Introducing @whensmybus
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.