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Voila – From notebooks to standalone web applications and dashboards

voila.readthedocs.io

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Re: Voila – From notebooks to standalone web applications and dashboards

#91

Earlier quoted context omitted.

I don't think you're getting the difference between possible & clean for programmers, vs. easy & straightforward for the target market. Most non-engineers don't want to spend time learning and tweaking this stuff, they want to work on the analysis, domain problem, and later, sharing it with others, not spending hours learning & debugging development & UI stuff. That's time away from their actual work & their families…

Thanks for the response and context. I work in a different domain to data science and it's fair to say that most people I work with would prefer writing a few 10s of lines of python than many pages of SQL! Regarding your second point, looking at streamlits announcements page [1] it seems many features being added, layouts/themes and session state/callbacks for example, indicate to me that streamlit is heading in the…

Right, but the key is "you must do X" vs "later, and only if you want, you can optionally layer on X". Users of StreamLit disinterested in programming noise have a lot fewer framework-mandated operational burdens than Panel because the smart defaults are smart. In contrast, anyone using Panel has do a lot more practically + conceptually to get a minimally reasonable result. That's the difference between 1-2 people in a team/org being successful, vs most.

Though again, I'm not a zealot: the StreamLit starting point is still too high in my experience for most teams, so both are wrong. For most people, the default should be no Python, at most SQL or whatever DB lang, and optionally drop down to Python for some cool bits. Ironically, I just got off a call a few hours ago where this exact issue makes us excited about starting with StreamLit, yet we're also already scheduling tools to replace it with something more realistic for 10X+ wider enterprise adoption.

Re: Voila – From notebooks to standalone web applications and dashboards

#92
post #18
post #5

Earlier quoted context omitted.

Only you know your data volumes but for the scenarios in which I've reached for Jupyter they've often involved very large amounts of data and calculating on the server is what I wanted and needed. Agreed that for some things, it would be great to be able to explicitly offload to the browser.

Yes, my dataset is tiny. I mainly use the JS notebook to analyze my selftracking log [1] which is about 10k lines of data at the moment. I have not yet tried to load a lot of data into it. Would be interesting to see when the load time starts to outweight the benefits of instant calculations. Maybe at something like 10 million datasets? Hard to say. 1: https://www.gibney.org/a_syntax_for_self-tracking

Have you seen https://nomie.app? You can use a CouchDB backend to store the logs as semi-structured data.
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