
``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.

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.


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 within the rest of the regular expression 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.  So the group named ``id`` in
   the example below can also be referenced as the numbered group
   ``1``.

   For example, if the pattern is ``(?P<id>[a-zA-Z_]\w*)``, the group
   can be referenced by its name in arguments to methods of match
   objects, such as ``m.group('id')`` or ``m.end('id')``, and also by
   name in the regular expression itself (using ``(?P=id)``) and
   replacement text given to ``.sub()`` (using ``\g<id>``).

``(?P=name)``
   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'`` 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 ``'the end'`` (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      \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.


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.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.

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.
   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 a 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.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 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 3.1: 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.

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 ``\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 addition to character escapes and backreferences as 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.

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.

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
==========================

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 at ...>
   >>> 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 at ...>

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

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.


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.

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()``.


Regular Expression 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 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'


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 *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


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 ...>


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(s):
       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
       ]
       tok_regex = '|'.join('(?P<%s>%s)' % pair for pair in token_specification)
       get_token = re.compile(tok_regex).match
       line = 1
       pos = line_start = 0
       mo = get_token(s)
       while mo is not None:
           typ = mo.lastgroup
           if typ == 'NEWLINE':
               line_start = pos
               line += 1
           elif typ != 'SKIP':
               val = mo.group(typ)
               if typ == 'ID' and val in keywords:
                   typ = val
               yield Token(typ, val, line, mo.start()-line_start)
           pos = mo.end()
           mo = get_token(s, pos)
       if pos != len(s):
           raise RuntimeError('Unexpected character %r on line %d' %(s[pos], line))

   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=5)
   Token(typ='ID', value='quantity', line=2, column=8)
   Token(typ='THEN', value='THEN', line=2, column=17)
   Token(typ='ID', value='total', line=3, column=9)
   Token(typ='ASSIGN', value=':=', line=3, column=15)
   Token(typ='ID', value='total', line=3, column=18)
   Token(typ='OP', value='+', line=3, column=24)
   Token(typ='ID', value='price', line=3, column=26)
   Token(typ='OP', value='*', line=3, column=32)
   Token(typ='ID', value='quantity', line=3, column=34)
   Token(typ='END', value=';', line=3, column=42)
   Token(typ='ID', value='tax', line=4, column=9)
   Token(typ='ASSIGN', value=':=', line=4, column=13)
   Token(typ='ID', value='price', line=4, column=16)
   Token(typ='OP', value='*', line=4, column=22)
   Token(typ='NUMBER', value='0.05', line=4, column=24)
   Token(typ='END', value=';', line=4, column=28)
   Token(typ='ENDIF', value='ENDIF', line=5, column=5)
   Token(typ='END', value=';', line=5, column=10)
