django-rest-framework-gis

Geographic add-ons for Django Rest Framework - Mailing List.

Install

pip install djangorestframework-gis

Fields

Provides a GeometryField, which is a subclass of Django Rest Framework (from now on DRF) WritableField. This field handles GeoDjango geometry fields, providing custom to_native and from_native methods for GeoJSON input/output.

Serializers

GeoModelSerializer

Provides a GeoModelSerializer, which is a sublass of DRF ModelSerializer. This serializer updates the field_mapping dictionary to include field mapping of GeoDjango geometry fields to the above GeometryField.

For example, the following model:

class Location(models.Model):
    """
    A model which holds information about a particular location
    """
    address = models.Charfield(max_length=255)
    city = models.CharField(max_length=100)
    state = models.CharField(max_length=100)
    point = models.PointField()

By default, the DRF ModelSerializer will output::

{
    "id": 1,
    "address": "742 Evergreen Terrace",
    "city":  "Springfield",
    "state": "Oregon",
    "point": "POINT(-123.0208 44.0464)"
}

In contrast, the GeoModelSerizalizer will output::

{
    "id": 1,
    "address": "742 Evergreen Terrace",
    "city":  "Springfield",
    "state": "Oregon",
    "point": {
        "type": "Point",
        "coordinates": [-123.0208, 44.0464],
    }
}

GeoFeatureModelSerializer

GeoFeatureModelSerializer is a subclass of GeoModelSerializer which will output data in a format that is GeoJSON compatible. Using the above example, the GeoFeatureModelSerializer will output:

 {
    "id": 1,
    "type": "Feature",
    "geometry": {
        "point": {
            "type": "Point",
            "coordinates": [-123.0208, 44.0464],
        },
    },
    "properties": {
        "address": "742 Evergreen Terrace",
        "city":  "Springfield",
        "state": "Oregon"
    }
}

If you are serializing an object list, GeoFeatureModelSerializer will create a FeatureCollection:

(NOTE: This currenty does not work with the default pagination serializer)

{
    "type": "FeatureCollection",
    "features": [
    {
        "id": 1
        "type": "Feature",
        "geometry": {
            "point": {
                "type": "Point",
                "coordinates": [-123.0208, 44.0464],
            }
        },
        "properties": {
            "address": "742 Evergreen Terrace",
            "city":  "Springfield",
            "state": "Oregon",
        }
    }
    {
        "id": 2,
        "type": "Feature",
        "geometry": {
            "point": {
                "type": "Point",
                "coordinates": [-123.0208, 44.0489],
            },
        },
        "properties": {
            "address": "744 Evergreen Terrace",
            "city":  "Springfield",
            "state": "Oregon"
        }
    }
}

GeoFeatureModelSerializer requires you to define a geo_field to be serialized as the "geometry". For example:

class LocationSerializer(GeoFeatureModelSerializer):
    """ A class to serialize locations as GeoJSON compatible data """

    class Meta:
        model = Location
        geo_field = "point"

        # you can also explicitly declare which fields you want to include
        # as with a ModelSerializer.
        fields = ('id', 'address', 'city', 'state')

The primary key of the model (usually the "id" attribute) is automatically put outside the "properties" object (before "type") unless id_field is set to False:

class LocationSerializer(GeoFeatureModelSerializer):

    class Meta:
        model = Location
        geo_field = "point"
        id_field = False
        fields = ('id', 'address', 'city', 'state')

You could also set the id_field to some other unique field in your model, like "slug":

class LocationSerializer(GeoFeatureModelSerializer):

    class Meta:
        model = Location
        geo_field = "point"
        id_field = "slug"
        fields = ('slug', 'address', 'city', 'state')

Filters

We provide a GeometryFilter field as well as a GeometryFilterSet for usage with django_filter. You simply provide, in the query string, one of the textual types supported by GEOSGeometry. By default, this includes WKT, HEXEWKB, WKB (in a buffer), and GeoJSON.

GeometryFilter

from rest_framework_gis.filters import GeoFilterSet

class RegionFilter(GeoFilterSet):
    slug = filters.CharFilter(name='slug', lookup_type='istartswith')
    contains_geom = filters.GeometryFilter(name='geom', lookup_type='contains')

    class Meta:
        model = Region

We can then filter in the URL, using GeoJSON, and we will perform a __contains geometry lookup, e.g. /region/?contains_geom={ "type": "Point", "coordinates": [ -123.26436996459961, 44.564178042345375 ] }.

GeoFilterSet

The GeoFilterSet provides a django_filter compatible FilterSet that will automatically create GeometryFilters for GeometryFields.

InBBOXFilter

Provides a InBBOXFilter, which is a subclass of DRF BaseFilterBackend. Filters a queryset to only those instances within a certain bounding box.

Running the tests

Assuming one has the dependencies installed (restframework and restframework_gis), and one of the Spatial Database server supported by GeoDjango is up and running:

python setup.py test

You might need to tweak the DB settings according to your DB configuration. You can copy the file local_settings.example.py to local_settings.py and change the DATABASES and/or INSTALLED_APPS directives there.

If you want to contribute you need to install the test app in a proper development environment.

These steps should do the trick:

• create a spatial database named "django_restframework_gis"
• create local_settings.py, eg: cp local_settings.example.py local_settings.py
• tweak the DATABASES configuration directive according to your DB settings
• optionally install olwidget with pip install olwidget
• uncomment INSTALLED_APPS (remove olwidget if you did not install it)
• run python manage.py syncdb
• run python manage.py collectstatic
• run python manage.py runserver

Contributing

1. Join the Django REST Framework GIS Mailing List and announce your intentions
2. Follow the PEP8 Style Guide for Python Code
3. Fork this repo
4. Write code
5. Write tests for your code
6. Ensure all tests pass
7. Ensure test coverage is not under 90%
8. Document your changes
9. Send pull request