Grow your data science skills at posit::conf(2024)

August 12th-14th in Seattle

One persistent challenge with developing Shiny apps for live deployment, has been the R language runtime’s single-threaded nature. Because of this, a given Shiny app process can only do one thing at a time: if it is fitting a model for one client, it cannot simultaneously serve up a CSV download for another client. Asynchronous programming offers a way to offload certain classes of long-running operations from the main R thread, such that Shiny apps can remain responsive. The next major release of Shiny will include deep support for asynchronous programming via promises, inspired by the JavaScript abstraction of the same name, but with significant enhancements to integrate seamlessly with Shiny’s reactive constructs and to allow app authors to write code that looks mostly like idiomatic R. Programming with these promises has its own learning curve, but the payoff can be huge if your app has a significant bottleneck.

View Slides

Subscribe to more inspiring open-source data science content.

We love to celebrate and help people do great data science. By subscribing, you'll get alerted whenever we publish something new.