Let's say I've got such regex (python notation) r'^namespace/(\w+)/([0-9]+)/', is there a way to reverse this regex and find a string fulfilling it?
By reversing I don't mean manual constructing 'namespace/' + 'a_1' + '/' + '1', but systematic way to reverse any regular expression consisting of some special characters. So that for every regex I can generate (any) string fulfilling it.
The only thing that comes to my mind is to parse the given regex with some other regexs, but it does not seem acceptable solution. Although I expect the whole operation to have huge complexity, I still look for at least a bit more sophisticated way to do it.
The only thing that comes to my mind is to parse the given regex with some other regexs, but it does not seem acceptable solution
You don't need to parse the regex with regexes, but yes you will need to parse it. When you have an AST of the regular expression, you can easily traverse that and build a possible match in linear time (for plain regular expression, nothing too fancy like lookaround).
Check Enumerating Regular Languages for an example code and continuative links.
Context:
Say I have a set of strings that are all distinct, though they may share starting sequences, i.e. apple, banana, bpple, canana, applf.
How best would I use a regex to match on a string that can contain any left-starting subset of one of those strings? For example apple and banana would obviously match. So would banan, ba, bp and c. b and appl would be ambiguous (and therefore should not match).
Using generated character classes in dynamically-built regexes (slow and ugly), I can make a match engine for this. However, it's complicated to the point that when I try, I end up doing most of the matching logic in Python/pick-your-language and ditching regex altogether. Is there some succinct way to make this work with regular expressions?
The simplest way to do this might be to break out each possible string (apple, banana etc) into a list and match against each one in sequence, but curiosity and stubbornness make me wonder if there isn't some way to do it with regex alone/primarily.
TL;DR:
Is there a way, using regex, to match: if and only if the string supplied is a unique and left-starting substring of only one of a given set of strings?
Don't use regular expressions. You are asking for the leaves in a trie.
If you absolutely have to use regular expressions, then they could be built like this:
(a(p(p(le?)?)?)?|b(a(n(a(na?)?)?)?)? ...)
It is easy to write some code that constructs this, but you won't be able to find out what actually matched (e. g. the user enters 'app' - you probably want to know that this matches 'apple'). Also, modifying this to ensure that there is no more than one match is really cumbersome. The code that constructs the regex will be much more complicated than just creating a trie (in fact, you probably have to create something equivalent to a trie in order to create the regex, you are asking for).
At the risk of open a can of worms and getting negative votes I find myself needing to ask,
When should I use Regular Expressions and when is it more appropriate to use String Parsing?
And I'm going to need examples and reasoning as to your stance. I'd like you to address things like readability, maintainability, scaling, and probably most of all performance in your answer.
I found another question Here that only had 1 answer that even bothered giving an example. I need more to understand this.
I'm currently playing around in C++ but Regular Expressions are in almost every Higher Level language and I'd like to know how different languages use/ handle regular expressions also but that's more an after thought.
Thanks for the help in understanding it!
Edit: I'm still looking for more examples and talk on this but the response so far has been great. :)
It depends on how complex the language you're dealing with is.
Splitting
This is great when it works, but only works when there are no escaping conventions.
It does not work for CSV for example because commas inside quoted strings are not proper split points.
foo,bar,baz
can be split, but
foo,"bar,baz"
cannot.
Regular
Regular expressions are great for simple languages that have a "regular grammar". Perl 5 regular expressions are a little more powerful due to back-references but the general rule of thumb is this:
If you need to match brackets ((...), [...]) or other nesting like HTML tags, then regular expressions by themselves are not sufficient.
You can use regular expressions to break a string into a known number of chunks -- for example, pulling out the month/day/year from a date. They are the wrong job for parsing complicated arithmetic expressions though.
Obviously, if you write a regular expression, walk away for a cup of coffee, come back, and can't easily understand what you just wrote, then you should look for a clearer way to express what you're doing. Email addresses are probably at the limit of what one can correctly & readably handle using regular expressions.
Context free
Parser generators and hand-coded pushdown/PEG parsers are great for dealing with more complicated input where you need to handle nesting so you can build a tree or deal with operator precedence or associativity.
Context free parsers often use regular expressions to first break the input into chunks (spaces, identifiers, punctuation, quoted strings) and then use a grammar to turn that stream of chunks into a tree form.
The rule of thumb for CF grammars is
If regular expressions are insufficient but all words in the language have the same meaning regardless of prior declarations then CF works.
Non context free
If words in your language change meaning depending on context, then you need a more complicated solution. These are almost always hand-coded solutions.
For example, in C,
#ifdef X
typedef int foo
#endif
foo * bar
If foo is a type, then foo * bar is the declaration of a foo pointer named bar. Otherwise it is a multiplication of a variable named foo by a variable named bar.
It should be Regular Expression AND String Parsing..
You can use both of them to your advantage!Many a times programmers try to make a SINGLE regular expression for parsing a text and then find it very difficult to maintain..You should use both as and when required.
The REGEX engine is FAST.A simple match takes less than a microsecond.But its not recommended for parsing HTML.
I have some problem with my regular expression. I need to find all functions in text. I have this regular expression \w*\([^(]*\). It works fine until text does not contais brackets without function name. For example for this string 'hello world () testFunction()' it returns () and testFunction(), but I need only testFunction(). I want to use it in my c# application to parse passed to my method string. Can anybody help me?
Thanks!
Programming languages have a hierarchical structure, which means that they cannot be parsed by simple regular expressions in the general case. If you want to write correct code that always works, you need to use an LR-parser. If you simply want to apply a hack that will pick up most functions, use something like:
\w+\([^)]*\)
But keep in mind that this will fail in some cases. E.g. it cannot differentiate between a function definition (signature) and a function call, because it does not look at the context.
Try \w+\([^(]*\)
Here I have changed \w* to \w+. This means that the match will need to contain atleast one text character.
Hope that helps
Change the * to + (if it exists in your regex implementation, otherwise do \w\w*). This will ensure that \w is matched one or more times (rather than the zero or more that you currently have).
It largely depends on the definition of "function name". For example, based on your description you only want to filter out the "empty"names, and not want to find all valid names.
If your current solution is largely enough, and you have problems with this empty names, then try to change the * to a +, requiring at least one word character right before the bracket.
\w+([^(]*)
OR
\w\w*([^(]*)
Depending on your regexp application's syntax.
(\w+)\(
regex groups would have the names of variables without any parentesis, you can add them later if you want, i supposed you don't need the parameters.
If you do need the parameters then use:
\w+\(.*\)
for a greedy regex (it would match nested functions calls)
or...
\w+\([^)]*\)
for a non-greedy regex (doesn't match nested function calls, will match only the inner one)
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....