This is the story of two countries. One of them, Clojureland, is newly founded. It has a very egalitarian society, everyboby is willing to talk to you casually and answer your questions in the same way, regardless of his job or status. The other country, Javaland, has a rigid class system, and an intricate system of courtesy. In order to ask a question to anyone and have him answer with some info or data, you need to know to which of many classes he belongs to. You also need to know who his ancestors are and what classes they belong to. If you do not talk to him in the specific way he expects, he will not answer you at all.
And so it is that when young students from the new land travel to see the old masters to get their wisdom, they get bored and irrate quite quickly. They say, “Why should I care if the old schmuck wants to call his method getName or getLabel? And why can’t I ask him directly about the names?” And they go back to their land and try to reinvent the wisdom of their forebearers in their own data-driven way. Which is not bad, but probably not the fastest path to progress either.
But there is another way. What the students need is a way to ask old masters questions in their own way. What they need is a translator. Let me introduce you to it. Its name is gavagai and it is a cute white rabbit. It is also a parable about the indeterminacy of translation. It acts as a translation dictionary, and helps you get your data out of Javaland.
Let’s take an exemple. Let’s say you want to parse a RSS feed. It is only XML, so theoretically you can easily parse it directly in Clojure. But in fact they are many formats (RSS 0.9, RSS 2.0, Atom, etc.). Also, the Web is a wild place, and you get all sort of junk and malformed fields you have to account for in your parsing. All in all, this is dreary work, and you soon hope someone else had done it for you.
Well someone has. ROME can parse most of what you can throw at it. Let’s see how we can go about getting all the post titles and dates in a feed.
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Not bad, but notice how verbose it would become rather cumbersome if
we wanted more keys. We have a great function to do this,
select-keys, but we need a Clojure data structuire to use it on.
That’s where gavagai comes in.
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That’s much better and easy to read. And that’s how gavagai works in a
nutshell. You define a translator by registering the class names
you’re interested in with
register-converters, then you call
translate with it and an object, and you get back a translated
Clojure data structure. It acts a bit like the core function
But it is recursive, configurable, and faster because most
reflection happens only once when registering the classes in the
translator. It is also quite easy to use from the REPL, which makes it
great to explore big Java APIs.
So, I invite you to look at the README of gavagai for further details. There are a lot of options. You can also look at the tests for more examples.
And if you need to parse some feed and you wonder if this exemple has been turned into a true wrapper, the answer is yes. It’s called clj-rome and it is only 60 lines long thanks to gavagai. This code is a good exemple of real production usage of gavagai.