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-==================
-GeoDjango Tutorial
-==================
-
-Introduction
-============
-
-GeoDjango is an add-on for Django that turns it into a world-class geographic
-Web framework.  GeoDjango strives to make at as simple as possible to create
-geographic Web applications, like location-based services.  Some features include:
-
-* Django model fields for `OGC`_ geometries.
-* Extensions to Django's ORM for the querying and manipulation of spatial data.
-* Loosely-coupled, high-level Python interfaces for GIS geometry operations and
-  data formats.
-* Editing of geometry fields inside the admin.
-
-This tutorial assumes a familiarity with Django; thus, if you're brand new to
-Django please read through the :doc:`regular tutorial </intro/tutorial01>` to introduce
-yourself with basic Django concepts.
-
-.. note::
-
-    GeoDjango has special prerequisites overwhat is required by Django --
-    please consult the :ref:`installation documentation <ref-gis-install>`
-    for more details.
-
-This tutorial will guide you through the creation of a geographic Web
-application for viewing the `world borders`_. [#]_ Some of the code
-used in this tutorial is taken from and/or inspired by the `GeoDjango
-basic apps`_ project. [#]_
-
-.. note::
-
-    Proceed through the tutorial sections sequentially for step-by-step
-    instructions.
-
-.. _OGC: http://www.opengeospatial.org/
-.. _world borders: http://thematicmapping.org/downloads/world_borders.php
-.. _GeoDjango basic apps: http://code.google.com/p/geodjango-basic-apps/
-
-Setting Up
-==========
-
-Create a Spatial Database
--------------------------
-
-.. note::
-
-    MySQL and Oracle users can skip this section because spatial types
-    are already built into the database.
-
-First, a spatial database needs to be created for our project.  If using
-PostgreSQL and PostGIS, then the following commands will
-create the database from a :ref:`spatial database template <spatialdb_template>`::
-
-    $ createdb -T template_postgis geodjango
-
-.. note::
-
-    This command must be issued by a database user that has permissions to
-    create a database.  Here is an example set of commands to create such
-    a user::
-
-        $ sudo su - postgres
-        $ createuser --createdb geo
-        $ exit
-
-    Replace ``geo`` to correspond to the system login user name will be
-    connecting to the database.  For example, ``johndoe`` if that is the
-    system user that will be running GeoDjango.
-
-Users of SQLite and SpatiaLite should consult the instructions on how
-to create a :ref:`SpatiaLite database <create_spatialite_db>`.
-
-Create GeoDjango Project
-------------------------
-
-Use the ``django-admin.py`` script like normal to create a ``geodjango`` project::
-
-    $ django-admin.py startproject geodjango
-
-With the project initialized, now create a ``world`` Django application within
-the ``geodjango`` project::
-
-    $ cd geodjango
-    $ python manage.py startapp world
-
-Configure ``settings.py``
--------------------------
-
-The ``geodjango`` project settings are stored in the ``settings.py`` file.  Edit
-the database connection settings appropriately::
-
-    DATABASES = {
-        'default': {
-             'ENGINE': 'django.contrib.gis.db.backends.postgis',
-             'NAME': 'geodjango',
-             'USER': 'geo',
-         }
-    }
-
-.. note::
-
-    These database settings are for Django 1.2 and above.
-
-In addition, modify the :setting:`INSTALLED_APPS` setting to include
-:mod:`django.contrib.admin`, :mod:`django.contrib.gis`,
-and ``world`` (our newly created application)::
-
-    INSTALLED_APPS = (
-        'django.contrib.auth',
-        'django.contrib.contenttypes',
-        'django.contrib.sessions',
-        'django.contrib.sites',
-        'django.contrib.admin',
-        'django.contrib.gis',
-        'world'
-    )
-
-Geographic Data
-===============
-
-.. _worldborders:
-
-World Borders
--------------
-
-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 the following commands should do it::
-
-    $ 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 data set 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.
-
-__ http://thematicmapping.org/downloads/TM_WORLD_BORDERS-0.3.zip
-__ http://en.wikipedia.org/wiki/Shapefile
-
-Use ``ogrinfo`` to examine spatial data
----------------------------------------
-
-The GDAL ``ogrinfo`` utility is excellent for examining metadata about
-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)
-
-Here ``ogrinfo`` is telling us that the shapefile has one layer, and that
-layer contains polygon data.  To find out more we'll specify the layer name
-and use the ``-so`` option to get only 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 geographical extent, the spatial reference system ("SRS WKT"),
-as well as detailed information for each attribute field.  For example,
-``FIPS: String (2.0)`` indicates that there's a ``FIPS`` character field
-with 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.  Although
-this information may be found right on the `world borders`_ Web site, this shows
-you how to determine this information yourself when such metadata is not
-provided.
-
-Geographic Models
-=================
-
-Defining a Geographic Model
----------------------------
-
-Now that we've examined our world borders data set using ``ogrinfo``, we can
-create a GeoDjango model to represent this data::
-
-    from django.contrib.gis.db import models
-
-    class WorldBorders(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), and
-        # overriding the default manager with a GeoManager instance.
-	mpoly = models.MultiPolygonField()
-	objects = models.GeoManager()
-
-        # So the model is pluralized correctly in the admin.
-        class Meta:
-            verbose_name_plural = "World Borders"
-
-        # Returns the string representation of the model.
-        def __unicode__(self):
-            return self.name
-
-Two important things to note:
-
-1. The ``models`` module is imported from :mod:`django.contrib.gis.db`.
-2. The model overrides its default manager with
-   :class:`~django.contrib.gis.db.models.GeoManager`; this is *required*
-   to perform spatial queries.
-
-When declaring a geometry field on your model the default spatial reference system
-is WGS84 (meaning the `SRID`__ is 4326) -- in other words, the field coordinates are in
-longitude/latitude pairs in units of degrees.  If you want the coordinate system to be
-different, then SRID of the geometry field may be customized by setting the ``srid``
-with an integer corresponding to the coordinate system of your choice.
-
-__ http://en.wikipedia.org/wiki/SRID
-
-Run ``syncdb``
---------------
-
-After you've defined your model, it needs to be synced with the spatial database.
-First, let's look at the SQL that will generate the table for the ``WorldBorders``
-model::
-
-    $ python manage.py sqlall world
-
-This management command should produce the following output::
-
-    BEGIN;
-    CREATE TABLE "world_worldborders" (
-        "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
-    )
-    ;
-    SELECT AddGeometryColumn('world_worldborders', 'mpoly', 4326, 'MULTIPOLYGON', 2);
-    ALTER TABLE "world_worldborders" ALTER "mpoly" SET NOT NULL;
-    CREATE INDEX "world_worldborders_mpoly_id" ON "world_worldborders" USING GIST ( "mpoly" GIST_GEOMETRY_OPS );
-    COMMIT;
-
-If satisfied, you may then create this table in the database by running the
-``syncdb`` management command::
-
-    $ python manage.py syncdb
-    Creating table world_worldborders
-    Installing custom SQL for world.WorldBorders model
-
-The ``syncdb`` command may also prompt you to create an admin user; go ahead and
-do so (not required now, may be done at any point in the future using the
-``createsuperuser`` management command).
-
-Importing Spatial Data
-======================
-
-This section will show you how to take the data from the world borders
-shapefile and import it into GeoDjango models using the :ref:`ref-layermapping`.
-There are many different different ways to import data in to a
-spatial database -- besides the tools included within GeoDjango, you
-may also use the following to populate your spatial database:
-
-* `ogr2ogr`_: Command-line utility, included with GDAL, that
-  supports loading a multitude of vector data formats into
-  the PostGIS, MySQL, and Oracle spatial databases.
-* `shp2pgsql`_: This utility is included with PostGIS and only supports
-  ESRI shapefiles.
-
-.. _ogr2ogr: http://www.gdal.org/ogr2ogr.html
-.. _shp2pgsql: http://postgis.refractions.net/documentation/manual-1.5/ch04.html#shp2pgsql_usage
-
-.. _gdalinterface:
-
-GDAL Interface
---------------
-
-Earlier we used the the ``ogrinfo`` to explore the contents of the world borders
-shapefile.  Included within GeoDjango is an interface to GDAL's powerful OGR
-library -- in other words, you'll be able explore all the vector data sources
-that OGR supports via a Pythonic API.
-
-First, invoke the Django shell::
-
-    $ python manage.py shell
-
-If the :ref:`worldborders` data was downloaded like earlier in the
-tutorial, then we can determine the path using Python's built-in
-``os`` module::
-
-    >>> import os
-    >>> from geodjango import world
-    >>> world_shp = os.path.abspath(os.path.join(os.path.dirname(world.__file__),
-    ...                             'data/TM_WORLD_BORDERS-0.3.shp'))
-
-Now, the world borders shapefile may be opened using GeoDjango's
-:class:`~django.contrib.gis.gdal.DataSource` interface::
-
-    >>> from django.contrib.gis.gdal import *
-    >>> 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 what the geometry type of the layer is and how many features it
-contains::
-
-    >>> print lyr.geom_type
-    Polygon
-    >>> print len(lyr)
-    246
-
-.. note::
-
-    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 in its
-    features.  You need to watch out for this when creating your models
-    as a GeoDjango ``PolygonField`` will not accept a ``MultiPolygon``
-    type geometry -- thus a ``MultiPolygonField`` is used in our model's
-    definition instead.
-
-The :class:`~django.contrib.gis.gdal.Layer` may also have a spatial reference
-system associated with it -- if it does, the ``srs`` attribute will return a
-:class:`~django.contrib.gis.gdal.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 '
-
-Here we've noticed that the shapefile is in the popular WGS84 spatial reference
-system -- in other words, the data uses units of degrees longitude and latitude.
-
-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']
-
-Here we are examining the OGR types (e.g., whether a field is an integer or
-a 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
-
-:class:`~django.contrib.gis.gdal.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
-
-Here the boundary geometry for San Marino is extracted and looking
-exported to 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``
-----------------
-
-We're going to dive right in -- create a file called ``load.py`` inside the
-``world`` application, and insert the following::
-
-    import os
-    from django.contrib.gis.utils import LayerMapping
-    from models import WorldBorders
-
-    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(WorldBorders, world_shp, world_mapping,
-                          transform=False, encoding='iso-8859-1')
-
-        lm.save(strict=True, verbose=verbose)
-
-A few notes about what's going on:
-
-* Each key in the ``world_mapping`` dictionary corresponds to a field in the
-  ``WorldBorders`` model, and 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 we wish to import as.  Even if simple polygons are encountered
-  in the shapefile they 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,
-  then 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 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()
-
-
-.. _ogrinspect-intro:
-
-Try ``ogrinspect``
-------------------
-Now that you've seen how to define geographic models and import data with the
-:ref:`ref-layermapping`, it's possible to further automate this process with
-use of the :djadmin:`ogrinspect` management command.  The :djadmin:`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]
-
-Where ``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 ``WorldBorders`` model
-and mapping dictionary created above, automatically::
-
-    $ python manage.py ogrinspect world/data/TM_WORLD_BORDERS-0.3.shp WorldBorders --srid=4326 --mapping --multi
-
-A few notes about the command-line options given above:
-
-* The ``--srid=4326`` option sets the SRID for the geographic field.
-* The ``--mapping`` option tells ``ogrinspect`` to also generate a
-  mapping dictionary for use with :class:`~django.contrib.gis.utils.LayerMapping`.
-* The ``--multi`` option is specified so that the geographic field is a
-  :class:`~django.contrib.gis.db.models.MultiPolygonField` instead of just a
-  :class:`~django.contrib.gis.db.models.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 WorldBorders(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)
-        objects = models.GeoManager()
-
-    # Auto-generated `LayerMapping` dictionary for WorldBorders 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
-===============
-
-Spatial Lookups
----------------
-GeoDjango extends the Django ORM and allows the use of spatial lookups.
-Let's do an example where we find the ``WorldBorder`` model that contains
-a point.  First, fire up the management shell::
-
-    $ python manage.py shell
-
-Now, define a point of interest [#]_::
-
-    >>> pnt_wkt = 'POINT(-95.3385 29.7245)'
-
-The ``pnt_wkt`` string represents the point at -95.3385 degrees longitude,
-and 29.7245 degrees latitude.  The geometry is in a format known as
-Well Known Text (WKT), an open standard issued by the Open Geospatial
-Consortium (OGC). [#]_  Import the ``WorldBorders`` model, and perform
-a ``contains`` lookup using the ``pnt_wkt`` as the parameter::
-
-    >>> from world.models import WorldBorders
-    >>> qs = WorldBorders.objects.filter(mpoly__contains=pnt_wkt)
-    >>> qs
-    [<WorldBorders: United States>]
-
-Here we retrieved a ``GeoQuerySet`` that has only one model: the one
-for the United States (which is what we would expect).  Similarly,
-a :ref:`GEOS geometry object <ref-geos>` may also be used -- here the ``intersects``
-spatial lookup is combined with the ``get`` method to retrieve
-only the ``WorldBorders`` instance for San Marino instead of a queryset::
-
-    >>> from django.contrib.gis.geos import Point
-    >>> pnt = Point(12.4604, 43.9420)
-    >>> sm = WorldBorders.objects.get(mpoly__intersects=pnt)
-    >>> sm
-    <WorldBorders: San Marino>
-
-The ``contains`` and ``intersects`` lookups are just a subset of what's
-available -- the :ref:`ref-gis-db-api` documentation has more.
-
-Automatic Spatial Transformations
----------------------------------
-When querying the spatial database GeoDjango automatically transforms
-geometries if they're in a different coordinate system.  In the following
-example, the coordinate will be expressed in terms of `EPSG SRID 32140`__,
-a coordinate system specific to south Texas **only** and in units of
-**meters** and not degrees::
-
-    >>> from django.contrib.gis.geos import *
-    >>> pnt = Point(954158.1, 4215137.1, srid=32140)
-
-Note that ``pnt`` may also constructed with EWKT, an "extended" form of
-WKT that includes the SRID::
-
-    >>> pnt = GEOSGeometry('SRID=32140;POINT(954158.1 4215137.1)')
-
-When using GeoDjango's ORM, it will automatically wrap geometry values
-in transformation SQL, allowing the developer to work at a higher level
-of abstraction::
-
-    >>> qs = WorldBorders.objects.filter(mpoly__intersects=pnt)
-    >>> qs.query.as_sql() # Generating the SQL
-    ('SELECT "world_worldborders"."id", "world_worldborders"."name", "world_worldborders"."area",
-    "world_worldborders"."pop2005", "world_worldborders"."fips", "world_worldborders"."iso2",
-    "world_worldborders"."iso3", "world_worldborders"."un", "world_worldborders"."region",
-    "world_worldborders"."subregion", "world_worldborders"."lon", "world_worldborders"."lat",
-    "world_worldborders"."mpoly" FROM "world_worldborders"
-    WHERE ST_Intersects("world_worldborders"."mpoly", ST_Transform(%s, 4326))',
-    (<django.contrib.gis.db.backend.postgis.adaptor.PostGISAdaptor object at 0x25641b0>,))
-    >>> qs # printing evaluates the queryset
-    [<WorldBorders: United States>]
-
-__ http://spatialreference.org/ref/epsg/32140/
-
-Lazy Geometries
----------------
-Geometries come to GeoDjango in a standardized textual representation.  Upon
-access of the geometry field, GeoDjango creates a `GEOS geometry object <ref-geos>`,
-exposing powerful functionality, such as serialization properties for
-popular geospatial formats::
-
-    >>> sm = WorldBorders.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 (requires GDAL)
-    '{ "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
-
-``GeoQuerySet`` Methods
------------------------
-
-
-Putting your data on the map
-============================
-
-Google
-------
-
-Geographic Admin
-----------------
-
-GeoDjango extends :doc:`Django's admin application </ref/contrib/admin/index>`
-to enable support for editing geometry fields.
-
-Basics
-^^^^^^
-
-GeoDjango also supplements the Django admin by allowing users to create
-and modify geometries on a JavaScript slippy map (powered by `OpenLayers`_).
-
-Let's dive in again -- create a file called ``admin.py`` inside the
-``world`` application, and insert the following::
-
-    from django.contrib.gis import admin
-    from models import WorldBorders
-
-    admin.site.register(WorldBorders, admin.GeoModelAdmin)
-
-Next, edit your ``urls.py`` in the ``geodjango`` project folder to look
-as follows::
-
-    from django.conf.urls.defaults import *
-    from django.contrib.gis import admin
-
-    admin.autodiscover()
-
-    urlpatterns = patterns('',
-        (r'^admin/', include(admin.site.urls)),
-    )
-
-Start up the Django development server::
-
-    $ python manage.py runserver
-
-Finally, browse to ``http://localhost:8000/admin/``, and log in with the admin
-user created after running ``syncdb``.  Browse to any of the ``WorldBorders``
-entries -- the borders may be edited by clicking on a polygon and dragging
-the vertexes to the desired position.
-
-.. _OpenLayers: http://openlayers.org/
-.. _Open Street Map: http://openstreetmap.org/
-.. _Vector Map Level 0: http://earth-info.nga.mil/publications/vmap0.html
-.. _Metacarta: http://metacarta.com
-
-.. _osmgeoadmin-intro:
-
-``OSMGeoAdmin``
-^^^^^^^^^^^^^^^
-
-With the :class:`~django.contrib.gis.admin.OSMGeoAdmin`, GeoDjango uses
-a `Open Street Map`_ layer in the admin.
-This provides more context (including street and thoroughfare details) than
-available with the :class:`~django.contrib.gis.admin.GeoModelAdmin`
-(which uses the `Vector Map Level 0`_ WMS data set hosted at `Metacarta`_).
-
-First, there are some important requirements and limitations:
-
-* :class:`~django.contrib.gis.admin.OSMGeoAdmin` requires that the
-  :ref:`spherical mercator projection be added <addgoogleprojection>`
-  to the to be added to the ``spatial_ref_sys`` table (PostGIS 1.3 and
-  below, only).
-* The PROJ.4 datum shifting files must be installed (see the
-  :ref:`PROJ.4 installation instructions <proj4>` for more details).
-
-If you meet these requirements, then just substitute in the ``OSMGeoAdmin``
-option class in your ``admin.py`` file::
-
-    admin.site.register(WorldBorders, admin.OSMGeoAdmin)
-
-.. rubric:: Footnotes
-
-.. [#] Special thanks to Bjørn Sandvik of `thematicmapping.org <http://thematicmapping.org>`_ for providing and maintaining this data set.
-.. [#] GeoDjango basic apps was written by Dane Springmeyer, Josh Livni, and Christopher Schmidt.
-.. [#] Here the point is for the `University of Houston Law Center <http://www.law.uh.edu/>`_ .
-.. [#] Open Geospatial Consortium, Inc., `OpenGIS Simple Feature Specification For SQL <http://www.opengis.org/docs/99-049.pdf>`_, Document 99-049.