A frequently occurring usecase in Jupyter notebooks is to read from and write data to a database.
This repository contains a Docker recipe for jupyter/docker-stacks, which cooks up an additional layer providing support for Microsoft SQL Server. In your notebooks you can use pyodbc and sqlalchemy to interact with the database. See the test notebook for a Python sample.
Containers based on the following images are built and published weekly to ghcr.io using GitHub Actions:
- jupyter/minimal-notebook
- jupyter/r-notebook
- jupyter/scipy-notebook
- jupyter/tensorflow-notebook
- jupyter/datascience-notebook
- jupyter/pyspark-noteboo
- jupyter/all-spark-notebook
In the examples folder, you can find a script for generating a docker-compose.yml which spins up a Jupyter notebook, and an ephemeral instance of Microsoft SQL Server.
cd example
sh create_docker_compose.sh "jupyter/minimal-notebook" "mcr.microsoft.com/mssql/server:2019-latest"
docker-compose up
The test notebook can be accessed using this link or by manually
typing http://127.0.0.1:8888 into the browser and logging in with the token foo123.
You can build and distribute your own container images by forking this repository. Note that the workflows use cron-scheduled actions, and these are disabled in forks by default. I would recommend to remove the cron from the workflow file and then manually enable the workflows for which you want images to be built and published.