Value between opening and closing bracket [duplicate] - regex

I'm trying to match a mathematical-expression-like string, that have nested parentheses.
import re
p = re.compile('\(.+\)')
str = '(((1+0)+1)+1)'
print p.findall(s)
['(((1+0)+1)+1)']
I wanted it to match all the enclosed expressions, such as (1+0), ((1+0)+1)...
I don't even care if it matches unwanted ones like (((1+0), I can take care of those.
Why it's not doing that already, and how can I do it?

As others have mentioned, regular expressions are not the way to go for nested constructs. I'll give a basic example using pyparsing:
import pyparsing # make sure you have this installed
thecontent = pyparsing.Word(pyparsing.alphanums) | '+' | '-'
parens = pyparsing.nestedExpr( '(', ')', content=thecontent)
Here's a usage example:
>>> parens.parseString("((a + b) + c)")
Output:
( # all of str
[
( # ((a + b) + c)
[
( # (a + b)
['a', '+', 'b'], {}
), # (a + b) [closed]
'+',
'c'
], {}
) # ((a + b) + c) [closed]
], {}
) # all of str [closed]
(With newlining/indenting/comments done manually)
Edit: Modified to eliminate unnecessary Forward, as per Paul McGuire's suggestions.
To get the output in nested list format:
res = parens.parseString("((12 + 2) + 3)")
res.asList()
Output:
[[['12', '+', '2'], '+', '3']]

There is a new regular engine module being prepared to replace the existing one in Python. It introduces a lot of new functionality, including recursive calls.
import regex
s = 'aaa(((1+0)+1)+1)bbb'
result = regex.search(r'''
(?<rec> #capturing group rec
\( #open parenthesis
(?: #non-capturing group
[^()]++ #anyting but parenthesis one or more times without backtracking
| #or
(?&rec) #recursive substitute of group rec
)*
\) #close parenthesis
)
''',s,flags=regex.VERBOSE)
print(result.captures('rec'))
Output:
['(1+0)', '((1+0)+1)', '(((1+0)+1)+1)']
Related bug in regex: http://code.google.com/p/mrab-regex-hg/issues/detail?id=78

Regex languages aren't powerful enough to matching arbitrarily nested constructs. For that you need a push-down automaton (i.e., a parser). There are several such tools available, such as PLY.
Python also provides a parser library for its own syntax, which might do what you need. The output is extremely detailed, however, and takes a while to wrap your head around. If you're interested in this angle, the following discussion tries to explain things as simply as possible.
>>> import parser, pprint
>>> pprint.pprint(parser.st2list(parser.expr('(((1+0)+1)+1)')))
[258,
[327,
[304,
[305,
[306,
[307,
[308,
[310,
[311,
[312,
[313,
[314,
[315,
[316,
[317,
[318,
[7, '('],
[320,
[304,
[305,
[306,
[307,
[308,
[310,
[311,
[312,
[313,
[314,
[315,
[316,
[317,
[318,
[7, '('],
[320,
[304,
[305,
[306,
[307,
[308,
[310,
[311,
[312,
[313,
[314,
[315,
[316,
[317,
[318,
[7,
'('],
[320,
[304,
[305,
[306,
[307,
[308,
[310,
[311,
[312,
[313,
[314,
[315,
[316,
[317,
[318,
[2,
'1']]]]],
[14,
'+'],
[315,
[316,
[317,
[318,
[2,
'0']]]]]]]]]]]]]]]],
[8,
')']]]]],
[14,
'+'],
[315,
[316,
[317,
[318,
[2,
'1']]]]]]]]]]]]]]]],
[8, ')']]]]],
[14, '+'],
[315,
[316,
[317,
[318, [2, '1']]]]]]]]]]]]]]]],
[8, ')']]]]]]]]]]]]]]]],
[4, ''],
[0, '']]
You can ease the pain with this short function:
def shallow(ast):
if not isinstance(ast, list): return ast
if len(ast) == 2: return shallow(ast[1])
return [ast[0]] + [shallow(a) for a in ast[1:]]
>>> pprint.pprint(shallow(parser.st2list(parser.expr('(((1+0)+1)+1)'))))
[258,
[318,
'(',
[314,
[318, '(', [314, [318, '(', [314, '1', '+', '0'], ')'], '+', '1'], ')'],
'+',
'1'],
')'],
'',
'']
The numbers come from the Python modules symbol and token, which you can use to build a lookup table from numbers to names:
map = dict(token.tok_name.items() + symbol.sym_name.items())
You could even fold this mapping into the shallow() function so you can work with strings instead of numbers:
def shallow(ast):
if not isinstance(ast, list): return ast
if len(ast) == 2: return shallow(ast[1])
return [map[ast[0]]] + [shallow(a) for a in ast[1:]]
>>> pprint.pprint(shallow(parser.st2list(parser.expr('(((1+0)+1)+1)'))))
['eval_input',
['atom',
'(',
['arith_expr',
['atom',
'(',
['arith_expr',
['atom', '(', ['arith_expr', '1', '+', '0'], ')'],
'+',
'1'],
')'],
'+',
'1'],
')'],
'',
'']

The regular expression tries to match as much of the text as possible, thereby consuming all of your string. It doesn't look for additional matches of the regular expression on parts of that string. That's why you only get one answer.
The solution is to not use regular expressions. If you are actually trying to parse math expressions, use a real parsing solutions. If you really just want to capture the pieces within parenthesis, just loop over the characters counting when you see ( and ) and increment a decrement a counter.

Stack is the best tool for the job: -
import re
def matches(line, opendelim='(', closedelim=')'):
stack = []
for m in re.finditer(r'[{}{}]'.format(opendelim, closedelim), line):
pos = m.start()
if line[pos-1] == '\\':
# skip escape sequence
continue
c = line[pos]
if c == opendelim:
stack.append(pos+1)
elif c == closedelim:
if len(stack) > 0:
prevpos = stack.pop()
# print("matched", prevpos, pos, line[prevpos:pos])
yield (prevpos, pos, len(stack))
else:
# error
print("encountered extraneous closing quote at pos {}: '{}'".format(pos, line[pos:] ))
pass
if len(stack) > 0:
for pos in stack:
print("expecting closing quote to match open quote starting at: '{}'"
.format(line[pos-1:]))
In the client code, since the function is written as a generator function simply use the for loop pattern to unroll the matches: -
line = '(((1+0)+1)+1)'
for openpos, closepos, level in matches(line):
print(line[openpos:closepos], level)
This test code produces following on my screen, noticed the second param in the printout indicates the depth of the parenthesis.
1+0 2
(1+0)+1 1
((1+0)+1)+1 0

From a linked answer:
From the LilyPond convert-ly utility (and written/copyrighted by myself, so I can show it off here):
def paren_matcher (n):
# poor man's matched paren scanning, gives up
# after n+1 levels. Matches any string with balanced
# parens inside; add the outer parens yourself if needed.
# Nongreedy.
return r"[^()]*?(?:\("*n+r"[^()]*?"+r"\)[^()]*?)*?"*n
convert-ly tends to use this as paren_matcher (25) in its regular expressions which is likely overkill for most applications. But then it uses it for matching Scheme expressions.
Yes, it breaks down after the given limit, but the ability to just plug it into regular expressions still beats the "correct" alternatives supporting unlimited depth hands-down in usability.

Balanced pairs (of parentheses, for example) is an example of a language that cannot be recognized by regular expressions.
What follows is a brief explanation of the math for why that is.
Regular expressions are a way of defining finite state automata (abbreviated FSM). Such a device has a finite amount of possible state to store information. How that state can be used is not particularly restricted, but it does mean that there are an absolute maximum number of distinct positions it can recognize.
For example, the state can be used for counting, say, unmatched left parentheses. But because the amount of state for that kind of counting must be completely bounded, then a given FSM can count to a maximum of n-1, where n is the number of states the FSM can be in. If n is, say, 10, then the maximum number of unmatched left parenthesis the FSM can match is 10, until it breaks. Since it's perfectly possible to have one more left parenthesis, there is no possible FSM that can correctly recognize the complete language of matched parentheses.
So what? Suppose you just pick a really large n? The problem is that as a way of describing FSM, regular expressions basically describe all of the transitions from one state to another. Since for any N, an FSM would need 2 state transitions (one for matching a left parenthesis, and one for matching right), the regular expression itself must grow by at least a constant factor multiple of n
By comparison, the next better class of languages, (context free grammars) can solve this problem in a totally compact way. Here's an example in BNF
expression ::= `(` expression `)` expression
| nothing

I believe this function may suit your need, I threw this together fast so feel free to clean it up a bit. When doing nests its easy to think of it backwards and work from there =]
def fn(string,endparens=False):
exp = []
idx = -1
for char in string:
if char == "(":
idx += 1
exp.append("")
elif char == ")":
idx -= 1
if idx != -1:
exp[idx] = "(" + exp[idx+1] + ")"
else:
exp[idx] += char
if endparens:
exp = ["("+val+")" for val in exp]
return exp

You can use regexps, but you need to do the recursion yourself. Something like the following does the trick (if you only need to find, as your question says, all the expressions enclosed into parentheses):
import re
def scan(p, string):
found = p.findall(string)
for substring in found:
stripped = substring[1:-1]
found.extend(scan(p, stripped))
return found
p = re.compile('\(.+\)')
string = '(((1+0)+1)+1)'
all_found = scan(p, string)
print all_found
This code, however, does not match the 'correct' parentheses. If you need to do that you will be better off with a specialized parser.

Here is a demo for your question, though it is clumsy, while it works
import re s = '(((1+0)+1)+1)'
def getContectWithinBraces( x , *args , **kwargs):
ptn = r'[%(left)s]([^%(left)s%(right)s]*)[%(right)s]' %kwargs
Res = []
res = re.findall(ptn , x)
while res != []:
Res = Res + res
xx = x.replace('(%s)' %Res[-1] , '%s')
res = re.findall(ptn, xx)
print(res)
if res != []:
res[0] = res[0] %('(%s)' %Res[-1])
return Res
getContectWithinBraces(s , left='\(\[\{' , right = '\)\]\}')

my solution is that: define a function to extract content within the outermost parentheses, and then you call that function repeatedly until you get the content within the innermost parentheses.
def get_string_inside_outermost_parentheses(text):
content_p = re.compile(r"(?<=\().*(?=\))")
r = content_p.search(text)
return r.group()
def get_string_inside_innermost_parentheses(text):
while '(' in text:
text = get_string_inside_outermost_parentheses(text)
return text

You should write a proper parser for parsing such expression (e.g. using pyparsing).
Regular expressions are not an appropriate tool for writing decent parsers.

Many posts suggest that for nested braces,
REGEX IS NOT THE WAY TO DO IT. SIMPLY COUNT THE BRACES:
For example, see: Regular expression to detect semi-colon terminated C++ for & while loops
Here is a complete python sample to iterate through a string and count braces:
# decided for nested braces to not use regex but brace-counting
import re, string
texta = r'''
nonexistent.\note{Richard Dawkins, \textit{Unweaving the Rainbow: Science, Delusion
and the Appetite for Wonder} (Boston: Houghton Mifflin Co., 1998), pp. 302, 304,
306-309.} more text and more.
This is a statistical fact, not a
guess.\note{Zheng Wu, \textit{Cohabitation: An Alternative Form
of Family Living} (Ontario, Canada: Oxford University Press,
2000), p. 149; \hbox{Judith} Treas and Deirdre Giesen, ``Title
and another title,''
\textit{Journal of Marriage and the Family}, February 2000,
p.\,51}
more and more text.capitalize
'''
pos = 0
foundpos = 0
openBr = 0 # count open braces
while foundpos <> -1:
openBr = 0
foundpos = string.find(texta, r'\note',pos)
# print 'foundpos',foundpos
pos = foundpos + 5
# print texta[pos]
result = ""
while foundpos > -1 and openBr >= 0:
pos = pos + 1
if texta[pos] == "{":
openBr = openBr + 1
if texta[pos] == "}":
openBr = openBr - 1
result = result + texta[pos]
result = result[:-1] # drop the last } found.
result = string.replace(result,'\n', ' ') # replace new line with space
print result

Related

Find value of a string given a superstring regex

How can I match for a string that is a substring of a given input string, preferable with regex?
Given a value: A789Lfu891MatchMe2ENOTSTH, construct a regex that would match a string where the string is a substring of the given value.
Expected matches:
MatchMe
ENOTST
891
Expected Non Match
foo
A789L<fu891MatchMe2ENOTSTH_extra
extra_A789L<fu891MatchMe2ENOTSTH
extra_A789L<fu891MatchMe2ENOTSTH_extra
It seems easier for me to do the reverse: /\w*MatchMe\w*/, but I can't wrap my head around this problem.
Something like how SQL would do it:
SELECT * FROM my_table mt WHERE 'A789Lfu891MatchMe2ENOTSTH' LIKE '%' || mt.foo || '%';
Prefix suffixes
You could alternate prefix suffixes, like turn the superstring abcd into a pattern like ^(a|(a)?b|((a)?b)?c|(((a)?b)?c)?d)$. For your example, the pattern has 1253 characters (exactly 2000 fewer than #tobias_k's).
Python code to produce the regex, can then be tested with tobias_k's code (try it online):
from itertools import accumulate
t = "A789Lfu891MatchMe2ENOTSTH"
p = '^(' + '|'.join(accumulate(t, '({})?{}'.format)) + ')$'
Suffix prefixes
Suffix prefixes look nicer and match faster: ^(a(b(c(d)?)?)?|b(c(d)?)?|c(d)?|d)$. Sadly the generating code is less elegant.
Divide and conquer
For a shorter regex, we can use divide and conquer. For example for the superstring abcdefg, every substring falls into one of three cases:
Contains the middle character (the d). Pattern for that: ((a?b)?c)?d(e(fg?)?)?
Is left of that middle character. So recursively build a regex for the superstring abc: a|a?bc?|c.
Is right of that middle character. So recursively build a regex for the superstring efg: e|e?fg?|g.
And then make an alternation of those three cases:
a|a?bc?|c|((a?b)?c)?d(e(fg?)?)?|e|e?fg?|g
Regex length will be Θ(n log n) instead of our previous Θ(n2).
The result for your superstring example of 25 characters is this regex with 301 characters:
^(A|A?78?|8|((A?7)?8)?9(Lf?)?|Lf?|f|(((((A?7)?8)?9)?L)?f)?u(8(9(1(Ma?)?)?)?)?|89?|9|(8?9)?1(Ma?)?|Ma?|a|(((((((((((A?7)?8)?9)?L)?f)?u)?8)?9)?1)?M)?a)?t(c(h(M(e(2(E(N(O(T(S(TH?)?)?)?)?)?)?)?)?)?)?)?|c|c?hM?|M|((c?h)?M)?e(2E?)?|2E?|E|(((((c?h)?M)?e)?2)?E)?N(O(T(S(TH?)?)?)?)?|OT?|T|(O?T)?S(TH?)?|TH?|H)$
Benchmark
Speed benchmarks don't really make that much sense, as in reality we'd just do a regular substring check (in Python s in t), but let's do one anyway.
Results for matching all substrings of your superstring, using Python 3.9.6 on my PC:
1.09 ms just_all_substrings
25.18 ms prefix_suffixes
3.47 ms suffix_prefixes
3.46 ms divide_and_conquer
And on TIO and their "Python 3.8 (pre-release)" with quite different results:
0.30 ms just_all_substrings
46.90 ms prefix_suffixes
2.24 ms suffix_prefixes
2.95 ms divide_and_conquer
Regex lengths (also printed by the below benchmark code):
3253 characters - just_all_substrings
1253 characters - prefix_suffixes
1253 characters - suffix_prefixes
301 characters - divide_and_conquer
Benchmark code (Try it online!):
from timeit import repeat
import re
from itertools import accumulate
def just_all_substrings(t):
return "^(" + '|'.join(t[i:k] for i in range(0, len(t))
for k in range(i+1, len(t)+1)) + ")$"
def prefix_suffixes(t):
return '^(' + '|'.join(accumulate(t, '({})?{}'.format)) + ')$'
def suffix_prefixes(t):
return '^(' + '|'.join(list(accumulate(t[::-1], '{1}({0})?'.format))[::-1]) + ')$'
def divide_and_conquer(t):
def suffixes(t):
# Example: abc => ((a?b)?c)?
regex = f'{t[0]}?'
for c in t[1:]:
regex = f'({regex}{c})?'
return regex
def prefixes(t):
# Example: efg => (e(fg?)?)?
regex = f'{t[-1]}?'
for c in t[-2::-1]:
regex = f'({c}{regex})?'
return regex
def superegex(t):
n = len(t)
if n == 1:
return t
if n == 2:
return f'{t}?|{t[1]}'
mid = n // 2
contain = suffixes(t[:mid]) + t[mid] + prefixes(t[mid+1:])
left = superegex(t[:mid])
right = superegex(t[mid+1:])
return '|'.join([left, contain, right])
return '^(' + superegex(t) + ')$'
creators = just_all_substrings, prefix_suffixes, suffix_prefixes, divide_and_conquer,
t = "A789Lfu891MatchMe2ENOTSTH"
substrings = [t[start:stop]
for start in range(len(t))
for stop in range(start+1, len(t)+1)]
def test(p):
match = re.compile(p).match
return all(map(re.compile(p).match, substrings))
for creator in creators:
print(test(creator(t)), creator.__name__)
print()
print('Regex lengths:')
for creator in creators:
print('%5d characters -' % len(creator(t)), creator.__name__)
print()
for _ in range(3):
for creator in creators:
p = creator(t)
number = 10
time = min(repeat(lambda: test(p), number=number)) / number
print('%5.2f ms ' % (time * 1e3), creator.__name__)
print()
One way to "construct" such a regex would be to build a disjunction of all possible substrings of the original value. Example in Python:
import re
t = "A789Lfu891MatchMe2ENOTSTH"
p = "^(" + '|'.join(t[i:k] for i in range(0, len(t))
for k in range(i+1, len(t)+1)) + ")$"
good = ["MatchMe", "ENOTST", "891"]
bad = ["foo", "A789L<fu891MatchMe2ENOTSTH_extra",
"extra_A789L<fu891MatchMe2ENOTSTH",
"extra_A789L<fu891MatchMe2ENOTSTH_extra"]
assert all(re.match(p, s) is not None for s in good)
assert all(re.match(p, s) is None for s in bad)
For the value "abcd", this would e.g. be "^(a|ab|abc|abcd|b|bc|bcd|c|cd|d)$"; for the given example it's a bit longer, with 3253 characters...

How to add parentheses to build a complicated dynamic Django filter with Q()?

I want to build a complicated filter:
queryset.filter(
(Q(k__contains=“1”) & Q(k__contains=“2”) & (~Q(k__contains=“3”))) |
(Q(k1__contains=“2”) & (~Q(k4__contains=“3”)))
)
The structure is fixed, but the query is dynamic and depends on a case specified by given input.
Tthe input could be for example :
(k=1&k=2&~k=3) | (k1=1&~k4=3)
or
(k=1&~k=3) | (k1=1&~k4=3) | (k=4&~k=3)
How to add parentheses to build this query to make it run as expected?
Two answers are presented: one simple and one perfect
1) A simple answer for similarly simple expressions:
It your expressions are simple and it seems better to read it by a short Python code. The most useful simplification is that parentheses are not nested. Less important simplification is that the operator OR ("|") is never in parentheses. The operator NOT is used only inside parentheses. The operator NOT is never double repeated ("~~").
Syntax: I express these simplifications in a form of EBNF syntax rules that could be useful later in a discussion about Python code.
expression = term, [ "|", term ];
term = "(", factor, { "&", factor }, ")";
factor = [ "~" ], variable, "=", constant;
variable = "a..z_0..9"; # anything except "(", ")", "|", "&", "~", "="
constant = "0-9_a-z... ,'\""; # anything except "(", ")", "|", "&", "~", "="
Optional white spaces are handled easily by .strip() method to can freely accept expressions like in mathematics. White spaces inside constants are supported.
Solution:
def compile_q(input_expression):
q_expression = ~Q() # selected empty
for term in input_expression.split('|'):
q_term = Q() # selected all
for factor in term.strip().lstrip('(').rstrip(')').split('&'):
left, right = factor.strip().split('=', 1)
negated, left = left.startswith('~'), left.lstrip('~')
q_factor = Q(**{left.strip() + '__contains': right.strip()})
if negated:
q_factor = ~q_factor
q_term &= q_factor
q_expression |= q_term
return q_expression
The superfluous empty and full Q expressions ~Q() and Q() are finally optimized and eliminated by Django.
Example:
>>> expression = "(k=1&k=2&~k=3) | ( k1 = 1 & ~ k4 = 3 )"
>>> qs = queryset.filter(compile_q(expression))
Check:
>>> print(str(qs.values('pk').query)) # a simplified more readable sql print
SELECT id FROM ... WHERE
((k LIKE %1% AND k LIKE %2% AND NOT (k LIKE %3%)) OR (k1 LIKE %1% AND NOT (k4 LIKE %3%)))
>>> sql, params = qs.values('pk').query.get_compiler('default').as_sql()
>>> print(sql); print(params) # a complete parametrized escaped print
SELECT... k LIKE %s ...
[... '%2%', ...]
The first "print" is a Django command for simplified more readable SQL without apostrophes and escaping, because it is actually delegated to the driver. The second print is a more complicated parametrized SQL command with all possible safe escaping.
2) Perfect, but longer solution
This answer can compile any combination of boolean operators "|", "&", "~", any level of nested parentheses and a comparision operator "=" to a Q() expression:
Solution: (not much more complicated)
import ast # builtin Python parser
from django.contrib.auth.models import User
from django.db.models import Q
def q_combine(node: ast.AST) -> Q:
if isinstance(node, ast.Module):
assert len(node.body) == 1 and isinstance(node.body[0], ast.Expr)
return q_combine(node.body[0].value)
if isinstance(node, ast.BoolOp):
if isinstance(node.op, ast.And):
q = Q()
for val in node.values:
q &= q_combine(val)
return q
if isinstance(node.op, ast.Or):
q = ~Q()
for val in node.values:
q |= q_combine(val)
return q
if isinstance(node, ast.UnaryOp):
assert isinstance(node.op, ast.Not)
return ~q_combine(node.operand)
if isinstance(node, ast.Compare):
assert isinstance(node.left, ast.Name)
assert len(node.ops) == 1 and isinstance(node.ops[0], ast.Eq)
assert len(node.comparators) == 1 and isinstance(node.comparators[0], ast.Constant)
return Q(**{node.left.id + '__contains': str(node.comparators[0].value)})
raise ValueError('unexpected node {}'.format(type(node).__name__))
def compile_q(expression: str) -> Q:
std_expr = (expression.replace('=', '==').replace('~', ' not ')
.replace('&', ' and ').replace('|', ' or '))
return q_combine(ast.parse(std_expr))
Example: the same as in my previous answer a more complex following:
>>> expression = "~(~k=1&(k1=2|k1=3|(k=5 & k4=3))"
>>> qs = queryset.filter(compile_q(expression))
The same example gives the same result, a more nested example gives a correct more nested result.
EBNF syntax rules are not important in this case, because no parser is implemented in this solution and the standard Python parser AST is used. It is little different with recursion.
expression = term, [ "|", term ];
term = factor, { "&", factor };
factor = [ "~" ], variable, "=", constant | [ "~" ], "(", expression, ")";
variable = "a..z_0..9"; # any identifier acceptable by Python, e.g. not a Python keyword
constant = "0-9_a-z... ,'\""; # any numeric or string literal acceptable by Python
This answer can compile any combination of boolean operators "|", "&", "~", any level of nested parentheses and a comparision operator "=" to a Q() expression:
Solution: (not much more complicated)
import ast # builtin Python parser
from django.contrib.auth.models import User
from django.db.models import Q
def q_combine(node: ast.AST) -> Q:
if isinstance(node, ast.Module):
assert len(node.body) == 1 and isinstance(node.body[0], ast.Expr)
return q_combine(node.body[0].value)
if isinstance(node, ast.BoolOp):
if isinstance(node.op, ast.And):
q = Q()
for val in node.values:
q &= q_combine(val)
return q
if isinstance(node.op, ast.Or):
q = ~Q()
for val in node.values:
q |= q_combine(val)
return q
if isinstance(node, ast.UnaryOp):
assert isinstance(node.op, ast.Not)
return ~q_combine(node.operand)
if isinstance(node, ast.Compare):
assert isinstance(node.left, ast.Name)
assert len(node.ops) == 1 and isinstance(node.ops[0], ast.Eq)
assert len(node.comparators) == 1 and isinstance(node.comparators[0], ast.Constant)
return Q(**{node.left.id + '__contains': str(node.comparators[0].value)})
raise ValueError('unexpected node {}'.format(type(node).__name__))
def compile_q(expression: str) -> Q:
std_expr = (expression.replace('=', '==').replace('~', ' not ')
.replace('&', ' and ').replace('|', ' or '))
return q_combine(ast.parse(std_expr))
Example: the same as in my previous answer a more complex following:
>>> expression = "~(~k=1&(k1=2|k1=3|(k=5 & k4=3))"
>>> qs = queryset.filter(compile_q(expression))
The same example gives the same result, a more nested example gives a correct more nested result.
EBNF syntax rules are not important in this case, because no parser is implemented in this solution and the standard Python parser AST is used. It is little different with recursion.
expression = term, [ "|", term ];
term = factor, { "&", factor };
factor = [ "~" ], variable, "=", constant | [ "~" ], "(", expression, ")";
variable = "a..z_0..9"; # any identifier acceptable by Python, e.g. not a Python keyword
constant = "0-9_a-z... ,'\""; # any numeric or string literal acceptable by Python
Finally I failed to make this work using django Q.
Bug use extra to build code like
queryset.extra(where =
["(k1 like '%1%' and k2 like '%2%' and (k3 not like '%3%')) or (k1 like '%4%' and (k3 not like '%3%'))"]
)
and it works.
😂

Regular Expression: match and count "A" and stop after found "B" by counted times [duplicate]

I need a regular expression to select all the text between two outer brackets.
Example:
START_TEXT(text here(possible text)text(possible text(more text)))END_TXT
^ ^
Result:
(text here(possible text)text(possible text(more text)))
I want to add this answer for quickreference. Feel free to update.
.NET Regex using balancing groups:
\((?>\((?<c>)|[^()]+|\)(?<-c>))*(?(c)(?!))\)
Where c is used as the depth counter.
Demo at Regexstorm.com
Stack Overflow: Using RegEx to balance match parenthesis
Wes' Puzzling Blog: Matching Balanced Constructs with .NET Regular Expressions
Greg Reinacker's Weblog: Nested Constructs in Regular Expressions
PCRE using a recursive pattern:
\((?:[^)(]+|(?R))*+\)
Demo at regex101; Or without alternation:
\((?:[^)(]*(?R)?)*+\)
Demo at regex101; Or unrolled for performance:
\([^)(]*+(?:(?R)[^)(]*)*+\)
Demo at regex101; The pattern is pasted at (?R) which represents (?0).
Perl, PHP, Notepad++, R: perl=TRUE, Python: PyPI regex module with (?V1) for Perl behaviour.
(the new version of PyPI regex package already defaults to this → DEFAULT_VERSION = VERSION1)
Ruby using subexpression calls:
With Ruby 2.0 \g<0> can be used to call full pattern.
\((?>[^)(]+|\g<0>)*\)
Demo at Rubular; Ruby 1.9 only supports capturing group recursion:
(\((?>[^)(]+|\g<1>)*\))
Demo at Rubular  (atomic grouping since Ruby 1.9.3)
JavaScript  API :: XRegExp.matchRecursive
XRegExp.matchRecursive(str, '\\(', '\\)', 'g');
Java: An interesting idea using forward references by #jaytea.
Without recursion up to 3 levels of nesting:
(JS, Java and other regex flavors)
To prevent runaway if unbalanced, with * on innermost [)(] only.
\((?:[^)(]|\((?:[^)(]|\((?:[^)(]|\([^)(]*\))*\))*\))*\)
Demo at regex101; Or unrolled for better performance (preferred).
\([^)(]*(?:\([^)(]*(?:\([^)(]*(?:\([^)(]*\)[^)(]*)*\)[^)(]*)*\)[^)(]*)*\)
Demo at regex101; Deeper nesting needs to be added as required.
Reference - What does this regex mean?
RexEgg.com - Recursive Regular Expressions
Regular-Expressions.info - Regular Expression Recursion
Mastering Regular Expressions - Jeffrey E.F. Friedl 1 2 3 4
Regular expressions are the wrong tool for the job because you are dealing with nested structures, i.e. recursion.
But there is a simple algorithm to do this, which I described in more detail in this answer to a previous question. The gist is to write code which scans through the string keeping a counter of the open parentheses which have not yet been matched by a closing parenthesis. When that counter returns to zero, then you know you've reached the final closing parenthesis.
You can use regex recursion:
\(([^()]|(?R))*\)
[^\(]*(\(.*\))[^\)]*
[^\(]* matches everything that isn't an opening bracket at the beginning of the string, (\(.*\)) captures the required substring enclosed in brackets, and [^\)]* matches everything that isn't a closing bracket at the end of the string. Note that this expression does not attempt to match brackets; a simple parser (see dehmann's answer) would be more suitable for that.
This answer explains the theoretical limitation of why regular expressions are not the right tool for this task.
Regular expressions can not do this.
Regular expressions are based on a computing model known as Finite State Automata (FSA). As the name indicates, a FSA can remember only the current state, it has no information about the previous states.
In the above diagram, S1 and S2 are two states where S1 is the starting and final step. So if we try with the string 0110 , the transition goes as follows:
0 1 1 0
-> S1 -> S2 -> S2 -> S2 ->S1
In the above steps, when we are at second S2 i.e. after parsing 01 of 0110, the FSA has no information about the previous 0 in 01 as it can only remember the current state and the next input symbol.
In the above problem, we need to know the no of opening parenthesis; this means it has to be stored at some place. But since FSAs can not do that, a regular expression can not be written.
However, an algorithm can be written to do this task. Algorithms are generally falls under Pushdown Automata (PDA). PDA is one level above of FSA. PDA has an additional stack to store some additional information. PDAs can be used to solve the above problem, because we can 'push' the opening parenthesis in the stack and 'pop' them once we encounter a closing parenthesis. If at the end, stack is empty, then opening parenthesis and closing parenthesis matches. Otherwise not.
(?<=\().*(?=\))
If you want to select text between two matching parentheses, you are out of luck with regular expressions. This is impossible(*).
This regex just returns the text between the first opening and the last closing parentheses in your string.
(*) Unless your regex engine has features like balancing groups or recursion. The number of engines that support such features is slowly growing, but they are still not a commonly available.
It is actually possible to do it using .NET regular expressions, but it is not trivial, so read carefully.
You can read a nice article here. You also may need to read up on .NET regular expressions. You can start reading here.
Angle brackets <> were used because they do not require escaping.
The regular expression looks like this:
<
[^<>]*
(
(
(?<Open><)
[^<>]*
)+
(
(?<Close-Open>>)
[^<>]*
)+
)*
(?(Open)(?!))
>
I was also stuck in this situation when dealing with nested patterns and regular-expressions is the right tool to solve such problems.
/(\((?>[^()]+|(?1))*\))/
This is the definitive regex:
\(
(?<arguments>
(
([^\(\)']*) |
(\([^\(\)']*\)) |
'(.*?)'
)*
)
\)
Example:
input: ( arg1, arg2, arg3, (arg4), '(pip' )
output: arg1, arg2, arg3, (arg4), '(pip'
note that the '(pip' is correctly managed as string.
(tried in regulator: http://sourceforge.net/projects/regulator/)
I have written a little JavaScript library called balanced to help with this task. You can accomplish this by doing
balanced.matches({
source: source,
open: '(',
close: ')'
});
You can even do replacements:
balanced.replacements({
source: source,
open: '(',
close: ')',
replace: function (source, head, tail) {
return head + source + tail;
}
});
Here's a more complex and interactive example JSFiddle.
Adding to bobble bubble's answer, there are other regex flavors where recursive constructs are supported.
Lua
Use %b() (%b{} / %b[] for curly braces / square brackets):
for s in string.gmatch("Extract (a(b)c) and ((d)f(g))", "%b()") do print(s) end (see demo)
Raku (former Perl6):
Non-overlapping multiple balanced parentheses matches:
my regex paren_any { '(' ~ ')' [ <-[()]>+ || <&paren_any> ]* }
say "Extract (a(b)c) and ((d)f(g))" ~~ m:g/<&paren_any>/;
# => (「(a(b)c)」 「((d)f(g))」)
Overlapping multiple balanced parentheses matches:
say "Extract (a(b)c) and ((d)f(g))" ~~ m:ov:g/<&paren_any>/;
# => (「(a(b)c)」 「(b)」 「((d)f(g))」 「(d)」 「(g)」)
See demo.
Python re non-regex solution
See poke's answer for How to get an expression between balanced parentheses.
Java customizable non-regex solution
Here is a customizable solution allowing single character literal delimiters in Java:
public static List<String> getBalancedSubstrings(String s, Character markStart,
Character markEnd, Boolean includeMarkers)
{
List<String> subTreeList = new ArrayList<String>();
int level = 0;
int lastOpenDelimiter = -1;
for (int i = 0; i < s.length(); i++) {
char c = s.charAt(i);
if (c == markStart) {
level++;
if (level == 1) {
lastOpenDelimiter = (includeMarkers ? i : i + 1);
}
}
else if (c == markEnd) {
if (level == 1) {
subTreeList.add(s.substring(lastOpenDelimiter, (includeMarkers ? i + 1 : i)));
}
if (level > 0) level--;
}
}
return subTreeList;
}
}
Sample usage:
String s = "some text(text here(possible text)text(possible text(more text)))end text";
List<String> balanced = getBalancedSubstrings(s, '(', ')', true);
System.out.println("Balanced substrings:\n" + balanced);
// => [(text here(possible text)text(possible text(more text)))]
The regular expression using Ruby (version 1.9.3 or above):
/(?<match>\((?:\g<match>|[^()]++)*\))/
Demo on rubular
The answer depends on whether you need to match matching sets of brackets, or merely the first open to the last close in the input text.
If you need to match matching nested brackets, then you need something more than regular expressions. - see #dehmann
If it's just first open to last close see #Zach
Decide what you want to happen with:
abc ( 123 ( foobar ) def ) xyz ) ghij
You need to decide what your code needs to match in this case.
"""
Here is a simple python program showing how to use regular
expressions to write a paren-matching recursive parser.
This parser recognises items enclosed by parens, brackets,
braces and <> symbols, but is adaptable to any set of
open/close patterns. This is where the re package greatly
assists in parsing.
"""
import re
# The pattern below recognises a sequence consisting of:
# 1. Any characters not in the set of open/close strings.
# 2. One of the open/close strings.
# 3. The remainder of the string.
#
# There is no reason the opening pattern can't be the
# same as the closing pattern, so quoted strings can
# be included. However quotes are not ignored inside
# quotes. More logic is needed for that....
pat = re.compile("""
( .*? )
( \( | \) | \[ | \] | \{ | \} | \< | \> |
\' | \" | BEGIN | END | $ )
( .* )
""", re.X)
# The keys to the dictionary below are the opening strings,
# and the values are the corresponding closing strings.
# For example "(" is an opening string and ")" is its
# closing string.
matching = { "(" : ")",
"[" : "]",
"{" : "}",
"<" : ">",
'"' : '"',
"'" : "'",
"BEGIN" : "END" }
# The procedure below matches string s and returns a
# recursive list matching the nesting of the open/close
# patterns in s.
def matchnested(s, term=""):
lst = []
while True:
m = pat.match(s)
if m.group(1) != "":
lst.append(m.group(1))
if m.group(2) == term:
return lst, m.group(3)
if m.group(2) in matching:
item, s = matchnested(m.group(3), matching[m.group(2)])
lst.append(m.group(2))
lst.append(item)
lst.append(matching[m.group(2)])
else:
raise ValueError("After <<%s %s>> expected %s not %s" %
(lst, s, term, m.group(2)))
# Unit test.
if __name__ == "__main__":
for s in ("simple string",
""" "double quote" """,
""" 'single quote' """,
"one'two'three'four'five'six'seven",
"one(two(three(four)five)six)seven",
"one(two(three)four)five(six(seven)eight)nine",
"one(two)three[four]five{six}seven<eight>nine",
"one(two[three{four<five>six}seven]eight)nine",
"oneBEGINtwo(threeBEGINfourENDfive)sixENDseven",
"ERROR testing ((( mismatched ))] parens"):
print "\ninput", s
try:
lst, s = matchnested(s)
print "output", lst
except ValueError as e:
print str(e)
print "done"
You need the first and last parentheses. Use something like this:
str.indexOf('('); - it will give you first occurrence
str.lastIndexOf(')'); - last one
So you need a string between,
String searchedString = str.substring(str1.indexOf('('),str1.lastIndexOf(')');
because js regex doesn't support recursive match, i can't make balanced parentheses matching work.
so this is a simple javascript for loop version that make "method(arg)" string into array
push(number) map(test(a(a()))) bass(wow, abc)
$$(groups) filter({ type: 'ORGANIZATION', isDisabled: { $ne: true } }) pickBy(_id, type) map(test()) as(groups)
const parser = str => {
let ops = []
let method, arg
let isMethod = true
let open = []
for (const char of str) {
// skip whitespace
if (char === ' ') continue
// append method or arg string
if (char !== '(' && char !== ')') {
if (isMethod) {
(method ? (method += char) : (method = char))
} else {
(arg ? (arg += char) : (arg = char))
}
}
if (char === '(') {
// nested parenthesis should be a part of arg
if (!isMethod) arg += char
isMethod = false
open.push(char)
} else if (char === ')') {
open.pop()
// check end of arg
if (open.length < 1) {
isMethod = true
ops.push({ method, arg })
method = arg = undefined
} else {
arg += char
}
}
}
return ops
}
// const test = parser(`$$(groups) filter({ type: 'ORGANIZATION', isDisabled: { $ne: true } }) pickBy(_id, type) map(test()) as(groups)`)
const test = parser(`push(number) map(test(a(a()))) bass(wow, abc)`)
console.log(test)
the result is like
[ { method: 'push', arg: 'number' },
{ method: 'map', arg: 'test(a(a()))' },
{ method: 'bass', arg: 'wow,abc' } ]
[ { method: '$$', arg: 'groups' },
{ method: 'filter',
arg: '{type:\'ORGANIZATION\',isDisabled:{$ne:true}}' },
{ method: 'pickBy', arg: '_id,type' },
{ method: 'map', arg: 'test()' },
{ method: 'as', arg: 'groups' } ]
While so many answers mention this in some form by saying that regex does not support recursive matching and so on, the primary reason for this lies in the roots of the Theory of Computation.
Language of the form {a^nb^n | n>=0} is not regular. Regex can only match things that form part of the regular set of languages.
Read more # here
I didn't use regex since it is difficult to deal with nested code. So this snippet should be able to allow you to grab sections of code with balanced brackets:
def extract_code(data):
""" returns an array of code snippets from a string (data)"""
start_pos = None
end_pos = None
count_open = 0
count_close = 0
code_snippets = []
for i,v in enumerate(data):
if v =='{':
count_open+=1
if not start_pos:
start_pos= i
if v=='}':
count_close +=1
if count_open == count_close and not end_pos:
end_pos = i+1
if start_pos and end_pos:
code_snippets.append((start_pos,end_pos))
start_pos = None
end_pos = None
return code_snippets
I used this to extract code snippets from a text file.
This do not fully address the OP question but I though it may be useful to some coming here to search for nested structure regexp:
Parse parmeters from function string (with nested structures) in javascript
Match structures like:
matches brackets, square brackets, parentheses, single and double quotes
Here you can see generated regexp in action
/**
* get param content of function string.
* only params string should be provided without parentheses
* WORK even if some/all params are not set
* #return [param1, param2, param3]
*/
exports.getParamsSAFE = (str, nbParams = 3) => {
const nextParamReg = /^\s*((?:(?:['"([{](?:[^'"()[\]{}]*?|['"([{](?:[^'"()[\]{}]*?|['"([{][^'"()[\]{}]*?['")}\]])*?['")}\]])*?['")}\]])|[^,])*?)\s*(?:,|$)/;
const params = [];
while (str.length) { // this is to avoid a BIG performance issue in javascript regexp engine
str = str.replace(nextParamReg, (full, p1) => {
params.push(p1);
return '';
});
}
return params;
};
This might help to match balanced parenthesis.
\s*\w+[(][^+]*[)]\s*
This one also worked
re.findall(r'\(.+\)', s)

groovy regex, how to match array items in a string

The string looks like this "[xx],[xx],[xx]"
Where xx is a ploygon like this "(1.0,2.3),(2.0,3)...
Basically, we are looking for a way to get the string between each pair of square brackets into an array.
E.g. String source = "[hello],[1,2],[(1,2),(2,4)]"
would result in an object a such that:
a[0] == 'hello'
a[1] == '1,2'
a[2] == '(1,2),(2,4)'
We have tried various strategies, including using groovy regex:
def p = "[12],[34]"
def points = p =~ /(\[([^\[]*)\])*/
println points[0][2] // yields 12
However,this yields the following 2 dim array:
[[12], [12], 12]
[, null, null]
[[34], [34], 34]
so if we took the 3rd item from every even rows we would be ok, but this does look very correct. We are not talking into account the ',' and we are not sure why we are getting "[12]" twice, when it should be zero times?
Any regex experts out there?
I think that this is what you're looking for:
def p = "[hello],[1,2],[(1,2),(2,4)]"
def points = p.findAll(/\[(.*?)\]/){match, group -> group }
println points[0]
println points[1]
println points[2]
This scripts prints:
hello
1,2
(1,2),(2,4)
The key is the use of the .*? to make the expression non-greedy to found the minimum between chars [] to avoid that the first [ match with the last ] resulting match in hello],[1,2],[(1,2),(2,4) match... then with findAll you returns only the group captured.
Hope it helps,

REGEX - Matching any character which repeats n times

How to match any character which repeats n times?
Example:
for input: abcdbcdcdd
for n=1: ..........
for n=2: .........
for n=3: .. .....
for n=4: . . ..
for n=5: no matches
After several hours my best is this expression
(\w)(?=(?:.*\1){n-1,}) //where n is variable
which uses lookahead. However the problem with this expression is this:
for input: abcdbcdcdd
for n=1 ..........
for n=2 ... .. .
for n=3 .. .
for n=4 .
for n=5 no matches
As you can see, when lookahead matches for a character, let's look for n=4 line, d's lookahead assertion satisfied and first d matched by regex. But remaining d's are not matched because they don't have 3 more d's ahead of them.
I hope I stated the problem clearly. Hoping for your solutions, thanks in advance.
let's look for n=4 line, d's lookahead assertion satisfied
and first d matched by regex.
But remaining d's are not matched because they don't have 3 more d's
ahead of them.
And obviously, without regex, this is a very simple string manipulation
problem. I'm trying to do this with and only with regex.
As with any regex implementation, the answer depends on the regex flavour. You could create a solution with .net regex engine, because it allows variable width lookbehinds.
Also, I'll provide a more generalized solution below for perl-compatible/like regex flavours.
.net Solution
As #PetSerAl pointed out in his answer, with variable width lookbehinds, we can assert back to the beggining of the string, and check there are n occurrences.
ideone demo
regex module in Python
You can implement this solution in python, using the regex module by Matthew Barnett, which also allows variable-width lookbehinds.
>>> import regex
>>> regex.findall( r'(\w)(?<=(?=(?>.*?\1){2})\A.*)', 'abcdbcdcdd')
['b', 'c', 'd', 'b', 'c', 'd', 'c', 'd', 'd']
>>> regex.findall( r'(\w)(?<=(?=(?>.*?\1){3})\A.*)', 'abcdbcdcdd')
['c', 'd', 'c', 'd', 'c', 'd', 'd']
>>> regex.findall( r'(\w)(?<=(?=(?>.*?\1){4})\A.*)', 'abcdbcdcdd')
['d', 'd', 'd', 'd']
>>> regex.findall( r'(\w)(?<=(?=(?>.*?\1){5})\A.*)', 'abcdbcdcdd')
[]
Generalized Solution
In pcre or any of the "perl-like" flavours, there is no solution that would actually return a match for every repeated character, but we could create one, and only one, capture for each character.
Strategy
For any given n, the logic involves:
Early matches: Match and capture every character followed by at least n more occurences.
Final captures:
Match and capture a character followed by exactly n-1 occurences, and
also capture every one of the following occurrences.
Example
for n = 3
input = abcdbcdcdd
The character c is Matched only once (as final), and the following 2 occurrences are also Captured in the same match:
abcdbcdcdd
M C C
and the character d is (early) Matched once:
abcdbcdcdd
M
and (finally) Matched one more time, Capturing the rest:
abcdbcdcdd
M CC
Regex
/(\w) # match 1 character
(?:
(?=(?:.*?\1){≪N≫}) # [1] followed by other ≪N≫ occurrences
| # OR
(?= # [2] followed by:
(?:(?!\1).)*(\1) # 2nd occurence <captured>
(?:(?!\1).)*(\1) # 3rd occurence <captured>
≪repeat previous≫ # repeat subpattern (n-1) times
# *exactly (n-1) times*
(?!.*?\1) # not followed by another occurence
)
)/xg
For n =
/(\w)(?:(?=(?:.*?\1){2})|(?=(?:(?!\1).)*(\1)(?!.*?\1)))/g
demo
/(\w)(?:(?=(?:.*?\1){3})|(?=(?:(?!\1).)*(\1)(?:(?!\1).)*(\1)(?!.*?\1)))/g
demo
/(\w)(?:(?=(?:.*?\1){4})|(?=(?:(?!\1).)*(\1)(?:(?!\1).)*(\1)(?:(?!\1).)*(\1)(?!.*?\1)))/g
demo
... etc.
Pseudocode to generate the pattern
// Variables: N (int)
character = "(\w)"
early_match = "(?=(?:.*?\1){" + N + "})"
final_match = "(?="
for i = 1; i < N; i++
final_match += "(?:(?!\1).)*(\1)"
final_match += "(?!.*?\1))"
pattern = character + "(?:" + early_match + "|" + final_match + ")"
JavaScript Code
I'll show an implementation using javascript because we can check the result here (and if it works in javascript, it works in any perl-compatible regex flavour, including .net, java, python, ruby, perl, and all languages that implemented pcre, among others).
var str = 'abcdbcdcdd';
var pattern, re, match, N, i;
var output = "";
// We'll show the results for N = 2, 3 and 4
for (N = 2; N <= 4; N++) {
// Generate pattern
pattern = "(\\w)(?:(?=(?:.*?\\1){" + N + "})|(?=";
for (i = 1; i < N; i++) {
pattern += "(?:(?!\\1).)*(\\1)";
}
pattern += "(?!.*?\\1)))";
re = new RegExp(pattern, "g");
output += "<h3>N = " + N + "</h3><pre>Pattern: " + pattern + "\nText: " + str;
// Loop all matches
while ((match = re.exec(str)) !== null) {
output += "\nPos: " + match.index + "\tMatch:";
// Loop all captures
x = 1;
while (match[x] != null) {
output += " " + match[x];
x++;
}
}
output += "</pre>";
}
document.write(output);
Python3 code
As requested by the OP, I'm linking to a Python3 implementation in ideone.com
Regular expressions (and finite automata) are not able to count to arbitrary integers. They can only count to a predefined integer and fortunately this is your case.
Solving this problem is much easier if we first construct a nondeterministic finite automata (NFA) ad then convert it to regular expression.
So the following automata for n=2 and input alphabet = {a,b,c,d}
will match any string that has exactly 2 repetitions of any char. If no character has 2 repetitions (all chars appear less or more that two times) the string will not match.
Converting it to regex should look like
"^([^a]*a[^a]*a[^a]*)|([^b]*b[^b]*b[^b]*)|([^b]*c[^c]*c[^C]*)|([^d]*d[^d]*d[^d]*)$"
This can get problematic if the input alphabet is big, so that regex should be shortened somehow, but I can't think of it right now.
With .NET regular expressions you can do following:
(\w)(?<=(?=(?:.*\1){n})^.*) where n is variable
Where:
(\w) — any character, captured in first group.
(?<=^.*) — lookbehind assertion, which return us to the start of the string.
(?=(?:.*\1){n}) — lookahead assertion, to see if string have n instances of that character.
Demo
I would not use regular expressions for this. I would use a scripting language such as python. Try out this python function:
alpha = 'abcdefghijklmnopqrstuvwxyz'
def get_matched_chars(n, s):
s = s.lower()
return [char for char in alpha if s.count(char) == n]
The function will return a list of characters, all of which appear in the string s exactly n times. Keep in mind that I only included letters in my alphabet. You can change alpha to represent anything that you want to get matched.