Quantifying Installation Costs

This post originally appeared on the Software Carpentry website.

A few months ago, I tried to quantify the cost of poor software skills. A recent post from Adam Klein gives is a good excuse to try to do something similar for the cost of installing software. In his post, Klein describes the 17 steps he went through to set up a Python data hacking environment on a new machine. If we assume that each step has a 5% chance of failing for some reason (packages have moved on, the compiler isn't exactly the same version as Klein was using, whatever), then the chances of the whole process working are (1-.05)¹⁷, or roughly 42%. In other words, his process will fail to work the first time for over half of the people who try it. In some cases, they'll be able to figure out why, fix the problem, and move on, but in many others they won't—as I said earlier this week on my personal blog, we've taken something that may or may not be intrinsically hard (programming), and made it much harder by burying under layer upon layer of grief. The end result is that when a scientist sits down to try something new, s/he has no way of knowing whether it will take an hour, a day, or forever. It's hard to build a career on top of that kind of uncertainty...