GeoQuerySet
(model=None)¶The spatial lookups in this section are available for GeometryField
and RasterField
.
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.
Spatial lookups now support raster input.
All examples in the reference below are given for geometry fields and inputs, but the lookups can be used the same way with rasters on both sides. Whenever a lookup doesn’t support raster input, the input is automatically converted to a geometry where necessary using the ST_Polygon function. See also the introduction to raster lookups.
The database operators used by the lookups can be divided into three categories:
N
: the operator accepts rasters natively on both
sides of the lookup, and raster input can be mixed with geometry inputs.B
: the operator supports rasters only if both
sides of the lookup receive raster inputs. Raster data is automatically
converted to geometries for mixed lookups.C
. The lookup does not have native raster
support, all raster data is automatically converted to geometries.The examples below show the SQL equivalent for the lookups in the different types of raster support. The same pattern applies to all spatial lookups.
Case  Lookup  SQL Equivalent 

N, B  rast__contains=rst 
ST_Contains(rast, rst) 
N, B  rast__1__contains=(rst, 2) 
ST_Contains(rast, 1, rst, 2) 
B, C  rast__contains=geom 
ST_Contains(ST_Polygon(rast), geom) 
B, C  rast__1__contains=geom 
ST_Contains(ST_Polygon(rast, 1), geom) 
B, C  poly__contains=rst 
ST_Contains(poly, ST_Polygon(rst)) 
B, C  poly__contains=(rst, 1) 
ST_Contains(poly, ST_Polygon(rst, 1)) 
C  rast__crosses=rst 
ST_Crosses(ST_Polygon(rast), ST_Polygon(rst)) 
C  rast__1__crosses=(rst, 2) 
ST_Crosses(ST_Polygon(rast, 1), ST_Polygon(rst, 2)) 
C  rast__crosses=geom 
ST_Crosses(ST_Polygon(rast), geom) 
C  poly__crosses=rst 
ST_Crosses(poly, ST_Polygon(rst)) 
Spatial lookups with rasters are only supported for PostGIS backends (denominated as PGRaster in this section).
bbcontains
¶Availability: PostGIS, MySQL, SpatiaLite, PGRaster (Native)
Tests if the geometry or raster 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) 
bboverlaps
¶Availability: PostGIS, MySQL, SpatiaLite, PGRaster (Native)
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) 
contained
¶Availability: PostGIS, MySQL, SpatiaLite, PGRaster (Native)
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) 
contains
¶Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Bilateral)
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) 
contains_properly
¶Availability: PostGIS, PGRaster (Bilateral)
Returns true if the lookup geometry intersects the interior of the geometry field, but not the boundary (or exterior). [4]
Example:
Zipcode.objects.filter(poly__contains_properly=geom)
Backend  SQL Equivalent 

PostGIS  ST_ContainsProperly(poly, geom) 
coveredby
¶Availability: PostGIS, Oracle, PGRaster (Bilateral)
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) 
covers
¶Availability: PostGIS, Oracle, PGRaster (Bilateral)
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) 
crosses
¶Availability: PostGIS, SpatiaLite, PGRaster (Conversion)
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) 
disjoint
¶Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Bilateral)
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) 
equals
¶Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Conversion)
exact
, same_as
¶Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Bilateral)
intersects
¶Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Bilateral)
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) 
isvalid
¶Availability: PostGIS
Tests if the geometry is valid.
Example:
Zipcode.objects.filter(poly__isvalid=True)
PostGIS equivalent:
SELECT ... WHERE ST_IsValid(poly)
overlaps
¶Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Bilateral)
relate
¶Availability: PostGIS, Oracle, SpatiaLite, PGRaster (Conversion)
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]
Geometry 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*')
Raster example:
Zipcode.objects.filter(poly__relate=(rast, 1, 'T*T***FF*'))
Zipcode.objects.filter(rast__2__relate=(rast, 1, 'T*T***FF*'))
PostGIS SQL equivalent:
SELECT ... WHERE ST_Relate(poly, ST_Polygon(rast, 1), 'T*T***FF*')
SELECT ... WHERE ST_Relate(ST_Polygon(rast, 2), ST_Polygon(rast, 1), 'T*T***FF*')
Here the relation pattern is comprised of 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')
touches
¶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) 
within
¶Availability: PostGIS, Oracle, MySQL, SpatiaLite, PGRaster (Bilateral)
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) 
left
¶Availability: PostGIS, PGRaster (Conversion)
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
right
¶Availability: PostGIS, PGRaster (Conversion)
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
overlaps_left
¶Availability: PostGIS, PGRaster (Bilateral)
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
overlaps_right
¶Availability: PostGIS, PGRaster (Bilateral)
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
overlaps_above
¶Availability: PostGIS, PGRaster (Conversion)
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
overlaps_below
¶Availability: PostGIS, PGRaster (Conversion)
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
strictly_above
¶Availability: PostGIS, PGRaster (Conversion)
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
strictly_below
¶Availability: PostGIS, PGRaster (Conversion)
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, PGRaster (Native)
For an overview on performing distance queries, please refer to the distance queries introduction.
Distance lookups take the following form:
<field>__<distance lookup>=(<geometry/raster>, <distance value>[, 'spheroid'])
<field>__<distance lookup>=(<raster>, <band_index>, <distance value>[, 'spheroid'])
<field>__<band_index>__<distance lookup>=(<raster>, <band_index>, <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, a
Distance
object, or a query expression
<ref/models/expressions>). To pass a band index to the lookup, use a 3tuple
where the second entry is the band index.
With PostGIS, on every distance lookup but dwithin
, an optional
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
). The simpler ST_Distance
function is used with
projected coordinate systems. Rasters are converted to geometries for spheroid
based lookups.
The ability to pass an expression as the distance value was added.
distance_gt
¶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/ST_Distance_Sphere(poly, geom) > 5 
Oracle  SDO_GEOM.SDO_DISTANCE(poly, geom, 0.05) > 5 
SpatiaLite  Distance(poly, geom) > 5 
distance_gte
¶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/ST_Distance_Sphere(poly, geom) >= 5 
Oracle  SDO_GEOM.SDO_DISTANCE(poly, geom, 0.05) >= 5 
SpatiaLite  Distance(poly, geom) >= 5 
distance_lt
¶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/ST_Distance_Sphere(poly, geom) < 5 
Oracle  SDO_GEOM.SDO_DISTANCE(poly, geom, 0.05) < 5 
SpatiaLite  Distance(poly, geom) < 5 
distance_lte
¶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/ST_Distance_Sphere(poly, geom) <= 5 
Oracle  SDO_GEOM.SDO_DISTANCE(poly, geom, 0.05) <= 5 
SpatiaLite  Distance(poly, geom) <= 5 
dwithin
¶Returns models where the distance to the geometry field from the lookup
geometry are within the given distance from one another. Note that you can only
provide Distance
objects if the targeted
geometries are in a projected system. For geographic geometries, you should use
units of the geometry field (e.g. degrees for WGS84
) .
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) 
注解
This lookup is not available on SpatiaLite.
GeoQuerySet
Methods¶1.9 版后已移除: Using GeoQuerySet
methods is now deprecated in favor of the new
Geographic Database Functions. Albeit a little more verbose, they are much more powerful
in how it is possible to combine them to build more complex queries.
GeoQuerySet
methods specify that a spatial operation be performed
on each spatial 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.
注解
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)¶1.9 版后已移除: Use the Area
function
instead.
Returns the area of the geographic field in an area
attribute on
each element of this GeoQuerySet.
distance
¶GeoQuerySet.
distance
(geom, **kwargs)¶1.9 版后已移除: Use the Distance
function
instead.
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
注解
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 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)¶1.9 版后已移除: Use the Centroid
function
instead.
Availability: PostGIS, Oracle, SpatiaLite
Returns the centroid
value for the geographic field in a centroid
attribute on each element of the GeoQuerySet
.
envelope
¶GeoQuerySet.
envelope
(**kwargs)¶1.9 版后已移除: Use the Envelope
function
instead.
Availability: PostGIS, SpatiaLite
Returns a geometry representing the bounding box of the geometry field in
an envelope
attribute on each element of the GeoQuerySet
.
point_on_surface
¶GeoQuerySet.
point_on_surface
(**kwargs)¶1.9 版后已移除: Use the PointOnSurface
function instead.
Availability: PostGIS, Oracle, SpatiaLite
Returns a Point geometry guaranteed to lie on the surface of the
geometry field in a point_on_surface
attribute on each element
of the queryset; otherwise sets with None.
force_rhr
¶GeoQuerySet.
force_rhr
(**kwargs)¶1.9 版后已移除: Use the ForceRHR
function
instead.
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)¶1.9 版后已移除: Use the Reverse
function
instead.
Availability: PostGIS, Oracle
Reverse the coordinate order of the geometry field, and attaches as a
reverse
attribute on each element of the queryset.
scale
¶GeoQuerySet.
scale
(x, y, z=0.0, **kwargs)¶1.9 版后已移除: Use the Scale
function
instead.
Availability: PostGIS, SpatiaLite
snap_to_grid
¶GeoQuerySet.
snap_to_grid
(*args, **kwargs)¶1.9 版后已移除: Use the SnapToGrid
function
instead.
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)¶1.9 版后已移除: Use the Transform
function
instead.
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.
注解
Unlike other GeoQuerySet
methods, transform
stores its output
“inplace”. In other words, no new attribute for the transformed
geometry is placed on the models.
注解
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)¶1.9 版后已移除: Use the Difference
function
instead.
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)¶1.9 版后已移除: Use the Intersection
function instead.
Returns the spatial intersection of the geographic field with the
given geometry in an intersection
attribute on each element of the
GeoQuerySet
.
sym_difference
¶GeoQuerySet.
sym_difference
(geom)¶1.9 版后已移除: Use the SymDifference
function instead.
Returns the symmetric difference of the geographic field with the
given geometry in a sym_difference
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)¶1.9 版后已移除: Use the GeoHash
function
instead.
Attaches a geohash
attribute to every model the queryset
containing the GeoHash representation of the geometry.
geojson
¶GeoQuerySet.
geojson
(**kwargs)¶1.9 版后已移除: Use the AsGeoJSON
function
instead.
Availability: PostGIS, SpatiaLite
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)¶1.9 版后已移除: Use the AsGML
function
instead.
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)¶1.9 版后已移除: Use the AsKML
function
instead.
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)¶1.9 版后已移除: Use the AsSVG
function
instead.
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)¶1.9 版后已移除: Use the MemSize
function
instead.
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
.
num_geom
¶GeoQuerySet.
num_geom
(**kwargs)¶1.9 版后已移除: Use the NumGeometries
function instead.
Availability: PostGIS, Oracle, SpatiaLite
Returns the number of geometries in a num_geom
attribute on
each element of the GeoQuerySet
if the geometry field is a
collection (e.g., a GEOMETRYCOLLECTION
or MULTI*
field);
otherwise sets with None
.
Django provides some GISspecific aggregate functions. For details on how to use these aggregate functions, see the topic guide on aggregation.
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'))
Collect
¶Collect
(geo_field)¶Availability: PostGIS, SpatiaLite
Returns a GEOMETRYCOLLECTION
or a MULTI
geometry object from the geometry
column. This is analogous to a simplified version of the Union
aggregate, 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
¶Extent
(geo_field)¶Availability: PostGIS, Oracle, SpatiaLite
Returns the extent of all geo_field
in the QuerySet
as a fourtuple,
comprising the lower left coordinate and the upper right coordinate.
Example:
>>> qs = City.objects.filter(name__in=('Houston', 'Dallas')).aggregate(Extent('poly'))
>>> print(qs['poly__extent'])
(96.8016128540039, 29.7633724212646, 95.3631439208984, 32.782058715820)
Extent3D
¶Extent3D
(geo_field)¶Availability: PostGIS
Returns the 3D extent of all geo_field
in the QuerySet
as a sixtuple,
comprising the lower left coordinate and upper right coordinate (each with x, y,
and z coordinates).
Example:
>>> qs = City.objects.filter(name__in=('Houston', 'Dallas')).aggregate(Extent3D('poly'))
>>> print(qs['poly__extent3d'])
(96.8016128540039, 29.7633724212646, 0, 95.3631439208984, 32.782058715820, 0)
MakeLine
¶MakeLine
(geo_field)¶Availability: PostGIS, SpatiaLite
Returns a LineString
constructed from the point field geometries in the
QuerySet
. Currently, ordering the queryset has no effect.
SpatiaLite support was added.
Example:
>>> qs = City.objects.filter(name__in=('Houston', 'Dallas')).aggregate(MakeLine('poly'))
>>> print(qs['poly__makeline'])
LINESTRING (95.3631510000000020 29.7633739999999989, 96.8016109999999941 32.7820570000000018)
Union
¶Union
(geo_field)¶Availability: PostGIS, Oracle, SpatiaLite
This method returns a GEOSGeometry
object
comprising the union of every geometry in the queryset. Please note that use of
Union
is processor intensive and may take a significant amount of time on
large querysets.
注解
If the computation time for using this method is too expensive, consider
using Collect
instead.
Example:
>>> u = Zipcode.objects.aggregate(Union(poly)) # This may take a long time.
>>> u = Zipcode.objects.filter(poly__within=bbox).aggregate(Union(poly)) # A more sensible approach.
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. 
10月 29, 2021