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Reusing documentation

roxygen2 provides several ways to avoid repeating yourself in code documentation, while assembling information from multiple places in one documentation file:

The chapter concludes by showing you how to update superseded reuse mechanisms that we no longer recommend: @includeRmd, @eval/@evalRd, and @template.

Multiple functions in the same topic

You can document multiple functions in the same file by using either @rdname or @describeIn tag. It’s a technique best used with care: documenting too many functions in one place leads to confusion. Use it when all functions have the same (or very similar) arguments.

@rdname

Use @rdname <destination>1 to include multiple functions in the same page. Tags (e.g. @title, @description, @examples) will be combined, across blocks but often this yields text that is hard to understand. So we recommend that you make one block that contains the title, description, common parameters, examples and so on, and then only document individual parameters in the other blocks.

There are two basic ways to do that. You can create a standalone documentation block and then add the functions to it. This typically works best when you have a family of related functions and you want to link to that family from other functions (i.e. trig in the examples below).

#' Trigonometric approximations
#' @param x Input, in radians.
#' @name trig
NULL
#> NULL

#' @rdname trig
#' @export
sin_ish <- function(x) x - x^3 / 6

#' @rdname trig
#' @export
cos_ish <- function(x) 1 - x^2 / 2

#' @rdname trig
#' @export
tan_ish <- function(x) x + x^3 / 3

Alternatively, you can add docs to an existing function. This tends to work better if you have a “primary” function with some variants or some helpers.

#' Logarithms
#' 
#' @param x A numeric vector
#' @export
log <- function(x, base) ...

#' @rdname log
#' @export
log2 <- function(x) log(x, 2)

#' @rdname log
#' @export
ln <- function(x) log(x, exp(1))

@describeIn

An alternative to @rdname is @describeIn. It has a slightly different syntax because as well as a topic name, you also provide a brief description for the function, like @describein topic one sentence description. The primary difference between @rdname and @describeIn, is that @describeIn creates a new section containing a bulleted list all of each function, along with its description. It uses a number of heuristics to determine the heading of this section, depending on you’re documenting related functions, methods for a generic, or methods for a class.

In general, I no longer recommend @describeIn because I don’t think the heuristics it uses are as good as a thoughtful hand-crafted summary. If you’re currently using @describeIn, you can general replace it with @rdname, as long as you give some thought to the multiple-function @description.

Order of includes

By default, roxygen blocks are processed in the order in which they appear in the file. When you’re combining multiple files, this can sometimes cause the function usage to appear in a suboptimal order. You can override the default ordering with @order. For example, the following the block would place times first in arith.Rd because 1 comes before 2.

#' @rdname arith
#' @order 2
add <- function(x, y) x + y

#' @rdname arith
#' @order 1
times <- function(x, y) x * y

Automatically copy tags

If two or more functions share have similarities but are different or complex enough that you don’t want to document them in a single file, you can use one of the four @inherit tags to automatically copy various components from another topic:

We think of this as “inheritance” rather than just copying, because anything you inherit can be overridden by a more specific definition in the documentation. This applies particularly to @inheritParams which allows you to copy the documentation for some parameters while documenting others directly. We’ll focus on this first.

Parameters

The oldest, and most frequently used, inherits tag is @inheritParams. It’s particularly useful when multiple functions use the same argument name for the same task, as you can document the argument once, then inherit those docs elsewhere. For example, take the dplyr functions arrange(), mutate(), and summarise() which all have an argument called .data. arrange() is documented like so:

#' @param .data A data frame, data frame extension (e.g. a tibble), or a
#'   lazy data frame (e.g. from dbplyr or dtplyr). See *Methods*, below, for
#'   more details.
#' @param ... <[`data-masking`][rlang::args_data_masking]> Variables, or
#'   functions of variables. Use [desc()] to sort a variable in descending
#'   order.
arrange <- function(.data, ...) {}

Then mutate() and summarise() don’t need to provide @param .data but can instead inherit the documentation from arrange():

#' @inheritParams arrange
mutate <- function(.data, ...) {}

#' @inheritParams arrange
summarise <- function(.data, ...) {}

If this was all you wrote it wouldn’t be quite right because mutate() and summarise() would also inherit the documentation for ..., which has a different interpretation in these functions. So, for example, mutate() provides its own definition for ...:

#' @inheritParams arrange
#' @param ... <[`data-masking`][rlang::args_data_masking]> Name-value pairs.
#'   The name gives the name of the column in the output.
#'
#'   The value can be:
#'
#'   * A vector of length 1, which will be recycled to the correct length.
#'   * A vector the same length as the current group (or the whole data frame
#'     if ungrouped).
#'   * `NULL`, to remove the column.
#'   * A data frame or tibble, to create multiple columns in the output.
mutate <- function(.data, ...) {}

Note that only the documentation for arguments with the same names are inherited. For example, arrange() also has a .by_group argument. Since no other function in dplyr has an argument with this name, its documentation will never be inherited.

Multiple parameters

Sometimes you document two (or more) tightly coupled parameters together. For example, dplyr::left_join() has:

#' @param x,y A pair of data frames, data frame extensions (e.g. a tibble), or
#'   lazy data frames (e.g. from dbplyr or dtplyr). See *Methods*, below, for
#'   more details.

When joint parameter documentation is inherited, it’s all or nothing, i.e. if a function has @inheritParams left_join it will only inherit the documentation for x and y if it has both x and y arguments and neither is documented by the inheriting function.

The dot prefix

Many tidyverse functions that accept named arguments in ... also use a . prefix for their own arguments. This reduces the risk of an argument going to the wrong place. For example, dplyr::mutate() has .by, .keep, .before, and .after arguments, because if they didn’t have that prefix, you wouldn’t be able to create new variables called by, keep, before, or after. We call this pattern the dot prefix.

This means that an argument with the same meaning can come in one of two forms: with and without the .. @inheritParams knows about this common pattern so ignores a . prefix when matching argument name. In other words, .x will inherit documentation for x, and x will inherit documentation from .x.

Inheriting other components

You can use @inherits foo to inherit the documentation for every supported tag from another topic. Currently, @inherits supports inheriting the following tags: params, return, title, description, details, seealso, sections, references, examples, author, source, note, format.

By supplying a space separated list of components after the function name, you can also choose to inherit only selected components. For example, @inherit foo returns would just inherit the @returns tag, and @inherit foo seealso source would inherit the @seealso and @source tags.

@inherit foo sections will inherit every @section tag (which can also be specified in markdown by using the top-level heading spec, #). To inherit a specific section from another function, use @inheritSection foo Section title. For example, all the “adverbs” in purrr use #' @inheritSection safely Adverbs to inherit a standard section that provides advice on using an adverb in package code.

Documenting ...

When your function passes ... on to another function, it can be useful to inline the documentation for some of the most common arguments. This technique is inspired by the documentation for plot(), where ... can take any graphical parameter; ?plot describes some of the most common arguments so that you don’t have to look them up in ?par.

@inheritDotParams has two components: the function to inherit from and the arguments to inherit. Since you’ll typically only want to document the most important arguments, @inheritDotParams comes with a flexible specification for argument selection inspired by dplyr::select():

Inheriting from other packages

It’s most common to inherit from other documentation topics within the current package, but roxygen2 also supports inheriting documentation from other packages by using package::function syntax, e.g.:

When inheriting documentation from another package bear in mind that you’re now taking a fairly strong dependency on an external package, and to ensure every developer produces the same documentation you’ll need to make sure that they all have the same version of the package installed. And if the package changes the name of the topic or section, your documentation will require an update. For those reasons, this technique is best used sparingly.

Inline code

To insert code inline, enclose it in `r `. Roxygen will interpret the rest of the text within backticks as R code and evaluate it, and replace the backtick expression with its value. Here’s a simple example:

#' Title `r 1 + 1`
#'
#' Description `r 2 + 2`
foo <- function() NULL

This is equivalent to writing:

#' Title 2
#'
#' Description 4
foo <- function() NULL

The resulting text, together with the whole tag is interpreted as markdown, as usual. This means that you can use R to dynamically write markdown. For example if you defined this function in your package:

alphabet <- function(n) {
  paste0("`", letters[1:n], "`", collapse = ", ")
}

You could then write:

#' Title
#' 
#' @param x A string. Must be one of `r alphabet(5)`
foo <- function(x) NULL

The result is equivalent to writing the following by hand:

#' Title
#' 
#' @param x A string. Must be one of `a`, `b`, `c`, `d`, `e`
foo <- function(x) NULL

This is a powerful technique for reducing duplication because you can flexibly parameterise the function however best meets your needs. Note that the evaluation environment is deliberately a child of the package that you’re documenting so you can call internal functions.

Child documents

You can use the same .Rmd or .md document in the documentation, README.Rmd, and vignettes by using child documents:

```{r child = "common.Rmd"}
```

The included Rmd file can have roxygen Markdown-style links to other help topics. E.g. [roxygen2::roxygenize()] will link to the manual page of the roxygenize function in roxygen2. See vignette("rd-formatting") for details.

If the Rmd file contains roxygen (Markdown-style) links to other help topics, then some care is needed, as those links will not work in Rmd files by default. A workaround is to specify external HTML links for them. These external locations will not be used for the manual which instead always links to the help topics in the manual. Example:

See also the [roxygen2::roxygenize()] function.

[roxygen2::roxygenize()]: https://roxygen2.r-lib.org/reference/roxygenize.html

This example will link to the supplied URLs in HTML / Markdown files and it will link to the roxygenize help topic in the manual.

Note that if you add external link targets like these, then roxygen will emit a warning about these link references being defined multiple times (once externally, and once to the help topic). This warning originates in Pandoc, and it is harmless.

Superseded

Over the years, we have experimented with a number of other ways to reduce duplication across documentation files. A number of these are now superseded and we recommend changing them to use the techniques described above:

Inline R markdown can only generate markdown text within a tag so in principle it is less flexible than @eval/@evalRd/@template. However, our experience has revealed that generating multiple tags at once tends to be rather inflexible, and you often end up refactoring into smaller pieces so we don’t believe this reflects a real loss of functionality.

  1. The destination is a topic name. There’s a one-to-one correspondence between topic names and .Rd files where a topic called foo will produce a file called man/foo.Rd.↩︎

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