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During/after execution, failed notebooks would also be stored in the cache, in a separate
folder, with a 'failure record' that's linked to the 'staged record' (not yet implemented). This will be deleted when the notebook is unstaged or execution re-run.
Then, given a staged PK/URI, you can work out the build status, based on whether a complimentary commit/failure record exists, and retrieve any requisite data/notebooks.
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For html plugins to parse the reports we will need to define a default report structure. In QuantEcon we have used json with the following structure but we may want to think a bit more deeply about what fields we wish to record etc.
`JupyterExecutorBasic` has been restructured to:
- handle more exception
- have a better separation between cache access and notebook execution (may be changed further at a later date)
- Capture notebook execution, exception tracebacks and store them on the staged record (see README). This moves towards addressing #14
- Report final summary of executed/excepted on CLI
Also added an 'auto-generate' function for creating the CLI example section of the README