Easy-to-setup local deployment of the Wrattler notebook, using pre-built docker images pulled from dockerhub.
To run locally, the various components of Wrattler run in their own Docker containers. To install Docker, follow the instructions here. You also need docker-compose which should already be installed with Docker if you are using Windows or OSX. For Ubuntu, this can be installed following the instructions here.
To build and run:
docker-compose build
docker-compose up
And you should be able to:
- Access the Wrattler client directly by pointing your browswer to
localhost:8080, or - Access Wrattler via Jupyter lab by going to
localhost:8889/?token=<token>where the<token>can be found in the console output from thedocker-compose upcommand.
Using Jupyter lab enables you to load files with a .wrattler extension in Wrattler, and save changes.
The local directory resources/ is mounted on the docker containers for jupyterlab and the language services.
In addition to notebook files, you can put python or R files containing e.g. function definitions or import statements here, and use them in your notebooks with either
%local <filename> (will import contents of to the current cell) or %global <filename> (will import contents of to all cells of that language).
This directory can also be used to load data into the language services - e.g. if you put myData.csv into resources/, you can load it into a pandas dataframe with df = pd.read_csv("resources/myData.csv").
Once you have finished, you can stop the docker containers by running (from this directory):
docker-compose down