Shiny is a framework that makes it easy to build interactive web applications without requiring traditional web development skills. Since its introduction ten years ago for R, Shiny has made it possible for R users to communicate with a much broader audience—and now Shiny is available for Python! Python users can now use Shiny to create interactive data-driven web applications by writing Python code.
Shiny for Python is currently in alpha. We’d love for you to try it out and give us your feedback.
To see what Shiny for Python can do, take a look at the interactive examples in the Gallery.
Try Out Shiny for Python
You can start writing Shiny applications right in your web browser, without installing Shiny on your computer!
To get going, visit the Get Started page. You can also see some interactive examples from shinylive.io (and more) on our YouTube playlist:
After you’ve created a Shiny application, you’ll want to make it available to the world. You can deploy Shiny for Python apps to:
- shinyapps.io: RStudio’s managed hosting service
- Shiny Server Open Source: A free, open-source server platform.
- RStudio Connect: Our professional data science publishing platform that you can host on your own servers
- Or other hosting services that support FastAPI.
Learn more about deploying Shiny for Python applications in its documentation.
One of the really cool new things about Shiny for Python is that it can run without Python on the server. Instead of running Python on the server, it can run Python in the user’s web browser. We’re calling this Shinylive. Our interactive online documentation and examples are deployed using Shinylive.
How does Shinylive work? It uses the magic of WebAssembly, which is a binary format that can run inside of web browsers. Shinylive runs on Pyodide, which is a version of Python compiled to WebAssembly. Because Python runs inside of the user’s browser instead of on a server, you deploy Shinylive applications to any web hosting service.
- Check out the Shiny for Python playlist on YouTube.
- Visit the documentation website, which includes:
- Editor support:
- Watch Joe Cheng introduce Shiny for Python at his rstudio::conf 2022 keynote.