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Generally save to assume that suggest packages will be installed when you vignette is executed. Need to make sure they work everywhere which can be challenging if yourДЄny packages used by your vignette must be listed in Imports or Suggests fields. Your vignettes will be evaluated in many different places, not just your computer - CI/CD, CRAN, and users can run on their computers (although not typical). I usually set these globally by putting the following knitr block at the start of my document.

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Knitr::opts_chunk$set(collapse = TRUE, comment = '#>')Д¬ollapse = TRUE and comment = '#>' are my preferred way of displaying code output. If you change the title, you must also change the VignetteIndeењЋntry It indicates the following lines of text are plain text and shouldnвЂ™t use any special YAML features. The one special YAML feature weвЂ™re using here is >.

The basics of the syntax is much like the DESCRIPTION file, where each line consists of a field name, a colon, then the value of the field. This metadata is written in yaml, a format designed to be both human and computer readable. The default template contains the following information:. The first few lines of the vignette contain important metadata. This is a good way to verify that youвЂ™ve captured all the needed dependencies. The check workflow, Cmd + Shift + E, will run the code in all vignettes. This builds with the installed package - but you probably want the dev package. Press Ctrl/Cmd + Shift + K (or click ) to knit the vignette and preview the output. Once you have this file, the workflow is straightforward: It serves as a useful reference when youвЂ™re creating a new vignette. The draft vignette has been designed to remind you of the important parts of an R Markdown file. Usethis :: use_vignette ( 'my-vignette' )ДЄdd the necessary dependencies to DESCRIPTION (i.e.В it adds knitr to the Suggests and VignetteBuilder fields).Дraft a vignette, vignettes/my-vignette.Rmd.

If this describes, your package, I highly recommend switching to RMarkdown. Older packages can include vignettes written with Sweave, a precursor to RMarkdown. If youвЂ™re not already familiar with RMarkdown youвЂ™ll need to learn the basics elsewhere at good place to start is. In this chapter, weвЂ™re going to use RMarkdown to write our vignettes. To see vignettes for a package you havenвЂ™t installed, look at its CRAN page, e.g. You can read a specific vignette with vignette(x), and see its code with edit(vignette(x)). Each vignette provides three things: the original source file, a readable HTML page or PDF, and a file of R code. To see the vignette for a specific package, use the argument, browseVignettes('packagename'). You can see all the installed vignettes with browseVignettes().

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A vignette is like a book chapter or an academic paper: it can describe the problem that your package is designed to solve, and then show the reader how to solve it.

Function documentation is great if you know the name of the function you need, but itвЂ™s useless otherwise. 17.1 IntroductionДЄ vignette is a long-form guide to your package.

This chapter is undergoing heavy restructuring and may be confusing or incomplete. You are reading the work-in-progress second edition of R Packages.