6.2. `re` — Regular expression operations¶

This module provides regular expression matching operations similar to those found in Perl.

Both patterns and strings to be searched can be Unicode strings as well as 8-bit strings. However, Unicode strings and 8-bit strings cannot be mixed: that is, you cannot match an Unicode string with a byte pattern or vice-versa; similarly, when asking for a substitution, the replacement string must be of the same type as both the pattern and the search string.

Regular expressions use the backslash character ('\') to indicate special forms or to allow special characters to be used without invoking their special meaning. This collides with Python’s usage of the same character for the same purpose in string literals; for example, to match a literal backslash, one might have to write '\\\\' as the pattern string, because the regular expression must be \\, and each backslash must be expressed as \\ inside a regular Python string literal.

The solution is to use Python’s raw string notation for regular expression patterns; backslashes are not handled in any special way in a string literal prefixed with 'r'. So r"\n" is a two-character string containing '\' and 'n', while "\n" is a one-character string containing a newline. Usually patterns will be expressed in Python code using this raw string notation.

It is important to note that most regular expression operations are available as module-level functions and methods on compiled regular expressions. The functions are shortcuts that don’t require you to compile a regex object first, but miss some fine-tuning parameters.

6.2.1. Regular Expression Syntax¶

A regular expression (or RE) specifies a set of strings that matches it; the functions in this module let you check if a particular string matches a given regular expression (or if a given regular expression matches a particular string, which comes down to the same thing).

Regular expressions can be concatenated to form new regular expressions; if A and B are both regular expressions, then AB is also a regular expression. In general, if a string p matches A and another string q matches B, the string pq will match AB. This holds unless A or B contain low precedence operations; boundary conditions between A and B; or have numbered group references. Thus, complex expressions can easily be constructed from simpler primitive expressions like the ones described here. For details of the theory and implementation of regular expressions, consult the Friedl book referenced above, or almost any textbook about compiler construction.

A brief explanation of the format of regular expressions follows. For further information and a gentler presentation, consult the Regular Expression HOWTO.

Regular expressions can contain both special and ordinary characters. Most ordinary characters, like 'A', 'a', or '0', are the simplest regular expressions; they simply match themselves. You can concatenate ordinary characters, so last matches the string 'last'. (In the rest of this section, we’ll write RE’s in this special style, usually without quotes, and strings to be matched 'in single quotes'.)

Some characters, like '|' or '(', are special. Special characters either stand for classes of ordinary characters, or affect how the regular expressions around them are interpreted. Regular expression pattern strings may not contain null bytes, but can specify the null byte using a \number notation such as '\x00'.

The special characters are:

'.'

(Dot.) In the default mode, this matches any character except a newline. If the DOTALL flag has been specified, this matches any character including a newline.

'^'

(Caret.) Matches the start of the string, and in MULTILINE mode also matches immediately after each newline.

'$'

Matches the end of the string or just before the newline at the end of the string, and in MULTILINE mode also matches before a newline. foo matches both ‘foo’ and ‘foobar’, while the regular expression foo$ matches only ‘foo’. More interestingly, searching for foo.$ in 'foo1\nfoo2\n' matches ‘foo2’ normally, but ‘foo1’ in MULTILINE mode; searching for a single $ in 'foo\n' will find two (empty) matches: one just before the newline, and one at the end of the string.

'*'

Causes the resulting RE to match 0 or more repetitions of the preceding RE, as many repetitions as are possible. ab* will match ‘a’, ‘ab’, or ‘a’ followed by any number of ‘b’s.

'+'

Causes the resulting RE to match 1 or more repetitions of the preceding RE. ab+ will match ‘a’ followed by any non-zero number of ‘b’s; it will not match just ‘a’.

'?'

Causes the resulting RE to match 0 or 1 repetitions of the preceding RE. ab? will match either ‘a’ or ‘ab’.

*?, +?, ??

The '*', '+', and '?' qualifiers are all greedy; they match as much text as possible. Sometimes this behaviour isn’t desired; if the RE <.*> is matched against '<H1>title</H1>', it will match the entire string, and not just '<H1>'. Adding '?' after the qualifier makes it perform the match in non-greedy or minimal fashion; as few characters as possible will be matched. Using .*? in the previous expression will match only '<H1>'.

{m}

Specifies that exactly m copies of the previous RE should be matched; fewer matches cause the entire RE not to match. For example, a{6} will match exactly six 'a' characters, but not five.

{m,n}

Causes the resulting RE to match from m to n repetitions of the preceding RE, attempting to match as many repetitions as possible. For example, a{3,5} will match from 3 to 5 'a' characters. Omitting m specifies a lower bound of zero, and omitting n specifies an infinite upper bound. As an example, a{4,}b will match aaaab or a thousand 'a' characters followed by a b, but not aaab. The comma may not be omitted or the modifier would be confused with the previously described form.

{m,n}?

Causes the resulting RE to match from m to n repetitions of the preceding RE, attempting to match as few repetitions as possible. This is the non-greedy version of the previous qualifier. For example, on the 6-character string 'aaaaaa', a{3,5} will match 5 'a' characters, while a{3,5}? will only match 3 characters.

'\'

Either escapes special characters (permitting you to match characters like '*', '?', and so forth), or signals a special sequence; special sequences are discussed below.

If you’re not using a raw string to express the pattern, remember that Python also uses the backslash as an escape sequence in string literals; if the escape sequence isn’t recognized by Python’s parser, the backslash and subsequent character are included in the resulting string. However, if Python would recognize the resulting sequence, the backslash should be repeated twice. This is complicated and hard to understand, so it’s highly recommended that you use raw strings for all but the simplest expressions.

[]

Used to indicate a set of characters. In a set:

Characters can be listed individually, e.g. [amk] will match 'a', 'm', or 'k'.
Ranges of characters can be indicated by giving two characters and separating them by a '-', for example [a-z] will match any lowercase ASCII letter, [0-5][0-9] will match all the two-digits numbers from 00 to 59, and [0-9A-Fa-f] will match any hexadecimal digit. If - is escaped (e.g. [a\-z]) or if it’s placed as the first or last character (e.g. [a-]), it will match a literal '-'.
Special characters lose their special meaning inside sets. For example, [(+*)] will match any of the literal characters '(', '+', '*', or ')'.
Character classes such as \w or \S (defined below) are also accepted inside a set, although the characters they match depends on whether ASCII or LOCALE mode is in force.
Characters that are not within a range can be matched by complementing the set. If the first character of the set is '^', all the characters that are not in the set will be matched. For example, [^5] will match any character except '5', and [^^] will match any character except '^'. ^ has no special meaning if it’s not the first character in the set.
To match a literal ']' inside a set, precede it with a backslash, or place it at the beginning of the set. For example, both [()[\]{}] and []()[{}] will both match a parenthesis.

'|'

A|B, where A and B can be arbitrary REs, creates a regular expression that will match either A or B. An arbitrary number of REs can be separated by the '|' in this way. This can be used inside groups (see below) as well. As the target string is scanned, REs separated by '|' are tried from left to right. When one pattern completely matches, that branch is accepted. This means that once A matches, B will not be tested further, even if it would produce a longer overall match. In other words, the '|' operator is never greedy. To match a literal '|', use \|, or enclose it inside a character class, as in [|].

(...)

Matches whatever regular expression is inside the parentheses, and indicates the start and end of a group; the contents of a group can be retrieved after a match has been performed, and can be matched later in the string with the \number special sequence, described below. To match the literals '(' or ')', use $ or $, or enclose them inside a character class: [(] [)].

(?...)

This is an extension notation (a '?' following a '(' is not meaningful otherwise). The first character after the '?' determines what the meaning and further syntax of the construct is. Extensions usually do not create a new group; (?P<name>...) is the only exception to this rule. Following are the currently supported extensions.

(?aiLmsux)

(One or more letters from the set 'a', 'i', 'L', 'm', 's', 'u', 'x'.) The group matches the empty string; the letters set the corresponding flags: re.A (ASCII-only matching), re.I (ignore case), re.L (locale dependent), re.M (multi-line), re.S (dot matches all), and re.X (verbose), for the entire regular expression. (The flags are described in Module Contents.) This is useful if you wish to include the flags as part of the regular expression, instead of passing a flag argument to the re.compile() function.

Note that the (?x) flag changes how the expression is parsed. It should be used first in the expression string, or after one or more whitespace characters. If there are non-whitespace characters before the flag, the results are undefined.

(?:...)

A non-capturing version of regular parentheses. Matches whatever regular expression is inside the parentheses, but the substring matched by the group cannot be retrieved after performing a match or referenced later in the pattern.

(?P<name>...)

Similar to regular parentheses, but the substring matched by the group is accessible via the symbolic group name name. Group names must be valid Python identifiers, and each group name must be defined only once within a regular expression. A symbolic group is also a numbered group, just as if the group were not named.

Named groups can be referenced in three contexts. If the pattern is (?P<quote>['"]).*?(?P=quote) (i.e. matching a string quoted with either single or double quotes):

Context of reference to group “quote”	Ways to reference it
in the same pattern itself	`(?P=quote)` (as shown) `\1`
when processing match object `m`	`m.group('quote')` `m.end('quote')` (etc.)
in a string passed to the `repl` argument of `re.sub()`	`\g<quote>` `\g<1>` `\1`

(?P=name)

A backreference to a named group; it matches whatever text was matched by the earlier group named name.

(?#...)

A comment; the contents of the parentheses are simply ignored.

(?=...)

Matches if ... matches next, but doesn’t consume any of the string. This is called a lookahead assertion. For example, Isaac (?=Asimov) will match 'Isaac ' only if it’s followed by 'Asimov'.

(?!...)

Matches if ... doesn’t match next. This is a negative lookahead assertion. For example, Isaac (?!Asimov) will match 'Isaac ' only if it’s not followed by 'Asimov'.

(?<=...)

Matches if the current position in the string is preceded by a match for ... that ends at the current position. This is called a positive lookbehind assertion. (?<=abc)def will find a match in abcdef, since the lookbehind will back up 3 characters and check if the contained pattern matches. The contained pattern must only match strings of some fixed length, meaning that abc or a|b are allowed, but a* and a{3,4} are not. Note that patterns which start with positive lookbehind assertions will not match at the beginning of the string being searched; you will most likely want to use the search() function rather than the match() function:

>>> import re
>>> m = re.search('(?<=abc)def', 'abcdef')
>>> m.group(0)
'def'

This example looks for a word following a hyphen:

>>> m = re.search('(?<=-)\w+', 'spam-egg')
>>> m.group(0)
'egg'

Changed in version 3.5: Added support for group references of fixed length.

(?<!...)

Matches if the current position in the string is not preceded by a match for .... This is called a negative lookbehind assertion. Similar to positive lookbehind assertions, the contained pattern must only match strings of some fixed length. Patterns which start with negative lookbehind assertions may match at the beginning of the string being searched.

(?(id/name)yes-pattern|no-pattern)

Will try to match with yes-pattern if the group with given id or name exists, and with no-pattern if it doesn’t. no-pattern is optional and can be omitted. For example, (<)?(\w+@\w+(?:\.\w+)+)(?(1)>|$) is a poor email matching pattern, which will match with '<user@host.com>' as well as 'user@host.com', but not with '<user@host.com' nor 'user@host.com>'.

The special sequences consist of '\' and a character from the list below. If the ordinary character is not on the list, then the resulting RE will match the second character. For example, \$ matches the character '$'.

\number

Matches the contents of the group of the same number. Groups are numbered starting from 1. For example, (.+) \1 matches 'the the' or '55 55', but not 'thethe' (note the space after the group). This special sequence can only be used to match one of the first 99 groups. If the first digit of number is 0, or number is 3 octal digits long, it will not be interpreted as a group match, but as the character with octal value number. Inside the '[' and ']' of a character class, all numeric escapes are treated as characters.

\A

Matches only at the start of the string.

\b

Matches the empty string, but only at the beginning or end of a word. A word is defined as a sequence of Unicode alphanumeric or underscore characters, so the end of a word is indicated by whitespace or a non-alphanumeric, non-underscore Unicode character. Note that formally, \b is defined as the boundary between a \w and a \W character (or vice versa), or between \w and the beginning/end of the string. This means that r'\bfoo\b' matches 'foo', 'foo.', '(foo)', 'bar foo baz' but not 'foobar' or 'foo3'.

By default Unicode alphanumerics are the ones used, but this can be changed by using the ASCII flag. Inside a character range, \b represents the backspace character, for compatibility with Python’s string literals.

\B

Matches the empty string, but only when it is not at the beginning or end of a word. This means that r'py\B' matches 'python', 'py3', 'py2', but not 'py', 'py.', or 'py!'. \B is just the opposite of \b, so word characters are Unicode alphanumerics or the underscore, although this can be changed by using the ASCII flag.

\d

For Unicode (str) patterns:: Matches any Unicode decimal digit (that is, any character in Unicode character category [Nd]). This includes [0-9], and also many other digit characters. If the ASCII flag is used only [0-9] is matched (but the flag affects the entire regular expression, so in such cases using an explicit [0-9] may be a better choice).
For 8-bit (bytes) patterns:: Matches any decimal digit; this is equivalent to [0-9].

\D

Matches any character which is not a Unicode decimal digit. This is the opposite of \d. If the ASCII flag is used this becomes the equivalent of [^0-9] (but the flag affects the entire regular expression, so in such cases using an explicit [^0-9] may be a better choice).

\s

For Unicode (str) patterns:: Matches Unicode whitespace characters (which includes [ \t\n\r\f\v], and also many other characters, for example the non-breaking spaces mandated by typography rules in many languages). If the ASCII flag is used, only [ \t\n\r\f\v] is matched (but the flag affects the entire regular expression, so in such cases using an explicit [ \t\n\r\f\v] may be a better choice).
For 8-bit (bytes) patterns:: Matches characters considered whitespace in the ASCII character set; this is equivalent to [ \t\n\r\f\v].

\S

Matches any character which is not a Unicode whitespace character. This is the opposite of \s. If the ASCII flag is used this becomes the equivalent of [^ \t\n\r\f\v] (but the flag affects the entire regular expression, so in such cases using an explicit [^ \t\n\r\f\v] may be a better choice).

\w

For Unicode (str) patterns:: Matches Unicode word characters; this includes most characters that can be part of a word in any language, as well as numbers and the underscore. If the ASCII flag is used, only [a-zA-Z0-9_] is matched (but the flag affects the entire regular expression, so in such cases using an explicit [a-zA-Z0-9_] may be a better choice).
For 8-bit (bytes) patterns:: Matches characters considered alphanumeric in the ASCII character set; this is equivalent to [a-zA-Z0-9_].

\W

Matches any character which is not a Unicode word character. This is the opposite of \w. If the ASCII flag is used this becomes the equivalent of [^a-zA-Z0-9_] (but the flag affects the entire regular expression, so in such cases using an explicit [^a-zA-Z0-9_] may be a better choice).

\Z

Matches only at the end of the string.

Most of the standard escapes supported by Python string literals are also accepted by the regular expression parser:

\a      \b      \f      \n
\r      \t      \u      \U
\v      \x      \\

(Note that \b is used to represent word boundaries, and means “backspace” only inside character classes.)

'\u' and '\U' escape sequences are only recognized in Unicode patterns. In bytes patterns they are not treated specially.

Octal escapes are included in a limited form. If the first digit is a 0, or if there are three octal digits, it is considered an octal escape. Otherwise, it is a group reference. As for string literals, octal escapes are always at most three digits in length.

Changed in version 3.3: The '\u' and '\U' escape sequences have been added.

Deprecated since version 3.5, will be removed in version 3.6: Unknown escapes consist of '\' and ASCII letter now raise a deprecation warning and will be forbidden in Python 3.6.

6.2.2. Module Contents¶

The module defines several functions, constants, and an exception. Some of the functions are simplified versions of the full featured methods for compiled regular expressions. Most non-trivial applications always use the compiled form.

re.compile(pattern, flags=0)¶

Compile a regular expression pattern into a regular expression object, which can be used for matching using its match() and search() methods, described below.

The expression’s behaviour can be modified by specifying a flags value. Values can be any of the following variables, combined using bitwise OR (the | operator).

The sequence

prog = re.compile(pattern)
result = prog.match(string)

is equivalent to

result = re.match(pattern, string)

but using re.compile() and saving the resulting regular expression object for reuse is more efficient when the expression will be used several times in a single program.

Note

The compiled versions of the most recent patterns passed to re.compile() and the module-level matching functions are cached, so programs that use only a few regular expressions at a time needn’t worry about compiling regular expressions.

re.A¶

re.ASCII¶

Make \w, \W, \b, \B, \d, \D, \s and \S perform ASCII-only matching instead of full Unicode matching. This is only meaningful for Unicode patterns, and is ignored for byte patterns.

Note that for backward compatibility, the re.U flag still exists (as well as its synonym re.UNICODE and its embedded counterpart (?u)), but these are redundant in Python 3 since matches are Unicode by default for strings (and Unicode matching isn’t allowed for bytes).

re.DEBUG¶: Display debug information about compiled expression.

re.I¶
re.IGNORECASE¶: Perform case-insensitive matching; expressions like [A-Z] will match lowercase letters, too. This is not affected by the current locale and works for Unicode characters as expected.

re.L¶
re.LOCALE¶: Make \w, \W, \b, \B, \s and \S dependent on the current locale. The use of this flag is discouraged as the locale mechanism is very unreliable, and it only handles one “culture” at a time anyway; you should use Unicode matching instead, which is the default in Python 3 for Unicode (str) patterns. This flag makes sense only with bytes patterns.

Deprecated since version 3.5, will be removed in version 3.6: Deprecated the use of re.LOCALE with string patterns or re.ASCII.

re.M¶
re.MULTILINE¶: When specified, the pattern character '^' matches at the beginning of the string and at the beginning of each line (immediately following each newline); and the pattern character '$' matches at the end of the string and at the end of each line (immediately preceding each newline). By default, '^' matches only at the beginning of the string, and '$' only at the end of the string and immediately before the newline (if any) at the end of the string.

re.S¶
re.DOTALL¶: Make the '.' special character match any character at all, including a newline; without this flag, '.' will match anything except a newline.

re.X¶

re.VERBOSE¶

This flag allows you to write regular expressions that look nicer and are more readable by allowing you to visually separate logical sections of the pattern and add comments. Whitespace within the pattern is ignored, except when in a character class or when preceded by an unescaped backslash. When a line contains a # that is not in a character class and is not preceded by an unescaped backslash, all characters from the leftmost such # through the end of the line are ignored.

This means that the two following regular expression objects that match a decimal number are functionally equal:

a = re.compile(r"""\d +  # the integral part
                   \.    # the decimal point
                   \d *  # some fractional digits""", re.X)
b = re.compile(r"\d+\.\d*")

re.search(pattern, string, flags=0)¶: Scan through string looking for the first location where the regular expression pattern produces a match, and return a corresponding match object. Return None if no position in the string matches the pattern; note that this is different from finding a zero-length match at some point in the string.

re.match(pattern, string, flags=0)¶

If zero or more characters at the beginning of string match the regular expression pattern, return a corresponding match object. Return None if the string does not match the pattern; note that this is different from a zero-length match.

Note that even in MULTILINE mode, re.match() will only match at the beginning of the string and not at the beginning of each line.

If you want to locate a match anywhere in string, use search() instead (see also search() vs. match()).

re.fullmatch(pattern, string, flags=0)¶: If the whole string matches the regular expression pattern, return a corresponding match object. Return None if the string does not match the pattern; note that this is different from a zero-length match.

New in version 3.4.

re.split(pattern, string, maxsplit=0, flags=0)¶

Split string by the occurrences of pattern. If capturing parentheses are used in pattern, then the text of all groups in the pattern are also returned as part of the resulting list. If maxsplit is nonzero, at most maxsplit splits occur, and the remainder of the string is returned as the final element of the list.

>>> re.split('\W+', 'Words, words, words.')
['Words', 'words', 'words', '']
>>> re.split('(\W+)', 'Words, words, words.')
['Words', ', ', 'words', ', ', 'words', '.', '']
>>> re.split('\W+', 'Words, words, words.', 1)
['Words', 'words, words.']
>>> re.split('[a-f]+', '0a3B9', flags=re.IGNORECASE)
['0', '3', '9']

If there are capturing groups in the separator and it matches at the start of the string, the result will start with an empty string. The same holds for the end of the string:

>>> re.split('(\W+)', '...words, words...')
['', '...', 'words', ', ', 'words', '...', '']

That way, separator components are always found at the same relative indices within the result list.

Note

split() doesn’t currently split a string on an empty pattern match. For example:

>>> re.split('x*', 'axbc')
['a', 'bc']

Even though 'x*' also matches 0 ‘x’ before ‘a’, between ‘b’ and ‘c’, and after ‘c’, currently these matches are ignored. The correct behavior (i.e. splitting on empty matches too and returning ['', 'a', 'b', 'c', '']) will be implemented in future versions of Python, but since this is a backward incompatible change, a FutureWarning will be raised in the meanwhile.

Patterns that can only match empty strings currently never split the string. Since this doesn’t match the expected behavior, a ValueError will be raised starting from Python 3.5:

>>> re.split("^$", "foo\n\nbar\n", flags=re.M)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  ...
ValueError: split() requires a non-empty pattern match.

Changed in version 3.1: Added the optional flags argument.

Changed in version 3.5: Splitting on a pattern that could match an empty string now raises a warning. Patterns that can only match empty strings are now rejected.

re.findall(pattern, string, flags=0)¶: Return all non-overlapping matches of pattern in string, as a list of strings. The string is scanned left-to-right, and matches are returned in the order found. If one or more groups are present in the pattern, return a list of groups; this will be a list of tuples if the pattern has more than one group. Empty matches are included in the result unless they touch the beginning of another match.

re.finditer(pattern, string, flags=0)¶: Return an iterator yielding match objects over all non-overlapping matches for the RE pattern in string. The string is scanned left-to-right, and matches are returned in the order found. Empty matches are included in the result unless they touch the beginning of another match.

re.sub(pattern, repl, string, count=0, flags=0)¶

Return the string obtained by replacing the leftmost non-overlapping occurrences of pattern in string by the replacement repl. If the pattern isn’t found, string is returned unchanged. repl can be a string or a function; if it is a string, any backslash escapes in it are processed. That is, \n is converted to a single newline character, \r is converted to a carriage return, and so forth. Unknown escapes such as \& are left alone. Backreferences, such as \6, are replaced with the substring matched by group 6 in the pattern. For example:

>>> re.sub(r'def\s+([a-zA-Z_][a-zA-Z_0-9]*)\s*\(\s*\):',
...        r'static PyObject*\npy_\1(void)\n{',
...        'def myfunc():')
'static PyObject*\npy_myfunc(void)\n{'

If repl is a function, it is called for every non-overlapping occurrence of pattern. The function takes a single match object argument, and returns the replacement string. For example:

>>> def dashrepl(matchobj):
...     if matchobj.group(0) == '-': return ' '
...     else: return '-'
>>> re.sub('-{1,2}', dashrepl, 'pro----gram-files')
'pro--gram files'
>>> re.sub(r'\sAND\s', ' & ', 'Baked Beans And Spam', flags=re.IGNORECASE)
'Baked Beans & Spam'

The pattern may be a string or an RE object.

The optional argument count is the maximum number of pattern occurrences to be replaced; count must be a non-negative integer. If omitted or zero, all occurrences will be replaced. Empty matches for the pattern are replaced only when not adjacent to a previous match, so sub('x*', '-', 'abc') returns '-a-b-c-'.

In string-type repl arguments, in addition to the character escapes and backreferences described above, \g<name> will use the substring matched by the group named name, as defined by the (?P<name>...) syntax. \g<number> uses the corresponding group number; \g<2> is therefore equivalent to \2, but isn’t ambiguous in a replacement such as \g<2>0. \20 would be interpreted as a reference to group 20, not a reference to group 2 followed by the literal character '0'. The backreference \g<0> substitutes in the entire substring matched by the RE.

Changed in version 3.1: Added the optional flags argument.

Changed in version 3.5: Unmatched groups are replaced with an empty string.

Deprecated since version 3.5, will be removed in version 3.6: Unknown escapes consist of '\' and ASCII letter now raise a deprecation warning and will be forbidden in Python 3.6.

re.subn(pattern, repl, string, count=0, flags=0)¶: Perform the same operation as sub(), but return a tuple (new_string, number_of_subs_made).

Changed in version 3.1: Added the optional flags argument.

Changed in version 3.5: Unmatched groups are replaced with an empty string.

re.escape(string)¶: Escape all the characters in pattern except ASCII letters, numbers and '_'. This is useful if you want to match an arbitrary literal string that may have regular expression metacharacters in it.

Changed in version 3.3: The '_' character is no longer escaped.

re.purge()¶: Clear the regular expression cache.

exception re.error(msg, pattern=None, pos=None)¶

Exception raised when a string passed to one of the functions here is not a valid regular expression (for example, it might contain unmatched parentheses) or when some other error occurs during compilation or matching. It is never an error if a string contains no match for a pattern. The error instance has the following additional attributes:

msg¶: The unformatted error message.

pattern¶: The regular expression pattern.

pos¶: The index of pattern where compilation failed.

lineno¶: The line corresponding to pos.

colno¶: The column corresponding to pos.

Changed in version 3.5: Added additional attributes.

6.2.3. Regular Expression Objects¶

Compiled regular expression objects support the following methods and attributes:

regex.search(string[, pos[, endpos]])¶

Scan through string looking for a location where this regular expression produces a match, and return a corresponding match object. Return None if no position in the string matches the pattern; note that this is different from finding a zero-length match at some point in the string.

The optional second parameter pos gives an index in the string where the search is to start; it defaults to 0. This is not completely equivalent to slicing the string; the '^' pattern character matches at the real beginning of the string and at positions just after a newline, but not necessarily at the index where the search is to start.

The optional parameter endpos limits how far the string will be searched; it will be as if the string is endpos characters long, so only the characters from pos to endpos - 1 will be searched for a match. If endpos is less than pos, no match will be found; otherwise, if rx is a compiled regular expression object, rx.search(string, 0, 50) is equivalent to rx.search(string[:50], 0).

>>> pattern = re.compile("d")
>>> pattern.search("dog")     # Match at index 0
<_sre.SRE_Match object; span=(0, 1), match='d'>
>>> pattern.search("dog", 1)  # No match; search doesn't include the "d"

regex.match(string[, pos[, endpos]])¶

If zero or more characters at the beginning of string match this regular expression, return a corresponding match object. Return None if the string does not match the pattern; note that this is different from a zero-length match.

The optional pos and endpos parameters have the same meaning as for the search() method.

>>> pattern = re.compile("o")
>>> pattern.match("dog")      # No match as "o" is not at the start of "dog".
>>> pattern.match("dog", 1)   # Match as "o" is the 2nd character of "dog".
<_sre.SRE_Match object; span=(1, 2), match='o'>

If you want to locate a match anywhere in string, use search() instead (see also search() vs. match()).

regex.fullmatch(string[, pos[, endpos]])¶

If the whole string matches this regular expression, return a corresponding match object. Return None if the string does not match the pattern; note that this is different from a zero-length match.

The optional pos and endpos parameters have the same meaning as for the search() method.

>>> pattern = re.compile("o[gh]")
>>> pattern.fullmatch("dog")      # No match as "o" is not at the start of "dog".
>>> pattern.fullmatch("ogre")     # No match as not the full string matches.
>>> pattern.fullmatch("doggie", 1, 3)   # Matches within given limits.
<_sre.SRE_Match object; span=(1, 3), match='og'>

New in version 3.4.

regex.split(string, maxsplit=0)¶: Identical to the split() function, using the compiled pattern.

regex.findall(string[, pos[, endpos]])¶: Similar to the findall() function, using the compiled pattern, but also accepts optional pos and endpos parameters that limit the search region like for match().

regex.finditer(string[, pos[, endpos]])¶: Similar to the finditer() function, using the compiled pattern, but also accepts optional pos and endpos parameters that limit the search region like for match().

regex.sub(repl, string, count=0)¶: Identical to the sub() function, using the compiled pattern.

regex.subn(repl, string, count=0)¶: Identical to the subn() function, using the compiled pattern.

regex.flags¶: The regex matching flags. This is a combination of the flags given to compile(), any (?...) inline flags in the pattern, and implicit flags such as UNICODE if the pattern is a Unicode string.

regex.groups¶: The number of capturing groups in the pattern.

regex.groupindex¶: A dictionary mapping any symbolic group names defined by (?P<id>) to group numbers. The dictionary is empty if no symbolic groups were used in the pattern.

regex.pattern¶: The pattern string from which the RE object was compiled.

6.2.4. Match Objects¶

Match objects always have a boolean value of True. Since match() and search() return None when there is no match, you can test whether there was a match with a simple if statement:

match = re.search(pattern, string)
if match:
    process(match)

Match objects support the following methods and attributes:

match.expand(template)¶: Return the string obtained by doing backslash substitution on the template string template, as done by the sub() method. Escapes such as \n are converted to the appropriate characters, and numeric backreferences (\1, \2) and named backreferences (\g<1>, \g<name>) are replaced by the contents of the corresponding group.

Changed in version 3.5: Unmatched groups are replaced with an empty string.

match.group([group1, ...])¶

Returns one or more subgroups of the match. If there is a single argument, the result is a single string; if there are multiple arguments, the result is a tuple with one item per argument. Without arguments, group1 defaults to zero (the whole match is returned). If a groupN argument is zero, the corresponding return value is the entire matching string; if it is in the inclusive range [1..99], it is the string matching the corresponding parenthesized group. If a group number is negative or larger than the number of groups defined in the pattern, an IndexError exception is raised. If a group is contained in a part of the pattern that did not match, the corresponding result is None. If a group is contained in a part of the pattern that matched multiple times, the last match is returned.

>>> m = re.match(r"(\w+) (\w+)", "Isaac Newton, physicist")
>>> m.group(0)       # The entire match
'Isaac Newton'
>>> m.group(1)       # The first parenthesized subgroup.
'Isaac'
>>> m.group(2)       # The second parenthesized subgroup.
'Newton'
>>> m.group(1, 2)    # Multiple arguments give us a tuple.
('Isaac', 'Newton')

If the regular expression uses the (?P<name>...) syntax, the groupN arguments may also be strings identifying groups by their group name. If a string argument is not used as a group name in the pattern, an IndexError exception is raised.

A moderately complicated example:

>>> m = re.match(r"(?P<first_name>\w+) (?P<last_name>\w+)", "Malcolm Reynolds")
>>> m.group('first_name')
'Malcolm'
>>> m.group('last_name')
'Reynolds'

Named groups can also be referred to by their index:

>>> m.group(1)
'Malcolm'
>>> m.group(2)
'Reynolds'

If a group matches multiple times, only the last match is accessible:

>>> m = re.match(r"(..)+", "a1b2c3")  # Matches 3 times.
>>> m.group(1)                        # Returns only the last match.
'c3'

match.groups(default=None)¶

Return a tuple containing all the subgroups of the match, from 1 up to however many groups are in the pattern. The default argument is used for groups that did not participate in the match; it defaults to None.

For example:

>>> m = re.match(r"(\d+)\.(\d+)", "24.1632")
>>> m.groups()
('24', '1632')

If we make the decimal place and everything after it optional, not all groups might participate in the match. These groups will default to None unless the default argument is given:

>>> m = re.match(r"(\d+)\.?(\d+)?", "24")
>>> m.groups()      # Second group defaults to None.
('24', None)
>>> m.groups('0')   # Now, the second group defaults to '0'.
('24', '0')

match.groupdict(default=None)¶

Return a dictionary containing all the named subgroups of the match, keyed by the subgroup name. The default argument is used for groups that did not participate in the match; it defaults to None. For example:

>>> m = re.match(r"(?P<first_name>\w+) (?P<last_name>\w+)", "Malcolm Reynolds")
>>> m.groupdict()
{'first_name': 'Malcolm', 'last_name': 'Reynolds'}

match.start([group])¶

match.end([group])¶

Return the indices of the start and end of the substring matched by group; group defaults to zero (meaning the whole matched substring). Return -1 if group exists but did not contribute to the match. For a match object m, and a group g that did contribute to the match, the substring matched by group g (equivalent to m.group(g)) is

m.string[m.start(g):m.end(g)]

Note that m.start(group) will equal m.end(group) if group matched a null string. For example, after m = re.search('b(c?)', 'cba'), m.start(0) is 1, m.end(0) is 2, m.start(1) and m.end(1) are both 2, and m.start(2) raises an IndexError exception.

An example that will remove remove_this from email addresses:

>>> email = "tony@tiremove_thisger.net"
>>> m = re.search("remove_this", email)
>>> email[:m.start()] + email[m.end():]
'tony@tiger.net'

match.span([group])¶: For a match m, return the 2-tuple (m.start(group), m.end(group)). Note that if group did not contribute to the match, this is (-1, -1). group defaults to zero, the entire match.

match.pos¶: The value of pos which was passed to the search() or match() method of a regex object. This is the index into the string at which the RE engine started looking for a match.

match.endpos¶: The value of endpos which was passed to the search() or match() method of a regex object. This is the index into the string beyond which the RE engine will not go.

match.lastindex¶: The integer index of the last matched capturing group, or None if no group was matched at all. For example, the expressions (a)b, ((a)(b)), and ((ab)) will have lastindex == 1 if applied to the string 'ab', while the expression (a)(b) will have lastindex == 2, if applied to the same string.

match.lastgroup¶: The name of the last matched capturing group, or None if the group didn’t have a name, or if no group was matched at all.

match.re¶: The regular expression object whose match() or search() method produced this match instance.

match.string¶: The string passed to match() or search().

6.2.5. Regular Expression Examples¶

6.2.5.1. Checking for a Pair¶

In this example, we’ll use the following helper function to display match objects a little more gracefully:

def displaymatch(match):
    if match is None:
        return None
    return '<Match: %r, groups=%r>' % (match.group(), match.groups())

Suppose you are writing a poker program where a player’s hand is represented as a 5-character string with each character representing a card, “a” for ace, “k” for king, “q” for queen, “j” for jack, “t” for 10, and “2” through “9” representing the card with that value.

To see if a given string is a valid hand, one could do the following:

>>> valid = re.compile(r"^[a2-9tjqk]{5}$")
>>> displaymatch(valid.match("akt5q"))  # Valid.
"<Match: 'akt5q', groups=()>"
>>> displaymatch(valid.match("akt5e"))  # Invalid.
>>> displaymatch(valid.match("akt"))    # Invalid.
>>> displaymatch(valid.match("727ak"))  # Valid.
"<Match: '727ak', groups=()>"

That last hand, "727ak", contained a pair, or two of the same valued cards. To match this with a regular expression, one could use backreferences as such:

>>> pair = re.compile(r".*(.).*\1")
>>> displaymatch(pair.match("717ak"))     # Pair of 7s.
"<Match: '717', groups=('7',)>"
>>> displaymatch(pair.match("718ak"))     # No pairs.
>>> displaymatch(pair.match("354aa"))     # Pair of aces.
"<Match: '354aa', groups=('a',)>"

To find out what card the pair consists of, one could use the group() method of the match object in the following manner:

>>> pair.match("717ak").group(1)
'7'

# Error because re.match() returns None, which doesn't have a group() method:
>>> pair.match("718ak").group(1)
Traceback (most recent call last):
  File "<pyshell#23>", line 1, in <module>
    re.match(r".*(.).*\1", "718ak").group(1)
AttributeError: 'NoneType' object has no attribute 'group'

>>> pair.match("354aa").group(1)
'a'

6.2.5.2. Simulating scanf()¶

Python does not currently have an equivalent to scanf(). Regular expressions are generally more powerful, though also more verbose, than scanf() format strings. The table below offers some more-or-less equivalent mappings between scanf() format tokens and regular expressions.

`scanf()` Token	Regular Expression
`%c`	`.`
`%5c`	`.{5}`
`%d`	`[-+]?\d+`
`%e`, `%E`, `%f`, `%g`	`[-+]?(\d+(\.\d*)?\|\.\d+)([eE][-+]?\d+)?`
`%i`	`[-+]?(0[xX][\dA-Fa-f]+\|0[0-7]*\|\d+)`
`%o`	`[-+]?[0-7]+`
`%s`	`\S+`
`%u`	`\d+`
`%x`, `%X`	`[-+]?(0[xX])?[\dA-Fa-f]+`

To extract the filename and numbers from a string like

/usr/sbin/sendmail - 0 errors, 4 warnings

you would use a scanf() format like

%s - %d errors, %d warnings

The equivalent regular expression would be

(\S+) - (\d+) errors, (\d+) warnings

6.2.5.3. search() vs. match()¶

Python offers two different primitive operations based on regular expressions: re.match() checks for a match only at the beginning of the string, while re.search() checks for a match anywhere in the string (this is what Perl does by default).

For example:

>>> re.match("c", "abcdef")  # No match
>>> re.search("c", "abcdef") # Match
<_sre.SRE_Match object; span=(2, 3), match='c'>

Regular expressions beginning with '^' can be used with search() to restrict the match at the beginning of the string:

>>> re.match("c", "abcdef")  # No match
>>> re.search("^c", "abcdef") # No match
>>> re.search("^a", "abcdef")  # Match
<_sre.SRE_Match object; span=(0, 1), match='a'>

Note however that in MULTILINE mode match() only matches at the beginning of the string, whereas using search() with a regular expression beginning with '^' will match at the beginning of each line.

>>> re.match('X', 'A\nB\nX', re.MULTILINE)  # No match
>>> re.search('^X', 'A\nB\nX', re.MULTILINE)  # Match
<_sre.SRE_Match object; span=(4, 5), match='X'>

6.2.5.4. Making a Phonebook¶

split() splits a string into a list delimited by the passed pattern. The method is invaluable for converting textual data into data structures that can be easily read and modified by Python as demonstrated in the following example that creates a phonebook.

First, here is the input. Normally it may come from a file, here we are using triple-quoted string syntax:

>>> text = """Ross McFluff: 834.345.1254 155 Elm Street
...
... Ronald Heathmore: 892.345.3428 436 Finley Avenue
... Frank Burger: 925.541.7625 662 South Dogwood Way
...
...
... Heather Albrecht: 548.326.4584 919 Park Place"""

The entries are separated by one or more newlines. Now we convert the string into a list with each nonempty line having its own entry:

>>> entries = re.split("\n+", text)
>>> entries
['Ross McFluff: 834.345.1254 155 Elm Street',
'Ronald Heathmore: 892.345.3428 436 Finley Avenue',
'Frank Burger: 925.541.7625 662 South Dogwood Way',
'Heather Albrecht: 548.326.4584 919 Park Place']

Finally, split each entry into a list with first name, last name, telephone number, and address. We use the maxsplit parameter of split() because the address has spaces, our splitting pattern, in it:

>>> [re.split(":? ", entry, 3) for entry in entries]
[['Ross', 'McFluff', '834.345.1254', '155 Elm Street'],
['Ronald', 'Heathmore', '892.345.3428', '436 Finley Avenue'],
['Frank', 'Burger', '925.541.7625', '662 South Dogwood Way'],
['Heather', 'Albrecht', '548.326.4584', '919 Park Place']]

The :? pattern matches the colon after the last name, so that it does not occur in the result list. With a maxsplit of 4, we could separate the house number from the street name:

>>> [re.split(":? ", entry, 4) for entry in entries]
[['Ross', 'McFluff', '834.345.1254', '155', 'Elm Street'],
['Ronald', 'Heathmore', '892.345.3428', '436', 'Finley Avenue'],
['Frank', 'Burger', '925.541.7625', '662', 'South Dogwood Way'],
['Heather', 'Albrecht', '548.326.4584', '919', 'Park Place']]

6.2.5.5. Text Munging¶

sub() replaces every occurrence of a pattern with a string or the result of a function. This example demonstrates using sub() with a function to “munge” text, or randomize the order of all the characters in each word of a sentence except for the first and last characters:

>>> def repl(m):
...   inner_word = list(m.group(2))
...   random.shuffle(inner_word)
...   return m.group(1) + "".join(inner_word) + m.group(3)
>>> text = "Professor Abdolmalek, please report your absences promptly."
>>> re.sub(r"(\w)(\w+)(\w)", repl, text)
'Poefsrosr Aealmlobdk, pslaee reorpt your abnseces plmrptoy.'
>>> re.sub(r"(\w)(\w+)(\w)", repl, text)
'Pofsroser Aodlambelk, plasee reoprt yuor asnebces potlmrpy.'

6.2.5.6. Finding all Adverbs¶

findall() matches all occurrences of a pattern, not just the first one as search() does. For example, if one was a writer and wanted to find all of the adverbs in some text, he or she might use findall() in the following manner:

>>> text = "He was carefully disguised but captured quickly by police."
>>> re.findall(r"\w+ly", text)
['carefully', 'quickly']

6.2.5.7. Finding all Adverbs and their Positions¶

If one wants more information about all matches of a pattern than the matched text, finditer() is useful as it provides match objects instead of strings. Continuing with the previous example, if one was a writer who wanted to find all of the adverbs and their positions in some text, he or she would use finditer() in the following manner:

>>> text = "He was carefully disguised but captured quickly by police."
>>> for m in re.finditer(r"\w+ly", text):
...     print('%02d-%02d: %s' % (m.start(), m.end(), m.group(0)))
07-16: carefully
40-47: quickly

6.2.5.8. Raw String Notation¶

Raw string notation (r"text") keeps regular expressions sane. Without it, every backslash ('\') in a regular expression would have to be prefixed with another one to escape it. For example, the two following lines of code are functionally identical:

>>> re.match(r"\W(.)\1\W", " ff ")
<_sre.SRE_Match object; span=(0, 4), match=' ff '>
>>> re.match("\\W(.)\\1\\W", " ff ")
<_sre.SRE_Match object; span=(0, 4), match=' ff '>

When one wants to match a literal backslash, it must be escaped in the regular expression. With raw string notation, this means r"\\". Without raw string notation, one must use "\\\\", making the following lines of code functionally identical:

>>> re.match(r"\\", r"\\")
<_sre.SRE_Match object; span=(0, 1), match='\\'>
>>> re.match("\\\\", r"\\")
<_sre.SRE_Match object; span=(0, 1), match='\\'>

6.2.5.9. Writing a Tokenizer¶

A tokenizer or scanner analyzes a string to categorize groups of characters. This is a useful first step in writing a compiler or interpreter.

The text categories are specified with regular expressions. The technique is to combine those into a single master regular expression and to loop over successive matches:

import collections
import re

Token = collections.namedtuple('Token', ['typ', 'value', 'line', 'column'])

def tokenize(code):
    keywords = {'IF', 'THEN', 'ENDIF', 'FOR', 'NEXT', 'GOSUB', 'RETURN'}
    token_specification = [
        ('NUMBER',  r'\d+(\.\d*)?'), # Integer or decimal number
        ('ASSIGN',  r':='),          # Assignment operator
        ('END',     r';'),           # Statement terminator
        ('ID',      r'[A-Za-z]+'),   # Identifiers
        ('OP',      r'[+\-*/]'),     # Arithmetic operators
        ('NEWLINE', r'\n'),          # Line endings
        ('SKIP',    r'[ \t]+'),      # Skip over spaces and tabs
        ('MISMATCH',r'.'),           # Any other character
    ]
    tok_regex = '|'.join('(?P<%s>%s)' % pair for pair in token_specification)
    line_num = 1
    line_start = 0
    for mo in re.finditer(tok_regex, code):
        kind = mo.lastgroup
        value = mo.group(kind)
        if kind == 'NEWLINE':
            line_start = mo.end()
            line_num += 1
        elif kind == 'SKIP':
            pass
        elif kind == 'MISMATCH':
            raise RuntimeError('%r unexpected on line %d' % (value, line_num))
        else:
            if kind == 'ID' and value in keywords:
                kind = value
            column = mo.start() - line_start
            yield Token(kind, value, line_num, column)

statements = '''
    IF quantity THEN
        total := total + price * quantity;
        tax := price * 0.05;
    ENDIF;
'''

for token in tokenize(statements):
    print(token)

The tokenizer produces the following output:

Token(typ='IF', value='IF', line=2, column=4)
Token(typ='ID', value='quantity', line=2, column=7)
Token(typ='THEN', value='THEN', line=2, column=16)
Token(typ='ID', value='total', line=3, column=8)
Token(typ='ASSIGN', value=':=', line=3, column=14)
Token(typ='ID', value='total', line=3, column=17)
Token(typ='OP', value='+', line=3, column=23)
Token(typ='ID', value='price', line=3, column=25)
Token(typ='OP', value='*', line=3, column=31)
Token(typ='ID', value='quantity', line=3, column=33)
Token(typ='END', value=';', line=3, column=41)
Token(typ='ID', value='tax', line=4, column=8)
Token(typ='ASSIGN', value=':=', line=4, column=12)
Token(typ='ID', value='price', line=4, column=15)
Token(typ='OP', value='*', line=4, column=21)
Token(typ='NUMBER', value='0.05', line=4, column=23)
Token(typ='END', value=';', line=4, column=27)
Token(typ='ENDIF', value='ENDIF', line=5, column=4)
Token(typ='END', value=';', line=5, column=9)

6.2. `re` — Regular expression operations¶

6.2.1. Regular Expression Syntax¶

6.2.2. Module Contents¶

6.2.3. Regular Expression Objects¶

6.2.4. Match Objects¶

6.2.5. Regular Expression Examples¶

6.2.5.1. Checking for a Pair¶

6.2.5.2. Simulating scanf()¶

6.2.5.3. search() vs. match()¶

6.2.5.4. Making a Phonebook¶

6.2.5.5. Text Munging¶

6.2.5.6. Finding all Adverbs¶

6.2.5.7. Finding all Adverbs and their Positions¶

6.2.5.8. Raw String Notation¶

6.2.5.9. Writing a Tokenizer¶

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6.2. re — Regular expression operations¶

6.2.1. Regular Expression Syntax¶

6.2.2. Module Contents¶

6.2.3. Regular Expression Objects¶

6.2.4. Match Objects¶

6.2.5. Regular Expression Examples¶

6.2.5.1. Checking for a Pair¶

6.2.5.2. Simulating scanf()¶

6.2.5.3. search() vs. match()¶

6.2.5.4. Making a Phonebook¶

6.2.5.5. Text Munging¶

6.2.5.6. Finding all Adverbs¶

6.2.5.7. Finding all Adverbs and their Positions¶

6.2.5.8. Raw String Notation¶

6.2.5.9. Writing a Tokenizer¶

6.2. `re` — Regular expression operations¶