Datapane is the easiest way to create data science reports from Python.
Thanks for the mention - I'm one of the people building datapane. Our Python framework (https://github.com/datapane/datapane) allows you to programmatically create reports from data, plots, and markdown which you can share -- from within your pipeline or from a local notebook/script.
Dynamic Documents for R
If you're not already aware of and using RMarkdown, make learning it a priority. I use both R and Python extensively. Although Jupyter Notebooks have utility, RMarkdown is the superior tool for the most flexibility in reporting.
Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.
Obsidian Compatibility with R
1 project | reddit.com/r/ObsidianMD | 31 May 2022
As of today, LaTeX-styled maths natively supported in GitHub Markdown (comments, issues, README.md, etc) $n!!$
1 project | reddit.com/r/math | 20 May 2022
R Studio R Markdown error code
1 project | reddit.com/r/RStudio | 8 Mar 2022
Securing R Markdown Documents
4 projects | reddit.com/r/rstats | 16 Feb 2022
[D] Research paper figure drawing
4 projects | reddit.com/r/MachineLearning | 27 Dec 2021