Ganimede

Store, version, edit and execute notebooks in sandboxes and integrate them directly via REST interfaces.

Use cases

Ability to write machine learning logic and expose them to systems as rest api
Write Jupyter nb locally and run them in a centralised powerful machine to reduce cost
Create framework to directly connect Jupyter notebook to other systems

Requirements

docker
redis

Stack

Redis
FastAPI
Papermill
Jupyter
Poetry
Docker

Build

Clone the repo
Run poetry install
Run run.py or scripts\launch.sh or cd docker;docker-compose up -d

Deployment

Clone the repo and in docker folder, run docker-compose build. The docker image will be build
Push to registry or use your custom publishing method to publish the image

API Docs

Start the application
Go to localhost:8000/docs for swagger and localhost:8000/redoc for redoc

Main APIs

Jupyter Notebook

define for defining projects and its dependencies
store for storing notebook and associated files
run for executing a jupyter file
html to get a rendered page of executed notebook
output to get the output of Jupyter execution in json format
plain_text to get the plain text output

Jupyter Notebook Editor

edit for editing notebook in a sandbox
view for viewing notebook in sandbox and can run it, but not save the changes

Jupyter Updater

update for storing the next version of notebook from edit endpoint

TODO

Provide live environment for editing and running jupyter
Custom transformations for jupyter output
Scheduled cleanup of created jupyter docker containers
Change container implementation to podman or other rootless systems