AnswerDotAI / AnswerDotAI/nbdev

Use different requirements for different notebooks when testing for Documentation

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enhancement
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Jupyter Notebook
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Beschreibung

One popular request I'm hearing about are companies that want to use Quarto as a modern [Knowledge Repo](https://github.com/airbnb/knowledge-repo). Other products like [Rsutdio Connect](https://www.rstudio.com/products/connect/) offer similar functionality to the Knowledge Repo.

The business problem to be solved is that data teams want to share insights, experiments and knowledge in the form of more syndicated knowledge internally within their companies. The sharing of knowledge is absolutely critical when there are larger data teams and you don't want people redoing the same work over and over again.[^1] Where the current solutions are somewhat lacking is the ability to test articles automatically for reproduceability, whereby anyone else can reliably run a notebook backed article, so they too can play with the code and tweak it. A closely related problem is having notebook specific requirements, with an affordance running notebooks easily in the right environment.

While this hetrogenous environment scenario is not important for creating python projects, it is critical for a "Central Knowledge Repository" across a distributed team of people using many different tools.

cc: @jph00 @seeM

[^1]: We faced this problem as well at Airbnb, which created [The Knowledge Repo](https://github.com/airbnb/knowledge-repo), and were on the cusp of purchasing RStudio Connect when I was at GitHub, but I left before that process could be completed.

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Rechercherichtung

Das Issue nennt keine Dateien, Tests oder Einstiegspunkte. Kläre zunächst, welche Notebook-Umgebungen und Anforderungsformate unterstützt werden müssen, und ermittle anschließend den aktuellen Workflow für Dokumentationstests. Als abgeschlossen sollte gelten, dass verschiedene Notebooks geeignete Anforderungen deklarieren oder verwenden können und reproduzierbar in ihren vorgesehenen Umgebungen getestet werden.

Vom Indexierungsmodell aus dem Issue-Text verfasst.

Bewertung

Tech-Stack
jupyter-notebook, python
Bereich
documentation, testing-qa
Issue-Typ
Feature
Schwierigkeit
5/5
Geschätzter Aufwand
Über eine Woche
Aktivitätsstatus
Veraltet
Klarheit
Muss geklärt werden
Anfängerfreundlichkeit
20/100

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