Fun with Layars

Last night I installed Layar on my phone, and had some fun checking out the twitter and wikipedia layers. So I signed up for an API key, and 30 seconds later saw a tweet mentioning the California Data Camp. Perfect! After a rare and blissful sleep-in, I wandered over to see what was going on at Citizen Space, thinking I'd try get a proof of concept demo showing some City of SF data in Layar.

Turns out, despite a number of interesting conversations taking precedence over my coding, I managed to get a simple demo working, and even win Honorary Mention (and an iPod touch) for my efforts. And a couple of Layars (crime data and handicapped parking spaces) are just waiting for publishing approval from Layar, and will hopefully be available in a few hours. Just search for "datasf" in your Layar app.

Since GeoDjango was the reason I was able to get a mockup going so quickly, I thought I'd just write a few short notes on the steps I took to build the Layar compatible API, and make the code available. Note that the code here is not particularly pretty - it's the result of a partial afernoon of work (including finding/downloading the layers, going over the layar api docs, and dealing with incredibly spotty internet connectivity). Nonetheless it may be interesting to some geodjango newbies as an example of a quick proof of concept.

The homepage is at http://code.google.com/p/geodjango-layar/, and the wiki includes some play-by-play instructions if you're just getting started with this stuff. Enjoy!

[EDIT]: I now see that someone else (sunlight foundation) had already built a more robust generic view for django, called django-layar. You should definitely use theirs instead .. but if you're curious for more ways to load spatial data into geodjango you might find my notes on google code interesting anyway.

Comments

koe61831 said…
I am not at all worried about the difficulties in studying due to the fact that I have an excellent assistant to justdomyhomework review, which does various written work at a small price competently and efficiently
May 20, 2022 at 1:05 PM
melanicasado32 said…
Hiya! Our paper writer company can help you with 30+ types of homework assignments across 50+ subject matters, including MBA, arts, English literature and language, history, biology, technology, law, and many others.
June 30, 2022 at 12:16 PM
Post a Comment

Popular posts from this blog

Shape Escape

Well it's been a while, so just a quick note: Since the last post, I started working full time for Google. And with that out of the way, here's a post on how and why I made shpescape.com , which lets you upload shapefiles to Google Fusion Tables . Why shpescape? Google Fusion tables makes it easy to import and visualize data from spreadsheets and KML, and while it has increasingly robust spatial support it does not currently let you upload shapefiles directly. And since shapefiles are still incredibly common in the wild, I thought I'd make a quick tool to let people upload shapefiles to Fusion Tables. Which platform? I thought I'd try Google App Engine to avoid any hosting costs (given this will likely not be an extremely popular website), but while there's a decent shapefile reader or two for python, there's not a lot of support for things like reprojecting and other geometry manipulation without additional c++ libraries that App Engine won't
Read more

Walk On

A few months ago, Walkscore.com launched their new API , aimed a Real Estate sites, academic and other largescale studies, and anyone else who might want programmatic access to the walkability of a set of locations. Recently, a number of large sites ( zillow.com , Estately.com , BaseEstate.com , and ColoProperty.com amongst many others) have started to incorporate walkscore in their listings, which has led to the happy situation of ensuring the site can handle the popularity. When the good folks at Walkscore first contacted me about designing the API, we talked about the likelyhood we'd be serving many, many millions of daily requests shortly after launch. This quickly led into discussions about what framework we wanted to build it on, and how much IT we were interested in taking on. Eventually, we decided to use Google's AppEngine . Given the current, and quickly growing, popularity of the API, I think this ended up being a great choice - no worries about having to even
Read more

Featureserver on AppEngine

AppEngine is awesome. The more we use it, the more we like it. Recently, someone contacted us who needed a site up, in a hurry, to serve up some points on a google map. The catch was there were about 50k points (so it seemed server side clustering might be nice). Also they wanted to be able to serve up at _least_ tens of millions of requests a day. And maybe quite a lot more. Given the scaling requirements, it seemed like AppEngine might be a nice fit, since then we wouldn't have to worry so much about tons of caching, or ensuring clients made similar bounding box requests, and so forth. And as for the posting/getting of points to/from appengine, we decided to go for using FeatureServer as a base. If you're not familiar with featureserver, a quick overview: It makes it easy to (amongst other things) post/update your features to some datastore, and pull them out with bounding box and/or attribute queries in a variety of vector formats (kml, json, wfs, etc). Al
Read more