def add_items_update_then_create(self, content_type_pk, objs):
config = self.backend.config
ids_and_objs = {}
for obj in objs:
obj._autocomplete_ = (ADD([
SearchVector(Value(text), weight=weight, config=config)
for text, weight in obj._autocomplete_
]) if obj._autocomplete_ else EMPTY_VECTOR)
obj._body_ = (ADD([
SearchVector(Value(text), weight=weight, config=config)
for text, weight in obj._body_
]) if obj._body_ else EMPTY_VECTOR)
ids_and_objs[obj._object_id_] = obj
index_entries_for_ct = self.entries.filter(
content_type_id=content_type_pk)
indexed_ids = frozenset(
index_entries_for_ct.filter(
object_id__in=ids_and_objs).values_list('object_id',
flat=True))
for indexed_id in indexed_ids:
obj = ids_and_objs[indexed_id]
index_entries_for_ct.filter(object_id=obj._object_id_) \
.update(autocomplete=obj._autocomplete_, body=obj._body_)
to_be_created = []
for object_id in ids_and_objs:
if object_id not in indexed_ids:
obj = ids_and_objs[object_id]
to_be_created.append(
IndexEntry(content_type_id=content_type_pk,
object_id=object_id,
autocomplete=obj._autocomplete_,
body=obj._body_))
self.entries.bulk_create(to_be_created)
def search(self, config, start, stop):
# TODO: Handle MatchAll nested inside other search query classes.
if isinstance(self.query, MatchAll):
return self.queryset[start:stop]
search_query = self.build_database_query(config=config)
queryset = self.queryset
query = queryset.query
if self.fields is None:
vector = F('index_entries__body_search')
else:
vector = ADD(
SearchVector(field,
config=search_query.config,
weight=get_weight(self.get_boost(field)))
for field in self.fields)
vector = vector.resolve_expression(query)
search_query = search_query.resolve_expression(query)
lookup = IndexEntry._meta.get_field('body_search').get_lookup('exact')(
vector, search_query)
query.where.add(lookup, 'AND')
if self.order_by_relevance:
# Due to a Django bug, arrays are not automatically converted here.
converted_weights = '{' + ','.join(map(str, WEIGHTS_VALUES)) + '}'
queryset = queryset.order_by(
SearchRank(vector, search_query,
weights=converted_weights).desc(), '-pk')
elif not queryset.query.order_by:
# Adds a default ordering to avoid issue #3729.
queryset = queryset.order_by('-pk')
return queryset[start:stop]
def search(self, config, start, stop):
# TODO: Handle MatchAll nested inside other search query classes.
if isinstance(self.query, MatchAll):
return self.queryset[start:stop]
search_query = self.build_database_query(config=config)
queryset = self.queryset
query = queryset.query
if self.fields is None:
vector = F('index_entries__body_search')
else:
vector = ADD(
SearchVector(field, config=search_query.config,
weight=get_weight(self.get_boost(field)))
for field in self.fields)
vector = vector.resolve_expression(query)
search_query = search_query.resolve_expression(query)
lookup = IndexEntry._meta.get_field('body_search').get_lookup('exact')(
vector, search_query)
query.where.add(lookup, 'AND')
if self.order_by_relevance:
# Due to a Django bug, arrays are not automatically converted here.
converted_weights = '{' + ','.join(map(str, WEIGHTS_VALUES)) + '}'
queryset = queryset.order_by(SearchRank(vector, search_query,
weights=converted_weights).desc(),
'-pk')
elif not queryset.query.order_by:
# Adds a default ordering to avoid issue #3729.
queryset = queryset.order_by('-pk')
return queryset[start:stop]
def build_tsrank(self, vector, query, config=None, boost=1.0):
if isinstance(query, (Phrase, PlainText, Not)):
rank_expression = SearchRank(vector,
self.build_tsquery(query,
config=config),
weights=self.sql_weights)
if boost != 1.0:
rank_expression *= boost
return rank_expression
elif isinstance(query, Boost):
boost *= query.boost
return self.build_tsrank(vector,
query.subquery,
config=config,
boost=boost)
elif isinstance(query, And):
return MUL(
1 +
self.build_tsrank(vector, subquery, config=config, boost=boost)
for subquery in query.subqueries) - 1
elif isinstance(query, Or):
return ADD(
self.build_tsrank(vector, subquery, config=config, boost=boost)
for subquery in query.subqueries) / (len(query.subqueries)
or 1)
raise NotImplementedError(
'`%s` is not supported by the PostgreSQL search backend.' %
query.__class__.__name__)
def search(self, config, start, stop, score_field=None):
# TODO: Handle MatchAll nested inside other search query classes.
if isinstance(self.query, MatchAll):
return self.queryset[start:stop]
search_query = self.build_database_query(config=config)
if self.fields is None:
vector = F('index_entries__autocomplete')
if not self.is_autocomplete:
vector = vector._combine(F('index_entries__body'), '||', False)
else:
vector = ADD(
SearchVector(field_lookup,
config=search_query.config,
weight=get_weight(search_field.boost))
for field_lookup, search_field in self.search_fields.items()
if not self.is_autocomplete or search_field.partial_match)
rank_expression = SearchRank(vector,
search_query,
weights=self.sql_weights)
queryset = self.queryset.annotate(_vector_=vector).filter(
_vector_=search_query)
if self.order_by_relevance:
queryset = queryset.order_by(rank_expression.desc(), '-pk')
elif not queryset.query.order_by:
# Adds a default ordering to avoid issue #3729.
queryset = queryset.order_by('-pk')
rank_expression = F('pk')
if score_field is not None:
queryset = queryset.annotate(**{score_field: rank_expression})
return queryset[start:stop]
def get_fields_vector(self, search_query):
return ADD(
SearchVector(field_lookup,
config=search_query.config,
weight=get_weight(search_field.boost))
for field_lookup, search_field in self.search_fields.items()
if search_field.partial_match)
def get_fields_vector(self, search_query):
return ADD(
SearchVector(
field_lookup,
config=search_query.config,
weight='D',
) for field_lookup, search_field in self.search_fields.items())
def add_items_update_then_create(self, content_type_pk, objs, config):
ids_and_objs = {}
for obj in objs:
obj._search_vector = (ADD([
SearchVector(Value(text), weight=weight, config=config)
for text, weight in obj._body_
]) if obj._body_ else SearchVector(Value('')))
ids_and_objs[obj._object_id] = obj
index_entries_for_ct = self.index_entries.filter(
content_type_id=content_type_pk)
indexed_ids = frozenset(
index_entries_for_ct.filter(
object_id__in=ids_and_objs).values_list('object_id',
flat=True))
for indexed_id in indexed_ids:
obj = ids_and_objs[indexed_id]
index_entries_for_ct.filter(object_id=obj._object_id) \
.update(body_search=obj._search_vector)
to_be_created = []
for object_id in ids_and_objs:
if object_id not in indexed_ids:
to_be_created.append(
IndexEntry(
content_type_id=content_type_pk,
object_id=object_id,
body_search=ids_and_objs[object_id]._search_vector,
))
self.index_entries.bulk_create(to_be_created)
def as_vector(self, texts):
"""
Converts an array of strings into a SearchVector that can be indexed.
"""
if not texts:
return EMPTY_VECTOR
return ADD([
SearchVector(Value(text, output_field=TextField()),
weight=weight,
config=self.search_config) for text, weight in texts
])
def as_vector(self, texts, for_autocomplete=False):
"""
Converts an array of strings into a SearchVector that can be indexed.
"""
if not texts:
return EMPTY_VECTOR
search_config = self.autocomplete_config if for_autocomplete else self.config
return ADD([
SearchVector(Value(text, output_field=TextField()),
weight=weight,
config=search_config) for text, weight in texts
])
