def actionUpdate(self, action, data):
min_score = data['min_score']
same_query = data['same_query']
max_results = data['max_results']
max_related = data['max_related']
basequery = self.context.buildQuery()
if basequery is None:
return LazyCat([[]])
baseresults = self.portal_catalog.searchResults(basequery)
uids = [brain.UID for brain in baseresults]
service = SimService()
for brain in baseresults:
if len(brain.getRawRelatedItems) >= max_related:
continue
response = service.query(brain.UID, min_score=min_score)
if response['status'] == 'OK':
simserveritems = response['response']
suids =[s[0] for s in simserveritems
if brain.UID != s[0]]
if same_query:
suids =[s for s in suids if s in uids]
if suids:
related = brain.getRawRelatedItems
if len(related) < max_results:
new_related = related +[s for s in suids
if s not in related]
else:
continue
if len(new_related[:max_results]) > len(related):
ob = brain.getObject()
ob.setRelatedItems(new_related[:max_results])
logger.info('set %i new relations to "%s"' %
(len(new_related[:max_results]) - len(related),
brain.Title))
elif response['status'] == 'NOTFOUND':
logger.info('document "%s" not in index' % brain.Title)
else:
IStatusMessage(self.request).addStatusMessage(
response['response'], type='error')
status = _(u'related items set')
IStatusMessage(self.request).addStatusMessage(status, type='info')
self.request.response.redirect(self.next_url)
def queryCatalog(self, *args, **kw):
"""Invoke the catalog using our criteria to augment any passed
in query before calling the catalog.
"""
basequery = self.buildQuery()
if basequery is None:
return LazyCat([[]])
portal_catalog = getToolByName(self, 'portal_catalog')
baseresults = portal_catalog.searchResults(basequery)
uids = [brain.UID for brain in baseresults]
service = SimService()
min_score = self.getMin_score()
response = service.query(documents=uids, min_score=min_score, max_results=200)
if response['status']=='OK':
indexed_documents = response['response'].keys()
similar_documents = []
for values in response['response'].itervalues():
similar_documents +=[k[0] for k in values]
unique_docs = list(set(similar_documents))
doc_count={}
for doc in unique_docs:
count = similar_documents.count(doc)
docs = doc_count.get(count, [])
docs.append(doc)
doc_count[count] = docs
min_similar = self.getMin_similar()
for k, v in doc_count.iteritems():
if (k*100)/len(indexed_documents) < min_similar:
for doc in v:
if doc in unique_docs:
unique_docs.remove(doc)
query={}
citerions_to_apply = self.getCiterions_to_apply()
if citerions_to_apply:
status =''
if self.hasSortCriterion() and self.getExclude_orig():
if len(citerions_to_apply)+1 == len(self.listCriteria()):
status = _('You excluded all items')
elif self.getExclude_orig():
if len(citerions_to_apply)== len(self.listCriteria()):
status = _('You excluded all items')
if status:
i = zope.security.management.getInteraction()
for p in i.participations:
if zope.publisher.interfaces.IRequest.providedBy(p):
request = p
break
#IStatusMessage(request).addStatusMessage(
# status, type='error')
criteria = self.listCriteria()
for criterion in criteria:
for key, value in criterion.getCriteriaItems():
if key in citerions_to_apply:
query[key]=value
if self.getExclude_orig():
for doc in indexed_documents:
if doc in unique_docs:
unique_docs.remove(doc)
else:
if not citerions_to_apply:
unique_docs += uids
if self.hasSortCriterion():
criterion = self.getSortCriterion()
sort_order = None
sort_on = criterion.getCriteriaItems()[0][1]
if len(criterion.getCriteriaItems())==2:
sort_order = criterion.getCriteriaItems()[1][1]
query['sort_on'] = sort_on
query['sort_order'] = sort_order
query['UID'] = unique_docs
return portal_catalog(**query)
else:
sim_relevance = {}
for values in response['response'].itervalues():
for v in values:
rel = sim_relevance.get(v[0],0)
rel += v[1]
sim_relevance[v[0]] = rel
by_relevance = sorted(sim_relevance.items(),
key=itemgetter(1), reverse=True)
query['UID'] = unique_docs
brains= portal_catalog(**query)
uid_brains ={}
for brain in brains:
uid_brains[brain.UID] = brain
result = []
for r in by_relevance:
if r[0] in uid_brains:
result.append(uid_brains[r[0]])
return result