db-api.txt 20 KB

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  1. ======================
  2. GeoDjango Database API
  3. ======================
  4. .. _spatial-backends:
  5. Spatial Backends
  6. ================
  7. .. module:: django.contrib.gis.db.backends
  8. :synopsis: GeoDjango's spatial database backends.
  9. GeoDjango currently provides the following spatial database backends:
  10. * ``django.contrib.gis.db.backends.postgis``
  11. * ``django.contrib.gis.db.backends.mysql``
  12. * ``django.contrib.gis.db.backends.oracle``
  13. * ``django.contrib.gis.db.backends.spatialite``
  14. .. _mysql-spatial-limitations:
  15. MySQL Spatial Limitations
  16. -------------------------
  17. Django supports spatial functions operating on real geometries available in
  18. modern MySQL versions. However, the spatial functions are not as rich as other
  19. backends like PostGIS.
  20. Raster Support
  21. --------------
  22. ``RasterField`` is currently only implemented for the PostGIS backend. Spatial
  23. lookups are available for raster fields, but spatial database functions and
  24. aggregates aren't implemented for raster fields.
  25. Creating and Saving Models with Geometry Fields
  26. ===============================================
  27. Here is an example of how to create a geometry object (assuming the ``Zipcode``
  28. model)::
  29. >>> from zipcode.models import Zipcode
  30. >>> z = Zipcode(code=77096, poly='POLYGON(( 10 10, 10 20, 20 20, 20 15, 10 10))')
  31. >>> z.save()
  32. :class:`~django.contrib.gis.geos.GEOSGeometry` objects may also be used to save geometric models::
  33. >>> from django.contrib.gis.geos import GEOSGeometry
  34. >>> poly = GEOSGeometry('POLYGON(( 10 10, 10 20, 20 20, 20 15, 10 10))')
  35. >>> z = Zipcode(code=77096, poly=poly)
  36. >>> z.save()
  37. Moreover, if the ``GEOSGeometry`` is in a different coordinate system (has a
  38. different SRID value) than that of the field, then it will be implicitly
  39. transformed into the SRID of the model's field, using the spatial database's
  40. transform procedure::
  41. >>> poly_3084 = GEOSGeometry('POLYGON(( 10 10, 10 20, 20 20, 20 15, 10 10))', srid=3084) # SRID 3084 is 'NAD83(HARN) / Texas Centric Lambert Conformal'
  42. >>> z = Zipcode(code=78212, poly=poly_3084)
  43. >>> z.save()
  44. >>> from django.db import connection
  45. >>> print(connection.queries[-1]['sql']) # printing the last SQL statement executed (requires DEBUG=True)
  46. INSERT INTO "geoapp_zipcode" ("code", "poly") VALUES (78212, ST_Transform(ST_GeomFromWKB('\\001 ... ', 3084), 4326))
  47. Thus, geometry parameters may be passed in using the ``GEOSGeometry`` object, WKT
  48. (Well Known Text [#fnwkt]_), HEXEWKB (PostGIS specific -- a WKB geometry in
  49. hexadecimal [#fnewkb]_), and GeoJSON (see :rfc:`7946`). Essentially, if the
  50. input is not a ``GEOSGeometry`` object, the geometry field will attempt to
  51. create a ``GEOSGeometry`` instance from the input.
  52. For more information creating :class:`~django.contrib.gis.geos.GEOSGeometry`
  53. objects, refer to the :ref:`GEOS tutorial <geos-tutorial>`.
  54. .. _creating-and-saving-raster-models:
  55. Creating and Saving Models with Raster Fields
  56. =============================================
  57. When creating raster models, the raster field will implicitly convert the input
  58. into a :class:`~django.contrib.gis.gdal.GDALRaster` using lazy-evaluation.
  59. The raster field will therefore accept any input that is accepted by the
  60. :class:`~django.contrib.gis.gdal.GDALRaster` constructor.
  61. Here is an example of how to create a raster object from a raster file
  62. ``volcano.tif`` (assuming the ``Elevation`` model)::
  63. >>> from elevation.models import Elevation
  64. >>> dem = Elevation(name='Volcano', rast='/path/to/raster/volcano.tif')
  65. >>> dem.save()
  66. :class:`~django.contrib.gis.gdal.GDALRaster` objects may also be used to save
  67. raster models::
  68. >>> from django.contrib.gis.gdal import GDALRaster
  69. >>> rast = GDALRaster({'width': 10, 'height': 10, 'name': 'Canyon', 'srid': 4326,
  70. ... 'scale': [0.1, -0.1], 'bands': [{"data": range(100)}]})
  71. >>> dem = Elevation(name='Canyon', rast=rast)
  72. >>> dem.save()
  73. Note that this equivalent to::
  74. >>> dem = Elevation.objects.create(
  75. ... name='Canyon',
  76. ... rast={'width': 10, 'height': 10, 'name': 'Canyon', 'srid': 4326,
  77. ... 'scale': [0.1, -0.1], 'bands': [{"data": range(100)}]},
  78. ... )
  79. .. _spatial-lookups-intro:
  80. Spatial Lookups
  81. ===============
  82. GeoDjango's lookup types may be used with any manager method like
  83. ``filter()``, ``exclude()``, etc. However, the lookup types unique to
  84. GeoDjango are only available on spatial fields.
  85. Filters on 'normal' fields (e.g. :class:`~django.db.models.CharField`)
  86. may be chained with those on geographic fields. Geographic lookups accept
  87. geometry and raster input on both sides and input types can be mixed freely.
  88. The general structure of geographic lookups is described below. A complete
  89. reference can be found in the :ref:`spatial lookup reference<spatial-lookups>`.
  90. Geometry Lookups
  91. ----------------
  92. Geographic queries with geometries take the following general form (assuming
  93. the ``Zipcode`` model used in the :doc:`model-api`)::
  94. >>> qs = Zipcode.objects.filter(<field>__<lookup_type>=<parameter>)
  95. >>> qs = Zipcode.objects.exclude(...)
  96. For example::
  97. >>> qs = Zipcode.objects.filter(poly__contains=pnt)
  98. >>> qs = Elevation.objects.filter(poly__contains=rst)
  99. In this case, ``poly`` is the geographic field, :lookup:`contains <gis-contains>`
  100. is the spatial lookup type, ``pnt`` is the parameter (which may be a
  101. :class:`~django.contrib.gis.geos.GEOSGeometry` object or a string of
  102. GeoJSON , WKT, or HEXEWKB), and ``rst`` is a
  103. :class:`~django.contrib.gis.gdal.GDALRaster` object.
  104. .. _spatial-lookup-raster:
  105. Raster Lookups
  106. --------------
  107. The raster lookup syntax is similar to the syntax for geometries. The only
  108. difference is that a band index can be specified as additional input. If no band
  109. index is specified, the first band is used by default (index ``0``). In that
  110. case the syntax is identical to the syntax for geometry lookups.
  111. To specify the band index, an additional parameter can be specified on both
  112. sides of the lookup. On the left hand side, the double underscore syntax is
  113. used to pass a band index. On the right hand side, a tuple of the raster and
  114. band index can be specified.
  115. This results in the following general form for lookups involving rasters
  116. (assuming the ``Elevation`` model used in the :doc:`model-api`)::
  117. >>> qs = Elevation.objects.filter(<field>__<lookup_type>=<parameter>)
  118. >>> qs = Elevation.objects.filter(<field>__<band_index>__<lookup_type>=<parameter>)
  119. >>> qs = Elevation.objects.filter(<field>__<lookup_type>=(<raster_input, <band_index>)
  120. For example::
  121. >>> qs = Elevation.objects.filter(rast__contains=geom)
  122. >>> qs = Elevation.objects.filter(rast__contains=rst)
  123. >>> qs = Elevation.objects.filter(rast__1__contains=geom)
  124. >>> qs = Elevation.objects.filter(rast__contains=(rst, 1))
  125. >>> qs = Elevation.objects.filter(rast__1__contains=(rst, 1))
  126. On the left hand side of the example, ``rast`` is the geographic raster field
  127. and :lookup:`contains <gis-contains>` is the spatial lookup type. On the right
  128. hand side, ``geom`` is a geometry input and ``rst`` is a
  129. :class:`~django.contrib.gis.gdal.GDALRaster` object. The band index defaults to
  130. ``0`` in the first two queries and is set to ``1`` on the others.
  131. While all spatial lookups can be used with raster objects on both sides, not all
  132. underlying operators natively accept raster input. For cases where the operator
  133. expects geometry input, the raster is automatically converted to a geometry.
  134. It's important to keep this in mind when interpreting the lookup results.
  135. The type of raster support is listed for all lookups in the :ref:`compatibility
  136. table <spatial-lookup-compatibility>`. Lookups involving rasters are currently
  137. only available for the PostGIS backend.
  138. .. _distance-queries:
  139. Distance Queries
  140. ================
  141. Introduction
  142. ------------
  143. Distance calculations with spatial data is tricky because, unfortunately,
  144. the Earth is not flat. Some distance queries with fields in a geographic
  145. coordinate system may have to be expressed differently because of
  146. limitations in PostGIS. Please see the :ref:`selecting-an-srid` section
  147. in the :doc:`model-api` documentation for more details.
  148. .. _distance-lookups-intro:
  149. Distance Lookups
  150. ----------------
  151. *Availability*: PostGIS, MariaDB, MySQL, Oracle, SpatiaLite, PGRaster (Native)
  152. The following distance lookups are available:
  153. * :lookup:`distance_lt`
  154. * :lookup:`distance_lte`
  155. * :lookup:`distance_gt`
  156. * :lookup:`distance_gte`
  157. * :lookup:`dwithin` (except MariaDB and MySQL)
  158. .. note::
  159. For *measuring*, rather than querying on distances, use the
  160. :class:`~django.contrib.gis.db.models.functions.Distance` function.
  161. Distance lookups take a tuple parameter comprising:
  162. #. A geometry or raster to base calculations from; and
  163. #. A number or :class:`~django.contrib.gis.measure.Distance` object containing the distance.
  164. If a :class:`~django.contrib.gis.measure.Distance` object is used,
  165. it may be expressed in any units (the SQL generated will use units
  166. converted to those of the field); otherwise, numeric parameters are assumed
  167. to be in the units of the field.
  168. .. note::
  169. In PostGIS, ``ST_Distance_Sphere`` does *not* limit the geometry types
  170. geographic distance queries are performed with. [#fndistsphere15]_ However,
  171. these queries may take a long time, as great-circle distances must be
  172. calculated on the fly for *every* row in the query. This is because the
  173. spatial index on traditional geometry fields cannot be used.
  174. For much better performance on WGS84 distance queries, consider using
  175. :ref:`geography columns <geography-type>` in your database instead because
  176. they are able to use their spatial index in distance queries.
  177. You can tell GeoDjango to use a geography column by setting ``geography=True``
  178. in your field definition.
  179. For example, let's say we have a ``SouthTexasCity`` model (from the
  180. :source:`GeoDjango distance tests <tests/gis_tests/distapp/models.py>` ) on a
  181. *projected* coordinate system valid for cities in southern Texas::
  182. from django.contrib.gis.db import models
  183. class SouthTexasCity(models.Model):
  184. name = models.CharField(max_length=30)
  185. # A projected coordinate system (only valid for South Texas!)
  186. # is used, units are in meters.
  187. point = models.PointField(srid=32140)
  188. Then distance queries may be performed as follows::
  189. >>> from django.contrib.gis.geos import GEOSGeometry
  190. >>> from django.contrib.gis.measure import D # ``D`` is a shortcut for ``Distance``
  191. >>> from geoapp.models import SouthTexasCity
  192. # Distances will be calculated from this point, which does not have to be projected.
  193. >>> pnt = GEOSGeometry('POINT(-96.876369 29.905320)', srid=4326)
  194. # If numeric parameter, units of field (meters in this case) are assumed.
  195. >>> qs = SouthTexasCity.objects.filter(point__distance_lte=(pnt, 7000))
  196. # Find all Cities within 7 km, > 20 miles away, and > 100 chains away (an obscure unit)
  197. >>> qs = SouthTexasCity.objects.filter(point__distance_lte=(pnt, D(km=7)))
  198. >>> qs = SouthTexasCity.objects.filter(point__distance_gte=(pnt, D(mi=20)))
  199. >>> qs = SouthTexasCity.objects.filter(point__distance_gte=(pnt, D(chain=100)))
  200. Raster queries work the same way by replacing the geometry field ``point`` with
  201. a raster field, or the ``pnt`` object with a raster object, or both. To specify
  202. the band index of a raster input on the right hand side, a 3-tuple can be
  203. passed to the lookup as follows::
  204. >>> qs = SouthTexasCity.objects.filter(point__distance_gte=(rst, 2, D(km=7)))
  205. Where the band with index 2 (the third band) of the raster ``rst`` would be
  206. used for the lookup.
  207. .. _compatibility-table:
  208. Compatibility Tables
  209. ====================
  210. .. _spatial-lookup-compatibility:
  211. Spatial Lookups
  212. ---------------
  213. The following table provides a summary of what spatial lookups are available
  214. for each spatial database backend. The PostGIS Raster (PGRaster) lookups are
  215. divided into the three categories described in the :ref:`raster lookup details
  216. <spatial-lookup-raster>`: native support ``N``, bilateral native support ``B``,
  217. and geometry conversion support ``C``.
  218. ================================= ========= ======== ========= ============ ========== ========
  219. Lookup Type PostGIS Oracle MariaDB MySQL [#]_ SpatiaLite PGRaster
  220. ================================= ========= ======== ========= ============ ========== ========
  221. :lookup:`bbcontains` X X X X N
  222. :lookup:`bboverlaps` X X X X N
  223. :lookup:`contained` X X X X N
  224. :lookup:`contains <gis-contains>` X X X X X B
  225. :lookup:`contains_properly` X B
  226. :lookup:`coveredby` X X X B
  227. :lookup:`covers` X X X B
  228. :lookup:`crosses` X X X X C
  229. :lookup:`disjoint` X X X X X B
  230. :lookup:`distance_gt` X X X X X N
  231. :lookup:`distance_gte` X X X X X N
  232. :lookup:`distance_lt` X X X X X N
  233. :lookup:`distance_lte` X X X X X N
  234. :lookup:`dwithin` X X X B
  235. :lookup:`equals` X X X X X C
  236. :lookup:`exact <same_as>` X X X X X B
  237. :lookup:`intersects` X X X X X B
  238. :lookup:`isempty` X
  239. :lookup:`isvalid` X X X X
  240. :lookup:`overlaps` X X X X X B
  241. :lookup:`relate` X X X X C
  242. :lookup:`same_as` X X X X X B
  243. :lookup:`touches` X X X X X B
  244. :lookup:`within` X X X X X B
  245. :lookup:`left` X C
  246. :lookup:`right` X C
  247. :lookup:`overlaps_left` X B
  248. :lookup:`overlaps_right` X B
  249. :lookup:`overlaps_above` X C
  250. :lookup:`overlaps_below` X C
  251. :lookup:`strictly_above` X C
  252. :lookup:`strictly_below` X C
  253. ================================= ========= ======== ========= ============ ========== ========
  254. .. _database-functions-compatibility:
  255. Database functions
  256. ------------------
  257. The following table provides a summary of what geography-specific database
  258. functions are available on each spatial backend.
  259. .. currentmodule:: django.contrib.gis.db.models.functions
  260. ==================================== ======= ============== ============ =========== =================
  261. Function PostGIS Oracle MariaDB MySQL SpatiaLite
  262. ==================================== ======= ============== ============ =========== =================
  263. :class:`Area` X X X X X
  264. :class:`AsGeoJSON` X X X X X
  265. :class:`AsGML` X X X
  266. :class:`AsKML` X X
  267. :class:`AsSVG` X X
  268. :class:`AsWKB` X X X X X
  269. :class:`AsWKT` X X X X X
  270. :class:`Azimuth` X X (LWGEOM/RTTOPO)
  271. :class:`BoundingCircle` X X
  272. :class:`Centroid` X X X X X
  273. :class:`Difference` X X X X X
  274. :class:`Distance` X X X X X
  275. :class:`Envelope` X X X X X
  276. :class:`ForcePolygonCW` X X
  277. :class:`GeoHash` X X X (LWGEOM/RTTOPO)
  278. :class:`Intersection` X X X X X
  279. :class:`IsEmpty` X
  280. :class:`IsValid` X X X X
  281. :class:`Length` X X X X X
  282. :class:`LineLocatePoint` X X
  283. :class:`MakeValid` X X (LWGEOM/RTTOPO)
  284. :class:`MemSize` X
  285. :class:`NumGeometries` X X X X X
  286. :class:`NumPoints` X X X X X
  287. :class:`Perimeter` X X X
  288. :class:`PointOnSurface` X X X X
  289. :class:`Reverse` X X X
  290. :class:`Scale` X X
  291. :class:`SnapToGrid` X X
  292. :class:`SymDifference` X X X X X
  293. :class:`Transform` X X X
  294. :class:`Translate` X X
  295. :class:`Union` X X X X X
  296. ==================================== ======= ============== ============ =========== =================
  297. Aggregate Functions
  298. -------------------
  299. The following table provides a summary of what GIS-specific aggregate functions
  300. are available on each spatial backend. Please note that MySQL does not
  301. support any of these aggregates, and is thus excluded from the table.
  302. .. currentmodule:: django.contrib.gis.db.models
  303. ======================= ======= ====== ==========
  304. Aggregate PostGIS Oracle SpatiaLite
  305. ======================= ======= ====== ==========
  306. :class:`Collect` X X
  307. :class:`Extent` X X X
  308. :class:`Extent3D` X
  309. :class:`MakeLine` X X
  310. :class:`Union` X X X
  311. ======================= ======= ====== ==========
  312. .. rubric:: Footnotes
  313. .. [#fnwkt] *See* Open Geospatial Consortium, Inc., `OpenGIS Simple Feature Specification For SQL <https://portal.ogc.org/files/?artifact_id=829>`_, Document 99-049 (May 5, 1999), at Ch. 3.2.5, p. 3-11 (SQL Textual Representation of Geometry).
  314. .. [#fnewkb] *See* `PostGIS EWKB, EWKT and Canonical Forms <https://postgis.net/docs/using_postgis_dbmanagement.html#EWKB_EWKT>`_, PostGIS documentation at Ch. 4.1.2.
  315. .. [#fndistsphere15] *See* `PostGIS documentation <https://postgis.net/docs/ST_DistanceSphere.html>`_ on ``ST_DistanceSphere``.
  316. .. [#] Refer :ref:`mysql-spatial-limitations` section for more details.