prefab

prefab provides an opinionated theme system for setting up R projects. A theme is a function that returns an ordered list of steps that deploy files, inject text, or run functions. Because themes are functions, they take parameters, compose with +, and ship in packages. Nothing touches the file system until you apply a theme with use_theme() or create_project().

Installation

install.packages(
  "prefab",
  repos = c("https://economic.r-universe.dev", getOption("repos"))
)

Quick start

Create a new project with scaffolding and Claude Code config:

library(prefab)

create_project("~/projects/my-analysis", r_analysis())
#> ✔ Running fs::dir_create('data_raw')
#> ✔ Running fs::dir_create('data_processed')
#> ✔ Writing 'main.R' (new)
#> ✔ Writing 'README.md' (new)
#> ✔ Writing '.gitignore' (new)

Add a theme to an existing project:

use_theme(claude_r_analysis())
#> ✔ Writing '.claude/settings.json' (new)
#> ✔ Writing '.claude/rules/r_analysis.md' (new)
#> ✔ Writing '.gitignore' (new)

Built-in themes

Theme	Description
r_analysis()	main.R, README.md, .gitignore, data_raw/, data_processed/
r_targets()	_targets.R, packages.R, README.md, R/ dir, .gitignore
claude_r_analysis()	Claude Code settings and rules for data analysis projects
claude_r_package()	Claude Code settings and rules for R packages
claude_r_targets()	Claude Code settings and rules for targets projects

Composition

Themes compose with +. Steps execute left-to-right:

theme <- r_targets() + claude_r_targets()

create_project("my-project", theme)
#> ✔ Writing '_targets.R' (new)
#> ✔ Writing 'packages.R' (new)
#> ✔ Writing 'README.md' (new)
#> ✔ Writing '.gitignore' (new)
#> ✔ Running fs::dir_create('R')
#> ✔ Writing '.claude/settings.json' (new)
#> ✔ Writing '.claude/rules/r_targets.md' (new)
#> ✔ Writing '.claude/skills/targets-branching/SKILL.md' (new)
#> ✔ Writing '.claude/rules/r_analysis.md' (new)
#> ✔ Writing '.gitignore' (union)

Building custom themes

prefab ships with some basic themes, but its real goal is to make it simple for you to apply the kinds of project scaffolding that you prefer. There are three ways to build your own themes:

From a directory of files. Arrange template files in a folder and theme_from_dir() turns them into a theme.

my_theme <- theme_from_dir("~/my-project-layout")

From steps. Build themes programmatically with step_file(), step_text(), and step_run():

my_theme <- function() {
  new_theme(
    step_file("~/my_themes/header.R", "R/header.R"),
    step_text(c("*.csv", "*.rds"), ".gitignore", strategy = "union"),
    step_run(fs::dir_create, "tables", .label = "fs::dir_create('tables')")
  )
}

By composing existing themes. Combine and extend built-in or custom themes with +:

my_theme <- theme_from_dir("~/my-project-layout") + claude_r_analysis() 

Sharing and re-using custom themes

Source a file. Save theme functions in an external script and source them. load_themes() makes that easy: put themes in ~/.prefab-themes.R (or set the PREFAB_THEMES environment variable) and call load_themes() to make them available.

load_themes()
use_theme(my_analysis_theme())

Ship in a package. This package ships with several basic themes, and you can add themes (which are just functions) to your own package. Use from_package() to resolve template files from inst/. Best for sharing themes across an organization.

More information on building and deploying themes is in the Getting Started vignette.

Acknowledgments

This package draws heavily on ideas from the R packages:

• starter by Daniel D. Sjoberg
• tflow by Miles McBain
• usethis by Hadley Wickham, Jennifer Bryan, Malcolm Barrett, and Andy Teucher.