{"title":"Pengajaran Tambahan GeoDjango","version":"5.0","locale":"id","docname":"ref/contrib/gis/tutorial","url":"/id/5.0/ref/contrib/gis/tutorial/","canonical":"https://djangodocs.dev/id/5.0/ref/contrib/gis/tutorial/","summary":"Kata Pengantar Link to this heading # GeoDjango is an included contrib module for Django that turns it into a world-class geographic web framework. GeoDjango…","html":"

Pengajaran Tambahan GeoDjangoLink to this heading#

\n
\n

Kata PengantarLink to this heading#

\n

GeoDjango is an included contrib module for Django that turns it into a\nworld-class geographic web framework. GeoDjango strives to make it as simple\nas possible to create geographic web applications, like location-based services.\nIts features include:

\n\n

Pengajaran tambahan ini menganggap keakraban dengan Django; dengan demikian, jika anda adalah baru pada Django, harap baca melalui the regular tutorial untuk mengakrabkan anda sendiri dengan Django terlebih dahulu.

\n\n

Pengajaran tambahan ini akan memandu anda melalui pembuatan dari aplikasi jaringan geografis untuk menampilkan world borders. [1] Beberapa dari kode digunakan dalam pengajaran tambahan ini diambil dari dan/atau diilhami oleh proyek GeoDjango basic apps. [2]

\n\n
\n
\n

PengaturanLink to this heading#

\n
\n

Buat Basisdata SpasialLink to this heading#

\n

Secara khusus tidak ada pengaturan khusus diperlukan, jadi anda dapat membuat sebuah basisdata seperti anda aakan untuk proyek lain apapun. Kami menyediakan saran untuk basisdata terpilih:

\n\n
\n
\n

Buat Proyek BaruLink to this heading#

\n

Gunakan tulisan django-admin standar untuk membuat sebuah proyek dipanggil geodjango:

\n

Linux / macOS

Shell
$ django-admin startproject geodjango\n
\n

Windows

Windows
...\\> django-admin startproject geodjango\n
\n

Ini akan memulai sebuah proyek baru. Sekarang, buat sebuah aplikasi Django world dalam proyek geodjango:

\n

Linux / macOS

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

Windows

Windows
...\\> cd geodjango\n...\\> py manage.py startapp world\n
\n
\n
\n

Konfigurasi settings.pyLink to this heading#

\n

Pengaturan proyek geodjango disimpan dalam berkas geodjango/settings.py. Sunting pengaturan hubungan basisdata untuk mencocokkan pengaturan anda:

\n
Code
DATABASES = {\n    "default": {\n        "ENGINE": "django.contrib.gis.db.backends.postgis",\n        "NAME": "geodjango",\n        "USER": "geo",\n    },\n}\n
\n

Sebagai tambahan, rubah pengaturan INSTALLED_APPS untuk menyertakan django.contrib.admin, django.contrib.gis, dan world (aplikasi dibuat terbaru anda):

\n
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
\n
\n
\n
\n

Data GeografisLink to this heading#

\n
\n

Batasan DuniaLink to this heading#

\n

Data perbatasan dunia tersedia di zip file. Buat sebuah direktori data di aplikasi world, unduh data perbatasan dunia, dan buka. Pada serambi GNU/Linux, gunakan perintah berikut:

\n

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
\n

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
\n

Berkas ZIP world borders mengandung kumpulan dari berkas-berkas data secara kolektif dikenal sebagai ESRI Shapefile, satu dari bentuk data geospasial paling terkenal. Ketika dibuka, kumpulan data world borders menyertakan berkas-berkas dengan tambahan berikut:

\n\n
\n
\n

Gunakan ogrinfo untuk menjalankan data spasialLink to this heading#

\n

Kegunaan ogrinfo GDAL mengizinkan mennguji metadata dari shapefile atau sumber data vektor:

\n

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
\n

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
\n

ogrinfo memberitahu kita bahwa shapefile mempunyai satu lapisan, dan lapisan ini mengandung data poligon. Untuk menemukan satu lagi, kami akan menentukan nama lapisan dan menggunakan pilihan -so untuk hanya mendapatkan informasi ringkasan penting:

\n

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\nGeometry: Polygon\nFeature Count: 246\nExtent: (-180.000000, -90.000000) - (180.000000, 83.623596)\nLayer SRS WKT:\nGEOGCS["GCS_WGS_1984",\n    DATUM["WGS_1984",\n        SPHEROID["WGS_1984",6378137.0,298.257223563]],\n    PRIMEM["Greenwich",0.0],\n    UNIT["Degree",0.0174532925199433]]\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: Integer (10.0)\nREGION: Integer (3.0)\nSUBREGION: Integer (3.0)\nLON: Real (8.3)\nLAT: Real (7.3)\n
\n

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\nGeometry: Polygon\nFeature Count: 246\nExtent: (-180.000000, -90.000000) - (180.000000, 83.623596)\nLayer SRS WKT:\nGEOGCS["GCS_WGS_1984",\n    DATUM["WGS_1984",\n        SPHEROID["WGS_1984",6378137.0,298.257223563]],\n    PRIMEM["Greenwich",0.0],\n    UNIT["Degree",0.0174532925199433]]\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: Integer (10.0)\nREGION: Integer (3.0)\nSUBREGION: Integer (3.0)\nLON: Real (8.3)\nLAT: Real (7.3)\n
\n

Ringkasan informasi rincian memberitahu kami angka dari fitur-fitur dalam apisan (246), batasan geografis dari data, sistem acuan spasial ("SRS WKT"), sama seperti jenis informasi untuk setiap bidang atribut. Sebagai contoh, FIPS: String (2.0) menunjukkan bahwa bidang karakter FIPS mempunyai panjang maksimal dari 2. Mirip, LON: Real (8.3) adalah bdiang floating-point yang menampung maksimal dari 8 angka sampai tiga tempat desimal.

\n
\n
\n
\n

Model GeografisLink to this heading#

\n
\n

Menentukan Model GeografisLink to this heading#

\n

Sekarang anda telah mengujikan dataset anda menggunakan originfo, membuat sebuah model GeoDjango untuk mewakili data ini:

\n
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
\n

Catat bahwa modul models diimpor dari django.contrib.gis.db.

\n

Sistem acuan spasial awalan untuk bidang-bidang geometri adalah WGS84 (berarti SRID adalah 4326) -- dengan kata lain, kordinat bidang adalah pasangan bujur, lintang dalam satuan derajat. Untuk menggunakan sistem kordinat berbeda, setel SRID dari bidang geometri dengan argumen srid. Gunakan sebuah integer mewakili kode EPSG sistem kordinat.

\n
\n
\n

Jalankan migrateLink to this heading#

\n

Setelah menentukan model anda, anda butuh mensinkronisasikan itu dengan basisdata. Pertama, buat sebuah perpindahan basisdata:

\n

Linux / macOS

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

Windows

Windows
...\\> py manage.py makemigrations\nMigrations for 'world':\n  world/migrations/0001_initial.py:\n    - Create model WorldBorder\n
\n

Mari kita lihat pada SQL yang akan membangkitkan tabel untuk model WorldBorder:

\n

Linux / macOS

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

Windows

Windows
...\\> py manage.py sqlmigrate world 0001\n
\n

Perintah ini harus menghasilkan keluaran berikut:

\n
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
\n

Jika ini terlihat benar, jalankan migrate untuk membuat tabel ini dalam basisdata:

\n

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
\n

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
\n
\n
\n
\n

Mengimpor Data SpasialLink to this heading#

\n

Bagian ini akan menunjukkan anda bagaimana meng impor shapefile batasan dunia kedalam basisdata melalui model GeoDjango menggunakan Kegunaan impor data LayerMapping.

\n

Ada banyak cara berbeda utuk meng impor data kedalam basisdata spasial -- disamping alat-alat disertakan dalam GeoDjango, anda mungkin juga menggunakan berikut:

\n\n
\n

Antarmuka GDALLink to this heading#

\n

Diawal, anda menggunakan ogrinfo untuk menjalankan isi dari batasan dunia shapefile. GeoDjango juga menyertakan sebuah antarmuka Pythonic pada pustaka OGR GDAL yang hebat yang dapat bekerja dengan semua sumber data vektor yang dukung OGR.

\n

Pertama, minta cangkang Django:

\n

Linux / macOS

Shell
$ python manage.py shell\n
\n

Windows

Windows
...\\> py manage.py shell\n
\n

If you downloaded the Batasan Dunia data earlier in the tutorial, then\nyou can determine its path using Python's pathlib.Path:

\n
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
\n

Now, open the world borders shapefile using GeoDjango's\nDataSource interface:

\n
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
\n

Data source objects can have different layers of geospatial features; however,\nshapefiles are only allowed to have one layer:

\n
Python console
>>> print(len(ds))\n1\n>>> lyr = ds[0]\n>>> print(lyr)\nTM_WORLD_BORDERS-0.3\n
\n

You can see the layer's geometry type and how many features it contains:

\n
Python console
>>> print(lyr.geom_type)\nPolygon\n>>> print(len(lyr))\n246\n
\n\n

The Layer may also have a spatial reference\nsystem associated with it. If it does, the srs attribute will return a\nSpatialReference object:

\n
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
\n

Shapefile ini dalam sistem acuan spasial WGS84 yang terkenal -- dengan kata lain, data menggunakan pasangan garis, bujur dalam satuan derajat.

\n

Seabgai tambahan, shapefile juga mendukung bidang-bidang atribut yang mungkin mengandung data tambahan. Disini adalah bidang-bidang pada lapisan World Borders:

\n
Code
>>> print(lyr.fields)\n['FIPS', 'ISO2', 'ISO3', 'UN', 'NAME', 'AREA', 'POP2005', 'REGION', 'SUBREGION', 'LON', 'LAT']\n
\n

Kode berikut akan membiarkan anda menguji jenis-jenis OGR (misalnya integer atau string) berkaitan dengan masing-masing bidang:

\n
Code
>>> [fld.__name__ for fld in lyr.field_types]\n['OFTString', 'OFTString', 'OFTString', 'OFTInteger', 'OFTString', 'OFTInteger', 'OFTInteger64', 'OFTInteger', 'OFTInteger', 'OFTReal', 'OFTReal']\n
\n

You can iterate over each feature in the layer and extract information from both\nthe feature's geometry (accessed via the geom attribute) as well as the\nfeature's attribute fields (whose values are accessed via get()\nmethod):

\n
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
\n

Layer objects may be sliced:

\n
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
\n

And individual features may be retrieved by their feature ID:

\n
Python console
>>> feat = lyr[234]\n>>> print(feat.get("NAME"))\nSan Marino\n
\n

Boundary geometries may be exported as WKT and GeoJSON:

\n
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
\n
\n
\n

LayerMappingLink to this heading#

\n

To import the data, use a LayerMapping in a Python script.\nCreate a file called load.py inside the world application,\nwith the following code:

\n
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
\n

Sedikit catatan mengenai apa yang terjadi:

\n\n

Afterward, invoke the Django shell from the geodjango project directory:

\n

Linux / macOS

Shell
$ python manage.py shell\n
\n

Windows

Windows
...\\> py manage.py shell\n
\n

Next, import the load module, call the run routine, and watch\nLayerMapping do the work:

\n
Python console
>>> from world import load\n>>> load.run()\n
\n
\n
\n

Coba ogrinspectLink to this heading#

\n

Sekarang anda telah melihat bagaimana menentukan model geografis dan impor data dengan Kegunaan impor data LayerMapping, itu memungkinkan untuk mengotomatisasi lebih jauh pengolahan ini dengan menggunakan perintah pengelolaan ogrinspect. Perintah ogrinspect memawas diri sumber data vektor didukung-GDAL (misalnya, sebuah shapefile) dan dan membangkitkan sebuah penentuan model dan dictionary LayerMapping secara otomatis.

\n

Penggunaan umum dari perintah sebagai berikut:

\n

Linux / macOS

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

Windows

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

data_source adalah jalur pada sumber data didukung-GDAL dan model_name adalah nama digunakan untuk model. Pilihan-pilihan baris-perintah mungkin digunkana untuk penentukan lebih jauh bagaimana model dibangkitkan.

\n

Sebagai contoh, perintah berikut hampir membuat kembali model WorldBorder dan dictionary pemetaan dibuat diatas, secara otomatis:

\n

Linux / macOS

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

Windows

Windows
...\\> py manage.py ogrinspect world\\data\\TM_WORLD_BORDERS-0.3.shp WorldBorder \\\n    --srid=4326 --mapping --multi\n
\n

Sedikit catatan tentang pilihan baris-perintah diberikan diatas:

\n\n

Perintah menghasilkan keluaran berikut, yang mungkin disalin langsung kedalam models.py dari aplikasi GeoDjango:

\n
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
\n
\n
\n
\n

Spatial QueriesLink to this heading#

\n
\n

Pencarian SpasialLink to this heading#

\n

GeoDjango menambahkan pencarian spasial pada ORM Django. Sebagai contoh, anda dapat menemukan negara dalam tabel WorldBorder yang mengandung titik tertentu. Pertama, nyalakan cangkang pengelolaan:

\n

Linux / macOS

Shell
$ python manage.py shell\n
\n

Windows

Windows
...\\> py manage.py shell\n
\n

Now, define a point of interest [3]:

\n
Python console
>>> pnt_wkt = "POINT(-95.3385 29.7245)"\n
\n

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:

\n
Python console
>>> from world.models import WorldBorder\n>>> WorldBorder.objects.filter(mpoly__contains=pnt_wkt)\n<QuerySet [<WorldBorder: United States>]>\n
\n

Disini, anda mengambil sebuah QuerySet dengan hanya satu model: batasan dari Amerika Serikat (tepatnya apa anda ingin harapkan).

\n

Similarly, you may also use a GEOS geometry object.\nHere, you can combine the intersects spatial lookup with the get\nmethod to retrieve only the WorldBorder instance for San Marino instead\nof a queryset:

\n
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
\n

Pencarian contains dan intersects adalah hanya himpunan bagian dari permintaan tersedia -- dokumentasi API Basisdata GeoDjango mempunyai lebih.

\n
\n
\n

Automatic Spatial TransformationsLink to this heading#

\n

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:

\n
Python console
>>> from django.contrib.gis.geos import GEOSGeometry, Point\n>>> pnt = Point(954158.1, 4215137.1, srid=32140)\n
\n

Note that pnt may also be constructed with EWKT, an "extended" form of\nWKT that includes the SRID:

\n
Python console
>>> pnt = GEOSGeometry("SRID=32140;POINT(954158.1 4215137.1)")\n
\n

GeoDjango's ORM will automatically wrap geometry values\nin transformation SQL, allowing the developer to work at a higher level\nof abstraction:

\n
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
\n\n
\n
\n

Geometri LazyLink to this heading#

\n

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:

\n
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
\n

This includes access to all of the advanced geometric operations provided by\nthe GEOS library:

\n
Python console
>>> pnt = Point(12.4604, 43.9420)\n>>> sm.mpoly.contains(pnt)\nTrue\n>>> pnt.contains(sm.mpoly)\nFalse\n
\n
\n
\n

Keterangan geografisLink to this heading#

\n

GeoDjango juga menawarkan kumpulan dari penjelasan geografis untuk menghitung jarak dan beberapa tindakan lain (persimpangan, berbeda, dll). Lihat dokumentasi Fungsi Basisdata Geografis.

\n
\n
\n
\n

Menaruh data anda di petaLink to this heading#

\n
\n

Admin GeografisLink to this heading#

\n

Django's admin application supports editing\ngeometry fields.

\n
\n

DasarLink to this heading#

\n

The Django admin allows users to create and modify geometries on a JavaScript\nslippy map (powered by OpenLayers).

\n

Let's dive right in. Create a file called admin.py inside the world\napplication with the following code:

\n
Code
from django.contrib.gis import admin\nfrom .models import WorldBorder\n\nadmin.site.register(WorldBorder, admin.ModelAdmin)\n
\n

Selanjutnya, sunting urls.py anda dalam pelipat aplikasi geodjango seperti berikut:

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

Buat pengguna admin:

\n

Linux / macOS

Shell
$ python manage.py createsuperuser\n
\n

Windows

Windows
...\\> py manage.py createsuperuser\n
\n

Selanjutnya, mulai peladen pengembangan Django:

\n

Linux / macOS

Shell
$ python manage.py runserver\n
\n

Windows

Windows
...\\> py manage.py runserver\n
\n

Akhirnya, telusuri http://localhost:8000/admin/, dan masuk dengan pengguna anda baru buat. Telusuri apapun dari masukan WorldBorder -- batasan mungkin disunting dengan mengklik pada poligon dan menarik simpul pada tempat yang diinginkan.

\n
\n
\n

GISModelAdminLink to this heading#

\n

With the GISModelAdmin, GeoDjango uses an\nOpenStreetMap layer in the admin.\nThis provides more context (including street and thoroughfare details) than\navailable with the ModelAdmin (which uses the\nVector Map Level 0 WMS dataset hosted at OSGeo).

\n

The PROJ datum shifting files must be installed (see the PROJ\ninstallation instructions for more details).

\n

If you meet this requirement, then use the GISModelAdmin option class\nin your admin.py file:

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

Catatan kaki

\n\n
\n
\n
","rootId":"geodjango-tutorial","toc":[{"title":"Kata Pengantar","anchor":"introduction","children":[]},{"title":"Pengaturan","anchor":"setting-up","children":[{"title":"Buat Basisdata Spasial","anchor":"create-a-spatial-database","children":[]},{"title":"Buat Proyek Baru","anchor":"create-a-new-project","children":[]},{"title":"Konfigurasi settings.py","anchor":"configure-settings-py","children":[]}]},{"title":"Data Geografis","anchor":"geographic-data","children":[{"title":"Batasan Dunia","anchor":"worldborders","children":[]},{"title":"Gunakan ogrinfo untuk menjalankan data spasial","anchor":"use-ogrinfo-to-examine-spatial-data","children":[]}]},{"title":"Model Geografis","anchor":"geographic-models","children":[{"title":"Menentukan Model Geografis","anchor":"defining-a-geographic-model","children":[]},{"title":"Jalankan migrate","anchor":"run-migrate","children":[]}]},{"title":"Mengimpor Data Spasial","anchor":"importing-spatial-data","children":[{"title":"Antarmuka GDAL","anchor":"gdal-interface","children":[]},{"title":"LayerMapping","anchor":"layermapping","children":[]},{"title":"Coba ogrinspect","anchor":"try-ogrinspect","children":[]}]},{"title":"Spatial Queries","anchor":"spatial-queries","children":[{"title":"Pencarian Spasial","anchor":"spatial-lookups","children":[]},{"title":"Automatic Spatial Transformations","anchor":"automatic-spatial-transformations","children":[]},{"title":"Geometri Lazy","anchor":"lazy-geometries","children":[]},{"title":"Keterangan geografis","anchor":"geographic-annotations","children":[]}]},{"title":"Menaruh data anda di peta","anchor":"putting-your-data-on-the-map","children":[{"title":"Admin Geografis","anchor":"geographic-admin","children":[{"title":"Dasar","anchor":"basics","children":[]},{"title":"GISModelAdmin","anchor":"gismodeladmin","children":[]}]}]}],"breadcrumbs":[{"docname":"ref/index","title":"Acuan API","url":"/id/5.0/ref/"},{"docname":"ref/contrib/index","title":"Paket contrib","url":"/id/5.0/ref/contrib/"},{"docname":"ref/contrib/gis/index","title":"GeoDjango","url":"/id/5.0/ref/contrib/gis/"}],"prev":{"docname":"ref/contrib/gis/index","title":"GeoDjango","url":"/id/5.0/ref/contrib/gis/"},"next":{"docname":"ref/contrib/gis/install/index","title":"Pemasangan GeoDjango","url":"/id/5.0/ref/contrib/gis/install/"},"formats":{"html":"/id/5.0/ref/contrib/gis/tutorial/","markdown":"/id/5.0/ref/contrib/gis/tutorial.md","json":"/id/5.0/ref/contrib/gis/tutorial.json"},"source":"https://github.com/django/django/blob/stable/5.0.x/docs/ref/contrib/gis/tutorial.txt","official":"https://docs.djangoproject.com/id/5.0/ref/contrib/gis/tutorial/","inVersions":["6.1","6.0","5.2","5.1","5.0","4.2","4.1","4.0","3.2","3.1","3.0","2.2","2.1","2.0","1.11","1.10","1.9"],"inLocales":["en","zh-hans","fr","ja","id","it","pt-br","ko","es","el","pl"]}