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Perl Compatible Regular Expressions - PCRE

Perl Compatible Regular Expressions (PCRE) are a type of regular expression syntax and engine that follows the powerful and flexible style of the Perl programming language. They offer advanced features that go beyond the basic regular expressions found in many older systems.


Why "Perl Compatible"?

Perl was one of the first languages to introduce highly expressive regular expressions. The PCRE library was created to bring those capabilities to other programming languages and tools, including:

  • PHP

  • Python (similar via the re module)

  • JavaScript (with slight differences)

  • pcregrep (a grep version supporting PCRE)

  • Editors like VS Code, Sublime Text, etc.


Key Features of PCRE:

Lookahead & Lookbehind:

  • (?=...) – positive lookahead

  • (?!...) – negative lookahead

  • (?<=...) – positive lookbehind

  • (?<!...) – negative lookbehind

Non-greedy quantifiers:

  • *?, +?, ??, {m,n}?

Named capturing groups:

  • (?P<name>...) or (?<name>...)

Unicode support:

  • \p{L} matches any kind of letter in any language

Assertions and anchors:

  • \b, \B, \A, \Z, \z

Inline modifiers:

  • (?i) for case-insensitive

  • (?m) for multiline matching, etc.

(?<=\buser\s)\w+

This expression matches any word that follows "user " using a lookbehind assertion.


Summary:

PCRE are like the "advanced edition" of regular expressions — highly powerful, widely used, and very flexible. If you're working in an environment that supports PCRE, you can take advantage of rich pattern matching features inspired by Perl.


Regular expressions - Regex

Regular expressions, often abbreviated as "Regex," are sequences of characters that define a search pattern. They are primarily used in text processing to find, extract, or manipulate text patterns. Regular expressions provide a powerful and flexible way to search and manipulate text based on a specific pattern.

With regular expressions, you can, for example:

  1. Search for text patterns: You can search for specific strings that match a defined pattern, such as email addresses, phone numbers, or URLs.

  2. Extract text patterns: You can extract parts of a text that match a specific pattern, such as parsing data from a format.

  3. Replace text patterns: You can replace text patterns in a text with other strings, such as substituting placeholders or removing unwanted characters.

Regular expressions are extremely flexible and allow the use of metacharacters and quantifying expressions to define complex patterns. They are supported in many programming languages and text editors and are a fundamental tool for text manipulation and analysis in software development, data processing, web development, and other fields.

 


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