For the last 13 years I've been a professional software developer in computational chemistry and related fields, and mostly in chemical informatics, molecular modeling, and bioinformatics. I develop scientific software but it often seems distant from what others do at SciPy. For example, I import the numeric libraries about every time there's a name change. The science behind what I work on is more often based on graph theory than on matrices.Thankfully Python is popular in computational chemistry and there are a good number of chemistry tools for Python available, including the OpenEye toolkits and OpenBabel, so I don't often have to work on the low-level details. Much of what I do is tool and algorithm integration, which often means wrapping yet another program and figuring out how it breaks, or writing yet another specialized format parser.In my presentation I'll summarize some of the reasons I think Python became the dominant high-level language in computational chemistry, some of the algorithms and data types which are important to this field, and a few of the key projects.