We’ve both coincidentally dipped our toes in the wonderful world of pretty messaging with cli. cli::cli_alert_success("marvellous package adopted!") #> ✔ marvellous package adopted! In this post, we transform the hurdles we encountered in a series of tips so that your own journey might be slightly smoother, and also to encourage you to try out cli in your package! cli is the thing for package interfaces now! You can view cli as a domain-specific language (DSL) for command-line interfaces (CLI): Just like tidyverse makes your data pipelines easier to construct and more readable, cli makes your communication producing code simpler to write.
Read more...This post has been cross-posted on the Epiverse-TRACE blog. In a previous post, we discussed a package dependency that goes slightly beyond the normal R package ecosystem dependency: R itself. Today, we step even further and discuss dependencies outside of R: system dependencies. This happens when packages rely on external software, such as how R packages integrating CUDA GPU computation in R require the CUDA library. In particular, we are going to talk about system dependencies in the context of automated testing: is there anything extra to do when setting continuous integration for your package with system dependencies?
Read more...When I first started programming, I clearly remember feeling I had to add comments, that would repeat exactly what the code below was doing, as if it were the script for some sort of voice over. I want you to know like I now do that it’s not the way to comment one’s code. 😅 An important goal of good code is to be readable so that future contributors can build with and upon it as needed.
Read more...Sometimes, testing gets hard. For instance, you’d like to test for the behavior of your function in the absence of an internet connection, or in an interactive session, without actually cutting off the internet, or from the safety of a definitely non interactive R session for tests. In this post we shall present a not too involved pattern to avoid very complicated infrastructure, as a complement to mocking in your toolbelt.
Read more...There have been much talk and many blog posts about R package dependencies. Yet, one special dependency is more rarely mentioned, even though all packages include it: the dependency on R itself. The same way you can specify a dependency on a package, and optionally on a specific version, you can add a dependency to a minimum R version in the DESCRIPTION file of your package. In this post we shall explain why and how.
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