The subject of regular expressions is quite deep, and it takes an immense amount of practice to get used to the special character syntax. Furthermore, the re module contains a vast set of methods available for performing searches using regular expressions. Upon completing the examples in this section, you should have a much deeper appreciation for how powerful regular expressions can be.
re – Regular Expressions
Purpose: Searching within and changing text using formal patterns.
Regular expressions are text matching patterns described with a formal syntax. The patterns are interpreted as a set of instructions, which are then executed with a string as input to produce a matching subset or modified version of the original. The term "regular expressions" is frequently shortened to "regex" or "regexp" in conversation. Expressions can include literal text matching, repetition, pattern composition, branching, and other sophisticated rules. A large number of parsing problems are easier to solve with a regular expression than by creating a special-purpose lexer and parser.
Regular expressions are typically used in applications that involve a lot of text processing. For example, they are commonly used as search patterns in text editing programs used by developers, including vi, emacs, and modern IDEs. They are also an integral part of Unix command-line utilities such as sed, grep, and awk. Many programming languages include support for regular expressions in the language syntax (Perl, Ruby, Awk, and Tcl). Other languages, such as C, C++, and Python, support regular expressions through extension libraries.
Multiple open-source implementations of regular expressions exist, each sharing a common core syntax but with different extensions or modifications to their advanced features. The syntax used in Python's re module is based on the syntax used for regular expressions in Perl, with a few Python-specific enhancements.
Source: Doug Hellmann, https://pymotw.com/3/re/index.html
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