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[1.5.X] Fixed #19243 - Edited GeoDjango Tutorial for consistency and style.
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@ -5,28 +5,28 @@ GeoDjango Tutorial
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Introduction
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============
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GeoDjango is an add-on for Django that turns it into a world-class geographic
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Web framework. GeoDjango strives to make it as simple as possible to create
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geographic Web applications, like location-based services. Some features
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include:
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GeoDjango is an included contrib module for Django that turns it into a
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world-class geographic Web framework. GeoDjango strives to make it as simple
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as possible to create geographic Web applications, like location-based services.
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Its features include:
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* Django model fields for `OGC`_ geometries.
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* Extensions to Django's ORM for the querying and manipulation of spatial data.
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* Extensions to Django's ORM for querying and manipulating spatial data.
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* Loosely-coupled, high-level Python interfaces for GIS geometry operations and
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data formats.
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* Editing of geometry fields inside the admin.
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* Editing geometry fields from the admin.
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This tutorial assumes a familiarity with Django; thus, if you're brand new to
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Django please read through the :doc:`regular tutorial </intro/tutorial01>` to
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introduce yourself with basic Django concepts.
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This tutorial assumes familiarity with Django; thus, if you're brand new to
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Django, please read through the :doc:`regular tutorial </intro/tutorial01>` to
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familiarize yourself with Django first.
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.. note::
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GeoDjango has special prerequisites overwhat is required by Django --
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GeoDjango has additional requirements beyond what Django requires --
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please consult the :ref:`installation documentation <ref-gis-install>`
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for more details.
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This tutorial will guide you through the creation of a geographic Web
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This tutorial will guide you through the creation of a geographic web
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application for viewing the `world borders`_. [#]_ Some of the code
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used in this tutorial is taken from and/or inspired by the `GeoDjango
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basic apps`_ project. [#]_
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@ -51,10 +51,10 @@ Create a Spatial Database
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MySQL and Oracle users can skip this section because spatial types
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are already built into the database.
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First, a spatial database needs to be created for our project. If using
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PostgreSQL and PostGIS, then the following commands will
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create the database from a :ref:`spatial database template
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<spatialdb_template>`:
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First, create a spatial database for your project.
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If you are using PostGIS, create the database from the :ref:`spatial database
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template <spatialdb_template>`:
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.. code-block:: bash
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@ -62,9 +62,9 @@ create the database from a :ref:`spatial database template
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.. note::
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This command must be issued by a database user that has permissions to
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create a database. Here is an example set of commands to create such
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a user:
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This command must be issued by a database user with enough privileges to
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create a database. To create a user with ``CREATE DATABASE`` privileges in
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PostgreSQL, use the following commands:
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.. code-block:: bash
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@ -72,25 +72,24 @@ create the database from a :ref:`spatial database template
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$ createuser --createdb geo
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$ exit
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Replace ``geo`` with the system login user name that will be
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connecting to the database. For example, ``johndoe`` if that is the
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system user that will be running GeoDjango.
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Replace ``geo`` with your Postgres database user's username.
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(In PostgreSQL, this user will also be an OS-level user.)
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Users of SQLite and SpatiaLite should consult the instructions on how
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If you are using SQLite and SpatiaLite, consult the instructions on how
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to create a :ref:`SpatiaLite database <create_spatialite_db>`.
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Create GeoDjango Project
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Create a New Project
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------------------------
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Use the ``django-admin.py`` script like normal to create a ``geodjango``
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project:
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Use the standard ``django-admin.py`` script to create a project called
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``geodjango``:
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.. code-block:: bash
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$ django-admin.py startproject geodjango
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With the project initialized, now create a ``world`` Django application within
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the ``geodjango`` project:
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This will initialize a new project. Now, create a ``world`` Django application
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within the ``geodjango`` project:
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.. code-block:: bash
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@ -101,7 +100,7 @@ Configure ``settings.py``
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-------------------------
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The ``geodjango`` project settings are stored in the ``geodjango/settings.py``
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file. Edit the database connection settings appropriately::
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file. Edit the database connection settings to match your setup::
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DATABASES = {
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'default': {
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@ -113,7 +112,7 @@ file. Edit the database connection settings appropriately::
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In addition, modify the :setting:`INSTALLED_APPS` setting to include
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:mod:`django.contrib.admin`, :mod:`django.contrib.gis`,
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and ``world`` (our newly created application)::
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and ``world`` (your newly created application)::
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INSTALLED_APPS = (
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'django.contrib.auth',
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@ -135,9 +134,9 @@ Geographic Data
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World Borders
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-------------
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The world borders data is available in this `zip file`__. Create a data
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The world borders data is available in this `zip file`__. Create a ``data``
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directory in the ``world`` application, download the world borders data, and
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unzip. On GNU/Linux platforms the following commands should do it:
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unzip. On GNU/Linux platforms, use the following commands:
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.. code-block:: bash
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@ -149,7 +148,7 @@ unzip. On GNU/Linux platforms the following commands should do it:
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The world borders ZIP file contains a set of data files collectively known as
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an `ESRI Shapefile`__, one of the most popular geospatial data formats. When
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unzipped the world borders data set includes files with the following
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unzipped, the world borders dataset includes files with the following
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extensions:
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* ``.shp``: Holds the vector data for the world borders geometries.
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@ -165,8 +164,8 @@ __ http://en.wikipedia.org/wiki/Shapefile
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Use ``ogrinfo`` to examine spatial data
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---------------------------------------
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The GDAL ``ogrinfo`` utility is excellent for examining metadata about
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shapefiles (or other vector data sources):
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The GDAL ``ogrinfo`` utility allows examining the metadata of shapefiles or
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other vector data sources:
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.. code-block:: bash
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@ -175,9 +174,9 @@ shapefiles (or other vector data sources):
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using driver `ESRI Shapefile' successful.
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1: TM_WORLD_BORDERS-0.3 (Polygon)
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Here ``ogrinfo`` is telling us that the shapefile has one layer, and that such
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layer contains polygon data. To find out more we'll specify the layer name
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and use the ``-so`` option to get only important summary information:
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``ogrinfo`` tells us that the shapefile has one layer, and that this
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layer contains polygon data. To find out more, we'll specify the layer name
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and use the ``-so`` option to get only the important summary information:
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.. code-block:: bash
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@ -208,14 +207,11 @@ and use the ``-so`` option to get only important summary information:
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LAT: Real (7.3)
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This detailed summary information tells us the number of features in the layer
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(246), the geographical extent, the spatial reference system ("SRS WKT"),
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as well as detailed information for each attribute field. For example,
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``FIPS: String (2.0)`` indicates that there's a ``FIPS`` character field
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with a maximum length of 2; similarly, ``LON: Real (8.3)`` is a floating-point
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field that holds a maximum of 8 digits up to three decimal places. Although
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this information may be found right on the `world borders`_ Web site, this
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shows you how to determine this information yourself when such metadata is not
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provided.
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(246), the geographic bounds of the data, the spatial reference system
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("SRS WKT"), as well as type information for each attribute field. For example,
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``FIPS: String (2.0)`` indicates that the ``FIPS`` character field has
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a maximum length of 2. Similarly, ``LON: Real (8.3)`` is a floating-point
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field that holds a maximum of 8 digits up to three decimal places.
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Geographic Models
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=================
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@ -223,8 +219,8 @@ Geographic Models
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Defining a Geographic Model
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---------------------------
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Now that we've examined our world borders data set using ``ogrinfo``, we can
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create a GeoDjango model to represent this data::
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Now that you've examined your dataset using ``ogrinfo``, create a GeoDjango
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model to represent this data::
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from django.contrib.gis.db import models
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@ -252,32 +248,30 @@ create a GeoDjango model to represent this data::
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def __unicode__(self):
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return self.name
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Two important things to note:
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Please note two important things:
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1. The ``models`` module is imported from :mod:`django.contrib.gis.db`.
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2. The model overrides its default manager with
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:class:`~django.contrib.gis.db.models.GeoManager`; this is *required*
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to perform spatial queries.
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2. You must override the model's default manager with
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:class:`~django.contrib.gis.db.models.GeoManager` to perform spatial queries.
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When declaring a geometry field on your model the default spatial reference
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system is WGS84 (meaning the `SRID`__ is 4326) -- in other words, the field
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coordinates are in longitude/latitude pairs in units of degrees. If you want
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the coordinate system to be different, then SRID of the geometry field may be
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customized by setting the ``srid`` with an integer corresponding to the
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coordinate system of your choice.
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The default spatial reference system for geometry fields is WGS84 (meaning
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the `SRID`__ is 4326) -- in other words, the field coordinates are in
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longitude, latitude pairs in units of degrees. To use a different
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coordinate system, set the SRID of the geometry field with the ``srid``
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argument. Use an integer representing the coordinate system's EPSG code.
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__ http://en.wikipedia.org/wiki/SRID
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Run ``syncdb``
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--------------
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After you've defined your model, it needs to be synced with the spatial
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database. First, let's look at the SQL that will generate the table for the
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After defining your model, you need to sync it with the database. First,
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let's look at the SQL that will generate the table for the
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``WorldBorder`` model::
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$ python manage.py sqlall world
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This management command should produce the following output:
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This command should produce the following output:
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.. code-block:: sql
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@ -302,32 +296,28 @@ This management command should produce the following output:
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CREATE INDEX "world_worldborder_mpoly_id" ON "world_worldborder" USING GIST ( "mpoly" GIST_GEOMETRY_OPS );
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COMMIT;
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If satisfied, you may then create this table in the database by running the
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``syncdb`` management command::
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If this looks correct, run ``syncdb`` to create this table in the database::
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$ python manage.py syncdb
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Creating table world_worldborder
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Installing custom SQL for world.WorldBorder model
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The ``syncdb`` command may also prompt you to create an admin user; go ahead
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and do so (not required now, may be done at any point in the future using the
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``createsuperuser`` management command).
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The ``syncdb`` command may also prompt you to create an admin user. Either
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do so now, or later by running ``django-admin.py createsuperuser``.
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Importing Spatial Data
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======================
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This section will show you how to take the data from the world borders
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shapefile and import it into GeoDjango models using the
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This section will show you how to import the world borders
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shapefile into the database via GeoDjango models using the
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:ref:`ref-layermapping`.
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There are many different ways to import data in to a spatial database --
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besides the tools included within GeoDjango, you may also use the following to
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populate your spatial database:
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There are many different ways to import data into a spatial database --
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besides the tools included within GeoDjango, you may also use the following:
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* `ogr2ogr`_: Command-line utility, included with GDAL, that
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supports loading a multitude of vector data formats into
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the PostGIS, MySQL, and Oracle spatial databases.
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* `shp2pgsql`_: This utility is included with PostGIS and only supports
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ESRI shapefiles.
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* `ogr2ogr`_: A command-line utility included with GDAL that
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can import many vector data formats into PostGIS, MySQL, and Oracle databases.
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* `shp2pgsql`_: This utility included with PostGIS imports ESRI shapefiles into
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PostGIS.
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.. _ogr2ogr: http://www.gdal.org/ogr2ogr.html
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.. _shp2pgsql: http://postgis.refractions.net/documentation/manual-1.5/ch04.html#shp2pgsql_usage
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@ -337,10 +327,9 @@ populate your spatial database:
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GDAL Interface
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--------------
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Earlier we used the ``ogrinfo`` to explore the contents of the world borders
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shapefile. Included within GeoDjango is an interface to GDAL's powerful OGR
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library -- in other words, you'll be able explore all the vector data sources
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that OGR supports via a Pythonic API.
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Earlier, you used ``ogrinfo`` to examine the contents of the world borders
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shapefile. GeoDjango also includes a Pythonic interface to GDAL's powerful OGR
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library that can work with all the vector data sources that OGR supports.
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First, invoke the Django shell:
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@ -348,8 +337,8 @@ First, invoke the Django shell:
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$ python manage.py shell
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If the :ref:`worldborders` data was downloaded like earlier in the
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tutorial, then we can determine the path using Python's built-in
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If you downloaded the :ref:`worldborders` data earlier in the
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tutorial, then you can determine its path using Python's built-in
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``os`` module::
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>>> import os
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@ -357,7 +346,7 @@ tutorial, then we can determine the path using Python's built-in
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>>> world_shp = os.path.abspath(os.path.join(os.path.dirname(world.__file__),
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... 'data/TM_WORLD_BORDERS-0.3.shp'))
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Now, the world borders shapefile may be opened using GeoDjango's
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Now, open the world borders shapefile using GeoDjango's
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:class:`~django.contrib.gis.gdal.DataSource` interface::
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>>> from django.contrib.gis.gdal import DataSource
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@ -374,8 +363,7 @@ shapefiles are only allowed to have one layer::
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>>> print(lyr)
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TM_WORLD_BORDERS-0.3
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You can see what the geometry type of the layer is and how many features it
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contains::
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You can see the layer's geometry type and how many features it contains::
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>>> print(lyr.geom_type)
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Polygon
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@ -384,16 +372,16 @@ contains::
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.. note::
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Unfortunately the shapefile data format does not allow for greater
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Unfortunately, the shapefile data format does not allow for greater
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specificity with regards to geometry types. This shapefile, like
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many others, actually includes ``MultiPolygon`` geometries in its
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features. You need to watch out for this when creating your models
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as a GeoDjango ``PolygonField`` will not accept a ``MultiPolygon``
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type geometry -- thus a ``MultiPolygonField`` is used in our model's
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definition instead.
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many others, actually includes ``MultiPolygon`` geometries, not Polygons.
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It's important to use a more general field type in models: a
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GeoDjango ``MultiPolygonField`` will accept a ``Polygon`` geometry, but a
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``PolygonField`` will not accept a ``MultiPolygon`` type geometry. This
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is why the ``WorldBorder`` model defined above uses a ``MultiPolygonField``.
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The :class:`~django.contrib.gis.gdal.Layer` may also have a spatial reference
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system associated with it -- if it does, the ``srs`` attribute will return a
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system associated with it. If it does, the ``srs`` attribute will return a
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:class:`~django.contrib.gis.gdal.SpatialReference` object::
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>>> srs = lyr.srs
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@ -406,9 +394,9 @@ system associated with it -- if it does, the ``srs`` attribute will return a
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>>> srs.proj4 # PROJ.4 representation
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'+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs '
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Here we've noticed that the shapefile is in the popular WGS84 spatial reference
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system -- in other words, the data uses units of degrees longitude and
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latitude.
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This shapefile is in the popular WGS84 spatial reference
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system -- in other words, the data uses longitude, latitude pairs in
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units of degrees.
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In addition, shapefiles also support attribute fields that may contain
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additional data. Here are the fields on the World Borders layer:
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@ -416,8 +404,8 @@ additional data. Here are the fields on the World Borders layer:
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>>> print(lyr.fields)
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['FIPS', 'ISO2', 'ISO3', 'UN', 'NAME', 'AREA', 'POP2005', 'REGION', 'SUBREGION', 'LON', 'LAT']
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Here we are examining the OGR types (e.g., whether a field is an integer or
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a string) associated with each of the fields:
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The following code will let you examine the OGR types (e.g. integer or
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string) associated with each of the fields:
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>>> [fld.__name__ for fld in lyr.field_types]
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['OFTString', 'OFTString', 'OFTString', 'OFTInteger', 'OFTString', 'OFTInteger', 'OFTInteger', 'OFTInteger', 'OFTInteger', 'OFTReal', 'OFTReal']
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@ -446,8 +434,7 @@ And individual features may be retrieved by their feature ID::
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>>> print(feat.get('NAME'))
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San Marino
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Here the boundary geometry for San Marino is extracted and looking
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exported to WKT and GeoJSON::
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Boundary geometries may be exported as WKT and GeoJSON::
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>>> geom = feat.geom
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>>> print(geom.wkt)
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@ -459,8 +446,9 @@ exported to WKT and GeoJSON::
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``LayerMapping``
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----------------
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We're going to dive right in -- create a file called ``load.py`` inside the
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``world`` application, and insert the following::
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To import the data, use a LayerMapping in a Python script.
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Create a file called ``load.py`` inside the ``world`` application,
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with the following code::
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import os
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from django.contrib.gis.utils import LayerMapping
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@ -492,20 +480,20 @@ We're going to dive right in -- create a file called ``load.py`` inside the
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A few notes about what's going on:
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* Each key in the ``world_mapping`` dictionary corresponds to a field in the
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``WorldBorder`` model, and the value is the name of the shapefile field
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``WorldBorder`` model. The value is the name of the shapefile field
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that data will be loaded from.
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* The key ``mpoly`` for the geometry field is ``MULTIPOLYGON``, the
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geometry type we wish to import as. Even if simple polygons are encountered
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in the shapefile they will automatically be converted into collections prior
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to insertion into the database.
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geometry type GeoDjango will import the field as. Even simple polygons in
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the shapefile will automatically be converted into collections prior to
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insertion into the database.
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* The path to the shapefile is not absolute -- in other words, if you move the
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``world`` application (with ``data`` subdirectory) to a different location,
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then the script will still work.
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the script will still work.
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* The ``transform`` keyword is set to ``False`` because the data in the
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shapefile does not need to be converted -- it's already in WGS84 (SRID=4326).
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* The ``encoding`` keyword is set to the character encoding of string values in
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the shapefile. This ensures that string values are read and saved correctly
|
||||
from their original encoding system.
|
||||
* 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:
|
||||
|
||||
|
@ -513,8 +501,8 @@ 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::
|
||||
Next, import the ``load`` module, call the ``run`` routine, and watch
|
||||
``LayerMapping`` do the work::
|
||||
|
||||
>>> from world import load
|
||||
>>> load.run()
|
||||
|
@ -536,7 +524,7 @@ 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
|
||||
``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.
|
||||
|
||||
|
@ -600,9 +588,9 @@ 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:
|
||||
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:
|
||||
|
||||
.. code-block:: bash
|
||||
|
||||
|
@ -613,8 +601,8 @@ 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
|
||||
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). [#]_ Import the ``WorldBorder`` model, and perform
|
||||
a ``contains`` lookup using the ``pnt_wkt`` as the parameter::
|
||||
|
||||
|
@ -623,11 +611,13 @@ a ``contains`` lookup using the ``pnt_wkt`` as the parameter::
|
|||
>>> qs
|
||||
[<WorldBorder: 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 ``WorldBorder`` instance for San Marino instead of a queryset::
|
||||
Here, you retrieved a ``GeoQuerySet`` with only one model: the border of
|
||||
the United States (exactly what you would expect).
|
||||
|
||||
Similarly, you may also use a :ref:`GEOS geometry object <ref-geos>`.
|
||||
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)
|
||||
|
@ -635,16 +625,16 @@ only the ``WorldBorder`` instance for San Marino instead of a queryset::
|
|||
>>> sm
|
||||
<WorldBorder: San Marino>
|
||||
|
||||
The ``contains`` and ``intersects`` lookups are just a subset of what's
|
||||
available -- the :ref:`ref-gis-db-api` documentation has more.
|
||||
The ``contains`` and ``intersects`` lookups are just a subset of the
|
||||
available queries -- the :ref:`ref-gis-db-api` documentation has more.
|
||||
|
||||
Automatic Spatial Transformations
|
||||
---------------------------------
|
||||
When querying the spatial database GeoDjango automatically transforms
|
||||
When doing spatial queries, 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`__,
|
||||
example, coordinates will be expressed in `EPSG SRID 32140`__,
|
||||
a coordinate system specific to south Texas **only** and in units of
|
||||
**meters** and not degrees::
|
||||
**meters**, not degrees::
|
||||
|
||||
>>> from django.contrib.gis.geos import Point, GEOSGeometry
|
||||
>>> pnt = Point(954158.1, 4215137.1, srid=32140)
|
||||
|
@ -654,7 +644,7 @@ 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
|
||||
GeoDjango's ORM will automatically wrap geometry values
|
||||
in transformation SQL, allowing the developer to work at a higher level
|
||||
of abstraction::
|
||||
|
||||
|
@ -675,7 +665,7 @@ __ http://spatialreference.org/ref/epsg/32140/
|
|||
|
||||
When using :doc:`raw queries </topics/db/sql>`, you should generally wrap
|
||||
your geometry fields with the ``asText()`` SQL function (or ``ST_AsText``
|
||||
for PostGIS) so as the field value will be recognized by GEOS::
|
||||
for PostGIS) so that the field value will be recognized by GEOS::
|
||||
|
||||
City.objects.raw('SELECT id, name, asText(point) from myapp_city')
|
||||
|
||||
|
@ -684,8 +674,8 @@ __ 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
|
||||
GeoDjango loads geometries in a standardized textual representation. When the
|
||||
geometry field is first accessed, GeoDjango creates a `GEOS geometry object
|
||||
<ref-geos>`, exposing powerful functionality, such as serialization properties
|
||||
for popular geospatial formats::
|
||||
|
||||
|
@ -715,14 +705,11 @@ the GEOS library::
|
|||
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.
|
||||
with support for editing geometry fields.
|
||||
|
||||
Basics
|
||||
^^^^^^
|
||||
|
@ -730,16 +717,15 @@ 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::
|
||||
Let's dive right in. Create a file called ``admin.py`` inside the
|
||||
``world`` application with the following code::
|
||||
|
||||
from django.contrib.gis import admin
|
||||
from models import WorldBorder
|
||||
|
||||
admin.site.register(WorldBorder, admin.GeoModelAdmin)
|
||||
|
||||
Next, edit your ``urls.py`` in the ``geodjango`` application folder to look
|
||||
as follows::
|
||||
Next, edit your ``urls.py`` in the ``geodjango`` application folder as follows::
|
||||
|
||||
from django.conf.urls import patterns, url, include
|
||||
from django.contrib.gis import admin
|
||||
|
@ -775,9 +761,9 @@ 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 `OSGeo`_).
|
||||
(which uses the `Vector Map Level 0`_ WMS dataset hosted at `OSGeo`_).
|
||||
|
||||
First, there are some important requirements and limitations:
|
||||
First, there are some important requirements:
|
||||
|
||||
* :class:`~django.contrib.gis.admin.OSMGeoAdmin` requires that the
|
||||
:ref:`spherical mercator projection be added <addgoogleprojection>`
|
||||
|
@ -785,14 +771,19 @@ First, there are some important requirements and limitations:
|
|||
* 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``
|
||||
If you meet these requirements, then just substitute the ``OSMGeoAdmin``
|
||||
option class in your ``admin.py`` file::
|
||||
|
||||
admin.site.register(WorldBorder, 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.opengeospatial.org/standards/sfs>`_.
|
||||
.. [#] Special thanks to Bjørn Sandvik of `thematicmapping.org
|
||||
<http://thematicmapping.org>`_ for providing and maintaining this
|
||||
dataset.
|
||||
.. [#] GeoDjango basic apps was written by Dane Springmeyer, Josh Livni, and
|
||||
Christopher Schmidt.
|
||||
.. [#] This point is the `University of Houston Law Center
|
||||
<http://www.law.uh.edu/>`_.
|
||||
.. [#] Open Geospatial Consortium, Inc., `OpenGIS Simple Feature Specification
|
||||
For SQL <http://www.opengeospatial.org/standards/sfs>`_.
|
||||
|
|
Loading…
Reference in New Issue