示例#1
0
    def get_queryset(self, feature_type: FeatureType) -> QuerySet:
        """Generate the queryset for the specific feature type.

        This method can be overwritten in subclasses to define the returned data.
        However, consider overwriting :meth:`compile_query` instead of simple data.
        """
        queryset = feature_type.get_queryset()

        # Apply filters
        compiler = self.compile_query(feature_type, using=queryset.db)

        if self.value_reference is not None:
            if feature_type.resolve_element(
                    self.value_reference.xpath) is None:
                raise InvalidParameterValue(
                    "valueReference",
                    f"Field '{self.value_reference.xpath}' does not exist.",
                )

            # For GetPropertyValue, adjust the query so only that value is requested.
            # This makes sure XPath attribute selectors are already handled by the
            # database query, instead of being a presentation-layer handling.
            field = compiler.add_value_reference(self.value_reference)
            queryset = compiler.filter_queryset(queryset,
                                                feature_type=feature_type)
            return queryset.values("pk", member=field)
        else:
            return compiler.filter_queryset(queryset,
                                            feature_type=feature_type)
示例#2
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 def decorate_queryset(cls, feature_type: FeatureType, queryset, output_crs,
                       **params):
     """Update the queryset to let the database render the GML output."""
     value_reference = params["valueReference"]
     match = feature_type.resolve_element(value_reference.xpath)
     if match.child.is_geometry:
         # Add 'gml_member' to point to the pre-rendered GML version.
         return queryset.values(
             "pk",
             gml_member=AsGML(get_db_geometry_target(match, output_crs)))
     else:
         return queryset
示例#3
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 def decorate_queryset(self, feature_type: FeatureType, queryset,
                       output_crs, **params):
     """Update the queryset to let the database render the GML output.
     This is far more efficient then GeoDjango's logic, which performs a
     C-API call for every single coordinate of a geometry.
     """
     queryset = super().decorate_queryset(feature_type, queryset,
                                          output_crs, **params)
     # If desired, the entire FeatureCollection could be rendered
     # in PostgreSQL as well: https://postgis.net/docs/ST_AsGeoJSON.html
     match = feature_type.resolve_element(feature_type.geometry_field_name)
     return queryset.defer(feature_type.geometry_field_name).annotate(
         _as_db_geojson=AsGeoJSON(get_db_geometry_target(match, output_crs),
                                  precision=16))