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Fixed #19243 - Edited GeoDjango Tutorial for consistency and style.

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shepdl 2012-11-17 22:20:49 -08:00 committed by Tim Graham
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@ -5,28 +5,28 @@ GeoDjango Tutorial
Introduction
============
GeoDjango is an add-on for Django that turns it into a world-class geographic
Web framework. GeoDjango strives to make it as simple as possible to create
geographic Web applications, like location-based services. Some features
include:
GeoDjango is an included contrib module for Django that turns it into a
world-class geographic Web framework. GeoDjango strives to make it as simple
as possible to create geographic Web applications, like location-based services.
Its features include:
* Django model fields for `OGC`_ geometries.
* Extensions to Django's ORM for the querying and manipulation of spatial data.
* Extensions to Django's ORM for querying and manipulating spatial data.
* Loosely-coupled, high-level Python interfaces for GIS geometry operations and
data formats.
* Editing of geometry fields inside the admin.
* Editing geometry fields from 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.
This tutorial assumes familiarity with Django; thus, if you're brand new to
Django, please read through the :doc:`regular tutorial </intro/tutorial01>` to
familiarize yourself with Django first.
.. note::
GeoDjango has special prerequisites overwhat is required by Django --
GeoDjango has additional requirements beyond what Django requires --
please consult the :ref:`installation documentation <ref-gis-install>`
for more details.
This tutorial will guide you through the creation of a geographic Web
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. [#]_
@ -51,10 +51,10 @@ Create a Spatial Database
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>`:
First, create a spatial database for your project.
If you are using PostGIS, create the database from the :ref:`spatial database
template <spatialdb_template>`:
.. code-block:: bash
@ -62,9 +62,9 @@ create the database from a :ref:`spatial database template
.. 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:
This command must be issued by a database user with enough privileges to
create a database. To create a user with ``CREATE DATABASE`` privileges in
PostgreSQL, use the following commands:
.. code-block:: bash
@ -72,25 +72,24 @@ create the database from a :ref:`spatial database template
$ createuser --createdb geo
$ exit
Replace ``geo`` with the system login user name that will be
connecting to the database. For example, ``johndoe`` if that is the
system user that will be running GeoDjango.
Replace ``geo`` with your Postgres database user's username.
(In PostgreSQL, this user will also be an OS-level user.)
Users of SQLite and SpatiaLite should consult the instructions on how
If you are using SQLite and SpatiaLite, consult the instructions on how
to create a :ref:`SpatiaLite database <create_spatialite_db>`.
Create GeoDjango Project
Create a New Project
------------------------
Use the ``django-admin.py`` script like normal to create a ``geodjango``
project:
Use the standard ``django-admin.py`` script to create a project called
``geodjango``:
.. code-block:: bash
$ django-admin.py startproject geodjango
With the project initialized, now create a ``world`` Django application within
the ``geodjango`` project:
This will initialize a new project. Now, create a ``world`` Django application
within the ``geodjango`` project:
.. code-block:: bash
@ -101,7 +100,7 @@ Configure ``settings.py``
-------------------------
The ``geodjango`` project settings are stored in the ``geodjango/settings.py``
file. Edit the database connection settings appropriately::
file. Edit the database connection settings to match your setup::
DATABASES = {
'default': {
@ -113,7 +112,7 @@ file. Edit the database connection settings appropriately::
In addition, modify the :setting:`INSTALLED_APPS` setting to include
:mod:`django.contrib.admin`, :mod:`django.contrib.gis`,
and ``world`` (our newly created application)::
and ``world`` (your newly created application)::
INSTALLED_APPS = (
'django.contrib.auth',
@ -135,9 +134,9 @@ Geographic Data
World Borders
-------------
The world borders data is available in this `zip file`__. Create a data
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:
unzip. On GNU/Linux platforms, use the following commands:
.. code-block:: bash
@ -149,7 +148,7 @@ unzip. On GNU/Linux platforms the following commands should do it:
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
unzipped, the world borders dataset includes files with the following
extensions:
* ``.shp``: Holds the vector data for the world borders geometries.
@ -165,8 +164,8 @@ __ 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):
The GDAL ``ogrinfo`` utility allows examining the metadata of shapefiles or
other vector data sources:
.. code-block:: bash
@ -175,9 +174,9 @@ shapefiles (or other vector data sources):
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 such
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`` 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:
.. code-block:: bash
@ -208,14 +207,11 @@ and use the ``-so`` option to get only important summary information:
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.
(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.
Geographic Models
=================
@ -223,8 +219,8 @@ 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::
Now that you've examined your dataset using ``ogrinfo``, create a GeoDjango
model to represent this data::
from django.contrib.gis.db import models
@ -252,32 +248,30 @@ create a GeoDjango model to represent this data::
def __unicode__(self):
return self.name
Two important things to note:
Please note two important things:
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.
2. You must override the model's default manager with
:class:`~django.contrib.gis.db.models.GeoManager` 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.
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.
__ 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
After defining your model, you need to sync it with the database. First,
let's look at the SQL that will generate the table for the
``WorldBorder`` model::
$ python manage.py sqlall world
This management command should produce the following output:
This command should produce the following output:
.. code-block:: sql
@ -302,32 +296,28 @@ This management command should produce the following output:
CREATE INDEX "world_worldborder_mpoly_id" ON "world_worldborder" USING GIST ( "mpoly" GIST_GEOMETRY_OPS );
COMMIT;
If satisfied, you may then create this table in the database by running the
``syncdb`` management command::
If this looks correct, run ``syncdb`` to create this table in the database::
$ python manage.py syncdb
Creating table world_worldborder
Installing custom SQL for world.WorldBorder 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).
The ``syncdb`` command may also prompt you to create an admin user. Either
do so now, or later by running ``django-admin.py createsuperuser``.
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
This section will show you how to import the world borders
shapefile into the database via GeoDjango models using the
:ref:`ref-layermapping`.
There are many different ways to import data into a spatial database --
besides the tools included within GeoDjango, you may also use the following to
populate your spatial database:
besides the tools included within GeoDjango, you may also use the following:
* `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`_: A command-line utility included with GDAL that
can import many vector data formats into PostGIS, MySQL, and Oracle databases.
* `shp2pgsql`_: This utility included with PostGIS imports ESRI shapefiles into
PostGIS.
.. _ogr2ogr: http://www.gdal.org/ogr2ogr.html
.. _shp2pgsql: http://postgis.refractions.net/documentation/manual-1.5/ch04.html#shp2pgsql_usage
@ -337,10 +327,9 @@ populate your spatial database:
GDAL Interface
--------------
Earlier we used 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.
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.
First, invoke the Django shell:
@ -348,8 +337,8 @@ 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
If you downloaded the :ref:`worldborders` data earlier in the
tutorial, then you can determine its path using Python's built-in
``os`` module::
>>> import os
@ -357,7 +346,7 @@ tutorial, then we can determine the path using Python's built-in
>>> 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
Now, open the world borders shapefile using GeoDjango's
:class:`~django.contrib.gis.gdal.DataSource` interface::
>>> from django.contrib.gis.gdal import DataSource
@ -374,8 +363,7 @@ shapefiles are only allowed to have one layer::
>>> print(lyr)
TM_WORLD_BORDERS-0.3
You can see what the geometry type of the layer is and how many features it
contains::
You can see the layer's geometry type and how many features it contains::
>>> print(lyr.geom_type)
Polygon
@ -384,16 +372,16 @@ contains::
.. note::
Unfortunately the shapefile data format does not allow for greater
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.
many others, actually includes ``MultiPolygon`` geometries, not Polygons.
It's important to use a more general field type in models: a
GeoDjango ``MultiPolygonField`` will accept a ``Polygon`` geometry, but a
``PolygonField`` will not accept a ``MultiPolygon`` type geometry. This
is why the ``WorldBorder`` model defined above uses a ``MultiPolygonField``.
The :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
system associated with it. If it does, the ``srs`` attribute will return a
:class:`~django.contrib.gis.gdal.SpatialReference` object::
>>> srs = lyr.srs
@ -406,9 +394,9 @@ system associated with it -- if it does, the ``srs`` attribute will return a
>>> 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.
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:
@ -416,8 +404,8 @@ 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:
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']
@ -446,8 +434,7 @@ And individual features may be retrieved by their feature ID::
>>> print(feat.get('NAME'))
San Marino
Here the boundary geometry for San Marino is extracted and looking
exported to WKT and GeoJSON::
Boundary geometries may be exported as WKT and GeoJSON::
>>> geom = feat.geom
>>> print(geom.wkt)
@ -459,8 +446,9 @@ exported to WKT and GeoJSON::
``LayerMapping``
----------------
We're going to dive right in -- create a file called ``load.py`` inside the
``world`` application, and insert the following::
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
@ -492,20 +480,20 @@ We're going to dive right in -- create a file called ``load.py`` inside the
A few notes about what's going on:
* Each key in the ``world_mapping`` dictionary corresponds to a field in the
``WorldBorder`` model, and the value is the name of the shapefile field
``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 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.
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,
then the script will still work.
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.
* 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
@ -777,7 +763,7 @@ 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 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>`_.