mercury

I'm running a SaaS for serving Python notebooks as web apps [0]. We offer widgets for notebooks and server, both as open source [1]. In open source you are managing the server instance with default Django Admin Panel. In the SaaS version, we have a dashboard for managing site (adding users, setting visibility, usage analytics), the dashboard is closed source. The open source version by default is single site, but can be switched to multi-tenant (multiple domains and subdomains) just by adding instances in the database. In case of update, sometimes it is required to update both code bases. Employees have access to both code bases. We started with open-source first, and added SaaS offering after ~2 years. The code base split was a natural choice. At first, I didn't want to add SaaS, because managing servers is a lot of work. But, we have a

I build dashboards in Jupyter Lab. My plotting libraries are Altair, matplotlib, seaborn, Plotly - all work well in notebook. My favorite is Altair. It provides interactivity for charts, so you can move/zoom your plots and have tooltips. It is much lighter than Plotly after saving the notebook to ipynb file. Altair charts looks much better than in matplotlib. One drawback, that exporting to PDF doesn't work. To serve notebook as dashboard with code hidden, I use Mercury framework, you can check example https://runmercury.com/tutorials/vega-altair-dashboard/ disclaimer: I'm author of Mercury framework https://github.com/mljar/mercury