Welcome to Streamlit¶
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!
Make sure that you have Python 3.6+ installed.
Install Streamlit using PIP and run the ‘hello world’ app:
pip install streamlit streamlit hello
That’s it! In the next few seconds the sample app will open in a new tab in your default browser.
Still with us? Great! Now make your own app in just 3 more steps:
Open a new Python file, import Streamlit, and write some code
Run the file with:
streamlit run [filename]
When you’re ready, click ‘Deploy’ from the Streamlit menu to share your app with the world!
Now that you’re set up, let’s dive into more of how Streamlit works and how to build great apps.
How to use our docs¶
The docs are broken up into 5 sections that will help you get the most out of Streamlit.
Tutorials: include our Get Started guide and a few step-by-step examples to building different types of apps in Streamlit.
Topic guides: give you background on how different parts of Streamlit work. Make sure to check out the sections on Creating an app and Deploying an app, and for you advanced users who want to level up your apps, be sure to read up on Caching and Components.
Cookbook: provides short code snippets that you can copy in for specific use cases.
Support: gives you more options for when you’re stuck or want to talk about an idea. Check out our discussion forum as well as a number of troubleshooting guides.
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!