[IPython-dev] Docker IPython

Kyle Kelley rgbkrk at gmail.com
Tue Aug 5 01:33:12 EDT 2014


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!)
* 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
* 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.

Derivative image, ipython/scipystack (please suggest other names), could be

* numpy
* scipy
* matplotlib
* pandas
* scikit-learn

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.
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Kyle Kelley (@rgbkrk <https://twitter.com/rgbkrk>; http://lambdaops.com)
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