Archive for October, 2011

@whensmybus gets a whole lot better

13 October 2011

Wow. It’s been nine days since @whensmybus was released and the feedback has by and large been positive. It’s not all been plain sailing – the odd bug or two made it past my initial testing, and a database update I tried inadvertently corrupted it all. My thanks go to @LicenceToGil, @randallmurrow and @christiane who were all unlucky enough to manage to break it. As a result, I’ve ironed out some of the bugs, and even put in some unit testing to make sure new deployments don’t explode. I now feel this is A Proper Software Project and not a plaything.

Bugfixes are all very well, but… by and far away the most requested feature was to allow people to get bus times without needing a GPS fix, to allow use on Twitter via the web, desktop app or not-so-smartphone. And although using GPS is easier, and cool and proof-of-concepty, it’s plain to see that making access to the app as wide as possible is what makes it really useful. So, from now on you can check the time of a London bus by specifying the location name in the Tweet, such as:

@whensmybus 55 from Clerkenwell

This will try and find the nearest bus stop in Clerkenwell for your bus – in this case, the stops on Clerkenwell Road, which are probably what you’d want). The more precise the location given, the better; place names are OK, street names are better. It works great on postcodes and TfL’s SMS bus stop codes as well.

The geocoding that makes this possible is thanks to the Yahoo! PlaceFinder API, so my thanks goes to them for making a service free for low-volume use. (Aside: you may ask why not use Google Maps? Because Google Maps’s API terms only allow it to be used to generate a map, not for other geo applications like this).

So, play away, and let me know what you think. Of course, it may not always work – geocoding is tricky and not foolproof; if it doesn’t, please let me know in the comments here, or just ping me at @qwghlm on Twitter.

More information and FAQs can be found on the about page, and the technically-minded of you might want to check out the code on github.

Introducing @whensmybus

3 October 2011

A few weeks ago TfL put all their information from Countdown, the service they use to provide bus arrival times, online. There’s a TfL Countdown website and you can enter a bus stop name, or ID number, and find out the latest buses from the stop.

But, it’s a bit fiddly. The main website doesn’t automatically redirect you to the mobile version if you are on a phone. If you type in a location, (e.g. my local Tube station, “Limehouse Station”), you have to pick a match for the location first (from two identically-named options), then a second screen asking you to find a bus stop, and then you get the relevant times. On a phone, it’s just feels fiddly and frustrating especially when I know my phone has GPS in it and knows my location anyway.

Update/correction There is, as it turns out, the ability to find by geolocation on the mobile site, it’s just on a mobile browser I just get the main website and don’t get redirected to the special mobile site, which means I never knew about it (thanks to Ade in the comments for pointing this out).

If only there was a mobile-friendly, geolocation aware, real-time way of fetching information. Oh wait. There is. It’s called Twitter. Twitter has geolocation allowed on Tweets (if you opt in) and an API to fetch and send messages, so we have a system set up already in place for our needs.

I owe a big debt of gratitude to Adrian Short, who wrote a Ruby script to pull bus times from TfL. TfL have not officially released an API for Countdown just yet, but Adrian found it, and it’s there and accessible – providing the data in JSON format for each stop. That use got me thinking – if that data is available and can be parsed quickly and easily, why not make a Twitter bot for it?

With that, @whensmybus was born, and is now in beta. Try it out now if you like. Make sure your Tweet has geolocation turned on (for which you’ll need a GPS-capable smartphone), and send a message like:

@whensmybus 135

Or whatever bus you are looking for. Within 60 seconds, you’ll get a Tweet back with the times of the next buses for that route, in each direction, from the stops closest to your location.

Why each direction? Specifying a direction is fiddly and ambiguous; bus routes wind and twist, and some of them are even circular, so “northbound” and “southbound” are not easy things to parse. The name of your destination can have ambiguous spellings, and I haven’t yet got round to tying it in with a geocoding service like Google Maps. So, at the moment the bot simply tells you buses in both directions from the stops nearest to you. I might change this in future, once I’ve got my head around geolocation services and fuzzy string matching and all that.

It’s still beta (thanks to an early unveiling by Sian ;) ) and I plan in future to add enhancements such as the ability to use without GPS. I also need to write some proper documentation for it, and stick the source code on Github later tonight once I am home. The source code is now available on github, but do bear in mind the codebase is a bit unstable right now. So, if you are a Londoner, please do use it and tell me what you think, either on the comments below or on Twitter. @ me, don’t @ the bot – it will think it’s a request for a bus service and get confused. :) All suggestions are welcome.

(And now, some tech stuff for the more interested)

The bot is a Python script, run every minute via a cronjob. It’s quite short – 350 lines including comments for the main bit. As well as the live data API, the service also uses two databases officially provided by TfL’s syndication service for free; one is of all the routes, and one for all the bus stop locations. I converted these from CSV format to sqlite so the bot can make SQL queries on the data. TfL use OS Easting and Northing locations for the bus stops, so I have to convert the GPS longitude and latitude; I am indebted to Chris Veness and his lat/lng to OS conversion script, which I translated from JavaScript to Python; I am also now much more educated on subtleties like the difference between OSGB36 and WGS84. Finally, I use the Tweepy library to receive and send the Tweets, which is really rather excellent and saves a lot of faff. Finally, the whole project would not be possible without the ideals of open data and open source software behind it, so if you’ve written even a single line of free software, then thank you as well.