Package Development :: Cheatsheet

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Visit r-pkgs.org to learn more about writing and publishing packages for R.

library(devtools)
library(testthat)
library(roxygen2)

Package Structure

A package is a convention for organizing files into directories, and creates a shareable, installable collection of functions, sample data, and documentation. This cheatsheet shows you how to work with the 7 most common parts of an R package:

  • R/: Write R code for your package
  • DESCRIPTION: Set up metadata and organize package functions
  • NAMESPACE
  • tests/: Verify your code is correct
  • man/
  • vignettes/: Document your code and write tutorials and how-tos
  • data/: Include data sets in your package

There are multiple packages useful to package development, including usethis which handily automates many of the more repetitive tasks. Load and install devtools which wraps together several of these packages to access everything in one step.

Getting Started

Once per machine:

  • Get set up with use_devtools() so devtools is always loaded in interactive R sessions.

    if (interactive()) {
  require("devtools", quietly = TRUE)
  # automatically attaches usethis
}

  • create_github_token(): Set up GitHub credentials.

  • git_vaccinate(): Ignores common special files.

Once per package:

  • create_package(): Create a project with package scaffolding.

  • use_git(): Activate git.

  • use_github(): Connect to GitHub.

  • use_github_action(): Set up automated package checks.

Having problems with git? Get a situation report with git_sitrep().

Workflow

A flow chart describing a typical workflow of editing code, testing code, writing documentation, and checking your package.

Long description of flowchart.

Key steps in the workflow (with keyboard shortcuts)

  • load_all() (Ctrl/Cmd + Shift + L): Load code
  • test() (Ctrl/Cmd + Shift + T): Run tests
  • document() (Ctrl/Cmd + Shift + D): Rebuild docs and NAMESPACE
  • check() (Ctrl/Cmd + Shift + E): Check complete package

R/

All of the R code in your package goes in R/. A package with just an R/ directory is still a very useful package.

  • Create a new package project with create_package("path/to/name").

  • Create R files with use_r("file-name").

  • Follow the tidyverse style guide at style.tidyverse.org

  • Put your cursor on a function and press F2 to go to its definition

  • Find a function or file with the keyboard shortcut Ctrl+.

DESCRIPTION

The DESCRIPTION file describes your package, sets up how your package will work with other packages, and applies a license.

  • Pick a license with use_mit_license(), use_gpl3_license(), use_proprietary_license().

  • Add packages that you need with use_package().

Import packages that your package requires to work. R will install them when it installs your package. Add with use_package(pkgname, type = "imports")

Suggest packages that developers of your package need. Users can install or not, as they like. Add with use_package(pkgname, type = "suggests")

NAMESPACE

The NAMESPACE file helps you make your packages self-contained: it won’t interfere with other packages, and other packages won’t interfere with it.

  • Export functions for users by placing @export in their roxygen comments.

  • Use objects from other packages with package::object or @importFrom package object (recommended) or @import package (use with caution).

  • Call document() to generate NAMESPACE and load_all() to reload.

Table comparing features/purpose of DESCRIPTION (left column) vs NAMESPACE (right column)
DESCRIPTION NAMESPACE
Makes packages available Makes functions available
Mandatory Optional (can use :: instead)
use_package() use_import_from()

man/

The documentation will become the help pages in your package.

  • Document each function with a roxygen block above its definition in R/. In RStudio, Code > Insert Roxygen Skeleton (Keyboard shortcut: Mac Shift+Option+Cmd+R, Windows/Linux Shift+Alt+Ctrl+R) helps.

  • Document each data set with an roxygen block above the name of the data set in quotes.

  • Document the package with use_package_doc().

  • Build documentation in man/ from Roxygen blocks with document().

roxygen2

The roxygen2 package lets you write documentation inline in your .R files with shorthand syntax.

  • Add roxygen documentation as comments beginning with #'.

  • Place an roxygen @ tag (right) after #' to supply a specific section of documentation.

  • Untagged paragraphs will be used to generate a title, description, and details section (in that order).

#' Add together two numbers
#' 
#' @param x A number.
#' @param y A number.
#' @returns The sum of `x` and `y`
#' @export
#' @examples
#' add(1, 1)
add <- function(x, y) {
  x + y
}

Common roxygen Tags:

  • @examples
  • @export
  • @param
  • @returns

Also:

  • @description
  • @examplesif
  • @family
  • @inheritParams
  • @rdname
  • @seealso

vignettes/

  • Create a vignette that is included with your package with use_vignette().
  • Create an article that only appears on the website with use_article().
  • Write the body of your vignettes in R Markdown.

Websites with pkgdown

  • Use GitHub and use_pkgdown_github_pages() to set up pkgdown and configure an automated workflow using GitHub Actions and Pages.
  • If you’re not using GitHub, call use_pkgdown() to configure pkgdown. Then build locally with pkgdown::build_site().

README.Rmd + NEWS.md

  • Create a README and NEWS markdown files with use_readme_rmd() and use_news_md().

tests/

  • Create a test file with use_test().
  • Write tests with test_that() and expect_().
  • Run all tests with test() and run tests for current file with test_active_file().
  • See coverage of all files with test_coverage() and see coverage of current file with test_coverage_active_file().
Table of expect functions and what each one tests
Expect statement Tests
expect_equal() Is equal? (within numerical tolerance)
expect_error() Throws specified error?
expect_snapshot() Output is unchanged? 
test_that("Math works", {
  expect_equal(1 + 1, 2)
  expect_equal(1 + 2, 3)
  expect_equal(1 + 3, 4)
})

data/

  • Record how a data set was prepared as an R script and save that script to data-raw/ with use_data_raw().
  • Save a prepared data object to data/ with use_data().

Package States

The contents of a package can be stored on disk as a:

  • source - a directory with sub-directories (as shown in Package Structure)
  • bundle - a single compressed file (.tar.gz)
  • binary - a single compressed file optimized for a specific OS

Packages exist in those states locally or remotely, e.g. on CRAN or on GitHub.

From those states, a package can be installed into an R library and then loaded into memory for use during an R session.

A diagram describing the functions that move a package between different states. The description below describes this in detail.

Use the functions below to move between these states:

  • library(): Installed in Library to loaded in Memory.
  • install.packages(): Binary from CRAN repository to installed in Library.
  • install.packages(type = "source"): Source code from CRAN repository to Bundle, to installed in Library.
  • install_github(): Source code from GitHub repository to Bundle to installed in Library.
  • install(): Local source code to bundle to installed in Library.
  • build(): Local source to Bundle.
  • build(binary = TRUE): Local source to Binary.
  • load_all(): Local source to loaded in Memory.

CC BY SA Posit Software, PBC • info@posit.co • posit.co

Learn more at r-pkgs.org.

Updated: 2023-07.

packageVersion("devtools")
[1] '2.4.5'
packageVersion("usethis")
[1] '2.2.2'
packageVersion("testthat")
[1] '3.1.10'
packageVersion("roxygen2")
[1] '7.2.3'