def test_get_recommendable_item(self):
fb = Random_Recommender()
# inserting two items for domain1
fb.set_recommendables( 1, { 'domainid' : 'domain1' } )
fb.set_recommendables( 2, { 'domainid' : 'domain1' } )
g = fb.get_recommendable_item( { 'domainid' : 'domain1' } )
self.assertIn(int(g), (1,2), "fetched wrong recommendable item")
# for this domain there is no way of recommending anything, because we don't have any items
g = fb.get_recommendable_item( { 'domainid' : 'domain2' } )
self.assertIsNone(g, "fetched wrong recommendable item")
def insertRecommendables(self, additional_filter, N1, N2): fb = Random_Recommender() for item_id in xrange(N1,N2): fb.set_recommendables( itemid = item_id, additional_filter = additional_filter )
fullParsedDataModel = FullContestMessageParser()
fullParsedDataModel.parse(message)
fullParsedDataModel.save()
item_id = fullParsedDataModel.item_id
if config_global.SAVE_RAW_JSON in backends:
raw = rawJsonModel(message, mode='redis')
raw.save()
if config_global.SAVE_RANDOM_RECOMMENDER in backends:
fb = Random_Recommender()
domain_id = fullParsedDataModel.domain_id
## todo the recommender has to decide on its own what to save and therefore save constraints, even though the constrain management should be centralized
#constraints = {'domainid': domain_id}
fb.set_recommendables(item_id, constraints)
if api == 'orp':
# todo throw not implemented error
pass
elif api == 'id_list': ## this for debugging purposes
userid = message['userid']
itemid = message['itemid']
timestamp = message['timestamp']
domainid = message['domainid']
additional_filter = {'domainid': domainid}
if config_global.SAVE_RANDOM_RECOMMENDER in backends:
