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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 (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 .
The original Mozilla proxy auto-config implementation, which provides a glob-matching function on strings, uses a replace-as-RegExp implementation as above. The bracket syntax happens to be covered by regex in such an example. Python's fnmatch uses a more elaborate procedure to transform the pattern into a regular expression. [17]
String functions common to many languages are listed below, including the different names used. The below list of common functions aims to help programmers find the equivalent function in a language. Note, string concatenation and regular expressions are handled in separate pages.
Here, 0 is a single value pattern. Now, whenever f is given 0 as argument the pattern matches and the function returns 1. With any other argument, the matching and thus the function fail. As the syntax supports alternative patterns in function definitions, we can continue the definition extending it to take more generic arguments:
Greed, in regular expression context, describes the number of characters which will be matched (often also stated as "consumed") by a variable length portion of a regular expression – a token or group followed by a quantifier, which specifies a number (or range of numbers) of tokens. If the portion of the regular expression is "greedy", it ...
In computer science, the Knuth–Morris–Pratt algorithm (or KMP algorithm) is a string-searching algorithm that searches for occurrences of a "word" W within a main "text string" S by employing the observation that when a mismatch occurs, the word itself embodies sufficient information to determine where the next match could begin, thus bypassing re-examination of previously matched characters.
Standard examples of data-driven languages are the text-processing languages sed and AWK, [1] and the document transformation language XSLT, where the data is a sequence of lines in an input stream – these are thus also known as line-oriented languages – and pattern matching is primarily done via regular expressions or line numbers.