GeoQuerySet
([model=None])¶Just like when using the QuerySet API, interaction
with GeoQuerySet
by chaining filters.
Instead of the regular Django Field lookups, the
spatial lookups in this section are available for GeometryField
.
For an introduction, see the spatial lookups introduction. For an overview of what lookups are compatible with a particular spatial backend, refer to the spatial lookup compatibility table.
Availability: PostGIS, MySQL, SpatiaLite
Tests if the geometry field’s bounding box completely contains the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__bbcontains=geom)
Backend  SQL Equivalent 

PostGIS  poly ~ geom 
MySQL  MBRContains(poly, geom) 
SpatiaLite  MbrContains(poly, geom) 
Availability: PostGIS, MySQL, SpatiaLite
Tests if the geometry field’s bounding box overlaps the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__bboverlaps=geom)
Backend  SQL Equivalent 

PostGIS  poly && geom 
MySQL  MBROverlaps(poly, geom) 
SpatiaLite  MbrOverlaps(poly, geom) 
Availability: PostGIS, MySQL, SpatiaLite
Tests if the geometry field’s bounding box is completely contained by the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__contained=geom)
Backend  SQL Equivalent 

PostGIS  poly @ geom 
MySQL  MBRWithin(poly, geom) 
SpatiaLite  MbrWithin(poly, geom) 
Availability: PostGIS, Oracle, MySQL, SpatiaLite
Tests if the geometry field spatially contains the lookup geometry.
Example:
Zipcode.objects.filter(poly__contains=geom)
Backend  SQL Equivalent 

PostGIS  ST_Contains(poly, geom) 
Oracle  SDO_CONTAINS(poly, geom) 
MySQL  MBRContains(poly, geom) 
SpatiaLite  Contains(poly, geom) 
Availability: PostGIS
Returns true if the lookup geometry intersects the interior of the geometry field, but not the boundary (or exterior). [4]
Note
Requires PostGIS 1.4 and above.
Example:
Zipcode.objects.filter(poly__contains_properly=geom)
Backend  SQL Equivalent 

PostGIS  ST_ContainsProperly(poly, geom) 
Availability: PostGIS, Oracle
Tests if no point in the geometry field is outside the lookup geometry. [3]
Example:
Zipcode.objects.filter(poly__coveredby=geom)
Backend  SQL Equivalent 

PostGIS  ST_CoveredBy(poly, geom) 
Oracle  SDO_COVEREDBY(poly, geom) 
Availability: PostGIS, Oracle
Tests if no point in the lookup geometry is outside the geometry field. [3]
Example:
Zipcode.objects.filter(poly__covers=geom)
Backend  SQL Equivalent 

PostGIS  ST_Covers(poly, geom) 
Oracle  SDO_COVERS(poly, geom) 
Availability: PostGIS, SpatiaLite
Tests if the geometry field spatially crosses the lookup geometry.
Example:
Zipcode.objects.filter(poly__crosses=geom)
Backend  SQL Equivalent 

PostGIS  ST_Crosses(poly, geom) 
SpatiaLite  Crosses(poly, geom) 
Availability: PostGIS, Oracle, MySQL, SpatiaLite
Tests if the geometry field is spatially disjoint from the lookup geometry.
Example:
Zipcode.objects.filter(poly__disjoint=geom)
Backend  SQL Equivalent 

PostGIS  ST_Disjoint(poly, geom) 
Oracle  SDO_GEOM.RELATE(poly, 'DISJOINT', geom, 0.05) 
MySQL  MBRDisjoint(poly, geom) 
SpatiaLite  Disjoint(poly, geom) 
Availability: PostGIS, Oracle, MySQL, SpatiaLite
Availability: PostGIS, Oracle, MySQL, SpatiaLite
Availability: PostGIS, Oracle, MySQL, SpatiaLite
Tests if the geometry field spatially intersects the lookup geometry.
Example:
Zipcode.objects.filter(poly__intersects=geom)
Backend  SQL Equivalent 

PostGIS  ST_Intersects(poly, geom) 
Oracle  SDO_OVERLAPBDYINTERSECT(poly, geom) 
MySQL  MBRIntersects(poly, geom) 
SpatiaLite  Intersects(poly, geom) 
Availability: PostGIS, Oracle, MySQL, SpatiaLite
Availability: PostGIS, Oracle, SpatiaLite
Tests if the geometry field is spatially related to the lookup geometry by
the values given in the given pattern. This lookup requires a tuple parameter,
(geom, pattern)
; the form of pattern
will depend on the spatial backend:
On these spatial backends the intersection pattern is a string comprising
nine characters, which define intersections between the interior, boundary,
and exterior of the geometry field and the lookup geometry.
The intersection pattern matrix may only use the following characters:
1
, 2
, T
, F
, or *
. This lookup type allows users to “fine tune”
a specific geometric relationship consistent with the DE9IM model. [1]
Example:
# A tuple lookup parameter is used to specify the geometry and
# the intersection pattern (the pattern here is for 'contains').
Zipcode.objects.filter(poly__relate(geom, 'T*T***FF*'))
PostGIS SQL equivalent:
SELECT ... WHERE ST_Relate(poly, geom, 'T*T***FF*')
SpatiaLite SQL equivalent:
SELECT ... WHERE Relate(poly, geom, 'T*T***FF*')
Here the relation pattern is comprised at least one of the nine relation
strings: TOUCH
, OVERLAPBDYDISJOINT
, OVERLAPBDYINTERSECT
,
EQUAL
, INSIDE
, COVEREDBY
, CONTAINS
, COVERS
, ON
, and
ANYINTERACT
. Multiple strings may be combined with the logical Boolean
operator OR, for example, 'inside+touch'
. [2] The relation
strings are caseinsensitive.
Example:
Zipcode.objects.filter(poly__relate(geom, 'anyinteract'))
Oracle SQL equivalent:
SELECT ... WHERE SDO_RELATE(poly, geom, 'anyinteract')
Availability: PostGIS, Oracle, MySQL, SpatiaLite
Tests if the geometry field spatially touches the lookup geometry.
Example:
Zipcode.objects.filter(poly__touches=geom)
Backend  SQL Equivalent 

PostGIS  ST_Touches(poly, geom) 
MySQL  MBRTouches(poly, geom) 
Oracle  SDO_TOUCH(poly, geom) 
SpatiaLite  Touches(poly, geom) 
Availability: PostGIS, Oracle, MySQL, SpatiaLite
Tests if the geometry field is spatially within the lookup geometry.
Example:
Zipcode.objects.filter(poly__within=geom)
Backend  SQL Equivalent 

PostGIS  ST_Within(poly, geom) 
MySQL  MBRWithin(poly, geom) 
Oracle  SDO_INSIDE(poly, geom) 
SpatiaLite  Within(poly, geom) 
Availability: PostGIS
Tests if the geometry field’s bounding box is strictly to the left of the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__left=geom)
PostGIS equivalent:
SELECT ... WHERE poly << geom
Availability: PostGIS
Tests if the geometry field’s bounding box is strictly to the right of the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__right=geom)
PostGIS equivalent:
SELECT ... WHERE poly >> geom
Availability: PostGIS
Tests if the geometry field’s bounding box overlaps or is to the left of the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__overlaps_left=geom)
PostGIS equivalent:
SELECT ... WHERE poly &< geom
Availability: PostGIS
Tests if the geometry field’s bounding box overlaps or is to the right of the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__overlaps_right=geom)
PostGIS equivalent:
SELECT ... WHERE poly &> geom
Availability: PostGIS
Tests if the geometry field’s bounding box overlaps or is above the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__overlaps_above=geom)
PostGIS equivalent:
SELECT ... WHERE poly &> geom
Availability: PostGIS
Tests if the geometry field’s bounding box overlaps or is below the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__overlaps_below=geom)
PostGIS equivalent:
SELECT ... WHERE poly &< geom
Availability: PostGIS
Tests if the geometry field’s bounding box is strictly above the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__strictly_above=geom)
PostGIS equivalent:
SELECT ... WHERE poly >> geom
Availability: PostGIS
Tests if the geometry field’s bounding box is strictly below the lookup geometry’s bounding box.
Example:
Zipcode.objects.filter(poly__strictly_below=geom)
PostGIS equivalent:
SELECT ... WHERE poly << geom
Availability: PostGIS, Oracle, SpatiaLite
For an overview on performing distance queries, please refer to the distance queries introduction.
Distance lookups take the following form:
<field>__<distance lookup>=(<geometry>, <distance value>[, 'spheroid'])
The value passed into a distance lookup is a tuple; the first two
values are mandatory, and are the geometry to calculate distances to,
and a distance value (either a number in units of the field or a
Distance
object). On every
distance lookup but dwithin
, an optional
third element, 'spheroid'
, may be included to tell GeoDjango
to use the more accurate spheroid distance calculation functions on
fields with a geodetic coordinate system (e.g., ST_Distance_Spheroid
would be used instead of ST_Distance_Sphere
).
Returns models where the distance to the geometry field from the lookup geometry is greater than the given distance value.
Example:
Zipcode.objects.filter(poly__distance_gt=(geom, D(m=5)))
Backend  SQL Equivalent 

PostGIS  ST_Distance(poly, geom) > 5 
Oracle  SDO_GEOM.SDO_DISTANCE(poly, geom, 0.05) > 5 
SpatiaLite  Distance(poly, geom) > 5 
Returns models where the distance to the geometry field from the lookup geometry is greater than or equal to the given distance value.
Example:
Zipcode.objects.filter(poly__distance_gte=(geom, D(m=5)))
Backend  SQL Equivalent 

PostGIS  ST_Distance(poly, geom) >= 5 
Oracle  SDO_GEOM.SDO_DISTANCE(poly, geom, 0.05) >= 5 
SpatiaLite  Distance(poly, geom) >= 5 
Returns models where the distance to the geometry field from the lookup geometry is less than the given distance value.
Example:
Zipcode.objects.filter(poly__distance_lt=(geom, D(m=5)))
Backend  SQL Equivalent 

PostGIS  ST_Distance(poly, geom) < 5 
Oracle  SDO_GEOM.SDO_DISTANCE(poly, geom, 0.05) < 5 
SpatiaLite  Distance(poly, geom) < 5 
Returns models where the distance to the geometry field from the lookup geometry is less than or equal to the given distance value.
Example:
Zipcode.objects.filter(poly__distance_lte=(geom, D(m=5)))
Backend  SQL Equivalent 

PostGIS  ST_Distance(poly, geom) <= 5 
Oracle  SDO_GEOM.SDO_DISTANCE(poly, geom, 0.05) <= 5 
SpatiaLite  Distance(poly, geom) <= 5 
Returns models where the distance to the geometry field from the lookup geometry are within the given distance from one another.
Example:
Zipcode.objects.filter(poly__dwithin=(geom, D(m=5)))
Backend  SQL Equivalent 

PostGIS  ST_DWithin(poly, geom, 5) 
Oracle  SDO_WITHIN_DISTANCE(poly, geom, 5) 
Note
This lookup is not available on SpatiaLite.
GeoQuerySet
Methods¶GeoQuerySet
methods specify that a spatial operation be performed
on each patial operation on each geographic
field in the queryset and store its output in a new attribute on the model
(which is generally the name of the GeoQuerySet
method).
There are also aggregate GeoQuerySet
methods which return a single value
instead of a queryset. This section will describe the API and availability
of every GeoQuerySet
method available in GeoDjango.
Note
What methods are available depend on your spatial backend. See the compatibility table for more details.
With a few exceptions, the following keyword arguments may be used with all
GeoQuerySet
methods:
Keyword Argument  Description 

field_name 
By default, On PostGIS, the 
model_att 
By default, This keyword is required if
a method name clashes with an existing

Availability: PostGIS, Oracle, SpatiaLite
area
¶GeoQuerySet.
area
(**kwargs)¶Returns the area of the geographic field in an area
attribute on
each element of this GeoQuerySet.
distance
¶GeoQuerySet.
distance
(geom, **kwargs)¶This method takes a geometry as a parameter, and attaches a distance
attribute to every model in the returned queryset that contains the
distance (as a Distance
object) to the given geometry.
In the following example (taken from the GeoDjango distance tests),
the distance from the Tasmanian city of Hobart to every other
PointField
in the AustraliaCity
queryset is calculated:
>>> pnt = AustraliaCity.objects.get(name='Hobart').point
>>> for city in AustraliaCity.objects.distance(pnt): print(city.name, city.distance)
Wollongong 990071.220408 m
Shellharbour 972804.613941 m
Thirroul 1002334.36351 m
Mittagong 975691.632637 m
Batemans Bay 834342.185561 m
Canberra 598140.268959 m
Melbourne 575337.765042 m
Sydney 1056978.87363 m
Hobart 0.0 m
Adelaide 1162031.83522 m
Hillsdale 1049200.46122 m
Note
Because the distance
attribute is a
Distance
object, you can easily express
the value in the units of your choice. For example, city.distance.mi
is
the distance value in miles and city.distance.km
is the distance value
in kilometers. See the Measurement Objects for usage details and the list of
Supported units.
The following methods take no arguments, and attach geometry objects
each element of the GeoQuerySet
that is the result of relationship
function evaluated on the geometry field.
centroid
¶GeoQuerySet.
centroid
(**kwargs)¶Availability: PostGIS, Oracle, SpatiaLite
Returns the centroid
value for the geographic field in a centroid
attribute on each element of the GeoQuerySet
.
force_rhr
¶GeoQuerySet.
force_rhr
(**kwargs)¶Availability: PostGIS
Returns a modified version of the polygon/multipolygon in which all
of the vertices follow the RightHandRule, and attaches as a
force_rhr
attribute on each element of the queryset.
reverse_geom
¶GeoQuerySet.
reverse_geom
(**kwargs)¶Availability: PostGIS, Oracle
Reverse the coordinate order of the geometry field, and attaches as a
reverse
attribute on each element of the queryset.
snap_to_grid
¶GeoQuerySet.
snap_to_grid
(*args, **kwargs)¶Snap all points of the input geometry to the grid. How the geometry is snapped to the grid depends on how many numeric (either float, integer, or long) arguments are given.
Number of Arguments  Description 

1  A single size to snap bot the X and Y grids to. 
2  X and Y sizes to snap the grid to. 
4  X, Y sizes and the corresponding X, Y origins. 
transform
¶GeoQuerySet.
transform
(srid=4326, **kwargs)¶Availability: PostGIS, Oracle, SpatiaLite
The transform
method transforms the geometry field of a model to the spatial
reference system specified by the srid
parameter. If no srid
is given,
then 4326 (WGS84) is used by default.
Note
Unlike other GeoQuerySet
methods, transform
stores its output
“inplace”. In other words, no new attribute for the transformed
geometry is placed on the models.
Note
What spatial reference system an integer SRID corresponds to may depend on the spatial database used. In other words, the SRID numbers used for Oracle are not necessarily the same as those used by PostGIS.
Example:
>>> qs = Zipcode.objects.all().transform() # Transforms to WGS84
>>> qs = Zipcode.objects.all().transform(32140) # Transforming to "NAD83 / Texas South Central"
>>> print(qs[0].poly.srid)
32140
>>> print(qs[0].poly)
POLYGON ((234055.1698884720099159 4937796.9232223574072123 ...
Availability: PostGIS, Oracle, SpatiaLite
The following methods all take a geometry as a parameter and attach a geometry
to each element of the GeoQuerySet
that is the result of the operation.
difference
¶GeoQuerySet.
difference
(geom)¶Returns the spatial difference of the geographic field with the given
geometry in a difference
attribute on each element of the
GeoQuerySet
.
intersection
¶GeoQuerySet.
intersection
(geom)¶Returns the spatial intersection of the geographic field with the
given geometry in an intersection
attribute on each element of the
GeoQuerySet
.
The following GeoQuerySet
methods will return an attribute that has the value
of the geometry field in each model converted to the requested output format.
geohash
¶GeoQuerySet.
geohash
(precision=20, **kwargs)¶Attaches a geohash
attribute to every model the queryset
containing the GeoHash representation of the geometry.
geojson
¶GeoQuerySet.
geojson
(**kwargs)¶Availability: PostGIS, SpatiaLite
geojson
support for Spatialite > 3.0 has been added.
Attaches a geojson
attribute to every model in the queryset that contains the
GeoJSON representation of the geometry.
Keyword Argument  Description 

precision 
It may be used to specify the number of significant digits for the coordinates in the GeoJSON representation – the default value is 8. 
crs 
Set this to True if you want the coordinate
reference system to be included in the returned
GeoJSON. 
bbox 
Set this to True if you want the bounding box
to be included in the returned GeoJSON. 
gml
¶GeoQuerySet.
gml
(**kwargs)¶Availability: PostGIS, Oracle, SpatiaLite
Attaches a gml
attribute to every model in the queryset that contains the
Geographic Markup Language (GML) representation of the geometry.
Example:
>>> qs = Zipcode.objects.all().gml()
>>> print(qs[0].gml)
<gml:Polygon srsName="EPSG:4326"><gml:OuterBoundaryIs>147.78711,70.245363 ... 147.78711,70.245363</gml:OuterBoundaryIs></gml:Polygon>
Keyword Argument  Description 

precision 
This keyword is for PostGIS only. It may be used to specify the number of significant digits for the coordinates in the GML representation – the default value is 8. 
version 
This keyword is for PostGIS only. It may be used to specify the GML version used, and may only be values of 2 or 3. The default value is 2. 
kml
¶GeoQuerySet.
kml
(**kwargs)¶Availability: PostGIS, SpatiaLite
Attaches a kml
attribute to every model in the queryset that contains the
Keyhole Markup Language (KML) representation of the geometry fields. It
should be noted that the contents of the KML are transformed to WGS84 if
necessary.
Example:
>>> qs = Zipcode.objects.all().kml()
>>> print(qs[0].kml)
<Polygon><outerBoundaryIs><LinearRing><coordinates>103.04135,36.217596,0 ... 103.04135,36.217596,0</coordinates></LinearRing></outerBoundaryIs></Polygon>
Keyword Argument  Description 

precision 
This keyword may be used to specify the number of significant digits for the coordinates in the KML representation – the default value is 8. 
svg
¶GeoQuerySet.
svg
(**kwargs)¶Availability: PostGIS, SpatiaLite
Attaches a svg
attribute to every model in the queryset that contains
the Scalable Vector Graphics (SVG) path data of the geometry fields.
Keyword Argument  Description 

relative 
If set to True , the path data will be implemented
in terms of relative moves. Defaults to False ,
meaning that absolute moves are used instead. 
precision 
This keyword may be used to specify the number of significant digits for the coordinates in the SVG representation – the default value is 8. 
mem_size
¶GeoQuerySet.
mem_size
(**kwargs)¶Availability: PostGIS
Returns the memory size (number of bytes) that the geometry field takes
in a mem_size
attribute on each element of the GeoQuerySet
.
collect
¶GeoQuerySet.
collect
(**kwargs)¶Availability: PostGIS
Returns a GEOMETRYCOLLECTION
or a MULTI
geometry object from the geometry
column. This is analogous to a simplified version of the GeoQuerySet.unionagg()
method,
except it can be several orders of magnitude faster than performing a union because
it simply rolls up geometries into a collection or multi object, not caring about
dissolving boundaries.
extent
¶GeoQuerySet.
extent
(**kwargs)¶Availability: PostGIS, Oracle
Returns the extent of the GeoQuerySet
as a fourtuple, comprising the
lower left coordinate and the upper right coordinate.
Example:
>>> qs = City.objects.filter(name__in=('Houston', 'Dallas'))
>>> print(qs.extent())
(96.8016128540039, 29.7633724212646, 95.3631439208984, 32.782058715820)
extent3d
¶GeoQuerySet.
extent3d
(**kwargs)¶Availability: PostGIS
Returns the 3D extent of the GeoQuerySet
as a sixtuple, comprising
the lower left coordinate and upper right coordinate.
Example:
>>> qs = City.objects.filter(name__in=('Houston', 'Dallas'))
>>> print(qs.extent3d())
(96.8016128540039, 29.7633724212646, 0, 95.3631439208984, 32.782058715820, 0)
make_line
¶GeoQuerySet.
make_line
(**kwargs)¶Availability: PostGIS
Returns a LineString
constructed from the point field geometries in the
GeoQuerySet
. Currently, ordering the queryset has no effect.
Example:
>>> print(City.objects.filter(name__in=('Houston', 'Dallas')).make_line())
LINESTRING (95.3631510000000020 29.7633739999999989, 96.8016109999999941 32.7820570000000018)
unionagg
¶GeoQuerySet.
unionagg
(**kwargs)¶Availability: PostGIS, Oracle, SpatiaLite
This method returns a GEOSGeometry
object
comprising the union of every geometry in the queryset. Please note that
use of unionagg
is processor intensive and may take a significant amount
of time on large querysets.
Note
If the computation time for using this method is too expensive,
consider using GeoQuerySet.collect()
instead.
Example:
>>> u = Zipcode.objects.unionagg() # This may take a long time.
>>> u = Zipcode.objects.filter(poly__within=bbox).unionagg() # A more sensible approach.
Keyword Argument  Description 

tolerance 
This keyword is for Oracle only. It is for the
tolerance value used by the SDOAGGRTYPE
procedure; the Oracle documentation has more
details. 
Example:
>>> from django.contrib.gis.db.models import Extent, Union
>>> WorldBorder.objects.aggregate(Extent('mpoly'), Union('mpoly'))
Extent3D
¶Extent3D
(geo_field)¶Returns the same as the GeoQuerySet.extent3d()
aggregate method.
MakeLine
¶MakeLine
(geo_field)¶Returns the same as the GeoQuerySet.make_line()
aggregate method.
Union
¶Union
(geo_field)¶Returns the same as the GeoQuerySet.union()
aggregate method.
Footnotes
[1]  See OpenGIS Simple Feature Specification For SQL, at Ch. 2.1.13.2, p. 213 (The Dimensionally Extended NineIntersection Model). 
[2]  See SDO_RELATE documentation, from Ch. 11 of the Oracle Spatial User’s Guide and Manual. 
[3]  (1, 2) For an explanation of this routine, read Quirks of the “Contains” Spatial Predicate by Martin Davis (a PostGIS developer). 
[4]  Refer to the PostGIS ST_ContainsProperly documentation for more details. 
Oct 03, 2017