Help for package rebus

Type:

Package

Title:

Build Regular Expressions in a Human Readable Way

Version:

0.1-3

Date:

2017-04-25

Author:

Richard Cotton [aut, cre]

Maintainer:

Richard Cotton <richierocks@gmail.com>

Description:

Build regular expressions piece by piece using human readable code. This package is designed for interactive use. For package development, use the rebus.* dependencies.

Depends:

R (≥ 3.1.0)

Imports:

rebus.base (≥ 0.0-3), rebus.datetimes, rebus.numbers, rebus.unicode (≥ 0.0-2)

Suggests:

testthat

License:

Unlimited

LazyLoad:

yes

LazyData:

yes

Acknowledgments:

Development of this package was partially funded by the Proteomics Core at Weill Cornell Medical College in Qatar <http://qatar-weill.cornell.edu>. The Core is supported by 'Biomedical Research Program' funds, a program funded by Qatar Foundation.

RoxygenNote:

6.0.1

Collate:

'export-base.R' 'export-datetimes.R' 'export-numbers.R' 'export-unicode.R' 'imports.R' 'regex-package.R'

NeedsCompilation:

Packaged:

2017-04-25 16:46:25 UTC; richierocks

Repository:

CRAN

Date/Publication:

2017-04-25 21:42:46 UTC

rebus: Regular Expression Builder, Um, Something

Description

Build regular expressions in a human readable way.

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.

Author(s)

Richard Cotton richierocks@gmail.com

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