R Development

R Package Development

Use this skill when working with R packages to ensure proper development workflows, testing patterns, and documentation standards.

Development Workflow

R Environment

• Use radian with R as an alias so call R scripts using Rscript
• Do not run devtools::test with grep; read the whole output

Package Building and Management

# Load package for interactive development
devtools::load_all()

# Update documentation (REQUIRED before committing R changes)
devtools::document()

# Run all tests
devtools::test()

# Run specific test file
testthat::test_file("tests/testthat/test-filename.R")

# Run tests matching a pattern
devtools::test(filter = "pattern")
testthat::test_local(filter = "pattern")

# Check package (R CMD check)
devtools::check()

# Build package
devtools::build()

# Install package locally
devtools::install()

# Check with vignettes built
devtools::check(build_args = c("--compact-vignettes=both"))

Code Quality and Style

# Lint package (configuration in .lintr)
lintr::lint_package()

# Lint specific file
lintr::lint("R/filename.R")

# Style code (pre-commit hook typically uses tidyverse style)
styler::style_pkg()

# Check test coverage
covr::package_coverage()

Documentation Building

# Build vignettes
devtools::build_vignettes()

# Build specific vignette
rmarkdown::render("vignettes/name.Rmd")

# Build pkgdown site locally
pkgdown::build_site()

Testing Best Practices

testthat Patterns

Preferred expectations:

• expect_identical() > expect_equal() (when exact match expected)
• Multiple expect_true() calls > stacking conditions with &&
• expect_s3_class() > expect_true(inherits(...))
• Use specific expect_* functions:
• expect_lt(), expect_gt(), expect_lte(), expect_gte()
• expect_length()
• expect_named()
• expect_type()

Examples:

# Good
expect_identical(result, expected)
expect_s3_class(obj, "data.frame")
expect_lt(value, 10)
expect_true(condition1)
expect_true(condition2)

# Avoid
expect_equal(result, expected)  # when identical match is needed
expect_true(inherits(obj, "data.frame"))
expect_true(value < 10)
expect_true(condition1 && condition2)

Test Organisation

• Use testthat edition 3
• Test files named test-{component}.R
• Helper files in tests/testthat/helper-{name}.R
• Setup files in tests/testthat/setup.R for shared fixtures
• Custom expectations in tests/testthat/helper-expectations.R

Conditional Testing

# Skip tests on CRAN
testthat::skip_on_cran()

# Skip if not on CI
testthat::skip_if_not(on_ci())

# Skip if package not available
testthat::skip_if_not_installed("package")

Documentation Standards

roxygen2 Best Practices

Avoid duplication with `@inheritParams`:

#' @param x Input data
#' @param ... Additional arguments
my_function <- function(x, ...) {}

#' @inheritParams my_function
#' @param y Another parameter
wrapper_function <- function(x, y, ...) {}

Documentation structure:

• One sentence per line in descriptions
• Max 80 characters per line
• Use @family tags for related functions
• Use @examples or @examplesIf for examples
• UK English spelling

Example documentation:

#' Process input data
#'
#' This function processes the input data according to specified parameters.
#' It returns a processed data frame with additional columns.
#'
#' @param data A data.frame containing the input data
#' @param method Character string specifying the processing method
#'
#' @return A data.frame with processed results
#'
#' @family preprocessing
#'
#' @examples
#' \dontrun{
#' result <- process_data(my_data, method = "standard")
#' }
#'
#' @export
process_data <- function(data, method = "standard") {
  # implementation
}

Code Style Guidelines

Naming Conventions

• Internal functions: Prefix with .

  .internal_helper <- function() {}

• Exported functions: Use snake_case

  public_function <- function() {}

Formatting

• Max 80 characters per line
• No trailing whitespace
• No spurious blank lines
• Use tidyverse style guide
• Set up pre-commit hooks for automatic formatting

Pre-commit Hooks

Typical .pre-commit-config.yaml includes:

• style-files: Auto-format R code
• lintr: Lint R code
• readme-rmd-rendered: Ensure README.md is up-to-date
• parsable-R: Check R syntax
• deps-in-desc: Check dependencies are in DESCRIPTION

# Install pre-commit
pip install pre-commit

# Install hooks
pre-commit install

# Run manually
pre-commit run --all-files

Common Data Structures

data.table Usage

Many R packages use data.table for performance:

• Functions often expect/return data.table objects
• Use data.table::setDT() or custom coerce_dt() to ensure input is data.table
• Set keys for efficient joins: data.table::setkey(dt, col)
• Use := for in-place modification

S3 Classes

• Check class with inherits() or expect_s3_class()
• Document S3 methods properly
• Export constructors, not internal class definitions

Package Dependencies

Managing Dependencies

# Use specific package functions with ::
package::function()

# Add to DESCRIPTION Imports or Suggests
usethis::use_package("package_name")
usethis::use_package("package_name", type = "Suggests")

Common R Package Ecosystem Tools

• devtools: Development workflow
• testthat: Testing framework
• roxygen2: Documentation generation
• usethis: Package setup automation
• lintr: Code linting
• styler: Code formatting
• covr: Test coverage
• pkgdown: Website generation

When to Use This Skill

Activate this skill when:

• Developing R packages
• Writing R tests
• Documenting R functions
• Setting up R package infrastructure
• Running R package checks
• Working with devtools, testthat, or roxygen2

This skill provides R-specific development patterns. Project-specific architecture and domain knowledge should remain in project CLAUDE.md files.