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This will probably be easy for regex magicians, however I can't seem to figure out a way with my limited knowledge.
I need a regex that would check if an alphanumeric string contains a number smaller than a number (16539065 in my case).
For example the following should be matched:
alpha16000000beta
foo300bar
And the following should not be matched:
foo16539066bar
Help please.
EDIT: I'm aware that it's inefficient, however I'm doing it in a cPanel Account Level filter, which only accepts regex. Unless I figure out a way for it to trigger a script instead, this would definitely need to be done with regex. :(
Your best option for this kind of operation is to use a capture group to get the number and then use whatever language you are using to do the comparison. If you absolutely have to use a regex to do this, it will be extremely inefficient. To do so, you will need to combine a lot of similar expressions:
\d{1,7} will find any numbers with 1 to 7 digits, which will always be less than 16539065
1653906[1-4] will catch the absolute maximum values accepted
165390[1-5]\d will catch the next range of acceptable values
1653[1-8]\d{3} will continue on the acceptable range
Repeat the above until you reach 1[1-5]\d{6}
Once you have all of those expressions, they can be combined using the 'or' operator. Keep in mind that using regular expressions in this manner is considered to be bad practice and creates hard to read code.
Bad Karma might kill me, but here is a working solution for your cases (letters then numbers then letters). It will not work for e.g. ab12cd34de.
There is not really a way to shortcode anything, just the long way. I'm using a negative lookahead to check, that the number is not bigger or equal to 16539065.
^\D*(?!0*(?:\d{9}|2\d{7}|1[7-9]\d{6}|16[6-9]\d{5}|165[4-9]\d{4}|16539[1-9]\d{2}|165390[7-9]\d|1653906[5-9]))\d+\D*$
It checks for the general format ^\D*\d+\D*$ and then rolls 16539065 down to it's parts.
Here's a little demo to play around: https://regex101.com/r/aV6yQ9/1
Conditions updated
There is often a situation where you want to extract a substring upto (immediately before) certain characters. For example, suppose you have a text that:
Does not start with a semicolon or a period,
Contains several sentences,
Does not contain any "\n", and
Ends with a period,
and you want to extract the sequence from the start upto the closest semicolon or period. Two strategies come to mind:
/[^;.]*/
/.*?[;.]/
I do either of these quite randomly, with slight preference to the second strategy, and also see both ways in other people's code. Which is the better way? Is there a clear reason to prefer one over the other, or are there better ways? I personally feel, efficiency aside, that negating something (as with [^]) is conceptually more complex than not doing it. But efficiency may also be a good reason to chose one over the other.
I came up with my answer. The two regexes in my question were actually not expressing the same thing. And the better approach depends on what you want.
If you want a match up to and including a certain character, then using
/.*?[;.]/
is simpler.
If you want a match up to right before (excluding) a certain character, then you should use:
/[^;.]*/
Well, the first way is probably more efficient, not that it's likely to matter. By the way, \z in a character class does not mean "end of input"--in fact, it's a syntax error in every flavor I know of. /[^;.]*/ is all you need anyway.
I personally prefer the first one because it does exactly as you would expect. Get all characters except ...
But it's mostly a matter of preference. There are nearly always multiple ways to write a regular expression and it's mostly style that matters.
For example... do you prefer [0-9], [:digit:] or \d? They all do exactly* the same.
* In case of unicode the [:digit:] and \d classes match some other characters too.
you left out one other strategy. string split?
"my sentence; blahblah".split(/[;.]/,2)[0]
I think that it is mostly a matter of opinion as to which regular expression you use. On the note of efficiency, though, I think that adding \A to the beginning of a regular expression in this case would make the process faster because well designed regular expression engines should only try to match once in that case. For example:
/\A[^.;]/m
Note the m option; it indicates that newline characters can also be matched. This is just a technicality I would add for generic examples, but may not apply to you.
Although adding more to the solution might be viewed as increasing complexity, it can also serve to clarify meaning.
Given a regular expression, how can I list all possible matches?
For example: AB[CD]1234, I want it to return a list like:
ABC1234
ABD1234
I searched the web, but couldn't find anything.
Exrex can do this:
$ python exrex.py 'AB[CD]1234'
ABC1234
ABD1234
The reason you haven't found anything is probably because this is a problem of serious complexity given the amount of combinations certain expressions would allow. Some regular expressions could even allow infite matches:
Consider following expressions:
AB[A-Z0-9]{1,10}1234
AB.*1234
I think your best bet would be to create an algorithm yourself based on a small subset of allowed patterns. In your specific case, I would suggest to use a more naive approach than a regular expression.
For some simple regular expressions like the one you provided (AB[CD]1234), there is a limited set of matches. But for other expressions (AB[CD]*1234) the number of possible matches are not limited.
One method for locating all the posibilities, is to detect where in the regular expression there are choices. For each possible choice generate a new regular expression based on the original regular expression and the current choice. This new regular expression is now a bit simpler than the original one.
For an expression like "A[BC][DE]F", the method will proceed as follows
getAllMatches("A[BC][DE]F")
= getAllMatches("AB[DE]F") + getAllMatches("AC[DE]F")
= getAllMatches("ABDF") + getAllMatches("ABEF")
+ getAllMatches("ACDF")+ getAllMatches("ACEF")
= "ABDF" + "ABEF" + "ACDF" + "ACEF"
It's possible to write an algorithm to do this but it will only work for regular expressions that have a finite set of possible matches. Your regexes would be limited to using:
Optional: ?
Characters: . \d \D
Sets: like [1a-c]
Negated sets: [^2-9d-z]
Alternations: |
Positive lookarounds
So your regexes could NOT use:
Repeaters: * +
Word patterns: \w \W
Negative lookarounds
Some zero-width assertions: ^ $
And there are some others (word boundaries, lazy & greedy quantifiers) I'm not sure about yet.
As for the algorithm itself, another user posted a link to this answer which describes how to create it.
Well you could convert the regular expression into an equivalent finite state machine (is relatively simple and can be done algorithmly) and then recursively folow every possible path through that fsm, outputting the followed paths through the machine. It's neither very hard nor computer intensive per output (you will normally get a HUGE amount of output however). You should however take care to disallow potentielly infinite passes (like .*). This can be done by having a maximum allowed path length, after which the tracing is aborted
A regular expression is intended to do nothing more than match to a pattern, that being said, the regular expression will never 'list' anything, only match. If you want to get a list of all matches I believe you will need to do it on your own.
Impossible.
Really.
Consider look ahead assertions. And what about .*, how will you generate all possible strings that match that regex?
It may be possible to find some code to list all possible matches for something as simple as you are doing. But most regular expressions you would not even want to attempt listing all possible matches.
For example AB.*1234 would be AB followed by absolutely anything and then 1234.
I'm not entirely sure this is even possible, but if it were, it would be so cpu/time intensive for many situations that it would not be useful.
For instance, try to make a list of all matches for A.*Z
There are sites that help with building a good regular expression though:
http://www.fileformat.info/tool/regex.htm
http://www.regular-expressions.info/javascriptexample.html
http://www.regextester.com/
I have always written regexes like this
([^<]*)
but I just learned about this lazy thing and that I can write it like this
(.*?)
is there any disadvantage to using this second approach? The regex is definitely more compact (even SO parses it better).
Edit: There are two best answers here, which point out two important differences between the expressions. ysth's answer points to a weakness in the non-greedy/lazy one, in which the hyperlink itself could possibly include other attributes of the A tag (definitely not good). Rob Kennedy points out a weakness in the greedy example, in that anchor texts cannot include other tags (definitely not okay, because it wouldn't grab all the anchor text either)... so the answer is that, regular expressions being what they are, lazy and non-lazy solutions that seem the same are probably not semantically equivalent.
Edit: Third best answer is by Alan M about relative speed of the expressions. For the time being, I'll mark his as best answer so people give him more points :)
Another thing to consider is how long the target text is, and how much of it is going to be matched by the quantified subexpression. For example, if you were trying to match the whole <BODY> element in a large HTML document, you might be tempted to use this regex:
/<BODY>.*?<\/BODY>/is
But that's going to do a whole lot of unnecessary work, matching one character at a time while effectively doing a negative lookahead before each one. You know the </BODY> tag is going to be very near the end of the document, so the smart thing to do is to use a normal greedy quantitier; let it slurp up the whole rest of the document and then backtrack the few characters necessary to match the end tag.
In most cases you won't notice any speed difference between greedy and reluctant quantifiers, but it's something to keep in mind. The main reason why you should be judicious in your use of reluctant quantifiers is the one that was pointed out by the others: they may do it reluctantly, but they will match more than you want them to if that's what it takes to achieve an overall match.
The complemented character class more rigorously defines what you want to match, so whenever you can, I'd use it.
The non greedy regex will match things you probably don't want, such as:
foo
where your first .*? matches
foo" NAME="foo
Note that your examples are not equivalent. Your first regular expression will not select any links that contain other tags, such as img or b. The second regular expression will, and I expect that's probably what you wanted anyway.
Besides the difference in meaning, the only disadvantage I can think of is that support for non-greedy modifiers isn't quite as prevalent as character-class negation is. It's more widely supported than I thought, before I checked, but notably absent from the list is GNU Grep. If the regular-expression evaluators you're using support it, then go ahead and use it.
It's not about better or worse. The term I've seen the most is greedy vs. non-greedy, but however you put they do two different things. You want to use the right one for the task. I.e. turn off the greedy option when you don't want to capture multiple matches in a line.
“lazy” is the wrong word here. You mean non-greedy as opposed to greedy. There's no disadvantage in using it, that I know of. But in your special case, neither should it be more efficient.
Non-greedy is better, is it not? It works forward, checking for a match each time and stopping when it finds one, whereas the normal kleene closure (*) works backwards matching the rest of the input and removing things until it finds a match.
In the end, they do different things, but I think non-greedy outperforms greedy. Bear in mind that I haven't tested this, but now I'm curious.
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....