Correggi gli errori nelle expectation

A volte è necessario correggere test inseriti in modo errato, riportandoli alla forma corretta. Proprio come hai esaminato le definizioni di funzione come temp_converter(), il unit testing è anche una tecnica utile per familiarizzare con il funzionamento interno delle funzionalità di un pacchetto. In questo esercizio, esplorerai come correggere i test, raggrupparli e testare i gruppi tutti insieme.

Inizierai rivedendo gli errori nel primo passaggio, quindi li correggerai nel secondo.

I pacchetti testthat e unitConverter a questo punto dello sviluppo sono già stati caricati per te.

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Esercizio pratico interattivo

Prova a risolvere questo esercizio completando il codice di esempio.

# 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
)

Modifica ed esegui il codice

Questo esercizio fa parte del corso

Sviluppare pacchetti R

IntermediárioNível de habilidade

4.8+

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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: Test unitari Exercise 2: Vantaggi del unit testing Exercise 3: Prepara il tuo pacchetto per il testing Exercise 4: Crea un file di test Exercise 5: Esplorare le istruzioni expect Exercise 6: Converti un esempio in un test Exercise 7: Controlla avvisi ed errori Exercise 8: Controllare l'output e l'identicità Exercise 9: Salvare le aspettative come unit test ed eseguire i test Exercise 10: Correggi gli errori nelle expectation

Esercizio in corso

Exercise 11: Esegui un test sugli esempi della funzione Exercise 12: Esegui tutti i test nel pacchetto Exercise 13: Passi finali Exercise 14: Finalizza il tuo file DESCRIPTION Exercise 15: Documenta i tuoi dati Exercise 16: Verifica il tuo pacchetto R Exercise 17: Congratulazioni!