If you’ve never heard of cache (/kaSH/) before, Google it and you’ll quickly find that it is “a collection of items of the same type stored in a hidden or inaccessible place”. Basically, you have “something” stored “somewhere” so you can fetch it “sometime” later. If it sounds basic, it (can be) is! This simple technic can come quite handy when you are coding functions that take some time to gather and/or process the data you’re working with. In other words, think of those processes that take some time to run and there’s really no need to re-run it “every time” because the outcome will be exactly the same. Also, you are unnecessarily spending time, computer power, and real energy when you re-process cache-able stuff.
Today I’ll show you how I use cache in R to accelerate results, avoid re-processing, and improve UX for my users using the lareslares library. Let’s see a couple of functions that actually leverage cache usage and how can you start using them.
Read on for a walkthrough of the process.