I spent most of this week adding more logging to the build, but this time, I was working with groovy instead of Java. I’ve already outlined all my thoughts on groovy and why I find it less than ideal to work with, but ultimately the work has to get done, so I buckled up and galumphed through all the groovy and tried to figure out how it worked, so that the logging would be more effective.

If I haven’t mentioned it already, the build is huge. Massive. There are multiple parts to it, and each part has thousands of lines of code, which are initially not very easy to decipher unless you’re already familiar with the overall structure and function of the build, which itself can take a while. Fortunately, since I’ve been working with the build for a while now, I gained a cursory understanding of how it works, and that seemed to me to be enough to be armed with as I dove into the code. Making a few elementary changes first also helped, and just reading the code (along with some help from QA and Laura, the people who actually work with the build) led to a slightly better understanding of how it worked. It was a very interesting experience, as the build has had to grow with the markets, and the methods of data collection have morphed and evolved as more technologies have introduced different, and possibly better ways of solving the same problem.

The build is majestic. It has, as part of it, code written as far back as 2001, and as recently as two days ago. All these parts work together to supply the company with data continuously. I’m working on implementing something that has a relatively low chance of breaking the build, but even so, making changes to it is a strange feeling, almost like I’m changing something that I shouldn’t be messing with, as it’s far beyond my current capabilities to manage it. Working on it also teaches me more about stocks and how they work, because as I sift through the code looking for where and how I am to insert the necessary logging, I end up internalizing some of the code that explains how the data is collected, and what the different types of data mean.

Well, that’s a very flamboyant way of describing what I’m doing. It’s pretty routine, and looking at large chunks of code for hours on end can get a little enervating, but it’s ultimately worth it. Contrary to how it sounds, it honestly is a lot of fun, and is something I look forward to doing everyday, as I always end up learning something new. I’m hoping to be done with my current project in about a week, so check in next week and find out how I’m doing!