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Regular expressions entered popular use from 1968 in two uses: pattern matching in a text editor [9] and lexical analysis in a compiler. [10] Among the first appearances of regular expressions in program form was when Ken Thompson built Kleene's notation into the editor QED as a means to match patterns in text files.
Has two implementations, with PCRE being the more efficient in speed, functions POSIX C POSIX.1 web publication: Licensed by the respective implementation Supports POSIX BRE and ERE syntax Python: python.org: Python Software Foundation License: Python has two major implementations, the built in re and the regex library. Ruby: ruby-doc.org
A parsing expression is a kind of pattern that each string may either match or not match.In case of a match, there is a unique prefix of the string (which may be the whole string, the empty string, or something in between) which has been consumed by the parsing expression; this prefix is what one would usually think of as having matched the expression.
The closeness of a match is measured in terms of the number of primitive operations necessary to convert the string into an exact match. This number is called the edit distance between the string and the pattern. The usual primitive operations are: [1] insertion: cot → coat; deletion: coat → cot
In formal language theory and pattern matching (including regular expressions), the concatenation operation on strings is generalised to an operation on sets of strings as follows: For two sets of strings S 1 and S 2, the concatenation S 1 S 2 consists of all strings of the form vw where v is a string from S 1 and w is a string from S 2, or ...
Parse tree of Python code with inset tokenization. The syntax of textual programming languages is usually defined using a combination of regular expressions (for lexical structure) and Backus–Naur form (a metalanguage for grammatical structure) to inductively specify syntactic categories (nonterminal) and terminal symbols. [7]
The difference between the two algorithms consists in that the optimal string alignment algorithm computes the number of edit operations needed to make the strings equal under the condition that no substring is edited more than once, whereas the second one presents no such restriction. Take for example the edit distance between CA and ABC.
Python supports a wide variety of string operations. Strings in Python are immutable, so a string operation such as a substitution of characters, that in other programming languages might alter the string in place, returns a new string in Python. Performance considerations sometimes push for using special techniques in programs that modify ...