devtools
Tools to make an R developer’s life easier
devtools is an R package that simplifies the workflow of developing R packages by providing functions for common tasks like loading code, generating documentation, running tests, and building packages.
The package streamlines iterative development through functions like load_all() for instantly testing changes without reinstalling, document() for updating documentation, and check() for validating package structure. It also provides installation helpers for packages from GitHub, GitLab, and other sources. devtools has been modularized into focused packages (like testthat, roxygen2, and usethis) that it automatically loads, giving developers a comprehensive toolkit through a single library call.
Contributors#
Resources featuring devtools#
Using R package structure for data science projects | Kylie Ainslie | Data Science Lab
The Data Science Lab is a live weekly call. Register at pos.it/dslab! Discord invites go out each week on lives calls. We’d love to have you!
The Lab is an open, messy space for learning and asking questions. Think of it like pair coding with a friend or two. Learn something new, and share what you know to help others grow.
On this call, Libby Heeren is joined by Kylie Ainslie who walks through how structuring data science projects as R packages provides a consistent framework that integrates documentation for you and facilitates collaboration with others by organizing things really well. Kylie says, “I stumbled on using an R package structure to organize my projects a number of years ago and it has changed how I work in such a positive way that I want to share it with others! In a world where our attention is constantly being pulled in many directions, efficiency is crucial. Structuring projects as R packages is how I work more efficiently.”
Hosting crew from Posit: Libby Heeren, Isabella Velasquez
Kylie’s Bluesky: @kylieainslie.bsky.social Kylie’s LinkedIn: https://www.linkedin.com/in/kylieainslie/ Kylie’s Website: https://kylieainslie.github.io/ Kylie’s GitHub: https://github.com/kylieainslie
Resources from the hosts and chat:
posit::conf(2026) call for talks: https://posit.co/blog/posit-conf-2026-call-for-talks/ Kylie’s posit::conf(2025) talk: https://www.youtube.com/watch?v=YzIiWg4rySA {usethis} package: https://usethis.r-lib.org/ R Packages (2e) book: https://r-pkgs.org/ Paquetes de R (R Packages in Spanish): https://davidrsch.github.io/rpkgs-es/ {box} package: https://github.com/klmr/box extdata docs in Writing R Extensions: https://cran.r-project.org/doc/manuals/R-exts.html#Data-in-packages-1 Tan Ho’s talk on NFL data: https://tanho.ca/talks/rsconf2022-github/ {rv} package: https://a2-ai.github.io/rv-docs/ Whether to Import or Depend: https://r-pkgs.org/dependencies-mindset-background.html#sec-dependencies-imports-vs-depends {pkgdown} package: https://pkgdown.r-lib.org/ Edgar Ruiz’s {pkgsite} package: https://github.com/edgararuiz/pkgsite
Attendees shared examples of data packages in the chat! Here they are: https://kjhealy.github.io/nycdogs/ https://kjhealy.github.io/gssr/ https://github.com/deepshamenghani/richmondway https://github.com/kyleGrealis/nascaR.data https://github.com/ivelasq/leaidr
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Timestamps: 00:00 Introduction 06:17 Reviewing the disorganized project example 10:01 Creating the package structure using create_package 17:50 Organizing external data and scripts in the inst folder 22:55 Adding a README and License 29:06 “What are the advantages to packaging a project?” 33:35 Writing Roxygen2 documentation 36:06 “Do you type return at the end of your functions?” 41:55 Handling dependencies with use_package 43:53 “Can you just use require(dplyr) at the top?” 47:45 Setting up a pkgdown site 50:11 Creating vignettes 52:22 “What is the role of the usethis package?” 54:18 Loading the package with devtools::load_all
Teaching Data Sharing through R Data Packages (Kelly McConville, Bucknell) | posit::conf(2025)
Teaching Data Sharing through R Data Packages
Speaker(s): Kelly McConville
Abstract:
Data science courses tend to teach students reproducible workflows. However, the origin of the data used in these workflows and definitions of the variables used are often not emphasized. This talk addresses this gap by focusing on how to teach students effective data sharing through the creation of R data packages. We’ll explore how to leverage key packages, such as devtools and usethis, and will demonstrate how to guide students in generating appropriate documentation through ReadMes, help files, and vignettes. Furthermore, we’ll discuss common pitfalls encountered when first learning to create R packages and will propose how to structure a project assignment where an R data package serves as the primary deliverable.
Materials - https://mcconvil.github.io/r-data-package-talk-f25/data_packages_talk posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/
Unlock the Power of DataViz Animation and Interactivity in Quarto - posit::conf(2023)
Presented by Deepsha Menghani
Plot animated and interactive visualizations with Plotly and Crosstalk in Quarto using R. In thi sintro to Plotly & Crosstalk in R: Using code examples, learn to integrate dashboard elements into Quarto with animated plots, interactive widgets (checkboxes), and linked plots via brushing.
This talk showcases how to use packages, such as Plotly and Crosstalk, to create interactive data visualizations and add dashboard-like elements to Quarto. Using a fun dataset available through the “Richmondway” package, we examine the number of times Roy Kent uses salty language throughout all seasons of ““Ted Lasso.”” We illustrate this using animated plots, interactive selection widgets such as checkboxes, and by linking two plots with brushing capabilities.
Materials:
- Slides: https://deepshamenghani.github.io/posit_plotly_crosstalk/#/title-slide
- Code repo: https://github.com/deepshamenghani/posit_plotly_crosstalk
- Richmondway data package: https://github.com/deepshamenghani/richmondway
- In-Depth Guide to Creating and Publishing an R Data Package (Richmondway) Using Devtools: https://medium.com/p/245b0fd4c359
Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.#
Talk Track: Quarto (2). Session Code: TALK-1143
posit::conf(2023) Workshop: Fundamentals of Package Development
Register now: http://pos.it/conf Instructor: Andy Teucher Workshop Duration: 1-Day Workshop
This workshop is for you if: • You have written several R scripts and find yourself wondering how to reuse or share the code you’ve written • You know how to write functions in R • You are looking for a way to take the next step in your R programming journey
We will be demonstrating some workflows using Git and GitHub. Knowledge of these tools is not required, and you will absolutely be able to complete the workshop without them, but some of the lessons will be more rewarding to you if you are prepared to try them out. If you are looking to get started with Git and GitHub, we recommend you register for the “What they forgot to teach you about R” workshop on Day 1, and join us for this workshop on Day 2.
We are often faced with the need to share our code with others, or find ourselves writing similar code over and over again across different projects. In R, the fundamental unit of reusable code is a package, containing helpful functions, documentation, and sometimes sample data. This workshop will teach you the fundamentals of package development in R, using tools and principles developed and used extensively by the tidyverse team - specifically the ‘devtools’ family of packages including usethis, testthat, and roxygen2. These packages and workflows help you focus on the contents of your package rather than the minutiae of package structure.
You will learn the structure of a package, how to organize your code, and workflows to help you develop your package iteratively. You will learn how to write good documentation so that users can learn how to use your package, and how to use automated testing to ensure it is functioning the way you expect it to, now and into the future. You will also learn how to check your package for common problems, and how to distribute your package for others to use.
This will be an interactive 1-day workshop, and we will be using the RStudio IDE to work through the materials, as it has been designed to work well with the development practices we will be featuring
Building R packages with devtools and usethis | RStudio
Package building doesn’t have to be scary! The tidyverse team has made it easy to get started with RStudio and the devtools/usethis packages. This hour long presentation will walk you through the basics of R package building, and hopefully leave you prepared to go out and build your own package!
Slides: https://colorado.rstudio.com/rsc/pkg-building/ Source Code: https://github.com/jthomasmock/pkg-building
devtools: https://devtools.r-lib.org/ usethis: https://usethis.r-lib.org/ R Packages book: https://r-pkgs.org/index.html
Hadley Wickham | testthat 3.0.0 | RStudio (2020)
In this webinar, I’ll introduce some of the major changes coming in testthat 3.0.0. The biggest new idea in testthat 3.0.0 is the idea of an edition. You must deliberately choose to use the 3rd edition, which allows us to make breaking changes without breaking old packages. testthat 3e deprecates a number of older functions that we no longer believe are a good idea, and tweaks the behaviour of expect_equal() and expect_identical() to give considerably more informative output (using the new waldo package).
testthat 3e also introduces the idea of snapshot tests which record expected value in external files, rather than in code. This makes them particularly well suited to testing user output and complex objects. I’ll show off the main advantages of snapshot testing, and why it’s better than our previous approaches of verify_output() and expect_known_output().
Finally, I’ll go over a bunch of smaller quality-of-life improvements, including tweaks to test reporting and improvements to expect_error(), expect_warning() and expect_message().
Webinar materials: https://rstudio.com/resources/webinars/testthat-3/
About Hadley: Hadley Wickham is the Chief Scientist at RStudio, a member of the R Foundation, and Adjunct Professor at Stanford University and the University of Auckland. He builds tools (both computational and cognitive) to make data science easier, faster, and more fun. You may be familiar with his packages for data science (the tidyverse: including ggplot2, dplyr, tidyr, purrr, and readr) and principled software development (roxygen2, testthat, devtools, pkgdown). Much of the material for the course is drawn from two of his existing books, Advanced R and R Packages, but the course also includes a lot of new material that will eventually become a book called “Tidy tools”
