
"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.

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 "RegexObject" methods.  The
functions are shortcuts that don't require you to compile a regex
object first, but miss some fine-tuning parameters.


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 the "\number" notation, e.g., "'\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 "LOCALE" or  "UNICODE" 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.

"(?iLmsux)"
   (One or more letters from the set "'i'", "'L'", "'m'", "'s'",
   "'u'", "'x'".)  The group matches the empty string; the letters set
   the corresponding flags: "re.I" (ignore case), "re.L" (locale
   dependent), "re.M" (multi-line), "re.S" (dot matches all), "re.U"
   (Unicode dependent), 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"        | * "\g<quote>"  * "\g<1>"  * "\1"   |
   | argument of "re.sub()"                  |                                    |
   +-----------------------------------------+------------------------------------+

"(?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'

"(?<!...)"
   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'".

   New in version 2.4.

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 alphanumeric or
   underscore characters, so the end of a word is indicated by
   whitespace or a non-alphanumeric, non-underscore 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, so the precise set of characters
   deemed to be alphanumeric depends on the values of the "UNICODE"
   and "LOCALE" flags. For example, "r'\bfoo\b'" matches "'foo'",
   "'foo.'", "'(foo)'", "'bar foo baz'" but not "'foobar'" or
   "'foo3'". 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 is also subject to the
   settings of "LOCALE" and "UNICODE".

"\d"
   When the "UNICODE" flag is not specified, matches any decimal
   digit; this is equivalent to the set "[0-9]".  With "UNICODE", it
   will match whatever is classified as a decimal digit in the Unicode
   character properties database.

"\D"
   When the "UNICODE" flag is not specified, matches any non-digit
   character; this is equivalent to the set  "[^0-9]".  With
   "UNICODE", it will match  anything other than character marked as
   digits in the Unicode character  properties database.

"\s"
   When the "UNICODE" flag is not specified, it matches any whitespace
   character, this is equivalent to the set "[ \t\n\r\f\v]". The
   "LOCALE" flag has no extra effect on matching of the space. If
   "UNICODE" is set, this will match the characters "[ \t\n\r\f\v]"
   plus whatever is classified as space in the Unicode character
   properties database.

"\S"
   When the "UNICODE" flag is not specified, matches any non-
   whitespace character; this is equivalent to the set "[^
   \t\n\r\f\v]" The "LOCALE" flag has no extra effect on non-
   whitespace match.  If "UNICODE" is set, then any character not
   marked as space in the Unicode character properties database is
   matched.

"\w"
   When the "LOCALE" and "UNICODE" flags are not specified, matches
   any alphanumeric character and the underscore; this is equivalent
   to the set "[a-zA-Z0-9_]".  With "LOCALE", it will match the set
   "[0-9_]" plus whatever characters are defined as alphanumeric for
   the current locale.  If "UNICODE" is set, this will match the
   characters "[0-9_]" plus whatever is classified as alphanumeric in
   the Unicode character properties database.

"\W"
   When the "LOCALE" and "UNICODE" flags are not specified, matches
   any non-alphanumeric character; this is equivalent to the set
   "[^a-zA-Z0-9_]". With "LOCALE", it will match any character not in
   the set "[0-9_]", and not defined as alphanumeric for the current
   locale. If "UNICODE" is set, this will match anything other than
   "[0-9_]" plus characters classified as not alphanumeric in the
   Unicode character properties database.

"\Z"
   Matches only at the end of the string.

If both "LOCALE" and "UNICODE" flags are included for a particular
sequence, then "LOCALE" flag takes effect first followed by the
"UNICODE".

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

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

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

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.

See also: Mastering Regular Expressions

     Book on regular expressions by Jeffrey Friedl, published by
     O'Reilly.  The second edition of the book no longer covers Python
     at all, but the first edition covered writing good regular
     expression patterns in great detail.


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.match()", "re.search()" or "re.compile()" are cached, so
     programs that use only a few regular expressions at a time
     needn't worry about compiling regular expressions.

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.

re.L
re.LOCALE

   Make "\w", "\W", "\b", "\B", "\s" and "\S" dependent on the current
   locale.

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.U
re.UNICODE

   Make "\w", "\W", "\b", "\B", "\d", "\D", "\s" and "\S" dependent on
   the Unicode character properties database.

   New in version 2.0.

re.X
re.VERBOSE

   This flag allows you to write regular expressions that look nicer.
   Whitespace within the pattern is ignored, except when in a
   character class or preceded by an unescaped backslash, and, when a
   line contains a "'#'" neither in a character class or preceded by
   an unescaped backslash, all characters from the leftmost such "'#'"
   through the end of the line are ignored.

   That 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 "MatchObject" instance. 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 "MatchObject"
   instance. 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.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.  (Incompatibility note: in the original Python 1.5 release,
   *maxsplit* was ignored.  This has been fixed in later releases.)

   >>> 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 (e.g., if there's one
   capturing group in the separator, the 0th, the 2nd and so forth).

   Note that *split* will never split a string on an empty pattern
   match. For example:

   >>> re.split('x*', 'foo')
   ['foo']
   >>> re.split("(?m)^$", "foo\n\nbar\n")
   ['foo\n\nbar\n']

   Changed in version 2.7: Added the optional flags argument.

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.

   New in version 1.5.2.

   Changed in version 2.4: Added the optional flags argument.

re.finditer(pattern, string, flags=0)

   Return an *iterator* yielding "MatchObject" instances 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.

   New in version 2.2.

   Changed in version 2.4: Added the optional flags argument.

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 "\j" 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 2.7: Added the optional flags argument.

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 2.7: Added the optional flags argument.

re.escape(string)

   Return *string* with all non-alphanumerics backslashed; this is
   useful if you want to match an arbitrary literal string that may
   have regular expression metacharacters in it.

re.purge()

   Clear the regular expression cache.

exception exception re.error

   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.


Regular Expression Objects
==========================

class class re.RegexObject

   The "RegexObject" class supports the following methods and
   attributes:

   search(string[, pos[, endpos]])

      Scan through *string* looking for a location where this regular
      expression produces a match, and return a corresponding
      "MatchObject" instance. 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 at ...>
      >>> pattern.search("dog", 1)  # No match; search doesn't include the "d"

   match(string[, pos[, endpos]])

      If zero or more characters at the *beginning* of *string* match
      this regular expression, return a corresponding "MatchObject"
      instance.  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 at ...>

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

   split(string, maxsplit=0)

      Identical to the "split()" function, using the compiled pattern.

   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()".

   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()".

   sub(repl, string, count=0)

      Identical to the "sub()" function, using the compiled pattern.

   subn(repl, string, count=0)

      Identical to the "subn()" function, using the compiled pattern.

   flags

      The regex matching flags.  This is a combination of the flags
      given to "compile()" and any "(?...)" inline flags in the
      pattern.

   groups

      The number of capturing groups in the pattern.

   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.

   pattern

      The pattern string from which the RE object was compiled.


Match Objects
=============

class class re.MatchObject

   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:

   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.

   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'

   groups([default])

      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".  (Incompatibility note: in the
      original Python 1.5 release, if the tuple was one element long,
      a string would be returned instead.  In later versions (from
      1.5.1 on), a singleton tuple is returned in such cases.)

      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')

   groupdict([default])

      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'}

   start([group])
   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'

   span([group])

      For "MatchObject" *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.

   pos

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

   endpos

      The value of *endpos* which was passed to the "search()" or
      "match()" method of the "RegexObject".  This is the index into
      the string beyond which the RE engine will not go.

   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.

   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.

   re

      The regular expression object whose "match()" or "search()"
      method produced this "MatchObject" instance.

   string

      The string passed to "match()" or "search()".


Examples
========


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 "MatchObject" 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'


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


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 at ...>

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 at ...>

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 at ...>


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']]


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.'


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']


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 instances of
"MatchObject" 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


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 at ...>
>>> re.match("\\W(.)\\1\\W", " ff ")
<_sre.SRE_Match object at ...>

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 at ...>
>>> re.match("\\\\", r"\\")
<_sre.SRE_Match object at ...>
