I am not looking for a specific regular expression, but for a software that find them.
Let us say I have a file A and a file B: how to find a regexp that matches all words of A, but does not match any of the words in A?
If A contains "truit fruit" and B contains "ridiculous", then the software could return something like ".ru." but '.r.' only would be invalid.
It is the "practical" aspect of another question [1], though what interests me is to find an actual software that solves it in practice.
Thanks for your help,
Nathann
[1] https://cstheory.stackexchange.com/questions/1854/is-finding-the-minimum-regular-expression-an-np-complete-problem
There is no algorithm to somehow "cleverly derive" a regular expression from examples. You can only implement a brute force attempt of an iteration through all permutations of common substrings of the words in A and tests B against it until you find a solution. You are not guaranteed to find a solution, though.
For the case that there are no common substrings of all words in A you could then extend that approach to introduce the "or" operator in regular expressions. But that get's really ugly and slow.
If that does not lead to a solution, then you'd have to go on extending your attempts such that also exclusion rules are added to the expression by iterating through all words in B and creating anti patterns from it. Horrible attempt.
And as said: you are never guaranteed to find a solution.
There is one thing though:
If you are not interested in how the final regular expression looks like you can do this: create a regex simply combining all words in a "whitespace padded version of A" with an "or" operation (so \struit\s|\sfruit\s in your example). Obviously that attempt creates huge expressions. You then would have to take care to exclude exact substrings that might occur in B again. Which may lead to much longer expressions still.
Bottom line: there is no really elegant solution for this. Simply because the question does not allow for that. Question is: why does it have to be a regular expression? Why can't you simply do string comparisions? That would probably not be more expensive anyway in such an vaguely defined scenario...
For the strings:
text::handle:e#ma.il::text
text::chat_identifier:chat0123456789&text
I have the current regex:
m/(handle:|chat_identifier:)(.+?)(:{2}|&)/
And I am currently using $2 in order to obtain the value I wish (in the first string e#ma.il and in the second, chat0123456789).
Is there a better/faster/simpler way to solve this problem, though?
Whether it's "better" or not depends on the context, but you could take this approach: split the string on ":" and take the fourth element of the resulting list. That's arguably more readable than the regex and more robust if the third field can be something other than "handle" or "chat_identifier".
I think the speed would be very similar for either approach but probably for almost any implementation in perl. I'd want to show that speed was critical for this step before worrying about it...
For a regex solution, this one is slightly simpler and doesn't need to backtrack:
m/(handle|chat_identifier):([^:&]+)/
Note the slight difference: yours allows single colons within the value, mine doesn't (it stops at the first colon encountered). If that is not a problem, you can use my variant. Or as I mentioned in a comment, split at : and use the fourth element in the result.
An equivalent version that does only stop at double colons is this:
m/(handle|chat_identifier):((?:(?!::|&).)+)/
Not so beautiful, but it still avoids backtracking (the lookahead might make it slower, though... you will need to profile that, if speed matters at all).
Looks like you have allot of good solutions already here. The split method seems like the simplest. But depending on your requirements you could also use a more generic regex that breaks the string in its basic pieces. It will work for other datatypes and property names than in your examples.
([^:]+)::([^:]+):([^:&]+)(?:::|&)\1
The captures groups are as follows:
Group 1: the datatype. (the keyword "text" from your examples.)
Group 2: The property name. (The keywords "handle" and "chat_identifier"
from your examples.)
Group 3: The property value.
If the values you want are always in the same position and it's safe to split on : and &, then perhaps the following will work for you:
use Modern::Perl;
say +( split /[:&]+/ )[2] for <DATA>;
__DATA__
text::handle:e#ma.il::text
text::chat_identifier:chat0123456789&text
Output:
e#ma.il
chat0123456789
Is it possible/practical to build a single regular expression that matches hierarchical data?
For example:
<h1>Action</h1>
<h2>Title1</h2><div>data1</div>
<h2>Title2</h2><div>data2</div>
<h1>Adventure</h1>
<h2>Title3</h2><div>data3</div>
I would like to end up with matches.
"Action", "Title1", "data1"
"Action", "Title2", "data2"
"Adventure", "Title3", "data3"
As I see it this would require knowing that there is a hierarchical structure at play here and if I code the pattern to capture the H1, it only matches the first entry of that hierarchy. If I don't code for H1 then I can't capture it. Was wondering if there are any special tricks I an employ to solve this.
This is a .NET project.
The solution is to not use regular expressions. They're not powerful enough for this sort of thing.
What you want is a parser - since it looks like you're trying to match HTML, there are plenty to choose from.
It's generally considered bad practice to attempt to parse HTML/XML with RegEx, precisely because it's hierarchical. You COULD use a recursive function to do so, but a better solution in this case is to use a real XML parser. I couldn't give you better advice than that without knowing the platform you're using.
EDIT: Regex is also very slow, which is another reason it's bad for processing HTML; however, I don't know that an XML/DOM processor is likely to be faster since it's likely to use a lot more memory.
If you JUST want data from a simple document like you've demonstrated, and/or if you want to build a solution yourself, it's not that tough to do. Just build a simple, recursive state-based stream processor that looks for tags and passes the contents to the the next recursive level.
For example:
- In a recursive function, seek out a "<" character.
- Now find a ">" character.
- Preserve everything you find until the next "<" character.
- Find a ">" character.
- Pass whatever you found between those tags into the recursive function.
You'd have to work out error checking yourself, but the base case (when you return back up to the previous level) is just when there's nothing else to find.
Maybe this helps, maybe not. Good luck to you.
Regex does not work for this type of data. It is not regular, per se.
You should use an XML parser for this.
I have a command line application that needs to support arguments of the following brand:
all: return everything
search: return the first match to search
all*search: return everything matching search
X*search: return the first X matches to search
search#Y: return the Yth match to search
Where search can be either a single keyword or a space separated list of keywords, delimited by single quotes. Keywords are a sequence of one or more letters and digits - nothing else.
A few examples might be:
2*foo
bar#8
all*'foo bar'
This sounds just complex enough that flex/bison come to mind - but the application can expect to have to parse strings like this very frequently, and I feel like (because there's no counting involved) a fully-fledged parser would incur entirely too much overhead.
What would you recommend? A long series of string ops? A few beefy subpattern-capturing regular expressions? Is there actually a plausible argument for a "real" parser?
It might be useful to note that the syntax for this pseudo-grammar is not subject to change, so if the code turns out less-than-wonderfully-maintainable, I won't cry. This is all in C++, if that makes a difference.
Thanks!
I wouldn't reccomend a full lex/yacc parser just for this. What you described can fit a simple regular expression:
((all|[0-9]+)\*)?('[A-Za-z0-9\t ]*'|[A-Za-z0-9]+)(#[0-9]+)?
If you have a regex engine that support captures, it's easy to extract the single pieces of information you need. (Most probably in captures 1,3 and 4).
If I understood what you mean, you will probably want to check that capture 1 and capture 4 are not non-empty at the same time.
If you need to further split the search terms, you could do it in a subsequent step, parsing capture 3.
Even without regex, I would hand write a function. It would be simpler than dealing with lex/yacc and I guess you could put together something that is even more efficient than a regular expression.
The answer mostly depends on a balance between how much coding you want to do and how much libraries you want to depend on - if your application can depend on other libraries, you can use any of the many regular expression libraries - e.g. POSIX regex which comes with all Linux/Unix flavors.
OR
If you just want those specific syntaxes, I would use the string tokenizer (strtok) - split on '*' and split on '#' - then handle each case.
In this case the strtok approach would be much better since the number of commands to be parsed are few.
Lets say that I have 10,000 regexes and one string and I want to find out if the string matches any of them and get all the matches.
The trivial way to do it would be to just query the string one by one against all regexes. Is there a faster,more efficient way to do it?
EDIT:
I have tried substituting it with DFA's (lex)
The problem here is that it would only give you one single pattern. If I have a string "hello" and patterns "[H|h]ello" and ".{0,20}ello", DFA will only match one of them, but I want both of them to hit.
This is the way lexers work.
The regular expressions are converted into a single non deterministic automata (NFA) and possibily transformed in a deterministic automata (DFA).
The resulting automaton will try to match all the regular expressions at once and will succeed on one of them.
There are many tools that can help you here, they are called "lexer generator" and there are solutions that work with most of the languages.
You don't say which language are you using. For C programmers I would suggest to have a look at the re2c tool. Of course the traditional (f)lex is always an option.
I've come across a similar problem in the past. I used a solution similar to the one suggested by akdom.
I was lucky in that my regular expressions usually had some substring that must appear in every string it matches. I was able to extract these substrings using a simple parser and index them in an FSA using the Aho-Corasick algorithms. The index was then used to quickly eliminate all the regular expressions that trivially don't match a given string, leaving only a few regular expressions to check.
I released the code under the LGPL as a Python/C module. See esmre on Google code hosting.
We had to do this on a product I worked on once. The answer was to compile all your regexes together into a Deterministic Finite State Machine (also known as a deterministic finite automaton or DFA). The DFA could then be walked character by character over your string and would fire a "match" event whenever one of the expressions matched.
Advantages are it runs fast (each character is compared only once) and does not get any slower if you add more expressions.
Disadvantages are that it requires a huge data table for the automaton, and there are many types of regular expressions that are not supported (for instance, back-references).
The one we used was hand-coded by a C++ template nut in our company at the time, so unfortunately I don't have any FOSS solutions to point you toward. But if you google regex or regular expression with "DFA" you'll find stuff that will point you in the right direction.
Martin Sulzmann Has done quite a bit of work in this field.
He has a HackageDB project explained breifly here which use partial derivatives seems to be tailor made for this.
The language used is Haskell and thus will be very hard to translate to a non functional language if that is the desire (I would think translation to many other FP languages would still be quite hard).
The code is not based on converting to a series of automata and then combining them, instead it is based on symbolic manipulation of the regexes themselves.
Also the code is very much experimental and Martin is no longer a professor but is in 'gainful employment'(1) so may be uninterested/unable to supply any help or input.
this is a joke - I like professors, the less the smart ones try to work the more chance I have of getting paid!
10,000 regexen eh? Eric Wendelin's suggestion of a hierarchy seems to be a good idea. Have you thought of reducing the enormity of these regexen to something like a tree structure?
As a simple example: All regexen requiring a number could branch off of one regex checking for such, all regexen not requiring one down another branch. In this fashion you could reduce the number of actual comparisons down to a path along the tree instead of doing every single comparison in 10,000.
This would require decomposing the regexen provided into genres, each genre having a shared test which would rule them out if it fails. In this way you could theoretically reduce the number of actual comparisons dramatically.
If you had to do this at run time you could parse through your given regular expressions and "file" them into either predefined genres (easiest to do) or comparative genres generated at that moment (not as easy to do).
Your example of comparing "hello" to "[H|h]ello" and ".{0,20}ello" won't really be helped by this solution. A simple case where this could be useful would be: if you had 1000 tests that would only return true if "ello" exists somewhere in the string and your test string is "goodbye;" you would only have to do the one test on "ello" and know that the 1000 tests requiring it won't work, and because of this, you won't have to do them.
If you're thinking in terms of "10,000 regexes" you need to shift your though processes. If nothing else, think in terms of "10,000 target strings to match". Then look for non-regex methods built to deal with "boatloads of target strings" situations, like Aho-Corasick machines. Frankly, though, it seems like somethings gone off the rails much earlier in the process than which machine to use, since 10,000 target strings sounds a lot more like a database lookup than a string match.
Aho-Corasick was the answer for me.
I had 2000 categories of things that each had lists of patterns to match against. String length averaged about 100,000 characters.
Main Caveat: The patters to match were all language patters not regex patterns e.g. 'cat' vs r'\w+'.
I was using python and so used https://pypi.python.org/pypi/pyahocorasick/.
import ahocorasick
A = ahocorasick.Automaton()
patterns = [
[['cat','dog'],'mammals'],
[['bass','tuna','trout'],'fish'],
[['toad','crocodile'],'amphibians'],
]
for row in patterns:
vals = row[0]
for val in vals:
A.add_word(val, (row[1], val))
A.make_automaton()
_string = 'tom loves lions tigers cats and bass'
def test():
vals = []
for item in A.iter(_string):
vals.append(item)
return vals
Running %timeit test() on my 2000 categories with about 2-3 traces per category and a _string length of about 100,000 got me 2.09 ms vs 631 ms doing sequential re.search() 315x faster!.
You'd need to have some way of determining if a given regex was "additive" compared to another one. Creating a regex "hierarchy" of sorts allowing you to determine that all regexs of a certain branch did not match
You could combine them in groups of maybe 20.
(?=(regex1)?)(?=(regex2)?)(?=(regex3)?)...(?=(regex20)?)
As long as each regex has zero (or at least the same number of) capture groups, you can look at what what captured to see which pattern(s) matched.
If regex1 matched, capture group 1 would have it's matched text. If not, it would be undefined/None/null/...
If you're using real regular expressions (the ones that correspond to regular languages from formal language theory, and not some Perl-like non-regular thing), then you're in luck, because regular languages are closed under union. In most regex languages, pipe (|) is union. So you should be able to construct a string (representing the regular expression you want) as follows:
(r1)|(r2)|(r3)|...|(r10000)
where parentheses are for grouping, not matching. Anything that matches this regular expression matches at least one of your original regular expressions.
I would recommend using Intel's Hyperscan if all you need is to know which regular expressions match. It is built for this purpose. If the actions you need to take are more sophisticated, you can also use ragel. Although it produces a single DFA and can result in many states, and consequently a very large executable program. Hyperscan takes a hybrid NFA/DFA/custom approach to matching that handles large numbers of expressions well.
I'd say that it's a job for a real parser. A midpoint might be a Parsing Expression Grammar (PEG). It's a higher-level abstraction of pattern matching, one feature is that you can define a whole grammar instead of a single pattern. There are some high-performance implementations that work by compiling your grammar into a bytecode and running it in a specialized VM.
disclaimer: the only one i know is LPEG, a library for Lua, and it wasn't easy (for me) to grasp the base concepts.
I'd almost suggest writing an "inside-out" regex engine - one where the 'target' was the regex, and the 'term' was the string.
However, it seems that your solution of trying each one iteratively is going to be far easier.
You could compile the regex into a hybrid DFA/Bucchi automata where each time the BA enters an accept state you flag which regex rule "hit".
Bucchi is a bit of overkill for this, but modifying the way your DFA works could do the trick.
I use Ragel with a leaving action:
action hello {...}
action ello {...}
action ello2 {...}
main := /[Hh]ello/ % hello |
/.+ello/ % ello |
any{0,20} "ello" % ello2 ;
The string "hello" would call the code in the action hello block, then in the action ello block and lastly in the action ello2 block.
Their regular expressions are quite limited and the machine language is preferred instead, the braces from your example only work with the more general language.
Try combining them into one big regex?
I think that the short answer is that yes, there is a way to do this, and that it is well known to computer science, and that I can't remember what it is.
The short answer is that you might find that your regex interpreter already deals with all of these efficiently when |'d together, or you might find one that does. If not, it's time for you to google string-matching and searching algorithms.
The fastest way to do it seems to be something like this (code is C#):
public static List<Regex> FindAllMatches(string s, List<Regex> regexes)
{
List<Regex> matches = new List<Regex>();
foreach (Regex r in regexes)
{
if (r.IsMatch(string))
{
matches.Add(r);
}
}
return matches;
}
Oh, you meant the fastest code? i don't know then....