regex 2018.08.29

Alternative regular expression module, to replace re.

Introduction

This regex implementation is backwards-compatible with the standard ‘re’ module, but offers additional functionality.

Note

The re module’s behaviour with zero-width matches changed in Python 3.7, and this module will follow that behaviour when compiled for Python 3.7.

Old vs new behaviour

In order to be compatible with the re module, this module has 2 behaviours:

• Version 0 behaviour (old behaviour, compatible with the re module):

  Please note that the re module’s behaviour may change over time, and I’ll endeavour to match that behaviour in version 0.

  • Indicated by the VERSION0 or V0 flag, or (?V0) in the pattern.

  • Zero-width matches are not handled correctly in the re module before Python 3.7. The behaviour in those earlier versions is:

    • .split won’t split a string at a zero-width match.

    • .sub will advance by one character after a zero-width match.

  • Inline flags apply to the entire pattern, and they can’t be turned off.

  • Only simple sets are supported.

  • Case-insensitive matches in Unicode use simple case-folding by default.

• Version 1 behaviour (new behaviour, possibly different from the re module):

  • Indicated by the VERSION1 or V1 flag, or (?V1) in the pattern.

  • Zero-width matches are handled correctly.

  • Inline flags apply to the end of the group or pattern, and they can be turned off.

  • Nested sets and set operations are supported.

  • Case-insensitive matches in Unicode use full case-folding by default.

If no version is specified, the regex module will default to regex.DEFAULT_VERSION.

Case-insensitive matches in Unicode

The regex module supports both simple and full case-folding for case-insensitive matches in Unicode. Use of full case-folding can be turned on using the FULLCASE or F flag, or (?f) in the pattern. Please note that this flag affects how the IGNORECASE flag works; the FULLCASE flag itself does not turn on case-insensitive matching.

In the version 0 behaviour, the flag is off by default.

In the version 1 behaviour, the flag is on by default.

Nested sets and set operations

It’s not possible to support both simple sets, as used in the re module, and nested sets at the same time because of a difference in the meaning of an unescaped "[" in a set.

For example, the pattern [[a-z]--[aeiou]] is treated in the version 0 behaviour (simple sets, compatible with the re module) as:

• Set containing “[” and the letters “a” to “z”

• Literal “–”

• Set containing letters “a”, “e”, “i”, “o”, “u”

but in the version 1 behaviour (nested sets, enhanced behaviour) as:

• Set which is:

  • Set containing the letters “a” to “z”

• but excluding:

  • Set containing the letters “a”, “e”, “i”, “o”, “u”

Version 0 behaviour: only simple sets are supported.

Version 1 behaviour: nested sets and set operations are supported.

Flags

There are 2 kinds of flag: scoped and global. Scoped flags can apply to only part of a pattern and can be turned on or off; global flags apply to the entire pattern and can only be turned on.

The scoped flags are: FULLCASE, IGNORECASE, MULTILINE, DOTALL, VERBOSE, WORD.

The global flags are: ASCII, BESTMATCH, ENHANCEMATCH, LOCALE, POSIX, REVERSE, UNICODE, VERSION0, VERSION1.

If neither the ASCII, LOCALE nor UNICODE flag is specified, it will default to UNICODE if the regex pattern is a Unicode string and ASCII if it’s a bytestring.

The ENHANCEMATCH flag makes fuzzy matching attempt to improve the fit of the next match that it finds.

The BESTMATCH flag makes fuzzy matching search for the best match instead of the next match.

Notes on named capture groups

All capture groups have a group number, starting from 1.

Groups with the same group name will have the same group number, and groups with a different group name will have a different group number.

The same name can be used by more than one group, with later captures ‘overwriting’ earlier captures. All of the captures of the group will be available from the captures method of the match object.

Group numbers will be reused across different branches of a branch reset, eg. (?|(first)|(second)) has only group 1. If capture groups have different group names then they will, of course, have different group numbers, eg. (?|(?P<foo>first)|(?P<bar>second)) has group 1 (“foo”) and group 2 (“bar”).

In the regex (\s+)(?|(?P<foo>[A-Z]+)|(\w+) (?P<foo>[0-9]+) there are 2 groups:

• (\s+) is group 1.

• (?P<foo>[A-Z]+) is group 2, also called “foo”.

• (\w+) is group 2 because of the branch reset.

• (?P<foo>[0-9]+) is group 2 because it’s called “foo”.

If you want to prevent (\w+) from being group 2, you need to name it (different name, different group number).

Multithreading

The regex module releases the GIL during matching on instances of the built-in (immutable) string classes, enabling other Python threads to run concurrently. It is also possible to force the regex module to release the GIL during matching by calling the matching methods with the keyword argument concurrent=True. The behaviour is undefined if the string changes during matching, so use it only when it is guaranteed that that won’t happen.

Unicode

This module supports Unicode 11.0.

Full Unicode case-folding is supported.

Additional features

The issue numbers relate to the Python bug tracker, except where listed as “Hg issue”.

• Added support for lookaround in conditional pattern (Hg issue 163)

  The test of a conditional pattern can now be a lookaround.

  Examples:

  >>> regex.match(r'(?(?=\d)\d+|\w+)', '123abc')
  <regex.Match object; span=(0, 3), match='123'>
  >>> regex.match(r'(?(?=\d)\d+|\w+)', 'abc123')
  <regex.Match object; span=(0, 6), match='abc123'>

  This is not quite the same as putting a lookaround in the first branch of a pair of alternatives.

  Examples:

  >>> print(regex.match(r'(?:(?=\d)\d+\b|\w+)', '123abc'))
  <regex.Match object; span=(0, 6), match='123abc'>
  >>> print(regex.match(r'(?(?=\d)\d+\b|\w+)', '123abc'))
  None

  In the first example, the lookaround matched, but the remainder of the first branch failed to match, and so the second branch was attempted, whereas in the second example, the lookaround matched, and the first branch failed to match, but the second branch was not attempted.

• Added POSIX matching (leftmost longest) (Hg issue 150)

  The POSIX standard for regex is to return the leftmost longest match. This can be turned on using the POSIX flag ((?p)).

  Examples:

  >>> # Normal matching.
  >>> regex.search(r'Mr|Mrs', 'Mrs')
  <regex.Match object; span=(0, 2), match='Mr'>
  >>> regex.search(r'one(self)?(selfsufficient)?', 'oneselfsufficient')
  <regex.Match object; span=(0, 7), match='oneself'>
  >>> # POSIX matching.
  >>> regex.search(r'(?p)Mr|Mrs', 'Mrs')
  <regex.Match object; span=(0, 3), match='Mrs'>
  >>> regex.search(r'(?p)one(self)?(selfsufficient)?', 'oneselfsufficient')
  <regex.Match object; span=(0, 17), match='oneselfsufficient'>

  Note that it will take longer to find matches because when it finds a match at a certain position, it won’t return that immediately, but will keep looking to see if there’s another longer match there.

• Added (?(DEFINE)...) (Hg issue 152)

  If there’s no group called “DEFINE”, then … will be ignored, but any group definitions within it will be available.

  Examples:

  >>> regex.search(r'(?(DEFINE)(?P<quant>\d+)(?P<item>\w+))(?&quant) (?&item)', '5 elephants')
  <regex.Match object; span=(0, 11), match='5 elephants'>

• Added (*PRUNE), (*SKIP) and (*FAIL) (Hg issue 153)

  (*PRUNE) discards the backtracking info up to that point. When used in an atomic group or a lookaround, it won’t affect the enclosing pattern.

  (*SKIP) is similar to (*PRUNE), except that it also sets where in the text the next attempt to match will start. When used in an atomic group or a lookaround, it won’t affect the enclosing pattern.

  (*FAIL) causes immediate backtracking. (*F) is a permitted abbreviation.

• Added \K (Hg issue 151)

  Keeps the part of the entire match after the position where \K occurred; the part before it is discarded.

  It does not affect what capture groups return.

  Examples:

  >>> m = regex.search(r'(\w\w\K\w\w\w)', 'abcdef')
  >>> m[0]
  'cde'
  >>> m[1]
  'abcde'
  >>>
  >>> m = regex.search(r'(?r)(\w\w\K\w\w\w)', 'abcdef')
  >>> m[0]
  'bc'
  >>> m[1]
  'bcdef'

• Added capture subscripting for expandf and subf/subfn (Hg issue 133)

  You can now use subscripting to get the captures of a repeated capture group.

  Examples:

  >>> m = regex.match(r"(\w)+", "abc")
  >>> m.expandf("{1}")
  'c'
  >>> m.expandf("{1[0]} {1[1]} {1[2]}")
  'a b c'
  >>> m.expandf("{1[-1]} {1[-2]} {1[-3]}")
  'c b a'
  >>>
  >>> m = regex.match(r"(?P<letter>\w)+", "abc")
  >>> m.expandf("{letter}")
  'c'
  >>> m.expandf("{letter[0]} {letter[1]} {letter[2]}")
  'a b c'
  >>> m.expandf("{letter[-1]} {letter[-2]} {letter[-3]}")
  'c b a'

• Added support for referring to a group by number using (?P=...).

  This is in addition to the existing \g<...>.

• Fixed the handling of locale-sensitive regexes.

  The LOCALE flag is intended for legacy code and has limited support. You’re still recommended to use Unicode instead.

• Added partial matches (Hg issue 102)

  A partial match is one that matches up to the end of string, but that string has been truncated and you want to know whether a complete match could be possible if the string had not been truncated.

  Partial matches are supported by match, search, fullmatch and finditer with the partial keyword argument.

  Match objects have a partial attribute, which is True if it’s a partial match.

  For example, if you wanted a user to enter a 4-digit number and check it character by character as it was being entered:

  >>> pattern = regex.compile(r'\d{4}')
  
  >>> # Initially, nothing has been entered:
  >>> print(pattern.fullmatch('', partial=True))
  <regex.Match object; span=(0, 0), match='', partial=True>
  
  >>> # An empty string is OK, but it's only a partial match.
  >>> # The user enters a letter:
  >>> print(pattern.fullmatch('a', partial=True))
  None
  >>> # It'll never match.
  
  >>> # The user deletes that and enters a digit:
  >>> print(pattern.fullmatch('1', partial=True))
  <regex.Match object; span=(0, 1), match='1', partial=True>
  >>> # It matches this far, but it's only a partial match.
  
  >>> # The user enters 2 more digits:
  >>> print(pattern.fullmatch('123', partial=True))
  <regex.Match object; span=(0, 3), match='123', partial=True>
  >>> # It matches this far, but it's only a partial match.
  
  >>> # The user enters another digit:
  >>> print(pattern.fullmatch('1234', partial=True))
  <regex.Match object; span=(0, 4), match='1234'>
  >>> # It's a complete match.
  
  >>> # If the user enters another digit:
  >>> print(pattern.fullmatch('12345', partial=True))
  None
  >>> # It's no longer a match.
  
  >>> # This is a partial match:
  >>> pattern.match('123', partial=True).partial
  True
  
  >>> # This is a complete match:
  >>> pattern.match('1233', partial=True).partial
  False

• * operator not working correctly with sub() (Hg issue 106)

  Sometimes it’s not clear how zero-width matches should be handled. For example, should .* match 0 characters directly after matching >0 characters?

  Examples:

  # Python 3.7 and later
  >>> regex.sub('.*', 'x', 'test')
  'xx'
  >>> regex.sub('.*?', '|', 'test')
  '|||||||||'
  
  # Python 3.6 and earlier
  >>> regex.sub('(?V0).*', 'x', 'test')
  'x'
  >>> regex.sub('(?V1).*', 'x', 'test')
  'xx'
  >>> regex.sub('(?V0).*?', '|', 'test')
  '|t|e|s|t|'
  >>> regex.sub('(?V1).*?', '|', 'test')
  '|||||||||'

• Added capturesdict (Hg issue 86)

  capturesdict is a combination of groupdict and captures:

  groupdict returns a dict of the named groups and the last capture of those groups.

  captures returns a list of all the captures of a group

  capturesdict returns a dict of the named groups and lists of all the captures of those groups.

  Examples:

  >>> m = regex.match(r"(?:(?P<word>\w+) (?P<digits>\d+)\n)+", "one 1\ntwo 2\nthree 3\n")
  >>> m.groupdict()
  {'word': 'three', 'digits': '3'}
  >>> m.captures("word")
  ['one', 'two', 'three']
  >>> m.captures("digits")
  ['1', '2', '3']
  >>> m.capturesdict()
  {'word': ['one', 'two', 'three'], 'digits': ['1', '2', '3']}

• Allow duplicate names of groups (Hg issue 87)

  Group names can now be duplicated.

  Examples:

  >>> # With optional groups:
  >>>
  >>> # Both groups capture, the second capture 'overwriting' the first.
  >>> m = regex.match(r"(?P<item>\w+)? or (?P<item>\w+)?", "first or second")
  >>> m.group("item")
  'second'
  >>> m.captures("item")
  ['first', 'second']
  >>> # Only the second group captures.
  >>> m = regex.match(r"(?P<item>\w+)? or (?P<item>\w+)?", " or second")
  >>> m.group("item")
  'second'
  >>> m.captures("item")
  ['second']
  >>> # Only the first group captures.
  >>> m = regex.match(r"(?P<item>\w+)? or (?P<item>\w+)?", "first or ")
  >>> m.group("item")
  'first'
  >>> m.captures("item")
  ['first']
  >>>
  >>> # With mandatory groups:
  >>>
  >>> # Both groups capture, the second capture 'overwriting' the first.
  >>> m = regex.match(r"(?P<item>\w*) or (?P<item>\w*)?", "first or second")
  >>> m.group("item")
  'second'
  >>> m.captures("item")
  ['first', 'second']
  >>> # Again, both groups capture, the second capture 'overwriting' the first.
  >>> m = regex.match(r"(?P<item>\w*) or (?P<item>\w*)", " or second")
  >>> m.group("item")
  'second'
  >>> m.captures("item")
  ['', 'second']
  >>> # And yet again, both groups capture, the second capture 'overwriting' the first.
  >>> m = regex.match(r"(?P<item>\w*) or (?P<item>\w*)", "first or ")
  >>> m.group("item")
  ''
  >>> m.captures("item")
  ['first', '']

• Added fullmatch (issue #16203)

  fullmatch behaves like match, except that it must match all of the string.

  Examples:

  >>> print(regex.fullmatch(r"abc", "abc").span())
  (0, 3)
  >>> print(regex.fullmatch(r"abc", "abcx"))
  None
  >>> print(regex.fullmatch(r"abc", "abcx", endpos=3).span())
  (0, 3)
  >>> print(regex.fullmatch(r"abc", "xabcy", pos=1, endpos=4).span())
  (1, 4)
  >>>
  >>> regex.match(r"a.*?", "abcd").group(0)
  'a'
  >>> regex.fullmatch(r"a.*?", "abcd").group(0)
  'abcd'

• Added subf and subfn

  subf and subfn are alternatives to sub and subn respectively. When passed a replacement string, they treat it as a format string.

  Examples:

  >>> regex.subf(r"(\w+) (\w+)", "{0} => {2} {1}", "foo bar")
  'foo bar => bar foo'
  >>> regex.subf(r"(?P<word1>\w+) (?P<word2>\w+)", "{word2} {word1}", "foo bar")
  'bar foo'

• Added expandf to match object

  expandf is an alternative to expand. When passed a replacement string, it treats it as a format string.

  Examples:

  >>> m = regex.match(r"(\w+) (\w+)", "foo bar")
  >>> m.expandf("{0} => {2} {1}")
  'foo bar => bar foo'
  >>>
  >>> m = regex.match(r"(?P<word1>\w+) (?P<word2>\w+)", "foo bar")
  >>> m.expandf("{word2} {word1}")
  'bar foo'

• Detach searched string

  A match object contains a reference to the string that was searched, via its string attribute. The detach_string method will ‘detach’ that string, making it available for garbage collection, which might save valuable memory if that string is very large.

  Example:

  >>> m = regex.search(r"\w+", "Hello world")
  >>> print(m.group())
  Hello
  >>> print(m.string)
  Hello world
  >>> m.detach_string()
  >>> print(m.group())
  Hello
  >>> print(m.string)
  None

• Recursive patterns (Hg issue 27)

  Recursive and repeated patterns are supported.

  (?R) or (?0) tries to match the entire regex recursively. (?1), (?2), etc, try to match the relevant capture group.

  (?&name) tries to match the named capture group.

  Examples:

  >>> regex.match(r"(Tarzan|Jane) loves (?1)", "Tarzan loves Jane").groups()
  ('Tarzan',)
  >>> regex.match(r"(Tarzan|Jane) loves (?1)", "Jane loves Tarzan").groups()
  ('Jane',)
  
  >>> m = regex.search(r"(\w)(?:(?R)|(\w?))\1", "kayak")
  >>> m.group(0, 1, 2)
  ('kayak', 'k', None)

  The first two examples show how the subpattern within the capture group is reused, but is _not_ itself a capture group. In other words, "(Tarzan|Jane) loves (?1)" is equivalent to "(Tarzan|Jane) loves (?:Tarzan|Jane)".

  It’s possible to backtrack into a recursed or repeated group.

  You can’t call a group if there is more than one group with that group name or group number ("ambiguous group reference").

  The alternative forms (?P>name) and (?P&name) are also supported.

• Full Unicode case-folding is supported.

  In version 1 behaviour, the regex module uses full case-folding when performing case-insensitive matches in Unicode.

  Examples (in Python 3):

  >>> regex.match(r"(?iV1)strasse", "stra\N{LATIN SMALL LETTER SHARP S}e").span()
  (0, 6)
  >>> regex.match(r"(?iV1)stra\N{LATIN SMALL LETTER SHARP S}e", "STRASSE").span()
  (0, 7)

  In version 0 behaviour, it uses simple case-folding for backward compatibility with the re module.

• Approximate “fuzzy” matching (Hg issue 12, Hg issue 41, Hg issue 109)

  Regex usually attempts an exact match, but sometimes an approximate, or “fuzzy”, match is needed, for those cases where the text being searched may contain errors in the form of inserted, deleted or substituted characters.

  A fuzzy regex specifies which types of errors are permitted, and, optionally, either the minimum and maximum or only the maximum permitted number of each type. (You cannot specify only a minimum.)

  The 3 types of error are:

  • Insertion, indicated by “i”

  • Deletion, indicated by “d”

  • Substitution, indicated by “s”

  In addition, “e” indicates any type of error.

  The fuzziness of a regex item is specified between “{” and “}” after the item.

  Examples:

  • foo match “foo” exactly

  • (?:foo){i} match “foo”, permitting insertions

  • (?:foo){d} match “foo”, permitting deletions

  • (?:foo){s} match “foo”, permitting substitutions

  • (?:foo){i,s} match “foo”, permitting insertions and substitutions

  • (?:foo){e} match “foo”, permitting errors

  If a certain type of error is specified, then any type not specified will not be permitted.

  In the following examples I’ll omit the item and write only the fuzziness:

  • {d<=3} permit at most 3 deletions, but no other types

  • {i<=1,s<=2} permit at most 1 insertion and at most 2 substitutions, but no deletions

  • {1<=e<=3} permit at least 1 and at most 3 errors

  • {i<=2,d<=2,e<=3} permit at most 2 insertions, at most 2 deletions, at most 3 errors in total, but no substitutions

  It’s also possible to state the costs of each type of error and the maximum permitted total cost.

  Examples:

  • {2i+2d+1s<=4} each insertion costs 2, each deletion costs 2, each substitution costs 1, the total cost must not exceed 4

  • {i<=1,d<=1,s<=1,2i+2d+1s<=4} at most 1 insertion, at most 1 deletion, at most 1 substitution; each insertion costs 2, each deletion costs 2, each substitution costs 1, the total cost must not exceed 4

  You can also use “<” instead of “<=” if you want an exclusive minimum or maximum.

  By default, fuzzy matching searches for the first match that meets the given constraints. The ENHANCEMATCH flag will cause it to attempt to improve the fit (i.e. reduce the number of errors) of the match that it has found.

  The BESTMATCH flag will make it search for the best match instead.

  Further examples to note:

  • regex.search("(dog){e}", "cat and dog")[1] returns "cat" because that matches "dog" with 3 errors (an unlimited number of errors is permitted).

  • regex.search("(dog){e<=1}", "cat and dog")[1] returns " dog" (with a leading space) because that matches "dog" with 1 error, which is within the limit.

  • regex.search("(?e)(dog){e<=1}", "cat and dog")[1] returns "dog" (without a leading space) because the fuzzy search matches " dog" with 1 error, which is within the limit, and the (?e) then it attempts a better fit.

  In the first two examples there are perfect matches later in the string, but in neither case is it the first possible match.

  The match object has an attribute fuzzy_counts which gives the total number of substitutions, insertions and deletions.

  >>> # A 'raw' fuzzy match:
  >>> regex.fullmatch(r"(?:cats|cat){e<=1}", "cat").fuzzy_counts
  (0, 0, 1)
  >>> # 0 substitutions, 0 insertions, 1 deletion.
  
  >>> # A better match might be possible if the ENHANCEMATCH flag used:
  >>> regex.fullmatch(r"(?e)(?:cats|cat){e<=1}", "cat").fuzzy_counts
  (0, 0, 0)
  >>> # 0 substitutions, 0 insertions, 0 deletions.

  The match object also has an attribute fuzzy_changes which gives a tuple of the positions of the substitutions, insertions and deletions.

  >>> m = regex.search('(fuu){i<=2,d<=2,e<=5}', 'anaconda foo bar')
  >>> m
  <regex.Match object; span=(7, 10), match='a f', fuzzy_counts=(0, 2, 2)>
  >>> m.fuzzy_changes
  ([], [7, 8], [10, 11])

  What this means is that if the matched part of the string had been:

  'anacondfuuoo bar'

  it would’ve been an exact match.

  However, there were insertions at positions 7 and 8:

  'anaconda fuuoo bar'
          ^^

  and deletions at positions 10 and 11:

  'anaconda f~~oo bar'
             ^^

  So the actual string was:

  'anaconda foo bar'

• Named lists (Hg issue 11)

  \L<name>

  There are occasions where you may want to include a list (actually, a set) of options in a regex.

  One way is to build the pattern like this:

  >>> p = regex.compile(r"first|second|third|fourth|fifth")

  but if the list is large, parsing the resulting regex can take considerable time, and care must also be taken that the strings are properly escaped and properly ordered, for example, “cats” before “cat”.

  The new alternative is to use a named list:

  >>> option_set = ["first", "second", "third", "fourth", "fifth"]
  >>> p = regex.compile(r"\L<options>", options=option_set)

  The order of the items is irrelevant, they are treated as a set. The named lists are available as the .named_lists attribute of the pattern object :

  >>> print(p.named_lists)
  # Python 3
  {'options': frozenset({'fifth', 'first', 'fourth', 'second', 'third'})}
  # Python 2
  {'options': frozenset(['fifth', 'fourth', 'second', 'third', 'first'])}

• Start and end of word

  \m matches at the start of a word.

  \M matches at the end of a word.

  Compare with \b, which matches at the start or end of a word.

• Unicode line separators

  Normally the only line separator is \n (\x0A), but if the WORD flag is turned on then the line separators are \x0D\x0A, \x0A, \x0B, \x0C and \x0D, plus \x85, \u2028 and \u2029 when working with Unicode.

  This affects the regex dot ".", which, with the DOTALL flag turned off, matches any character except a line separator. It also affects the line anchors ^ and $ (in multiline mode).

• Set operators

  Version 1 behaviour only

  Set operators have been added, and a set [...] can include nested sets.

  The operators, in order of increasing precedence, are:

  • || for union (“x||y” means “x or y”)

  • ~~ (double tilde) for symmetric difference (“x~~y” means “x or y, but not both”)

  • && for intersection (“x&&y” means “x and y”)

  • -- (double dash) for difference (“x–y” means “x but not y”)

  Implicit union, ie, simple juxtaposition like in [ab], has the highest precedence. Thus, [ab&&cd] is the same as [[a||b]&&[c||d]].

  Examples:

  • [ab] # Set containing ‘a’ and ‘b’

  • [a-z] # Set containing ‘a’ .. ‘z’

  • [[a-z]--[qw]] # Set containing ‘a’ .. ‘z’, but not ‘q’ or ‘w’

  • [a-z--qw] # Same as above

  • [\p{L}--QW] # Set containing all letters except ‘Q’ and ‘W’

  • [\p{N}--[0-9]] # Set containing all numbers except ‘0’ .. ‘9’

  • [\p{ASCII}&&\p{Letter}] # Set containing all characters which are ASCII and letter

• regex.escape (issue #2650)

  regex.escape has an additional keyword parameter special_only. When True, only ‘special’ regex characters, such as ‘?’, are escaped.

  Examples:

  >>> regex.escape("foo!?", special_only=False)
  'foo\\!\\?'
  >>> regex.escape("foo!?", special_only=True)
  'foo!\\?'

• regex.escape (Hg issue 249)

  regex.escape has an additional keyword parameter literal_spaces. When True, spaces are not escaped.

  Examples:

  >>> regex.escape("foo bar!?", literal_spaces=False)
  'foo\\ bar!\\?'
  >>> regex.escape("foo bar!?", literal_spaces=True)
  'foo bar!\\?'

• Repeated captures (issue #7132)

  A match object has additional methods which return information on all the successful matches of a repeated capture group. These methods are:

  • matchobject.captures([group1, ...])

    • Returns a list of the strings matched in a group or groups. Compare with matchobject.group([group1, ...]).

  • matchobject.starts([group])

    • Returns a list of the start positions. Compare with matchobject.start([group]).

  • matchobject.ends([group])

    • Returns a list of the end positions. Compare with matchobject.end([group]).

  • matchobject.spans([group])

    • Returns a list of the spans. Compare with matchobject.span([group]).

  Examples:

  >>> m = regex.search(r"(\w{3})+", "123456789")
  >>> m.group(1)
  '789'
  >>> m.captures(1)
  ['123', '456', '789']
  >>> m.start(1)
  6
  >>> m.starts(1)
  [0, 3, 6]
  >>> m.end(1)
  9
  >>> m.ends(1)
  [3, 6, 9]
  >>> m.span(1)
  (6, 9)
  >>> m.spans(1)
  [(0, 3), (3, 6), (6, 9)]

• Atomic grouping (issue #433030)

  (?>...)

  If the following pattern subsequently fails, then the subpattern as a whole will fail.

• Possessive quantifiers.

  (?:...)?+ ; (?:...)*+ ; (?:...)++ ; (?:...){min,max}+

  The subpattern is matched up to ‘max’ times. If the following pattern subsequently fails, then all of the repeated subpatterns will fail as a whole. For example, (?:...)++ is equivalent to (?>(?:...)+).

• Scoped flags (issue #433028)

  (?flags-flags:...)

  The flags will apply only to the subpattern. Flags can be turned on or off.

• Definition of ‘word’ character (issue #1693050)

  The definition of a ‘word’ character has been expanded for Unicode. It now conforms to the Unicode specification at http://www.unicode.org/reports/tr29/.

• Variable-length lookbehind

  A lookbehind can match a variable-length string.

• Flags argument for regex.split, regex.sub and regex.subn (issue #3482)

  regex.split, regex.sub and regex.subn support a ‘flags’ argument.

• Pos and endpos arguments for regex.sub and regex.subn

  regex.sub and regex.subn support ‘pos’ and ‘endpos’ arguments.

• ‘Overlapped’ argument for regex.findall and regex.finditer

  regex.findall and regex.finditer support an ‘overlapped’ flag which permits overlapped matches.

• Splititer

  regex.splititer has been added. It’s a generator equivalent of regex.split.

• Subscripting for groups

  A match object accepts access to the captured groups via subscripting and slicing:

  >>> m = regex.search(r"(?P<before>.*?)(?P<num>\d+)(?P<after>.*)", "pqr123stu")
  >>> print(m["before"])
  pqr
  >>> print(len(m))
  4
  >>> print(m[:])
  ('pqr123stu', 'pqr', '123', 'stu')

• Named groups

  Groups can be named with (?<name>...) as well as the current (?P<name>...).

• Group references

  Groups can be referenced within a pattern with \g<name>. This also allows there to be more than 99 groups.

• Named characters

  \N{name}

  Named characters are supported. (Note: only those known by Python’s Unicode database are supported.)

• Unicode codepoint properties, including scripts and blocks

  \p{property=value}; \P{property=value}; \p{value} ; \P{value}

  Many Unicode properties are supported, including blocks and scripts. \p{property=value} or \p{property:value} matches a character whose property property has value value. The inverse of \p{property=value} is \P{property=value} or \p{^property=value}.

  If the short form \p{value} is used, the properties are checked in the order: General_Category, Script, Block, binary property:

  • Latin, the ‘Latin’ script (Script=Latin).

  • BasicLatin, the ‘BasicLatin’ block (Block=BasicLatin).

  • Alphabetic, the ‘Alphabetic’ binary property (Alphabetic=Yes).

  A short form starting with Is indicates a script or binary property:

  • IsLatin, the ‘Latin’ script (Script=Latin).

  • IsAlphabetic, the ‘Alphabetic’ binary property (Alphabetic=Yes).

  A short form starting with In indicates a block property:

  • InBasicLatin, the ‘BasicLatin’ block (Block=BasicLatin).

• POSIX character classes

  [[:alpha:]]; [[:^alpha:]]

  POSIX character classes are supported. These are normally treated as an alternative form of \p{...}.

  The exceptions are alnum, digit, punct and xdigit, whose definitions are different from those of Unicode.

  [[:alnum:]] is equivalent to \p{posix_alnum}.

  [[:digit:]] is equivalent to \p{posix_digit}.

  [[:punct:]] is equivalent to \p{posix_punct}.

  [[:xdigit:]] is equivalent to \p{posix_xdigit}.

• Search anchor

  \G

  A search anchor has been added. It matches at the position where each search started/continued and can be used for contiguous matches or in negative variable-length lookbehinds to limit how far back the lookbehind goes:

  >>> regex.findall(r"\w{2}", "abcd ef")
  ['ab', 'cd', 'ef']
  >>> regex.findall(r"\G\w{2}", "abcd ef")
  ['ab', 'cd']

  • The search starts at position 0 and matches 2 letters ‘ab’.

  • The search continues at position 2 and matches 2 letters ‘cd’.

  • The search continues at position 4 and fails to match any letters.

  • The anchor stops the search start position from being advanced, so there are no more results.

• Reverse searching

  Searches can now work backwards:

  >>> regex.findall(r".", "abc")
  ['a', 'b', 'c']
  >>> regex.findall(r"(?r).", "abc")
  ['c', 'b', 'a']

  Note: the result of a reverse search is not necessarily the reverse of a forward search:

  >>> regex.findall(r"..", "abcde")
  ['ab', 'cd']
  >>> regex.findall(r"(?r)..", "abcde")
  ['de', 'bc']

• Matching a single grapheme

  \X

  The grapheme matcher is supported. It now conforms to the Unicode specification at http://www.unicode.org/reports/tr29/.

• Branch reset

  (?|...|...)

  Capture group numbers will be reused across the alternatives, but groups with different names will have different group numbers.

  Examples:

  >>> regex.match(r"(?|(first)|(second))", "first").groups()
  ('first',)
  >>> regex.match(r"(?|(first)|(second))", "second").groups()
  ('second',)

  Note that there is only one group.

• Default Unicode word boundary

  The WORD flag changes the definition of a ‘word boundary’ to that of a default Unicode word boundary. This applies to \b and \B.