from collections import OrderedDict from functools import reduce from django.db import ( NotSupportedError, connections, router, transaction, ) from django.db.models import Avg, Count, F, Manager, Q, TextField from django.db.models.constants import LOOKUP_SEP from django.db.models.functions import Cast, Length from django.db.utils import OperationalError from django.utils.encoding import force_str from django.utils.functional import cached_property from ....index import AutocompleteField, RelatedFields, SearchField, get_indexed_models from ....models import IndexEntry, SQLiteFTSIndexEntry from ....query import And, MatchAll, Not, Or, Phrase, PlainText from ....utils import ( ADD, MUL, OR, get_content_type_pk, get_descendants_content_types_pks, ) from ...base import ( BaseSearchBackend, BaseSearchQueryCompiler, BaseSearchResults, FilterFieldError, ) from .query import ( BM25, AndNot, Lexeme, MatchExpression, SearchQueryExpression, normalize, ) class ObjectIndexer: """ Responsible for extracting data from an object to be inserted into the index. """ def __init__(self, obj, backend): self.obj = obj self.search_fields = obj.get_search_fields() self.config = backend.config def prepare_value(self, value): if isinstance(value, str): return value elif isinstance(value, list): return ", ".join(self.prepare_value(item) for item in value) elif isinstance(value, dict): return ", ".join(self.prepare_value(item) for item in value.values()) return force_str(value) def prepare_field(self, obj, field): if isinstance(field, SearchField): yield (field, self.prepare_value(field.get_value(obj))) elif isinstance(field, AutocompleteField): yield (field, self.prepare_value(field.get_value(obj))) elif isinstance(field, RelatedFields): sub_obj = field.get_value(obj) if sub_obj is None: return if isinstance(sub_obj, Manager): sub_objs = sub_obj.all() else: if callable(sub_obj): sub_obj = sub_obj() sub_objs = [sub_obj] for sub_obj in sub_objs: for sub_field in field.fields: yield from self.prepare_field(sub_obj, sub_field) @cached_property def id(self): """ Returns the value to use as the ID of the record in the index """ return force_str(self.obj.pk) @cached_property def title(self): """ Returns all values to index as "title". This is the value of all SearchFields that have the field_name 'title' """ texts = [] for field in self.search_fields: for current_field, value in self.prepare_field(self.obj, field): if ( isinstance(current_field, SearchField) and current_field.field_name == "title" ): texts.append(value) return " ".join(texts) @cached_property def body(self): """ Returns all values to index as "body". This is the value of all SearchFields excluding the title """ texts = [] for field in self.search_fields: for current_field, value in self.prepare_field(self.obj, field): if ( isinstance(current_field, SearchField) and not current_field.field_name == "title" ): texts.append(value) return " ".join(texts) @cached_property def autocomplete(self): """ Returns all values to index as "autocomplete". This is the value of all AutocompleteFields """ texts = [] for field in self.search_fields: for current_field, value in self.prepare_field(self.obj, field): if isinstance(current_field, AutocompleteField): texts.append(value) return " ".join(texts) def as_vector(self, texts, for_autocomplete=False): """ Converts an array of strings into a SearchVector that can be indexed. """ texts = [(text.strip(), weight) for text, weight in texts] texts = [(text, weight) for text, weight in texts if text] return " ".join(texts) class Index: def __init__(self, backend): self.backend = backend self.name = self.backend.index_name self.read_connection = connections[router.db_for_read(IndexEntry)] self.write_connection = connections[router.db_for_write(IndexEntry)] if ( self.read_connection.vendor != "sqlite" or self.write_connection.vendor != "sqlite" ): raise NotSupportedError( "You must select a SQLite database to use the SQLite search backend." ) self.entries = IndexEntry._default_manager.all() def add_model(self, model): pass def refresh(self): pass def _refresh_title_norms(self, full=False): """ Refreshes the value of the title_norm field. This needs to be set to 'lavg/ld' where: - lavg is the average length of titles in all documents (also in terms) - ld is the length of the title field in this document (in terms) """ lavg = ( self.entries.annotate(title_length=Length("title")) .filter(title_length__gt=0) .aggregate(Avg("title_length"))["title_length__avg"] ) if full: # Update the whole table # This is the most accurate option but requires a full table rewrite # so we can't do it too often as it could lead to locking issues. entries = self.entries else: # Only update entries where title_norm is 1.0 # This is the default value set on new entries. # It's possible that other entries could have this exact value but there shouldn't be too many of those entries = self.entries.filter(title_norm=1.0) entries.annotate(title_length=Length("title")).filter( title_length__gt=0 ).update(title_norm=lavg / F("title_length")) def delete_stale_model_entries(self, model): existing_pks = model._default_manager.annotate( object_id=Cast("pk", TextField()) ).values("object_id") content_types_pks = get_descendants_content_types_pks(model) stale_entries = self.entries.filter( content_type_id__in=content_types_pks ).exclude(object_id__in=existing_pks) stale_entries.delete() def delete_stale_entries(self): for model in get_indexed_models(): # We don’t need to delete stale entries for non-root models, # since we already delete them by deleting roots. if not model._meta.parents: self.delete_stale_model_entries(model) def add_item(self, obj): self.add_items(obj._meta.model, [obj]) def add_items_update_then_create(self, content_type_pk, indexers): ids_and_data = {} for indexer in indexers: ids_and_data[indexer.id] = ( indexer.title, indexer.autocomplete, indexer.body, ) 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_data.keys()).values_list( "object_id", flat=True ) ) for indexed_id in indexed_ids: title, autocomplete, body = ids_and_data[indexed_id] index_entries_for_ct.filter(object_id=indexed_id).update( title=title, autocomplete=autocomplete, body=body ) to_be_created = [] for object_id in ids_and_data.keys(): if object_id not in indexed_ids: title, autocomplete, body = ids_and_data[object_id] to_be_created.append( IndexEntry( content_type_id=content_type_pk, object_id=object_id, title=title, autocomplete=autocomplete, body=body, ) ) self.entries.bulk_create(to_be_created) self._refresh_title_norms() def add_items(self, model, objs): search_fields = model.get_search_fields() if not search_fields: return indexers = [ObjectIndexer(obj, self.backend) for obj in objs] # TODO: Delete unindexed objects while dealing with proxy models. if indexers: content_type_pk = get_content_type_pk(model) update_method = self.add_items_update_then_create update_method(content_type_pk, indexers) def delete_item(self, item): item.index_entries.all()._raw_delete(using=self.write_connection.alias) def __str__(self): return self.name class SQLiteSearchRebuilder: def __init__(self, index): self.index = index def start(self): self.index.delete_stale_entries() return self.index def finish(self): self.index._refresh_title_norms(full=True) class SQLiteSearchAtomicRebuilder(SQLiteSearchRebuilder): def __init__(self, index): super().__init__(index) self.transaction = transaction.atomic(using=index.write_connection.alias) self.transaction_opened = False def start(self): self.transaction.__enter__() self.transaction_opened = True return super().start() def finish(self): self.index._refresh_title_norms(full=True) self.transaction.__exit__(None, None, None) self.transaction_opened = False def __del__(self): # TODO: Implement a cleaner way to close the connection on failure. if self.transaction_opened: self.transaction.needs_rollback = True self.finish() class SQLiteSearchQueryCompiler(BaseSearchQueryCompiler): DEFAULT_OPERATOR = "AND" LAST_TERM_IS_PREFIX = False TARGET_SEARCH_FIELD_TYPE = SearchField FTS_TABLE_FIELDS = ["title", "body"] def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) local_search_fields = self.get_search_fields_for_model() if self.fields is None: # search over the fields defined on the current model self.search_fields = local_search_fields else: # build a search_fields set from the passed definition, # which may involve traversing relations self.search_fields = { field_lookup: self.get_search_field( field_lookup, fields=local_search_fields ) for field_lookup in self.fields } def get_config(self, backend): return backend.config def get_search_fields_for_model(self): return self.queryset.model.get_searchable_search_fields() def get_search_field(self, field_lookup, fields=None): if fields is None: fields = self.search_fields if LOOKUP_SEP in field_lookup: field_lookup, sub_field_name = field_lookup.split(LOOKUP_SEP, 1) else: sub_field_name = None for field in fields: if ( isinstance(field, self.TARGET_SEARCH_FIELD_TYPE) and field.field_name == field_lookup ): return field # Note: Searching on a specific related field using # `.search(fields=…)` is not yet supported by Wagtail. # This method anticipates by already implementing it. if isinstance(field, RelatedFields) and field.field_name == field_lookup: return self.get_search_field(sub_field_name, field.fields) def build_search_query_content(self, query, config=None): """ Takes a SearchQuery and returns another SearchQuery object, which can be used to construct the query in SQL. """ if isinstance(query, PlainText): terms = query.query_string.split() if not terms: return None last_term = terms.pop() lexemes = Lexeme( last_term, prefix=self.LAST_TERM_IS_PREFIX ) # Combine all terms into a single lexeme. for term in terms: new_lexeme = Lexeme(term) if query.operator.upper() == "AND": lexemes &= new_lexeme else: lexemes |= new_lexeme return SearchQueryExpression(lexemes, config=config) elif isinstance(query, Phrase): return SearchQueryExpression(query.query_string) elif isinstance(query, AndNot): # Combine the two sub-queries into a query of the form `(first) AND NOT (second)`. subquery_a = self.build_search_query_content( query.subquery_a, config=config ) subquery_b = self.build_search_query_content( query.subquery_b, config=config ) combined_query = subquery_a._combine(subquery_b, "NOT") return combined_query elif isinstance(query, (And, Or)): subquery_lexemes = [ self.build_search_query_content(subquery, config=config) for subquery in query.subqueries ] is_and = isinstance(query, And) if is_and: return reduce(lambda a, b: a & b, subquery_lexemes) else: return reduce(lambda a, b: a | b, subquery_lexemes) raise NotImplementedError( "`%s` is not supported by the SQLite search backend." % query.__class__.__name__ ) def build_search_query(self, query, config=None): if isinstance(query, MatchAll): return query if isinstance(query, Not): unwrapped_query = query.subquery built_query = Not( self.build_search_query(unwrapped_query, config=config) ) # We don't take the Not operator into account. else: built_query = self.build_search_query_content(query, config=config) return built_query def build_tsrank(self, vector, query, config=None, boost=1.0): if isinstance(query, (Phrase, PlainText, Not)): rank_expression = BM25() if boost != 1.0: rank_expression *= boost return rank_expression 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 SQLite search backend." % query.__class__.__name__ ) def get_index_vectors(self): return [ (F("index_entries__title"), F("index_entries__title_norm")), (F("index_entries__body"), 1.0), ] def get_search_vectors(self): return self.get_index_vectors() def _build_rank_expression(self, vectors, config): # TODO: Come up with my own expression class that compiles down to bm25 rank_expressions = [ self.build_tsrank(vector, self.query, config=config) * boost for vector, boost in vectors ] rank_expression = rank_expressions[0] for other_rank_expression in rank_expressions[1:]: rank_expression += other_rank_expression return rank_expression def search(self, config, start, stop, score_field=None): normalized_query = normalize(self.query) if isinstance(normalized_query, MatchAll): return self.queryset[start:stop] elif isinstance(normalized_query, Not) and isinstance( normalized_query.subquery, MatchAll ): return self.queryset.none() if isinstance(normalized_query, Not): normalized_query = normalized_query.subquery negated = True else: negated = False search_query = self.build_search_query( normalized_query, config=config ) # We build a search query here, for example: "%s MATCH '(hello AND world)'" vectors = self.get_search_vectors() rank_expression = self._build_rank_expression(vectors, config) combined_vector = vectors[ 0 ][ 0 ] # We create a combined vector for the search results queryset. We start with the first vector and build from there. for vector, boost in vectors[1:]: combined_vector = combined_vector._combine( vector, " ", False ) # We add the subsequent vectors to the combined vector. # Build the FTS match expression. expr = MatchExpression(self.fields or self.FTS_TABLE_FIELDS, search_query) # Perform the FTS search. We'll get entries in the SQLiteFTSIndexEntry model. objs = ( SQLiteFTSIndexEntry.objects.filter(expr) .select_related("index_entry") .filter( index_entry__content_type__in=get_descendants_content_types_pks( self.queryset.model ) ) ) if self.order_by_relevance: objs = objs.order_by(BM25().desc()) elif not objs.query.order_by: # Adds a default ordering to avoid issue #3729. queryset = objs.order_by("-pk") rank_expression = F("pk") from django.db import connection from django.db.models.sql.subqueries import InsertQuery compiler = InsertQuery(IndexEntry).get_compiler(connection=connection) try: obj_ids = [ obj.index_entry.object_id for obj in objs ] # Get the IDs of the objects that matched. They're stored in the IndexEntry model, so we need to get that first. except OperationalError as e: raise OperationalError( str(e) + " The original query was: " + compiler.compile(objs.query)[0] + str(compiler.compile(objs.query)[1]) ) from e if not negated: queryset = self.queryset.filter( id__in=obj_ids ) # We need to filter the source queryset to get the objects that matched the search query. else: queryset = self.queryset.exclude( id__in=obj_ids ) # We exclude the objects that matched the search query from the source queryset, if the query is negated. if score_field is not None: queryset = queryset.annotate(**{score_field: rank_expression}) return queryset[start:stop] def _process_lookup(self, field, lookup, value): lhs = field.get_attname(self.queryset.model) + "__" + lookup return Q(**{lhs: value}) def _process_match_none(self): return Q(pk__in=[]) def _connect_filters(self, filters, connector, negated): if connector == "AND": q = Q(*filters) elif connector == "OR": q = OR([Q(fil) for fil in filters]) else: return if negated: q = ~q return q class SQLiteAutocompleteQueryCompiler(SQLiteSearchQueryCompiler): LAST_TERM_IS_PREFIX = True TARGET_SEARCH_FIELD_TYPE = AutocompleteField FTS_TABLE_FIELDS = ["autocomplete"] def get_config(self, backend): return backend.autocomplete_config def get_search_fields_for_model(self): return self.queryset.model.get_autocomplete_search_fields() def get_index_vectors(self): return [(F("index_entries__autocomplete"), 1.0)] class SQLiteSearchResults(BaseSearchResults): def get_queryset(self, for_count=False): if for_count: start = None stop = None else: start = self.start stop = self.stop return self.query_compiler.search( self.query_compiler.get_config(self.backend), start, stop, score_field=self._score_field, ) def _do_search(self): return list(self.get_queryset()) def _do_count(self): return self.get_queryset(for_count=True).count() supports_facet = True def facet(self, field_name): # Get field field = self.query_compiler._get_filterable_field(field_name) if field is None: raise FilterFieldError( 'Cannot facet search results with field "' + field_name + "\". Please add index.FilterField('" + field_name + "') to " + self.query_compiler.queryset.model.__name__ + ".search_fields.", field_name=field_name, ) query = self.query_compiler.search( self.query_compiler.get_config(self.backend), None, None ) results = ( query.values(field_name).annotate(count=Count("pk")).order_by("-count") ) return OrderedDict( [(result[field_name], result["count"]) for result in results] ) class SQLiteSearchBackend(BaseSearchBackend): query_compiler_class = SQLiteSearchQueryCompiler autocomplete_query_compiler_class = SQLiteAutocompleteQueryCompiler results_class = SQLiteSearchResults rebuilder_class = SQLiteSearchRebuilder atomic_rebuilder_class = SQLiteSearchAtomicRebuilder def __init__(self, params): super().__init__(params) self.index_name = params.get("INDEX", "default") # SQLite backend currently has no config options self.config = None self.autocomplete_config = None if params.get("ATOMIC_REBUILD", False): self.rebuilder_class = self.atomic_rebuilder_class def get_index_for_model(self, model): return Index(self) def get_index_for_object(self, obj): return self.get_index_for_model(obj._meta.model) def reset_index(self): for connection in [ connection for connection in connections.all() if connection.vendor == "sqlite" ]: IndexEntry._default_manager.all()._raw_delete(using=connection.alias) def add_type(self, model): pass # Not needed. def refresh_index(self): pass # Not needed. def add(self, obj): self.get_index_for_object(obj).add_item(obj) def add_bulk(self, model, obj_list): if obj_list: self.get_index_for_object(obj_list[0]).add_items(model, obj_list) def delete(self, obj): self.get_index_for_object(obj).delete_item(obj) SearchBackend = SQLiteSearchBackend