rebus (version 0.0-4)

regex: Create a regex

Description

Creates a regex object. Build regular expressions in a human readable way.

Usage

regex(...)

perl_regex(...)

## S3 method for class 'perl_regex':
format(x, ...)

Arguments

...

Passed to paste0.

x

A regex.

Value

• An object of class regex.

Details

Regular expressions are a very powerful tool, but the syntax is terse enough to be difficult to read. This makes bugs easy to introduce, and hard to find. This package contains functions to make building regular expressions easier.

See Also

paste0 as.regex(month.abb) regex(letters[1:5], "?") as.perl_regex(month.abb) perl_regex(letters[1:5], "?") regex and regexpr The `stringr` and `stringi` packages provide tools for matching regular expressions and nicely complement this package. http://www.regular-expressions.info has good advice on using regular expression in R. In particular, see http://www.regular-expressions.info/rlanguage.html and http://www.regular-expressions.info/examples.html https://www.debuggex.com is a visual regex debugging and testing site.

Examples

### Match a hex colour, like `"#99af01"`
# This reads *Match a hash, followed by six hexadecimal values.*

"#" %R% hex_digit(6)

# To match only a hex colour and nothing else, you can add anchors to the
# start and end of the expression.

START %R% "#" %R% hex_digit(6) %R% END

### Simple email address matching.
# This reads *Match one or more letters, numbers, dots, underscores, percents,
# plusses or hyphens. Then match an 'at' symbol. Then match one or more letters,
# numbers, dots, or hyphens. Then match a dot. Then match two to four letters.*

one_or_more(char_class(ASCII_ALNUM %R% "._%+-")) %R%
  "@" %R%
  one_or_more(char_class(ASCII_ALNUM %R% ".-")) %R%
  DOT %R%
  ascii_alpha(2, 4)

### IP address matching.
# First we need an expression to match numbers between 0 and 255.  Both the
# following syntaxes read *Match two then five then a number between zero and
# five.  Or match two then a number between zero and four then a digit. Or match
# an optional zero or one followed by an optional digit folowed by a compulsory
# digit.  Make this a single token, but don't capture it.*

# Using the \%|\% operator
ip_element <- group(
  "25" %R% char_range(0, 5) %|%
  "2" %R% char_range(0, 4) %R% ascii_digit() %|%
  optional(char_class("01")) %R% optional(ascii_digit()) %R% ascii_digit()
)

# The same again, this time using the or function
ip_element <- or(
  "25" %R% char_range(0, 5),
  "2" %R% char_range(0, 4) %R% ascii_digit(),
  optional(char_class("01")) %R% optional(ascii_digit()) %R% ascii_digit()
)

# It's easier to write using number_range, though it isn't quite as optimal
# as handcrafted regexes.
number_range(0, 255, allow_leading_zeroes = TRUE)

# Now an IP address consists of 4 of these numbers separated by dots. This
# reads *Match a word boundary. Then create a token from an `ip_element`
# followed by a dot, and repeat it three times.  Then match another `ip_element`
# followed by a word boundary.*

BOUNDARY %R%
  repeated(group(ip_element %R% DOT), 3) %R%
  ip_element %R%
  BOUNDARY