Additional Resources / Readings • writing.reusable.code

Style Guides

“The tidyverse style guide”
- Hadley Wickham’s online resource with details on naming and styling R code
“Style Guide for Python Code”
- the Python Enhancement Proposal from Guido van Rossum, Barry Warsaw, and Nick Coghlan

“Code Smells and Feels”
- GitHub repo from Jenny Bryan on “code smells” - also check out the related slides
“Writing clear code”
- notes from Karl Broman
“Writing Clean Scientific Software”
- slides from Nick Murphy on clean coding (examples in Python, a bit physics-oriented)
“Column Names as Contracts”
- Blogpost from Emily Riederer on selecting good column names to facilitate a data analysis workflow
“How patterns in variable names can make code easier to read.”
- Short video from Felienne Hermans on variable and object naming
“Twelve quick tips for software design”
- paper from Greg Wilson about designing larger pieces of code

“Functions”
- book chapter from Hadley Wickham & Garrett Grolemund’s “R for Data Science”

“RMarkdown Driven Development (RmdDD)”
- Blogpost from Emily Riederer on structuring RMarkdown documents for data analysis; see also the “RMarkdown Driven Development: the Technical Appendix”
“The Wrong Abstraction”
- blogpost from Sandi Metz on refactoring and complexity
“The targets R package”
- targets is a workflow package to help manage large and complex analyses
“My Workflow for Open and Reproducible Science as an Academic Researcher in Biomedicine”
- a broad overview of combining snakemake, RStudio projects, and github for reproducible workflows, from Ruben Van Paemel