Regular Expressions – a Powerful Mechanism for Search & Replace Operations and Input Validation

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 \b[A-Za-z0-9._% + -] + @[A-Za-z0-9.-] + \.[A-Za-z]{2,6}\b

The challenge is that it takes a while to learn the use of regular expressions, and beginners are often struggling a lot until they manage to compose such expressions correctly. Nevertheless, it can be very worthwhile to invest a couple of hours into learning that, since you can then solve a lot of problems which would normally have required writing specialized programs (or alternatively a huge amount of manual work). And once you have learned that stuff, you will quickly stumble across additional nice applications.

The principles of regular expressions are explained on various websites. A good example is http://www.regular-expressions.info/tutorialcnt.html. If you want to get started seriously, it could be very useful to get the utility RegExBuddy – a nice assistant, helping you to compose and test regular expressions.

Of course, you can use regular expressions only in software which supports those. In addition, you need to know about that support; for example, I assume that only few users of Microsoft Word are aware that the advanced find & replace dialog box has the option “Use wildcards”, which switches on the support of something like regular expressions – in that case, unfortunately only some subset, lacking essential features.

Some advanced text editors like the above mentioned EditPad Pro offer full support of regular expressions, in that case using the “Regex” option below the search and replace fields.

The same supplier offers the truly amazing search & replace tool PowerGREP. With that, one can perform complex search-and-replace operations on multiple files. I have rarely been so much impressed by a software tool.

Since May 2013, the script language of our software products RP Fiber Power, RP Resonator, RP ProPulse and RP Coating also supports regular expressions:

• The function matches_re() can check whether a string (which may, for example, contain everything from a whole text file) contains certain items, and it can also store found matches in an array.
• The function replace_re() is used for search-and-replace operations. For example, one could find all links in a downloaded html file and insert or remove the nofollow attribute as shown above.
• The function split_re() can split a character string into substrings, where the separator is given as a regular expression. For example, the separator could be defined to be a comma, followed by any number of blank characters.

These functions allow one to perform rather advanced operations with only a little amount of script code. As an example, imagine that you have a text file which defines waveguide parameters of multiple fibers. Each line would contain the fiber's name, its core diameter, the numerical aperture and possibly other data. A script for RP Fiber Power could use a regular expression to extract all these data from the line corresponding to a particular fiber name, identified by a string variable in the script. You would not have to deal with awkward programming, e.g. searching for delimiters, cutting out substrings, etc. Similarly, all sorts of other input data could be conveniently read from text files – for example, CSV files produced by some laboratory instruments, say an optical spectrometer.

Obviously, regular expressions can enormously simplify life when one has to solve certain problems which actually occur quite often in practice. Therefore, they further enhance the great flexibility of simulation software which supports a powerful script language. A software having only a graphical user interface may make it easy to get started, but can never provide the amount of flexibility which is often required in a real life.