In tidyverse/glue: Interpreted String Literals

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "README-"
)
library(glue)

glue

glue offers interpreted string literals that are small, fast, and dependency-free. glue does this by embedding R expressions in curly braces, which are then evaluated and inserted into the string.

Installation

::: .pkgdown-release

# Install released version from CRAN
install.packages("glue")

:::

::: .pkgdown-devel

# Install development version from GitHub
pak::pak("tidyverse/glue")

:::

Usage

glue() makes it easy to interpolate data into strings:

library(glue)

name <- "Fred"
glue("My name is {name}.")

stringr::str_glue() is an alias for glue::glue(). So if you've already attached stringr (or perhaps the whole tidyverse), you can use str_glue() to access all of the functionality of glue():

library(stringr) # or library(tidyverse)

name <- "Wilma"
str_glue("My name is {name}.")
#> My name is Wilma.

You're not limited to using a bare symbol inside {}; it can be any little bit of R code:

name <- "Pebbles"
glue("Here is my name in uppercase and doubled: {strrep(toupper(name), 2)}.")

Data can come from various sources

glue can interpolate values from the local environment or from data passed in name = value form:

x <- "the local environment"
glue(
  "`glue()` can access values from {x} or from {y}. {z}",
  y = "named arguments",
  z = "Woo!"
)

If the relevant data lives in a data frame (or list or environment), use glue_data() instead:

mini_mtcars <- head(cbind(model = rownames(mtcars), mtcars))
glue_data(mini_mtcars, "{model} has {hp} hp.")

glue_data() is very natural to use with the pipe:

mini_mtcars |>
  glue_data("{model} gets {mpg} miles per gallon.")

These glue_data() examples also demonstrate that glue() is vectorized over the data.

What you see is awfully close to what you get

glue() lets you write code that makes it easy to predict what the final string will look like. There is considerably less syntactical noise and mystery compared to paste() and sprintf().

Empty first and last lines are automatically trimmed, as is leading whitespace that is common across all lines. You don't have to choose between indenting your code properly and getting the output you actually want. Consider what happens when glue() is used inside the body of a function:

foo <- function() {
  glue("
    A formatted string
    Can have multiple lines
      with additional indention preserved")
}
foo()

The leading whitespace that is common to all 3 lines is absent from the result.

Learning more

glue is a relatively small and focused package, but there's more to it than the basic usage of glue() and glue_data() shown here. More recommended functions and resources:

The "Get started" article (vignette("glue")) demonstrates more interesting features of glue() and glue_data().
glue_sql() and glue_data_sql() are specialized functions for producing SQL statements.
glue provides a couple of custom knitr engines that allow you to use glue syntax in chunks; learn more in vignette("engines", package = "glue").