The one ring to rule them all: Python

Ringfrodo

This lays out why I think all scientists should learn Python first and use it as their primary programming language. I think many of the reasons why scientists should learn Python first are equally applicable to everyone, but computer scientists and others probably have different demands for their primary language.

First, a quick history of languages I have programmed in. My first programming project was as a freshman in college and I used Fortran for simulations of water molecules. Then as a sophomore I used MATLAB for a summer research project that testing components for a high energy experiment. The following summer I used C for a summer research project on stochastic simulations. This was followed by me taking my first programming course where I used Java.

At this point I had used a slew of programming languages, but MATLAB was my primary language. I rarely had to deal with strings or statistics, so MATLAB had everything I needed. This continued into graduate school. Eventually, I ended up doing some bioinformatics, so I had to learn R. And finally, just for the hell of it, I decided to write some code in Python. Additionally, I have used Mathematica, but I wouldn’t count it as a true language.

So this is a really long-winded explanation of why I have some credibility when I say Python is the best (compared to Fortran, C, MATLAB, Java, and R which with I have personal experience). When I started my postdoc, it seemed like the perfect time to make the complete switch to only use Python.

So to start with, why would I recommend it as a first language?

  1. Correct level of difficulty
  2. Pythonic – simple expressions usually work as you would guess
  3. Versatile – can do everything one needs
  4. Open sourced
  5. Community – lots of great packages

And why should scientists use it?

  1. Versatile – handles all data types easily (unlike MATLAB)
  2. Fast enough – Cython, Theano, etc can be used when speed matters
  3. Plenty of scientific packages – Numpy, Scipy, Matplotlib, Scikit-Learn, etc
  4. Large science community – new packages all the time

Additionally, its a language that is popular enough (see here and here) to lead to a job in industry and will safely be around for years to come. So please drink the Kool-Aid and join the Python cult!

 

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