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
I would appreciate knowing if any development of this has been discussed - as
well as ideas or useful feedback in general?
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