The GoDaddy.com Auto-Renewal Headache

Today I got two emails from GoDaddy.com. One informed me that a few of my domain registrations were about to expire. That was expected; I no longer wanted them. The other was a puzzling order confirmation. My credit card had been charged for renewal of “business registrations” for those same domains.

So while I no longer owned those three domains, I did now have active business registrations for them costing $4.99 each. (I actually can’t even remember what those are or why I had them in the first place.) Great.

It actually took me a few minutes of navigating the insanity that is GoDaddy.com’s website in order to figure out what had happened. Under “Domain Manager,” my settings had auto-renew set to Off for each domain, which was correct. But under the “Business Registration” page, there is no such setting. The interface only allows you to edit profile information. There appears to be NO WAY to turn off the default auto-renewal for business registrations.

To their credit, I was able to call their billing support number, explain my situation, and get a refund. The person I spoke understood immediately what had happened and was extremely helpful.

Beware, GoDaddy customers.

Okay, I lied.

When I needed a break over the holidays from my research, where do I turn? To coding, of course.

I’m a FixedGearGallery addict. The idea of the site is that people send in photos of their fixed-gear bicycles and usually some details about how they built them up. The site is updated every weekday with new entries. Yeah, it’s a little dorky but for bike nuts (like me!), it’s a lot of fun. There are some really creative things people have done with their bikes.

I decided to write a little script to parse the FGG listings and create an index organized by “marque” (make/model). There’s already two search functions on FGG, but my index lets you browse and also provides a count for each marque. It’s just another way to navigate the content.

Here is the link: http://codefork.com/fgg/

Enjoy.

My Perl Hating Days are Over…

… as are my coding days in general. Since September, I’ve returned to grad school.

The decision wasn’t one I made lightly. And with the economic slump, I often wonder if I’ve made a smart choice in taking a 400% pay cut, only to return to teaching and writing my dissertation. In good times, the job prospects for my field were poor; in bad times, they may be practically non-existent.

So why do it? I miss having the kind of intellectual stimulation centered upon social impact. Application programming is challenging and fun, but I no longer find it as fulfilling as I once did or as others do. Increasingly, it is a thankless job where the headaches tend to outweigh personal growth and learning. In the past year, the best gig I had involved smart architecturally-minded people and a strong project lead. And that was pretty nice, though I still felt something missing. The worst gig involved passive aggressive people who mostly feigned their knowledge. It’s interesting that since I left that job, my replacement (a “CTO” who asked for double the salary) did many of the things I recommended, including a complete overhaul of the codebase. Oh well, I guess they needed to hear it from someone other than me.

So this post is a good-bye of sorts. I may still blog occasionally here about technology when the mood strikes. And I have an idea for a project I’d like to do once my time frees up, one that is more about today’s “culture of technology” than about coding.

Thanks to everyone for reading.

Perl Makes You Cry Harder

Slashdot is linking to an ONLamp.com article, Why Corporates Hate Perl. I think it’s interesting that while zealots exist for every language, you rarely encounter the kind of vehement hatred for a language the way you do for perl. Which probably just fuels the antagonism in both directions.

Many Slashdot comments point out that the requirements specific to corporate environments are rather idiosyncratic. Some stress the “right tool for the job” philosophy, which I totally agree with.
And here’s one that makes a wonderful characterization about what perl is and is not:

The problem is, Perl is just a programming language, not a conceptual system. Arguably it is the antithesis of a conceptual system. Many teams then create their own application frameworks atop it (e.g. Mason, POE), and it’s rare for these frameworks to be compatible since Perl offers so many variations in the construction of even standard programming artifacts like classes & objects.

In addition, the level of expression (i.e. TMTOWTDI) means in practice that highly varying programming styles occur throughout large, long-lived bodies of code.

As a result, significant Perl-based business applications tend to become hard-to-maintain hairballs of divergent style and subtly variegated concept.

The root cause: as I started with; the absence of a standard conceptual framework for Perl means that during the early phases of a project, it’s much harder to reason meaningfully about the eventual form of the system than it is with, say, Java or .NET where many of the design patterns are explicitly standardised.

I wouldn’t say that “Corporates Hate Perl”. It’s just the Perl as an application language doesn’t suit the formal design & architecture process we’re seeing increasingly as IT departments start to grow up and realise that they’re not the most important people in the company.

That doesn’t disqualify Perl from being a useful tool, and it’ll always have a place in data transformation, but it does mean that Perl isn’t going to be one of the general-purpose application programming languages of the future.

Bravo. I’d add that what the author identifies as a “problem” is also Perl’s strength. There’s more than one way to do it, so do it as you please. That definitely has allure for many programmers. As a project scales up, though, I think this does in fact become a detriment, and not only for corporate projects.

In response to someone who wrote, “chomp is not ambiguous. RTFM and stop crying,” here’s another awesome comment:

http://perldoc.perl.org/functions/chomp.html [perl.org]
This safer version of “chop” removes any trailing string that corresponds to the current value of $/ (also known as $INPUT_RECORD_SEPARATOR in the English module). It returns the total number of characters removed from all its arguments. It’s often used to remove the newline from the end of an input record when you’re worried that the final record may be missing its newline. When in paragraph mode ($/ = “” ), it removes all trailing newlines from the string. When in slurp mode ($/ = undef ) or fixed-length record mode ($/ is a reference to an integer or the like, see perlvar) chomp() won’t remove anything. If VARIABLE is omitted, it chomps $_ . Example:

If anything I’m crying harder after reading that.

Amen, brother.

Comparing Documentation Methods

I’ve always thought Javadoc was one of the best features of Java. The Javadoc pages for the core API are invaluable for finding what I need very quickly. The utility can be run on any Java source files to generate a nice set of HTML pages that gives you a thousand-foot view of packages, classes, members, and method signatures. Nothing special or extra is required. Of course, you’ll often want to add comments and descriptions and that’s done by following commenting conventions that Javadoc can recognize and insert automatically into its HTML output, but you don’t need to do this for Javadoc to work.

Python’s docstring conventions are not quite as elegant, in my opinion, but they work just as well. Documentation is so much more important in a dynamic language like Python because unlike Javadoc, the pydoc utility can’t determine types. So if a parameter for a function or object method is “user,” one needs to know whether to pass in a User object, a username string, an integer id… or whether any of those will work.

Both Python’s docstring and Javadoc let you document as-you-go, eliminating or reducing the need for documentation as a separate task. If you change something, the documentation is right there for you to update.

Perl’s POD format isn’t nearly as convenient. The markup is oriented more towards layout and formatting rather than following the structure of the code. You can write section headers, indent, and list items in the documentation, but you don’t really attach them to subroutines or methods. Well, you can, sort of, with “=item” but each item must be nested inside other markup, and it feels kludgey and weird. The consequence is that the documentation feels really much separate from the code, even if it resides in the same file. It doesn’t encourage documentation as you go.

In the perl project I worked on, I wrote some POD comments in the very beginning but it fell by the wayside. I should have kept up with it, but it felt like an extra thing to do. My client’s taken over the code, and he’s spending time reading a lot of code to figure out what the parameters should be for various calls. In a dynamic language, there’s no easy way around this if there’s no documentation. Plus perl’s subroutine syntax can make it very difficult to decipher parameter lists quickly. It’s frustrating. I can’t really blame Perl for my own failure to write extensive documentation, but I must say, the idiosyncrasies of POD don’t exactly make it easy.