coding-in-r

name	coding-in-r
description	How to write R well — renv, tidyverse/data.table, project paths, style, scripts, seeds. TRIGGER when authoring or editing .R/.Rmd/.qmd files. For running R on the Yale SOM HPC cluster (Slurm, renv on /gpfs), use running-r instead.
related	["programming-and-coding","running-r","accelerating-python","code-review"]
updated	2026-05-22T00:00:00.000Z

Coding in R

Rule: renv, portable paths, script as source of truth. Never rely on the global workspace.

For cluster execution, also load running R.

Defaults

• renv for package versions. Commit renv.lock and .Rprofile.
• On SOM HPC: module load r; no rig or mise default.
• pak for fast installs when available.
• styler for formatting.
• lintr for linting.
• here::here() for paths. No setwd() in tracked scripts.
• readr::read_csv() over base read.csv().

install.packages("renv")
renv::init()
renv::install(c("tidyverse", "data.table", "here", "fs", "styler", "lintr"))
renv::snapshot()

Restore with:

renv::restore()

On HPC, restore once before arrays. Do not let many workers install packages concurrently.

Layout

project/
├── renv.lock
├── .Rprofile
├── README.md
├── scripts/       # entry points
├── R/             # shared helpers
├── notebooks/     # .Rmd / .qmd
├── data/raw/      # immutable; usually ignored
├── data/derived/  # rebuildable
└── results/       # figures/tables/logs

Paths

Never commit setwd() or personal absolute paths.

library(here)
counts_path <- here("data", "raw", "counts.csv")
counts <- readr::read_csv(counts_path)

For machine-specific roots, read an environment variable from .Renviron or the shell.

Style

• snake_case for variables/functions.
• <- for assignment; = for arguments.
• Native pipe |> unless %>% materially helps.
• 2-space indentation; aim for 80-char lines, max 120.
• Named arguments: mean(x, na.rm = TRUE), not mean(x, T).
• library() at top.
• Never attach() or <<-.
• set.seed(42) before stochastic work.

Data

Default to tidyverse for clarity. Use data.table when data are large, joins/grouping dominate, or in-place mutation matters. Benchmark before rewriting clear code for speed.

CLI skeleton

#!/usr/bin/env Rscript
suppressPackageStartupMessages({
  library(optparse)
})

option_list <- list(
  make_option(c("-i", "--input"), type = "character"),
  make_option(c("-o", "--output"), type = "character")
)
opt <- parse_args(OptionParser(option_list = option_list))
if (is.null(opt$input) || is.null(opt$output)) {
  stop("--input and --output are required", call. = 


set.seed

Checklist

• styler::style_dir(".") run
• lintr::lint_dir(".") clean or justified
• No setwd() or personal paths
• set.seed() where needed
• renv::snapshot() if deps changed
• Small smoke test run
• HPC uses module load r + renv, not rig/mise

Further reading

• Tidyverse style guide
• renv
• data.table
• here