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

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