mirror of https://github.com/django/django.git
Fixed #10182 -- Corrected realiasing and the process of evaluating values() for queries with aggregate clauses. This means that aggregate queries can now be used as subqueries (such as in an __in clause). Thanks to omat for the report.
This involves a slight change to the interaction of annotate() and values() clauses that specify a list of columns. See the docs for details. git-svn-id: http://code.djangoproject.com/svn/django/trunk@9888 bcc190cf-cafb-0310-a4f2-bffc1f526a37
This commit is contained in:
Russell Keith-Magee
parent
4bd24474c0
commit
542709d0d1
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@ -46,7 +46,7 @@ class Aggregate(object):
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# Validate that the backend has a fully supported, correct
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# implementation of this aggregate
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query.connection.ops.check_aggregate_support(aggregate)
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query.aggregate_select[alias] = aggregate
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query.aggregates[alias] = aggregate
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class Avg(Aggregate):
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name = 'Avg'
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@ -596,7 +596,7 @@ class QuerySet(object):
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obj = self._clone()
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obj._setup_aggregate_query()
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obj._setup_aggregate_query(kwargs.keys())
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# Add the aggregates to the query
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for (alias, aggregate_expr) in kwargs.items():
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@ -693,7 +693,7 @@ class QuerySet(object):
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"""
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pass
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def _setup_aggregate_query(self):
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def _setup_aggregate_query(self, aggregates):
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"""
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Prepare the query for computing a result that contains aggregate annotations.
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"""
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@ -773,6 +773,8 @@ class ValuesQuerySet(QuerySet):
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self.query.select = []
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self.query.add_fields(self.field_names, False)
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if self.aggregate_names is not None:
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self.query.set_aggregate_mask(self.aggregate_names)
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def _clone(self, klass=None, setup=False, **kwargs):
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"""
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@ -798,13 +800,17 @@ class ValuesQuerySet(QuerySet):
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raise TypeError("Merging '%s' classes must involve the same values in each case."
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% self.__class__.__name__)
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def _setup_aggregate_query(self):
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def _setup_aggregate_query(self, aggregates):
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"""
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Prepare the query for computing a result that contains aggregate annotations.
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"""
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self.query.set_group_by()
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super(ValuesQuerySet, self)._setup_aggregate_query()
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if self.aggregate_names is not None:
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self.aggregate_names.extend(aggregates)
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self.query.set_aggregate_mask(self.aggregate_names)
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super(ValuesQuerySet, self)._setup_aggregate_query(aggregates)
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def as_sql(self):
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"""
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@ -824,6 +830,7 @@ class ValuesListQuerySet(ValuesQuerySet):
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def iterator(self):
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if self.extra_names is not None:
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self.query.trim_extra_select(self.extra_names)
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if self.flat and len(self._fields) == 1:
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for row in self.query.results_iter():
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yield row[0]
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@ -837,6 +844,7 @@ class ValuesListQuerySet(ValuesQuerySet):
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extra_names = self.query.extra_select.keys()
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field_names = self.field_names
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aggregate_names = self.query.aggregate_select.keys()
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names = extra_names + field_names + aggregate_names
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# If a field list has been specified, use it. Otherwise, use the
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@ -77,7 +77,9 @@ class BaseQuery(object):
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self.related_select_cols = []
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# SQL aggregate-related attributes
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self.aggregate_select = SortedDict() # Maps alias -> SQL aggregate function
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self.aggregates = SortedDict() # Maps alias -> SQL aggregate function
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self.aggregate_select_mask = None
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self._aggregate_select_cache = None
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# Arbitrary maximum limit for select_related. Prevents infinite
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# recursion. Can be changed by the depth parameter to select_related().
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@ -187,7 +189,15 @@ class BaseQuery(object):
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obj.distinct = self.distinct
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obj.select_related = self.select_related
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obj.related_select_cols = []
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obj.aggregate_select = self.aggregate_select.copy()
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obj.aggregates = self.aggregates.copy()
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if self.aggregate_select_mask is None:
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obj.aggregate_select_mask = None
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else:
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obj.aggregate_select_mask = self.aggregate_select_mask[:]
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if self._aggregate_select_cache is None:
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obj._aggregate_select_cache = None
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else:
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obj._aggregate_select_cache = self._aggregate_select_cache.copy()
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obj.max_depth = self.max_depth
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obj.extra_select = self.extra_select.copy()
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obj.extra_tables = self.extra_tables
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@ -940,12 +950,15 @@ class BaseQuery(object):
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"""
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assert set(change_map.keys()).intersection(set(change_map.values())) == set()
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# 1. Update references in "select" and "where".
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# 1. Update references in "select" (normal columns plus aliases),
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# "group by", "where" and "having".
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self.where.relabel_aliases(change_map)
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for pos, col in enumerate(self.select):
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self.having.relabel_aliases(change_map)
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for columns in (self.select, self.aggregates.values(), self.group_by or []):
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for pos, col in enumerate(columns):
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if isinstance(col, (list, tuple)):
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old_alias = col[0]
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self.select[pos] = (change_map.get(old_alias, old_alias), col[1])
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columns[pos] = (change_map.get(old_alias, old_alias), col[1])
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else:
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col.relabel_aliases(change_map)
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@ -1205,11 +1218,11 @@ class BaseQuery(object):
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opts = model._meta
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field_list = aggregate.lookup.split(LOOKUP_SEP)
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if (len(field_list) == 1 and
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aggregate.lookup in self.aggregate_select.keys()):
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aggregate.lookup in self.aggregates.keys()):
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# Aggregate is over an annotation
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field_name = field_list[0]
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col = field_name
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source = self.aggregate_select[field_name]
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source = self.aggregates[field_name]
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elif (len(field_list) > 1 or
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field_list[0] not in [i.name for i in opts.fields]):
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field, source, opts, join_list, last, _ = self.setup_joins(
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@ -1299,7 +1312,7 @@ class BaseQuery(object):
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value = SQLEvaluator(value, self)
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having_clause = value.contains_aggregate
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for alias, aggregate in self.aggregate_select.items():
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for alias, aggregate in self.aggregates.items():
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if alias == parts[0]:
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entry = self.where_class()
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entry.add((aggregate, lookup_type, value), AND)
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@ -1824,8 +1837,8 @@ class BaseQuery(object):
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self.group_by = []
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if self.connection.features.allows_group_by_pk:
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if len(self.select) == len(self.model._meta.fields):
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self.group_by.append('.'.join([self.model._meta.db_table,
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self.model._meta.pk.column]))
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self.group_by.append((self.model._meta.db_table,
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self.model._meta.pk.column))
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return
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for sel in self.select:
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@ -1858,7 +1871,11 @@ class BaseQuery(object):
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# Distinct handling is done in Count(), so don't do it at this
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# level.
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self.distinct = False
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self.aggregate_select = {None: count}
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# Set only aggregate to be the count column.
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# Clear out the select cache to reflect the new unmasked aggregates.
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self.aggregates = {None: count}
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self.set_aggregate_mask(None)
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def add_select_related(self, fields):
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"""
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@ -1920,6 +1937,29 @@ class BaseQuery(object):
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for key in set(self.extra_select).difference(set(names)):
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del self.extra_select[key]
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def set_aggregate_mask(self, names):
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"Set the mask of aggregates that will actually be returned by the SELECT"
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self.aggregate_select_mask = names
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self._aggregate_select_cache = None
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def _aggregate_select(self):
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"""The SortedDict of aggregate columns that are not masked, and should
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be used in the SELECT clause.
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This result is cached for optimization purposes.
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"""
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if self._aggregate_select_cache is not None:
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return self._aggregate_select_cache
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elif self.aggregate_select_mask is not None:
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self._aggregate_select_cache = SortedDict([
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(k,v) for k,v in self.aggregates.items()
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if k in self.aggregate_select_mask
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])
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return self._aggregate_select_cache
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else:
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return self.aggregates
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aggregate_select = property(_aggregate_select)
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def set_start(self, start):
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"""
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Sets the table from which to start joining. The start position is
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@ -213,10 +213,14 @@ class WhereNode(tree.Node):
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elif isinstance(child, tree.Node):
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self.relabel_aliases(change_map, child)
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else:
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if isinstance(child[0], (list, tuple)):
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elt = list(child[0])
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if elt[0] in change_map:
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elt[0] = change_map[elt[0]]
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node.children[pos] = (tuple(elt),) + child[1:]
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else:
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child[0].relabel_aliases(change_map)
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# Check if the query value also requires relabelling
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if hasattr(child[3], 'relabel_aliases'):
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child[3].relabel_aliases(change_map)
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@ -284,9 +284,6 @@ two authors with the same name, their results will be merged into a single
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result in the output of the query; the average will be computed as the
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average over the books written by both authors.
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The annotation name will be added to the fields returned
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as part of the ``ValuesQuerySet``.
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Order of ``annotate()`` and ``values()`` clauses
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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@ -303,12 +300,21 @@ output.
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For example, if we reverse the order of the ``values()`` and ``annotate()``
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clause from our previous example::
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>>> Author.objects.annotate(average_rating=Avg('book__rating')).values('name')
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>>> Author.objects.annotate(average_rating=Avg('book__rating')).values('name', 'average_rating')
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This will now yield one unique result for each author; however, only
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the author's name and the ``average_rating`` annotation will be returned
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in the output data.
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You should also note that ``average_rating`` has been explicitly included
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in the list of values to be returned. This is required because of the
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ordering of the ``values()`` and ``annotate()`` clause.
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If the ``values()`` clause precedes the ``annotate()`` clause, any annotations
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will be automatically added to the result set. However, if the ``values()``
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clause is applied after the ``annotate()`` clause, you need to explicitly
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include the aggregate column.
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Aggregating annotations
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-----------------------
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@ -207,10 +207,9 @@ u'The Definitive Guide to Django: Web Development Done Right'
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>>> Book.objects.filter(pk=1).annotate(mean_age=Avg('authors__age')).values('pk', 'isbn', 'mean_age')
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[{'pk': 1, 'isbn': u'159059725', 'mean_age': 34.5}]
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# Calling it with paramters reduces the output but does not remove the
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# annotation.
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# Calling values() with parameters reduces the output
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>>> Book.objects.filter(pk=1).annotate(mean_age=Avg('authors__age')).values('name')
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[{'name': u'The Definitive Guide to Django: Web Development Done Right', 'mean_age': 34.5}]
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[{'name': u'The Definitive Guide to Django: Web Development Done Right'}]
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# An empty values() call before annotating has the same effect as an
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# empty values() call after annotating
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@ -95,10 +95,18 @@ __test__ = {'API_TESTS': """
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>>> sorted(Book.objects.all().values().annotate(mean_auth_age=Avg('authors__age')).extra(select={'manufacture_cost' : 'price * .5'}).get(pk=2).items())
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[('contact_id', 3), ('id', 2), ('isbn', u'067232959'), ('manufacture_cost', ...11.545...), ('mean_auth_age', 45.0), ('name', u'Sams Teach Yourself Django in 24 Hours'), ('pages', 528), ('price', Decimal("23.09")), ('pubdate', datetime.date(2008, 3, 3)), ('publisher_id', 2), ('rating', 3.0)]
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# A values query that selects specific columns reduces the output
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# If the annotation precedes the values clause, it won't be included
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# unless it is explicitly named
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>>> sorted(Book.objects.all().annotate(mean_auth_age=Avg('authors__age')).extra(select={'price_per_page' : 'price / pages'}).values('name').get(pk=1).items())
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[('name', u'The Definitive Guide to Django: Web Development Done Right')]
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>>> sorted(Book.objects.all().annotate(mean_auth_age=Avg('authors__age')).extra(select={'price_per_page' : 'price / pages'}).values('name','mean_auth_age').get(pk=1).items())
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[('mean_auth_age', 34.5), ('name', u'The Definitive Guide to Django: Web Development Done Right')]
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# If an annotation isn't included in the values, it can still be used in a filter
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>>> Book.objects.annotate(n_authors=Count('authors')).values('name').filter(n_authors__gt=2)
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[{'name': u'Python Web Development with Django'}]
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# The annotations are added to values output if values() precedes annotate()
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>>> sorted(Book.objects.all().values('name').annotate(mean_auth_age=Avg('authors__age')).extra(select={'price_per_page' : 'price / pages'}).get(pk=1).items())
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[('mean_auth_age', 34.5), ('name', u'The Definitive Guide to Django: Web Development Done Right')]
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@ -207,6 +215,11 @@ FieldError: Cannot resolve keyword 'foo' into field. Choices are: authors, conta
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>>> Book.objects.extra(select={'pub':'publisher_id','foo':'pages'}).values('pub').annotate(Count('id')).order_by('pub')
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[{'pub': 1, 'id__count': 2}, {'pub': 2, 'id__count': 1}, {'pub': 3, 'id__count': 2}, {'pub': 4, 'id__count': 1}]
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# Regression for #10182 - Queries with aggregate calls are correctly realiased when used in a subquery
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>>> ids = Book.objects.filter(pages__gt=100).annotate(n_authors=Count('authors')).filter(n_authors__gt=2).order_by('n_authors')
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>>> Book.objects.filter(id__in=ids)
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[<Book: Python Web Development with Django>]
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# Regression for #10199 - Aggregate calls clone the original query so the original query can still be used
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>>> books = Book.objects.all()
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>>> _ = books.aggregate(Avg('authors__age'))
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