My original post detailing how I recreated Apple's flip-style counter is a popular one, and I get many questions about how to properly implement it. It didn't take long before I saw some shortcomings to the original technique I used, so I thought it was time to revisit the counter and make some improvements.
I rely heavily on regular expressions when processing old data. Like my post about cleaning phone numbers, I'll demonstrate another example of how useful regex can be when dealing with unruly data.
A few months ago, a project bid had me looking at YouTube's JavaScript API for ways to manage a video library through a custom interface. Most of the videos were over 30 minutes, and I thought it would be great if I could provide some analytics on how users were interacting with the videos.
Clicky is an amazing web analytics service. Its killer feature is the ability see data in real-time, allowing you to watch your visitors as they browse your site.
I love Clicky, and I love their API. Because the analytics data is available immediately, I found myself wishing I could have a constant notification of how many visitors were on my site without having to leave a tab or window open all the time.
I also love Google Chrome. As soon as LastPass made an extension for it, Chrome became my default browser. After reading a little about Chrome extensions and how they were just HTML and JavaScript, I knew what my next project would be... ClickyChrome.
When I saw the 10 billion song counter on Apple's website yesterday, I immediately right-clicked on it to see if it was flash. No big surprise to see that it wasn't, this being Apple, and when I saw it was done using JavaScript I knew how I'd be wasting the next few hours.