From: Benoît Pin Date: Tue, 24 Jun 2014 08:27:04 +0000 (+0200) Subject: Recopie de l'implémentation de ZCatalog.Catalog.Catalog.search, sans les imports. X-Git-Url: https://scm.cri.ensmp.fr/git/Plinn.git/commitdiff_plain/e9f249dc773d6b5b9648310e7bfcc5a2d3cbb330 Recopie de l'implémentation de ZCatalog.Catalog.Catalog.search, sans les imports. --- diff --git a/catalog.py b/catalog.py index fbe323f..382fc57 100644 --- a/catalog.py +++ b/catalog.py @@ -99,7 +99,187 @@ InitializeClass(CatalogTool) class DelegatedCatalog(Catalog) : '''C'est ici qu'on délègue effectivement à Solr ''' + def search(self, query, sort_index=None, reverse=0, limit=None, merge=1): - return Catalog.search(self, query, - sort_index=sort_index, - reverse=reverse, limit=limit, merge=merge) \ No newline at end of file + """Iterate through the indexes, applying the query to each one. If + merge is true then return a lazy result set (sorted if appropriate) + otherwise return the raw (possibly scored) results for later merging. + Limit is used in conjuntion with sorting or scored results to inform + the catalog how many results you are really interested in. The catalog + can then use optimizations to save time and memory. The number of + results is not guaranteed to fall within the limit however, you should + still slice or batch the results as usual.""" + + rs = None # resultset + + # Indexes fulfill a fairly large contract here. We hand each + # index the query mapping we are given (which may be composed + # of some combination of web request, kw mappings or plain old dicts) + # and the index decides what to do with it. If the index finds work + # for itself in the query, it returns the results and a tuple of + # the attributes that were used. If the index finds nothing for it + # to do then it returns None. + + # Canonicalize the request into a sensible query before passing it on + query = self.make_query(query) + + cr = self.getCatalogPlan(query) + cr.start() + + plan = cr.plan() + if not plan: + plan = self._sorted_search_indexes(query) + + indexes = self.indexes.keys() + for i in plan: + if i not in indexes: + # We can have bogus keys or the plan can contain index names + # that have been removed in the meantime + continue + + index = self.getIndex(i) + _apply_index = getattr(index, "_apply_index", None) + if _apply_index is None: + continue + + cr.start_split(i) + limit_result = ILimitedResultIndex.providedBy(index) + if limit_result: + r = _apply_index(query, rs) + else: + r = _apply_index(query) + + if r is not None: + r, u = r + # Short circuit if empty result + # BBB: We can remove the "r is not None" check in Zope 2.14 + # once we don't need to support the "return everything" case + # anymore + if r is not None and not r: + cr.stop_split(i, result=None, limit=limit_result) + return LazyCat([]) + + # provide detailed info about the pure intersection time + intersect_id = i + '#intersection' + cr.start_split(intersect_id) + # weightedIntersection preserves the values from any mappings + # we get, as some indexes don't return simple sets + if hasattr(rs, 'items') or hasattr(r, 'items'): + _, rs = weightedIntersection(rs, r) + else: + rs = intersection(rs, r) + + cr.stop_split(intersect_id) + + # consider the time it takes to intersect the index result with + # the total resultset to be part of the index time + cr.stop_split(i, result=r, limit=limit_result) + if not rs: + break + else: + cr.stop_split(i, result=None, limit=limit_result) + + # Try to deduce the sort limit from batching arguments + b_start = int(query.get('b_start', 0)) + b_size = query.get('b_size', None) + if b_size is not None: + b_size = int(b_size) + + if b_size is not None: + limit = b_start + b_size + elif limit and b_size is None: + b_size = limit + + if rs is None: + # None of the indexes found anything to do with the query + # We take this to mean that the query was empty (an empty filter) + # and so we return everything in the catalog + warnings.warn('Your query %s produced no query restriction. ' + 'Currently the entire catalog content is returned. ' + 'In Zope 2.14 this will result in an empty LazyCat ' + 'to be returned.' % repr(cr.make_key(query)), + DeprecationWarning, stacklevel=3) + + rlen = len(self) + if sort_index is None: + sequence, slen = self._limit_sequence(self.data.items(), rlen, + b_start, b_size) + result = LazyMap(self.instantiate, sequence, slen, + actual_result_count=rlen) + else: + cr.start_split('sort_on') + result = self.sortResults( + self.data, sort_index, reverse, limit, merge, + actual_result_count=rlen, b_start=b_start, + b_size=b_size) + cr.stop_split('sort_on', None) + elif rs: + # We got some results from the indexes. + # Sort and convert to sequences. + # XXX: The check for 'values' is really stupid since we call + # items() and *not* values() + rlen = len(rs) + if sort_index is None and hasattr(rs, 'items'): + # having a 'items' means we have a data structure with + # scores. Build a new result set, sort it by score, reverse + # it, compute the normalized score, and Lazify it. + + if not merge: + # Don't bother to sort here, return a list of + # three tuples to be passed later to mergeResults + # note that data_record_normalized_score_ cannot be + # calculated and will always be 1 in this case + getitem = self.__getitem__ + result = [(score, (1, score, rid), getitem) + for rid, score in rs.items()] + else: + cr.start_split('sort_on') + + rs = rs.byValue(0) # sort it by score + max = float(rs[0][0]) + + # Here we define our getter function inline so that + # we can conveniently store the max value as a default arg + # and make the normalized score computation lazy + def getScoredResult(item, max=max, self=self): + """ + Returns instances of self._v_brains, or whatever is + passed into self.useBrains. + """ + score, key = item + r=self._v_result_class(self.data[key])\ + .__of__(aq_parent(self)) + r.data_record_id_ = key + r.data_record_score_ = score + r.data_record_normalized_score_ = int(100. * score / max) + return r + + sequence, slen = self._limit_sequence(rs, rlen, b_start, + b_size) + result = LazyMap(getScoredResult, sequence, slen, + actual_result_count=rlen) + cr.stop_split('sort_on', None) + + elif sort_index is None and not hasattr(rs, 'values'): + # no scores + if hasattr(rs, 'keys'): + rs = rs.keys() + sequence, slen = self._limit_sequence(rs, rlen, b_start, + b_size) + result = LazyMap(self.__getitem__, sequence, slen, + actual_result_count=rlen) + else: + # sort. If there are scores, then this block is not + # reached, therefore 'sort-on' does not happen in the + # context of a text index query. This should probably + # sort by relevance first, then the 'sort-on' attribute. + cr.start_split('sort_on') + result = self.sortResults(rs, sort_index, reverse, limit, + merge, actual_result_count=rlen, b_start=b_start, + b_size=b_size) + cr.stop_split('sort_on', None) + else: + # Empty result set + result = LazyCat([]) + cr.stop() + return result