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

Flask and its component modules

Flask, as opposed to Django and GeoDjango (covered in Chapter 12, GeoDjango), does not include batteries. Instead, it allows a number of supporting modules to be installed as needed. This gives more freedom to you as the programmer, but it also makes it necessary to install the required components separately.

I've chosen some modules for this chapter that will allow us to create a Flask application with a geospatial component. The following sections will detail how to set up, install, and utilize these modules to generate a website, using a demonstration site with a PostGIS database backend (as covered in Chapter 7, Geoprocessing with Geodatabases) and the ability to perform spatial queries through a web-based interface.


A number of important Python modules must be in place to ensure that the Flask application and its connection to the PostgreSQL and PostGIS database components, will run as required. These modules will be downloaded and installed using...