Streamlit

Streamlit is an open-source Python library that makes it easy to build beautiful custom web-apps for machine learning and data science.

• Streamlit Documentation
• Streamlit App Gallery
• Streamlit Source

Deploying

Streamlit apps can be deployed with the rsconnect-python package. See the Publishing with rsconnect-python section for details.

Example apps

There are some Streamlit example apps available from the Streamlit developers:

• Uber Pickups in New York City
• Face-GAN explorer

To deploy one of these examples, first clone the repository:

git clone https://github.com/streamlit/<app-name>

Install any required dependencies. Test the app locally:

streamlit run <app-name>/streamlit_app.py

Then deploy to RStudio Connect:

rsconnect deploy streamlit -n <saved server name> --entrypoint streamlit_app.py <app-name>/

Limitations

User meta-data

Due to a limitation in Streamlit, Streamlit apps cannot currently access HTTP request headers. This includes the RStudio-Connect-Credentials header, which provides the accessing username and group membership information.

Python 2 Compatibility

• RStudio Connect requires Streamlit v56.1 or higher.
• As of version 0.56, Streamlit no longer supports Python 2.x. Streamlit apps must use Python 3.5 or higher.

Bokeh Compatibility

• Streamlit versions starting with 0.57 require Bokeh 2.0 or higher.
• Streamlit versions prior to 0.57 require Bokeh 1.4.
• Bokeh charts embedded within Streamlit can use Javascript callback functions, but Bokeh's Python callbacks are not supported by Streamlit.

Internet Explorer Compatibility

Important

Internet Explorer 11 is no longer supported by RStudio server products. Please see our Platform Support page for a list of supported browsers.

As of version 0.60, Streamlit is not compatible with Internet Explorer due to a known issue in Streamlit.