As pointed out by a recent read the R source post on the R hub’s website, reading the actual code, not just the documentation is a great way to learn more about programming and implementation details. But there is one more activity to get even more hands-on experience and understanding of the code in practice. In this post, we provide tips on how to interactively debug R code step-by-step and investigate the values of objects in the middle of function execution.
In the previous post, we looked at how to easily automate R analysis, modeling, and development work for free using GitLab’s CI/CD. Together with the fantastic R-hub project, we can use GitLab CI/CD to do much more. In this post, we will take it to the next level by using R-hub to test our development work on many different platforms such as multiple Linux setups, MS Windows and MacOS.
Automating the execution, testing and deployment of R work is a very powerful tool to ensure the reproducibility, quality and overall robustness of the code that we are building, be it for data analysis and modeling purposes, developing R packages or even blogging. Modern tools also provide a free an easy to use way of achieving this goal. In this post, we will show a quick and simple way to automate R data analysis and package development checking, testing and installation with GitLab CI/CD and provide example files that can be used for testing packages and deploying blogdown-based websites.
Code documentation is extremely important if you want to share the code with anyone else, future you included. In this second post in the RStudio:addins series we will pay a part of our technical debt from the previous article and document our R functions conveniently using a new addin we will build for this purpose. The addin we will create in this article will let us create well formatted roxygen documentation easily by using keyboard shortcuts to add useful tags such as \code{} or \link{} around selected text in RStudio.
This is the first post in the RStudio:addins series. The aim of the series is to walk the readers through creating an R package that will contain functionality for integrating useful addins into the RStudio IDE. At the end of this first article, your RStudio will be 1 useful addin richer. The addin we will create in this article will let us run a script open in RStudio in R vanilla mode via a keyboard shortcut and open a file with the script’s output in RStudio.