Crea le vignette del pacchetto

Usare Knit HTML (o rmarkdown::render()) è un modo per testare se la tua vignetta si compila. Tuttavia, è preferibile usare le funzionalità del pacchetto devtools per costruire tutte le vignette. In questo modo puoi compilarle e aggiornarle automaticamente, assicurandoti che siano sempre allineate alle modifiche più recenti del tuo pacchetto unitConverter. Questo semplifica il flusso di lavoro per creare, testare e mantenere le vignette, facendo risparmiare tempo e fatica nella documentazione.

Il pacchetto devtools è stato caricato per te insieme al pacchetto finora, inclusi i file dist_conversion.Rmd e func_conversion.Rmd.

Questo esercizio fa parte del corso

Sviluppare pacchetti R

Visualizza il corso

Istruzioni dell'esercizio

Compila tutte le vignette del pacchetto con una singola chiamata di funzione.

Esercizio pratico interattivo

Prova a risolvere questo esercizio completando il codice di esempio.

# Build all package vignettes
___

Modifica ed esegui il codice

Questo esercizio fa parte del corso

Sviluppare pacchetti R

IntermediárioNível de habilidade

4.8+

Inizia il corso 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: File di help con i pacchetti R Exercise 2: Ordine dei componenti del file di help Exercise 3: Funzioni esportate e non esportate Exercise 4: Documentazione con roxygen2 Exercise 5: Avvii per la documentazione delle funzioni Exercise 6: Documentazione degli argomenti di funzione Exercise 7: Valori di ritorno delle funzioni ed esportazione Exercise 8: Genera la documentazione dei file di help Exercise 9: Primi passi con le vignette dei pacchetti R Exercise 10: Esplora le vignette del pacchetto Exercise 11: Proprietà di vignette e articoli Exercise 12: Progettare le vignette di un pacchetto R Exercise 13: Genera uno scheletro di vignetta per un pacchetto R Exercise 14: Progetta una vignetta per un pacchetto R Exercise 15: Crea le vignette del pacchetto

Esercizio in corso

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!