nse-force {rlang}R Documentation

Force parts of an expression


It is sometimes useful to force early evaluation of part of an expression before it gets fully evaluated. The tidy eval framework provides several forcing operators for different use cases.

Use qq_show() to experiment with forcing operators. qq_show() defuses its input, processes all forcing operators, and prints the result with expr_print() to reveal objects inlined in the expression by the forcing operators.





An expression to be quasiquoted.

Forcing names

When a function takes multiple named arguments (e.g. dplyr::mutate()), it is difficult to supply a variable as name. Since the LHS of = is defused, giving the name of a variable results in the argument having the name of the variable rather than the name stored in that variable. This problem of forcing evaluation of names is exactly what the !! operator is for.

Unfortunately R is very strict about the kind of expressions supported on the LHS of =. This is why rlang interprets the walrus operator := as an alias of =. You can use it to supply names, e.g. a := b is equivalent to a = b. Since its syntax is more flexible you can also force names on its LHS:

name <- "Jane"

list2(!!name := 1 + 2)
exprs(!!name := 1 + 2)

Like =, the := operator expects strings or symbols on its LHS.

Since unquoting names is related to interpolating within a string with the glue package, we have made the glue syntax available on the LHS of :=:

list2("{name}" := 1)
tibble("{name}" := 1)

You can also interpolate defused function arguments with double braces {{, similar to the curly-curly syntax:

wrapper <- function(data, var) {
  data %>% mutate("{{ var }}_foo" := {{ var }} * 2)

Currently, forcing names with := only works in top level expressions. These are all valid:

exprs("{name}" := x)
tibble("{name}" := x)

But deep-forcing names isn't supported:

exprs(this(is(deep("{name}" := x))))


Formally, quo() and expr() are quasiquotation functions, !! is the unquote operator, and !!! is the unquote-splice operator. These terms have a rich history in Lisp languages, and live on in modern languages like Julia and Racket.

Life cycle


# Interpolation with {{  }} is the easiest way to forward
# arguments to tidy eval functions:
if (is_attached("package:dplyr")) {

# Forward all arguments involving data frame columns by
# interpolating them within other data masked arguments.
# Here we interpolate `arg` in a `summarise()` call:
my_function <- function(data, arg) {
  summarise(data, avg = mean({{ arg }}, na.rm = TRUE))

my_function(mtcars, cyl)
my_function(mtcars, cyl * 10)

# The  operator is just a shortcut for `!!enquo()`:
my_function <- function(data, arg) {
  summarise(data, avg = mean(!!enquo(arg), na.rm = TRUE))

my_function(mtcars, cyl)


# Quasiquotation functions quote expressions like base::quote()

# In addition, they support unquoting. Let's store symbols
# (i.e. object names) in variables:
this <- sym("apples")
that <- sym("oranges")

# With unquotation you can insert the contents of these variables
# inside the quoted expression:

# You can also insert values:
expr(how_many(!!(1 + 2)))
quo(how_many(!!(1 + 2)))

# Note that when you unquote complex objects into an expression,
# the base R printer may be a bit misleading. For instance compare
# the output of `expr()` and `quo()` (which uses a custom printer)
# when we unquote an integer vector:

# This is why it's often useful to use qq_show() to examine the
# result of unquotation operators. It uses the same printer as
# quosures but does not return anything:

# Use `!!!` to add multiple arguments to a function. Its argument
# should evaluate to a list or vector:
args <- list(1:3, na.rm = TRUE)

# You can combine the two
var <- quote(xyz)
extra_args <- list(trim = 0.9, na.rm = TRUE)
quo(mean(!!var , !!!extra_args))

# The plural versions have support for the `:=` operator.
# Like `=`, `:=` creates named arguments:
quos(mouse1 := bernard, mouse2 = bianca)

# The `:=` is mainly useful to unquote names. Unlike `=` it
# supports `!!` on its LHS:
var <- "unquote me!"
quos(!!var := bernard, mouse2 = bianca)

# All these features apply to dots captured by enquos():
fn <- function(...) enquos(...)
fn(!!!args, !!var := penny)

# Unquoting is especially useful for building an expression by
# expanding around a variable part (the unquoted part):
quo1 <- quo(toupper(foo))

quo2 <- quo(paste(!!quo1, bar))

quo3 <- quo(list(!!quo2, !!!syms(letters[1:5])))

[Package rlang version 0.4.11 Index]