wrattler-examples

Easy-to-setup local deployment of the Wrattler notebook, using pre-built docker images pulled from dockerhub, or cloud deployment on binder.

Local setup

To run locally, the various components of Wrattler run in a Docker container. To install Docker, follow the instructions here.

To build and run:

./wrattler-start

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:8888/?token=<token> where the <token> can be found in the console output from the wrattler-start command.

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 container so you can save files in Jupyterlab and have this reflected in your local filesystem.

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 container by doing Ctrl+C, then pressing y to confirm you want to stop the jupyter lab instance.

Cloud setup

Click the "binder" button at the top of the page :)