Good Software Engineering Practice for R Packages
rconis, gswep, r, gxp
Welcome to the homepage of the tutorial “Good Software Engineering Practice for R Packages”, part of the useR! Conference 2024 in Salzburg, Austria. In this course you will learn hands-on skills and tools to engineer reliable R packages. The workshop will be conducted in about 3 hours and will be a mix of presentations and exercises. Participants need to be comfortable with writing functions in R and use their own laptops as a prerequisite.
Event Details
This live event will be held on Monday July 8, 2024 14:00 - 17:30 CEST as an in-person tutorial in the room Tennegau.
Description
Join us for an engaging 3-hour face-to-face course designed to enhance your R programming skills with a focus on developing reliable R packages used in statistics or data science. This course is a blend of informative presentations and interactive team exercises, aimed at equipping participants with practical tools and techniques for engineering high-quality R packages. Throughout the session, you will collaborate to build a small R package that adheres to clean code rules and incorporates good software engineering practices.
This course is tailored for individuals who are comfortable with writing functions in R and are looking to elevate their package development skills. Bring your laptop and be prepared to transform your approach to R package development through hands-on learning and collaboration. Whether you’re looking to improve your workflow, meet regulatory standards, or simply enhance the quality of your statistical tools, this course offers valuable insights and skills to achieve your goals.
Learning Outcomes
Learn, understand, and practice good software engineering rules. Participants will delve into the significance of good engineering habits to avoid the pitfalls of maintenance overload, inefficient development, and regulatory non-compliance. By emphasizing best practices, the course will guide them towards faster releases on CRAN, saving valuable time on refactoring for PoC to release version transitions, and fostering an open environment for community contributions on GitHub. All course materials, including R scripts, will be shared with participants via GitHub, providing easy access to resources for continued learning and application beyond the course.
Schedule
| Time | Topic |
|---|---|
| 14:00 - 14:30 CEST | Introduction and outline |
| 14:30 - 15:15 CEST | R packages, what are they? + practical |
| 15:15 - 15:45 CEST | Workflow for creating R packages + practical |
| 15:45 - 16:30 CEST | R Package quality + exercise |
| 16:30 - 17:15 CEST | Publication of R packages + practical |
| 17:15 - 17:30 CEST | Conclusion |
Prerequisites & Technical Setup
Prior to the course, participants should:
- Install the latest R and RStudio software.
- Install Rtools (only on Windows).
- Install additional R packages using the installation script.
- Download and extract simulatr.zip
For the course, participants are required to use their own laptop to be able to participate in the exercises.
Optional reading list
- Excellent and very comprehensive R Packages (2e)
- (Hardcore) description about Writing R Extensions works
- Minimum Viable Good Practices for High Quality Statistical Software Packages: openstatsguide