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I just put the finishing touches on the first version of Gigbayes, the learning gig filter.
It aggregates the newest freelance listings from all of the US Craigslists as well as other freelance sites such as rentacoder and elance. It presents the newest gigs to you in one simple box with infinite scrolling.
You train the filter by starring the gigs, or following their links. Over time I’ve found* it gets pretty good at figuring out what you’re looking for.
Under the Hood
I hosted the site on nearly free speech, which is bad because they don’t have mod_whatever’s, everything just runs as plain CGI. But it’s good because it’s so easy put up a quick site, and it’s really cheap since they charge you only by the bandwidth you use. So failed projects cost me nothing.
By the way, my Python framework was the CGI module . It’s very flexible, and doesn’t get in your way. Besides, I find frameworks are too heavy to import anew for every page request (I’m on plain CGI, remember).
I use a modified version of Reverend to do the Bayesian filtering. It seems to be working pretty well.
This is also my first time trying out the gradual user engagement model. So as you can see, you can start viewing and rating gigs right away. You only have to register if you want to save your training. This way there’s no barrier to trying out the tool.
So those are the basics. Let me know in the comments if you have any specific questions about the design. General feedback would also be very appreciated.
* I’m not looking for any freelance gigs right now, so for me, Gigbayes learned that I want quick projects involving no more than pasting some input into one of my already made utilities.
(Well, learned to some degree at least.)