Los expectation-fouten op

Soms moet je tests corrigeren die onjuist zijn ingevoerd, zodat ze de juiste vorm krijgen. Terwijl je naar functiedefinities zoals temp_converter() hebt gekeken, is unit testing ook een handige manier om vertrouwd te raken met de werking van de functionaliteit in een package. In deze oefening ga je aan de slag met het herstellen van tests, ze groeperen en ook hele groepen in één keer testen.

Je begint met het bekijken van fouten in de eerste stap en herstelt die fouten in de tweede stap.

De packages testthat en unitConverter zijn in deze ontwikkelfase alvast voor je geladen.

Deze oefening maakt deel uit van de cursus

R-pakketten ontwikkelen

Cursus bekijken

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

# Change each of the expectations below to have correct outputs
expect_equal(
  dist_converter(200, unit_from = "meters", unit_to = "feet"),
  60.96
)
expect_equal(
  dist_converter(656, unit_from = "feet", unit_to = "meters"),
  14
)

Code bewerken en uitvoeren

Deze oefening maakt deel uit van de cursus

R-pakketten ontwikkelen

SkillTag.level.intermediateSkillTag.label

4.8+

Begin de cursus gratis

Dive into the essentials of R package construction, from understanding the architecture, the critical R and man directories, to the significance of the DESCRIPTION and NAMESPACE files. Get hands-on with the usethis package as you create your own package skeleton and include data. Strengthen your R function writing skills, grasp best practices for package development, and get comfortable saving functions to a file. Finally, install your package locally using devtools.

Exercise 1: Components of an R package Exercise 2: R package truths Exercise 3: What's needed in all R packages?Exercise 4: Required package components Exercise 5: Data and R Markdown template in an R package Exercise 6: Create an R package Exercise 7: Add data to the R package Exercise 8: Create an R package R Markdown template file Exercise 9: R Markdown template file layout Exercise 10: Building package functions Exercise 11: R function for converting distances Exercise 12: Install the R package and try it out

Learn the advantages of creating packages versus using scripts, exploring the impact on code organization, reproducibility, collaboration, and sharing. Discover effective strategies for structuring code and functions within the R directory, and choosing an appropriate name and license for your package. Finally, you’ll learn how to manage CRAN package dependencies.

Exercise 1: More package structure Exercise 2: Comparing packages and scripts Exercise 3: Checking your package name Exercise 4: Choosing an appropriate license for your package Exercise 5: Package build Exercise 6: Adding and testing a new function in the package Exercise 7: Debug errors with load_all()Exercise 8: Differences between check() errors, warnings, and notes Exercise 9: Package dependencies Exercise 10: Types of R package dependencies Exercise 11: Set package dependencies Exercise 12: Set more package dependencies

Harness the power of examples in documentation by creating function examples with roxygen2. Understand the significance of examples in clarifying function behavior and identifying key components of a well-documented R function. Explore the purpose of vignettes in R package documentation and learn best practices for creating engaging vignettes and evaluating their content and quality through metadata analysis.

Exercise 1: Help files with R packages Exercise 2: Order of help file components Exercise 3: Exported and non-exported functions Exercise 4: Documentation with roxygen2 Exercise 5: Function documentation starters Exercise 6: Function argument documentation Exercise 7: Function returns and exporting Exercise 8: Generate help file documentation Exercise 9: Getting started with R package vignettes Exercise 10: Browse package vignette Exercise 11: Properties of vignettes and articles Exercise 12: Designing R package vignettes Exercise 13: Generate an R package vignette skeleton Exercise 14: Design an R package vignette Exercise 15: Build package vignettes

Identify why the unit tests are important to package development and maintenance and learn how to implement the testthat package for unit tests. Convert R examples into expectations to build your unit test knowledge. You’ll then gain an understanding on how to document your package data and run some final checks to ensure you have developed a robust R package.

Exercise 1: Unittests Exercise 2: Voordelen van unit testing Exercise 3: Bereid je package voor op testen Exercise 4: Maak een testbestand Exercise 5: Expect-uitspraken verkennen Exercise 6: Zet een voorbeeld om in een test Exercise 7: Controleer op waarschuwingen en fouten Exercise 8: Controleer op output en identiciteit Exercise 9: Verwachtingen opslaan als unittests en tests uitvoeren Exercise 10: Los expectation-fouten op

Huidige oefening

Exercise 11: Voer een test uit op functievoorbeelden Exercise 12: Voer alle tests in het pakket uit Exercise 13: Laatste stappen Exercise 14: Rond je DESCRIPTION-bestand af Exercise 15: Documenteer je data Exercise 16: Controleer je R-pakket Exercise 17: Gefeliciteerd!