Comment by RobinL | Hacker News Reader

Comment by RobinL | Hacker News Reader

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As an occasional R user, I think R markdown one of the things that R does really well. For data scientists who want to output reports (mix of text and calculations), I haven't come across anything as mature or easy to use in the Python ecosystem. I'm a big user of Jupyter notebooks, but version control issues put me off, and I've never got to grips customising the formatting of jupyter nbconvert.

It's worth highlighting that R Markdown actually supports a number of languages including Python - for instance see here: https://bookdown.org/yihui/rmarkdown/language-engines.html

For example, I am currently considering using R markdown to author the documentation for one of my Python packages. Currently my documentation is written in markdown, but I keep having to copy and paste calculations and tables into the markdown. When things change, it would be nice to just be able to re-run the R markdown, converting Rmd -> md and thereby interpolating the latest version of all calculations into the final markdown doc.

For the Python in markdown case, you might be interested in one of my projects that allows executable Python code (including optional Jupyter kernel support) in Pandoc markdown: https://github.com/gpoore/codebraid. Pandoc does all the document parsing (there is no regex preprocessor for extracting code), so converting markdown to markdown often works particularly well.

Hydrogen for Atom actually can have executable python in markdown, and more - write python in .py files and execute strings or define blocks by "# %%". It's not the same of course but for my usecases it's more convenient (given that it works in a proper code-editor with all needed plugins).

I'd strongly agree with this. I use R Markdown with Python in the Rstudio IDE, and prefer it to Jupyter. The publishing pipeline is really flexible, e.g. with one-click deployment to RStudio Server [0] (which is a paid product).

No affiliation to RStudio, just a happy customer.

[0]: https://rstudio.com/products/rstudio/download-server/

Currently working on a DA masters with a background in markdown and was so happy to discover this.

Then I was baffled to discover that there wasn’t an equivalent for Python. Jupyter is great, but I really love the simplicity of my text files and I’m surprised that there isn’t a major implementation given how popular both markdown and Python are. I guess notebooks are just too appealing.

Honestly jank and bad ergonomics pervade the Python data science ecosystem. The pandas API is kind of bad (multi-indexes anyone?) matplotlib is way too low level, tensorflow is a shitshow. I think the R community got lucky with a greater focus on user experience, even if it comes at the cost of explicitness sometimes (lots of DSL's with a lot of 'magic').

Honestly, in my experience, R's DSLs are not a bad thing. When you are doing analytics day in and out you basically are speaking the DSL anyway, so what if you have to learn this slightly different language if it expresses what you want to accomplish clearly?

it was pretty wild to hear Hadley Wickham invoke Cognitive Behavioral Therapy in his most recent rstudio::conf keynote - dude is super in tune with how humans use open source data analysis tools

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