Dear database owner,

I’m not a huge fan of the open letter format - its use for pithy snark has long since diluted whatever potency it once had - so I’ll get right to the point: I want access to your data.

Not in a creepy stalker way, I don’t want to know your three sizes and nor do I want whatever user data you choose to collect. No, I’m talking about the data you have on anime and its minutiae - characters, staff, companies and all the tidbits in between. Whether you call it a database, an encyclopaedia, a list, a planet or otherwise, I’m interested.

But why?

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I was recently tasked with recreating an existing supplier search for a client; I was provided with a database of suppliers, most of which had been geocoded, and not much else. This scenario is fairly standard when dealing with mapping applications: a user enters in a postcode and the system will return a list of the closest suppliers to that location. The postcode part of this equation is well travelled - the Post Office in the UK will not relinquish the mapping from a postcode to a latitude, longitude tuple without a large outlay of cash (and numerous non-disclosure agreements), the easiest option is to use an external service for this. I opted for PostcodeAnywhere as I had used them before with great success. The latter part of this challenge - the return of the closest database entries - was something that I wanted to try myself as I didn't known when I would get such an opportunity again.

To say there are many different ways of calculating the distance between two points would be an understatement. One which I had used before involved northing and easting co-ordinates from a known point within the UK (usually the centroid or London). Using this meant a smattering of trigonometry would be enough to return a decent list of matches; this always struck me as crude, despite it's usefulness, using an antiquated and subjective co-ordinate system seemed the wrong way to approach the problem. Latitude and longitude are globally recognised and provide a precise way of defining points on the globe - reading up on how they are calculated was the step one. Step two was finding an algorithm that calculated the distance between two arbitrary points. The first one I found was the Haversine formula: simple, easy to follow and easy to implement. Knowing that this formula was based upon the assumption that the Earth was perfectly spherical grated slightly with me - I reasoned there must be a more accurate algorithm. I found this precision in Vinencty's algorithm, it was then I decided to enact a contrived but deliciously fun maxim: if something is worth doing, then it's worth overdoing.

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