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Learning Geospatial Analysis with Python-Second Edition

You're reading from   Learning Geospatial Analysis with Python-Second Edition An effective guide to geographic information systems and remote sensing analysis using Python 3

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Product type Paperback
Published in Dec 2015
Publisher Packt
ISBN-13 9781783552429
Length 394 pages
Edition 1st Edition
Languages
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Author (1):
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Joel Lawhead Joel Lawhead
Author Profile Icon Joel Lawhead
Joel Lawhead
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Toc

Table of Contents (12) Chapters Close

Preface 1. Learning Geospatial Analysis with Python FREE CHAPTER 2. Geospatial Data 3. The Geospatial Technology Landscape 4. Geospatial Python Toolbox 5. Python and Geographic Information Systems 6. Python and Remote Sensing 7. Python and Elevation Data 8. Advanced Geospatial Python Modeling 9. Real-Time Data 10. Putting It All Together Index

PyMySQL


The popular MySQL (available at http://dev.mysql.com/downloads) database is gradually evolving spatial functions. It has support for OGC geometries and a few spatial functions. It also has a pure Python API available in the PyMySQL library. The limited spatial functions use planar geometry and bounding rectangles as opposed to spherical geometry and shapes. The latest development release of MySQL contains some additional functions that improve this capability.

In the following example, we'll create a database in MySQL called spatial_db. Then, we'll add a table called PLACES with a geometry column. Next, we'll add two cities as point locations. And finally, we'll calculate the distance using MySQL's ST_Distance function and then convert the result from degrees to miles:

>>> import pymysql

>>> conn = pymysql.connect(host='localhost', port=3306, user='root', passwd='', db='mysql')
>>> cur = conn.cursor()
>>> cur.execute("DROP DATABASE IF EXISTS spatial_db...
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