I just wanted to follow up on the community discussion yesterday.
@choldgraf shared notes from the Moore-Sloan summit (this one Welcome to the 2019 MSDSE Summit!) that, I think, are from a talk/meeting about pooling resources around best practices for software development (sorry for all the prepositions in that sentence)
Collecting resources on best practices for scientific software development - Google Docs
and we talked about related efforts, #8 in the notes here:
pyOpenSci Meeting Notes - 14 November 2019 - HackMD
There’s a couple of resources I thought might be useful that I didn’t see in there.
The Merely Useful site from Greg Wilson and co-conspirators has a whole section on research software engineering:
They are definitely still developing it but I think big picture the outline is very good and language agnostic
One of the sources they cite is this Python 102:
Not sure if those links are useful, but … hopefully maybe
I was thinking about this more today because our graduate data science group is holding a Software Carpentry workshop next weekend, and I really would like to hold a (less intense) event right after to help keep new coders going, and help keep our little community together.
I think the “Organizing Code” section from Python 102 could be the basis for a nice walkthrough on how to go from scripts to a first package: Organizing code for a Python project — Python 102
My idea is to do a follow-along demo based on that, and then send people home with links to read the rest of the site. I have a couple little things I thought might be nice to throw in, e.g. an example with
@lwasser @xmnlab if you all think a report back on my first attempt at teaching some sort of Scientific Python 102 would be interesting as a blog post, I’d be happy to write it up. E.g., to spark more dialogue about best practices and how to make things less intimidating for beginners