Streamlit documentation

Streamlit is an open-source Python library that makes it easy to create and share beautiful, custom web apps for machine learning and data science. In just a few minutes you can build and deploy powerful data apps. So let's get started!


Streamlit library includes our Get started guide, API reference, and more advanced features of the core library including caching, theming, and Streamlit Components.


Streamlit Community Cloud is an open and free platform for the community to deploy, discover, and share Streamlit apps and code with each other. Create a new app, share it with the community, get feedback, iterate quickly with live code updates, and have an impact!


Knowledge base is a self-serve library of tips, step-by-step tutorials, and articles that answer your questions about creating and deploying Streamlit apps.



Introducing st.experimental_connection to let you easily connect your app to data sources and APIs.


Supercharged! has been revamped to show more information about object methods, attributes, classes, and more, which is great for debugging!


Tooltips on text elements

Most text elements can optionally include tooltips with thehelp parameter.


Line numbers in st.code

st.code supports optionally displaying line numbers to the code block's left with the boolean line_numbers parameter.


Global secrets.toml file

Streamlit now supports the use of a global secrets.tomlfile, in addition to a project-level file, to easily store and securely access your secrets. Click to read the docs.


Editable dataframes!

Display a data editor widget with st.experimental_data_editorto edit dataframes and many other data structures in a table-like UI.

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Join the community

Streamlit is more than just a way to make data apps, it's also a community of creators that share their apps and ideas and help each other make their work better. Please come join us on the community forum. We love to hear your questions, ideas, and help you work through your bugs — stop by today!

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