Advanced R Package Development
🗓️ February 2026 24-26 ⏱️ 08:00 - 12:30 daily 🌎 Online
Overview
This advanced workshop builds on the fundamentals of R package development, diving deeper into topics that will help you create robust, well-tested, and maintainable packages. Whether you’ve built one or two basic packages and want to level up your skills, or you’re looking to refine your development practices, this workshop will provide you with advanced techniques and best practices used by experienced package developers.
You will learn advanced function design principles, sophisticated debugging techniques, and comprehensive testing strategies with testthat. We’ll explore object-oriented programming in R (S3, S4, and R6), best practices for including data in packages, and strategies for versioning and releasing your packages. The workshop also covers collaborative development workflows using Git and GitHub, including pull request workflows.
This will be an online, interactive workshop delivered virtually over three consecutive half-days. We will be using RStudio as our primary IDE, though we’ll demonstrate Positron equivalents where relevant.
This workshop is for you if you…
- Have built 1-2 basic R packages and want to advance your skills
- Want to learn best practices for function design and package architecture
- Are looking to improve your testing and debugging workflows
- Want to understand object-oriented programming in R
- Need to collaborate with others on package development
- Are ready to take your R package development to the next level
Prework
Please ensure you have completed the steps in System Setup
Schedule
See the Course Schedule for the full program.
Code of Conduct
Please review and adhere to our Code of Conduct.
Instructors
Andy Teucher is a freelance data scientist and package developer with a passion for teaching others how to use data science tools to make their work more efficient and reproducible. His background is in conservation biology, with an MSc in Ecology from the University of Calgary. He has spent much of his career as a data scientist in government, where he made it his mission to promote and teach open, reproducible data science practices. He has written many R packages for internal use in his teams as well as for a broader audience, with several hosted on CRAN. Andy especially enjoys developing packages to make it easier to work with spatial data in R. Andy is a certified Software Carpentry and Data Carpentry instructor, and has led many workshops teaching programming skills to scientists and data professionals.
Sam Albers is a data scientist with 15 years experience writing code for scientific research. Sam wrote his first line of code to process data collected on salmon spawning in the Horsefly River watershed. Gradually, he ended up spending more time writing code than studying salmon and moved into a full time data scientist role in government. During that time, Sam developed several packages to facilitate reproducible research and gained a solid foundation in what it takes to build a good R package.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.