Package-vignetten bouwen

Knit HTML (of rmarkdown::render()) gebruiken is één manier om te testen of je vignette te bouwen is. Het is het beste om de functionaliteit van het devtools-pakket te gebruiken om alle vignetten te bouwen. Zo kun je ze automatisch bouwen en bijwerken, zodat ze altijd up-to-date zijn met de nieuwste wijzigingen in je unitConverter-pakket. Dit vereenvoudigt de workflow voor het maken, testen en onderhouden van vignetten, en bespaart tijd en moeite in het documentatieproces.

Het devtools-pakket is voor je geladen samen met het pakket tot nu toe, inclusief de bestanden dist_conversion.Rmd en func_conversion.Rmd.

Deze oefening maakt deel uit van de cursus

R-pakketten ontwikkelen

Cursus bekijken

Oefeninstructies

Bouw alle vignetten in het pakket met één functieverzoek.

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

# Build all package vignettes
___

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: Helpbestanden bij R-pakketten Exercise 2: Volgorde van onderdelen in een helpbestand Exercise 3: Geëxporteerde en niet-geëxporteerde functies Exercise 4: Documentatie met roxygen2 Exercise 5: Starters voor functiedocumentatie Exercise 6: Documentatie van functieargumenten Exercise 7: Functieresultaat en exporteren Exercise 8: Helpbestanden genereren Exercise 9: Aan de slag met vignetten voor R-pakketten Exercise 10: Blader door packagevignetten Exercise 11: Eigenschappen van vignettes en artikelen Exercise 12: Vignetten voor R-pakketten ontwerpen Exercise 13: Genereer een skelet voor een R-pakketvignet Exercise 14: Ontwerp een R-packagevignet Exercise 15: Package-vignetten bouwen

Huidige oefening

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: Unit tests Exercise 2: Advantages of unit testing Exercise 3: Set up your package for testing Exercise 4: Create a testing file Exercise 5: Exploring expect statements Exercise 6: Convert an example into a test Exercise 7: Check for warnings and errors Exercise 8: Check for output and identicalness Exercise 9: Storing expectations as unit tests and running tests Exercise 10: Fix expectation errors Exercise 11: Run a test on function examples Exercise 12: Run all tests in the package Exercise 13: Final steps Exercise 14: Finalize your DESCRIPTION file Exercise 15: Document your data Exercise 16: Check your R package Exercise 17: Congratulations!