Turns data scripts into shareable web apps in minutes. All in pure Python. No front‑end experience required.
Streamlit: The Basics
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.
In practice, a Streamlit application is just a .py file where you add a few Streamlit commands and then you run it with streamlit run:
streamlit run your_script.py [-- script args]
As soon as you run the script as shown above, a local Streamlit server will spin up and your app will open in a new tab in your default web browser. This app is your canvas, where you'll draw charts, text, widgets, tables, and more. This .py file is all you need to build a fully-featured web-app!
What gets drawn in the app is up to you. For example st.text writes raw text to your Streamlit app, and st.line_chart draws a line chart. Refer to Streamlit's API documentation to see all commands that are available to you.
Core Concepts in Streamlit
New to writing Streamlit applications and looking to understand more? Check out the Streamlit docs to learn more core concepts.