GeoDjango Database API¶

MySQL Spatial Limitations¶

MySQL’s spatial extensions only support bounding box operations (what MySQL calls minimum bounding rectangles, or MBR). Specifically, MySQL does not conform to the OGC standard:

Currently, MySQL does not implement these functions [Contains, Crosses, Disjoint, Intersects, Overlaps, Touches, Within] according to the specification. Those that are implemented return the same result as the corresponding MBR-based functions.

In other words, while spatial lookups such as contains are available in GeoDjango when using MySQL, the results returned are really equivalent to what would be returned when using bbcontains on a different spatial backend.

Introduction¶

Distance calculations with spatial data is tricky because, unfortunately, the Earth is not flat. Some distance queries with fields in a geographic coordinate system may have to be expressed differently because of limitations in PostGIS. Please see the Selecting an SRID section in the GeoDjango Model API documentation for more details.

Distance Lookups¶

Availability: PostGIS, Oracle, SpatiaLite

The following distance lookups are available:

• distance_lt
• distance_lte
• distance_gt
• distance_gte
• dwithin

Distance lookups take a tuple parameter comprising:

1. A geometry to base calculations from; and
2. A number or Distance object containing the distance.

If a Distance object is used, it may be expressed in any units (the SQL generated will use units converted to those of the field); otherwise, numeric parameters are assumed to be in the units of the field.

For example, let’s say we have a SouthTexasCity model (from the GeoDjango distance tests ) on a projected coordinate system valid for cities in southern Texas:

from django.contrib.gis.db import models

class SouthTexasCity(models.Model):
    name = models.CharField(max_length=30)
    # A projected coordinate system (only valid for South Texas!)
    # is used, units are in meters.
    point = models.PointField(srid=32140)
    objects = models.GeoManager()

Then distance queries may be performed as follows:

>>> from django.contrib.gis.geos import *
>>> from django.contrib.gis.measure import D # ``D`` is a shortcut for ``Distance``
>>> from geoapp import SouthTexasCity
# Distances will be calculated from this point, which does not have to be projected.
>>> pnt = fromstr('POINT(-96.876369 29.905320)', srid=4326)
# If numeric parameter, units of field (meters in this case) are assumed.
>>> qs = SouthTexasCity.objects.filter(point__distance_lte=(pnt, 7000))
# Find all Cities within 7 km, > 20 miles away, and > 100 chains  away (an obscure unit)
>>> qs = SouthTexasCity.objects.filter(point__distance_lte=(pnt, D(km=7)))
>>> qs = SouthTexasCity.objects.filter(point__distance_gte=(pnt, D(mi=20)))
>>> qs = SouthTexasCity.objects.filter(point__distance_gte=(pnt, D(chain=100)))

Spatial Lookups¶

The following table provides a summary of what spatial lookups are available for each spatial database backend.

GeoQuerySet Methods¶

The following table provides a summary of what GeoQuerySet methods are available on each spatial backend. Please note that MySQL does not support any of these methods, and is thus excluded from the table.

Footnotes