NOTE: This is a toy package created for expository purposes, for the second edition of R Packages. It is not meant to actually be useful. If you want a package for factor handling, please see stringr, stringi, rex, and rematch2.

The goal of regexcite is to provide better, easier, more convenient function for string manipulation.

You can install the development version of regexcite from GitHub with:

# install.packages("devtools")
devtools::install_github("yuwangy/regexcite")

A fairly common task when dealing with strings is the need to split a single string into many parts. This is what base::strplit() and stringr::str_split() do.

(x <- "alfa,bravo,charlie,delta")
#> [1] "alfa,bravo,charlie,delta"
strsplit(x, split = ",")
#> [[1]]
#> [1] "alfa"    "bravo"   "charlie" "delta"
stringr::str_split(x, pattern = ",")
#> [[1]]
#> [1] "alfa"    "bravo"   "charlie" "delta"

Notice how the return value is a list of length one, where the first element holds the character vector of parts. Often the shape of this output is inconvenient, i.e. we want the un-listed version.

That’s exactly what regexcite::str_split_one() does.

library(regexcite)

str_split_one(x, pattern = ",")
#> [1] "alfa"    "bravo"   "charlie" "delta"

Use str_split_one() when the input is known to be a single string. For safety, it will error if its input has length greater than one.

str_split_one() is built on stringr::str_split(), so you can use its n argument and stringr’s general interface for describing the pattern to be matched.

str_split_one(x, pattern = ",", n = 2)
#> [1] "alfa"                "bravo,charlie,delta"

y <- "192.168.0.1"
str_split_one(y, pattern = stringr::fixed("."))
#> [1] "192" "168" "0"   "1"

This is a basic example which shows you how to solve a common problem:

library(regexcite)
## basic example code

What is special about using README.Rmd instead of just README.md? You can include R chunks like so:

summary(cars)
#>      speed           dist       
#>  Min.   : 4.0   Min.   :  2.00  
#>  1st Qu.:12.0   1st Qu.: 26.00  
#>  Median :15.0   Median : 36.00  
#>  Mean   :15.4   Mean   : 42.98  
#>  3rd Qu.:19.0   3rd Qu.: 56.00  
#>  Max.   :25.0   Max.   :120.00

You’ll still need to render README.Rmd regularly, to keep README.md up-to-date. devtools::build_readme() is handy for this. You could also use GitHub Actions to re-render README.Rmd every time you push. An example workflow can be found here: https://github.com/r-lib/actions/tree/v1/examples.

You can also embed plots, for example:

In that case, don’t forget to commit and push the resulting figure files, so they display on GitHub and CRAN.