I was always drawn to math and computers, ever since I was a kid playing computer games on my Sinclair ZX81. When I attended university, I had a special interest in numerical analysis, a field that I felt combines math and computers ideally. During my career, I learned of
MATLAB, widely popular for digital signal processing, numerical analysis, and feedback and control. MATLAB’s strong suits include a high-level programming language, excellent graphing capabilities, and numerous packages from almost every imaginable engineering field. But
I found that MATLAB wasn’t enough. I worked with very large files and needed the ability to manipulate both text and data. So I combined Perl, AWK, and Bash scripts to write programs that automate data analysis and visualization. And along the way, I’ve developed practices and ideas involving the organization of data—for example, ways to ensure file names are unique and self-explanatory.
With the increasing popularity of the Internet, I learned of GNU/Linux and the open source movement. I made an effort to use open source software whenever possible, and so I’ve learned of GNU-Octave and gnuplot, which together provide excellent scientific computing functionality. That fit well on my Linux machine: Bash scripts, Perl and AWK, GNU-Octave and gnuplot. Knowing I was interested in programming languages and open source software, a friend suggested I give Python a try. My first impression was that it’s just another programming language: I can do most anything I need with Perl and Bash, resorting to C/C++ if things got hairy.
And I’d still need GNU-Octave and gnuplot, so what’s to gain? Eventually, I did learn Python and discovered that it is far better than my collection of tools. Python provides something that is extremely appealing: it’s a one-stop shop—you can do it all in Python.
I’ve shared my enthusiasm with