Getting started

Last updated on 2024-04-23 | Edit this page

Overview

Questions

  • “I want to write a package. Where should I start?”

Objectives

  • “Create a minimal package”

What does a package look like?


The minimal folder structure of a package looks like this

.
├── R
│   └── <R functions>
├── README.md
├── LICENSE
├── DESCRIPTION
└── NAMESPACE

where:

  • The folder R contains all the R code (more on this in Writing our own functions).
  • The README.md file contains human-readable information about the package (more on this in the Documentation episode).
  • The LICENSE contains information about who and how can use this package (more below).
  • The DESCRIPTION file contains information about the package itself (more information in the episode on Dependencies).
  • The NAMESPACE file is automatically generated and tells R which functions can be accessed (more in the Documentation episode).

A minimal package


The menus in RStudio will help us in creating the most minimal of packages. Let’s open RStudio and look at the upper left corner. We will press File > New project > New directory, and see a menu like this:

New project menu
New project menu

As you can guess, we will now press R package. The new menu asks us to fill in some information. For the moment, bear with me and fill in the following:

New project menu
New project menu

Notice that:

  • We gave the package a name: mysterycoffee.
  • I created my package on my ~/Desktop folder, but you can use another location if you prefer.
  • We left Create git repository unticked. If you want to know more about git, please refer to our courses on Version control. Integrating packages with Git is very useful, but we will not talk about it in this lesson.
  • We left Use renv with this project unticked.
  • We ticked Open in new session.

Now we are ready to press Create Project.

What just happened?

After pressing Create Project, a new RStudio window should have appeared. The working folder should be mysterycoffee, and it should already have some contents:

New project menu
New project menu

Also, the file ./R/hello.R would appear open in the editor. This is an example file that contains a toy function. Its only functionality is to, well, to say “hello”. This may sound silly, but it will help you writing your first packaged R functions.

Thehello.Rfile

Let’s take a look at the hello.R file. You’ll see that it contains a tiny function and some comments. The comments are actually more important than the function itself. They contain very useful tips about how to install, check and test the package.

As a rule of thumb: always read the contents of the example files RStudio creates for you.

Play with the package


Believe it or not, this package is ready to be installed. Just go to the upper right corner and press Build > Install and Restart (or, in newer versions of RStudio, press Build > Install > Clean and install).

Install and restart
Install and restart

This will install and attach the package. The package contains only one function so far: hello().

Try out thehello()function. Edit it, and reload the package.

  1. What does it print?
  2. Change this function to generate a different output. (Have fun with it, perhaps add an argument or two!)
  3. Build and install the package, and call the function again to see that it works differently.

R

mysterycoffee::hello()

OUTPUT

[1] Hello, world!

We can add an argument like this:

R

hello <- function(name) {
   print(paste0("Hello, ", name, "!"))
}

To use the updated function available in RStudio, we can use either

R

devtools::load_all() # then call with hello("Luke")
devtools::install() # then call with mysterycoffee::hello("Luke")

Alternatively, we can also use the graphical user interface as above: Build Install and Restart.

Note: load_all() simulates installing and attaching the package. In larger projects, it allows us to iterate more quickly between changing functions and testing them in the console.

Tell me how you load your functions

There are many ways of using functions, but all of them involve loading them into the workspace. We just learned how to do that using a package.

How do you usually work with functions? Perhaps you source them from an external file? Do you usually work on a single, long script?

Can you think of any advantage of using packages instead? Don’t worry if the answer is no. This is actually a difficult question at this stage. We’ll show the full power of packages along the course.

More advanced folder structures


In this course we will show you how to unleash the full power of packaging. In order to do so, we will use some optional folders. You can see an overview below

.
├── R
│   └── <R functions>
├── data (optional)
│   └── <data>
├── tests (optional)
│   ├── testthat.R
│   └── testthat
│       └── <tests>
├── vignettes (optional)
│   └── <Rmd vignettes>
├── inst (optional)
│   └── <any other files>
├── README.md
├── LICENSE
├── DESCRIPTION
└── NAMESPACE

where:

  • The data folder contains, as the name suggests, data (more in the Data episode).
  • The tests folder contains unit tests, that will be very useful for making our package robust and mantainable (more in the episode on Testing).
  • The vignettes folder contains documentation in Rmd format. As we’ll see, this is a very suitable format for your reports and publications (more in the Vignette episode).
  • The inst folder contains any extra file you may want to include (more in the Data episode).

Key Points

  • “A package is no more and no less than a folder structure”
  • “RStudio can help you”