As package developers, we often focus on custom functions, their documentation, and unit testing. To provide a more complete user experience, it can be helpful to include data within the package. Here’s everything you need to know! If you’re not familiar with unit testing, we recommend reading our article on the subject: : https://rtask.thinkr.fr/expectations-verified-dive-into-the-world-of-unit-tests-with-expect_/ Short on time? Here’s the gist ...

Unit tests are essential in the development of an R package. They ensure that your functions work as expected while protecting you from regressions when you improve or modify your code. Thanks to the {testthat} package, writing and automating tests in R becomes simple and intuitive. At the core of this approach are the expect_*() functions, which play a central ...

Context Whether during the (training sessions) I can provide or the (coaching) sessions I can conduct, there is often a moment when I go on a long rant about the power and usefulness of caching. How awesome it is, not so complicated to set up, and super interesting. The last time I gave a presentation was to talk about ({targets}), ...

One aim of our open-source packages at ThinkR is to make our development workflows easier. {attachment} and {fusen} are developed maintained to help packages development and maintenance. Inception… If they help us every day, they can probably help you as well! In this blog post, I present the lastest changes of these two packages. If you want to know how ...

If you think {fusen} is not for you because you’ve been building R packages your entire life without it, it’s time to give it a try! Refer to the new tips and tricks in the dedicated vignette in case you feel you need additional functionalities: chances are I already implemented them… Go back to the previous blog post to know ...

We are often asked how to perform row-wise operations in a data.frame (or a tibble) the answer is, as usual, “it depends” 🙂 Let’s look at some cases that should fit your needs. library(tidyverse) Let’s make an example dataset: base <- tibble::tibble( a = 1:10, b = 1:10, c = 21:30 ) %>% head() base ## # A tibble: 6 ...

You regularly create projects on GitLab with a common skeleton, you want to retrieve the list of GitLab issues to create a report, you are looking for batch modifications of your projects? Use the GitLab API from your preferred programming language R. Communicate with GitLab API from R Here is a small example as issued from the {gitlabr} Readme on ...

With our “PROPRE” Project Guide, get a publishing committee and a development team to collaborate on creating your automated reports using the “PROPRE” methodology. Follow our suggestions for organization, tools and R development practices, for a controlled and benevolent DevOps practice. It is possible to collaborate around git in a team composed of developers and non developers. In this guide ...

In the same way you fall learning to walk, you make mistakes learning R. The goal of this article was to regroup the most common mistakes one makes while learning R and to explain them in order for you you know how to fix them. Facing an issue, the most important advice would be : “Read the error message”. It ...

At the last Raddicts Paris Meetup, Romain Francois (to be followed on twitter here) made one strong impression, among others, with his RStudio console which indicates the active git branch and the RAM memory used by R. If you too want to have this (to shine in society or because you spend your time doing git checkout):   Here is ...

While working on our {gitdown} package, I wanted to show more information on the report generated by retrieving all issues of my Gitlab / Github repositories. Indeed, titles of issues could improve readability and information of the git report of this package. How can I download all issues information from git repositories? Context of {gitdown} development {gitdown} is a package ...

At useR!2019 in Toulouse, ThinkR opened a quizz allowing to win a pipe knight. About a hundred of respondents won this Playmobil. In this blog post, we review the questions and respondents answers. We’ll see that the crowd as almost always right, but they do not know who the real R oracle is… The quizz showed some difficulties and tricks ...

Documentation matters ! Think about future you and others. Whatever is the aim of your script and analyses, you should think about documentation. The way I see it, R package structure is made for that. Let me try to convince you. At use’R 2019 in Toulouse, I did a presentation entitled: ‘The “Rmd first” method: when projects start with documentation’ ...

We are pleased to announce that our package {attachment} is now available on CRAN. The goal of attachment is to help to deal with package dependencies during package development. It also gives useful tools to install or list missing packages used inside Rscripts or Rmds. Deal with dependencies during package development If you ever had the following error when checking ...

PostGIS extends capabilities of PostgreSQL database to deal with spatial data. Using PostGIS, your database supports geographic queries to be run directly in SQL. In this blog post, we will connect and interact with a PostGIS database from R, using {DBI} and {sf}. Package {sf} and PostGIS are friends Package {sf} is similar to PostGIS database in multiple ways: R ...

Can mapping tools be diverted to other uses? Of course ! See how we play with leaflet and leafgl to quickly render a giant waffle made of millions of polygons. Spatial tools are not only for spatial data At SatRday in Paris, I presented a talk entitled “Everything but maps with spatial tools”. The aim is to show that there ...