Good Software Engineering Practice for R Packages

R/Pharma 2024 Workshop
Author

Daniel Sabanés Bové and Joe Zhu

Keywords

rpharma, gswep, r, gxp

Welcome to the homepage of the tutorial “Good Software Engineering Practice for R Packages”, part of the R/Pharma Conference 2024 APAC track. 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 online event will be held on Monday October 28, 2024 12:00 - 15:00 GMT+8 as a virtual workshop.

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
12:00 - 12:15 GMT+8 Introduction and outline
12:15 - 12:55 GMT+8 R packages, what are they?
12:55 - 13:25 GMT+8 Workflow for creating R packages
13:25 - 13:40 GMT+8 Break
13:40 - 14:20 GMT+8 Package quality
14:20 - 14:50 GMT+8 Publication
14:50 - 15:00 GMT+8 Conclusion

Prerequisites & Technical Setup

Prior to the course, participants should:

For the course, participants are required to use their own laptop to be able to participate in the exercises.

Optional reading list

Past Events