Streamlit documentation

Streamlit is an open-source Python framework for data scientists and AI/ML engineers to deliver dynamic data apps with only a few lines of code. Build and deploy powerful data apps in minutes. Let's get started!

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Get started with Streamlit! Set up your development environment and learn the fundamental concepts, and start coding!

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Develop your Streamlit app! Our API reference explains each Streamlit function with examples. Dive deep into all of our features with conceptual guides. Try out our step-by-step tutorials.

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Deploy your Streamlit app! Streamlit Community Cloud our free platform for deploying and sharing Streamlit apps. Streamlit in Snowflake is an enterprise-class solution where you can house your data and apps in one, unified, global system. Explore all your options!

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

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More dataframe types!

Streamlit natively supports even more dataframe types. Use Dask, Modin, Numpy, pandas, Polars, PyArrow, Snowpark, Xarray, and more.

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Configurable JSON expansion

You can control the initial expansion state ofst.json elements.

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User session context

Introducing st.context, a read-only interface to access headers and cookies!

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User feedback

Introducing st.feedback to collect user ratings and sentiment.

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Fragments and dialogs

We've polished st.fragment andst.dialog with multiple bug fixes and improvements. They're no longer experimental!

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Rerun scope

st.rerun can be scoped to a fragment.

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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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