---
title: "super"
output:
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embed_resources: ["all"]
vignette: >
%\VignetteEngine{litedown::vignette}
%\VignetteIndexEntry{ympes}
%\VignetteEncoding{UTF-8}
%\VignetteDepends{microbenchmark, glue}
---
super is a fork / reimplementation of the [glue](https://glue.tidyverse.org)
package with a focus on efficiency and simplicity at a cost of flexibility.
As of the 0.0.1 release it should be considered 'experimental'.
## Differences from glue
- `super::glue()` takes only two arguments: A character string that is used as
a template and an environment to look up the embraced inputs. There is no
option to change the delimiters from being a pair of braces (e.g. `{name}`).
- Embraced inputs are always looked up in the provided environment (akin to
calling `get()`) and are not evaluated. This is similar to `glue::glue_safe()`
and `glue::glue_data_safe()` but note that this is not the default behaviour
of `glue::glue()`.
- `super::glue()` does not trim inputs. Instead this is done by either the
function `super::glut()` or explicitly by `glue(trim(x))`.
- `super::glue()` returns an unclassed character vector whereas `glue::glue()`
returns a `` object and provides a variety of methods to work on that
object.
- At present, `super::glue()` does not provide any allowance for different
handling of `NA` and `NULL` values, instead following the behaviour of
`paste()`.
- Recycling of embraced arguments currently follows standard R recycling rules
where the arguments will be recycled to the length of the longest one.
- `glue::glue()` arguments (and their associated behaviours) `.comment`,
`.literal` and `.transformer` are not implemented.
## Examples
```{r}
library(super)
```
### Simple concatenation
```{r}
bar <- "baz"
glue("foo{bar}")
```
### list-like input
```{r}
dat <- head(cbind(car = rownames(mtcars), mtcars))
glue("{car} does {mpg} mpg.", dat)
```
### Trimmed output
```{r}
name <- "Fred"
age <- 50
anniversary <- as.Date("1991-10-12")
out <- glut("
My name is {name},
my age next year is {age},
my anniversary is {anniversary}.
")
cat(out)
```
### Partially vectorised
Over embraced arguments
```{r}
head(glue("Item {LETTERS}"))
```
But not over input strings (yet)
```{r}
tryCatch(
glue(letters),
error = function(e) conditionMessage(e)
)
```
## Relative timing benchmarks
```{r}
library(microbenchmark)
```
### Simple concatenation
```{r}
#| print = xfun:::record_print.default
bar <- "baz"
bob <- 20
microbenchmark(
sprintf = sprintf("foo%s %d", bar, bob),
paste0 = paste0("foo", bar, " ", bob),
super = super::glue("foo{bar} {bob}"),
glue = as.character(glue::glue_safe("foo{bar} {bob}", .trim = FALSE)),
unit = "relative",
check = "identical"
)
```
### Data frame input
```{r}
#| print = xfun:::record_print.default
dat <- head(cbind(car = rownames(mtcars), mtcars))
microbenchmark(
sprintf = with(dat, sprintf("%s does %.3g mpg.", car, mpg)),
paste0 = with(dat, paste(car, "does", mpg, "mpg.")),
super = super::glue("{car} does {mpg} mpg.", dat),
glue = as.character(glue::glue_data(dat, "{car} does {mpg} mpg.")),
unit = "relative",
check = "identical"
)
```
### Trimmed output
```{r}
#| print = xfun:::record_print.default
microbenchmark(
super = super::glut("
My name is {name},
my age next year is {age},
my anniversary is {anniversary}.
"),
glue = as.character(glue::glue("
My name is {name},
my age next year is {age},
my anniversary is {anniversary}.
")),
unit = "relative",
check = "identical"
)
```
### Vectorized performance
For larger input with both `glue::glue()` and `super::glue()`, the performance
becomes dominated by the internally constructed call to `paste0()`, hence the
convergence observed below.
```{r}
#| print = xfun:::record_print.default
bar <- rep("baz", 1e5)
microbenchmark(
sprintf = sprintf("foo%s %d", bar, bob),
paste0 = paste0("foo", bar, " ", bob),
super = super::glue("foo{bar} {bob}"),
glue = as.character(glue::glue_safe("foo{bar} {bob}", .trim = FALSE)),
unit = "relative",
check = "identical"
)
```