This week we welcome John Cook as our PyDev of the Week! John has a fun Python blog that I read from to time and he graciously accepted my offer of interviewing him this week. Let’s take a few moments to get to know him better.
Can you tell us a little about yourself (hobbies, education, etc):
I’m a consultant working in the overlap of math, data analysis, and software development. Most projects I do have two of these elements if not all three. I had a variety of jobs before starting my own company, and most of them involved some combination of math and software development.
Why did you start using Python?
What other programming languages do you know and which is your favorite?
I’ve written a lot of C++. When Python isn’t fast enough, I turn to C++, though I don’t do that often. In the last few years I’ve used R, C#, and Haskell on different projects.
I really like the consistency and predictability of Mathematica, though I haven’t used it in a while. I now use Python for the kinds of work I used to do in Mathematica. Even though some things are easier to do Mathematica, it’s worth some extra effort to keep from having to switch contexts and use two languages and environments. And of course Mathematica is expensive. Even if I decide the price of a Mathematica license is worth it for my own use, I can’t ask clients to buy Mathematica licenses.
What projects are you working on now?
Which Python libraries are your favorite (core or 3rd party)?
I use SciPy daily. It’s my favorite in the sense that I depend on it and I’m grateful for the tremendous effort that has gone into it. I can’t say it’s my favorite in terms of API design; I wish it were more consistent and predictable.
I wish I knew pandas and SymPy better. I use them occasionally, but not often enough to keep their syntax in my head.
Conda is a sort of meta library rather than a library per se, but I really appreciate conda. It’s made it so much easier to install packages. I go back and forth between Windows and Linux, and it’s so nice to be able to count on the same libraries in both environments. Before some packages would install smoothly on one OS but not the other.
Where do you see Python going as a programming language?