IllumiDesk Apple Stacks

Dockerfiles and related assets for IllumiDesk's workspace images for the Apple.

What do these images contain?

Everything from the jupyter/datascience-notebook plus PyTorch.

Pre Requisits

• Docker

Quickstart

1. Install dependencies

make venv

2. Build images

make build-all

3. Run:

Running the image standalone is helpful for testing:

docker run -p 8888:8888 illumidesk/apple-notebook:latest

Then, navigate to http://localhost:8888 to access your Jupyter Notebook server.

Refer to docker's documentation for additional docker run ... options.

4. Test:

make test

Image catalogue

Image	DockerHub Link
illumidesk/apple-notebook
illumidesk/apple-grader

Build Mechanism

1. Build and tag the base image or all images at once. Use the TAG argument to add your custom tag. The TAG argument defaults to python-3.9.5 if not specified.

Build all images:

make build-all

Build one image with custom tag:

make build/apple-notebook TAG=mytag

2. (Optional) Use the base image from step 1 above as a base image for an image compatible with the IllumiDesk stack.

FROM jupyter/scipy-notebook:python-3.9.5

RUN ... do stuff

# make sure you run fix-permissions after doing stuff
USER root
RUN fix-permissions "${HOME} \
 && fix-permissions "${CONDA_DIR}

USER "${NB_USER}"

3. (Optional) Push images to DockerHub

If you would like to use an organization other than IllumiDesk's, then step requires creating an Organization account in DockerHub or other docker image compatible registry. The docker push ... command will push the image to the DockerHub registry by default. Please refer to the official Docker documentation if you would like to push another registry.

For example:

docker push illumidesk/apple-notebook:python-3.9.5

Development and Testing

Build and Test

1. Create your virtual environment and install dev-requirements:

make venv

2. Check Dockerfiles with linter:

make lint-all

3. Build the images and run tests:

make build-all
make test

Update Dependencies

There are two ways to add additional dependencies:

1. Update the spec-list.txt file with conda/pip dependencies

Similar to Python's requirements.txt, the spec-list.txt locks a dependency tree. The difference is that the spec-list.txt combines both conda and pip dependencies.

After you have updated the dependencies in your docker image update the spec-list.txt file with the following the steps below:

docker run -it --rm -v $(pwd):/tmp illumidesk/apple-notebook:<your-tag> /bin/bash

... steps to install conda/pip packages ...

conda list --explicit > /tmp/apple-notebook/spec-list.txt

Note: replace <your-tag> with the tag you used to build the image. The default value is located in the Makefile if using the make command or the FROM directive in the Dockerfile if using the native docker build ... command.

2. Update the Dockerfile(s) with additional dependencies

3. Build the docker image with custom arguments (ARGS):

Use the --build-args flag with the docker build command to override the arguments included in the Dockerfile. For example, if you would like to build/test an image with a different version of Apache Spark (let's assume version 1.2.3) then build the image like so:

docker build --build-args spark_version=1.2.3 illumidesk/apple-notebook:mytag apple-notebook/.

Or

make DARGS="--build-args spark_version=1.2.3" build/apple-notebook

Releasing

Overview

There are two environments configured with this repo:

• Development: associated to the main branch
• Production: associated to the production branch

Development and production versions are built with the DockerHub build actions located in the illumidesk/apple-grader and the illumidesk/apple-notebook for the grader and end-user notebooks, respectively.

Create a Pull Request

The steps below are applicable to both the main and production branches.

1. Fork this repository with GitHub's Fork option.
2. Clone the repository to your local machine using:

$ git clone `https://github.com/<github-account>/apple-stacks.git`

NOTE: Replace the <apple-account> placeholder above with your GitHub username.

3. Add the remote upstream branch:

git remote add upstream https://github.com/illumidesk/apple-stacks.git

4. Verify that your git remote settings are set up correctly:

git remote -v

The command above should return an output similar to:

origin  https://github.com/foobar/apple-stacks (fetch)
origin  https://github.com/foobar/apple-stacks (push)
upstream        https://github.com/illumidesk/apple-stacks (fetch)
upstream        https://github.com/illumidesk/apple-stacks (push)

5. Install the dependencies required for the project by running:

$ make dev
$ source venv/bin/activate

or

$ virtualenv -p python3 venv
$ python3 -m pip install -r dev-requirements.txt
$ source venv/bin/activate

6. Create a new branch for your feature or fix using:

$ git checkout -b branch-name-here

7. Make the appropriate changes for the issue you are trying to address. Build and test the image(s) as instructed in the Build and Test section above. Please note that these are very basic validations. It is recommended to run tests with actual Jupyter Notebook (*.ipynb) files.

8. Add and commit the changed files:

git add .
git commit -m "my commit message here"

9. Push the changes to your fork:

$ git push origin <branch-name-here>

11. Submit a pull request to the upstream repository.
12. Set the description of the pull request. We recommend using declaritive terms, such as Updates instead of Updated or Updating.
13. Wait for the pull request to be reviewed by a maintainer.
14. Make changes to the pull request if the reviewing maintainer recommends them.
15. Celebrate your success after your pull request is merged! 🎉

Squash and Merge for Release

1. Once the Pull Request is approved, squash and merge the Pull Request into the main or production branch.
2. Merges to main will trigger a build with DockerHub with the dev tag. Merges to production will create a build with the prod tag.
3. Once the images are built the development and production clusters are automatically updated. However there are some caveats to consider:

• Running end-user Notebooks are not automatically culled when a new release is available. The end-user should logout and log back into their environment using the Logout button in the Notebook interface.
• The new image is pulled once the the end-user restarts their environment.
• The new image may be a small update or it may required downloading all image layers from scratch. Therefore the first user to launch the new Notebook may epxerience a longer wait time until their Notebook is available.
• Shared Grader Notebooks are not automatically updated by the system. To update a Shared Grader Notebook, please send a support request to IllumiDesk Support in the #apple Slack channel. If you do not have access to this channel then you may request support by visiting https://support.illumidesk.com to chat with a customer support agent.

References

These images are based on the jupyter/docker-stacks images. Refer to their documentation for the full set of configuration options.

Attributions

• jupyter/docker-stacks images

License

MIT