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I have not gotten into the field of formal languages in computer science yet, so maybe my question is silly. I am writing a simple NMEA parser in C++, and I have to choose:
My first idea was to build a simple finite state machine manually, but then I thought that maybe I could do it with less work, even more efficiently. I used regular expressions before, but I think the NMEA regular expression is very long and should take "long time" to match it.
Then I thought about using a parser generator. I think all use the same method: they generate a FSA. But I don't know which is more efficient. When do you normally use parser generators instead of regexes (I think you could write regex in parser generator)?
Please explain the differences, I'm interested in both theory and experience.
Well, a simple rule of thumb is: If the grammar of the data you are trying to parse is regular, use regular expressions. If it is not, regular expressions may still work (as most regex engines also support non-regular grammars), but it might well be painful (complicated / bad performance).
Another aspect is what you are trying to do with the parsed data. If you are only interested in one field, a regex is probably easier to read. If you need to read deeply nested structures, a parser is likely to be more maintainable.
Regex is a parser-generator.
From wikipedia:
Regular expressions (abbreviated as regex or regexp, with plural forms regexes, regexps, or regexen) are written in a formal language that can be interpreted by a regular expression processor, a program that either serves as a parser generator or examines text and identifies parts that match the provided specification.
If you're going over a list that only needs to be gone over once, then save the list to a file and read it from there. If you're checking things that are different every time, use regex and store the results in an array or something.
It's much faster than you would assume it to be. I've seen expressions bigger than this post.
Adding that you can nest as much as you'd like, in whatever language you decide to code it in. You could even do it in sections, for maximum re-usability.
As Sneakyness points out, you can have a large and complicated regular expression that is surprisingly powerful. I've seen some examples of this, but none were maintainable by mere mortals. Even using Expresso only helped so much; it was still difficult to understand and risky to modify. So unless you're a savant with a fixation on Grep, I would not recommend this direction.
Instead, consider focusing on the grammar and letting a compiler compiler do the heavy lifting for you.
It strikes me that regular expressions are not understood well by the majority of developers. It also strikes me that for a lot of problems where regular expressions are used, a lump of code could be used instead. Granted, it might be slower and be 20 lines for something like email validation, but if performance of the code is not desperately important, is it reasonable to assume that not using regular expressions might be better practise?
I'm thinking in terms of maintenance of the code rather that straight line execution time.
Maintaining one regular expression is a lot less effort than maintaining 20 lines of code. And you underestimate the amount of code needed - for a regex of any complexity, the replacement code could easily be 200 rather than 20 lines.
Professional developers should be familiar with basic syntax
At the very least. In all the years long I've been a professional developer I haven't come across a developer that wouldn't know what Regular Expressions are. It's true, not everybody likes using them or is very good at knowing its syntax, but that doesn't mean one shouldn't use them. Developers should learn the syntax and regular expressions should be used.
It's like: "Ok. We have Lambda expressions, but who cares, I can still do it the old fashioned way."
Not learning key aspects of professional development is pure laziness and shouldn't be tolerated for too long.
Whenever i use a Regex i always try to leave a comment explaining exactly how it's structured because I agree with you that not all developers understand them and going back to a regex, even if you've written it yourself, can be a headache to understand again.
That said, they definitely have their uses. Try stripping out all html elements from a box of text without it!
I'm thinking in terms of maintenance of the code rather that straight line execution time.
Code size is the single most important factor in reducing maintainability.
And while Regexps can be very hard to decipher, so are 50 line string processing methods - and the latter are more likely to contain bugs in rare corner cases.
The thing is: any non-trivial regexp must be commented just as thoroughly as you'd comment a 50 line method.
Regular expressions are a domain-specific language: no generic programming language is quite as expressive or quite as efficient at doing what regular expressions do with string matching. The sheer size of the lump of code you will have to write in a standard programming language (even one with a good string library) will make it harder to maintain. It is also a good separation-of-concerns to make sure that the regular expression only does the matching. Having a code blob that basically does matching, but does something else in-between can produce some surprising bugs.
Also note that there are mechanisms to make regular expressions more readable. In Python you can enable verbose mode, which allows you to write things like this:
a = re.compile(r"""\d + # the integral part
\. # the decimal point
\d * # some fractional digits""", re.X)
Another possibility is to build the regular expression up from strings, by line and comment each line, like this:
a = re.compile("\d+" # the integral part
"\." # the decimal point
"\d *" # fraction digits
)
This is possible in different ways in most programming languages. My advice is to keep using regular expressions where appropriate, but treat them like you do other code. Write them as clear as possible, comment them and test them.
You raise a very good point with regards to maintainability. Regular expressions can require some deciphering to understand but I doubt the code which would replace them would be easier to maintain. Regular Expressions are VERY powerful and a valuable tool. Use them but use them carefully, and think about how to make it clear what the intent of the regular expression is.
Regards
With great power comes great responsibility!
Regular expressions are great, but there can be a tendancy to over-use them! There are not suitable in all cases!
In my opinion, it might make more sense to enforce better practices with using regular expressesions other than forgoing it all together.
Always comment your regular expressions. You might know what it does now, but someone else might not and even you might not remember in two weeks. Moreover, descriptive comments should be used, stating exactly what the regular expression is meant to do.
Use unit testing. Create unit tests for your regular expressions. So can have a degree of assurance as to the reliability and correctness of your regular expression statement. And if the regex is being maintained, it would ensure that any code changes does not break existing functionality.
Using regular expression has some advantages:
Time. You don't have to write your own code to do exactly what is built in.
Maintainability. You have to maintain only a couple of lines as opposed to 30 or 300
Performance. The code is optimized
Reliability. If your regex statement is correct, it should function correctly.
Flexibility. Regex gives you a lot of power which is very useful if used properly
Think of regular expressions as the lingua Franca of string processing. You simply need to know them if you are going tocode in a professional capacity. Unless you just write SQL maybe.
I would just like to add that unit testing is the ideal way to make your regular expressions maintainable. I consider Regex an essential developer skill that is always a practical alternative to writing many lines of string manipulation code.
The most hassle I see is when people try to parse non-regular languages with regular expressions (yes, that includes all programming and many markup languages, yes, also HTML). I sometimes wish all coders had to demonstrate that they have understood at least the difference between context-free and regular languages before they are allowed to use regular expressions. Alternatively, they could get their regex license revoked when they are caught trying to parse non-regular languages with them. Yes, I'm joking, but only half.
The next problem arises when people try to do more than character matching in a regular expression, for example, checking for a valid date, perhaps even including leap year considerations (this could also lead to regex license revokation).
Regular expressions really are just a convenient shorthand for a finite state automaton (You know what that is, don't you? Where is your regex license, please?). The problems come from people expecting some kind of magic from them, not from the regular expressions themselves.
I see regex as a fast, readable and preferable way to perform pattern matching on string data. So many languages support regex for this reason. If you wanted to write string manipulation code to match say, a Canadian zip code, be my guest, but the regex equivalent is so much more succinct. Definitely worth it.
In .NET regex'es you can have comments, and break them up into multiple lines, use indenting etc. (I don't know about other dialects...)
Use the "ignore pattern whitespace" setting, and either # for commenting out the rest of the line, or "(#comments)" in your pattern...
So if you wanted to, you can actually make them sort of readable/maintainable...
I just ran into this issue. I built a regular expression to pull out groups of data from a long string of numbers and some other noise. The regex was quite long, though concise, and it got even bigger when i tried to add it to the C# app i was writing. In total the reg ex was 3 lines of code.
However it was painful to look at after i escaped it for C# and the other developers i work with don't under stand regular expressions. I ended up stripping out most of the noise characters and splitting on space to get the groups of data. Very simple code and only 5 lines.
Which is better? My ego says Regular Expressions. Any new hire would say character stripping.
I would never wish for fewer options in programming. Regular expressions can be very powerful, but do require skill. I like problems that can be solved in a few lines of code. It is really cool how many elements of validation can be accomplished. As long as the code is commented on what the expression checks for, I do not see a problem. I also have never seen a professional programmer not know what a regex was. It is another tool in the tool box.
Regex is one tool among many. But as many craftsmen will attest, the more tools you have at your disposal, and the more skilled you are at using them, the more likely you will become a Master Craftsman.
Is Regex worth the hassle to you? Dunno. Depends how seriously you take what you do.
It's a lot easier to see at first glance that a regex is probably correct. Why would I write a long state machine in code (probably containing bugs at first) when I could write a simple one line regex?
Regexes may be considered "write only", but I think that is sometimes a benefit. When writing a relatively simple regex from scratch, it's pretty easy to get it right.
True, learning to decipher regexes is difficult -- but so is learning to decipher the hosting program code in the first place. But is that so difficult, that we would rather write out manual instruction for a person to perform? No -- because that would be ridiculously longer and complicated. Same thing for not using a properly-formed regex.
I've found with reg ex it's easier to maintain, but fine tuning someone else's reg ex is a bit of a pain. I think you underestimate the developers by saying most people don't understand it. Usually what I found is that over time, requirements adjust, and the regex that used to validate something is no longer effective and attempting to remove portions that are no longer valid is harder than to just rewrite the entire thing.
Also, imagine if you were validating phone numbers, and you decided to use code instead of reg ex. So it amounts to let's say 20 lines. Over time, your company decides to expand to other regions where now the phone validation is no longer totally true. So you have to adjust it to fit the other requirements. It could be possible that the code would be harder to maintain because you have to adjust over 20 lines of code rather than simply removing the old reg ex, and replacing it with a new one.
However, I think code can be used in certain cases along with regex. For example, let's say you want to validate US phone numbers, in every case, it has 10 digits numbers, but there are literally a ton of ways to write it out. For example (xxx) xxx-xxxx, or xxx-xxx-xxxx, or xxx xxx xxxx, etc, etc, etc. So if you write reg ex, you'd have to account for each of the cases. However, if you just strip all non-numerics and spaces with a regex replace, then go for a second pass and check if it has 10 digits, you'd find it easier than accounting each and every possible way to write a phone number.
One thing that doesn't seem mentioned (from a quick scan of the answers above) is that regular expressions are useful outside of code too. That means they are worth the hassle for a coder, or even for end users.
For example, I just wrote a bunch of unit tests for a formatter. I then made a copy of the test, and used a single regex in my editor to invert values and resulting strings (changing the method name too), giving expected value to a string to parse...
Another example: in our product, we allow using regular expressions for searching or filtering columns of data: sometime it is useful to get only names starting with something, ending with something, with letters followed by digits, or similar: no need to be a master of regexes to use them.
In these cases, writing code isn't an option (well, I could have made a small Lua script in the first case, but it would have been longer) and performance isn't a major issue.
But even in code, I often find easier and more readable to use a simple regular expression than a bunch of substring() with complex offsets and whatnot. Beside, they shine to validate user input where, again, performance isn't an issue.
Due to the type of apps I build, the only RegEx's I regularly use are for email validation, html stripping, and character stripping to remove the garbage around phone numbers.
It's rare that I need to do very much string manipulation other than concatenation.
Incidentally, the apps are typically CRM's.
So the hassle for me is limited to googling for a regex in the event I find myself in need. ;)
Read the section under "Using Benchmarks" at JavaWorld.
Sure regular expressions are a very helpful tool, but I agree that they are overused and over complicate what can easily be a simple solution.
That being said, you should use regular expressions whenever the situation calls for it. Some things, such as searching for text in a string, can just as easily be done with an iterative search (or using the API searches), but for more complex situations you need regular expressions.
Surly all code needs to be optimized where possible!
In the context where code need not be optimized, and the logic will need to be maintained then it is down to the skill set of the team.
If the bulk of the team responsible for the code is regEX savvy then do it with a regEX. Else write it in the way the team is likely to be most comfortable with.
VB.net is best, No, C# is, No F# is the best. It's really more a matter of what will be the people maintaining be better suited to handle, in my opinion. That's more a flame question, than something that is absolutely answerable.
Personally I'd choose regex whenever there's complex string validation (phone numbers,emails, ss#, ip addresses) where there are well known regex's out there. Get it from regex.org, give attribution with a comment and/or get the authors permission whichever is appropriate, and be done with it.
Also, for extracting pieces of a string, or complex splitting of strings, regex can be a great time saver.
But if you're writing your own, rather than using someone else's, using something like regex buddy or sells brothers regexdesigner is a must for testing and validation.
It always depends on where it's used. If by doing the same task using a lump of code is being too complex and hard to maintain which can be a 1 liner less complex regex, then go with regex. Other wise use the lump of code.
Also I encountered problems which can I believe can only be answered by regex effective and concisely. Such question like this which can only be answered by another regex effectively: Dart regex for capturing groups but ignoring certain similar patterns
i dunno, but will your machine suffer great slowdown if you use a very complex regex?
like for example the famous email validation module proposed just recently? which can be found here RFC822
update: sorry i had to ask this question in a hurry anyway i posted the link to the email regex i was talking about
It highly depends on the individual regex: features like look-behind or look-ahead can get very expensive, while simple regular expressions are fine for most situations.
Tutorials on http://www.regular-expressions.info/ offer performance advice, so that can be a good start.
Regexes are usually implemented as one of two algorithms (NFA or DFA) that correspond to two different FSMs. Different languages and even different versions of the same language may have a different type of regex. Naturally, some regexes work faster in one and some work faster in the other. If it's really critical, you might want to find what type of regex FSM is implemented.
I'm no expert here. I got all this from reading Mastering Regular Expressions by Jeffrey E. F. Friedl. You might want to look that up.
Depends also on how well you optimise your query, and knowing the internal working of regex.
Using the negated character class, for example, saves the cost of having the engine backtracking characters (i.e. /<[^>]+>/ instead of /<.+?>/)(*).Trivial in small matches, but saves a lot of cycles when you have to match inside a big chunk of text.
And there are many other ways to save resources in regex operations, so performance can vary wildly.
example taken from http://www.regular-expressions.info/repeat.html
You might be interested by articles like: Regular Expression Matching Can Be Simple And Fast or Understanding Regular Expressions.
It is, alas, easy to write inefficient REs, which can match quite quickly on success but can look for hours if no match is found, because the engine stupidly try a long match on every position of a long string!
There are a few recipes for this, like anchoring whenever it is possible, avoiding greediness if possible, etc.
Note that the giant e-mail expression isn't recent, and not necessarily slow: a short, simple expression can be slower than a more convoluted one!
Note also that in some situations (like e-mail, precisely), it can be more efficient (and maintainable!) to use a mix of regexes and code to handle cases, like splitting at #, handling different cases (first part starts with " or not, second part is IP address or domain, etc.).
Regexes are not the ultimate tool able to do everything, but it is a very useful tool well worth to master!
It depends on your regexp engine. As explained here (Regular Expression Matching Can Be Simple And Fast) there may be some important difference in the performance depending on the implementation.
You can't talk about regexes in general any more than you can talk about code in general.
Regular expressions are little programs on their own. Just as any given program may be fast or slow, any given regex may be fast or slow.
One thing to remember, however, is that the regular expression handler is is very well optimized to do its job and run the regex quickly.
I once made a program that analyzed a lot of text (a big code base, >300k lines). First I used regex but when I switched to using regular string functions it got a lot faster, like taking 40% of the time of the regex version. So while of course it depends, my thing got a lot faster.
Once I had written a greedy - accidentally, of course :-) - a multi-line regex and had it search/replace on 10 * 200 GB of text files. It was damn slow... So it depends what you write, and what you check.
Depends on the complexity of the expression and the language the expression is used with.
In JavaScript; you have to optimize everything. In C#; not so much.
I don’t understand or see the need for regular expressions.
Can some explain them in simple terms and provide some basic examples where they could be useful, or even critical.
Use them where you need to use/manipulate patterns. For instance, suppose you need to recognise the following pattern:
Any letter, A-Z, either upper or lower case, 5 or 6 times
3 digits
a single letter a-z (definitely lower case)
(Things like this crop up for zip code, credit card, social security number validation etc.)
That's not really hard to write in code - but it becomes harder as the pattern becomes more complicated. With a regular expression, you describe the pattern (rather than the code to validate it) and let the regex engine do the work for you.
The pattern here would be something like
[A-Za-z]{5,6}[0-9]{3}[a-z]
(There are other ways of expressing it too.) Grouping constructs make it easy to match a whole pattern and grab (or replace) different bits of it, too.
A few downsides though:
Regexes can become complicated and hard to read quite quickly. Document thoroughly!
There are variations in behaviour between different regex engines
The complexity can be hard to judge if you're not an expert (which I'm certainly not!); there are "gotchas" which can make the patterns really slow against particular input, and these gotchas aren't obvious at all
Some people overuse regular expressions massively (and some underuse them, of course). The worst example I've seen was where someone asked (on a C# group) how to check whether a string was length 3 - this is clearly a job for using String.Length, but someone seriously suggested matching a regex. Madness. (They also got the regex wrong, which kinda proves the point.)
Regexes use backslashes to escape various things (e.g. use . to mean "a dot" rather than just "any character". In many languages the backslash itself needs escaping.
What regular expressions are used for:
Regular expressions is a language in itself that allows you to perform complex validation of string inputs. I.e. you pass it a string and it will return true or false if it is a match or not.
How regular expressions are used:
Form validation, determine if what the user entered is of the format you want
Finding the position of a certain pattern in a block of text
Search and replace where the search term is a regex and what to replace is a normal string.
Some regular expression language features:
Alternation: allows you to select one thing or another. Example match only yes or no.
yes|no
Grouping: You can define scope and have precedence using parentheses. For example match 3 color shades.
gr(a|e)y|black|white
Quantification: You can quantify how much of something you want. ? means 1 or 0, * means 0 or more. + means at least one. Example: Accept a binary string that is not empty:
(0|1)+
Why regular expressions?
Regular expressions make it easy to match strings, it can often replace several dozen lines of source code with a simple small regular expression string.
Not for all types of matching:
To understand how something is useful, you should also understand how it is not useful. Regular expressions are bad for certain tasks for example when you need to guarantee that a string has an equal number of parentheses.
Available in just about all languages:
Regular expressions are available in just about any programming language.
Formal language:
Any regular expression can be converted to a deterministic finite state machine. And in this same way you can figure out how to make source code that will validate your regular expression.
Example:
[hc]+at
matches "hat", "cat", "hhat", "chat", "hcat", "ccchat", and so on, but not "at"
Source, further reading
They look a bit cryptic but they provide a very powerful tool for finding patterns in text. Anything from href tags in HTML pages to validating email addresses.
And they can be processed into a very efficient data structure (FSA) that finds matches very fast.
They are a bit tricky, but extremely powerful and worth learning. The web is full of tutorial and examples, start for example from here and look at the examples here.
If I could direct the OP to some of the answers/comments on one of my own questions: How important is knowing Regexs?
Regular expressions are a very concise way to specify most pattern-matching and -replacement problems, and regexp engines can be very highly optimized.
If you wanted to do the same job as even a relatively simple regexp, you'd have to write a lot of code, which probably would contain a number of bugs, be hard to understand and perform badly.
Whereas doing the same with a regexp is much shorter, almost certainly performs as well as is technically possible, and is easier to understand to anyone familiar with regexpes (though it should be commented in either case)
The email example is actually a bad example for regular expressions. Regexes can be used, but the resulting expression (for example this one which doesn't handle "John Doe " style addresses) is hugely complicated - take a look at the email address specification and you'll see why...
However regexes are very useful in a host of other situations, extracting ip addresses from text, tags from html etc. Finding all versioned files would be another example. Something along the lines of:
my_versioned_file_(\d{4}-\d{2}-\d{2}).txt
will match any filenames of the format my_versioned_file_2009-02-26.txt and pull out the date as a captured group (the part wrapped in "()") for you to further analyse.
No regexes are not necessary, but they can save a world of time in writing a hand rolled parser for something a regex can easily achieve.
Whenever you've got some pattern to find in a lot of textual data or if you want to check that a string is in a certain format.
For example an email address...
The code for checking for an at symbol and the presence of a valid domain will look quite big where you could just use a regular expression and have an answer in 2 lines of code.
Regex r = new Regex("<An Email Address Regex>");
bool isValidEmail = r.IsMatch(MyInput);
Other examples would be for checking numbers are in the correct format before parsing them into integers etc.
Jon and Sqook gave a fine explanation and definition of Regular Expressions, and for simple problems it is pretty understandable, but if you use it for complex problems regular expressions can be a &$#( (at least for me ;-))
I use Expresso a lot to help me build complex regular expression code.
http://www.ultrapico.com/Expresso.htm
It has a build in library with expressions you can use, a design mode where you can build your code and a test mode where you can test and validate the code. It helped me build and understand complex expressions better!
Goodluck!
Some practical real world usages:
Finding abstract classes that extend JUnit's TestCase:
abstract\s+class\s+\w+\s+extends\s+TestCase
This is useful for finding test cases that cannot be instantiated and will need excluding from an ant build script that runs test cases. You cannot search for regular text because you don't know the class names in advance. hence the \w+ (At least one word character).
Finding running bash or bourne shell scripts:
ps -e | grep -e " sh| bash"
this is useful if you want to kill them all or something, if you did a search for just sh you'd not get the bash ones and have to run the command again for bash scripts. Again, more serviceable than perfect, but nearly no regex you write on the fly will be.
It's not perfect, but most regexes won't be, or they'll take so long to write they're not worth it. The ones you perfect are the ones you commit as part of some sort of validation or built application.
Example of critical use is JavaScript:
If you need to do search or replace on a string, the only matching you can do is a regular expression. It's in the JavaScript API on those string methods...
Personally, I mostly use regular expressions only when I need some advanced matching in some automated find/replace in a text editor (TextPad or Visual Studio). The most powerful feature in my view is the ability to match a pattern that can be inserted in the replace.
To give you some examples:
Email Address
Password requires at least 1 alphabet and 1 digit
How can you acheive these requirements?
The best way is to use regular expression.
Read the following links to learn more:
How To: Use Regular Expressions to Constrain Input in ASP.NET
http://msdn.microsoft.com/en-us/library/ms998267.aspx
Please don't answer the obvious, but what are the limit signs that tell us a problem should not be solved using regular expressions?
For example: Why is a complete email validation too complex for a regular expression?
Regular expressions are a textual representation of finite-state automata. That is to say, they are limited to only non-recursive matching. This means that you can't have any concept of "scope" or "sub-match" in your regexp. Consider the following problem:
(())()
Are all the open parens matched with a close paren?
Obviously, when we look at this as human beings, we can easily see that the answer is "yes". However, no regular expression will be able to reliably answer this question. In order to do this sort of processing, you will need a full pushdown automaton (like a DFA with a stack). This is most commonly found in the guise of a parser such as those generated by ANTLR or Bison.
A few things to look out for:
beginning and ending tag detection -- matched pairing
recursion
needing to go backwards (though you can reverse the string, but that's a hack)
regexes, as much as I love them, aren't good at those three things. And remember, keep it simple! If you're trying to build a regex that does "everything", then you're probably doing it wrong.
When you need to parse an expression that's not defined by a regular language.
What it comes down to is using common sense. If what you are trying to match becomes an unmanageable, monster regular expression then you either need to break it up into small, logical sub-regular expressions or you need to start re-thinking your solution.
Take email addresses (as per your example). This simple regular expression (taken from RegEx buddy) matches 99% of all emails out there:
\b[A-Z0-9._%+-]+#[A-Z0-9.-]+\.[A-Z]{2,4}\b
It is short and to the point and you will rarely run into issues with it. However, as the author of RegEx buddy points out, if your email address is in the rare top-level domain ".museum" it will not be accepted.
To truely match all email addresses you need to adhere to the standard known as RFC 2822. It outlines the multitude of ways email addresses can be formatted and it is extremely complex.
Here is a sample regular expression attempting to adhere to RFC 2822:
(?:[a-z0-9!#$%&'*+/=?^_`{|}~-]+(?:\.[a-z0-9!#$%&'*+/=?^_`{|}~-]+)*|"
(?:[\x01-\x08\x0b\x0c\x0e-\x1f\x21\x23-\x5b\x5d-\x7f]|\\[\x01-\x09\x0b\x
0c\x0e-\x7f])*")#(?:(?:[a-z0-9](?:[a-z0-9-]*[a-z0-9])?\.)+[a-z0-9]
(?:[a-z0-9-]*[a-z0-9])?|\[(?:(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.)
{3}(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?|[a-z0-9-]*[a-z0-9]:(?:[\x01-\x08
\x0b\x0c\x0e-\x1f\x21-\x5a\x53-\x7f]|\\[\x01-\x09\x0b\x0c\x0e-\x7f])+)\])
This obviously becomes a problem of diminishing returns. It is better to use the easily maintained implementation that matches 99% of email addresses vs the monsterous one that accepts 99.9% of them.
Regular expressions are a great tool to have in your programmers toolbox but they aren't a solution to all your parsing problems. If you find your RegEx solution starting to become extremely complex you need to either attempt to logically break it up into smaller regular expressions to match portions of your text or you need to start looking at other methods to solve your problem. Similarly, there are simply problems that Regular Expressions, due to their nature, can't solve (as one poster said, not adhering to Regular Language).
Regular expressions are suited for tokenizing, finding or identifying individual bits of text, e.g. finding keywords, strings, comments, etc. in source code.
Regular expressions are not suited for determining the relationship between multiple bits of text, e.g. finding a block of source code with properly paired braces. You need a parser for that. The parser can use regular expressions for tokenizing the input, while the parser itself determines how the different regex matches fit together.
Essentially, you're going to far with your regular expressions if you start thinking about "balancing groups" (.NET's capture group subtraction feature) or "recursion" (Perl 5.10 and PCRE).
Here's a good quote from Raymond Chen:
Don't make regular expressions do what they're not good at. If you want to match a simple pattern, then match a simple pattern. If you want to do math, then do math. As commenter Maurits put it, "The trick is not to spend time developing a combination hammer/screwdriver, but just use a hammer and a screwdriver.
Source
Solve the problem with a regex, then give it to somebody else conversant in regexes. If they can't tell you what it does (or at least say with confidence that they understand) in about 10 minutes, it's too complex.
Sure sign to stop using regexps is this: if you have many grouping braces '()' and many alternatives '|' then it is a sure sign that you try to do a (complex) parsing with regular expressions.
Add to the mix Perl extensions, backreferences, etc and soon you have yourself a parser that is hard to read, hard to modify, and hard to reason about it's properties (e.g. is there an input on which this parser will work in a exponential time).
This is a time to stop regexing and start parsing (with hand-made parser, parser generators or parser combinators).
Along with tremendous expressions, there are principal limitations on the words, which can be handled by regexp.
For instance you can not not write regexp for word described by n chars a, then n chars b, where n can be any, more strictly .
In different languages regexp is a extension of Regular language, but time of parsing can be extremely large and this code is non-portable.
Whenever you can't be sure it really solves the problem, for example:
HTML parsing
Email validation
Language parsers
Especially so when there already exist tools that solve the problem in a totally understandable way.
Regex can be used in the domains I mentioned, but only as a subset of the whole problem and for specific, simple cases.
This goes beyond the technical limitations of regexes (regular languages + extensions), the maintainability and readability limit is surpassed a lot earlier than the technical limit in most cases.
A problem is too complex for regular expressions when constraints of the problem can change after the solution is written. So, in your example, how can you be sure an email address is valid when you do not have access to the target mail system to verify that the email address is attached to a valid user? You can't.
My limit is a Regex pattern that's about 30-50 characters long (varying depending on how much is fixed text and how much is regex commands)
This may sound stupid but I often lament not being able to do database type of queries using regular expression. Now especially more then before because I am entering those types of search string all the time on search engines. its very difficult, if not impossible to search for +complex AND +"regular expression"
For example, how do I search in emacs for commands that have both Buffer and Window in their name? I need to search separately for .*Buffer.*Window and .*Window.*Buffer