Regular expressions are extremely useful in extracting information from text such as code, log files, spreadsheets, or even documents. And while there is a lot of theory behind formal languages, the following lessons and examples will explore the more practical uses of regular expressions so that you can use them as quickly as possible.

The first thing to recognize when using regular expressions is that everything is essentially a character, and we are writing patterns to match a specific sequence of characters (also knownas a string). Most patterns use normal ASCII, which includes letters, digits, punctuation and other symbols on your keyboard like %#$@!, but unicode characters can also be used to match any type ofinternational text.

Regular Expressions Made Easy

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You may find it a little odd that a hack who grew up using a language with the ain't keyword would fall so head over heels in love with something as obtuse and arcane as regular expressions. I'm not sure how that works. But it does. Regular expressions rock.They should absolutely be a key part of every modern coder's toolkit.

The quote is from Jamie Zawinski, a world class hacker who I admire greatly. If he's telling us not to use regular expressions, should we even bother? Maybe, if you live and die by soundbites. But there's a bit more to the story than that, as evidenced by Jeffrey Friedl's exhaustive research on the Zawinski quote. Zawinski himself commented on it. Analyzing the full text of Jamie's posts in the original 1997 thread, we find the following:

The first quote is too glib to be taken seriously. But this, I completely agree with. Here's the point Jamie was trying to make: not that regular expressions are evil, per se, but that overuse of regular expressions is evil.

Let me be very clear on this point: If you read an incredibly complex, impossible to decipher regular expression in your codebase, they did it wrong. If you write regular expressions that are difficult to read into your codebase, you are doing it wrong.

Look. Writing so that people can understand you is hard. I don't care if it's code, English, regular expressions, or Klingon. Whatever it is, I can show you an example of someone who has written something that is pretty much indistinguishable from gibberish in it. I can also show you something written in the very same medium that is so beautiful it will make your eyes water. So the argument that regular expressions are somehow fundamentally impossible to write or read, to me, holds no water. Like everything else, it just takes a modicum of skill.

Buck up, soldier. Even Ruby code is hard to read until you learn the symbols and keywords that make up the language. If you can learn to read code in whatever your language of choice is, you can absolutely handle reading a few regular expressions. It's just not that difficult. I won't bore you with a complete explanation of the dozen or so basic elements of regular expressions; Mike already covered this ground better than I can:

What do you see here? The variable name whitelist is a strong hint. One thing I like about regular expressions is that they generally look like what they're matching. You see a list of HTML tags, right? Maybe with and without their closing tags?

RegexBuddy is far and away the best regex tool on the market in my estimation. Nothing else even comes close. But it does cost money. If you don't use software that costs money, there are plenty of alternatives out there. You wouldn't read or write code in notepad, right? Then why in the world would you attempt to read or write regular expressions that way? Before you complain how hard regular expressions are to deal with, get the right tools!

This trouble is worth it, because regular expressions are incredibly powerful and succinct. How powerful? I was able to write a no-nonsense, special purpose HTML sanitizer in about 25 lines of code and four regular expressions. Compare that with a general purpose HTML sanitizer which would take hundreds if not thousands of lines of procedural code to do the same thing.

I've just seen a huge regex for Java that made me think a little about maintainability of regular expressions in general. I believe that most people - except some badass perl mongers - would agree that regular expressions are hardly maintainable.

In this very short example, the common way of creating regular expression is still quite readable to any mediocre talented developer. However, think about those spooky expressions that fill two or more lines with 80 characters each. Sure, the (verbose) fluent interface would require several lines instead of only two, but I'm sure it would be much more readable (hence maintainable).

It's interesting to read that most people think that regular expressions are here to stay - although it takes tools to read them and smart guys to think of ways to make them maintainable. While I'm not sure that a fluent interface is the best way to go, I'm sure that some smart engineers - we? ;) - should spend some time to make regular expressions a thing of the past - it's enough that they've been with us for 50 years know, don't you think?

Fluent languages are not well suited to the recursive nature of regular expressions. So consideration needs to be given to the order of operations. Just chaining methods together does not allow for very complex regular expressions. Exactly the situation where such a tool would be useful.

Long answer:The company I work for makes hardware-based regular expression engines for enterprise content filtering applications. Think running anti-virus or firewall applications at 20GB/sec speeds right in the network routers rather than taking up valuable server or processor cycles. Most anti-virus, anti-spam or firewall apps are a bunch of regex expressions at the core.

The short answer, for me, is that, once you get to regular expressions (or other pattern matching that does the same thing) that are long enough to cause a problem... you should probably be considering if they're the right tool for the job in the first place.

Honestly, any fluent interface seems like it would be harder to read than a standard regular expression. For really short expressions, the fluent version is verbose, but not too long; it's readable. But so is the regular expression for something that long.

I would most likely not. I think this is a case of using the right tool for the job. There are some great answers here such as: 1579202 from Jeremy Stein. I have recently "gotten" regular expressions on a recent project and found them to be very useful just as they are, and when properly commented they are understandable if you know the syntax.

As they say "With great power comes great responsibility." I have seen people use regular expressions everywhere for everything, but used judiciously by someone who has taken the time to learn the syntax thoroughly, they are incredibly helpful; to me, adding another layer would in a way defeat their purpose, or at a minimum take away their power.

This just my own opinion and I can understand where people are coming from who would desire a framework like this, or who would avoid regular expressions, but I have hard time hearing "Regular Expressions are bad" from those who haven't take the time to learn them and make an informed decision.

Neither one of these regular expressions is bulletproof, but they will give you a good starting point for developing your own regular expressions. If you come up with a good one, why not post it as a comment to this article?

We have barely scratched the surface of regular expressions, but we have accomplished what we set out to do. At the beginning of this article, I promised that you would be able to write simple validators, and that you would know enough to dig further into the subject. At this point, you should be able to do both.

Regular Expressions (RegExes) can be thought of as simple computer programs, but they are just as capable of stumping beginners. Inspired by how block-based languages like Snap! made code more accessible to new programmers, I decided to try doing the same for RegEx patterns. This project provides a (hopefully) easy-to-understand set of blocks that let you build RegExes without worrying about the syntax.

In my post about using regular expressions to find matches in a text file, I promised to tell you about the two applications I used to help me write my regex. By the way, Regex is what the cool kids call Regular Expressions.

Along with the naming of regex pattern constants, many (if not most) languages that support regular expressions also support some form of regex comments; C# for example has some excellent documentation on in-line comments.

This happened to me a lot early in my career, particularly when writing Snort signatures or searching for things in a SIEM. Most tools have limited native matching capability, so it always came down to writing regular expressions to dig deeper. I avoided them like the plague.

For the next several nights I locked my door, turned my phone off, stocked up on Coke Zero, and started researching everything I could about regular expressions. I read about how they were formed, what the components were, and different implementations. After several days of research, I tried to apply what I had learned in practical situations.

And now I want to teach you how not to be intimidated by them too, because your ability to write and read regular expressions quickly and effectively is one of the greatest career-enhancing skills I can give you.

Most security analysis and detection tools support matching with regular expressions because of limitations in their own feature set. This means that if you can write regular expressions, you can search with infinite precision. This applies to IDS engines, SIEMs, and even command line tools like grep.

Writing regular expressions is made easier when you have the right tools. The course will introduce you to tools like Espresso and RegeEx Buddy and how they can ease the development process and help you understand and troubleshoot complex expressions. 589ccfa754

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