Regular Expression

In computing, a regular expression is a specific pattern that provides concise and flexible means to "match" (specify and recognize) strings of text, such as particular characters, words, or patterns of characters. Common abbreviations for "regular expression" include regex and regexp.

Basic Concepts

A regular expression, often called a pattern, is an expression that specifies a set of strings. To specify such sets of strings, rules are often more concise than lists of a set's members. For example, the set containing the three strings "Handel", "Händel", and "Haendel" can be specified by the pattern H(ä|ae?)ndel (or alternatively, it is said that the pattern matches each of the three strings). In most formalisms, if there exists at least one regex that matches a particular set then there exist an infinite number of such expressions. 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".


A quantifier after a token (such as a character) or group specifies how often that 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 cross).

? The question mark indicates there is zero or one of the preceding element. For example, colou?r matches both "color" and "colour".
* The asterisk indicates there is zero or more of the preceding element. For example, ab*c matches "ac", "abc", "abbc", "abbbc", and so on.
+ The plus sign indicates there is one or more of the preceding element. For example, ab+c matches "abc", "abbc", "abbbc", and so on, but not "ac".


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".

Formal language theory

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

Formal Definition

Regular expressions consist of constants and operator symbols that denote sets of strings and operations over these sets, respectively. The following definition is standard, and found as such in most textbooks on formal language theory. Given a finite alphabet Σ, the following constants are defined as regular expressions:

  • (empty set) ∅ denoting the set ∅.
  • (empty string) ε denoting the set containing only the "empty" string, which has no characters at all.
  • (literal charactera in Σ denoting the set containing only the character a.

Given regular expressions R and S, the following operations over them are defined to produce regular expressions:

  • (concatenationRS denoting the set { αβ | α in set described by expression R and β in set described by S }. For example {"ab", "c"}{"d", "ef"} = {"abd", "abef", "cd", "cef"}.
  • (alternationR | S denoting the set union of sets described by R and S. For example, if R describes {"ab", "c"} and S describes {"ab", "d", "ef"}, expression R | Sdescribes {"ab", "c", "d", "ef"}.
  • (Kleene starR* denoting the smallest superset of set described by R that contains ε and is closed under string concatenation. This is the set of all strings that can be made by concatenating any finite number (including zero) of strings from set described by R. For example, {"0","1"}* is the set of all finite binary strings(including the empty string), and {"ab", "c"}* = {ε, "ab", "c", "abab", "abc", "cab", "cc", "ababab", "abcab", ... }.

To avoid parentheses it is assumed that the Kleene star has the highest priority, then concatenation and then alternation. If there is no ambiguity then parentheses may be omitted. For example, (ab)c can be written as abc, and a|(b(c*)) can be written as a|bc*. Many textbooks use the symbols ∪, +, or ∨ for alternation instead of the vertical bar.


  • a|b* denotes {ε, "a", "b", "bb", "bbb", ...}
  • (a|b)* denotes the set of all strings with no symbols other than "a" and "b", including the empty string: {ε, "a", "b", "aa", "ab", "ba", "bb", "aaa", ...}
  • ab*(c|ε) denotes the set of strings starting with "a", then zero or more "b"s and finally optionally a "c": {"a", "ac", "ab", "abc", "abb", "abbc", ...}

Expressive power and compactness

The formal definition of regular expressions is purposely parsimonious and avoids defining the redundant quantifiers ? and +, which can be expressed as follows: a+ = aa*, and a? = (a|ε). Sometimes the complement operator is added, to give a generalized regular expression; here Rc matches all strings over Σ* that do not match R. In principle, the complement operator is redundant, as it can always be circumscribed by using the other operators. However, the process for computing such a representation is complex, and the result may require expressions of a size that is double exponentially larger.

Regular expressions in this sense can express the regular languages, exactly the class of languages accepted by deterministic finite automata. There is, however, a significant difference in compactness. Some classes of regular languages can only be described by deterministic finite automata whose size grows exponentially in the size of the shortest equivalent regular expressions. The standard example here is the languages Lk consisting of all strings over the alphabet {a,b} whose kth-from-last letter equals a. On one hand, a regular expression describing L4 is given by (a | b)*a( a | b )( a | b )( a | b ).

On the other hand, it is known that every deterministic finite automaton accepting the language Lk must have at least 2k states. Luckily, there is a simple mapping from regular expressions to the more general nondeterministic finite automata (NFAs) that does not lead to such a blowup in size; for this reason NFAs are often used as alternative representations of regular languages. NFAs are a simple variation of the type-3 grammars of the Chomsky hierarchy.

Finally, it is worth noting that many real-world "regular expression" engines implement features that cannot be described by the regular expressions in the sense of formal language theory; see below for more on this.

Deciding equivalence of regular expressions

As seen in many of the examples above, there is more than one way to construct a regular expression to achieve the same results.

It is possible to write an algorithm which for two given regular expressions decides whether the described languages are essentially equal, reduces each expression to a minimal deterministic finite state machine, and determines whether they are isomorphic (equivalent).

The redundancy can be eliminated by using Kleene star and set union to find an interesting subset of regular expressions that is still fully expressive, but perhaps their use can be restricted. This is a surprisingly difficult problem. As simple as the regular expressions are, there is no method to systematically rewrite them to some normal form. The lack of axiom in the past led to the star height problem. In 1991, Dexter Kozen axiomatized regular expressions with Kleene algebra.



字符 描述
^ 匹配输入字符串的开始位置。如果设置了RegExp对象的Multiline属性,^也匹配“n”或“r”之后的位置。
$ 匹配输入字符串的结束位置。如果设置了RegExp对象的Multiline属性,$也匹配“n”或“r”之前的位置。
* 匹配前面的子表达式零次或多次。例如,zo*能匹配“z”以及“zoo”。*等价于{0,}。
+ 匹配前面的子表达式一次或多次。例如,“zo+”能匹配“zo”以及“zoo”,但不能匹配“z”。+等价于{1,}。
? 匹配前面的子表达式零次或一次。例如,“do(es)?”可以匹配“does”或“does”中的“do”。?等价于{0,1}。
{n} n是一个非负整数。匹配确定的n次。例如,“o{2}”不能匹配“Bob”中的“o”,但是能匹配“food”中的两个o。
{n,} n是一个非负整数。至少匹配n次。例如,“o{2,}”不能匹配“Bob”中的“o”,但能匹配“foooood”中的所有o。“o{1,}”等价于“o+”。“o{0,}”则等价于“o*”。
{n,m} m和n均为非负整数,其中n<=m。最少匹配n次且最多匹配m次。例如,“o{1,3}”将匹配“fooooood”中的前三个o。“o{0,1}”等价于“o?”。请注意在逗号和两个数之间不能有空格。
? 当该字符紧跟在任何一个其他限制符(*,+,?,{n},{n,},{n,m})后面时,匹配模式是非贪婪的。非贪婪模式尽可能少的匹配所搜索的字符串,而默认的贪婪模式则尽可能多的匹配所搜索的字符串。例如,对于字符串“oooo”,“o+?”将匹配单个“o”,而“o+”将匹配所有“o”。
. 匹配除“n”之外的任何单个字符。要匹配包括“n”在内的任何字符,请使用像“(.|n)”的模式。
(pattern) 匹配pattern并获取这一匹配。所获取的匹配可以从产生的Matches集合得到,在VBScript中使用SubMatches集合,在JScript中则使用$0…$9属性。要匹配圆括号字符,请使用“(”或“)”。
(?:pattern) 匹配pattern但不获取匹配结果,也就是说这是一个非获取匹配,不进行存储供以后使用。这在使用或字符“(|)”来组合一个模式的各个部分是很有用。例如“industr(?:y|ies)”就是一个比“industry|industries”更简略的表达式。
(?=pattern) 正向肯定预查,在任何匹配pattern的字符串开始处匹配查找字符串。这是一个非获取匹配,也就是说,该匹配不需要获取供以后使用。例如,“Windows(?=95|98|NT|2000)”能匹配“Windows2000”中的“Windows”,但不能匹配“Windows3.1”中的“Windows”。预查不消耗字符,也就是说,在一个匹配发生后,在最后一次匹配之后立即开始下一次匹配的搜索,而不是从包含预查的字符之后开始。
(?!pattern) 正向否定预查,在任何不匹配pattern的字符串开始处匹配查找字符串。这是一个非获取匹配,也就是说,该匹配不需要获取供以后使用。例如“Windows(?!95|98|NT|2000)”能匹配“Windows3.1”中的“Windows”,但不能匹配“Windows2000”中的“Windows”。预查不消耗字符,也就是说,在一个匹配发生后,在最后一次匹配之后立即开始下一次匹配的搜索,而不是从包含预查的字符之后开始
(?<=pattern) 反向肯定预查,与正向肯定预查类似,只是方向相反。例如,“(?<=95|98|NT|2000)Windows”能匹配“2000Windows”中的“Windows”,但不能匹配“3.1Windows”中的“Windows”。
(?<!pattern) 反向否定预查,与正向否定预查类似,只是方向相反。例如“(?<!95|98|NT|2000)Windows”能匹配“3.1Windows”中的“Windows”,但不能匹配“2000Windows”中的“Windows”。
x|y 匹配x或y。例如,“z|food”能匹配“z”或“food”。“(z|f)ood”则匹配“zood”或“food”。
[xyz] 字符集合。匹配所包含的任意一个字符。例如,“[abc]”可以匹配“plain”中的“a”。
[^xyz] 负值字符集合。匹配未包含的任意字符。例如,“[^abc]”可以匹配“plain”中的“p”。
[a-z] 字符范围。匹配指定范围内的任意字符。例如,“[a-z]”可以匹配“a”到“z”范围内的任意小写字母字符。
[^a-z] 负值字符范围。匹配任何不在指定范围内的任意字符。例如,“[^a-z]”可以匹配任何不在“a”到“z”范围内的任意字符。
b 匹配一个单词边界,也就是指单词和空格间的位置。例如,“erb”可以匹配“never”中的“er”,但不能匹配“verb”中的“er”。
B 匹配非单词边界。“erB”能匹配“verb”中的“er”,但不能匹配“never”中的“er”。
cx 匹配由x指明的控制字符。例如,cM匹配一个Control-M或回车符。x的值必须为A-Z或a-z之一。否则,将c视为一个原义的“c”字符。
d 匹配一个数字字符。等价于[0-9]。
D 匹配一个非数字字符。等价于[^0-9]。
f 匹配一个换页符。等价于x0c和cL。
n 匹配一个换行符。等价于x0a和cJ。
r 匹配一个回车符。等价于x0d和cM。
s 匹配任何空白字符,包括空格、制表符、换页符等等。等价于[ fnrtv]。
S 匹配任何非空白字符。等价于[^ fnrtv]。
t 匹配一个制表符。等价于x09和cI。
v 匹配一个垂直制表符。等价于x0b和cK。
w 匹配包括下划线的任何单词字符。等价于“[A-Za-z0-9_]”。
W 匹配任何非单词字符。等价于“[^A-Za-z0-9_]”。
xn 匹配n,其中n为十六进制转义值。十六进制转义值必须为确定的两个数字长。例如,“x41”匹配“A”。“x041”则等价于“x04&1”。正则表达式中可以使用ASCII编码。.
num 匹配num,其中num是一个正整数。对所获取的匹配的引用。例如,“(.)1”匹配两个连续的相同字符。
n 标识一个八进制转义值或一个向后引用。如果n之前至少n个获取的子表达式,则n为向后引用。否则,如果n为八进制数字(0-7),则n为一个八进制转义值。
nm 标识一个八进制转义值或一个向后引用。如果nm之前至少有nm个获得子表达式,则nm为向后引用。如果nm之前至少有n个获取,则n为一个后跟文字m的向后引用。如果前面的条件都不满足,若n和m均为八进制数字(0-7),则nm将匹配八进制转义值nm。
nml 如果n为八进制数字(0-3),且m和l均为八进制数字(0-7),则匹配八进制转义值nml。
un 匹配n,其中n是一个用四个十六进制数字表示的Unicode字符。例如,u00A9匹配版权符号(?0?8)。
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