rest-api-jupyter-course

Python and R notebooks to be used by Jupyter

Using Binder

You can use Binder to execute our Jupyter notebooks. Click on the above image to launch it.

Running locally using Docker

Dependencies

1. Git (should be installed on your system)
2. Docker
   • Mac
   • Windows
   • Linux

To run

Open your terminal/command window and type the following.

git clone https://github.com/Ensembl/rest-api-jupyter-course.git
cd rest-api-jupyter-course
docker run -it --rm -p 8888:8888 -v "$PWD":/home/jovyan/work jupyter/r-notebook

This will produce output which looks like:

Executing the command: jupyter notebook
[I 16:54:34.267 NotebookApp] Writing notebook server cookie secret to /home/jovyan/.local/share/jupyter/runtime/notebook_cookie_secret
[I 16:54:35.394 NotebookApp] JupyterLab extension loaded from /opt/conda/lib/python3.8/site-packages/jupyterlab
[I 16:54:35.396 NotebookApp] JupyterLab application directory is /opt/conda/share/jupyter/lab
[I 16:54:35.405 NotebookApp] Serving notebooks from local directory: /home/jovyan
[I 16:54:35.405 NotebookApp] The Jupyter Notebook is running at:
[I 16:54:35.406 NotebookApp] http://2d01bcf7895c:8888/?token=93244e3e79efe261a2d7600037dfd5d3d5c61c49b52e9328
[I 16:54:35.408 NotebookApp]  or http://127.0.0.1:8888/?token=93244e3e79efe261a2d7600037dfd5d3d5c61c49b52e9328
[I 16:54:35.408 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[C 16:54:35.415 NotebookApp]

    To access the notebook, open this file in a browser:
        file:///home/jovyan/.local/share/jupyter/runtime/nbserver-7-open.html
    Or copy and paste one of these URLs:
        http://2d01bcf7895c:8888/?token=93244e3e79efe261a2d7600037dfd5d3d5c61c49b52e9328
     or http://127.0.0.1:8888/?token=93244e3e79efe261a2d7600037dfd5d3d5c61c49b52e9328

The final line shows a URL formatted as http://127.0.0.1:8888/?token=NNNNNNNNNNNNNNN where NNNNNNNNNNNNNNN is a unique token to allow you to log into your Jupyter notebook instance. Click on this link or copy/paste it into your web-browser. You will be presented with the default Jupyter file-explorer. Click on work, then on Python3 or R to select your course of interest.