Jupyter DSLs
Cross-posted from the Helical project blog.
One of the broader goals of the Helical project is to make writing, maintaining, and debugging experiments easier and safer for the end-user through a novel domain-specific language. However, learning a new formal language can itself contribute to the difficulty of encoding an experiment. Therefore, we are intersted in mitigating the effects of language learning/novelty. To this end, a Northeastern coop student (Kevin G. Yang) investigated the suitability of using Jupyter notebooks as an execution environment for experiments last year.