| Python 3.6.5 Documentation > "re" — Regular expression operations
"re" — Regular expression operations
************************************
**Source code:** Lib/re.py
======================================================================
This module provides regular expression matching operations similar to
those found in Perl.
Both patterns and strings to be searched can be Unicode strings
("str") as well as 8-bit strings ("bytes"). However, Unicode strings
and 8-bit strings cannot be mixed: that is, you cannot match a 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: The third-party regex module, which has an API compatible
with the standard library "re" module, but offers additional
functionality and a more thorough Unicode support.
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 [Frie09], 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.
Repetition qualifiers ("*", "+", "?", "{m,n}", etc) cannot be directly
nested. This avoids ambiguity with the non-greedy modifier suffix "?",
and with other modifiers in other implementations. To apply a second
repetition to an inner repetition, parentheses may be used. For
example, the expression "(?:a{6})*" matches any multiple of six "'a'"
characters.
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 "'<a> b <c>'", it will match
the entire string, and not just "'<a>'". Adding "?" after the
qualifier makes it perform the match in *non-greedy* or *minimal*
fashion; as *few* characters as possible will be matched. Using
the RE "<.*?>" will match only "'<a>'".
"{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]" or
"[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), "re.U" (Unicode matching), 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. Flags
should be used first in the expression string.
"(?:...)"
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.
"(?imsx-imsx:...)"
(Zero or more letters from the set "'i'", "'m'", "'s'", "'x'",
optionally followed by "'-'" followed by one or more letters from
the same set.) The letters set or removes the corresponding flags:
"re.I" (ignore case), "re.M" (multi-line), "re.S" (dot matches
all), and "re.X" (verbose), for the part of the expression. (The
flags are described in Module Contents.)
New in version 3.6.
"(?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(r'(?<=-)\w+', 'spam-egg')
>>> m.group(0)
'egg'
Changed in version 3.5: Added support for group references of fixed
length.
"(?<!...)"
Matches if the current position in the string is not preceded by a
match for "...". This is called a *negative lookbehind assertion*.
Similar to positive lookbehind assertions, the contained pattern
must only match strings of some fixed length. Patterns which start
with negative lookbehind assertions may match at the beginning of
the string being searched.
"(?(id/name)yes-pattern|no-pattern)"
Will try to match with "yes-pattern" if the group with given *id*
or *name* exists, and with "no-pattern" if it doesn’t. "no-pattern"
is optional and can be omitted. For example,
"(<)?(\w+@\w+(?:\.\w+)+)(?(1)>|$)" is a poor email matching
pattern, which will match with "'<user@host.com>'" as well as
"'user@host.com'", but not with "'<user@host.com'" nor
"'user@host.com>'".
The special sequences consist of "'\'" and a character from the list
below. If the ordinary character is not an ASCII digit or an ASCII
letter, then the resulting RE will match the second character. For
example, "\$" matches the character "'$'".
"\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 word characters. 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 in Unicode
patterns, but this can be changed by using the "ASCII" flag. Word
boundaries are determined by the current locale if the "LOCALE"
flag is used. 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 in Unicode
patterns are Unicode alphanumerics or the underscore, although this
can be changed by using the "ASCII" flag. Word boundaries are
determined by the current locale if the "LOCALE" flag is used.
"\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 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 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_]". If the
"LOCALE" flag is used, matches characters considered
alphanumeric in the current locale and the underscore.
"\W"
Matches any character which is not a 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). If the "LOCALE" flag is
used, matches characters considered alphanumeric in the current
locale and the underscore.
"\Z"
Matches only at the end of the string.
Most of the standard escapes supported by Python string literals are
also accepted by the regular expression parser:
\a \b \f \n
\r \t \u \U
\v \x \\
(Note that "\b" is used to represent word boundaries, and means
“backspace” only inside character classes.)
"'\u'" and "'\U'" escape sequences are only recognized in Unicode
patterns. In bytes patterns they are errors.
Octal escapes are included in a limited form. If the first digit is a
0, or if there are three octal digits, it is considered an octal
escape. Otherwise, it is a group reference. As for string literals,
octal escapes are always at most three digits in length.
Changed in version 3.3: The "'\u'" and "'\U'" escape sequences have
been added.
Changed in version 3.6: Unknown escapes consisting of "'\'" and an
ASCII letter now are errors.
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.
Changed in version 3.6: Flag constants are now instances of
"RegexFlag", which is a subclass of "enum.IntFlag".
re.compile(pattern, flags=0)
Compile a regular expression pattern into a regular expression
object, which can be used for matching using its "match()",
"search()" and other methods, described below.
The expression’s behaviour can be modified by specifying a *flags*
value. Values can be any of the following variables, combined using
bitwise OR (the "|" operator).
The sequence
prog = re.compile(pattern)
result = prog.match(string)
is equivalent to
result = re.match(pattern, string)
but using "re.compile()" and saving the resulting regular
expression object for reuse is more efficient when the expression
will be used several times in a single program.
Note: The compiled versions of the most recent patterns passed to
"re.compile()" and the module-level matching functions are
cached, so programs that use only a few regular expressions at a
time needn’t worry about compiling regular expressions.
re.A
re.ASCII
Make "\w", "\W", "\b", "\B", "\d", "\D", "\s" and "\S" perform
ASCII-only matching instead of full Unicode matching. This is only
meaningful for Unicode patterns, and is ignored for byte patterns.
Corresponds to the inline flag "(?a)".
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. No
corresponding inline flag.
re.I
re.IGNORECASE
Perform case-insensitive matching; expressions like "[A-Z]" will
also match lowercase letters. Full Unicode matching (such as "Ü"
matching "ü") also works unless the "re.ASCII" flag is used to
disable non-ASCII matches. The current locale does not change the
effect of this flag unless the "re.LOCALE" flag is also used.
Corresponds to the inline flag "(?i)".
Note that when the Unicode patterns "[a-z]" or "[A-Z]" are used in
combination with the "IGNORECASE" flag, they will match the 52
ASCII letters and 4 additional non-ASCII letters: ‘?’ (U+0130,
Latin capital letter I with dot above), ‘?’ (U+0131, Latin small
letter dotless i), ‘?’ (U+017F, Latin small letter long s) and ‘?’
(U+212A, Kelvin sign). If the "ASCII" flag is used, only letters
‘a’ to ‘z’ and ‘A’ to ‘Z’ are matched (but the flag affects the
entire regular expression, so in such cases using an explicit
"(?-i:[a-zA-Z])" may be a better choice).
re.L
re.LOCALE
Make "\w", "\W", "\b", "\B" and case-insensitive matching dependent
on the current locale. This flag can be used only with bytes
patterns. The use of this flag is discouraged as the locale
mechanism is very unreliable, it only handles one “culture” at a
time, and it only works with 8-bit locales. Unicode matching is
already enabled by default in Python 3 for Unicode (str) patterns,
and it is able to handle different locales/languages. Corresponds
to the inline flag "(?L)".
Changed in version 3.6: "re.LOCALE" can be used only with bytes
patterns and is not compatible with "re.ASCII".
re.M
re.MULTILINE
When specified, the pattern character "'^'" matches at the
beginning of the string and at the beginning of each line
(immediately following each newline); and the pattern character
"'$'" matches at the end of the string and at the end of each line
(immediately preceding each newline). By default, "'^'" matches
only at the beginning of the string, and "'$'" only at the end of
the string and immediately before the newline (if any) at the end
of the string. Corresponds to the inline flag "(?m)".
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. Corresponds to the inline flag "(?s)".
re.X
re.VERBOSE
This flag allows you to write regular expressions that look nicer
and are more readable by allowing you to visually separate logical
sections of the pattern and add comments. Whitespace within the
pattern is ignored, except when in a character class, or when
preceded by an unescaped backslash, or within tokens like "*?",
"(?:" or "(?P<...>". When a line contains a "#" that is not in a
character class and is not preceded by an unescaped backslash, all
characters from the leftmost such "#" through the end of the line
are ignored.
This means that the two following regular expression objects that
match a decimal number are functionally equal:
a = re.compile(r"""\d + # the integral part
\. # the decimal point
\d * # some fractional digits""", re.X)
b = re.compile(r"\d+\.\d*")
Corresponds to the inline flag "(?x)".
re.search(pattern, string, flags=0)
Scan through *string* looking for the first location where the
regular expression *pattern* produces a match, and return a
corresponding match object. Return "None" if no position in the
string matches the pattern; note that this is different from
finding a zero-length match at some point in the string.
re.match(pattern, string, flags=0)
If zero or more characters at the beginning of *string* match the
regular expression *pattern*, return a corresponding match object.
Return "None" if the string does not match the pattern; note that
this is different from a zero-length match.
Note that even in "MULTILINE" mode, "re.match()" will only match at
the beginning of the string and not at the beginning of each line.
If you want to locate a match anywhere in *string*, use "search()"
instead (see also search() vs. match()).
re.fullmatch(pattern, string, flags=0)
If the whole *string* matches the regular expression *pattern*,
return a corresponding match object. Return "None" if the string
does not match the pattern; note that this is different from a
zero-length match.
New in version 3.4.
re.split(pattern, string, maxsplit=0, flags=0)
Split *string* by the occurrences of *pattern*. If capturing
parentheses are used in *pattern*, then the text of all groups in
the pattern are also returned as part of the resulting list. If
*maxsplit* is nonzero, at most *maxsplit* splits occur, and the
remainder of the string is returned as the final element of the
list.
>>> re.split(r'\W+', 'Words, words, words.')
['Words', 'words', 'words', '']
>>> re.split(r'(\W+)', 'Words, words, words.')
['Words', ', ', 'words', ', ', 'words', '.', '']
>>> re.split(r'\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(r'(\W+)', '...words, words...')
['', '...', 'words', ', ', 'words', '...', '']
That way, separator components are always found at the same
relative indices within the result list.
Note: "split()" doesn’t currently split a string on an empty
pattern match. For example:
>>> re.split('x*', 'axbc')
['a', 'bc']
Even though "'x*'" also matches 0 ‘x’ before ‘a’, between ‘b’ and
‘c’, and after ‘c’, currently these matches are ignored. The
correct behavior (i.e. splitting on empty matches too and
returning "['', 'a', 'b', 'c', '']") will be implemented in
future versions of Python, but since this is a backward
incompatible change, a "FutureWarning" will be raised in the
meanwhile.Patterns that can only match empty strings currently
never split the string. Since this doesn’t match the expected
behavior, a "ValueError" will be raised starting from Python 3.5:
>>> re.split("^$", "foo\n\nbar\n", flags=re.M)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
...
ValueError: split() requires a non-empty pattern match.
Changed in version 3.1: Added the optional flags argument.
Changed in version 3.5: Splitting on a pattern that could match an
empty string now raises a warning. Patterns that can only match
empty strings are now rejected.
re.findall(pattern, string, flags=0)
Return all non-overlapping matches of *pattern* in *string*, as a
list of strings. The *string* is scanned left-to-right, and
matches are returned in the order found. If one or more groups are
present in the pattern, return a list of groups; this will be a
list of tuples if the pattern has more than one group. Empty
matches are included in the result.
Note: Due to the limitation of the current implementation the
character following an empty match is not included in a next
match, so "findall(r'^|\w+', 'two words')" returns "['', 'wo',
'words']" (note missed “t”). This is changed in Python 3.7.
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. See also the
note about "findall()".
re.sub(pattern, repl, string, count=0, flags=0)
Return the string obtained by replacing the leftmost non-
overlapping occurrences of *pattern* in *string* by the replacement
*repl*. If the pattern isn’t found, *string* is returned
unchanged. *repl* can be a string or a function; if it is a
string, any backslash escapes in it are processed. That is, "\n"
is converted to a single newline character, "\r" is converted to a
carriage return, and so forth. Unknown escapes such as "\&" are
left alone. Backreferences, such as "\6", are replaced with the
substring matched by group 6 in the pattern. For example:
>>> re.sub(r'def\s+([a-zA-Z_][a-zA-Z_0-9]*)\s*\(\s*\):',
... r'static PyObject*\npy_\1(void)\n{',
... 'def myfunc():')
'static PyObject*\npy_myfunc(void)\n{'
If *repl* is a function, it is called for every non-overlapping
occurrence of *pattern*. The function takes a single match object
argument, and returns the replacement string. For example:
>>> def dashrepl(matchobj):
... if matchobj.group(0) == '-': return ' '
... else: return '-'
>>> re.sub('-{1,2}', dashrepl, 'pro----gram-files')
'pro--gram files'
>>> re.sub(r'\sAND\s', ' & ', 'Baked Beans And Spam', flags=re.IGNORECASE)
'Baked Beans & Spam'
The pattern may be a string or a pattern object.
The optional argument *count* is the maximum number of pattern
occurrences to be replaced; *count* must be a non-negative integer.
If omitted or zero, all occurrences will be replaced. Empty matches
for the pattern are replaced only when not adjacent to a previous
match, so "sub('x*', '-', 'abc')" returns "'-a-b-c-'".
In string-type *repl* arguments, in addition to the character
escapes and backreferences described above, "\g<name>" will use the
substring matched by the group named "name", as defined by the
"(?P<name>...)" syntax. "\g<number>" uses the corresponding group
number; "\g<2>" is therefore equivalent to "\2", but isn’t
ambiguous in a replacement such as "\g<2>0". "\20" would be
interpreted as a reference to group 20, not a reference to group 2
followed by the literal character "'0'". The backreference "\g<0>"
substitutes in the entire substring matched by the RE.
Changed in version 3.1: Added the optional flags argument.
Changed in version 3.5: Unmatched groups are replaced with an empty
string.
Changed in version 3.6: Unknown escapes in *pattern* consisting of
"'\'" and an ASCII letter now are errors.
Deprecated since version 3.5, will be removed in version 3.7:
Unknown escapes in *repl* consisting of "'\'" and an ASCII letter
now raise a deprecation warning and will be forbidden in Python
3.7.
re.subn(pattern, repl, string, count=0, flags=0)
Perform the same operation as "sub()", but return a tuple
"(new_string, number_of_subs_made)".
Changed in version 3.1: Added the optional flags argument.
Changed in version 3.5: Unmatched groups are replaced with an empty
string.
re.escape(pattern)
Escape all the characters in *pattern* except ASCII letters,
numbers and "'_'". This is useful if you want to match an arbitrary
literal string that may have regular expression metacharacters in
it. For example:
>>> print(re.escape('python.exe'))
python\.exe
>>> legal_chars = string.ascii_lowercase + string.digits + "!#$%&'*+-.^_`|~:"
>>> print('[%s]+' % re.escape(legal_chars))
[abcdefghijklmnopqrstuvwxyz0123456789\!\#\$\%\&\'\*\+\-\.\^_\`\|\~\:]+
>>> operators = ['+', '-', '*', '/', '**']
>>> print('|'.join(map(re.escape, sorted(operators, reverse=True))))
\/|\-|\+|\*\*|\*
This functions must not be used for the replacement string in
"sub()" and "subn()", only backslashes should be escaped. For
example:
>>> digits_re = r'\d+'
>>> sample = '/usr/sbin/sendmail - 0 errors, 12 warnings'
>>> print(re.sub(digits_re, digits_re.replace('\\', r'\\'), sample))
/usr/sbin/sendmail - \d+ errors, \d+ warnings
Changed in version 3.3: The "'_'" character is no longer escaped.
re.purge()
Clear the regular expression cache.
exception re.error(msg, pattern=None, pos=None)
Exception raised when a string passed to one of the functions here
is not a valid regular expression (for example, it might contain
unmatched parentheses) or when some other error occurs during
compilation or matching. It is never an error if a string contains
no match for a pattern. The error instance has the following
additional attributes:
msg
The unformatted error message.
pattern
The regular expression pattern.
pos
The index in *pattern* where compilation failed (may be "None").
lineno
The line corresponding to *pos* (may be "None").
colno
The column corresponding to *pos* (may be "None").
Changed in version 3.5: Added additional attributes.
Regular Expression Objects
==========================
Compiled regular expression objects support the following methods and
attributes:
regex.search(string[, pos[, endpos]])
Scan through *string* looking for the first location where this
regular expression produces a match, and return a corresponding
match object. Return "None" if no position in the string matches
the pattern; note that this is different from finding a zero-length
match at some point in the string.
The optional second parameter *pos* gives an index in the string
where the search is to start; it defaults to "0". This is not
completely equivalent to slicing the string; the "'^'" pattern
character matches at the real beginning of the string and at
positions just after a newline, but not necessarily at the index
where the search is to start.
The optional parameter *endpos* limits how far the string will be
searched; it will be as if the string is *endpos* characters long,
so only the characters from *pos* to "endpos - 1" will be searched
for a match. If *endpos* is less than *pos*, no match will be
found; otherwise, if *rx* is a compiled regular expression object,
"rx.search(string, 0, 50)" is equivalent to "rx.search(string[:50],
0)".
>>> pattern = re.compile("d")
>>> pattern.search("dog") # Match at index 0
<_sre.SRE_Match object; span=(0, 1), match='d'>
>>> pattern.search("dog", 1) # No match; search doesn't include the "d"
regex.match(string[, pos[, endpos]])
If zero or more characters at the *beginning* of *string* match
this regular expression, return a corresponding match object.
Return "None" if the string does not match the pattern; note that
this is different from a zero-length match.
The optional *pos* and *endpos* parameters have the same meaning as
for the "search()" method.
>>> pattern = re.compile("o")
>>> pattern.match("dog") # No match as "o" is not at the start of "dog".
>>> pattern.match("dog", 1) # Match as "o" is the 2nd character of "dog".
<_sre.SRE_Match object; span=(1, 2), match='o'>
If you want to locate a match anywhere in *string*, use "search()"
instead (see also search() vs. match()).
regex.fullmatch(string[, pos[, endpos]])
If the whole *string* matches this regular expression, return a
corresponding match object. Return "None" if the string does not
match the pattern; note that this is different from a zero-length
match.
The optional *pos* and *endpos* parameters have the same meaning as
for the "search()" method.
>>> pattern = re.compile("o[gh]")
>>> pattern.fullmatch("dog") # No match as "o" is not at the start of "dog".
>>> pattern.fullmatch("ogre") # No match as not the full string matches.
>>> pattern.fullmatch("doggie", 1, 3) # Matches within given limits.
<_sre.SRE_Match object; span=(1, 3), match='og'>
New in version 3.4.
regex.split(string, maxsplit=0)
Identical to the "split()" function, using the compiled pattern.
regex.findall(string[, pos[, endpos]])
Similar to the "findall()" function, using the compiled pattern,
but also accepts optional *pos* and *endpos* parameters that limit
the search region like for "search()".
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 "search()".
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.
Changed in version 3.5: Unmatched groups are replaced with an empty
string.
match.group([group1, ...])
Returns one or more subgroups of the match. If there is a single
argument, the result is a single string; if there are multiple
arguments, the result is a tuple with one item per argument.
Without arguments, *group1* defaults to zero (the whole match is
returned). If a *groupN* argument is zero, the corresponding return
value is the entire matching string; if it is in the inclusive
range [1..99], it is the string matching the corresponding
parenthesized group. If a group number is negative or larger than
the number of groups defined in the pattern, an "IndexError"
exception is raised. If a group is contained in a part of the
pattern that did not match, the corresponding result is "None". If
a group is contained in a part of the pattern that matched multiple
times, the last match is returned.
>>> m = re.match(r"(\w+) (\w+)", "Isaac Newton, physicist")
>>> m.group(0) # The entire match
'Isaac Newton'
>>> m.group(1) # The first parenthesized subgroup.
'Isaac'
>>> m.group(2) # The second parenthesized subgroup.
'Newton'
>>> m.group(1, 2) # Multiple arguments give us a tuple.
('Isaac', 'Newton')
If the regular expression uses the "(?P<name>...)" syntax, the
*groupN* arguments may also be strings identifying groups by their
group name. If a string argument is not used as a group name in
the pattern, an "IndexError" exception is raised.
A moderately complicated example:
>>> m = re.match(r"(?P<first_name>\w+) (?P<last_name>\w+)", "Malcolm Reynolds")
>>> m.group('first_name')
'Malcolm'
>>> m.group('last_name')
'Reynolds'
Named groups can also be referred to by their index:
>>> m.group(1)
'Malcolm'
>>> m.group(2)
'Reynolds'
If a group matches multiple times, only the last match is
accessible:
>>> m = re.match(r"(..)+", "a1b2c3") # Matches 3 times.
>>> m.group(1) # Returns only the last match.
'c3'
match.__getitem__(g)
This is identical to "m.group(g)". This allows easier access to an
individual group from a match:
>>> m = re.match(r"(\w+) (\w+)", "Isaac Newton, physicist")
>>> m[0] # The entire match
'Isaac Newton'
>>> m[1] # The first parenthesized subgroup.
'Isaac'
>>> m[2] # The second parenthesized subgroup.
'Newton'
New in version 3.6.
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; span=(2, 3), match='c'>
Regular expressions beginning with "'^'" can be used with "search()"
to restrict the match at the beginning of the string:
>>> re.match("c", "abcdef") # No match
>>> re.search("^c", "abcdef") # No match
>>> re.search("^a", "abcdef") # Match
<_sre.SRE_Match object; span=(0, 1), match='a'>
Note however that in "MULTILINE" mode "match()" only matches at the
beginning of the string, whereas using "search()" with a regular
expression beginning with "'^'" will match at the beginning of each
line.
>>> re.match('X', 'A\nB\nX', re.MULTILINE) # No match
>>> re.search('^X', 'A\nB\nX', re.MULTILINE) # Match
<_sre.SRE_Match object; span=(4, 5), match='X'>
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; span=(0, 4), match=' ff '>
>>> re.match("\\W(.)\\1\\W", " ff ")
<_sre.SRE_Match object; span=(0, 4), match=' ff '>
When one wants to match a literal backslash, it must be escaped in the
regular expression. With raw string notation, this means "r"\\"".
Without raw string notation, one must use ""\\\\"", making the
following lines of code functionally identical:
>>> re.match(r"\\", r"\\")
<_sre.SRE_Match object; span=(0, 1), match='\\'>
>>> re.match("\\\\", r"\\")
<_sre.SRE_Match object; span=(0, 1), match='\\'>
Writing a Tokenizer
-------------------
A tokenizer or scanner analyzes a string to categorize groups of
characters. This is a useful first step in writing a compiler or
interpreter.
The text categories are specified with regular expressions. The
technique is to combine those into a single master regular expression
and to loop over successive matches:
import collections
import re
Token = collections.namedtuple('Token', ['typ', 'value', 'line', 'column'])
def tokenize(code):
keywords = {'IF', 'THEN', 'ENDIF', 'FOR', 'NEXT', 'GOSUB', 'RETURN'}
token_specification = [
('NUMBER', r'\d+(\.\d*)?'), # Integer or decimal number
('ASSIGN', r':='), # Assignment operator
('END', r';'), # Statement terminator
('ID', r'[A-Za-z]+'), # Identifiers
('OP', r'[+\-*/]'), # Arithmetic operators
('NEWLINE', r'\n'), # Line endings
('SKIP', r'[ \t]+'), # Skip over spaces and tabs
('MISMATCH',r'.'), # Any other character
]
tok_regex = '|'.join('(?P<%s>%s)' % pair for pair in token_specification)
line_num = 1
line_start = 0
for mo in re.finditer(tok_regex, code):
kind = mo.lastgroup
value = mo.group(kind)
if kind == 'NEWLINE':
line_start = mo.end()
line_num += 1
elif kind == 'SKIP':
pass
elif kind == 'MISMATCH':
raise RuntimeError(f'{value!r} unexpected on line {line_num}')
else:
if kind == 'ID' and value in keywords:
kind = value
column = mo.start() - line_start
yield Token(kind, value, line_num, column)
statements = '''
IF quantity THEN
total := total + price * quantity;
tax := price * 0.05;
ENDIF;
'''
for token in tokenize(statements):
print(token)
The tokenizer produces the following output:
Token(typ='IF', value='IF', line=2, column=4)
Token(typ='ID', value='quantity', line=2, column=7)
Token(typ='THEN', value='THEN', line=2, column=16)
Token(typ='ID', value='total', line=3, column=8)
Token(typ='ASSIGN', value=':=', line=3, column=14)
Token(typ='ID', value='total', line=3, column=17)
Token(typ='OP', value='+', line=3, column=23)
Token(typ='ID', value='price', line=3, column=25)
Token(typ='OP', value='*', line=3, column=31)
Token(typ='ID', value='quantity', line=3, column=33)
Token(typ='END', value=';', line=3, column=41)
Token(typ='ID', value='tax', line=4, column=8)
Token(typ='ASSIGN', value=':=', line=4, column=12)
Token(typ='ID', value='price', line=4, column=15)
Token(typ='OP', value='*', line=4, column=21)
Token(typ='NUMBER', value='0.05', line=4, column=23)
Token(typ='END', value=';', line=4, column=27)
Token(typ='ENDIF', value='ENDIF', line=5, column=4)
Token(typ='END', value=';', line=5, column=9)
[Frie09] Friedl, Jeffrey. Mastering Regular Expressions. 3rd
ed., O’Reilly Media, 2009. The third edition of the book no
longer covers Python at all, but the first edition covered
writing good regular expression patterns in great detail.
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