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A simple django library that generates SLD documents from geographic models.

Project description


A django library that generates SLD documents from geographic models.


  • django Required for models and spatial fields.

  • python-sld Required for reading and generating SLD XML files.

  • pysal Required for classification algorithms.

To install these requirements, you may use pip to install these packages (except for django) with this command:

> sudo pip install -r requirements.txt


> easy_install django-sld


> pip install django-sld


This library implements a single module named “generator” that contains all the methods of interacting with the classification algorithms. Assuming that you have a geographic model in geodjango, you may classify your distribution with by constructing a queryset, and feeding it to the generator.

Assuming you have a spatial model named MySpatialModel, with a data field of population, you can classify all your data into 10 quantile classes with:

from djsld import generator

qs = MySpatialModel.objects.all() sld = generator.as_quantiles(qs, ‘population’, 10)

You may also any queryset to generate classes, such as a filtered queryset:

qs = MySpatialModel.objects.filter(owner__name = ‘David’) sld = generator.as_quantiles(qs, ‘population’, 10)

If your spatial model has a different geometry column name other than ‘geom’, you may specify that field as the geofield keyword:

sld = generator.as_quantiles(qs, ‘population’, 10, geofield=’state’)

The data field may also be distantly related to the queryset in question. For this example, assume that MySpatialModel has a foreign key to a model named Route, and that the data value you would like to classify is a field of the Route model:

sld = generater.as_quantiles(qs, ‘route__traffic’, 10)


If you have any problems, questions, or comments, please visit the django-sld project on github:

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