5 Documentation

Published

2024-12-20

TLDR

Documenting app-package functions:

Make sure each function has documentation for the @title, @description, @param(s), @return, and @examples (if applicable)
Use Markdown for code, emphasis, hyperlinks, etc.
Regularly load and document to preview the help files:

Ctrl/Cmd + Shift + L / D

Link modules with @seealso and group functions with @family
Include any additional information in a new @section

This chapter covers function documentation in an app-package by introducing the basic fundamentals of the roxygen2 syntax (i.e., the ‘bare minimum’ to include for each function). I’ll also touch on a few helpful roxygen2 tags specific to Shiny modules and standalone app functions.

Access the applications in this chapter

I’ve created the shinypak R package in an effort to make each section accessible and easy to follow. Install shinypak using pak (or remotes):

install.packages('pak')
pak::pak('mjfrigaard/shinypak')
library(shinypak)

List the apps in this chapter:

list_apps(regex = '^05')

Launch apps with launch()

launch(app = '05_roxygen2')

Download apps with get_app()

get_app(app = '05_roxygen2')

The current structure of our sap package is displayed in the folder tree below:

sap/
├── DESCRIPTION
├── NAMESPACE
├── R
│   ├── mod_scatter_display.R
│   ├── mod_var_input.R
│   └── utils.R
├── README.md
├── app.R
├── man
├── movies.RData
├── sap.Rproj
└── www
    └── shiny.png

4 directories, 10 files

(the rsconnect/ folder from deploying sap has been removed)

If you recall, the output from the previous call to install() returned the following message regarding the documentation:

No man pages found in package ‘sap’

Documenting the functions in the R/ folder will address this message, and I strongly encourage checking out the roxygen2 vignettes and the chapter in R Packages, 2ed for more information on documenting your app-package.

5.1 `roxygen2` intro

See the 04_devtools branch of sap.

roxygen2 connects the package code (i.e., the .R files in the R/ folder) to its documentation files (i.e., the .Rd files in the man/ folder):

%%{init: {'theme': 'base', 'themeVariables': { 'fontFamily': 'monospace', 'primaryColor': '#33a02c', 'edgeLabelBackground':'#02577A'}}}%%

flowchart TD
  X1(Code in <code>R/</code> Folder) --> X2(<code>roxygen2</code> Comments and Tags in <code>.R</code> Files)
  X2 --> X3(Run <code>devtools::document</code>)
  X3 --> X4(Parse <code>roxygen2</code> Comments and Tags)
  X4 --> X5(Generate <code>.Rd</code> Files in <code>man/</code> Folder)
  X4 --> X6(Generate <code>NAMESPACE</code> File)
  
  style X1 fill:#8dd38d,stroke:none,rx:10,ry:10;
  style X2 fill:#8dd38d,stroke:none,rx:10,ry:10;
  style X3 fill:#89D6FB,stroke:#000000,rx:1,ry:1;
  style X4 fill:#89D6FB,stroke:#000000,rx:1,ry:1;
  style X5 fill:#8dd38d,stroke:none,rx:10,ry:10;
  style X6 fill:#8dd38d,stroke:none,rx:10,ry:10;

roxygen2 creates the NAMESPACE and man/ documentation

Two pieces of roxygen2 syntax to know are comment blocks and tags:

Comment blocks are any lines beginning with #'
```
#' 
#' 
#' 
```
Tags begin with @
```
#' 
#' @tag
#' 
```

roxygen2 tags and comment blocks are placed above the functions stored in R/ to create help documentation:

#' 
#' @tag
#' 
my_fun <- function() {
  
}

In the following sections, we’ll cover some roxygen2 basics using the scatter_plot() function in the R/utils.R file.

Inserting roxygen2 skeletons

In RStudio , you can insert an roxygen2 skeleton into your function using Code > Insert Roxygen Skeleton

Standard roxygen2 skeleton — Standard `roxygen2` skeleton

5.1.1 `markdown = TRUE`

When we created our app-package with usethis::create_package(), support for markdown formatting in package help files was automatically included by adding Roxygen: list(markdown = TRUE) to the DESCRIPTION file:

Package: sap
Version: 0.0.0.9000
Type: Package
Title: movies app
Description: A movies data Shiny application.
Author: John Smith [aut, cre]
Maintainer: John Smith <John.Smith@email.io>
License: GPL-3
DisplayMode: Showcase
RoxygenNote: 7.2.3
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
# Always leave at least one empty final line in the DESCRIPTION file

5.1.2 `@title` & `@description`

The first two sections of roxygen2 documentation are the title and description. These sections don’t require tags–roxygen2 will detect each section as long as there is at least one #' line separating them (and their contents don’t extend past the length indicated in parentheses below):

#' function title (one line)
#'
#' A short description... (one paragraph)
#'

The @title and @description for the scatter_plot() function stored in R/utils.R might look like this:

#' Create scatter plot 
#'
#' Custom [`ggplot2`](https://ggplot2.tidyverse.org/) function for building scatter plots in `sap`.
#'

Function @description and @details

If the contents in the @description for a function requires more complicated formatting than a single paragraph (i.e., multiple paragraphs, lists, etc.), you can use the @details tag:

#' Create scatter plot  
#' 
#' @description
#' Custom [`ggplot2`](https://ggplot2.tidyverse.org/) function for building scatter plots in `sap`.
#' 
#' @details
#' `scatter_plot()` is a custom `ggplot2` function written to handle string arguments from reactive inputs (i.e., `input$x` or `input$y`)

5.1.3 `@param` & `@return`

Document function arguments and outputs with @param and @return:

@param: should include the name and description of each function input (i.e., their type and what they do)
```
#' @param name description of its action
```
- Read more about @param in the arguments chapter of R Packages, 2ed.
@return: these describe the type (or class) and structure of the function output
```
#' @return type/structure of the output
```
- Read more about @return in the return value chapter of R Packages, 2ed.

Below are examples for @param and @return in the scatter_plot() function stored in R/utils.R:

#' 
#' @param df `data.frame` or `tibble`
#' @param x_var string variable mapped to `x` axis
#' @param y_var string variable mapped to `y` axis
#' @param col_var string variable mapped to `color`
#' @param alpha_var number for point `alpha`
#' @param size_var number for point `size` 
#' 
#' @return A `ggplot2` plot object

To view how the roxygen2 syntax will appear in the .Rd file, I’ll document sap:

To reduce the amount of repetitive code, I’ll just be showing the keyboard shortcuts for each devtools function from this point forward

Ctrl/Cmd + Shift + D

I can see the scatter_plot.Rd file is written to the man/ folder:

ℹ Updating sap documentation
ℹ Loading sap
Writing scatter_plot.Rd
Documentation completed

File name alignment

Shiny apps (and most R projects) often contain utility functions in helper.R or utils.R files. Placing non-Shiny code in these files isn’t a bad practice–it’s is even encouraged in Mastering Shiny:

“You might want to collect smaller, simpler, functions into one place. I often use R/utils.R for this…”

However, because we’ll want to develop tests for scatter_plot(), we should follow the advice in R Packages,¹ and rename R/utils.R to R/scatter_plot.R as we transition to an app-package.²

R/utils.R

From now on, I’ve renamed R/utils.R to R/scatter_plot.R, so it aligns with the naming conventions in other R packages.

For a deep dive on R/utils.R files in R packages, I recommend reading Dissecting R Package “Utility Belts”

R documentation (.Rd) files have a formatting style similar to (La)TeX, but roxygen2 saves us from having to learn this syntax by automatically generating the .Rd files. When we open man/scatter_plot.Rd, we see it already contains the following:

The scatter_plot.Rd documentation file — The `scatter_plot.Rd` documentation file

.Rd file syntax

roxygen2 graciously generates the scatter_plot.Rd file (and warns us not to edit it by hand).

roxygen2 tag syntax in .Rd file — `roxygen2` tag syntax in `.Rd` file

Note the following items were added without needing tags:

\name: the name of the function (as it appears in the index)
\alias: used to group ‘topics’ and provides a look-up in the package index
\arguments: function arguments (header)
- \item: description of argument

The following two items are a result of the markdown syntax we used:

\href: used for hyperlinks
\code: code formatting

To view the help file, I can enter ?scatter_plot in the console:

?scatter_plot

And an informative message tells me that the development version scatter_plot.Rd is being rendered:

ℹ Rendering development documentation for "scatter_plot"

Previewing the development versions of our documentation is a great way to verify the content in each .Rd file meets our expectations.

5.1.4 `@examples`

@examples are unique because they include executable code that demonstrates how a particular function works. In the Posit Workbench IDE, @examples are especially helpful because they come with a clickable hyperlink (the @examples from ggplot2::aes() are below):

Below is an example demonstrating how the scatter_plot() utility function works:

#' @examples
#' scatter_plot(mtcars, 
#'     x_var = "mpg", 
#'     y_var = "disp", 
#'     col_var = "cyl", 
#'     alpha_var = 0.5, 
#'     size_var = 3)

Tab-completion for @tags

If you’re documenting your package functions in Posit Workbench, tab-completion is your friend! The help text displayed with each tag ensures you’re including the correct version (see @example vs. @examples below).

Tab completion for @example — Tab completion for `@example`

5.2 Documenting app functions

Your app-package will likely contain at least two functions specific to Shiny: modules and a standalone app function. roxygen2 has tags that can make the documentation for these functions more informative for readers.

Below are a few things to consider when documenting module functions:

Modules will typically include two functions in a single .R file: one for the UI and a counterpart in the server.
Every module function will include at least one @param for the shared id.
Returned objects are critical in Shiny’s reactive programming model, so I recommend extending the @description to include whether or not the returned output is reactive.
If the returned output is an input (i.e. @param) for another function, link to that documentation functions with @seealso or @family.

5.2.1 `@seealso`

When documenting Shiny modules, I tend to think of the audience as anyone looking to understand the execution path through an application. For example, in our sap application, the inputs are collected in the UI with the var_input module, then passed to the scatter_display module to render in the UI:

%%{init: {'theme': 'base', 'themeVariables': { 'fontFamily': 'monospace', 'primaryColor': '#33a02c', 'edgeLabelBackground':'#FFFFFF'}}}%%
flowchart 
    input(input module) --> seealso[<code>@seealso</code>] -->  display(display module)
    
  style input fill:#8dd38d,stroke:none,rx:10,ry:10;
  style display fill:#8dd38d,stroke:none,rx:10,ry:10;
  style seealso fill:#89D6FB,stroke:#000000,rx:1,ry:1;

seealso connecting documentation

The @seealso tag can be used to connect mod_var_input_ui() to it’s server function counterpart. The hyperlink to mod_var_input_server() from mod_var_input_ui() is created by placing the destination function in square brackets [fun()]:

show/hide mod_var_input_ui() roxygen2

#' Variable input module (UI)
#' 
#' @description
#' `var_input` collects the following graph inputs:
#'  * `input$x`
#'  * `input$y`
#'  * `input$z`
#'  * `input$alpha`
#'  * `input$size`
#'  * `input$plot_title`
#'
#' @param id UI module id
#'
#' @return module UI (HTML)
#' 
#' @seealso [mod_var_input_server()]
#'

Ctrl/Cmd + Shift + D

@seealso creates a hyperlink readers can use to open the next module in the execution path.

Link values from var_input to scatter_display — Link values from `var_input` to `scatter_display`

In mod_var_input_server(), a link can be made to mod_scatter_display_server() (the module function collecting the returned values) using the square brackets in the @return section (without @seealso):

show/hide mod_var_input_server() roxygen2

#' Variable input module (server)
#'
#' @param id server module id
#' 
#' @seealso [mod_var_input_ui()]
#'
#' @return reactive inputs are returned in a `list()`: 
#'  * `"y" = input$y`
#'  * `"x" = input$x`
#'  * `"z" = input$z`
#'  * `"alpha" = input$alpha`
#'  * `"size" = input$size`
#'  * `"plot_title" = input$plot_title`
#'  
#' These become in the `var_inputs()` argument in [mod_scatter_display_server()]
#'

Ctrl/Cmd + Shift + D

5.2.2 `@family`

Module functions can also be grouped into families using @family {"description"}. Below is an example of grouping the “scatter plot module functions” into a family:

show/hide mod_scatter_display_ui() roxygen2

#' Scatter plot display module (UI)
#'
#' @param id UI module id
#' 
#'
#' @return module UI (HTML)
#' 
#' @family {"scatter plot module functions"}
#'

5.2.3 `@section`

The @section tag will create a level two header (##/<h2></h2>) section, which can help organize topics (like how to use an input or argument).

@seealso can also be used to link back to the scatter_plot() utility function:

show/hide mod_scatter_display_server() roxygen2

#' Scatter plot display module (server)
#' 
#'
#' @param id server module id 
#' @param var_inputs returned reactive list from [mod_var_input_server()].
#' 
#' @section Referring to `var_inputs`: 
#' Refer to the reactive returned values from `mod_var_input_server()` as:
#'  * `var_inputs()$x`
#'  * `var_inputs()$y`
#'  * `var_inputs()$z`
#'  * `var_inputs()$alpha`
#'  * `var_inputs()$size`
#'  * `var_inputs()$plot_title`
#' 
#'
#' @return rendered plot and title output from [scatter_plot()]
#' 
#' @family {"scatter plot module functions"}
#'

Ctrl/Cmd + Shift + D

The figure above shows how the @seealso links can create a path for the graph parameters through the var_input and scatter_display modules. It also demonstrates how @family groups the scatter_display UI and server functions.

The scatter_plot() utility function should also include a @seealso tag for the module function it’s used in.

show/hide scatter_plot() roxygen2

#' Create scatter plot 
#'
#' Custom [`ggplot2`](https://ggplot2.tidyverse.org/) function for building scatter plots in `sap`.
#' 
#' 
#' @param df `data.frame` or `tibble`
#' @param x_var string variable mapped to `x` axis
#' @param y_var string variable mapped to `y` axis
#' @param col_var string variable mapped to `color`
#' @param alpha_var number for point `alpha`
#' @param size_var number for point `size` 
#' 
#' @return A `ggplot2` plot object
#' 
#' 
#' @examples
#' scatter_plot(mtcars, 
#'     x_var = "mpg", 
#'     y_var = "disp", 
#'     col_var = "cyl", 
#'     alpha_var = 0.5, 
#'     size_var = 3)
#'     
#' @seealso [mod_scatter_display_server()]
#'

Ctrl/Cmd + Shift + D

Connections between (a) modules and (b) utility function

The goal when cross-referencing functions in your app-package is for anyone reading your documentation to follow the links and better understand any modules, their inputs, reactive values, and outputs.

In this case, linking to the scatter_plot() function gives readers an interactive example to preview the output.

5.3 UI & Server functions

Splitting the standalone app function in app.R into separate UI and server functions has multiple benefits:

Developing and loading each function will be easier when it’s stored in the R/ folder.
Having dedicated UI, server, and app function means we can develop them independently.
Standalone app functions means we can have multiple applications in the same app-package.

I’ve split the UI and server from launch_app() into separate movies_ui() and movies_server() below.

The movies_ui() doesn’t have any arguments–the only change is wrapping the shiny::fluidPage() in shiny::tagList():

movies_ui <- function() {
  shiny::tagList(
    shiny::fluidPage(
      theme = shinythemes::shinytheme("spacelab"),
      shiny::titlePanel(
        shiny::div(
          shiny::img(
            src = "shiny.png",
            height = 60,
            width = 55,
            style = "margin:10px 10px"
            ), 
         "Movies Reviews"
        )
      ),
      shiny::sidebarLayout(
        shiny::sidebarPanel(
          mod_var_input_ui("vars")
        ),
        shiny::mainPanel(
          mod_scatter_display_ui("plot")
        )
      )
    )
  )
}

movies_server() is written to be passed to the server argument in shinyApp():

movies_server <- function(input, output, session) {

      selected_vars <- mod_var_input_server("vars")

      mod_scatter_display_server("plot", var_inputs = selected_vars)
      
}

5.3.1 `@usage`

I’ll explicitly describe the use of movies_ui() and set @usage to NULL (note the use of a code block). I’ll also use @section to describe each module UI function (and link to the server functions with @seealso).

show/hide roxygen2 for movies_ui()

#' Movies UI function
#' 
#' UI function for standalone app function 
#' 
#' @usage NULL
#' 
#' @details
#' The [launch_app()] function is as a wrapper for `shiny::shinyApp()`: 
#'  
#' ```
#' shinyApp(ui = movies_ui, server = movies_server)
#' ```
#' 
#' In [launch_app()]:
#'  * UI is stored in `movies_ui()`    
#'  * server is stored in [movies_server()]
#'  
#' @section `var_input` module: 
#' [mod_var_input_ui()] is used to collect the following inputs:
#'  * `input$x`
#'  * `input$y`
#'  * `input$z`
#'  * `input$alpha`
#'  * `input$size`
#'  * `input$plot_title`
#'  
#' @seealso [mod_var_input_server()]
#' 
#' 
#' @section `scatter_display` module: 
#' [mod_scatter_display_ui()] displays the graph output using [scatter_plot()]
#' 
#' @seealso [mod_scatter_display_server()]
#'
#' @return `ui` argument in `shiny::shinyApp()` 
#'

Ctrl/Cmd + Shift + D

The documentation for movies_server() is very similar to the Ui function–each module server function is documented in it’s own @section.

Still, I’ll include a @section for Communication that describes how values are passed between mod_var_input_server() and mod_scatter_display_server().

show/hide roxygen2 for movies_server()

#' Movies server function
#' 
#' Server function for standalone app function 
#' 
#' @usage NULL
#' 
#' @details
#' The [launch_app()] function is as a wrapper for `shiny::shinyApp()`: 
#' 
#' ```
#' shinyApp(movies_ui, movies_server)
#' ```
#' 
#' In [launch_app()]:
#'  * UI is stored in [movies_ui()]   
#'  * server is stored in `movies_server()`
#'  
#' @section `var_input` module: 
#' [mod_var_input_server()] returns following reactive values:
#'  * `x`
#'  * `y`
#'  * `z`
#'  * `alpha`
#'  * `size`
#'  * `plot_title`
#' 
#' @seealso [mod_var_input_ui()]
#' 
#' @section `scatter_display` module: 
#' [mod_scatter_display_server()] displays the `ggplot2` graph with the [scatter_plot()] function.
#' 
#' @seealso [mod_scatter_display_ui()]
#' 
#' @section Communication: 
#' The output from [mod_var_input_server()] should be supplied to the 
#' `var_inputs` argument of [mod_scatter_display_server()].
#
#' @return `server` argument in `shiny::shinyApp()`
#'

Ctrl/Cmd + Shift + D

5.3.2 `launch_app()`

The standalone app function (launch_app()) automatically calls shinyApp(), with the movies_ui and movies_server functions supplied to ui and server (without parentheses).

launch_app <- function() {
  shiny::shinyApp(ui = movies_ui, server = movies_server)
}

The documentation for the standalone app function can be minimal–as long as it provides links to the UI and server.

#' Movies app standalone function
#'
#' Wrapper function for `shiny::shinyApp()`
#'
#' @return Shiny app
#' 
#' 
#' @seealso [mod_var_input_ui()], [mod_var_input_server()], [mod_scatter_display_ui()], [mod_scatter_display_server()]
#'

Ctrl/Cmd + Shift + D

The contents of app.R can be changed to the following:

# pkgs <- c("shiny", "shinythemes", "stringr", "ggplot2", "rlang")
# install.packages(pkgs, quiet = TRUE)

# packages ------------------------------------
library(shiny)
library(shinythemes)
library(stringr)
library(ggplot2)
library(rlang)

# launch_app ------------------------------------
launch_app()

Now that we’ve documented everything in R/, we’ll load(), document(), and install() our package:

Ctrl/Cmd + Shift + L

devtools::load_all(".")

ℹ Loading sap

Ctrl/Cmd + Shift + D

==> devtools::document(roclets = c('rd', 'collate', 'namespace'))

ℹ Updating sap documentation
ℹ Loading sap
Documentation completed

Ctrl/Cmd + Shift + B

==> R CMD INSTALL --preclean --no-multiarch --with-keep.source sap

* installing to library ‘/path/to/local/install/sap-090c61fc/R-4.2/x86_64-apple-darwin17.0’
* installing *source* package ‘sap’ ...
** using staged installation
** R
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (sap)

In the Console, we should see the following:

Restarting R session...
> library(sap)

The roxygen2 documentation for sap is saved in the 02-roxygen branch. As we can see, calling devtools::document() generates the .Rd files in the man/ folder for each function in the R/ folder:

R/
├── launch_app.R
├── mod_scatter_display.R
├── mod_var_input.R
├── movies_server.R
├── movies_ui.R
└── scatter_plot.R

1 directory, 6 files

man/
├── launch_app.Rd
├── mod_scatter_display_server.Rd
├── mod_scatter_display_ui.Rd
├── mod_var_input_server.Rd
├── mod_var_input_ui.Rd
├── movies_server.Rd
├── movies_ui.Rd
└── scatter_plot.Rd

1 directory, 8 files

Recap

Good documentation aims to make it as easy as possible for others (and future you) to understand what your function does and how to use it.

Launch app with the shinypak package:

launch('05_roxygen2')

Below is a recap of the topics covered in this chapter.

Documentation Recap

This chapter covered:

Function @title and @description: The @title should be a short one-line description of the function, followed by a more detailed paragraph @description. These tags should give users an idea of what the function does (you can also use @details)
Arguments (@param) and outputs (@return): List all function arguments with @param. Include the argument type (e.g., integer, character, etc.) and a brief description of what the argument does. Be sure to mention any default or optional arguments. Function outputs should be listed with @return and describe the type or class of the object, whether or not it’s reactive, and mention any related functions.
Examples: @examples provide executable R code that captures how the function is used in your app-package. These are incredibly valuable for new users trying to understand how a function (and your app-package) works.

App-package specific considerations:

Connect functions with@seealso and @family: Use @seealso to provide links to related functions (i.e., modules) so users can click through a ‘guided tour’ of your application’s code–group similar functions using @family {description}.
Give more info with @sections: Use @section to give in-depth explanations and specific details about how a function works, including any information about the @usage or its @params.
@usage: This field will be automatically generated by roxygen2, but in some circumstances, it makes sense to set it to NULL and describe a function’s use explicitly.

In the next section, we’ll use roxygen2 to manage our app-package dependencies.

See a typo, error, or something missing?

Please open an issue on GitHub

‘More often, a single .R file will contain multiple function definitions: such as a main function and its supporting helpers, a family of related functions, or some combination of the two.’ - Organise functions into files, R Packages, 2ed ↩︎
Making .R file/function names brief but descriptive will also make writing and running tests easier.↩︎

5.1 roxygen2 intro

5.1.1 markdown = TRUE

5.1.2 @title & @description

5.1.3 @param & @return

File name alignment

5.1.4 @examples

5.2 Documenting app functions

5.2.1 @seealso

5.2.2 @family

5.2.3 @section

5.3 UI & Server functions

5.3.1 @usage

5.3.2 launch_app()

Recap

5.1 `roxygen2` intro

5.1.1 `markdown = TRUE`

5.1.2 `@title` & `@description`

5.1.3 `@param` & `@return`

5.1.4 `@examples`

5.2.1 `@seealso`

5.2.2 `@family`

5.2.3 `@section`

5.3.1 `@usage`

5.3.2 `launch_app()`