PyDev of the Week: Tyler Reddy | The Mouse vs The Python

PyDev of the Week: Tyler Reddy | The Mouse vs The Python

This week we welcome Tyler Reddy (@Tyler_Reddy) as our PyDev of the Week! Tyler is a core developer of Scipy and Numpy. He has also worked on the MDAnalysis library, which is for particle physics simulation analysis. If you’re interested in seeing some of his contributions, you can check out his Github profile. Let’s spend some time getting to know Tyler better!

Tyler Reddy

Can you tell us a little about yourself (hobbies, education, etc):

I grew up in Dartmouth, Nova Scotia, Canada and stayed there until my late twenties. My Bachelor and PhD degrees were both in biochemistry, focused on structural biology. I did travel a lot for chess, winning a few notable tournaments in my early teen years and achieving a master rating in Canada by my late teens. Dartmouth is also known as the “City of Lakes,” and I grew up paddling on the nearby Lake Banook. In the cold Canadian Winter the lake would freeze over and training would switch to a routine including distance running—this is where my biggest “hobby” really took off. I still run about 11 miles daily in the early morning.

I did an almost six year post-doc in Oxford, United Kingdom. I had started to realize during my PhD that my skill set was better suited to computational work than work on the lab bench. Formally, I was still a biol- ogist while at Oxford, but it was becoming clear that my contributions were starting to look a lot more like applied computer science and computational geometry in particular. I was recruited to Los Alamos National Labora- tory to work on viruses (the kind that make a person, not computer, sick), but ultimately my job has evolved into applied computer scientist here, and nothing beats distance running in beautiful Santa Fe, NM.

Why did you start using Python?

I think it started during my PhD with Jan Rainey in Canada. He was pretty good about letting me explore ways to use programming to make research processes more efficient, even when I might have been better off in the short term by “just doing the science.” Eventually my curiosity grew to the point where I just read one of the editions of Mark Lutz’s “Learning Python” from cover to cover. I very rarely used the terminal to test things out while reading the book—I just kept going through chapters feverishly—I suppose Python is pretty readable! I still prefer reading books to random experimenting when approaching new problems/languages, though I don’t always have the time/luxury to do so. I remember reading Peter Seibel’s “Coders at Work,” and making a list of all the books the famous programmers interviewed there were talking about.

What other programming languages do you know and which is your favorite?

During my second postdoc at Los Alamos I read Stephen Kochan’s “Pro- gramming in C.” For that book I did basically do every single exercise in the terminal as I read it—I found that far more necessary with C than Python to get the ideas to stick. I had made an earlier attempt at reading the classic “The C Programming Language” book by K&R and found it rather hard to learn from! I thought I was doing something wrong since it was described as a classic in “Coders at Work,” I think. I’ll probably never go back to that book now, but I certainly get a lot of mileage out of my C knowledge these days.

I did a sabbatical at UC Berkeley with Stéfan van der Walt and the NumPy core team, working on open source full time for a year. NumPy is written in C under the hood, so it was essential I could at least read the source. A lot of the algorithm implementations in SciPy that I review or write are written in the hybrid Cython (C/Python) language to speed up the inner loops, etc.

I’ve also written a fair bit of tcl, and I write a lot of CMake code these days at work.

Python easily wins out as my favorite language, but C isn’t too far be- hind. I have to agree with the high-profile authors in “Coders at Work” who described C as “beautiful” (or similar) and C++ as, well, something else. Indeed, the NumPy team wrote a custom type templating language in C, processed by Python, instead of using C++. That said, Bjarne did visit UC Berkeley while I was there and it sounds like C++ may be taking a few more ideas from the Python world in the future!

Thanks for doing the interview, Tyler!

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