Introduction Skip to the R code examples. Programmers are good at engineering software and designing web applications. I argue that we can apply the same logic to facilitate an environment which provides a natural, orchestrated flow between the various activities we undertake, both online and in the console. In this post I use searching the web, a process developers rely on heavily for many different reasons, as a basic example of an area for improvement.

Shiny Modules

Does your R package work best with some configuration? You probably want it to be easily found by your package. Does your R package download huge datasets that don’t change much on the provider side? Maybe you want to save the corresponding data somewhere persistent so that things will go faster during the next R session. Preface: standard locations on the user’s machine Throughout this post we’ll often refer to standard locations on the user’s machine.

.Renviron Once you start working with APIs, you will find yourself working with keys and tokens and shared secrets. To the extent possible, you should avoid putting those sorts of things directly in your code. The reason is quite simple: depending on the platform and its API, those alphanumeric identifiers may very well unlock access to your data for anyone who comes into possession of them. Or, if not unlocking access to your data, they can enable others to use cloud-based resources (like the Google Cloud platform) that can cost you money!

Overview Dealing with R Packages can be a pain sometimes, especially when dealing with development versions of evolving packages over time. Additionally, sometimes it is necessary to revert back to an old version of a package in order to reproduce an old project or replicate a test environment for a deployment. To resolve some of the pains associated with this process, I came up with a nice little solution, which I will explain in this post.