This repository demonstrates the integration of ODMX and Jupyterhub
This requires a working install of docker with compose and the ability to build docker images
config.env contains the default configuration values. jupyterhub_config_base.py
contains an example configuration for jupyterhub which works with the custom
container for the integration
./build.sh
After some time, you should see a message that the jupyterhub environment is available at http://127.0.0.1:8000/ (by default)
The work environment is defined by the docker-compose.yml file which creates the ODMX
API instance accessible at the hostname odxm-api and a postgres-db instance with
postgis extensions at the hostname odmx-db. This is accessible by all users in the
environment. The base jupyterhub configuration references a container built in the
build.sh to be launched with each specific user.
The default user is created by the build.sh script, additional users can be added using adduser inside the jupyterhub container. Jupyterhub can also be configured with external authentication such as with an organization's LDAP directory, see juptyerhub docs.
After logging in with the default username and password, there are some example notebooks in the example_notebooks directory of each user's workspace
-
ODMX_build_example.ipynbThis notebook showcases the building of the example ODMX project and doing basic queries -
ODMX_analysis_example.ipynbThis notebook showcases querying with the ODMX API and visualizing some data
This project was funded under DOE SBIR Award DE-SC0024850 to Subsurface Insights and support from DOE is gratefully acknowledged.. The PI for the project is Roelof Versteeg. The project associated with this award is titled Data fusion and analysis tools to enable machine learning for systems biology and bioenergy. More detail on this project can be found at https://subsurfaceinsights.com/data-fusion-and-analysis-tools-to-enable-machine-learning-for-systems-biology-and-bioenergy/