I began learning python a couple years ago in an effort to diverse my biological skill set. Its been a difficult process, but with some tenacity and perseverance I’ve managed to learn and make great use of the language in my research training. The advantages of learning a programming a language are indeed great. The skills taken away from learning just a single language can empower one to complete daunting tasks in data management and processing – though the applications are probably beyond the sight of the entry level learner.
I began learning Java with an early edition of the ‘Java for Dummies’ series. The series seemed appropriate to me at the time. After completing a few introductory projects, I put the book down and perhaps a year later decided to reinvest myself in to programming, only this time following freely available tutorials online. I had been heavily recommended python as a starter language and later learned that it was not only a more easily digested introductory language to programming but was also as versatile as it was powerful. Today many biological tools are coded in Python and we’ll be discussing some of those tools throughout the series.
This is the first in a series of Python tagged (for organization!) blog entries where I’ll share my thoughts and maybe even some advice on learning python and making use of it in research, and, importantly, when NOT to make use of it. For the computational biologist, a priority aside from optimizing system and program parameters should be optimizing the use of their time. Through these entries, I hope to convince you of the utility of learning python while also sharing details on the language that I have learned during my self guided education, and even some that I have yet to learn at the time of writing this.
Next time, we’ll talk about my path so far learning python so that some of you might follow something similar.