Using Python to Manipulate Spatial Data (and also possibly to test your ability to refrain from gratuitous use of hyperbole in writing...)

Computer programming, writing script, everything involved with learning the "language of the machines"(so to speak) isn't supposed to be easy. No one will tell you it's easy.  Going into your first class on the subject is intimidating, to say the least, but there isn't really anything to decently prepare an average intellect for the exact nature of the challenge ahead.  The minor victories along the way are as sweet as any devoted student has experienced- spending hours experimenting with this and that to persuade your script to perform the way you require, and finally getting it right.  The rush of satisfaction is unparalleled, but the dark and frustrating hours toiling to get there are enough to render helpless even the most stalwart resolve.  This week and last week were dedicated to grasping the finer points of spatial data manipulation with Python. Some of the concepts in Python introduced were a bit cryptic for a novice, but extensive experimentation with them in creating the assigned script was sufficient to reveal their basic workings, if not some of their many vagaries.

We have with the above screenshot, once again, a section from the printed output of the script that was created for the assignment.  The simple output displayed above is, like the previous assignments for the semester, the mere tip of the iceberg that was the required script.  The required outputs, some of which are displayed in the above screen capture, varied from a simple geodatabase created in a specified location, to a search cursor function that queried a feature class' table to output specific attributes of records meeting certain criteria.  Suffice it to say, getting the right output from the myriad processes the script performed was an epic test of patience for your humble blog author, and fortunately (for all involved) did not result in a frustrated burst of destructive rage.  For example- the concept of a "search cursor" is perhaps not so intuitive to the nascent programmer, and so employing its functionality became a heuristic lesson, as reading about or listening to someone describe these kinds of things isn't always sufficient to create an understanding.  The employment of some SQL functionality in Python and the necessity of "field delimiters" is another case in point from this week's assignment.  The varied plethora of capabilities that the humble list can have within a Python script is also something probably not immediately evident, but when iterated through with a process from a for loop this unassuming structure can be used to complete many a useful task.  In the end, though, after all of the frustration of learning and acquiring various skills and knowledge, the objective has been met- the concepts introduced in this series of lessons are now fully grasped, and a working understanding of the material covered is the prize.  It strikes one as rendering the difficult process of getting there completely worthwhile.