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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 ...
String functions are used in computer programming languages to manipulate a string or query information about a string (some do both).. Most programming languages that have a string datatype will have some string functions although there may be other low-level ways within each language to handle strings directly.
In many programming languages, a particular syntax of strings is used to represent regular expressions, which are patterns describing string characters. However, it is possible to perform some string pattern matching within the same framework that has been discussed throughout this article.
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.
A regular expression is a pattern that can be used to match strings. To increase the readability of patterns in the code, the RegularExpression class allows the use of symbolic names encapsulated with colons (:) for common sets. For instance, matching a string containing only letters typically described as [A-Za-z] can be abbreviated using ...
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]
The set of all strings over Σ of length n is denoted Σ n. For example, if Σ = {0, 1}, then Σ 2 = {00, 01, 10, 11}. We have Σ 0 = {ε} for every alphabet Σ. The set of all strings over Σ of any length is the Kleene closure of Σ and is denoted Σ *. In terms of Σ n,
Beyond syntactic requirements of C/C++, implicit concatenation is a form of syntactic sugar, making it simpler to split string literals across several lines, avoiding the need for line continuation (via backslashes) and allowing one to add comments to parts of strings. For example, in Python, one can comment a regular expression in this way: [21]