This repository holds the file to generate the Docker image (and run the Docker container) containing the following tools:
- the R interpreter;
- Jupyter Notebook and associated tools (JupyterLabs, Voilà, etc.);
- the RStudio IDE (server version), running inside the container.
We also include the necessary packages and utilities to glue R and Jupyter together.
Notice the name of the repo (and the tag of the Docker image) is justudior
,
a contraction of "Jupyter", "Studio" and "R", recalling the tools contained in
the image.
The only prerequisites is to install Docker on a Linux machine.
One can use instructions provided on Docker website: https://docs.docker.com/engine/install/
Simply run the script located at the root of the repository:
./buildrun.sh
The image takes some time to build.
After the image is built, the script automatically runs the container that
starts RStudio
and a tmux
session with Jupyter Notebook
, allowing you to
interact with a shell while Jupyter is running.
Once the container is started, RStudio
starts listening on port 8787 (and the
port is exposed to the host).
On a browser on your host, you can connect to http://127.0.0.1:8787/ to access the RStudio server. Use the Linux user/password credentials pre-configured in the Dockerfile (modify it according to your needs) to connect through the WebUI.
As the container starts, the tmux session loads Jupyter Notebook and provides a URL with a token. You can use the URL with the localhost IP address (127.0.0.1) to connect to the WebUI of Jupyter Notebook, as the port 8888 is exposed to the host.