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Mastering Geospatial Analysis with Python
book

Mastering Geospatial Analysis with Python

by Silas Toms, Paul Crickard, Eric van Rees
April 2018
Beginner to intermediate content levelBeginner to intermediate
440 pages
11h 36m
English
Packt Publishing
Content preview from Mastering Geospatial Analysis with Python

Other data converters

Besides integers, which use the converter int, floating point data can be converted using float, and URL data can be converted using path. Strings, which use the converter string, are the default.  In this case, a float value is captured and used to compare against county geometry areas. As the SRID for this data is in WKID, the area is in an odd format, but this query will work:

@app.route('/nba/api/v0.1/county/query/size/<float:size>', methods=['GET'])def get_county_size(size):  counties = session.query(County).filter(County.geom.ST_Area() > size).all()  data = [{"type": "Feature",   "properties":{"name":county.name,"id":county.id ,"state":county.state.name},   "geometry":{"type":"MultiPolygon",  "coordinates":[shapely.geometry.geo.mapping(to_shape(county.geom))["coordinates"]]}, ...
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Publisher Resources

ISBN: 9781788293334Supplemental Content