1. Installation

You can install formatR from CRAN, or yihui.r-universe.dev if you want to test the latest development version:

install.packages("formatR", repos = "http://cran.rstudio.com")
# or development version
options(repos = c(yihui = "https://yihui.r-universe.dev", CRAN = "https://cloud.r-project.org"))
install.packages("formatR")

Or check out the Github repository and install from source if you know what this means. This page is always based on the development version.

library(formatR)
sessionInfo()

## R version 4.2.1 (2022-06-23)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Big Sur ... 10.16
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods  
## [7] base     
## 
## other attached packages:
## [1] formatR_1.12
## 
## loaded via a namespace (and not attached):
## [1] compiler_4.2.1 magrittr_2.0.3 tools_4.2.1    stringi_1.7.8 
## [5] knitr_1.39.10  stringr_1.4.0  xfun_0.32      evaluate_0.16

2. Reformat R code

The formatR package was designed to reformat R code to improve readability; the main workhorse is the function tidy_source(). Features include:

• Long lines of code and comments are reorganized into appropriately shorter ones;
• Spaces and indentation are added where necessary;
• Comments are preserved in most cases;
• The number of spaces to indent the code (i.e., tab width) can be specified (default is 4);
• An else statement on a separate line without the leading } will be moved one line back;
• = as an assignment operator can be substituted with <-;
• %>% can be substituted with |>;
• The left brace { can be moved to a new line;
• Arguments of a function call can start on a new line after the function name when they cannot fit on one line;
• Lines can be wrapped after pipes (both magrittr pipes such as %>% and R’s native pipe |> are supported).

Below is an example of what tidy_source() can do. The source code is:

## comments are retained;
# a comment block will be reflowed if it contains long comments;
#' roxygen comments will not be wrapped in any case
1+1

if(TRUE){
x=1  # inline comments
}else{
x=2;print('Oh no... ask the right bracket to go away!')}
1*3 # one space before this comment will become two!
2+2+2    # only 'single quotes' are allowed in comments

lm(y~x1+x2, data=data.frame(y=rnorm(100),x1=rnorm(100),x2=rnorm(100)))  ### a linear model
1+1+1+1+1+1+1+1+1+1+1+1+1+1+1+1+1+1+1+1+1  # comment after a long line
## here is a long long long long long long long long long long long long long comment that may be wrapped

We can copy the above code to clipboard, and type tidy_source(width.cutoff = 50) to get:

## comments are retained; a comment block will be
## reflowed if it contains long comments;
#' roxygen comments will not be wrapped in any case
1 + 1

if (TRUE) {
    x = 1  # inline comments
} else {
    x = 2
    print("Oh no... ask the right bracket to go away!")
}
1 * 3  # one space before this comment will become two!
2 + 2 + 2  # only 'single quotes' are allowed in comments

lm(y ~ x1 + x2, data = data.frame(y = rnorm(100), x1 = rnorm(100),
    x2 = rnorm(100)))  ### a linear model
1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 +
    1 + 1 + 1 + 1 + 1 + 1 + 1 + 1  # comment after a long line
## here is a long long long long long long long
## long long long long long long comment that may
## be wrapped

Two applications of tidy_source():

• tidy_dir() can reformat all R scripts under a directory

• usage() can reformat the usage of a function, e.g. compare usage() with the default output of args():

  library(formatR)
  usage(glm, width = 40)  # can set arbitrary width here
  ## glm(formula, family = gaussian, data,
  ##     weights, subset, na.action,
  ##     start = NULL, etastart, mustart,
  ##     offset, control = list(...),
  ##     model = TRUE, method = "glm.fit",
  ##     x = FALSE, y = TRUE,
  ##     singular.ok = TRUE,
  ##     contrasts = NULL, ...)
  args(glm)
  ## function (formula, family = gaussian, data, weights, subset, 
  ##     na.action, start = NULL, etastart, mustart, offset, control = list(...), 
  ##     model = TRUE, method = "glm.fit", x = FALSE, y = TRUE, singular.ok = TRUE, 
  ##     contrasts = NULL, ...) 
  ## NULL
  

3. The Graphical User Interface

If the shiny packages has been installed, the function tidy_app() can launch a Shiny app to reformat R code like this (live demo at https://yihui.shinyapps.io/formatR/):

formatR::tidy_app()

After hitting the Format button:

4. Evaluate the code and mask output in comments

It is often a pain when trying to copy R code from other people’s code which has been run in R and the prompt characters (usually >) are attached in the beginning of code, because we have to remove all the prompts > and + manually before we are able to run the code. However, it will be convenient for the reader to understand the code if the output of the code can be attached. This motivates the function tidy_eval(), which uses tidy_source() to reformat the source code, evaluates the code in chunks, and attaches the output of each chunk as comments which will not actually break the original source code. Here is an example:

set.seed(123)
tidy_eval(text = c("a<-1+1;a  # print the value", "matrix(rnorm(10),5)"))

a <- 1 + 1
a  # print the value
## [1] 2

matrix(rnorm(10), 5)
##          [,1]    [,2]
## [1,] -0.56048  1.7151
## [2,] -0.23018  0.4609
## [3,]  1.55871 -1.2651
## [4,]  0.07051 -0.6869
## [5,]  0.12929 -0.4457

The default source of the code is from clipboard like tidy_source(), so we can copy our code to clipboard, and simply run this in R:

library(formatR)
tidy_eval()
# without specifying any arguments, it reads code from clipboard

5. Showcase

We continue the example code in Section 2, using different arguments in tidy_source() such as arrow, blank, indent, brace.newline and comment, etc.

Substitute = with <-

if (TRUE) {
    x <- 1  # inline comments
} else {
    x <- 2
    print("Oh no... ask the right bracket to go away!")
}

Discard blank lines

Note the 5th line (an empty line) was discarded:

## comments are retained; a comment block will be reflowed if it
## contains long comments;
#' roxygen comments will not be wrapped in any case
1 + 1
if (TRUE) {
    x = 1  # inline comments
} else {
    x = 2
    print("Oh no... ask the right bracket to go away!")
}
1 * 3  # one space before this comment will become two!

Reindent code (2 spaces instead of 4)

if (TRUE) {
  x = 1  # inline comments
} else {
  x = 2
  print("Oh no... ask the right bracket to go away!")
}

Start function arguments on a new line

With args.newline = TRUE, the example code below

shiny::updateSelectizeInput(session, "foo", label = "New Label", selected = c("A",
    "B"), choices = LETTERS, server = TRUE)

will be reformatted to:

shiny::updateSelectizeInput(
    session, "foo", label = "New Label", selected = c("A", "B"),
    choices = LETTERS, server = TRUE
)

The pipe operators %>% and |>

Since formatR 1.9, code lines contains operators |>, %>%, %T%, %$%, and/or %<>% will be automatically wrapped after these operators. For example,

mtcars %>% subset(am == 0) %>% lm(mpg~hp, data=.)

will be reformatted to:

mtcars %>%
    subset(am == 0) %>%
    lm(mpg ~ hp, data = .)

Move left braces { to new lines

if (TRUE)
{
    x = 1  # inline comments
} else
{
    x = 2
    print("Oh no... ask the right bracket to go away!")
}

Do not wrap comments

1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 +
    1 + 1 + 1  # comment after a long line
## here is a long long long long long long long long long long long long long comment that may be wrapped

Discard comments

1 + 1

if (TRUE) {
    x = 1
} else {
    x = 2
    print("Oh no... ask the right bracket to go away!")
}
1 * 3
2 + 2 + 2

lm(y ~ x1 + x2, data = data.frame(y = rnorm(100), x1 = rnorm(100),
    x2 = rnorm(100)))
1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 +
    1 + 1 + 1 + 1 + 1 + 1 + 1 + 1

6. Further notes

The tricks used in this packages are very dirty. There might be dangers in using the functions in formatR. Please read the next section carefully to know exactly how comments are preserved. The best strategy to avoid failure is to put comments in complete lines or after complete R expressions. Below are some known cases in which tidy_source() fails.

Inline comments after an incomplete expression or ;

1 + 2 + ## comments after an incomplete line
    3 + 4
x <- ## this is not a complete expression
     5
x <- 1; # you should not use ; here!

Code with comments after incomplete R expression cannot be reformatted by formatR. By the way, tidy_source() will move comments after { to the next line, e.g.,

if (TRUE) {## comments
}

will become

if (TRUE) {
    ## comments
}

Inappropriate blank lines

Blank lines are often used to separate complete chunks of R code, and arbitrary blank lines may cause failures in tidy_source() as well when the argument blank = TRUE, e.g.

if (TRUE)

{'this is a BAD style of R programming!'} else 'failure!'

There should not be a blank line after the if statement. Of course blank = FALSE will not fail in this case.

? with comments

We can use the question mark (?) to view the help page, but formatR package is unable to correctly format the code using ? with comments, e.g.

?sd  # help on sd()

In this case, it is recommended to use the function help() instead of the short-hand version ?.

7. How does tidy_source() actually work?

In a nutshell, tidy_source(text = code) is basically deparse(parse(text = code)), but actually it is more complicated only because of one thing: deparse() drops comments, e.g.,

deparse(parse(text = "1+2-3*4/5 # a comment"))

## [1] "expression(1 + 2 - 3 * 4/5)"

The method to preserve comments is to protect them as strings in R expressions. For example, there is a single line of comments in the source code:

  # asdf

It will be first masked as

invisible(".IDENTIFIER1  # asdf.IDENTIFIER2")

which is a legal R expression, so base::parse() can deal with it and will no longer remove the disguised comments. In the end the identifiers will be removed to restore the original comments, i.e. the strings invisible(".IDENTIFIER1 and .IDENTIFIER2") are substituted with empty strings.

Inline comments are handled differently: two spaces will be added before the hash symbol #, e.g.

1+1#  comments

will become

1+1  #  comments

Inline comments are first disguised as a weird operation with its preceding R code, which is essentially meaningless but syntactically correct! For example,

1+1 %\b% "#  comments"

then base::parse() will deal with this expression; again, the disguised comments will not be removed. In the end, inline comments will be freed as well (remove the operator %\b% and surrounding double quotes).

All these special treatments to comments are due to the fact that base::parse() and base::deparse() can tidy the R code at the price of dropping all the comments.

8. Global options

There are global options which can override some arguments in tidy_source():

argument	global option	default
comment	options('formatR.comment')	TRUE
blank	options('formatR.blank')	TRUE
arrow	options('formatR.arrow')	FALSE
pipe	options('formatR.pipe')	FALSE
indent	options('formatR.indent')	4
wrap	options('formatR.wrap')	TRUE
width.cutoff	options('formatR.width')	options('width')
brace.newline	options('formatR.brace.newline')	FALSE
args.newline	options('formatR.args.newline')	FALSE

Also note that single lines of long comments will be wrapped into shorter ones automatically when wrap = TRUE, but roxygen comments will not be wrapped (i.e., comments that begin with #').