|Version 128 (modified by vrehak, 4 years ago) (diff)|
TOC(GeoDjangoBackground, GeoDjango, GeoDjangoInstall, GeoDjangoModelAPI, GeoDjangoDatabaseAPI, GEOSGeometry, GeoDjangoExtras)? The GIS branch intends to be a world-class geographic web framework. Our goal is to make it as easy as possible to build GIS web applications and harness the power of spatially enabled data.
- GeoDjango is featured in the October 'Open Sources' Column by contributer Dane Springmeyer in GeoConnexion International Magazine
- GeoDjango was merged to trunk on 5th August 2008!
- An IRC channel is available for discussion on all things GeoDjango -- join #geodjango on freenode.
- The project was featured at DjangoCon on Sept 6, 2008 (http://www.youtube.com/watch?v=zOaimbSe6n8)
- GeoDjango creator, Justin Bronn, was interviewed on Episode 32 of This Week in Django
- GeoDjango was featured in a presentation and tutorial session at O'Reilly's Where 2.0 Conference, May 12-14, 2008 in Burlingame, California.
- The project was presented at FOSS4G 2007 on September 25, 2007. Thanks again for your support!
Note: The documentation has been re-factored into several pages. See the table of contents on the right for a complete listing of topics. Other GeoDjango pages include:
- Background Information
- Installation Instructions
- Model API
- Database API
- GEOS Geometries (in progress).
- OGR Geometries (in progress).
- Extra Features (in progress).
The wiki documentation is woefully behind, please use the 1.0 documentation.
When in doubt, use help on the feature in question, as most [browser:django/branches/gis/django/contrib/gis GeoDjango modules] and routines have docstrings.
Note: In order to minimize confusion, please don't modify the official roadmap below. If you have a suggestion, place it in the suggestion section or ask your question in the FAQ. If your request is urgent, submit a ticket requesting your feature or bugfix (make sure to specify the component as 'GIS'). Thanks for your cooperation!
All pending features for 1.1 may be found on the GeoDjango 1.1 page.
Significant GeoDjango changesets are mentioned below:
- r8219: Merged the gis branch into trunk.
- r7980: Merged in newforms-admin changesets from trunk, added geographic support for the admin.
- r7641: Refactor of the GeoQuerySet; added many new features from the PostGIS API.
- r7482: Merged with queryset-refactor changes from trunk.
- r7104: Added support for distance queries on models using geodetic coordinate systems.
- r6886: Added support for distance queries.
- r6527: MySQL backend added.
- r6524: Oracle Spatial backend added.
- r6467: The GeoMixin was completely deprecated.
- r6108: Created the maps module, which includes rudimentary support for generating Google Maps.
- r5657: "Lazy-Geometry" support was added (courtesy of Robert Coup's excellent patch in #4322) -- deprecating most of the extra instance methods.
- r5529: Added utilities for importing vector data (e.g., SHP files) directly into GeoDjango models.
- The [source:django/branches/gis/django/contrib/gis/utils/LayerMapping.py LayerMapping] class will import vector data from GDAL-supported data sources. This is still 'beta', and requires installation of the GDAL library.
- r5397: Added a ctypes interface for GDAL/OGR in [source:django/branches/gis/django/contrib/gis/gdal django.contrib.gis.gdal].
- r5008: Added a ctypes interface for GEOS in [source:django/branches/gis/django/contrib/gis/gdal django.contrib.gis.geos].
- GEOSGeometry: Wraps GEOS geometries; all accessed geometry fields are returned as GEOSGeometry instances.
- r4851: Added PostGIS indexing capability.
- Client JS/Flash framework. The maps module will be added soon, support for the following APIs will be implemented, or is being considered
- django.contrib.gis.maps.openlayers: Similar plans are in place for a OpenLayers module, which is the open source web mapping framework. Well-tested, BSD-licensed, and includes multitudes of features; for example, OpenLayers supports WMS/WFS/tiles as well as Google, MS Virtual Earth, and Yahoo layers. See also ticket #5472.
- Yahoo! , MapQuest, and Mapstraction are all possibilities for API hooks.
- Mapping Framework (generating custom tiles, layers, labels, etc.)
- Mapnik is a modern C++ engine that was designed for use with Python and generates beautiful maps. However, documentation is lacking and installation is difficult. First to use AGG rendering.
- Mapserver is the leading open source map renderer. MapServer is well documented and has strong community support. Uses text-based configuration files, which may be difficult to set up. AGG rendering and dynamic loading of configuration files (e.g., from a string) has been added to version 5.0.
- WMS Server
- I'm not satisfied with any of the current WMS/WFS implementations. One implemented in Django would be desirable, e.g., django.contrib.gis.wms. Thoughts anyone? (OWSLib looks good, see below)
- PCL (Python Cartographic Library), now part of GIS Python, has done a lot of good work already. Let's apply the DRY principle. Strong opportunities for collaboration with regards to:
- Mapping framework
- WMS/WMF Framework -- OWSLib looks excellent for this (BSD licensed and has unit tests!)
- Database representation ideas
- GEOS support, Sean Gillies (of PCL) was the maintainer of the old SWIG bindings, and is working on ShapeLy, a GeoDjango-inspired GEOS ctypes interface.
- Jannis Leidel has already come up with a way to manipulate points in the admin interface, BSD licensed.
- Brian Beck has written a good foundation for geocoding and distance calculations, BSD licensed.
- Decide what to do about "invalid" shape files, for example, float SHP field with ' ' value.
- This is a really great addition to the django framework. A single wiki page seems hardly sufficient for such an undertaking. A public forum dedicated specifically to questions, comments, and discussion regarding geodjango, its use, architecture, and development would be of tremendous benefit.
- Place your questions here.
- Q: When will geodjango be merged into trunk?
- The branch was merged into trunk on August 5th, 2008 in r8219.
- Q: When dealing with points (say, degrees) from, do they need to be converted to be useful on the back-end data, assuming -that- data is in degrees? Is it enough to have the same datum and origin? (Reading the intro above is likely to answer the question.)
- My (JDunck) reading indicates yes. Given the same coordinate system (i.e. datum, origin, and axes), degrees are useful without conversion.
- Q: Can this implementation work with MySQL spatial-extensions. If not, it's planned?
No, unfortunately support is not planned.Support for MySQL was added as of r6527. The changes required for the Oracle backend made it relatively easy to implement one for MySQL. However, MySQL is limited to bounding-box queries only, and many advanced features (e.g., coordinate transformation, geometry_columns and spatial_ref_sys tables) are missing because of MySQL's implementation. Furthermore, MySQL's spatial indexes are limited to MyISAM tables, which are not transactional.
- Q: Is this going to be a WMS Server/WMS Client/Both? OWSLib is just a WMS Client from what I have seen (from ruckc)
- WMS Server first, client capability a possibility in certain situations (i.e. you want to cache data from another WMS server). Yes, OWSLib is a client, but it contains code for validating the correct parameters to send to a WMS server, thus it can be adapted into a Django view that validates whether the proper WMS parameters were given. Mapnik has an ogcserver module that can parse the correct parameters for WMS 1.1.1 and 1.3.0, however since it is licensed under the LGPL it cannot be easily incorporated into this branch (unlike OWSLib).
- Q: Per this discussion in django-developers, "I can do spatial queries if they are directly between two models with polygon fields but I can't seem to get at the spatial queries through foreign keys."
- Geographic queries require GeoManager, even if the model does not have a geographic field itself (in the case of a foreign key to a geo-field). The reply in the discussion gives detail into why.
- Q: Why are the OGRGeometry methods transform and transform_to separate?
- They are no longer separate, as transform now accepts CoordTransform and SpatialReference objects, as well as string WKT and integer SRID values (transform checks the input type and dispatches to the correct routine). The former reason for the separation was that each mapped to the separate OGR routines OGR_G_Transform and OGR_G_TransformTo. For better performance use CoordTransform objects when you will be performing the same transformation repeatedly.
Here is an example of how the model API currently works (assume this example is in geoapp/models.py):
from django.contrib.gis.db import models class District(models.Model): name = models.CharField(max_length=35) num = models.IntegerField() poly = models.PolygonField() objects = models.GeoManager() class School(models.Model): name = models.CharField(max_length=35) point = models.PointField() objects = models.GeoManager()
Notes: The GeoMixin syntax is no longer needed as of r6467. By default, a GiST index will be created for the School PointFields fields. This behavior can be turned off by using models.PointField(spatial_index=False).
Both manage.py commands sqlall and syncdb work on geographic models:
$ python manage.py sqlall geoapp
BEGIN; CREATE TABLE "geoapp_school" ( "id" serial NOT NULL PRIMARY KEY, "name" varchar(35) NOT NULL ) ; CREATE TABLE "geoapp_district" ( "id" serial NOT NULL PRIMARY KEY, "name" varchar(35) NOT NULL, "num" integer NOT NULL ) ; SELECT AddGeometryColumn('geoapp_school', 'point', 4326, 'POINT', 2); ALTER TABLE "geoapp_school" ALTER "point" SET NOT NULL; CREATE INDEX "geoapp_school_point_id" ON "geoapp_school" USING GIST ( "point" GIST_GEOMETRY_OPS ); SELECT AddGeometryColumn('geoapp_district', 'poly', 4326, 'POLYGON', 2); ALTER TABLE "geoapp_district" ALTER "poly" SET NOT NULL; CREATE INDEX "geoapp_district_poly_id" ON "geoapp_district" USING GIST ( "poly" GIST_GEOMETRY_OPS ); COMMIT;
$ python manage.py syncdb
Note: The geometry columns are created outside of the CREATE TABLE statements by the AddGeometryColumn. This is done according to the OpenGIS specfication.
- See Open GIS Consortium, Inc., OpenGIS Simple Feature Specification For SQL, Document 99-049 (May 5, 1999), at Ch. 2.3.8 (Geometry Values and Spatial Reference Systems, pg. 39).
After a geographic model has been created, the PostGIS additions to the API may be used. Geographic queries are done normally by using filter() and exclude() on geometry-enabled models using geographic lookup types (see the Database API for lookup types). In the following example, the bbcontains lookup type is used which is the same as the PostGIS && operator. It looks to see if the bounding box of the polygon contains the specific point. The next example uses the PostGIS Contains() function, which calls GEOS library to test if the polygon actually contains the specific point, not just the bounding box.
>>> from geoapp.models import District, School >>> qs1 = District.objects.filter(poly__bbcontains='POINT(-95.362293 29.756539)') >>> qs2 = District.objects.filter(poly__contains='POINT(-95.362293 29.756539)')
Both spatial queries and normal queries using filter() may be used in the same query. For example, the following query set will only show school districts that have 'Houston' in their name and contain the given point within their polygon boundary:
>>> qs = District.objects.filter(name__contains='Houston').filter(poly__contains='POINT(-95.362293 29.756539)')
In PostGIS versions 1.2.2 and above, Refractions introduced a feature called "inline index magic" that automatically combines the indexed bounding box queries with their more computationally expensive counterparts. Prior to this revision the following filter could be used to get the same performance benefits:
>>> qs = District.objects.filter(poly__bbcontains='POINT(-95.362293 29.756539)').filter(poly__contains='POINT(-95.362293 29.756539)')
Geographic fields on models are proxies to GEOS Geometry objects, allowing for many interesting possibilities:
>>> from django.contrib.gis.geos import fromstr >>> pnt = fromstr('POINT(-95.362293 29.756539)', srid=4326) >>> hisd = District.objects.get(name='Houston ISD') >>> hisd.poly.contains(pnt) True >>> hisd.poly.within(pnt) False