djangorestframework-gis 0.8.1

Geographic add-ons for Django Rest Framework

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

Install last stable version from pypi

pip install djangorestframework-gis

Install development version

pip install https://github.com/djangonauts/django-rest-framework-gis/tarball/master

Compatibility with DRF, Django and Python

DRF-gis version	DRF version	Django version	Python version
0.8.1	3.0.4 to 3.1.1	1.5.x to 1.8	2.6 to 3.4
0.8	3.0.4	1.5.x to 1.7	2.6 to 3.4
0.7	2.4.3	1.5.x to 1.7	2.6 to 3.4
0.6	2.4.3	1.5.x to 1.7	2.6 to 3.4
0.5	from 2.3.14 to 2.4.2	1.5.x to 1.7	2.6 to 3.4
0.4	from 2.3.14 to 2.4.2	1.5.x to 1.7	2.6 to 3.4
0.3	from 2.3.14 to 2.4.2	1.5.x, 1.6.x	2.6, 2.7
0.2	from 2.2.2 to 2.3.13	1.5.x, 1.6.x	2.6, 2.7

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 GeoModelSerializer 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:

from rest_framework_gis.serializers import GeoFeatureModelSerializer

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:

from rest_framework_gis.serializers import GeoFeatureModelSerializer

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”:

from rest_framework_gis.serializers import GeoFeatureModelSerializer

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 GeoFilterSet 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.filterset 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.

views.py:

from rest_framework_gis.filters import InBBoxFilter

class LocationList(ListAPIView):

    queryset = models.Location.objects.all()
    serializer_class = serializers.LocationSerializer
    bbox_filter_field = 'point'
    filter_backends = (InBBoxFilter, )
    bbox_filter_include_overlapping = True # Optional

We can then filter in the URL, using Bounding Box format (min Lon, min Lat, max Lon, max Lat), and we can search for instances within the bounding box, e.g.: /location/?in_bbox=-90,29,-89,35.

By default, InBBoxFilter will only return those instances entirely within the stated bounding box. To include those instances which overlap the bounding box, include bbox_filter_include_overlapping = True in your view.

Note that if you are using other filters, you’ll want to include your other filter backend in your view. For example:

filter_backends = (InBBoxFilter, DjangoFilterBackend,)

TMSTileFilter

Provides a TMSTileFilter, which is a subclass of InBBoxFilter. Filters a queryset to only those instances within a bounding box defined by a TMS tile address.

views.py:

from rest_framework_gis.filters import TMSTileFilter

class LocationList(ListAPIView):

    queryset = models.Location.objects.all()
    serializer_class = serializers.LocationSerializer
    bbox_filter_field = 'point'
    filter_backends = (TMSTileFilter, )
    bbox_filter_include_overlapping = True # Optional

We can then filter in the URL, using TMS tile addresses in the zoom/x/y format, eg:. /location/?tile=8/100/200 which is equivalant to filtering on the bbox (-39.37500,-71.07406,-37.96875,-70.61261).

For more information on configuration options see InBBoxFilter.

Note that the tile address start in the upper left, not the lower left origin used by some implementations.

DistanceToPointFilter

Provides a DistanceToPointFilter, which is a subclass of DRF BaseFilterBackend. Filters a queryset to only those instances within a certain distance of a given point.

views.py:

from rest_framework_gis.filters import DistanceToPointFilter

class LocationList(ListAPIView):

    queryset = models.Location.objects.all()
    serializer_class = serializers.LocationSerializer
    distance_filter_field = 'geometry'
    filter_backends = (DistanceToPointFilter, )
    bbox_filter_include_overlapping = True # Optional

We can then filter in the URL, using a distance and a point in (lon, lat) format. The distance can be given in meters or in degrees.

eg:. /location/?dist=4000&point=-122.4862,37.7694&format=json which is equivalant to filtering within 4000 meters of the point (-122.4862, 37.7694).

By default, DistanceToPointFilter will pass the ‘distance’ in the URL directly to the database for the search. The effect depends on the srid of the database in use. If geo data is indexed in meters (srid 3875, aka 900913), a distance in meters can be passed in directly without conversion. For lat-lon databases such as srid 4326, which is indexed in degrees, the ‘distance’ will be interpreted as degrees. Set the flag, ‘distance_filter_convert_meters’ to ‘True’ in order to convert an input distance in meters to degrees. This conversion is approximate, and the errors at latitudes > 60 degrees are > 25%.

Projects using this package

• Nodeshot: Extensible Django web application for management of community-led georeferenced data

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:

./runtests.py

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