Dear all, I would appreciate your feedback with a potential research area, specifically within Jupyter - and perhaps more generally in Python.
Interactive data analysis in frameworks like jupyter notebooks has a common issue - the modification of potentially large datasets within an interactive session. Unintentional modification is frequent, and the common solution is to re-run the steps that were required to get from a data file to the point in question. This reduces the usability of the analysis tools, makes “what-if” exploration difficult, and creates a lot of unnecessary overhead for either manually saving state or re-running scripts to recreate it. I'm investigating a proposed project focused on the use of relational Multi-Version Concurrency Control (MVCC) techniques from database systems for these interactive workloads. In essence allowing a control z undo functionality to return to the previous state after running a particular step of an interactive script. I would appreciate knowing if any development of this has been discussed - as well as ideas or useful feedback in general? Kind regards Jayme Bird -- You received this message because you are subscribed to the Google Groups "Project Jupyter" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/jupyter/1410954636.3371205.1519295968702.JavaMail.zimbra%40cwi.nl. For more options, visit https://groups.google.com/d/optout.
