Geographic add-ons for Django Rest Framework - Mailing List.
pip install djangorestframework-gispip install https://github.com/djangonauts/django-rest-framework-gis/tarball/masterAdd rest_framework_gis in settings.INSTALLED_APPS, after rest_framework:
INSTALLED_APPS = [
# ...
'rest_framework',
'rest_framework_gis',
# ...
]| DRF-gis version | DRF version | Django version | Python version |
| 0.12.x | 3.1 to 3.7 | 1.11 to 2.0 | 2.7 to 3.6 |
| 0.11.x | 3.1 to 3.6 | 1.7 to 1.11 | 2.7 to 3.6 |
| 0.10.x | 3.1 to 3.3 | 1.7 to 1.9 | 2.7 to 3.5 |
| 0.9.6 | 3.1 to 3.2 | 1.5 to 1.8 | 2.6 to 3.5 |
| 0.9.5 | 3.1 to 3.2 | 1.5 to 1.8 | 2.6 to 3.4 |
| 0.9.4 | 3.1 to 3.2 | 1.5 to 1.8 | 2.6 to 3.4 |
| 0.9.3 | 3.1 | 1.5 to 1.8 | 2.6 to 3.4 |
| 0.9.2 | 3.1 | 1.5 to 1.8 | 2.6 to 3.4 |
| 0.9.1 | 3.1 | 1.5 to 1.8 | 2.6 to 3.4 |
| 0.9 | 3.1 | 1.5 to 1.8 | 2.6, 2.7, 3.3, 3.4 |
| 0.9 | 3.1 | 1.5 to 1.8 | 2.6, 2.7, 3.3, 3.4 |
| 0.9 | 3.1 | 1.5 to 1.8 | 2.6, 2.7, 3.3, 3.4 |
| 0.8.2 | 3.0.4 to 3.1.1 | 1.5 to 1.8 | 2.6, 2.7, 3.3, 3.4 |
| 0.8.1 | 3.0.4 to 3.1.1 | 1.5 to 1.8 | 2.6, 2.7, 3.3, 3.4 |
| 0.8 | 3.0.4 | 1.5 to 1.7 | 2.6, 2.7, 3.3, 3.4 |
| 0.7 | 2.4.3 | 1.5 to 1.7 | 2.6, 2.7, 3.3, 3.4 |
| 0.6 | 2.4.3 | 1.5 to 1.7 | 2.6, 2.7, 3.3, 3.4 |
| 0.5 | from 2.3.14 to 2.4.2 | 1.5 to 1.7 | 2.6, 2.7, 3.3, 3.4 |
| 0.4 | from 2.3.14 to 2.4.2 | 1.5 to 1.7 | 2.6, 2.7, 3.3, 3.4 |
| 0.3 | from 2.3.14 to 2.4.2 | 1.5, 1.6 | 2.6, 2.7 |
| 0.2 | from 2.2.2 to 2.3.13 | 1.5, 1.6 | 2.6, 2.7 |
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.
New in 0.9.3: there is no need to define this field explicitly in your serializer,
it's mapped automatically during initialization in rest_framework_gis.apps.AppConfig.ready().
Provides a GeometrySerializerMethodField, which is a subclass of DRF
SerializerMethodField and handles values which are computed with a serializer
method and are used as a geo_field. See example below.
Deprecated, will be removed in 1.0: Using this serializer is not needed anymore since 0.9.3 if you add
rest_framework_gis in settings.INSTALLED_APPS
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 is a subclass of rest_framework.ModelSerializer
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:
{
"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')geo_field may also be an instance of GeometrySerializerMethodField.
In this case you can compute its value during serialization. For example:
from django.contrib.gis.geos import Point
from rest_framework_gis.serializers import GeoFeatureModelSerializer, GeometrySerializerMethodField
class LocationSerializer(GeoFeatureModelSerializer):
""" A class to serialize locations as GeoJSON compatible data """
# a field which contains a geometry value and can be used as geo_field
other_point = GeometrySerializerMethodField()
def get_other_point(self, obj):
return Point(obj.point.lat / 2, obj.point.lon / 2)
class Meta:
model = Location
geo_field = 'other_point'Serializer for geo_field may also return None value, which will translate to null value for geojson geometry field.
The primary key of the model (usually the "id" attribute) is
automatically used as the id field of each
GeoJSON Feature Object.
The default behaviour follows the GeoJSON RFC,
but it can be disbaled by setting id_field 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')The id_field can also be set to use some other unique field in your model, eg: 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')The GeoJSON specification allows a feature to contain a
boundingbox of a feature.
GeoFeatureModelSerializer allows two different ways to fill this property. The first
is using the geo_field to calculate the bounding box of a feature. This only allows
read access for a REST client and can be achieved using auto_bbox. Example:
from rest_framework_gis.serializers import GeoFeatureModelSerializer
class LocationSerializer(GeoFeatureModelSerializer):
class Meta:
model = Location
geo_field = 'geometry'
auto_bbox = TrueThe second approach uses the bbox_geo_field to specify an additional
GeometryField of the model which will be used to calculate the bounding box. This allows
boundingboxes differ from the exact extent of a features geometry. Additionally this
enables read and write access for the REST client. Bounding boxes send from the client will
be saved as Polygons. Example:
from rest_framework_gis.serializers import GeoFeatureModelSerializer
class LocationSerializer(GeoFeatureModelSerializer):
class Meta:
model = BoxedLocation
geo_field = 'geometry'
bbox_geo_field = 'bbox_geometry'In GeoJSON each feature can have a properties member containing the
attributes of the feature. By default this field is filled with the
attributes from your Django model, excluding the id, geometry and bounding
box fields. It's possible to override this behaviour and implement a custom
source for the properties member.
The following example shows how to use a PostgreSQL HStore field as a source for
the properties member:
# models.py
class Link(models.Model):
"""
Metadata is stored in a PostgreSQL HStore field, which allows us to
store arbitrary key-value pairs with a link record.
"""
metadata = HStoreField(blank=True, null=True, default=dict)
geo = models.LineStringField()
objects = models.GeoManager()
# serializers.py
class NetworkGeoSerializer(GeoFeatureModelSerializer):
class Meta:
model = models.Link
geo_field = 'geo'
auto_bbox = True
def get_properties(self, instance, fields):
# This is a PostgreSQL HStore field, which django maps to a dict
return instance.metadata
def unformat_geojson(self, feature):
attrs = {
self.Meta.geo_field: feature["geometry"],
"metadata": feature["properties"]
}
if self.Meta.bbox_geo_field and "bbox" in feature:
attrs[self.Meta.bbox_geo_field] = Polygon.from_bbox(feature["bbox"])
return attrsWhen the serializer renders GeoJSON, it calls the method
get_properties for each object in the database. This function
should return a dictionary containing the attributes for the feature. In the
case of a HStore field, this function is easily implemented.
The reverse is also required: mapping a GeoJSON formatted structure to
attributes of your model. This task is done by unformat_geojson. It should
return a dictionary with your model attributes as keys, and the corresponding
values retrieved from the GeoJSON feature data.
We provide a GeoJsonPagination class.
Based on rest_framework.pagination.PageNumberPagination.
Code example:
from rest_framework_gis.pagination import GeoJsonPagination
# --- other omitted imports --- #
class GeojsonLocationList(generics.ListCreateAPIView):
# -- other omitted view attributes --- #
pagination_class = GeoJsonPaginationExample result response (cut to one element only instead of 10):
{
"type": "FeatureCollection",
"count": 25,
"next": "http://localhost:8000/geojson/?page=2",
"previous": null,
"features": [
{
"type": "Feature",
"geometry": {
"type": "Point",
"coordinates": [
42.0,
50.0
]
},
"properties": {
"name": "test"
}
}
]
}note: this feature has been tested up to django-filter 1.0.
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.
from rest_framework_gis.filterset import GeoFilterSet
from rest_framework_gis.filters import GeometryFilter
from django_filters import filters
class RegionFilter(GeoFilterSet):
slug = filters.CharFilter(name='slug', lookup_expr='istartswith')
contains_geom = GeometryFilter(name='geom', lookup_expr='contains')
class Meta:
model = RegionWe 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 ] }.
The GeoFilterSet provides a django_filter compatible
FilterSet that will automatically create GeometryFilters for
GeometryFields.
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 # OptionalWe 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,)
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 # OptionalWe 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.
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 # OptionalWe 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%.
- Nodeshot: Extensible Django web application for management of community-led georeferenced data
You need one of the Spatial Database servers supported by GeoDjango, and create a database for the tests.
The following can be used with PostgreSQL:
createdb django_restframework_gis
psql -U postgres -d django_restframework_gis -c "CREATE EXTENSION postgis"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.
This should allow you to run the tests already.
For reference, the following steps will setup a development environment for contributing to the project:
- create a spatial database named "django_restframework_gis"
- create
local_settings.py, eg:cp local_settings.example.py local_settings.py - tweak the
DATABASESconfiguration directive according to your DB settings - optionally install
olwidgetwithpip 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
The recommended way to run the tests is by using tox, which can be installed using pip install tox.
You can use tox -l to list the available environments, and then e.g. use
the following to run all tests with Python 3.6 and Django 1.11:
tox -e py36-django111By default Django's test runner is used, but there is a variation of tox's
envlist to use pytest (using the -pytest suffix).
You can pass optional arguments to the test runner like this:
tox -e py36-django111-pytest -- -k test_fooPlease refer to the tox.ini file for reference/help in case you want to run
tests manually / without tox.
- Join the Django REST Framework GIS Mailing List and announce your intentions
- Follow the PEP8 Style Guide for Python Code
- Fork this repo
- Write code
- Write tests for your code
- Ensure all tests pass
- Ensure test coverage is not under 90%
- Document your changes
- Send pull request