In this blog post I wanted to basically talk about a few different things that has worked well or not so well with Clojure.
Being on 1.4
When the project started, Clojure 1.4 was in alpha. We still decided to run with it, so we were running Clojure 1.4alpha for about one month, and two different betas for another month or so. I have to say I was pleasently surprised – we only had one issue during this time (which had to do with toArray of records, when interacting with JRuby) – and that bug had already been fixed in trunk. The alphas and betas were exceptionally stable and upgrading to the final release of 1.4 didn’t really make any difference from a stack standpoint.
Compojure and Ring
In order to get some dynamic things into our pages, we used Enlive. I really liked the model, and it was quite well suited for the restricted dynamicity we were after.
DSL with lots of data
One of my less bright ideas was to create an internal DSL for some of our data. The core part of the DSL was a bunch of macros that knew how to create domain objects of themselves. This ended up being very clean and a nice model to work with. However, since the data was in the amounts of millions of entries the slowness of actually evaluating that code (and compiling it, and dealing with the permgen issues) ended up getting unbearable. We recently moved to a model that is quite similar, except we don’t evalute the code, instead using read-string on the individual entries to parse them.
Clojure makes it really easy to create quite dense functions. I sometimes find myself combining five or six data structure manipulation functions in one go, then taking a step back and look at the whole thing. It usually makes sense the first time, but coming back to it later, or trying to explain what it does to a pair is usually quite complicated. Clojure has extraordinarily powerful functions for manipulation of data structures, and that makes it very easy to just chain them together into one big mess.
So in order to be nice to my team mates (and myself) I force myself to break up those functions into smaller pieces.
One aspect of breaking up functions like described above, is that the operations involved are usually highly abstract and sometimes not very coupled to domain language. I find naming of those kind of functions very hard, and many times spend a long time and still not coming up with something I’m completely comfortable with. I don’t really have a solution to this problem right now.
For some reason, we haven’t used most of the concurrency aspects of Clojure at all. Maybe this is because our problems doesn’t suit themselves to concurrent processing, but I’m not sure this is the root of the reason. Suffice to say, most of our app is currently quite sequential. We will see if that changes going forward.
I’ve been having a blast with Clojure. It’s clearly the exactly right technology for what I’m currently doing, and it’s got a lot of features that makes it very convenient to use. I’m really looking forward being able to use it more going forward.