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Last pushed: 2 years ago
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An ipython notebook server for data science development


The notebook is intended to contain the environment to perform development and anaysis. The data-only containers provide the source code (notebooks) and the data sources (data files, output, persistent caches, databases etc.. The notebook should therefore be stateless.

Guide for use

Create data-only containers for sprint notebooks and data folders:

docker run -d -v ~/notebooks:/notebooks --name notebooks ubuntu echo notebooks
docker run -d -v ~/data:/data --name sprint_data ubuntu echo data

Fork the repo and clone.

Modify requirements in to your needs requirements.txt.

Build the image from the root of the repo, for example:

docker build -t calvingiles/ds-notebook .

then start a container from the image:

docker run \
    -d \
    -e "PASSWORD=Password" \
    --name data-science-docker-notebook \
    -p 443:8888 \
    --volumes-from data \
    --volumes-from notebooks \

Automated docker builds

Add an automated build on docker pointing at your forked repo to keep the docker hub images up to date. Then you can skip the build stage above and the latest version will be pulled from docker hub.

Docker Pull Command
Source Repository