SciPy 2025: Shiny for Python
Shiny is a framework for building web applications and data dashboards in Python. In this workshop, you will see how the basic building blocks of shiny can be extended to create your own scalable production-ready python applications.
Schedule
| Time | Activity |
|---|---|
| 13:30 | Welcome! |
| 13:– | Basic building blocks of a Shiny application |
| 13:– | Input components |
| 13:– | Output components |
| 14:20 | break |
| 14:30 | A more complex application |
| 14:– | Shiny’s reactivity programming model |
| 15:– | Deploying your application to the web (for free!) |
| 15:20 | break |
| 15:– | Anatomy of a conversation |
| 15:– | Demo: 20 Questions |
| 15:– | Your first chat with an LLM |
| 15:– | AI Chat Interfaces |
| 15:– | Tool Calling |
| 16:20 | break |
| 16:30 | Shiny modules |
| 16:– | Testing your shiny apps with playwright |
| 17:00 | Q+A with the Shiny engineers |
| 17:30 | End |
FAQ
What if I’m a complete beginner?
You should have a basic understanding of Python and be able to install packages with pip, do basic data manipulation, and draw plots.
What if I’ve never built a Shiny app before?
This workshops doesn’t require any Shiny or web application experience. We’ll focus more on practical examples in the course. We do have additional resources for you to dive more into more Shiny details, but we will cover the basics needed to build larger and scalable applications.
Why should I learn Shiny if I already know Streamlit or Dash?
We believe that Shiny is the best framework for building data applications in Python. It’s reactive execution model means that you can build performant applications without explicitly caching data or managing application state. See this blog post for more on why we think that Shiny is worth learning.
I already know Shiny for R, is this workshop for me?
The R and Python Shiny packages are quite similar, so some of the content in this workshop may be familiar to you. That said it’s a great opportunity to fill in missing pieces and ask question about Python best practices. We will also talk about Shiny modules and testing in this workshop, which will also be a precursor for you to learn more or incorporate Python Packaging to your Shiny applications.