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Python Geospatial Development

You're reading from   Python Geospatial Development Develop sophisticated mapping applications from scratch using Python 3 tools for geospatial development

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Product type Paperback
Published in May 2016
Publisher
ISBN-13 9781785288937
Length 446 pages
Edition 3rd Edition
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Author (1):
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Erik Westra Erik Westra
Author Profile Icon Erik Westra
Erik Westra
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Table of Contents (15) Chapters Close

Preface 1. Geospatial Development Using Python FREE CHAPTER 2. GIS 3. Python Libraries for Geospatial Development 4. Sources of Geospatial Data 5. Working with Geospatial Data in Python 6. Spatial Databases 7. Using Python and Mapnik to Generate Maps 8. Working with Spatial Data 9. Improving the DISTAL Application 10. Tools for Web-based Geospatial Development 11. Putting It All Together – a Complete Mapping System 12. ShapeEditor – Importing and Exporting Shapefiles 13. ShapeEditor – Selecting and Editing Features Index

Mapnik concepts


In this section, we will examine the Python interface to the Mapnik toolkit in more detail. Since there are too many features to cover in their entirety, we will concentrate on the most important aspects of Mapnik that you are likely to use in your own programs. Feel free to refer to the Mapnik documentation (http://mapnik.org/docs) for anything not covered in this chapter.

Data sources

A data source object acts as a "bridge" between Mapnik and your geospatial data. You typically create the data source using one of the following convenience constructors and then add that data source to any Mapnik Layer objects that use that data:

layer.datasource = datasource

There are many different types of data sources supported by Mapnik, though some are experimental or access data in commercial databases. Let's take a closer look at the types of data sources you are most likely to find useful.

Shapefile

It is easy to use a shapefile as a Mapnik data source. All you need to do is supply the...

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