Book Image

Mastering Geospatial Analysis with Python

By : Silas Toms, Paul Crickard, Eric van Rees
Book Image

Mastering Geospatial Analysis with Python

By: Silas Toms, Paul Crickard, Eric van Rees

Overview of this book

Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis. You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API.
Table of Contents (23 chapters)
Title Page
Copyright and Credits
Packt Upsell
Geoprocessing with Geodatabases

Installing and configuring Django and GeoDjango

Django, compared to Flask, is a batteries-included framework. It includes modules that allow for database backend support, without requiring a separate database code package (unlike Flask, which relies on SQLAlchemy). Django also includes an admin panel that allows for easy data editing and management through a web interface. This means fewer modules are installed and more code is included to handle database interactions and web processing.

There are some major differences between Flask and Django. Django separates URLs from views and models in a more structured manner than Flask. Django also uses Python classes for databases tables, but it has built-in database support. For geospatial databases, no extra module is required. Django also supports geometry columns in a wider range of databases, though PostgreSQL and PostGIS are used the most often. 

Like many Python 3 modules, Django development is geared towards Linux development environments...