charcuterie

The goal of {charcuterie} is to finally have strings as iterable character vectors.

Installation

You can install the published version from CRAN with

install.packages("charcuterie")

You can install the development version with

# install.packages("remotes")
remotes::install_github("jonocarroll/charcuterie")

Motivation

See this blog post: https://jcarroll.com.au/2024/08/03/charcuterie-what-if-strings-were-iterable-in-r/

Most programming languages seem to treat a string as an array of characters, but not R, where a “string” is an object of type “character” which has a length of 1. The number of ‘characters’ in a string is obtained via nchar(x) but otherwise, the individual ‘characters’ comprising the string are rarely exposed.

The most common route around this limitation is to split the string into smaller strings, each containing a single character, i.e.

strsplit("string", split = "")
#> [[1]]
#> [1] "s" "t" "r" "i" "n" "g"

which produces a list of strings, each a single character. This is cumbersome to type out, so this package offers a cleaner approach (which does the above all the same)

library(charcuterie)
#> 
#> Attaching package: 'charcuterie'
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, union
s <- chars("string")
s
#> [1] "string"

This looks like it did nothing, but that’s the point - it still looks like a “string”. It’s actually a vector, though

unclass(s)
#> [1] "s" "t" "r" "i" "n" "g"

Example Usage

This means you can finally do vector things with it, like reverse it

rev(s)
#> [1] "gnirts"

or sort it

sort(s)
#> [1] "ginrst"

or index into it

s[3]
#> [1] "r"

or count elements

count(chars("strawberry"), "r")
#> [1] 3

{charcuterie} defines S3 methods of functions for a wide range of operations to be performed on a string built from a vector of characters

• index with [
• concatenate with c
• print with format and print
• slice with head and tail
• reverse with rev
• sort with sort
• set operations with setdiff, union, intersect, and a new except
• leverage existing vectorised operations like unique, toupper, and tolower

For more detailed usage examples, see the vignettes.