{"title":"GeoDjango handledning","version":"6.0","locale":"sv","docname":"ref/contrib/gis/tutorial","url":"/sv/6.0/ref/contrib/gis/tutorial/","canonical":"https://djangodocs.dev/sv/6.0/ref/contrib/gis/tutorial/","summary":"GeoDjango är en medföljande Contrib-modul för Django som förvandlar den till ett geografiskt webbramverk i världsklass.","html":"

GeoDjango handledningLink to this heading#

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IntroduktionLink to this heading#

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GeoDjango är en medföljande Contrib-modul för Django som förvandlar den till ett geografiskt webbramverk i världsklass. GeoDjango strävar efter att göra det så enkelt som möjligt att skapa geografiska webbapplikationer, t.ex. platsbaserade tjänster. Dess funktioner inkluderar:

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Denna handledning förutsätter att du känner till Django; om du är helt ny på Django, läs därför igenom vanlig handledning för att bekanta dig med Django först.

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Denna handledning kommer att vägleda dig genom skapandet av en geografisk webbapplikation för visning av världsgränserna. [1] En del av koden som används i denna handledning är hämtad från och/eller inspirerad av projektet GeoDjango basic apps. [2]

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UppsättningLink to this heading#

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Skapa en rumslig databasLink to this heading#

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Vanligtvis krävs ingen speciell installation, så du kan skapa en databas som du skulle göra för vilket annat projekt som helst. Vi ger några tips för utvalda databaser:

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Skapa ett nytt projektLink to this heading#

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Använd standardskriptet django-admin för att skapa ett projekt som heter geodjango:

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Linux / macOS

Shell
$ django-admin startproject geodjango\n
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Windows

Windows
...\\> django-admin startproject geodjango\n
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Detta kommer att initiera ett nytt projekt. Nu skapar du en Django-applikation world inom geodjango-projektet:

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Linux / macOS

Shell
$ cd geodjango\n$ python manage.py startapp world\n
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Windows

Windows
...\\> cd geodjango\n...\\> py manage.py startapp world\n
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Konfigurera settings.pyLink to this heading#

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Projektinställningarna för geodjango lagras i filen geodjango/settings.py. Redigera databasanslutningsinställningarna så att de matchar din installation:

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Code
DATABASES = {\n    "default": {\n        "ENGINE": "django.contrib.gis.db.backends.postgis",\n        "NAME": "geodjango",\n        "USER": "geo",\n    },\n}\n
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Ändra dessutom inställningen INSTALLED_APPS så att den inkluderar django.contrib.admin, django.contrib.gis och world (din nyskapade applikation):

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Code
INSTALLED_APPS = [\n    "django.contrib.admin",\n    "django.contrib.auth",\n    "django.contrib.contenttypes",\n    "django.contrib.sessions",\n    "django.contrib.messages",\n    "django.contrib.staticfiles",\n    "django.contrib.gis",\n    "world",\n]\n
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Geografiska dataLink to this heading#

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VärldsgränserLink to this heading#

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The world borders data is available in this zip file. Create a data\ndirectory in the world application, download the world borders data, and\nunzip. On GNU/Linux platforms, use the following commands:

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Linux / macOS

Shell
$ mkdir world/data\n$ cd world/data\n$ wget https://web.archive.org/web/20231220150759/https://thematicmapping.org/downloads/TM_WORLD_BORDERS-0.3.zip\n$ unzip TM_WORLD_BORDERS-0.3.zip\n$ cd ../..\n
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Windows

Windows
...\\> mkdir world\\data\n...\\> cd world\\data\n...\\> wget https://web.archive.org/web/20231220150759/https://thematicmapping.org/downloads/TM_WORLD_BORDERS-0.3.zip\n...\\> unzip TM_WORLD_BORDERS-0.3.zip\n...\\> cd ..\\..\n
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The world borders ZIP file contains a set of data files collectively known as\nan ESRI Shapefile, one of the most popular geospatial data formats. When\nunzipped, the world borders dataset includes files with the following\nextensions:

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Använd ogrinfo för att undersöka rumsliga dataLink to this heading#

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GDAL:s verktyg ogrinfo gör det möjligt att undersöka metadata för shapefiler eller andra vektordatakällor:

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Linux / macOS

Shell
$ ogrinfo world/data/TM_WORLD_BORDERS-0.3.shp\nINFO: Open of `world/data/TM_WORLD_BORDERS-0.3.shp'\n      using driver `ESRI Shapefile' successful.\n1: TM_WORLD_BORDERS-0.3 (Polygon)\n
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Windows

Windows
...\\> ogrinfo world\\data\\TM_WORLD_BORDERS-0.3.shp\nINFO: Open of `world/data/TM_WORLD_BORDERS-0.3.shp'\n      using driver `ESRI Shapefile' successful.\n1: TM_WORLD_BORDERS-0.3 (Polygon)\n
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ogrinfo tells us that the shapefile has one layer, and that this\nlayer contains polygon data. To find out more, we’ll specify the layer name\nand use the -so option to get only the important summary information:

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Linux / macOS

Shell
$ ogrinfo -so world/data/TM_WORLD_BORDERS-0.3.shp TM_WORLD_BORDERS-0.3\nINFO: Open of `world/data/TM_WORLD_BORDERS-0.3.shp'\n      using driver `ESRI Shapefile' successful.\n\nLayer name: TM_WORLD_BORDERS-0.3\nMetadata:\n  DBF_DATE_LAST_UPDATE=2008-07-30\nGeometry: Polygon\nFeature Count: 246\nExtent: (-180.000000, -90.000000) - (180.000000, 83.623596)\nLayer SRS WKT:\nGEOGCRS["WGS 84",\n    DATUM["World Geodetic System 1984",\n        ELLIPSOID["WGS 84",6378137,298.257223563,\n            LENGTHUNIT["metre",1]]],\n    PRIMEM["Greenwich",0,\n        ANGLEUNIT["degree",0.0174532925199433]],\n    CS[ellipsoidal,2],\n        AXIS["latitude",north,\n            ORDER[1],\n            ANGLEUNIT["degree",0.0174532925199433]],\n        AXIS["longitude",east,\n            ORDER[2],\n            ANGLEUNIT["degree",0.0174532925199433]],\n    ID["EPSG",4326]]\nData axis to CRS axis mapping: 2,1\nFIPS: String (2.0)\nISO2: String (2.0)\nISO3: String (3.0)\nUN: Integer (3.0)\nNAME: String (50.0)\nAREA: Integer (7.0)\nPOP2005: Integer64 (10.0)\nREGION: Integer (3.0)\nSUBREGION: Integer (3.0)\nLON: Real (8.3)\nLAT: Real (7.3)\n
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Windows

Windows
...\\> ogrinfo -so world\\data\\TM_WORLD_BORDERS-0.3.shp TM_WORLD_BORDERS-0.3\nINFO: Open of `world/data/TM_WORLD_BORDERS-0.3.shp'\n      using driver `ESRI Shapefile' successful.\n\nLayer name: TM_WORLD_BORDERS-0.3\nMetadata:\n  DBF_DATE_LAST_UPDATE=2008-07-30\nGeometry: Polygon\nFeature Count: 246\nExtent: (-180.000000, -90.000000) - (180.000000, 83.623596)\nLayer SRS WKT:\nGEOGCRS["WGS 84",\n    DATUM["World Geodetic System 1984",\n        ELLIPSOID["WGS 84",6378137,298.257223563,\n            LENGTHUNIT["metre",1]]],\n    PRIMEM["Greenwich",0,\n        ANGLEUNIT["degree",0.0174532925199433]],\n    CS[ellipsoidal,2],\n        AXIS["latitude",north,\n            ORDER[1],\n            ANGLEUNIT["degree",0.0174532925199433]],\n        AXIS["longitude",east,\n            ORDER[2],\n            ANGLEUNIT["degree",0.0174532925199433]],\n    ID["EPSG",4326]]\nData axis to CRS axis mapping: 2,1\nFIPS: String (2.0)\nISO2: String (2.0)\nISO3: String (3.0)\nUN: Integer (3.0)\nNAME: String (50.0)\nAREA: Integer (7.0)\nPOP2005: Integer64 (10.0)\nREGION: Integer (3.0)\nSUBREGION: Integer (3.0)\nLON: Real (8.3)\nLAT: Real (7.3)\n
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This detailed summary information tells us the number of features in the layer\n(246), the geographic bounds of the data, the spatial reference system\n(”SRS WKT”), as well as type information for each attribute field. For example,\nFIPS: String (2.0) indicates that the FIPS character field has\na maximum length of 2. Similarly, LON: Real (8.3) is a floating-point\nfield that holds a maximum of 8 digits up to three decimal places.

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Geografiska modellerLink to this heading#

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Definiera en geografisk modellLink to this heading#

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Nu när du har undersökt din dataset med hjälp av ogrinfo, skapa en GeoDjango modell för att representera dessa data:

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Code
from django.contrib.gis.db import models\n\n\nclass WorldBorder(models.Model):\n    # Regular Django fields corresponding to the attributes in the\n    # world borders shapefile.\n    name = models.CharField(max_length=50)\n    area = models.IntegerField()\n    pop2005 = models.IntegerField("Population 2005")\n    fips = models.CharField("FIPS Code", max_length=2, null=True)\n    iso2 = models.CharField("2 Digit ISO", max_length=2)\n    iso3 = models.CharField("3 Digit ISO", max_length=3)\n    un = models.IntegerField("United Nations Code")\n    region = models.IntegerField("Region Code")\n    subregion = models.IntegerField("Sub-Region Code")\n    lon = models.FloatField()\n    lat = models.FloatField()\n\n    # GeoDjango-specific: a geometry field (MultiPolygonField)\n    mpoly = models.MultiPolygonField()\n\n    # Returns the string representation of the model.\n    def __str__(self):\n        return self.name\n
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Observera att modulen models importeras från django.contrib.gis.db.

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The default spatial reference system for geometry fields is WGS84 (meaning\nthe SRID is 4326) – in other words, the field coordinates are in\nlongitude, latitude pairs in units of degrees. To use a different\ncoordinate system, set the SRID of the geometry field with the srid\nargument. Use an integer representing the coordinate system’s EPSG code.

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Kör migrateLink to this heading#

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När du har definierat din modell måste du synkronisera den med databasen. Först skapar du en databasmigrering:

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Linux / macOS

Shell
$ python manage.py makemigrations\nMigrations for 'world':\n  world/migrations/0001_initial.py:\n    + Create model WorldBorder\n
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Windows

Windows
...\\> py manage.py makemigrations\nMigrations for 'world':\n  world/migrations/0001_initial.py:\n    + Create model WorldBorder\n
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Låt oss titta på den SQL som kommer att generera tabellen för modellen WorldBorder:

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Linux / macOS

Shell
$ python manage.py sqlmigrate world 0001\n
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Windows

Windows
...\\> py manage.py sqlmigrate world 0001\n
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Detta kommando bör ge följande resultat:

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SQL
BEGIN;\n--\n-- Create model WorldBorder\n--\nCREATE TABLE "world_worldborder" (\n    "id" bigint NOT NULL PRIMARY KEY GENERATED BY DEFAULT AS IDENTITY,\n    "name" varchar(50) NOT NULL,\n    "area" integer NOT NULL,\n    "pop2005" integer NOT NULL,\n    "fips" varchar(2) NOT NULL,\n    "iso2" varchar(2) NOT NULL,\n    "iso3" varchar(3) NOT NULL,\n    "un" integer NOT NULL,\n    "region" integer NOT NULL,\n    "subregion" integer NOT NULL,\n    "lon" double precision NOT NULL,\n    "lat" double precision NOT NULL\n    "mpoly" geometry(MULTIPOLYGON,4326) NOT NULL\n)\n;\nCREATE INDEX "world_worldborder_mpoly_id" ON "world_worldborder" USING GIST ("mpoly");\nCOMMIT;\n
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Om detta ser korrekt ut, kör migrate för att skapa denna tabell i databasen:

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Linux / macOS

Shell
$ python manage.py migrate\nOperations to perform:\n  Apply all migrations: admin, auth, contenttypes, sessions, world\nRunning migrations:\n  ...\n  Applying world.0001_initial... OK\n
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Windows

Windows
...\\> py manage.py migrate\nOperations to perform:\n  Apply all migrations: admin, auth, contenttypes, sessions, world\nRunning migrations:\n  ...\n  Applying world.0001_initial... OK\n
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Importera rumsliga dataLink to this heading#

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This section will show you how to import the world borders shapefile into the\ndatabase via GeoDjango models using the LayerMapping verktyg för dataimport.

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Det finns många olika sätt att importera data till en rumslig databas - förutom de verktyg som ingår i GeoDjango kan du också använda följande:

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GDAL-gränssnittLink to this heading#

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Earlier, you used ogrinfo to examine the contents of the world borders\nshapefile. GeoDjango also includes a Pythonic interface to GDAL’s powerful OGR\nlibrary that can work with all the vector data sources that OGR supports.

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Först anropar du Django-skalet:

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Linux / macOS

Shell
$ python manage.py shell\n
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Windows

Windows
...\\> py manage.py shell\n
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Om du hämtade data från Världsgränser tidigare i handledningen kan du bestämma dess sökväg med hjälp av Pythons pathlib.Path:

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Python console
>>> from pathlib import Path\n>>> import world\n>>> world_shp = Path(world.__file__).resolve().parent / "data" / "TM_WORLD_BORDERS-0.3.shp"\n
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Öppna nu shapefilen med världsgränser med hjälp av GeoDjangos DataSource-gränssnitt:

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Python console
>>> from django.contrib.gis.gdal import DataSource\n>>> ds = DataSource(world_shp)\n>>> print(ds)\n/ ... /geodjango/world/data/TM_WORLD_BORDERS-0.3.shp (ESRI Shapefile)\n
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Datakällobjekt kan ha olika lager av geospatiala funktioner, men shapefiler får bara ha ett lager:

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Python console
>>> print(len(ds))\n1\n>>> lyr = ds[0]\n>>> print(lyr)\nTM_WORLD_BORDERS-0.3\n
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Du kan se skiktets geometrityp och hur många funktioner det innehåller:

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Python console
>>> print(lyr.geom_type)\nPolygon\n>>> print(len(lyr))\n246\n
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The Layer may also have a spatial reference\nsystem associated with it. If it does, the srs attribute will return a\nSpatialReference object:

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Python console
>>> srs = lyr.srs\n>>> print(srs)\nGEOGCS["WGS 84",\nDATUM["WGS_1984",\n    SPHEROID["WGS 84",6378137,298.257223563,\n        AUTHORITY["EPSG","7030"]],\n    AUTHORITY["EPSG","6326"]],\nPRIMEM["Greenwich",0,\n    AUTHORITY["EPSG","8901"]],\nUNIT["degree",0.0174532925199433,\n    AUTHORITY["EPSG","9122"]],\nAXIS["Latitude",NORTH],\nAXIS["Longitude",EAST],\nAUTHORITY["EPSG","4326"]]\n>>> srs.proj  # PROJ representation\n'+proj=longlat +datum=WGS84 +no_defs'\n
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Denna shapefil är i det populära rumsliga referenssystemet WGS84 - med andra ord använder data par av longitud, latitud i enheter av grader.

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In addition, shapefiles also support attribute fields that may contain\nadditional data. Here are the fields on the World Borders layer:

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Python console
>>> print(lyr.fields)\n['FIPS', 'ISO2', 'ISO3', 'UN', 'NAME', 'AREA', 'POP2005', 'REGION', 'SUBREGION', 'LON', 'LAT']\n
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Med följande kod kan du undersöka de OGR-typer (t.ex. heltal eller sträng) som är associerade med vart och ett av fälten:

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Python console
>>> [fld.__name__ for fld in lyr.field_types]\n['OFTString', 'OFTString', 'OFTString', 'OFTInteger', 'OFTString', 'OFTInteger', 'OFTInteger64', 'OFTInteger', 'OFTInteger', 'OFTReal', 'OFTReal']\n
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Du kan iterera över varje objekt i skiktet och extrahera information från både objektets geometri (som nås via attributet geom) och objektets attributfält (vars värden nås via metoden get()):

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Python console
>>> for feat in lyr:\n...     print(feat.get("NAME"), feat.geom.num_points)\n...\nGuernsey 18\nJersey 26\nSouth Georgia South Sandwich Islands 338\nTaiwan 363\n
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Layer-objekt kan skivas:

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Python console
>>> lyr[0:2]\n[<django.contrib.gis.gdal.feature.Feature object at 0x2f47690>, <django.contrib.gis.gdal.feature.Feature object at 0x2f47650>]\n
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Och enskilda funktioner kan hämtas med hjälp av deras funktions-ID:

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Python console
>>> feat = lyr[234]\n>>> print(feat.get("NAME"))\nSan Marino\n
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Gränsgeometrier kan exporteras som WKT och GeoJSON:

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Python console
>>> geom = feat.geom\n>>> print(geom.wkt)\nPOLYGON ((12.415798 43.957954,12.450554 ...\n>>> print(geom.json)\n{ "type": "Polygon", "coordinates": [ [ [ 12.415798, 43.957954 ], [ 12.450554, 43.979721 ], ...\n
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LayerMappingLink to this heading#

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För att importera data använder du en LayerMapping i ett Python-skript. Skapa en fil som heter load.py i applikationen world med följande kod:

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Code
from pathlib import Path\nfrom django.contrib.gis.utils import LayerMapping\nfrom .models import WorldBorder\n\nworld_mapping = {\n    "fips": "FIPS",\n    "iso2": "ISO2",\n    "iso3": "ISO3",\n    "un": "UN",\n    "name": "NAME",\n    "area": "AREA",\n    "pop2005": "POP2005",\n    "region": "REGION",\n    "subregion": "SUBREGION",\n    "lon": "LON",\n    "lat": "LAT",\n    "mpoly": "MULTIPOLYGON",\n}\n\nworld_shp = Path(__file__).resolve().parent / "data" / "TM_WORLD_BORDERS-0.3.shp"\n\n\ndef run(verbose=True):\n    lm = LayerMapping(WorldBorder, world_shp, world_mapping, transform=False)\n    lm.save(strict=True, verbose=verbose)\n
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Några anteckningar om vad som händer:

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Därefter anropar du Django-skalet från projektkatalogen geodjango:

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Linux / macOS

Shell
$ python manage.py shell\n
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Windows

Windows
...\\> py manage.py shell\n
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Därefter importerar du modulen load, anropar rutinen run och ser LayerMapping göra jobbet:

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Python console
>>> from world import load\n>>> load.run()\n
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Prova ogrinspectLink to this heading#

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Now that you’ve seen how to define geographic models and import data with the\nLayerMapping verktyg för dataimport, it’s possible to further automate this\nprocess with use of the ogrinspect management command. The\nogrinspect command introspects a GDAL-supported vector data source\n(e.g., a shapefile) and generates a model definition and LayerMapping\ndictionary automatically.

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Den allmänna användningen av kommandot går till på följande sätt:

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Linux / macOS

Shell
$ python manage.py ogrinspect [options] <data_source> <model_name> [options]\n
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Windows

Windows
...\\> py manage.py ogrinspect [options] <data_source> <model_name> [options]\n
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data_source is the path to the GDAL-supported data source and\nmodel_name is the name to use for the model. Command-line options may\nbe used to further define how the model is generated.

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Exempelvis kan följande kommando nästan automatiskt reproducera modellen WorldBorder och mappningsordlistan som skapats ovan:

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Linux / macOS

Shell
$ python manage.py ogrinspect world/data/TM_WORLD_BORDERS-0.3.shp WorldBorder \\\n    --srid=4326 --mapping --multi\n
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Windows

Windows
...\\> py manage.py ogrinspect world\\data\\TM_WORLD_BORDERS-0.3.shp WorldBorder \\\n    --srid=4326 --mapping --multi\n
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Några kommentarer om de kommandoradsalternativ som anges ovan:

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Kommandot ger följande resultat, som kan kopieras direkt till models.py i en GeoDjango-applikation:

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Code
# This is an auto-generated Django model module created by ogrinspect.\nfrom django.contrib.gis.db import models\n\n\nclass WorldBorder(models.Model):\n    fips = models.CharField(max_length=2)\n    iso2 = models.CharField(max_length=2)\n    iso3 = models.CharField(max_length=3)\n    un = models.IntegerField()\n    name = models.CharField(max_length=50)\n    area = models.IntegerField()\n    pop2005 = models.IntegerField()\n    region = models.IntegerField()\n    subregion = models.IntegerField()\n    lon = models.FloatField()\n    lat = models.FloatField()\n    geom = models.MultiPolygonField(srid=4326)\n\n\n# Auto-generated `LayerMapping` dictionary for WorldBorder model\nworldborders_mapping = {\n    "fips": "FIPS",\n    "iso2": "ISO2",\n    "iso3": "ISO3",\n    "un": "UN",\n    "name": "NAME",\n    "area": "AREA",\n    "pop2005": "POP2005",\n    "region": "REGION",\n    "subregion": "SUBREGION",\n    "lon": "LON",\n    "lat": "LAT",\n    "geom": "MULTIPOLYGON",\n}\n
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Rumsliga frågorLink to this heading#

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Rumsliga uppslagningarLink to this heading#

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GeoDjango adds spatial lookups to the Django ORM. For example, you\ncan find the country in the WorldBorder table that contains\na particular point. First, fire up the management shell:

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Linux / macOS

Shell
$ python manage.py shell\n
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Windows

Windows
...\\> py manage.py shell\n
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Nu ska du definiera en intressepunkt [3]:

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Python console
>>> pnt_wkt = "POINT(-95.3385 29.7245)"\n
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The pnt_wkt string represents the point at -95.3385 degrees longitude,\n29.7245 degrees latitude. The geometry is in a format known as\nWell Known Text (WKT), a standard issued by the Open Geospatial\nConsortium (OGC). [4] Import the WorldBorder model, and perform\na contains lookup using the pnt_wkt as the parameter:

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Python console
>>> from world.models import WorldBorder\n>>> WorldBorder.objects.filter(mpoly__contains=pnt_wkt)\n<QuerySet [<WorldBorder: United States>]>\n
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Här hämtade du en QuerySet med bara en modell: USA:s gräns (precis vad du förväntar dig).

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Similarly, you may also use a GEOS geometry object. Here, you can combine the intersects spatial\nlookup with the get method to retrieve only the WorldBorder instance\nfor San Marino instead of a queryset:

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Python console
>>> from django.contrib.gis.geos import Point\n>>> pnt = Point(12.4604, 43.9420)\n>>> WorldBorder.objects.get(mpoly__intersects=pnt)\n<WorldBorder: San Marino>\n
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The contains and intersects lookups are just a subset of the available\nqueries – the GeoDjango databas API documentation has more.

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Automatiska rumsliga omvandlingarLink to this heading#

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When doing spatial queries, GeoDjango automatically transforms\ngeometries if they’re in a different coordinate system. In the following\nexample, coordinates will be expressed in EPSG SRID 32140,\na coordinate system specific to south Texas only and in units of\nmeters, not degrees:

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Python console
>>> from django.contrib.gis.geos import GEOSGeometry, Point\n>>> pnt = Point(954158.1, 4215137.1, srid=32140)\n
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Observera att pnt också kan konstrueras med EWKT, en ”utökad” form av WKT som inkluderar SRID:

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Python console
>>> pnt = GEOSGeometry("SRID=32140;POINT(954158.1 4215137.1)")\n
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GeoDjangos ORM slår automatiskt in geometrivärden i transformations-SQL, vilket gör att utvecklaren kan arbeta på en högre abstraktionsnivå:

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Python console
>>> qs = WorldBorder.objects.filter(mpoly__intersects=pnt)\n>>> print(qs.query)  # Generating the SQL\nSELECT "world_worldborder"."id", "world_worldborder"."name", "world_worldborder"."area",\n"world_worldborder"."pop2005", "world_worldborder"."fips", "world_worldborder"."iso2",\n"world_worldborder"."iso3", "world_worldborder"."un", "world_worldborder"."region",\n"world_worldborder"."subregion", "world_worldborder"."lon", "world_worldborder"."lat",\n"world_worldborder"."mpoly" FROM "world_worldborder"\nWHERE ST_Intersects("world_worldborder"."mpoly", ST_Transform(%s, 4326))\n>>> qs  # printing evaluates the queryset\n<QuerySet [<WorldBorder: United States>]>\n
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Lata geometrierLink to this heading#

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GeoDjango loads geometries in a standardized textual representation. When the\ngeometry field is first accessed, GeoDjango creates a\nGEOSGeometry object, exposing powerful\nfunctionality, such as serialization properties for popular geospatial\nformats:

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Python console
>>> sm = WorldBorder.objects.get(name="San Marino")\n>>> sm.mpoly\n<MultiPolygon object at 0x24c6798>\n>>> sm.mpoly.wkt  # WKT\nMULTIPOLYGON (((12.4157980000000006 43.9579540000000009, 12.4505540000000003 43.9797209999999978, ...\n>>> sm.mpoly.wkb  # WKB (as Python binary buffer)\n<read-only buffer for 0x1fe2c70, size -1, offset 0 at 0x2564c40>\n>>> sm.mpoly.geojson  # GeoJSON\n'{ "type": "MultiPolygon", "coordinates": [ [ [ [ 12.415798, 43.957954 ], [ 12.450554, 43.979721 ], ...\n
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Detta inkluderar tillgång till alla avancerade geometriska operationer som tillhandahålls av GEOS-biblioteket:

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Python console
>>> pnt = Point(12.4604, 43.9420)\n>>> sm.mpoly.contains(pnt)\nTrue\n>>> pnt.contains(sm.mpoly)\nFalse\n
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Geografiska anteckningarLink to this heading#

\n

GeoDjango also offers a set of geographic annotations to compute distances and\nseveral other operations (intersection, difference, etc.). See the\nGeografiska databasfunktioner documentation.

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\n
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Placera dina data på kartanLink to this heading#

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Geografisk administratörLink to this heading#

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Djangos admin-applikation stöder redigering av geometriska fält.

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GrundläggandeLink to this heading#

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Django-admin låter användare skapa och ändra geometrier på en JavaScript-karta (som drivs av OpenLayers).

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Låt oss dyka rätt in. Skapa en fil som heter admin.py inuti applikationen world med följande kod:

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Code
from django.contrib.gis import admin\nfrom .models import WorldBorder\n\nadmin.site.register(WorldBorder, admin.ModelAdmin)\n
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Därefter redigerar du din urls.py i applikationsmappen geodjango enligt följande:

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Code
from django.contrib import admin\nfrom django.urls import include, path\n\nurlpatterns = [\n    path("admin/", admin.site.urls),\n]\n
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Skapa en administratörsanvändare:

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Linux / macOS

Shell
$ python manage.py createsuperuser\n
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Windows

Windows
...\\> py manage.py createsuperuser\n
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Starta sedan upp Django-utvecklingsservern:

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Linux / macOS

Shell
$ python manage.py runserver\n
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Windows

Windows
...\\> py manage.py runserver\n
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Slutligen, bläddra till http://localhost:8000/admin/ och logga in med den användare du just skapat. Bläddra till någon av WorldBorder-posterna - gränserna kan redigeras genom att klicka på en polygon och dra hörnen till önskad position.

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GISModelAdminLink to this heading#

\n

Med GISModelAdmin använder GeoDjango ett OpenStreetMap-lager i admin. Detta ger mer sammanhang (inklusive detaljer om gator och genomfartsleder) än vad som är tillgängligt med ModelAdmin (som använder WMS-datasetet Vector Map Level 0 som finns hos OSGeo).

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PROJ datumskiftesfiler måste installeras (se PROJ installationsinstruktioner för mer information).

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Om du uppfyller detta krav kan du använda alternativklassen GISModelAdmin i filen admin.py:

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Code
admin.site.register(WorldBorder, admin.GISModelAdmin)\n
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Fotnoter

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\n
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