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A regular expression (shortened as regex or regexp), [1] sometimes referred to as rational expression, [2] [3] is a sequence of characters that specifies a match pattern in text. Usually such patterns are used by string-searching algorithms for "find" or "find and replace" operations on strings , or for input validation .
A regex search scans the text of each page on Wikipedia in real time, character by character, to find pages that match a specific sequence or pattern of characters. Unlike keyword searching, regex searching is by default case-sensitive, does not ignore punctuation, and operates directly on the page source (MediaWiki markup) rather than on the ...
The patterns generally have the form of either sequences or tree structures. Uses of pattern matching include outputting the locations (if any) of a pattern within a token sequence, to output some component of the matched pattern, and to substitute the matching pattern with some other token sequence (i.e., search and replace).
Python has two major implementations, the built in re and the regex library. Ruby: ruby-doc.org: GNU Library General Public License: Ruby 1.8, Ruby 1.9, and Ruby 2.0 and later versions use different engines; Ruby 1.9 integrates Oniguruma, Ruby 2.0 and later integrate Onigmo, a fork from Oniguruma. Rust: docs.rs: MIT License
Another more complex type of search is regular expression searching, where the user constructs a pattern of characters or other symbols, and any match to the pattern should fulfill the search. For example, to catch both the American English word "color" and the British equivalent "colour", instead of searching for two different literal strings ...
Different approximate matchers impose different constraints. Some matchers use a single global unweighted cost, that is, the total number of primitive operations necessary to convert the match to the pattern. For example, if the pattern is coil, foil differs by one substitution, coils by one insertion, oil by one deletion, and foal by two ...
Then, the number of states of A is 2s − c (linear in the size of E). The number of transitions leaving any state is at most two. Since an NFA of m states and at most e transitions from each state can match a string of length n in time O(emn), a Thompson NFA can do pattern matching in linear time, assuming a fixed-size alphabet. [4] [better ...
RE2 is a software library which implements a regular expression engine. It uses finite-state machines, in contrast to most other regular expression libraries. RE2 supports a C++ interface. RE2 was implemented by Google and Google uses RE2 for Google products. [3]