Regular expression

The match results of the pattern

(?<=\.) {2,}(?=[A-Z])

At least two spaces are matched, but only if they occur directly after a period (.) and before an uppercase letter.

Stephen Cole Kleene, who helped invent the concept

A blacklist on Wikipedia which uses regular expressions to identify bad titles

A regular expression, regex or regexp^[1] (sometimes called a rational expression)^[2][3] is, in theoretical computer science and formal language theory, a sequence of characters that define a search pattern. Usually this pattern is then used by string searching algorithms for "find" or "find and replace" operations on strings, or for input validation.

The concept arose in the 1950s when the American mathematician Stephen Cole Kleene formalized the description of a regular language. The concept came into common use with Unix text-processing utilities. Since the 1980s, different syntaxes for writing regular expressions exist, one being the POSIX standard and another, widely used, being the Perl syntax.

Regular expressions are used in search engines, search and replace dialogs of word processors and text editors, in text processing utilities such as sed and AWK and in lexical analysis. Many programming languages provide regex capabilities, built-in or via libraries.

Patterns

The phrase regular expressions, and consequently, regexes, is often used to mean the specific, standard textual syntax (distinct from the mathematical notation described below) for representing patterns for matching text. Each character in a regular expression (that is, each character in the string describing its pattern) is either a metacharacter, having a special meaning, or a regular character that has a literal meaning. For example, in the regex a., a is a literal character which matches just 'a', while '.' is a meta character that matches every character except a newline. Therefore, this regex matches, for example, 'a ', or 'ax', or 'a0'. Together, metacharacters and literal characters can be used to identify text of a given pattern, or process a number of instances of it. Pattern matches may vary from a precise equality to a very general similarity, as controlled by the metacharacters. For example, . is a very general pattern, [a-z] (match all lower case letters from 'a' to 'z') is less general and a is a precise pattern (matches just 'a'). The metacharacter syntax is designed specifically to represent prescribed targets in a concise and flexible way to direct the automation of text processing of a variety of input data, in a form easy to type using a standard ASCII keyboard.

A very simple case of a regular expression in this syntax is to locate a word spelled two different ways in a text editor, the regular expression seriali[sz]e matches both "serialise" and "serialize". Wildcards also achieve this, but are more limited in what they can pattern, as they have fewer metacharacters and a simple language-base.

The usual context of wildcard characters is in globbing similar names in a list of files, whereas regexes are usually employed in applications that pattern-match text strings in general. For example, the regex ^[ \t]+|[ \t]+$ matches excess whitespace at the beginning or end of a line. An advanced regular expression that matches any numeral is [+-]?(\d+(\.\d+)?|\.\d+)([eE][+-]?\d+)? .

Translating the Kleene star
(s* means 'zero or more of s ')

A regex processor translates a regular expression in the above syntax into an internal representation which can be executed and matched against a string representing the text being searched in. One possible approach is the Thompson's construction algorithm to construct a nondeterministic finite automaton (NFA), which is then made deterministic and the resulting deterministic finite automaton (DFA) is run on the target text string to recognize substrings that match the regular expression. The picture shows the NFA scheme N(s*) obtained from the regular expression s*, where s denotes a simpler regular expression in turn, which has already been recursively translated to the NFA N(s).

History

Regular expressions originated in 1951, when mathematician Stephen Cole Kleene described regular languages using his mathematical notation called regular sets.^[4] These arose in theoretical computer science, in the subfields of automata theory (models of computation) and the description and classification of formal languages. Other early implementations of pattern matching include the SNOBOL language, which did not use regular expressions, but instead its own pattern matching constructs.

Regular expressions entered popular use from 1968 in two uses: pattern matching in a text editor^[5] and lexical analysis in a compiler.^[6] 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.^[5][7][8][9] For speed, Thompson implemented regular expression matching by just-in-time compilation (JIT) to IBM 7094 code on the Compatible Time-Sharing System, an important early example of JIT compilation.^[10] He later added this capability to the Unix editor ed, which eventually led to the popular search tool grep's use of regular expressions ("grep" is a word derived from the command for regular expression searching in the ed editor: g/re/p meaning "Global search for Regular Expression and Print matching lines"^[11]). Around the same time when Thompson developed QED, a group of researchers including Douglas T. Ross implemented a tool based on regular expressions that is used for lexical analysis in compiler design.^[6]

Many variations of these original forms of regular expressions were used in Unix^[9] programs at Bell Labs in the 1970s, including vi, lex, sed, AWK, and expr, and in other programs such as Emacs. Regexes were subsequently adopted by a wide range of programs, with these early forms standardized in the POSIX.2 standard in 1992.

In the 1980s the more complicated regexes arose in Perl, which originally derived from a regex library written by Henry Spencer (1986), who later wrote an implementation of Advanced Regular Expressions for Tcl.^[12] The Tcl library is a hybrid NFA/DFA implementation with improved performance characteristics. Software projects that have adopted Spencer's Tcl regular expression implementation include PostgreSQL.^[13] Perl later expanded on Spencer's original library to add many new features,^[14] but has not yet caught up with Spencer's Advanced Regular Expressions implementation in terms of performance or Unicode handling.^[15][16] Part of the effort in the design of Perl 6 is to improve Perl's regex integration, and to increase their scope and capabilities to allow the definition of parsing expression grammars.^[17] The result is a mini-language called Perl 6 rules, which are used to define Perl 6 grammar as well as provide a tool to programmers in the language. These rules maintain existing features of Perl 5.x regexes, but also allow BNF-style definition of a recursive descent parser via sub-rules.

The use of regexes in structured information standards for document and database modeling started in the 1960s and expanded in the 1980s when industry standards like ISO SGML (precursored by ANSI "GCA 101-1983") consolidated. The kernel of the structure specification language standards consists of regexes. Its use is evident in the DTD element group syntax.

Starting in 1997, Philip Hazel developed PCRE (Perl Compatible Regular Expressions), which attempts to closely mimic Perl's regex functionality and is used by many modern tools including PHP and Apache HTTP Server.

Today regexes are widely supported in programming languages, text processing programs (particular lexers), advanced text editors, and some other programs. Regex support is part of the standard library of many programming languages, including Java and Python, and is built into the syntax of others, including Perl and ECMAScript. Implementations of regex functionality is often called a regex engine, and a number of libraries are available for reuse.

Basic concepts

A regular expression, often called a pattern, is an expression used to specify a set of strings required for a particular purpose. A simple way to specify a finite set of strings is to list its elements or members. However, there are often more concise ways to specify the desired set of strings. For example, the set containing the three strings "Handel", "Händel", and "Haendel" can be specified by the pattern H(ä|ae?)ndel; we say that this pattern matches each of the three strings. In most formalisms, if there exists at least one regular expression that matches a particular set then there exists an infinite number of other regular expression that also match it—the specification is not unique. Most formalisms provide the following operations to construct regular expressions.

Boolean "or"

A vertical bar separates alternatives. For example, gray|grey can match "gray" or "grey".

Grouping

Parentheses are used to define the scope and precedence of the operators (among other uses). For example, gray|grey and gr(a|e)y are equivalent patterns which both describe the set of "gray" or "grey".

Quantification

A quantifier after a token (such as a character) or group specifies how often that a preceding element is allowed to occur. The most common quantifiers are the question mark ?, the asterisk * (derived from the Kleene star), and the plus sign + (Kleene plus).

?	The question mark indicates zero or one occurrences of the preceding element. For example, colou?r matches both "color" and "colour".
*	The asterisk indicates zero or more occurrences of the preceding element. For example, ab*c matches "ac", "abc", "abbc", "abbbc", and so on.
+	The plus sign indicates one or more occurrences of the preceding element. For example, ab+c matches "abc", "abbc", "abbbc", and so on, but not "ac".
{n}[18]	The preceding item is matched exactly n times.
{min,}[18]	The preceding item is matched min or more times.
{min,max}[18]	The preceding item is matched at least min times, but not more than max times.

Wildcard

The wildcard . matches any character. For example, a.b matches any string that contains an "a", then any other character and then a "b", a.*b matches any string that contains an "a" and a "b" at some later point.

These constructions can be combined to form arbitrarily complex expressions, much like one can construct arithmetical expressions from numbers and the operations +, −, ×, and ÷. For example, H(ae?|ä)ndel and H(a|ae|ä)ndel are both valid patterns which match the same strings as the earlier example, H(ä|ae?)ndel.

The precise syntax for regular expressions varies among tools and with context; more detail is given in the Syntax section.

Formal language theory

Regular expressions describe regular languages in formal language theory. They have the same expressive power as regular grammars.

Syntax

A regex pattern matches a target string. The pattern is composed of a sequence of atoms. An atom is a single point within the regex pattern which it tries to match to the target string. The simplest atom is a literal, but grouping parts of the pattern to match an atom will require using ( ) as metacharacters. Metacharacters help form: atoms; quantifiers telling how many atoms (and whether it is a greedy quantifier or not); a logical OR character, which offers a set of alternatives, and a logical NOT character, which negates an atom's existence; and backreferences to refer to previous atoms of a completing pattern of atoms. A match is made, not when all the atoms of the string are matched, but rather when all the pattern atoms in the regex have matched. The idea is to make a small pattern of characters stand for a large number of possible strings, rather than compiling a large list of all the literal possibilities.

Depending on the regex processor there are about fourteen metacharacters, characters that may or may not have their literal character meaning, depending on context, or whether they are "escaped", i.e. preceded by an escape sequence, in this case, the backslash \. Modern and POSIX extended regexes use metacharacters more often than their literal meaning, so to avoid "backslash-osis" or leaning toothpick syndrome it makes sense to have a metacharacter escape to a literal mode; but starting out, it makes more sense to have the four bracketing metacharacters ( ) and { } be primarily literal, and "escape" this usual meaning to become metacharacters. Common standards implement both. The usual metacharacters are {}[]()^$.|*+? and \. The usual characters that become metacharacters when escaped are dswDSW and N.

"Ganymede," he continued, "is the largest moon in the Solar System."

"Ganymede," he continued, "is the largest moon in the Solar System." EOF

"Ganymede," he continued, "is the largest moon in the Solar System."

Patterns for non-regular languages

Many features found in virtually all modern regular expression libraries provide an expressive power that far exceeds the regular languages. For example, many implementations allow grouping subexpressions with parentheses and recalling the value they match in the same expression (backreferences). This means that, among other things, a pattern can match strings of repeated words like "papa" or "WikiWiki", called squares in formal language theory. The pattern for these strings is (.+)\1.

The language of squares is not regular, nor is it context-free, due to the pumping lemma. However, pattern matching with an unbounded number of backreferences, as supported by numerous modern tools, is still context sensitive.^[33]

However, many tools, libraries, and engines that provide such constructions still use the term regular expression for their patterns. This has led to a nomenclature where the term regular expression has different meanings in formal language theory and pattern matching. For this reason, some people have taken to using the term regex, regexp, or simply pattern to describe the latter. Larry Wall, author of the Perl programming language, writes in an essay about the design of Perl 6:

"Regular expressions" […] are only marginally related to real regular expressions. Nevertheless, the term has grown with the capabilities of our pattern matching engines, so I'm not going to try to fight linguistic necessity here. I will, however, generally call them "regexes" (or "regexen", when I'm in an Anglo-Saxon mood).^[17]

Implementations and running times

There are at least three different algorithms that decide whether and how a given regex matches a string.

The oldest and fastest relies on a result in formal language theory that allows every nondeterministic finite automaton (NFA) to be transformed into a deterministic finite automaton (DFA). The DFA can be constructed explicitly and then run on the resulting input string one symbol at a time. Constructing the DFA for a regular expression of size m has the time and memory cost of O(2^m), but it can be run on a string of size n in time O(n).

An alternative approach is to simulate the NFA directly, essentially building each DFA state on demand and then discarding it at the next step. This keeps the DFA implicit and avoids the exponential construction cost, but running cost rises to O(mn). The explicit approach is called the DFA algorithm and the implicit approach the NFA algorithm. Adding caching to the NFA algorithm is often called the "lazy DFA" algorithm, or just the DFA algorithm without making a distinction. These algorithms are fast, but using them for recalling grouped subexpressions, lazy quantification, and similar features is tricky.^[34][35]

The third algorithm is to match the pattern against the input string by backtracking. This algorithm is commonly called NFA, but this terminology can be confusing. Its running time can be exponential, which simple implementations exhibit when matching against expressions like (a|aa)*b that contain both alternation and unbounded quantification and force the algorithm to consider an exponentially increasing number of sub-cases. This behavior can cause a security problem called Regular expression Denial of Service.

Although backtracking implementations only give an exponential guarantee in the worst case, they provide much greater flexibility and expressive power. For example, any implementation which allows the use of backreferences, or implements the various extensions introduced by Perl, must include some kind of backtracking. Some implementations try to provide the best of both algorithms by first running a fast DFA algorithm, and revert to a potentially slower backtracking algorithm only when a backreference is encountered during the match.

Unicode

In theoretical terms, any token set can be matched by regular expressions as long as it is pre-defined. In terms of historical implementations, regexes were originally written to use ASCII characters as their token set though regex libraries have supported numerous other character sets. Many modern regex engines offer at least some support for Unicode. In most respects it makes no difference what the character set is, but some issues do arise when extending regexes to support Unicode.

• Supported encoding. Some regex libraries expect to work on some particular encoding instead of on abstract Unicode characters. Many of these require the UTF-8 encoding, while others might expect UTF-16, or UTF-32. In contrast, Perl and Java are agnostic on encodings, instead operating on decoded characters internally.
• Supported Unicode range. Many regex engines support only the Basic Multilingual Plane, that is, the characters which can be encoded with only 16 bits. Currently (as of 2016) only a few regex engines (e.g., Perl's and Java's) can handle the full 21-bit Unicode range.
• Extending ASCII-oriented constructs to Unicode. For example, in ASCII-based implementations, character ranges of the form [x-y] are valid wherever x and y have code points in the range [0x00,0x7F] and codepoint(x) ≤ codepoint(y). The natural extension of such character ranges to Unicode would simply change the requirement that the endpoints lie in [0x00,0x7F] to the requirement that they lie in [0x0000,0x10FFFF]. However, in practice this is often not the case. Some implementations, such as that of gawk, do not allow character ranges to cross Unicode blocks. A range like [0x61,0x7F] is valid since both endpoints fall within the Basic Latin block, as is [0x0530,0x0560] since both endpoints fall within the Armenian block, but a range like [0x0061,0x0532] is invalid since it includes multiple Unicode blocks. Other engines, such as that of the Vim editor, allow block-crossing but the character values must not be more than 256 apart.^[36]
• Case insensitivity. Some case-insensitivity flags affect only the ASCII characters. Other flags affect all characters. Some engines have two different flags, one for ASCII, the other for Unicode. Exactly which characters belong to the POSIX classes also varies.
• Cousins of case insensitivity. As ASCII has case distinction, case insensitivity became a logical feature in text searching. Unicode introduced alphabetic scripts without case like Devanagari. For these, case sensitivity is not applicable. For scripts like Chinese, another distinction seems logical: between traditional and simplified. In Arabic scripts, insensitivity to initial, medial, final, and isolated position may be desired. In Japanese, insensitivity between hiragana and katakana is sometimes useful.
• Normalization. Unicode has combining characters. Like old typewriters, plain letters can be followed by one or more non-spacing symbols (usually diacritics like accent marks) to form a single printing character, but also provides precomposed characters, i.e. characters that already include one or more combining characters. A sequence of a character + combining character should be matched with the identical single precomposed character. The process of standardizing sequences of characters + combining characters is called normalization.
• New control codes. Unicode introduced amongst others, byte order marks and text direction markers. These codes might have to be dealt with in a special way.
• Introduction of character classes for Unicode blocks, scripts, and numerous other character properties. Block properties are much less useful than script properties, because a block can have code points from several different scripts, and a script can have code points from several different blocks.^[37] In Perl and the java.util.regex library, properties of the form \p{InX} or \p{Block=X} match characters in block X and \P{InX} or \P{Block=X} matches code points not in that block. Similarly, \p{Armenian}, \p{IsArmenian}, or \p{Script=Armenian} matches any character in the Armenian script. In general, \p{X} matches any character with either the binary property X or the general category X. For example, \p{Lu}, \p{Uppercase_Letter}, or \p{GC=Lu} matches any uppercase letter. Binary properties that are not general categories include \p{White_Space}, \p{Alphabetic}, \p{Math}, and \p{Dash}. Examples of non-binary properties are \p{Bidi_Class=Right_to_Left}, \p{Word_Break=A_Letter}, and \p{Numeric_Value=10}.

Uses

Regexes are useful in a wide variety of text processing tasks, and more generally string processing, where the data need not be textual. Common applications include data validation, data scraping (especially web scraping), data wrangling, simple parsing, the production of syntax highlighting systems, and many other tasks.

While regexes would be useful on Internet search engines, processing them across the entire database could consume excessive computer resources depending on the complexity and design of the regex. Although in many cases system administrators can run regex-based queries internally, most search engines do not offer regex support to the public. Notable exceptions: Google Code Search, Exalead. Google Code Search has been shut down as of January 2012.^[38] It used a trigram index to speed queries.^[39]

Examples

The specific syntax rules vary depending on the specific implementation, programming language, or library in use. Additionally, the functionality of regex implementations can vary between versions.

Because regexes can be difficult to both explain and understand without examples, interactive web sites for testing regexes are a useful resource for learning regexes by experimentation. This section provides a basic description of some of the properties of regexes by way of illustration.

The following conventions are used in the examples.^[40]

metacharacter(s) ;; the metacharacters column specifies the regex syntax being demonstrated
=~ m//           ;; indicates a regex match operation in Perl
=~ s///          ;; indicates a regex substitution operation in Perl

Also worth noting is that these regexes are all Perl-like syntax. Standard POSIX regular expressions are different.

Unless otherwise indicated, the following examples conform to the Perl programming language, release 5.8.8, January 31, 2006. This means that other implementations may lack support for some parts of the syntax shown here (e.g. basic vs. extended regex, \( \) vs. (), or lack of \d instead of POSIX [:digit:]).

The syntax and conventions used in these examples coincide with that of other programming environments as well.^[41]

$string1 = "Hello World\n";
if ($string1 =~ m/...../) {
  print "$string1 has length >= 5.\n";
}

Hello World
 has length >= 5.

$string1 = "Hello World\n";
if ($string1 =~ m/(H..).(o..)/) {
  print "We matched '$1' and '$2'.\n";
}

We matched 'Hel' and 'o W'.

$string1 = "Hello World\n";
if ($string1 =~ m/l+/) {
  print "There are one or more consecutive letter \"l\"'s in $string1.\n";
}

There are one or more consecutive letter "l"'s in Hello World.

$string1 = "Hello World\n";
if ($string1 =~ m/H.?e/) {
  print "There is an 'H' and a 'e' separated by ";
  print "0-1 characters (e.g., He Hue Hee).\n";
}

There is an 'H' and a 'e' separated by 0-1 characters (e.g., He Hue Hee).

$string1 = "Hello World\n";
if ($string1 =~ m/(l.+?o)/) {
  print "The non-greedy match with 'l' followed by one or\n";
  print "more characters is 'llo' rather than 'llo Wo'.\n";
}

The non-greedy match with 'l' followed by one or
more characters is 'llo' rather than 'llo Wo'.

$string1 = "Hello World\n";
if ($string1 =~ m/el*o/) {
  print "There is an 'e' followed by zero to many ";
  print "'l' followed by 'o' (e.g., eo, elo, ello, elllo).\n";
}

There is an 'e' followed by zero to many 'l' followed by 'o' (e.g., eo, elo, ello, elllo).

$string1 = "Hello World\n";
if ($string1 =~ m/l{1,2}/) {
  print "There exists a substring with at least 1 ";
  print "and at most 2 l's in $string1\n";
}

There exists a substring with at least 1 and at most 2 l's in Hello World

$string1 = "Hello World\n";
if ($string1 =~ m/[aeiou]+/) {
  print "$string1 contains one or more vowels.\n";
}

Hello World
 contains one or more vowels.

$string1 = "Hello World\n";
if ($string1 =~ m/(Hello|Hi|Pogo)/) {
  print "$string1 contains at least one of Hello, Hi, or Pogo.";
}

Hello World
 contains at least one of Hello, Hi, or Pogo.

$string1 = "Hello World\n";
if ($string1 =~ m/llo\b/) {
  print "There is a word that ends with 'llo'.\n";
}

There is a word that ends with 'llo'.

$string1 = "Hello World\n";
if ($string1 =~ m/\w/) {
  print "There is at least one alphanumeric ";
  print "character in $string1 (A-Z, a-z, 0-9, _).\n";
}

There is at least one alphanumeric character in Hello World
 (A-Z, a-z, 0-9, _).

$string1 = "Hello World\n";
if ($string1 =~ m/\W/) {
  print "The space between Hello and ";
  print "World is not alphanumeric.\n";
}

The space between Hello and World is not alphanumeric.

$string1 = "Hello World\n";
if ($string1 =~ m/\s.*\s/) {
  print "In $string1 there are TWO whitespace characters, which may";
  print " be separated by other characters.\n";
}

In Hello World
 there are TWO whitespace characters, which may be separated by other characters.

$string1 = "Hello World\n";
if ($string1 =~ m/\S.*\S/) {
  print "In $string1 there are TWO non-whitespace characters, which";
  print " may be separated by other characters.\n";
}

In Hello World
 there are TWO non-whitespace characters, which may be separated by other characters.

$string1 = "99 bottles of beer on the wall.";
if ($string1 =~ m/(\d+)/) {
  print "$1 is the first number in '$string1'\n";
}

99 is the first number in '99 bottles of beer on the wall.'

$string1 = "Hello World\n";
if ($string1 =~ m/\D/) {
  print "There is at least one character in $string1";
  print " that is not a digit.\n";
}

There is at least one character in Hello World
 that is not a digit.

$string1 = "Hello World\n";
if ($string1 =~ m/^He/) {
  print "$string1 starts with the characters 'He'.\n";
}

Hello World
 starts with the characters 'He'.

$string1 = "Hello World\n";
if ($string1 =~ m/rld$/) {
  print "$string1 is a line or string ";
  print "that ends with 'rld'.\n";
}

Hello World
 is a line or string that ends with 'rld'.

$string1 = "Hello\nWorld\n";
if ($string1 =~ m/\AH/) {
  print "$string1 is a string ";
  print "that starts with 'H'.\n";
}

Hello
World
 is a string that starts with 'H'.

$string1 = "Hello\nWorld\n";
if ($string1 =~ m/d\n\z/) {
  print "$string1 is a string ";
  print "that ends with 'd\\n'.\n";
}

Hello
World
 is a string that ends with 'd\n'.

$string1 = "Hello World\n";
if ($string1 =~ m/[^abc]/) {
 print "$string1 contains a character other than ";
 print "a, b, and c.\n";
}

Hello World
 contains a character other than a, b, and c.

Induction

Regular expressions can often be created ("induced" or "learned") based on a set of example strings. This is known as the induction of regular languages, and is part of the general problem of grammar induction in computational learning theory. Formally, given examples of strings in a regular language, and perhaps also given examples of strings not in that regular language, it is possible to induce a grammar for the language, i.e., a regular expression that generates that language. Not all regular languages can be induced in this way (see language identification in the limit), but many can. For example, the set of examples {1, 10, 100}, and negative set (of counterexamples) {11, 1001, 101, 0} can be used to induce the regular expression 1⋅0* (1 followed by zero or more 0s).

See also

• Comparison of regular expression engines
• Extended Backus–Naur Form
• Regular tree grammar
• Matching wildcards
• Thompson's construction algorithm – converts a regular expression into an equivalent nondeterministic finite automaton (NFA)

Notes

References

External links

Wikibooks has a book on the topic of: Regular Expressions

The Wikibook R Programming has a page on the topic of: Text Processing

Look up regular expression in Wiktionary, the free dictionary.

• Regular Expressions at Curlie (based on DMOZ)
• ISO/IEC 9945-2:1993 Information technology – Portable Operating System Interface (POSIX) – Part 2: Shell and Utilities
• ISO/IEC 9945-2:2002 Information technology – Portable Operating System Interface (POSIX) – Part 2: System Interfaces
• ISO/IEC 9945-2:2003 Information technology – Portable Operating System Interface (POSIX) – Part 2: System Interfaces
• ISO/IEC/IEEE 9945:2009 Information technology – Portable Operating System Interface (POSIX®) Base Specifications, Issue 7
• Regular Expression, IEEE Std 1003.1-2017, Open Group