R Packages organize, test, document, and share your code /

Turn your R code into packages that others can easily install and use. With this fully updated edition, developers and data scientists will learn how to bundle reusable R functions, sample data, and documentation together by applying the package development philosophy used by the team that maintains...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Wickham, Hadley
Otros Autores: Bryan, Jennifer
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Sebastopol : O'Reilly Media, Incorporated, 2023.
Edición:2nd ed.
Temas:
R (Computer program language)
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Intro
  • Copyright
  • Table of Contents
  • Preface
  • Welcome!
  • Introduction
  • Philosophy
  • In This Book
  • What's Not Here
  • Conventions Used in This Book
  • Colophon
  • O'Reilly Online Learning
  • How to Contact Us
  • Acknowledgments
  • Part I. Getting Started
  • Chapter 1. The Whole Game
  • Load devtools and Friends
  • Toy Package: regexcite
  • Preview the Finished Product
  • create_package()
  • use_git()
  • Write the First Function
  • use_r()
  • load_all()
  • Commit strsplit1()
  • check()
  • Edit DESCRIPTION
  • use_mit_license()
  • document()
  • NAMESPACE Changes
  • check() Again
  • Install()
  • use_testthat()
  • use_package()
  • use_github()
  • use_readme_rmd()
  • The End: check() and install()
  • Review
  • Chapter 2. System Setup
  • devtools, usethis, and You
  • Personal Startup Configuration
  • R Build Toolchain
  • Windows
  • macOS
  • Linux
  • Verify System Prep
  • Chapter 3. Package Structure and State
  • Package States
  • Source Package
  • Bundled Package
  • .Rbuildignore
  • Binary Package
  • Installed Package
  • In-Memory Package
  • Package Libraries
  • Chapter 4. Fundamental Development Workflows
  • Create a Package
  • Survey the Existing Landscape
  • Name Your Package
  • Package Creation
  • Where Should You create_package()?
  • RStudio Projects
  • Benefits of RStudio Projects
  • How to Get an RStudio Project
  • What Makes an RStudio Project?
  • How to Launch an RStudio Project
  • RStudio Project Versus Active usethis Project
  • Working Directory and Filepath Discipline
  • Test Drive with load_all()
  • Benefits of load_all()
  • Other Ways to Call load_all()
  • check() and R CMD check
  • Workflow
  • Background on R CMD check
  • Chapter 5. The Package Within
  • Alfa: A Script That Works
  • Bravo: A Better Script That Works
  • Charlie: A Separate File for Helper Functions
  • Delta: A Failed Attempt at Making a Package
  • Echo: A Working Package
  • Foxtrot: Build Time Versus Run Time
  • Golf: Side Effects
  • Concluding Thoughts
  • Script Versus Package
  • Finding the Package Within
  • Package Code Is Different
  • Part II. Package Components
  • Chapter 6. R Code
  • Organize Functions Into Files
  • Fast Feedback via load_all()
  • Code Style
  • Understand When Code Is Executed
  • Example: A Path Returned by system.file()
  • Example: Available Colors
  • Example: Aliasing a Function
  • Respect the R Landscape
  • Manage State with withr
  • Restore State with base::on.exit()
  • Isolate Side Effects
  • When You Do Need Side Effects
  • Constant Health Checks
  • Chapter 7. Data
  • Exported Data
  • Preserve the Origin Story of Package Data
  • Documenting Datasets
  • Non-ASCII Characters in Data
  • Internal Data
  • Raw Data File
  • Filepaths
  • pkg_example() Path Helpers
  • Internal State
  • Persistent User Data
  • Chapter 8. Other Components
  • Other Directories
  • Installed Files
  • Package Citation
  • Configuration Tools
  • Part III. Package Metadata
  • Chapter 9. DESCRIPTION
  • The DESCRIPTION File

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