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The goal of regexpert is to make regular expressions in R less of a headache. It provides a pipe-friendly, human-readable DSL for building and executing regex patterns — no symbol memorization required.

Installation

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

# install.packages("devtools")
devtools::install_github("byuirpytooling/regexpert")

Why regexpert?

Standard regular expressions are powerful but often unreadable. regexpert breaks the process into three logical steps:

  1. Build: Describe what you’re looking for using plain-English functions like xp_build_digits().
  2. Operate: Refine your pattern with xp_op_repeat(), xp_op_optional(), and more.
  3. Act: Use xp_action_find() to return matches, or xp_action_view() to inspect the raw regex being generated.

Example

The regexpert workflow is designed to be used with the pipe (%>% or |>):


# Find digits in a string
xp_build_digits() %>%
  xp_op_repeat(1, Inf) %>%
  xp_action_find("Order #88412 placed")
#> [1] "88412"

# Find only the letters
xp_build_letters(case = "both") %>%
  xp_op_repeat(1, Inf) %>%
  xp_action_find("Order #88412 placed")
#> [1] "Order" "placed"

# Use a standard pattern for common data types
xp_build_standard("email") %>%
  xp_action_find("Contact us at support@regexpert.com")
#> [1] "support@regexpert.com"

# Inspect the regex being built under the hood
xp_build_digits() %>%
  xp_op_repeat(3) %>%
  xp_action_view()
#> Current Regex Pattern:
#> (?:\d){3}

Documentation

Full documentation, including function references and vignettes, is available at https://byuirpytooling.github.io/regexpert/.

📖 Get started: Getting Started with regexpert