Over the past year, I have been teaching myself Python. I am writing this blog post so I remember how I wish I had learned Python in case I ever need to teach anybody else. My desire to learn Python has been driven by several factors: 1) my laziness and disdain for GUIs (i.e., I hate pointing and clicking); 2) my need to solve complex problems that GUIs would not solve (i.e., GUIs could not solve my problem); and 3) my curiosity to learn new things.
Python is a powerful computer language. I want to use Python for scripting and scientific computing, but many other uses of Python exist. A great way to learn Python and some computer science theory is with the book “Think Python: How to Think Like a Computer Scientist”. The book was originally written by the author for his college class using the Java language. However, he published the book with Creative Commons License and a high school teacher adapted the book for Python! Score one for open source freedom.
After working through this book, I went to the “Invent with Python” books, which are fun (but not necessarily that useful for my goal…). The first book, “Invent Your Own Computer Games with Python” covers basic game designs that are terminal based. The second book, “Making games with Python and Pygame” includes graphics. These books are good because they are simple and fun. If I was simply learning Python for fun, I would start with these books rather than “Think Python”. These books also gave me more experience coding (It’s been said the first 10,000 lines of coding are learning, so at least these gave me a fun couple of thousand), so perhaps the sugar coating of game development worked with me as well.
After these books, dive into subject area books. For me, these were GIS books. “Python Scripting for ArcGIS” does a great job introducing and covering ESRI’s flagship product, ArcGIS. The only downside is that the script is closed source. I decided to stop trying to read source code when a .py file including a warning about being a trade secret. “Learning Geospatial Analysis with Python” is an introduction to advanced (but open source) libraries such as Shapely and GDAL. However, the book is a bit pricey for what you get. But, the book is easier to read than the author’s blog that contains most of the same material. Also note that the ebook kills Pythons tab spacing (Python uses white space such as tabs to define functions and code). Also, I was initially overwhelmed because I did not know GIS or Python my first time reading it. My co-workers copy of “The Geospatial Desktop” provided a great refresher to my GIS skills!
Finally, Learning Python, 5th ed. is a tome, but very through. My own course of study began with the games books. Then I tried “Learning Geospatial Analysis with Python”. Along the way, I bought “Learning Python” and then discovered “Think Python”. I discovered the ArcGIS book only when I needed to script AcrPy for work. Not an optimal course of study, but needing to script ArcGIS has been a great crash course in Python for me. As an added bonus, Python has also made me a better R programmer! Horray for learning.