test.TransactionTestCase.multi_db

TransactionTestCase.multi_db Django sets up a test database corresponding to every database that is defined in the DATABASES definition in your settings file. However, a big part of the time taken to run a Django TestCase is consumed by the call to flush that ensures that you have a clean database at the start of each test run. If you have multiple databases, multiple flushes are required (one for each database), which can be a time consuming activity – especially if your tests don’t need to

test.Response.client

client The test client that was used to make the request that resulted in the response.

gis.gdal.Layer.extent

extent Returns the spatial extent of this layer, as an Envelope object: >>> layer.extent.tuple (-104.609252, 29.763374, -95.23506, 38.971823)

utils.translation.pgettext_lazy()

pgettext_lazy(context, message) Same as the non-lazy versions above, but using lazy execution. See lazy translations documentation.

forms.Form.has_error()

Form.has_error(field, code=None) This method returns a boolean designating whether a field has an error with a specific error code. If code is None, it will return True if the field contains any errors at all. To check for non-field errors use NON_FIELD_ERRORS as the field parameter.

dispatch.Signal

class Signal(providing_args=list) [source] All signals are django.dispatch.Signal instances. The providing_args is a list of the names of arguments the signal will provide to listeners. This is purely documentational, however, as there is nothing that checks that the signal actually provides these arguments to its listeners. For example: import django.dispatch pizza_done = django.dispatch.Signal(providing_args=["toppings", "size"]) This declares a pizza_done signal that will provide receiv

gis.geoip.GeoIP.city()

GeoIP.city(query) Returns a dictionary of city information for the given query. Some of the values in the dictionary may be undefined (None).

gis.gdal.GDALRaster.scale

scale Pixel width and height used for georeferencing the raster, as a as a point object with x and y members. See geotransform for more information. >>> rst = GDALRaster({'width': 10, 'height': 20, 'srid': 4326}) >>> rst.scale [1.0, -1.0] >>> rst.scale.x = 2 >>> rst.scale [2.0, -1.0]

gis.gdal.SpatialReference.validate()

validate() Checks to see if the given spatial reference is valid, if not an exception will be raised.

utils.feedgenerator.SyndicationFeed.add_root_elements()

add_root_elements(handler) [source] Add elements in the root (i.e. feed/channel) element. Called from write().