The fastest way to build and share data apps.
Streamlit lets you turn data scripts into sharable web apps in minutes, not weeks. It's all Python, open-source, and free! And once you've created an app you can use our free sharing platform to deploy, manage, and share your app with the world.
pip install streamlit
streamlit helloStreamlit can also be installed in a virtual environment on Windows, Mac, and Linux.
Streamlit makes it incredibly easy to build interactive apps:
import streamlit as st
x = st.slider('Select a value')
st.write(x, 'squared is', x * x)
Streamlit's simple and focused API lets you build incredibly rich and powerful tools. This demo project lets you browse the entire Udacity self-driving-car dataset and run inference in real-time using the YOLO object detection net.
The complete demo is implemented in less than 300 lines of Python. In fact, the app contains only 23 Streamlit calls which illustrates all the major building blocks of Streamlit. You can try it right now at share.streamlit.io/streamlit/demo-self-driving.
Streamlit's GitHub badge helps others find and play with your Streamlit app.
Once you deploy your app, you can embed this badge right into your GitHub readme.md as follows:
[](https://share.streamlit.io/yourGitHubName/yourRepo/yourApp/)- Our launch post explaining why we created Streamlit
- Our sharing platform announcement
- Our amazing community where Streamlit users share apps, ask questions, and help each other out
- Streamlit documentation and blog for the latest Streamlit info
- More demo projects to inspire you
- And if you would like to contribute, see instructions here
Streamlit for Teams is our enterprise solution for deploying, managing, sharing, and collaborating on your Streamlit apps. Streamlit for Teams provides secure single-click deploy, authentication, web editing, versioning, and much more. It is currently in closed beta, and you can join the wait-list here.
Streamlit is completely free and open-source and licensed under the Apache 2.0 license.