Using Python with RStudio
You can use Python with RStudio professional products to develop and publish Jupyter Notebooks, interactive applications with Shiny, reports with R Markdown, and REST APIs with Plumber.
For more information on administrator workflows for configuring RStudio with Python and Jupyter, refer to the resources on configuring Python with RStudio.
Developing with Jupyter Notebooks and JupyterLab
Data scientists and analysts can:
- Work with the RStudio IDE, Jupyter Notebook, or JupyterLab editors from RStudio Server Pro
Want to learn more about RStudio Server Pro and Jupyter?
View an overview of using Jupyter with RStudio Server Pro
Frequently asked questions for using Jupyter Notebooks with RStudio Server Pro
For more information on integrating RStudio Server Pro with Jupyter, refer to the resources on configuring Python with RStudio.
Publishing Python Content
Data scientists and analysts can publish Python content to RStudio Connect by:
- Publishing Jupyter Notebooks that can be scheduled and emailed as reports
- Publishing R applications that call Python scripts
Ready to publish Jupyter Notebooks to RStudio Connect?
View the user documentation for publishing Jupyter Notebooks to RStudio Connect
Ready to use Python with RStudio?
View the how-to guide for installing and configuring Python with RStudio
View the user documentation for publishing content that uses Python and R to RStudio Connect
Want to learn more about RStudio Connect and Python?
View an overview of using Python with RStudio Connect
Frequently asked questions for using Python with RStudio Connect
Want to see examples of using Python with RStudio?
View examples of content published to RStudio Connect with Jupyter Notebooks, Shiny, R Markdown, and Plumber
View code examples on GitHub of Python with Jupyter Notebooks and
Want to learn more about RStudio and Python?
Reference documentation for the reticulate package (R interface to Python)
Cheat sheet for using Python with R and reticulate