Integrating RStudio Workbench with reticulate to interface with Python#

These instructions describe how to use the reticulate R package with RStudio to interface with Python.

Once you configure reticulate with RStudio Workbench with an installation of Python, users will be able to develop mixed R and Python content with Shiny apps, R Markdown reports, and Plumber APIs that call out to Python code using the reticulate package.

Requirements#

RStudio uses the reticulate R package to interface with Python, and so RStudio's Python integration requires:

Installation of Python 3.5, or newer
The reticulate R package (1.20, or newer; as available from CRAN)

Step 1. Install Python for all users#

First, follow the Install Python from Source instructions on the server with RStudio Workbench in a central location for all users (e.g., /opt/python/3.7.7/).

Once you have completed the steps to Install Python from Source, continue to Step 2.

Step 2. Install `reticulate` for all users#

Install the reticulate R package for all users in the global R library.
For example, if R is installed in /opt/R/3.7.7/, then you you can use the following command:
Terminal
```
$ sudo /opt/R/3.7.7/bin/Rscript -e 'install.packages("reticulate")'
```

Step 3. Configure `reticulate` with Python for all users#

Set the RETICULATE_PYTHON environment variable for all RStudio Workbench users by putting the following line in the R session-specific profile script used by RStudio Workbench.
For example, if Python is installed in /opt/python/3.7.7/, then you you can use the following configuration:
File: /etc/rstudio/rsession-profile
```
export RETICULATE_PYTHON=/opt/python/3.7.7/bin/python
```

Next Steps#

Now, you are ready to develop Shiny apps, R Markdown, and Plumber APIs with Python/R in the RStudio IDE and RStudio Workbench using the reticulate package per https://blog.rstudio.com/2018/10/09/rstudio-1-2-preview-reticulated-python/ and https://rstudio.github.io/reticulate/ and deploy the applications to RStudio Connect.

Additional Information#

For more information on end-users working with custom, per-project Python environments, refer to the support article on Installing and Configuring Python with RStudio.

For more details on each step, refer to the concepts and best practices in the support article for Best Practices for Using Python with RStudio Connect.