You can use Python with RStudio professional products to develop and publish interactive applications with Shiny, Dash, Streamlit, or Bokeh; reports with R Markdown or Jupyter Notebooks; and REST APIs with Plumber or Flask.

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For an overview of how RStudio helps support Data Science teams using R & Python together, see R & Python: A Love Story.

For more information on administrator workflows for configuring RStudio with Python and Jupyter, refer to the resources on configuring Python with RStudio.

Developing with Python#

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Data scientists and analysts can:

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Work with the RStudio IDE, Jupyter Notebook, JupyterLab, or VS Code editors from RStudio Workbench

Want to learn more about RStudio Workbench and Python?#

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For more information on integrating RStudio Workbench with Python, refer to the resources on configuring Python with RStudio.

Publishing Python Content#

Data scientists and analysts can publish Python content to RStudio Connect by:

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Publishing Jupyter Notebooks that can be scheduled and emailed as reports
Publishing Flask applications and APIs
Publishing Dash applications
Publishing Streamlit applications
Publishing Bokeh applications

Ready to publish Jupyter Notebooks to RStudio Connect?#

View the user documentation for publishing Jupyter Notebooks to RStudio Connect

Ready to share interactive Python content on RStudio Connect?#

Learn more about publishing dash or flask applications and APIs.

View example code as well as samples in the user guide.

Publishing Python and R Content#

Data scientists and analysts can publish mixed Python and R content to RStudio Connect by publishing:

Shiny applications that call Python scripts
R Markdown reports that call Python scripts
Plumber APIs that call Python scripts

Mixed content relies on the reticulate package, which you can read more about on the project's website.

View the user documentation for publishing content that uses Python and R to RStudio Connect

Cheat sheet for using Python with R and reticulate

Managing Python Packages#

RStudio Package Manager supports both R and Python packages. Visit this guide to learn more about how you can securely mirror PyPI.

Additional Resources#

Want to learn more about RStudio Connect and Python?#

Frequently asked questions for using Python with RStudio Connect

Learn about best practices for using Python with RStudio Connect

Want to see examples of using Python with RStudio?#

View code examples on GitHub of Using Python with RStudio

View examples of Flask APIs published to RStudio Connect