Tutorial GeoDjango¶

Buat Basisdata Spasial¶

Typically no special setup is required, so you can create a database as you would for any other project. We provide some tips for selected databases:

• Memasang PostGIS
• Memasang SpatiaLite

Buat Proyek Baru¶

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

$ django-admin startproject geodjango

This will initialize a new project. Now, create a world Django application within the geodjango project:

$ cd geodjango
$ python manage.py startapp world

Konfigurasi settings.py¶

The geodjango project settings are stored in the geodjango/settings.py file. Edit the database connection settings to match your setup:

DATABASES = {
    'default': {
         'ENGINE': 'django.contrib.gis.db.backends.postgis',
         'NAME': 'geodjango',
         'USER': 'geo',
    },
}

In addition, modify the INSTALLED_APPS setting to include django.contrib.admin, django.contrib.gis, and world (your newly created application):

INSTALLED_APPS = [
    'django.contrib.admin',
    'django.contrib.auth',
    'django.contrib.contenttypes',
    'django.contrib.sessions',
    'django.contrib.messages',
    'django.contrib.staticfiles',
    'django.contrib.gis',
    'world',
]

Batasan Dunia¶

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:

$ mkdir world/data
$ cd world/data
$ wget http://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: Holds the vector data for the world borders geometries.
• .shx: Spatial index file for geometries stored in the .shp.
• .dbf: Database file for holding non-geometric attribute data (e.g., integer and character fields).
• .prj: Contains the spatial reference information for the geographic data stored in the shapefile.

Use ogrinfo to examine spatial data¶

The GDAL ogrinfo utility allows examining the metadata of shapefiles or other vector data sources:

$ 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
Geometry: Polygon
Feature Count: 246
Extent: (-180.000000, -90.000000) - (180.000000, 83.623596)
Layer SRS WKT:
GEOGCS["GCS_WGS_1984",
    DATUM["WGS_1984",
        SPHEROID["WGS_1984",6378137.0,298.257223563]],
    PRIMEM["Greenwich",0.0],
    UNIT["Degree",0.0174532925199433]]
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: Integer (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.

Menentukan Model Geografis¶

Now that you've examined your dataset using ogrinfo, create a GeoDjango model to represent this data:

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)
    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):              # __unicode__ on Python 2
        return self.name

Note that the models module is imported from 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¶

After defining your model, you need to sync it with the database. First, create a database migration:

$ python manage.py makemigrations
Migrations for 'world':
  world/migrations/0001_initial.py:
    - Create model WorldBorder

Let's look at the SQL that will generate the table for the WorldBorder model:

$ python manage.py sqlmigrate world 0001

Perintah ini harus menghasilkan keluaran berikut:

BEGIN;
--
-- Create model WorldBorder
--
CREATE TABLE "world_worldborder" (
    "id" serial NOT NULL PRIMARY KEY,
    "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

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

If you downloaded the Batasan Dunia data earlier in the tutorial, then you can determine its path using Python's built-in os module:

>>> import os
>>> import world
>>> world_shp = os.path.abspath(os.path.join(os.path.dirname(world.__file__),
...                             '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

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["GCS_WGS_1984",
    DATUM["WGS_1984",
        SPHEROID["WGS_1984",6378137.0,298.257223563]],
    PRIMEM["Greenwich",0.0],
    UNIT["Degree",0.0174532925199433]]
>>> srs.proj4 # PROJ.4 representation
'+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs '

This shapefile is in the popular WGS84 spatial reference system -- in other words, the data uses longitude, latitude pairs in units of degrees.

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']

The following code will let you examine the OGR types (e.g. integer or string) associated with each of the fields:

>>> [fld.__name__ for fld in lyr.field_types]
['OFTString', 'OFTString', 'OFTString', 'OFTInteger', 'OFTString', 'OFTInteger', 'OFTInteger', '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

Obyek Layer mungkin dipotong:

>>> lyr[0:2]
[<django.contrib.gis.gdal.feature.Feature object at 0x2f47690>, <django.contrib.gis.gdal.feature.Feature object at 0x2f47650>]

Dan fitur-fitur tersendiri dapat diambil berdasarkan ID fitur mereka:

>>> 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:

import os
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 = os.path.abspath(
    os.path.join(os.path.dirname(__file__), 'data', 'TM_WORLD_BORDERS-0.3.shp'),
)

def run(verbose=True):
    lm = LayerMapping(
        WorldBorder, world_shp, world_mapping,
        transform=False, encoding='iso-8859-1',
    )
    lm.save(strict=True, verbose=verbose)

Sedikit catatan mengenai apa yang terjadi:

• Each key in the world_mapping dictionary corresponds to a field in the WorldBorder model. The value is the name of the shapefile field that data will be loaded from.
• The key mpoly for the geometry field is MULTIPOLYGON, 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.
• The path to the shapefile is not absolute -- in other words, if you move the world application (with data subdirectory) to a different location, the script will still work.
• The transform keyword is set to False because the data in the shapefile does not need to be converted -- it's already in WGS84 (SRID=4326).
• The encoding keyword is set to the character encoding of the string values in the shapefile. This ensures that string values are read and saved correctly from their original encoding system.

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

$ python 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.

The general usage of the command goes as follows:

$ python 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.

For example, the following command nearly reproduces the WorldBorder model and mapping dictionary created above, automatically:

$ python 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=4326 menyetel SRID untuk bidang geografis
• The --mapping option tells ogrinspect to also generate a mapping dictionary for use with LayerMapping.
• The --multi option is specified so that the geographic field is a MultiPolygonField instead of just a PolygonField.

The command produces the following output, which may be copied directly into the models.py of a GeoDjango application:

# 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',
}

Pencarian Spasial¶

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

$ python manage.py shell

Sekarang, tentukan minat [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>]>

Here, you retrieved a QuerySet with only one model: the border of the United States (exactly what you would expect).

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 Point, GEOSGeometry
>>> 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>]>

City.objects.raw('SELECT id, name, asText(point) from myapp_city')

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.

Admin Geografis¶

GeoDjango extends Django's admin application with support for editing geometry fields.

from django.contrib.gis import admin
from .models import WorldBorder

admin.site.register(WorldBorder, admin.GeoModelAdmin)

from django.conf.urls import url, include
from django.contrib.gis import admin

urlpatterns = [
    url(r'^admin/', admin.site.urls),
]

$ python manage.py createsuperuser

$ python manage.py runserver

admin.site.register(WorldBorder, admin.OSMGeoAdmin)