Integrating RStudio Workbench with Jupyter Notebooks on a Single Server#

Overview#

These steps describe how to integrate RStudio Workbench, formerly RStudio Server Pro¹, with Jupyter Notebooks running on a single server.

This integration makes use of the Launcher in RStudio Workbench to spawn Jupyter Notebook and JupyterLab sessions on a single node without the use of an external resource manager.

Info

Launcher is a new feature of RStudio Workbench 1.2 that is only available under named user licensing. RStudio Workbench 1.2 without Launcher is available under existing server-based licensing. For questions about using Launcher with RStudio Workbench, please contact sales@rstudio.com.

Prerequisites#

This integration is intended to be performed on top of a base installation of RStudio Workbench.

Installation of RStudio Workbench 1.2.5 or higher

Step 1. Configure RStudio Workbench with Launcher#

Add the following lines to the RStudio Workbench configuration file:

File: /etc/rstudio/rserver.conf

# Launcher Config
launcher-address=127.0.0.1
launcher-port=5559
launcher-sessions-enabled=1
launcher-default-cluster=Local
launcher-sessions-callback-address=http://127.0.0.1:8787

In the launcher-sessions-callback-address setting, you should change the protocol and port if you are using HTTPS or a different port for RStudio Workbench.

Step 2. Configure Launcher settings and plugins#

Add the following lines to the Launcher configuration file:

File: /etc/rstudio/launcher.conf

[server]
address=127.0.0.1
port=5559
server-user=rstudio-server
admin-group=rstudio-server
authorization-enabled=1
thread-pool-size=4
enable-debug-logging=1

[cluster]
name=Local
type=Local

Now that you have updated the file, you must restart the RStudio Server service:

Terminal
```
$ sudo rstudio-server restart
```
Once you have restarted RStudio Server, run the following command to restart the RStudio Launcher service:

Terminal
```
$ sudo rstudio-launcher restart
```

Step 3. Install Python#

Use the Install Python steps to install the following on the server:
- Python, pip
- virtualenv
  
  Info
  
  Our recommended installation instructions for Python allow you to make multiple versions of Python available and avoid replacing existing versions of Python when updating system packages.

Step 4. Install Jupyter Notebooks, JupyterLab, and Python packages#

From the previous step, you should still have the PYTHON_VERSION environment variable defined with the version of Python that you installed. If not, then do then you can define this environment variable before proceed by running the following command and replacing 3.7.7 with the version of Python that you are using:

Terminal
```
$ export PYTHON_VERSION=3.7.7
```
Install Jupyter Notebooks, JupyterLab, and the notebook extensions for RStudio Workbench and RStudio Connect:

Terminal
```
$ sudo /opt/python/${PYTHON_VERSION}/bin/pip install jupyter jupyterlab rsp_jupyter rsconnect_jupyter
```

Install and enable the Jupyter Notebook extensions:

Terminal

$ sudo /opt/python/${PYTHON_VERSION}/bin/jupyter-nbextension install --sys-prefix --py rsp_jupyter
$ sudo /opt/python/${PYTHON_VERSION}/bin/jupyter-nbextension enable --sys-prefix --py rsp_jupyter
$ sudo /opt/python/${PYTHON_VERSION}/bin/jupyter-nbextension install --sys-prefix --py rsconnect_jupyter
$ sudo /opt/python/${PYTHON_VERSION}/bin/jupyter-nbextension enable --sys-prefix --py rsconnect_jupyter
$ sudo /opt/python/${PYTHON_VERSION}/bin/jupyter-serverextension enable --sys-prefix --py rsconnect_jupyter

(Optional) Install supplemental Python packages:

Terminal

$ sudo /opt/python/${PYTHON_VERSION}/bin/pip install altair beautifulsoup4 \
  cloudpickle cython dask gensim keras matplotlib nltk numpy pandas pillow \
  pyarrow requests scipy scikit-image scikit-learn scrapy seaborn spacy \
  sqlalchemy statsmodels tensorflow xgboost

Step 5. Configure Launcher with Jupyter Notebooks#

Add the following lines to the Launcher Jupyter configuration file:

File: /etc/rstudio/jupyter.conf
```
jupyter-exe=/opt/python/3.7.7/bin/jupyter
notebooks-enabled=1
labs-enabled=1
default-session-cluster=Local
```
- If you installed a version other than Python 3.7.7, then you can replace 3.7.7 in the above jupyter-exe setting with the the version of Python that you installed.

Step 6. Restart RStudio Workbench and Launcher Services#

Run the following to restart services:

Terminal

$ sudo rstudio-server restart
$ sudo rstudio-launcher restart

Step 7. Test RStudio Workbench with Launcher and Jupyter Notebooks#

Additional Documentation#

For more information on RStudio Workbench and Jupyter Notebooks, reference the Jupyter section in the RStudio Workbench Administration Guide.

We have renamed RStudio Server Pro to RStudio Workbench. This change reflects the product’s growing support for a wide range of different development environments. RStudio Workbench enables R and Python data scientists to use their preferred IDE in a secure, scalable, and collaborative environment -- whether that is the RStudio IDE, JupyterLab, Jupyter Notebooks, or VS Code. We want RStudio Workbench to be the best single platform to support open source, code-first data science, whether your team is using R or Python. Please see our official Announcement and review our FAQ regarding the name change from RStudio Server Pro to RStudio Workbench. ↩