11-09, 16:15–17:00 (America/New_York), Central Park East (6th floor)
Shiny lets data scientists easily create interactive data visualizations and web apps, without needing to know HTML, CSS, and JavaScript. Over the last ten years, Shiny has been the de facto standard for creating interactive apps in R; it is used by organizations in every major industry and is a common sight in many academic fields. And now, Shiny is coming to Python!
Shiny for Python is designed to let you create data dashboards, interactive visualizations, and workflow apps in pure Python, without needing to write HTML, CSS, and JavaScript. Apps can be hosted in our cloud-based hosting service; using open source or commercial on-prem servers; or even compiled down to static HTML through the magic of WASM and hosted anywhere you can put a web page.
Of course, Python already has plenty of excellent options for creating data-centric web applications, from high-level frameworks like Streamlit to low-level ones like Flask. So it's fair to ask what Shiny can offer the Python community.
In this talk, I will introduce Shiny for Python and answer that question. After showing various Shiny features and examples, I'll go deeper into the principles and concepts behind Shiny, and how they lead to a different point on the ease-vs-power tradeoff frontier than existing Python app frameworks.
I hope this talk will help attendees decide whether they should make Shiny part of their arsenal of skills, and get a head start in learning how to create Shiny apps.
No previous knowledge expected
Joe Cheng is the Chief Technology Officer and first employee at Posit, PBC (formerly known as RStudio), where he helped create the RStudio IDE and Shiny web framework, along with countless complementary tools and packages.