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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 algorithm works recursively by splitting an expression into its constituent subexpressions, from which the NFA will be constructed using a set of rules. [3] More precisely, from a regular expression E, the obtained automaton A with the transition function Δ [clarification needed] respects the following properties:
To make comparisons based on dates (e.g., if the current date and time is after some other date and time), first convert the time(s) to the number of seconds after January 1, 1970, using the function {{#time: U }}, then compare (or add, subtract, etc.) those numerical values.
Since there is no state numbered higher than n, the regular expression R n 0j represents the set of all strings that take M from its start state q 0 to q j. If F = { q 1,...,q f} is the set of accept states, the regular expression R n 01 | ... | R n 0f represents the language accepted by M. The initial regular expressions, for k = -1, are ...
In communications messages, a date-time group (DTG) is a set of characters, usually in a prescribed format, used to express the year, the month, the day of the month, the hour of the day, the minute of the hour, and the time zone, if different from Coordinated Universal Time (UTC).
the SenseTalk Pattern Language (readable regular expressions) in V1.81 (2018) date formats with readable tokens in V1.91 (2019) multi-case if statements in V2.00 (2020) every expressions; use of each expressions for containers in V2.04 (2021)
Python supports normal floating point numbers, which are created when a dot is used in a literal (e.g. 1.1), when an integer and a floating point number are used in an expression, or as a result of some mathematical operations ("true division" via the / operator, or exponentiation with a negative exponent).