have the ability to create custom images
>> based off the docker base image that have additional packages.
>>
>>
>>>   * In a chef cookbook and deployment setup, I just made the user named
>>> ipynb.
>>>
>>> * Is it ok to force HTTPS?
>>>   * If we do, we're stuck with self signed certs or requiring them to
>>> provide them on run
>>>   * This isn't really the right way to compose applications with Docker
>>> and probably makes things problematic for anyone building on top of ours
>>>
>>> * Who is our target audience?
>>>   * People deploying notebooks across their organization for users?
>>>   * Students (and their teachers) wanting access to an easy analytics
>>> environment?
>>>
>>
>> My interest is in providing an environment for external users of our
>> analysis API, so it somewhat similar to the latter description. Some are in
>> academia, but many are not.
>>
>> * What would you see out of a base image? Where would the value be?
>>>
>>> * Would people like to see a bleeding latest image that you can spin up
>>> to see the current state of the IPython notebook by just running `docker
>>> run ipython/notebook:bleeding-latest`?
>>>
>>> * Do people want a base image that has a large portion of the scipy
>>> stack?
>>>
>>
>> Yes, particularly matplotlib and pandas.
>>
>> Cheers,
>>  Tyler
>>
>> I'll stop with these and see where the discussion takes us.
>>>
>>> _______________________________________________
>>> IPython-dev mailing list
>>> IPython-dev at scipy.org
>>> http://mail.scipy.org/mailman/listinfo/ipython-dev
>>>
>>>
>>
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>>
>>
>
>
> --
> Kyle Kelley (@rgbkrk <https://twitter.com/rgbkrk>; http://lambdaops.com)
>
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