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Regular expressions are used in search engines, in search and replace dialogs of word processors and text editors, in text processing utilities such as sed and AWK, and in lexical analysis. Regular expressions are supported in many programming languages. Library implementations are often called an "engine", [4] [5] and many of these are ...
MediaWiki's regular expression syntax works like this: Most characters represent themselves. For example, insource:/C-3p0/ will search for pages containing the literal string "C-3p0" (case-sensitive). The following metacharacters are treated specially: . + * ? | { [ ] ( ) " \ # @ < ~. Any metacharacter can be escaped by preceding it with a ...
Regular Expression Flavor Comparison – Detailed comparison of the most popular regular expression flavors; Regexp Syntax Summary; Online Regular Expression Testing – with support for Java, JavaScript, .Net, PHP, Python and Ruby; Implementing Regular Expressions – series of articles by Russ Cox, author of RE2; Regular Expression Engines
A regular expression or regex is a sequence of characters that define a pattern to be searched for in a text. Each occurrence of the pattern may then be automatically replaced with another string, which may include parts of the identified pattern. AutoWikiBrowser uses the .NET flavor of regex. [1]
Regular languages are a category of languages (sometimes termed Chomsky Type 3) which can be matched by a state machine (more specifically, by a deterministic finite automaton or a nondeterministic finite automaton) constructed from a regular expression. In particular, a regular language can match constructs like "A follows B", "Either A or B ...
find wildcard expressions and regular expressions. A search matches what you see rendered on the screen and in a print preview. The raw "source" wikitext is searchable by employing the insource parameter. For these two kinds of searches a word is any string of consecutive letters and numbers matching a whole word or phrase.
TRE is an open-source library for pattern matching in text, [2] which works like a regular expression engine with the ability to do approximate string matching. [3] It was developed by Ville Laurikari [1] and is distributed under a 2-clause BSD-like license.
To decide whether two given regular expressions describe the same language, each can be converted into an equivalent minimal deterministic finite automaton via Thompson's construction, powerset construction, and DFA minimization. If, and only if, the resulting automata agree up to renaming of states, the regular expressions' languages agree.