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Sun 22 - Fri 27 October 2017 Vancouver, Canada
Sun 22 Oct 2017 13:52 - 14:15 at Regency A - Session 3 Chair(s): Eric Walkingshaw

Interactive notebooks, such as provided by the Jupyter platform [2], are gaining traction in scientific computing, data science, and machine learning. Developing a Jupyter kernel machinery for a new language, however, requires considerable effort. In this extended abstract, we present Bacatá, a language-parametric bridge between Jupyter and the Rascal language workbench [3]. Reusing existing language components, such as a parsers, interpreters, Read-Eval-Print Loop (REPLs) and autocomplete, Bacatá generates a Jupyter kernel machinery so that the DSL can be used in notebook form. We sketch the architecture of Bacatá and demonstrate it in action using a DSL for image processing, called Amalga.