Working with a programming language as a tool for geoprocessing provides the opportunity to construct a personalized application that can more optimally perform the task required by the user. This means that repetitive tasks can be automated, file inputs and outputs can be customized, and processes can be tuned to perform exactly what you want to be done.
Python is a powerful programming language that is gaining special attention as a tool for geoprocessing and scientific analysis. A number of factors may have contributed to its popularization, and three among them are worth mentioning: it's a scripting language, it's flexible and easy to learn, and it has a wide range of libraries available as open source software.
The number of available libraries and packages allow users to spend less time in programming basic functionalities and more in building processes and workflows to reach their goals.
In this first chapter, we will go through the process of installing all the libraries that you will need to go through the examples; it's likely that these same libraries will also satisfy most of your needs in real-world applications. Then, we will set up an Integrated Development Environment (IDE) that will help organize code and avoid mistakes. Finally, we will write a sample program with one of the libraries. Therefore, here are the topics that will be covered:
Installing Python and the packages that you need for the examples in this book
Learning the basics of the packages that you will use
Installing an IDE to write and organize your code
Creating a project for this book
Writing your first code