Pengajaran Tambahan GeoDjango¶
Kata Pengantar¶
GeoDjango is an included contrib module for Django that turns it into a world-class geographic web framework. GeoDjango strives to make it as simple as possible to create geographic web applications, like location-based services. Its features include:
Bidang model Django untuk geometri OGC dan data raster.
Tambahan pada ORM Django untuk meminta dan merubah data spasial.
Hubungan-renggang, antarmuka tingkat-tinggi Python untuk geometri GIS dan tindakan-tindakan raster dan pengubahan data dalam bentuk-bentuk berbeda.
Mengubah bidang geometri dari admin.
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.
Catatan
GeoDjango has additional requirements beyond what Django requires -- please consult the installation documentation for more details.
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]
Catatan
Diolah melalui bagian pengajaran tambahan berurutan untuk petunjuk langkah-demi-langkah.
Pengaturan¶
Buat Basisdata Spasial¶
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:
Buat Proyek Baru¶
Gunakan tulisan django-admin standar untuk membuat sebuah proyek dipanggil geodjango:
$ django-admin startproject geodjango
...\> django-admin startproject geodjango
Ini akan memulai sebuah proyek baru. Sekarang, buat sebuah aplikasi Django world dalam proyek geodjango:
$ cd geodjango
$ python manage.py startapp world
...\> cd geodjango
...\> py manage.py startapp world
Konfigurasi settings.py¶
Pengaturan proyek geodjango disimpan dalam berkas geodjango/settings.py. Sunting pengaturan hubungan basisdata untuk mencocokkan pengaturan anda:
DATABASES = {
"default": {
"ENGINE": "django.contrib.gis.db.backends.postgis",
"NAME": "geodjango",
"USER": "geo",
},
}
Sebagai tambahan, rubah pengaturan INSTALLED_APPS untuk menyertakan django.contrib.admin, django.contrib.gis, dan world (aplikasi dibuat terbaru anda):
INSTALLED_APPS = [
"django.contrib.admin",
"django.contrib.auth",
"django.contrib.contenttypes",
"django.contrib.sessions",
"django.contrib.messages",
"django.contrib.staticfiles",
"django.contrib.gis",
"world",
]
Data Geografis¶
Batasan Dunia¶
The world borders data is available in this zip file. Create a data
directory in the world application, download the world borders data, and
unzip. On GNU/Linux platforms, use the following commands:
$ mkdir world/data
$ cd world/data
$ wget https://web.archive.org/web/20231220150759/https://thematicmapping.org/downloads/TM_WORLD_BORDERS-0.3.zip
$ unzip TM_WORLD_BORDERS-0.3.zip
$ cd ../..
...\> mkdir world\data
...\> cd world\data
...\> wget https://web.archive.org/web/20231220150759/https://thematicmapping.org/downloads/TM_WORLD_BORDERS-0.3.zip
...\> unzip TM_WORLD_BORDERS-0.3.zip
...\> cd ..\..
The world borders ZIP file contains a set of data files collectively known as an ESRI Shapefile, one of the most popular geospatial data formats. When unzipped, the world borders dataset includes files with the following extensions:
.shp: Menahan data vektor untuk geometri batasan dunia..shx: Berkas indeks spatial untuk geometri disimpan dalam.shp..dbf: Berkas basisdata untuk menampung data atribut bukan-geometri (misalnya, bidang integer dan karakter)..prj: Mengandung informasi acuan spasial untuk data geografis disimpan dalam shapefile.
Gunakan ogrinfo untuk menjalankan data spasial¶
Kegunaan ogrinfo GDAL mengizinkan mennguji metadata dari shapefile atau sumber data vektor:
$ ogrinfo world/data/TM_WORLD_BORDERS-0.3.shp
INFO: Open of `world/data/TM_WORLD_BORDERS-0.3.shp'
using driver `ESRI Shapefile' successful.
1: TM_WORLD_BORDERS-0.3 (Polygon)
...\> ogrinfo world\data\TM_WORLD_BORDERS-0.3.shp
INFO: Open of `world/data/TM_WORLD_BORDERS-0.3.shp'
using driver `ESRI Shapefile' successful.
1: TM_WORLD_BORDERS-0.3 (Polygon)
ogrinfo tells us that the shapefile has one layer, and that this
layer contains polygon data. To find out more, we'll specify the layer name
and use the -so option to get only the important summary information:
$ ogrinfo -so world/data/TM_WORLD_BORDERS-0.3.shp TM_WORLD_BORDERS-0.3
INFO: Open of `world/data/TM_WORLD_BORDERS-0.3.shp'
using driver `ESRI Shapefile' successful.
Layer name: TM_WORLD_BORDERS-0.3
Metadata:
DBF_DATE_LAST_UPDATE=2008-07-30
Geometry: Polygon
Feature Count: 246
Extent: (-180.000000, -90.000000) - (180.000000, 83.623596)
Layer SRS WKT:
GEOGCRS["WGS 84",
DATUM["World Geodetic System 1984",
ELLIPSOID["WGS 84",6378137,298.257223563,
LENGTHUNIT["metre",1]]],
PRIMEM["Greenwich",0,
ANGLEUNIT["degree",0.0174532925199433]],
CS[ellipsoidal,2],
AXIS["latitude",north,
ORDER[1],
ANGLEUNIT["degree",0.0174532925199433]],
AXIS["longitude",east,
ORDER[2],
ANGLEUNIT["degree",0.0174532925199433]],
ID["EPSG",4326]]
Data axis to CRS axis mapping: 2,1
FIPS: String (2.0)
ISO2: String (2.0)
ISO3: String (3.0)
UN: Integer (3.0)
NAME: String (50.0)
AREA: Integer (7.0)
POP2005: Integer64 (10.0)
REGION: Integer (3.0)
SUBREGION: Integer (3.0)
LON: Real (8.3)
LAT: Real (7.3)
...\> ogrinfo -so world\data\TM_WORLD_BORDERS-0.3.shp TM_WORLD_BORDERS-0.3
INFO: Open of `world/data/TM_WORLD_BORDERS-0.3.shp'
using driver `ESRI Shapefile' successful.
Layer name: TM_WORLD_BORDERS-0.3
Metadata:
DBF_DATE_LAST_UPDATE=2008-07-30
Geometry: Polygon
Feature Count: 246
Extent: (-180.000000, -90.000000) - (180.000000, 83.623596)
Layer SRS WKT:
GEOGCRS["WGS 84",
DATUM["World Geodetic System 1984",
ELLIPSOID["WGS 84",6378137,298.257223563,
LENGTHUNIT["metre",1]]],
PRIMEM["Greenwich",0,
ANGLEUNIT["degree",0.0174532925199433]],
CS[ellipsoidal,2],
AXIS["latitude",north,
ORDER[1],
ANGLEUNIT["degree",0.0174532925199433]],
AXIS["longitude",east,
ORDER[2],
ANGLEUNIT["degree",0.0174532925199433]],
ID["EPSG",4326]]
Data axis to CRS axis mapping: 2,1
FIPS: String (2.0)
ISO2: String (2.0)
ISO3: String (3.0)
UN: Integer (3.0)
NAME: String (50.0)
AREA: Integer (7.0)
POP2005: Integer64 (10.0)
REGION: Integer (3.0)
SUBREGION: Integer (3.0)
LON: Real (8.3)
LAT: Real (7.3)
This detailed summary information tells us the number of features in the layer
(246), the geographic bounds of the data, the spatial reference system
("SRS WKT"), as well as type information for each attribute field. For example,
FIPS: String (2.0) indicates that the FIPS character field has
a maximum length of 2. Similarly, LON: Real (8.3) is a floating-point
field that holds a maximum of 8 digits up to three decimal places.
Model Geografis¶
Menentukan Model Geografis¶
Sekarang anda telah mengujikan dataset anda menggunakan originfo, membuat sebuah model GeoDjango untuk mewakili data ini:
from django.contrib.gis.db import models
class WorldBorder(models.Model):
# Regular Django fields corresponding to the attributes in the
# world borders shapefile.
name = models.CharField(max_length=50)
area = models.IntegerField()
pop2005 = models.IntegerField("Population 2005")
fips = models.CharField("FIPS Code", max_length=2, null=True)
iso2 = models.CharField("2 Digit ISO", max_length=2)
iso3 = models.CharField("3 Digit ISO", max_length=3)
un = models.IntegerField("United Nations Code")
region = models.IntegerField("Region Code")
subregion = models.IntegerField("Sub-Region Code")
lon = models.FloatField()
lat = models.FloatField()
# GeoDjango-specific: a geometry field (MultiPolygonField)
mpoly = models.MultiPolygonField()
# Returns the string representation of the model.
def __str__(self):
return self.name
Catat bahwa modul models diimpor dari django.contrib.gis.db.
The default spatial reference system for geometry fields is WGS84 (meaning
the SRID is 4326) -- in other words, the field coordinates are in
longitude, latitude pairs in units of degrees. To use a different
coordinate system, set the SRID of the geometry field with the srid
argument. Use an integer representing the coordinate system's EPSG code.
Jalankan migrate¶
Setelah menentukan model anda, anda butuh mensinkronisasikan itu dengan basisdata. Pertama, buat sebuah perpindahan basisdata:
$ python manage.py makemigrations
Migrations for 'world':
world/migrations/0001_initial.py:
+ Create model WorldBorder
...\> py manage.py makemigrations
Migrations for 'world':
world/migrations/0001_initial.py:
+ Create model WorldBorder
Mari kita lihat pada SQL yang akan membangkitkan tabel untuk model WorldBorder:
$ python manage.py sqlmigrate world 0001
...\> py manage.py sqlmigrate world 0001
Perintah ini harus menghasilkan keluaran berikut:
BEGIN;
--
-- Create model WorldBorder
--
CREATE TABLE "world_worldborder" (
"id" bigint NOT NULL PRIMARY KEY GENERATED BY DEFAULT AS IDENTITY,
"name" varchar(50) NOT NULL,
"area" integer NOT NULL,
"pop2005" integer NOT NULL,
"fips" varchar(2) NOT NULL,
"iso2" varchar(2) NOT NULL,
"iso3" varchar(3) NOT NULL,
"un" integer NOT NULL,
"region" integer NOT NULL,
"subregion" integer NOT NULL,
"lon" double precision NOT NULL,
"lat" double precision NOT NULL
"mpoly" geometry(MULTIPOLYGON,4326) NOT NULL
)
;
CREATE INDEX "world_worldborder_mpoly_id" ON "world_worldborder" USING GIST ("mpoly");
COMMIT;
Jika ini terlihat benar, jalankan migrate untuk membuat tabel ini dalam basisdata:
$ python manage.py migrate
Operations to perform:
Apply all migrations: admin, auth, contenttypes, sessions, world
Running migrations:
...
Applying world.0001_initial... OK
...\> py manage.py migrate
Operations to perform:
Apply all migrations: admin, auth, contenttypes, sessions, world
Running migrations:
...
Applying world.0001_initial... OK
Mengimpor Data Spasial¶
This section will show you how to import the world borders shapefile into the database via GeoDjango models using the Kegunaan impor data LayerMapping.
Ada banyak cara berbeda utuk meng impor data kedalam basisdata spasial -- disamping alat-alat disertakan dalam GeoDjango, anda mungkin juga menggunakan berikut:
ogr2ogr: Sebuah kegunaan baris-perintah disertakan dengan GDAL yang dapat mengimpor banyak bentuk data vektor kedalam basisdata PostGIS, MySQL, dan Oracle.
shp2pgsql: Kegunaan ini disertakan dengan PostGIS impor ESRI shapefile ke dalam PostGIS.
Antarmuka GDAL¶
Earlier, you used ogrinfo to examine the contents of the world borders
shapefile. GeoDjango also includes a Pythonic interface to GDAL's powerful OGR
library that can work with all the vector data sources that OGR supports.
Pertama, minta cangkang Django:
$ python manage.py shell
...\> py manage.py shell
If you downloaded the Batasan Dunia data earlier in the tutorial, then
you can determine its path using Python's pathlib.Path:
>>> from pathlib import Path
>>> import world
>>> world_shp = Path(world.__file__).resolve().parent / "data" / "TM_WORLD_BORDERS-0.3.shp"
Now, open the world borders shapefile using GeoDjango's
DataSource interface:
>>> from django.contrib.gis.gdal import DataSource
>>> ds = DataSource(world_shp)
>>> print(ds)
/ ... /geodjango/world/data/TM_WORLD_BORDERS-0.3.shp (ESRI Shapefile)
Data source objects can have different layers of geospatial features; however, shapefiles are only allowed to have one layer:
>>> print(len(ds))
1
>>> lyr = ds[0]
>>> print(lyr)
TM_WORLD_BORDERS-0.3
You can see the layer's geometry type and how many features it contains:
>>> print(lyr.geom_type)
Polygon
>>> print(len(lyr))
246
Catatan
Unfortunately, the shapefile data format does not allow for greater
specificity with regards to geometry types. This shapefile, like many
others, actually includes MultiPolygon geometries, not Polygons. It's
important to use a more general field type in models: a GeoDjango
MultiPolygonField will accept a Polygon geometry, but a
PolygonField will not accept a MultiPolygon type geometry. This is
why the WorldBorder model defined above uses a MultiPolygonField.
The Layer may also have a spatial reference
system associated with it. If it does, the srs attribute will return a
SpatialReference object:
>>> srs = lyr.srs
>>> print(srs)
GEOGCS["WGS 84",
DATUM["WGS_1984",
SPHEROID["WGS 84",6378137,298.257223563,
AUTHORITY["EPSG","7030"]],
AUTHORITY["EPSG","6326"]],
PRIMEM["Greenwich",0,
AUTHORITY["EPSG","8901"]],
UNIT["degree",0.0174532925199433,
AUTHORITY["EPSG","9122"]],
AXIS["Latitude",NORTH],
AXIS["Longitude",EAST],
AUTHORITY["EPSG","4326"]]
>>> srs.proj # PROJ representation
'+proj=longlat +datum=WGS84 +no_defs'
Shapefile ini dalam sistem acuan spasial WGS84 yang terkenal -- dengan kata lain, data menggunakan pasangan garis, bujur dalam satuan derajat.
In addition, shapefiles also support attribute fields that may contain additional data. Here are the fields on the World Borders layer:
>>> print(lyr.fields)
['FIPS', 'ISO2', 'ISO3', 'UN', 'NAME', 'AREA', 'POP2005', 'REGION', 'SUBREGION', 'LON', 'LAT']
Kode berikut akan membiarkan anda menguji jenis-jenis OGR (misalnya integer atau string) berkaitan dengan masing-masing bidang:
>>> [fld.__name__ for fld in lyr.field_types]
['OFTString', 'OFTString', 'OFTString', 'OFTInteger', 'OFTString', 'OFTInteger', 'OFTInteger64', 'OFTInteger', 'OFTInteger', 'OFTReal', 'OFTReal']
You can iterate over each feature in the layer and extract information from
both the feature's geometry (accessed via the geom attribute) as well as
the feature's attribute fields (whose values are accessed via get()
method):
>>> for feat in lyr:
... print(feat.get("NAME"), feat.geom.num_points)
...
Guernsey 18
Jersey 26
South Georgia South Sandwich Islands 338
Taiwan 363
Layer objects may be sliced:
>>> lyr[0:2]
[<django.contrib.gis.gdal.feature.Feature object at 0x2f47690>, <django.contrib.gis.gdal.feature.Feature object at 0x2f47650>]
And individual features may be retrieved by their feature ID:
>>> feat = lyr[234]
>>> print(feat.get("NAME"))
San Marino
Boundary geometries may be exported as WKT and GeoJSON:
>>> geom = feat.geom
>>> print(geom.wkt)
POLYGON ((12.415798 43.957954,12.450554 ...
>>> print(geom.json)
{ "type": "Polygon", "coordinates": [ [ [ 12.415798, 43.957954 ], [ 12.450554, 43.979721 ], ...
LayerMapping¶
To import the data, use a LayerMapping in a Python script.
Create a file called load.py inside the world application,
with the following code:
from pathlib import Path
from django.contrib.gis.utils import LayerMapping
from .models import WorldBorder
world_mapping = {
"fips": "FIPS",
"iso2": "ISO2",
"iso3": "ISO3",
"un": "UN",
"name": "NAME",
"area": "AREA",
"pop2005": "POP2005",
"region": "REGION",
"subregion": "SUBREGION",
"lon": "LON",
"lat": "LAT",
"mpoly": "MULTIPOLYGON",
}
world_shp = Path(__file__).resolve().parent / "data" / "TM_WORLD_BORDERS-0.3.shp"
def run(verbose=True):
lm = LayerMapping(WorldBorder, world_shp, world_mapping, transform=False)
lm.save(strict=True, verbose=verbose)
Sedikit catatan mengenai apa yang terjadi:
Each key in the
world_mappingdictionary corresponds to a field in theWorldBordermodel. The value is the name of the shapefile field that data will be loaded from.The key
mpolyfor the geometry field isMULTIPOLYGON, the geometry type GeoDjango will import the field as. Even simple polygons in the shapefile will automatically be converted into collections prior to insertion into the database.Jalur pada shapefile tidak mutlak -- dengan kata lain, jika anda memindahkan apliaksi
world(dengan subdirektoridata) ke tempat berbeda, tulisan akan masih bekerja.Kata kunci
transformdisetel menjadiFalsekarena data dalam shapefile tidak butuh dirubah -- itu sudah dalam WGS84 (SRID=4326).
Afterward, invoke the Django shell from the geodjango project directory:
$ python manage.py shell
...\> py manage.py shell
Next, import the load module, call the run routine, and watch
LayerMapping do the work:
>>> from world import load
>>> load.run()
Coba ogrinspect¶
Now that you've seen how to define geographic models and import data with the
Kegunaan impor data LayerMapping, it's possible to further automate this
process with use of the ogrinspect management command. The
ogrinspect command introspects a GDAL-supported vector data source
(e.g., a shapefile) and generates a model definition and LayerMapping
dictionary automatically.
Penggunaan umum dari perintah sebagai berikut:
$ python manage.py ogrinspect [options] <data_source> <model_name> [options]
...\> py manage.py ogrinspect [options] <data_source> <model_name> [options]
data_source is the path to the GDAL-supported data source and
model_name is the name to use for the model. Command-line options may
be used to further define how the model is generated.
Sebagai contoh, perintah berikut hampir membuat kembali model WorldBorder dan dictionary pemetaan dibuat diatas, secara otomatis:
$ python manage.py ogrinspect world/data/TM_WORLD_BORDERS-0.3.shp WorldBorder \
--srid=4326 --mapping --multi
...\> py manage.py ogrinspect world\data\TM_WORLD_BORDERS-0.3.shp WorldBorder \
--srid=4326 --mapping --multi
Sedikit catatan tentang pilihan baris-perintah diberikan diatas:
Pilihan
--srid=4326menyetel SRID untuk bidang geografisPilihan
--mappingmemberitahuogrinspectuntuk juga membangkitkan sebuah pemetaan dictionary untuk digunakan dengan class:~django.contrib.gis.utils.LayerMapping.Pilihan
--multiditentukan sehingga bidang geografis adalah sebuahMultiPolygonFielddaripada hanyaPolygonField.
Perintah menghasilkan keluaran berikut, yang mungkin disalin langsung kedalam models.py dari aplikasi GeoDjango:
# This is an auto-generated Django model module created by ogrinspect.
from django.contrib.gis.db import models
class WorldBorder(models.Model):
fips = models.CharField(max_length=2)
iso2 = models.CharField(max_length=2)
iso3 = models.CharField(max_length=3)
un = models.IntegerField()
name = models.CharField(max_length=50)
area = models.IntegerField()
pop2005 = models.IntegerField()
region = models.IntegerField()
subregion = models.IntegerField()
lon = models.FloatField()
lat = models.FloatField()
geom = models.MultiPolygonField(srid=4326)
# Auto-generated `LayerMapping` dictionary for WorldBorder model
worldborders_mapping = {
"fips": "FIPS",
"iso2": "ISO2",
"iso3": "ISO3",
"un": "UN",
"name": "NAME",
"area": "AREA",
"pop2005": "POP2005",
"region": "REGION",
"subregion": "SUBREGION",
"lon": "LON",
"lat": "LAT",
"geom": "MULTIPOLYGON",
}
Spatial Queries¶
Pencarian Spasial¶
GeoDjango adds spatial lookups to the Django ORM. For example, you
can find the country in the WorldBorder table that contains
a particular point. First, fire up the management shell:
$ python manage.py shell
...\> py manage.py shell
Now, define a point of interest [3]:
>>> pnt_wkt = "POINT(-95.3385 29.7245)"
The pnt_wkt string represents the point at -95.3385 degrees longitude,
29.7245 degrees latitude. The geometry is in a format known as
Well Known Text (WKT), a standard issued by the Open Geospatial
Consortium (OGC). [4] Import the WorldBorder model, and perform
a contains lookup using the pnt_wkt as the parameter:
>>> from world.models import WorldBorder
>>> WorldBorder.objects.filter(mpoly__contains=pnt_wkt)
<QuerySet [<WorldBorder: United States>]>
Disini, anda mengambil sebuah QuerySet dengan hanya satu model: batasan dari Amerika Serikat (tepatnya apa anda ingin harapkan).
Similarly, you may also use a GEOS geometry object. Here, you can combine the intersects spatial
lookup with the get method to retrieve only the WorldBorder instance
for San Marino instead of a queryset:
>>> from django.contrib.gis.geos import Point
>>> pnt = Point(12.4604, 43.9420)
>>> WorldBorder.objects.get(mpoly__intersects=pnt)
<WorldBorder: San Marino>
The contains and intersects lookups are just a subset of the available
queries -- the API Basisdata GeoDjango documentation has more.
Automatic Spatial Transformations¶
When doing spatial queries, GeoDjango automatically transforms geometries if they're in a different coordinate system. In the following example, coordinates will be expressed in EPSG SRID 32140, a coordinate system specific to south Texas only and in units of meters, not degrees:
>>> from django.contrib.gis.geos import GEOSGeometry, Point
>>> pnt = Point(954158.1, 4215137.1, srid=32140)
Note that pnt may also be constructed with EWKT, an "extended" form of
WKT that includes the SRID:
>>> pnt = GEOSGeometry("SRID=32140;POINT(954158.1 4215137.1)")
GeoDjango's ORM will automatically wrap geometry values in transformation SQL, allowing the developer to work at a higher level of abstraction:
>>> qs = WorldBorder.objects.filter(mpoly__intersects=pnt)
>>> print(qs.query) # Generating the SQL
SELECT "world_worldborder"."id", "world_worldborder"."name", "world_worldborder"."area",
"world_worldborder"."pop2005", "world_worldborder"."fips", "world_worldborder"."iso2",
"world_worldborder"."iso3", "world_worldborder"."un", "world_worldborder"."region",
"world_worldborder"."subregion", "world_worldborder"."lon", "world_worldborder"."lat",
"world_worldborder"."mpoly" FROM "world_worldborder"
WHERE ST_Intersects("world_worldborder"."mpoly", ST_Transform(%s, 4326))
>>> qs # printing evaluates the queryset
<QuerySet [<WorldBorder: United States>]>
Permintaan mentah
When using raw queries, you must wrap your geometry fields so that the field value can be recognized by GEOS:
>>> from django.db import connection
>>> # or if you're querying a non-default database:
>>> from django.db import connections
>>> connection = connections["your_gis_db_alias"]
>>> City.objects.raw(
... "SELECT id, name, %s as point from myapp_city" % (connection.ops.select % "point")
... )
Anda harus hanya menggunakan permintaan mentah ketika anda mengetahui persis apa yang anda sedang lakukan.
Geometri Lazy¶
GeoDjango loads geometries in a standardized textual representation. When the
geometry field is first accessed, GeoDjango creates a
GEOSGeometry object, exposing powerful
functionality, such as serialization properties for popular geospatial
formats:
>>> sm = WorldBorder.objects.get(name="San Marino")
>>> sm.mpoly
<MultiPolygon object at 0x24c6798>
>>> sm.mpoly.wkt # WKT
MULTIPOLYGON (((12.4157980000000006 43.9579540000000009, 12.4505540000000003 43.9797209999999978, ...
>>> sm.mpoly.wkb # WKB (as Python binary buffer)
<read-only buffer for 0x1fe2c70, size -1, offset 0 at 0x2564c40>
>>> sm.mpoly.geojson # GeoJSON
'{ "type": "MultiPolygon", "coordinates": [ [ [ [ 12.415798, 43.957954 ], [ 12.450554, 43.979721 ], ...
This includes access to all of the advanced geometric operations provided by the GEOS library:
>>> pnt = Point(12.4604, 43.9420)
>>> sm.mpoly.contains(pnt)
True
>>> pnt.contains(sm.mpoly)
False
Keterangan geografis¶
GeoDjango also offers a set of geographic annotations to compute distances and several other operations (intersection, difference, etc.). See the Fungsi Basisdata Geografis documentation.
Menaruh data anda di peta¶
Admin Geografis¶
Django's admin application supports editing geometry fields.
Dasar¶
The Django admin allows users to create and modify geometries on a JavaScript slippy map (powered by OpenLayers).
Mari kita gali lebih dalam. Buat sebuah berkas disebut admin.py didalam aplikasi world dengan kode berikut:
from django.contrib.gis import admin
from .models import WorldBorder
admin.site.register(WorldBorder, admin.ModelAdmin)
Selanjutnya, sunting urls.py anda dalam pelipat aplikasi geodjango seperti berikut:
from django.contrib import admin
from django.urls import include, path
urlpatterns = [
path("admin/", admin.site.urls),
]
Buat pengguna admin:
$ python manage.py createsuperuser
...\> py manage.py createsuperuser
Selanjutnya, mulai peladen pengembangan Django:
$ python manage.py runserver
...\> py manage.py runserver
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.
GISModelAdmin¶
With the GISModelAdmin, GeoDjango uses an
OpenStreetMap layer in the admin.
This provides more context (including street and thoroughfare details) than
available with the ModelAdmin (which uses the
Vector Map Level 0 WMS dataset hosted at OSGeo).
The PROJ datum shifting files must be installed (see the PROJ installation instructions for more details).
Jika anda memenuhi persyaratan ini, gunakan kelas pilihan GISModelAdmin di berkas admin.py anda:
admin.site.register(WorldBorder, admin.GISModelAdmin)
Catatan kaki
