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R Packages by Hadley Wickham
English | Apr 16, 2015 | ISBN: 1491910593 | 202 Pages | AZW3/MOBI/EPUB/PDF (conv) | 10.5 MB
Turn your R code into packages that others can easily download and use. This practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying author Hadley Wickham’s package development philosophy. In the process, you’ll work with devtools, roxygen, and testthat, a set of R packages that automate common development tasks. Devtools encapsulates best practices that Hadley has learned from years of working with this programming language.
Ideal for developers, data scientists, and programmers with various backgrounds, this book starts you with the basics and shows you how to improve your package writing over time. You’ll learn to focus on what you want your package to do, rather than think about package structure.
Learn about the most useful components of an R package, including vignettes and unit tests
Automate anything you can, taking advantage of the years of development experience embodied in devtools
Get tips on good style, such as organizing functions into files
Streamline your development process with devtools
Learn the best way to submit your package to the Comprehensive R Archive Network (CRAN)
Learn from a well-respected member of the R community who created 30 R packages, including ggplot2, dplyr, and tidyr
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In This Book
This book will guide you from being a user of R packages to being a creator of R packages. In Chapter 1, Introduction, you’ll learn why mastering this skill is so important, and why it’s easier than you think. Next, you’ll learn about the basic structure of a package, and the forms it can take, in Chapter 2, Package Structure. The subsequent chapters go into more detail about each component. They’re roughly organized in order of importance:
Chapter 3, R code
The most important directory is R/, where your R code lives. A package with just this directory is still a useful package. (And indeed, if you stop reading the book after this chapter, you’ll have still learned some useful new skills.)
Chapter 4, Package Metadata
The DESCRIPTION lets you describe what your package needs to work. If you’re sharing your package, you’ll also use the DESCRIPTION to describe what it does, who can use it (the license), and who to contact if things go wrong.
Chapter 5, Object Documentation
If you want other people (including “future you”!) to understand how to use the functions in your package, you’ll need to document them. I’ll show you how to use roxygen2 to document your functions. I recommend roxygen2 because it lets you write code and documentation together while continuing to produce R’s standard documentation format.
Chapter 6, Vignettes: Long-Form Documentation
Function documentation describes the nitpicky details of every function in your package. Vignettes give the big picture. They’re long-form documents that show how to combine multiple parts of your package to solve real problems. I’ll show you how to use Rmarkdown and knitr to create vignettes with a minimum of fuss.
Chapter 7, Testing
To ensure your package works as designed (and continues to work as you make changes), it’s essential to write unit tests that define correct behavior, and alert you when functions break. In this chapter, I’ll teach you how to use the testthat package to convert the informal interactive tests that you’re already doing to formal, automated tests.
Chapter 8, Namespace
To play nicely with others, your package needs to define what functions it makes available to other packages and what functions it requires from other packages. This is the job of the NAMESPACE file and I’ll show you how to use roxygen2 to generate it for you. NAMESPACE is one of the more challenging parts of developing an R package, but it’s critical to master if you want your package to work reliably.
Chapter 9, External Data
The data/ directory allows you to include data with your package. You might do this to bundle data in a way that’s easy for R users to access, or just to provide compelling examples in your documentation.
Chapter 10, Compiled Code
R code is designed for human efficiency, not computer efficiency, so it’s useful to have a tool in your back pocket that allows you to write fast code. The src/ directory allows you to include speedy compiled C and C++ code to solve performance bottlenecks in your package.
Chapter 11, Installed Files
You can include arbitrary extra files in the inst/ directory. This is most commonly used for extra information about how to cite your package, and to provide more details about copyrights and licenses.
Chapter 12, Other Components
This chapter documents the handful of other components that are rarely needed:demo/, exec/, po/, and tools/.
The final three chapters describe general best practices not specifically tied to one directory:
Chapter 13, Git and GitHub
Mastering a version control system is vital for collaborating with others, and is useful even for solo work because it allows you to easily undo mistakes. In this chapter, you’ll learn how to use the popular Git and GitHub combo with RStudio.
Chapter 14, Automated Checking
R provides useful automated quality checks in the form of R CMD check. Running them regularly is a great way to avoid many common mistakes. The results can sometimes be a bit cryptic, so I provide a comprehensive cheat sheet to help you convert warnings to actionable insight.
Chapter 15, Releasing a Package
The life cycle of a package culminates with release to the public. This chapter compares the two main options (CRAN and GitHub) and offers general advice on managing the process.
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