DataSpell Local History: Restored Notebook Lacks Cell Outputs

DataSpell’s built‑in Local History records incremental snapshots of project files, including Jupyter notebooks (.ipynb). When a notebook is restored from a snapshot, the JSON file is replaced exactly, but the IDE does not automatically re‑populate the cell output area or re‑establish the active Python kernel. As a result, users often see a notebook that looks identical to the snapshot but with empty output cells, requiring manual re‑execution of code.

This behavior stems from Local History’s file‑level design: it captures only the file contents, not the runtime environment or kernel state. Consequently, any variables, imports, or database connections that existed at the time of the snapshot are lost. Users must re‑configure the interpreter, reconnect to data sources, and re‑run cells to recover the full interactive experience.

Given these constraints, several questions remain open:

• Does Local History currently capture cell outputs, or are they always omitted?
• What reliable methods exist to verify that a restored notebook’s outputs match a known good snapshot?
• Should DataSpell extend Local History to preserve kernel state (variables, imports, environment) alongside the notebook file?