Good Software Engineering Practice for R Packages

Welcome to the homepage of the workshop “Good Software Engineering Practice for R Packages”, part of the Zurich R Course series. In this course you will learn hands-on skills and tools to engineer reliable R packages used in statistics. The workshop will be conducted in two days 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

The event will be held on Thursday 18th and Friday 19th April 2024 as an in-person workshop at the University of Zurich Zentrum for Weiterbildung (http://www.zwb.uzh.ch/anreise.html). Please register here.

This event is organized by Zurich R Courses and RCONIS. The presenter in this workshop will be Daniel Sabanés Bové.

Communication

We offer a gitter chat channel to communicate before, during, and after the course.

Workshop Program

Day 1: 18th April

9.00 - 9.45 Introduction and outline
9.45 - 10.00 Coffee break
10.00 - 10.45 R Package Syntax
10.45 - 11.30 Exercise
11.30 - 12.15 Software Engineering Workflow
12.15 - 13.15 Lunch break
13.15 - 14.00 Exercise
14:00 - 14:45 Package Quality
14.45 - 15.30 Exercise
15.30 - 15.45 Coffee break
15.45 - 16.30 Collaboration via GitHub
16.30 - 17.00 Exercise

Day 2: 19th April

9.00 - 9.45 Publication of R Packages
9.45 - 10.00 Coffee break
10.00 - 10.45 Exercise
10.45 - 11.30 Code Optimization
11.30 - 12.15 Exercise
12.15 - 13.15 Lunch break
13.15 - 14.00 Shiny Design and Modules
14.00 - 14.45 Exercise
14.45 - 15.15 Shiny Tests
15.15 - 15.45 Exercise
15.45 - 16.00 Coffee break
16.00 - 16.30 Summary and Q&A

Prerequisites & Technical Setup

Prior to the course, participants should

  • Set up a (free) GitHub.com account.
    • Note: There are other git platforms like Gitlab or Bitbucket, but we made the choice to go with GitHub.com for the course, since it is by far the most relevant git platform in the R community.
  • Download and extract simulatr.zip
  • Install the latest R and RStudio software.
  • Install Rtools (only on Windows and optional if you want to try out Rcpp)
  • Install additional R packages using the installation script.

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

Optional reading list

Past Events