351 lines
15 KiB
Python
351 lines
15 KiB
Python
from itertools import izip
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from django.db.models.query import sql
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from django.db.models.fields.related import ForeignKey
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from django.contrib.gis.db.backend import SpatialBackend
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from django.contrib.gis.db.models.fields import GeometryField
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from django.contrib.gis.db.models.sql import aggregates as gis_aggregates_module
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from django.contrib.gis.db.models.sql.conversion import AreaField, DistanceField, GeomField
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from django.contrib.gis.db.models.sql.where import GeoWhereNode
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from django.contrib.gis.measure import Area, Distance
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# Valid GIS query types.
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ALL_TERMS = sql.constants.QUERY_TERMS.copy()
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ALL_TERMS.update(SpatialBackend.gis_terms)
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TABLE_NAME = sql.constants.TABLE_NAME
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class GeoQuery(sql.Query):
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"""
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A single spatial SQL query.
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"""
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# Overridding the valid query terms.
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query_terms = ALL_TERMS
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aggregates_module = gis_aggregates_module
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#### Methods overridden from the base Query class ####
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def __init__(self, model, conn):
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super(GeoQuery, self).__init__(model, conn, where=GeoWhereNode)
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# The following attributes are customized for the GeoQuerySet.
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# The GeoWhereNode and SpatialBackend classes contain backend-specific
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# routines and functions.
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self.custom_select = {}
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self.transformed_srid = None
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self.extra_select_fields = {}
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if SpatialBackend.oracle:
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# Have to override this so that GeoQuery, instead of OracleQuery,
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# is returned when unpickling.
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def __reduce__(self):
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callable, args, data = super(GeoQuery, self).__reduce__()
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return (unpickle_geoquery, (), data)
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def clone(self, *args, **kwargs):
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obj = super(GeoQuery, self).clone(*args, **kwargs)
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# Customized selection dictionary and transformed srid flag have
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# to also be added to obj.
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obj.custom_select = self.custom_select.copy()
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obj.transformed_srid = self.transformed_srid
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obj.extra_select_fields = self.extra_select_fields.copy()
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return obj
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def get_columns(self, with_aliases=False):
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"""
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Return the list of columns to use in the select statement. If no
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columns have been specified, returns all columns relating to fields in
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the model.
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If 'with_aliases' is true, any column names that are duplicated
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(without the table names) are given unique aliases. This is needed in
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some cases to avoid ambiguitity with nested queries.
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This routine is overridden from Query to handle customized selection of
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geometry columns.
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"""
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qn = self.quote_name_unless_alias
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qn2 = self.connection.ops.quote_name
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result = ['(%s) AS %s' % (self.get_extra_select_format(alias) % col[0], qn2(alias))
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for alias, col in self.extra_select.iteritems()]
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aliases = set(self.extra_select.keys())
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if with_aliases:
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col_aliases = aliases.copy()
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else:
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col_aliases = set()
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if self.select:
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only_load = self.deferred_to_columns()
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# This loop customized for GeoQuery.
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for col, field in izip(self.select, self.select_fields):
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if isinstance(col, (list, tuple)):
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alias, column = col
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table = self.alias_map[alias][TABLE_NAME]
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if table in only_load and col not in only_load[table]:
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continue
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r = self.get_field_select(field, alias, column)
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if with_aliases:
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if col[1] in col_aliases:
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c_alias = 'Col%d' % len(col_aliases)
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result.append('%s AS %s' % (r, c_alias))
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aliases.add(c_alias)
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col_aliases.add(c_alias)
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else:
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result.append('%s AS %s' % (r, qn2(col[1])))
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aliases.add(r)
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col_aliases.add(col[1])
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else:
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result.append(r)
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aliases.add(r)
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col_aliases.add(col[1])
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else:
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result.append(col.as_sql(quote_func=qn))
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if hasattr(col, 'alias'):
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aliases.add(col.alias)
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col_aliases.add(col.alias)
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elif self.default_cols:
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cols, new_aliases = self.get_default_columns(with_aliases,
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col_aliases)
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result.extend(cols)
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aliases.update(new_aliases)
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result.extend([
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'%s%s' % (
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self.get_extra_select_format(alias) % aggregate.as_sql(quote_func=qn),
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alias is not None and ' AS %s' % alias or ''
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)
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for alias, aggregate in self.aggregate_select.items()
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])
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# This loop customized for GeoQuery.
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for (table, col), field in izip(self.related_select_cols, self.related_select_fields):
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r = self.get_field_select(field, table, col)
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if with_aliases and col in col_aliases:
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c_alias = 'Col%d' % len(col_aliases)
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result.append('%s AS %s' % (r, c_alias))
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aliases.add(c_alias)
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col_aliases.add(c_alias)
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else:
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result.append(r)
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aliases.add(r)
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col_aliases.add(col)
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self._select_aliases = aliases
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return result
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def get_default_columns(self, with_aliases=False, col_aliases=None,
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start_alias=None, opts=None, as_pairs=False):
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"""
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Computes the default columns for selecting every field in the base
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model. Will sometimes be called to pull in related models (e.g. via
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select_related), in which case "opts" and "start_alias" will be given
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to provide a starting point for the traversal.
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Returns a list of strings, quoted appropriately for use in SQL
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directly, as well as a set of aliases used in the select statement (if
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'as_pairs' is True, returns a list of (alias, col_name) pairs instead
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of strings as the first component and None as the second component).
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This routine is overridden from Query to handle customized selection of
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geometry columns.
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"""
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result = []
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if opts is None:
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opts = self.model._meta
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aliases = set()
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only_load = self.deferred_to_columns()
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proxied_model = opts.proxy and opts.proxy_for_model or 0
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if start_alias:
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seen = {None: start_alias}
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for field, model in opts.get_fields_with_model():
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if start_alias:
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try:
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alias = seen[model]
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except KeyError:
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if model is proxied_model:
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alias = start_alias
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else:
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link_field = opts.get_ancestor_link(model)
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alias = self.join((start_alias, model._meta.db_table,
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link_field.column, model._meta.pk.column))
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seen[model] = alias
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else:
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# If we're starting from the base model of the queryset, the
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# aliases will have already been set up in pre_sql_setup(), so
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# we can save time here.
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alias = self.included_inherited_models[model]
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table = self.alias_map[alias][TABLE_NAME]
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if table in only_load and field.column not in only_load[table]:
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continue
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if as_pairs:
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result.append((alias, field.column))
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aliases.add(alias)
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continue
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# This part of the function is customized for GeoQuery. We
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# see if there was any custom selection specified in the
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# dictionary, and set up the selection format appropriately.
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field_sel = self.get_field_select(field, alias)
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if with_aliases and field.column in col_aliases:
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c_alias = 'Col%d' % len(col_aliases)
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result.append('%s AS %s' % (field_sel, c_alias))
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col_aliases.add(c_alias)
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aliases.add(c_alias)
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else:
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r = field_sel
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result.append(r)
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aliases.add(r)
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if with_aliases:
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col_aliases.add(field.column)
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return result, aliases
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def resolve_columns(self, row, fields=()):
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"""
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This routine is necessary so that distances and geometries returned
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from extra selection SQL get resolved appropriately into Python
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objects.
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"""
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values = []
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aliases = self.extra_select.keys()
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# Have to set a starting row number offset that is used for
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# determining the correct starting row index -- needed for
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# doing pagination with Oracle.
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rn_offset = 0
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if SpatialBackend.oracle:
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if self.high_mark is not None or self.low_mark: rn_offset = 1
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index_start = rn_offset + len(aliases)
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# Converting any extra selection values (e.g., geometries and
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# distance objects added by GeoQuerySet methods).
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values = [self.convert_values(v, self.extra_select_fields.get(a, None))
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for v, a in izip(row[rn_offset:index_start], aliases)]
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if SpatialBackend.oracle or getattr(self, 'geo_values', False):
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# We resolve the rest of the columns if we're on Oracle or if
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# the `geo_values` attribute is defined.
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for value, field in izip(row[index_start:], fields):
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values.append(self.convert_values(value, field))
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else:
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values.extend(row[index_start:])
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return tuple(values)
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def convert_values(self, value, field):
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"""
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Using the same routines that Oracle does we can convert our
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extra selection objects into Geometry and Distance objects.
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TODO: Make converted objects 'lazy' for less overhead.
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"""
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if SpatialBackend.oracle:
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# Running through Oracle's first.
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value = super(GeoQuery, self).convert_values(value, field or GeomField())
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if isinstance(field, DistanceField):
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# Using the field's distance attribute, can instantiate
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# `Distance` with the right context.
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value = Distance(**{field.distance_att : value})
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elif isinstance(field, AreaField):
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value = Area(**{field.area_att : value})
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elif isinstance(field, (GeomField, GeometryField)) and value:
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value = SpatialBackend.Geometry(value)
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return value
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def resolve_aggregate(self, value, aggregate):
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"""
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Overridden from GeoQuery's normalize to handle the conversion of
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GeoAggregate objects.
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"""
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if isinstance(aggregate, self.aggregates_module.GeoAggregate):
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if aggregate.is_extent:
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return self.aggregates_module.convert_extent(value)
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else:
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return self.aggregates_module.convert_geom(value, aggregate.source)
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else:
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return super(GeoQuery, self).resolve_aggregate(value, aggregate)
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#### Routines unique to GeoQuery ####
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def get_extra_select_format(self, alias):
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sel_fmt = '%s'
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if alias in self.custom_select:
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sel_fmt = sel_fmt % self.custom_select[alias]
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return sel_fmt
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def get_field_select(self, field, alias=None, column=None):
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"""
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Returns the SELECT SQL string for the given field. Figures out
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if any custom selection SQL is needed for the column The `alias`
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keyword may be used to manually specify the database table where
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the column exists, if not in the model associated with this
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`GeoQuery`. Similarly, `column` may be used to specify the exact
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column name, rather than using the `column` attribute on `field`.
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"""
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sel_fmt = self.get_select_format(field)
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if field in self.custom_select:
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field_sel = sel_fmt % self.custom_select[field]
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else:
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field_sel = sel_fmt % self._field_column(field, alias, column)
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return field_sel
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def get_select_format(self, fld):
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"""
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Returns the selection format string, depending on the requirements
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of the spatial backend. For example, Oracle and MySQL require custom
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selection formats in order to retrieve geometries in OGC WKT. For all
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other fields a simple '%s' format string is returned.
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"""
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if SpatialBackend.select and hasattr(fld, 'geom_type'):
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# This allows operations to be done on fields in the SELECT,
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# overriding their values -- used by the Oracle and MySQL
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# spatial backends to get database values as WKT, and by the
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# `transform` method.
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sel_fmt = SpatialBackend.select
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# Because WKT doesn't contain spatial reference information,
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# the SRID is prefixed to the returned WKT to ensure that the
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# transformed geometries have an SRID different than that of the
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# field -- this is only used by `transform` for Oracle and
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# SpatiaLite backends.
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if self.transformed_srid and ( SpatialBackend.oracle or
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SpatialBackend.spatialite ):
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sel_fmt = "'SRID=%d;'||%s" % (self.transformed_srid, sel_fmt)
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else:
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sel_fmt = '%s'
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return sel_fmt
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# Private API utilities, subject to change.
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def _field_column(self, field, table_alias=None, column=None):
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"""
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Helper function that returns the database column for the given field.
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The table and column are returned (quoted) in the proper format, e.g.,
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`"geoapp_city"."point"`. If `table_alias` is not specified, the
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database table associated with the model of this `GeoQuery` will be
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used. If `column` is specified, it will be used instead of the value
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in `field.column`.
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"""
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if table_alias is None: table_alias = self.model._meta.db_table
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return "%s.%s" % (self.quote_name_unless_alias(table_alias),
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self.connection.ops.quote_name(column or field.column))
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def _geo_field(self, field_name=None):
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"""
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Returns the first Geometry field encountered; or specified via the
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`field_name` keyword. The `field_name` may be a string specifying
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the geometry field on this GeoQuery's model, or a lookup string
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to a geometry field via a ForeignKey relation.
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"""
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if field_name is None:
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# Incrementing until the first geographic field is found.
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for fld in self.model._meta.fields:
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if isinstance(fld, GeometryField): return fld
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return False
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else:
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# Otherwise, check by the given field name -- which may be
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# a lookup to a _related_ geographic field.
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return GeoWhereNode._check_geo_field(self.model._meta, field_name)
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if SpatialBackend.oracle:
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def unpickle_geoquery():
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"""
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Utility function, called by Python's unpickling machinery, that handles
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unpickling of GeoQuery subclasses of OracleQuery.
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"""
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return GeoQuery.__new__(GeoQuery)
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unpickle_geoquery.__safe_for_unpickling__ = True
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