Glinda: Supporting Data Science with Live Programming, GUIs and a Domain-specific Language

Researchers have explored several avenues to mitigate data scientists’ frustrations with computational notebooks, including: (1) live programming, to keep notebook results consistent and up to date; (2) supplementing scripting with graphical user interfaces (GUIs), to improve ease of use; and (3) providing domain-specific languages (DSLs), to raise a script’s level of abstraction. This paper introduces Glinda, which combines these three approaches by providing a live programming experience, with interactive results, for a domain-specific language for data science. The language’s compiler uses an open-ended set of “recipes” to execute steps in the user’s data science workflow. Each recipe is intended to combine the expressiveness of a written notation with the ease-of-use of a GUI. Live programming provides immediate feedback to a user’s input, whether in the form of program edits or GUI gestures. In a qualitative evaluation with 12 professional data scientists, participants highly rated the live programming and interactive results. They found the language productive and sufficiently expressive and suggested opportunities to extend it.