The earliest incarnation of this project was built as a way of running Haskell snippets in knitr (a report generation software for R). Jonathan Carroll, a DataHaskell contributor, was working on an article showcasing Haskell’s viability for data science workloads. We built a small shell script that took Haskell code snippets, transformed them to work with GHCi (particularly putting multi-line functions in blocks), evaluated them in the command line, and then captured the output.
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On expression-heavy workloads or just wide tables, it can give a significant performance boost for those operations. However, standard LLVM-based JIT is notoriously slow at compilation.