def load(self):
try:
tag_recommendation_data = loadFromJson(
RECOMMENDATION_DATA_DIR +
'Current_database_and_class_names.json')
DATABASE = tag_recommendation_data['database']
CLASSES = tag_recommendation_data['classes']
self.cbtr = CommunityBasedTagRecommender(dataset=DATABASE,
classes=CLASSES)
self.cbtr.load_recommenders()
except:
self.cbtr = None
logger.info(
"No computed matrices were found, recommendation system not loading for the moment (but service listening for data to come)."
)
try:
self.index_stats = loadFromJson(RECOMMENDATION_DATA_DIR +
'Current_index_stats.json')
logger.info("Matrices computed out of information from %i sounds" %
self.index_stats['n_sounds_in_matrix'])
except Exception, e:
print e
self.index_stats = {
'n_sounds_in_matrix': 0,
}
def load(self):
try:
tag_recommendation_data = loadFromJson(RECOMMENDATION_DATA_DIR + 'Current_database_and_class_names.json')
DATABASE = tag_recommendation_data['database']
CLASSES = tag_recommendation_data['classes']
self.cbtr = CommunityBasedTagRecommender(dataset=DATABASE, classes=CLASSES)
self.cbtr.load_recommenders()
except:
self.cbtr = None
logger.info("No computed matrices were found, recommendation system not loading for the moment (but service listening for data to come).")
try:
self.index_stats = loadFromJson(RECOMMENDATION_DATA_DIR + 'Current_index_stats.json')
logger.info("Matrices computed out of information from %i sounds" % self.index_stats['n_sounds_in_matrix'])
except Exception as e:
print(e)
self.index_stats = {
'n_sounds_in_matrix': 0,
}
try:
self.index = loadFromJson(RECOMMENDATION_DATA_DIR + 'Index.json')
self.index_stats['biggest_id_in_index'] = max([int(key) for key in self.index.keys()])
self.index_stats['n_sounds_in_index'] = len(self.index.keys())
except Exception as e:
logger.info("Index file not present. Listening for indexing data from appservers.")
self.index_stats['biggest_id_in_index'] = 0
self.index_stats['n_sounds_in_index'] = 0
self.index = dict()
def load(self):
try:
tag_recommendation_data = loadFromJson(
tr_settings.RECOMMENDATION_DATA_DIR + 'Current_database_and_class_names.json')
DATABASE = tag_recommendation_data['database']
CLASSES = tag_recommendation_data['classes']
self.cbtr = CommunityBasedTagRecommender(dataset=DATABASE, classes=CLASSES)
self.cbtr.load_recommenders()
except:
self.cbtr = None
logger.info("No computed matrices were found, recommendation system not loading for the moment (but service listening for data to come).")
try:
self.index_stats = loadFromJson(tr_settings.RECOMMENDATION_DATA_DIR + 'Current_index_stats.json')
logger.info("Matrices computed out of information from %i sounds" % self.index_stats['n_sounds_in_matrix'])
except Exception as e:
print(e)
self.index_stats = {
'n_sounds_in_matrix': 0,
}
try:
self.index = loadFromJson(tr_settings.RECOMMENDATION_DATA_DIR + 'Index.json')
self.index_stats['biggest_id_in_index'] = max([int(key) for key in self.index.keys()])
self.index_stats['n_sounds_in_index'] = len(self.index.keys())
except Exception as e:
logger.info("Index file not present. Listening for indexing data from appservers.")
self.index_stats['biggest_id_in_index'] = 0
self.index_stats['n_sounds_in_index'] = 0
self.index = dict()
def load(self):
try:
tag_recommendation_data = loadFromJson(RECOMMENDATION_DATA_DIR + 'Current_database_and_class_names.json')
DATABASE = tag_recommendation_data['database']
CLASSES = tag_recommendation_data['classes']
self.cbtr = CommunityBasedTagRecommender(dataset=DATABASE, classes=CLASSES)
self.cbtr.load_recommenders()
except:
self.cbtr = None
logger.info("No computed matrices were found, recommendation system not loading for the moment (but service listening for data to come).")
try:
self.index_stats = loadFromJson(RECOMMENDATION_DATA_DIR + 'Current_index_stats.json')
logger.info("Matrices computed out of information from %i sounds" % self.index_stats['n_sounds_in_matrix'])
except Exception, e:
print e
self.index_stats = {
'n_sounds_in_matrix': 0,
}
class TagRecommendationServer(resource.Resource):
def __init__(self):
resource.Resource.__init__(self)
self.methods = server_interface(self)
self.isLeaf = False
self.load()
def load(self):
try:
tag_recommendation_data = loadFromJson(
tr_settings.RECOMMENDATION_DATA_DIR +
'Current_database_and_class_names.json')
DATABASE = tag_recommendation_data['database']
CLASSES = tag_recommendation_data['classes']
self.cbtr = CommunityBasedTagRecommender(dataset=DATABASE,
classes=CLASSES)
self.cbtr.load_recommenders()
except:
self.cbtr = None
logger.info(
"No computed matrices were found, recommendation system not loading for the moment ("
"but service listening for data to come).")
try:
self.index_stats = loadFromJson(
tr_settings.RECOMMENDATION_DATA_DIR +
'Current_index_stats.json')
logger.info("Matrices computed out of information from %i sounds" %
self.index_stats['n_sounds_in_matrix'])
except Exception as e:
print(e)
self.index_stats = {
'n_sounds_in_matrix': 0,
}
try:
self.index = loadFromJson(tr_settings.RECOMMENDATION_DATA_DIR,
'Index.json')
self.index_stats['biggest_id_in_index'] = max(
[int(key) for key in self.index.keys()])
self.index_stats['n_sounds_in_index'] = len(self.index.keys())
except Exception as e:
logger.info(
"Index file not present. Listening for indexing data from appservers."
)
self.index_stats['biggest_id_in_index'] = 0
self.index_stats['n_sounds_in_index'] = 0
self.index = dict()
def error(self, message):
return json.dumps({'Error': message})
def getChild(self, name, request):
return self
def render_GET(self, request):
return self.methods[request.prepath[1]](**request.args)
def recommend_tags(self, input_tags, max_number_of_tags=None):
try:
logger.debug('Getting recommendation for input tags %s' %
input_tags)
input_tags = input_tags[0].split(",")
if max_number_of_tags:
max_number_of_tags = int(max_number_of_tags[0])
recommended_tags, com_name = self.cbtr.recommend_tags(
input_tags, max_number_of_tags=max_number_of_tags)
result = {
'error': False,
'result': {
'tags': recommended_tags,
'community': com_name
}
}
except Exception as e:
logger.debug('Errors occurred while recommending tags to %s' %
input_tags)
result = {'error': True, 'result': str(e)}
return json.dumps(result)
def reload(self):
logger.info('Reloading tagrecommendation server...')
self.load()
result = {'error': False, 'result': "Server reloaded"}
return json.dumps(result)
def last_indexed_id(self):
result = {
'error': False,
'result': self.index_stats['biggest_id_in_index']
}
logger.info(
'Getting last indexed id information (%i, %i sounds in index, %i sounds in matrix)'
% (self.index_stats['biggest_id_in_index'],
self.index_stats['n_sounds_in_index'],
self.index_stats['n_sounds_in_matrix']))
return json.dumps(result)
def add_to_index(self, sound_ids, sound_tagss):
sound_ids = sound_ids[0].split(",")
sound_tags = [
stags.split(",") for stags in sound_tagss[0].split("-!-!-")
]
logger.info('Adding %i sounds to recommendation index' %
len(sound_ids))
for count, sound_id in enumerate(sound_ids):
sid = sound_id
stags = sound_tags[count]
self.index[sid] = stags
if len(self.index.keys()) % 1000 == 0:
# Every 1000 indexed sounds, save the index
logger.info('Saving tagrecommendation index...')
saveToJson(tr_settings.RECOMMENDATION_DATA_DIR + 'Index.json',
self.index,
verbose=False)
self.index_stats['biggest_id_in_index'] = max(
[int(key) for key in self.index.keys()])
self.index_stats['n_sounds_in_index'] = len(self.index.keys())
result = {'error': False, 'result': True}
return json.dumps(result)
class TagRecommendationServer(resource.Resource):
def __init__(self):
resource.Resource.__init__(self)
self.methods = server_interface(self)
self.isLeaf = False
self.load()
def load(self):
try:
tag_recommendation_data = loadFromJson(
tr_settings.RECOMMENDATION_DATA_DIR + 'Current_database_and_class_names.json')
DATABASE = tag_recommendation_data['database']
CLASSES = tag_recommendation_data['classes']
self.cbtr = CommunityBasedTagRecommender(dataset=DATABASE, classes=CLASSES)
self.cbtr.load_recommenders()
except:
self.cbtr = None
logger.info("No computed matrices were found, recommendation system not loading for the moment (but service listening for data to come).")
try:
self.index_stats = loadFromJson(tr_settings.RECOMMENDATION_DATA_DIR + 'Current_index_stats.json')
logger.info("Matrices computed out of information from %i sounds" % self.index_stats['n_sounds_in_matrix'])
except Exception as e:
print(e)
self.index_stats = {
'n_sounds_in_matrix': 0,
}
try:
self.index = loadFromJson(tr_settings.RECOMMENDATION_DATA_DIR + 'Index.json')
self.index_stats['biggest_id_in_index'] = max([int(key) for key in self.index.keys()])
self.index_stats['n_sounds_in_index'] = len(self.index.keys())
except Exception as e:
logger.info("Index file not present. Listening for indexing data from appservers.")
self.index_stats['biggest_id_in_index'] = 0
self.index_stats['n_sounds_in_index'] = 0
self.index = dict()
def error(self,message):
return json.dumps({'Error': message})
def getChild(self, name, request):
return self
def render_GET(self, request):
return self.methods[request.prepath[1]](**request.args)
def recommend_tags(self, input_tags, max_number_of_tags=None):
try:
logger.debug('Getting recommendation for input tags %s' % input_tags)
input_tags = input_tags[0].split(",")
if max_number_of_tags:
max_number_of_tags = int(max_number_of_tags[0])
recommended_tags, com_name = self.cbtr.recommend_tags(input_tags,
max_number_of_tags=max_number_of_tags)
result = {'error': False, 'result': {'tags': recommended_tags, 'community': com_name}}
except Exception as e:
logger.debug('Errors occurred while recommending tags to %s' % input_tags)
result = {'error': True, 'result': str(e)}
return json.dumps(result)
def reload(self):
logger.info('Reloading tagrecommendation server...')
self.load()
result = {'error': False, 'result': "Server reloaded"}
return json.dumps(result)
def last_indexed_id(self):
result = {'error': False, 'result': self.index_stats['biggest_id_in_index']}
logger.info('Getting last indexed id information (%i, %i sounds in index, %i sounds in matrix)' % (self.index_stats['biggest_id_in_index'],
self.index_stats['n_sounds_in_index'],
self.index_stats['n_sounds_in_matrix']))
return json.dumps(result)
def add_to_index(self, sound_ids, sound_tagss):
sound_ids = sound_ids[0].split(",")
sound_tags = [stags.split(",") for stags in sound_tagss[0].split("-!-!-")]
logger.info('Adding %i sounds to recommendation index' % len(sound_ids))
for count, sound_id in enumerate(sound_ids):
sid = sound_id
stags = sound_tags[count]
self.index[sid] = stags
if len(self.index.keys()) % 1000 == 0:
# Every 1000 indexed sounds, save the index
logger.info('Saving tagrecommendation index...')
saveToJson(tr_settings.RECOMMENDATION_DATA_DIR + 'Index.json', self.index, verbose=False)
self.index_stats['biggest_id_in_index'] = max([int(key) for key in self.index.keys()])
self.index_stats['n_sounds_in_index'] = len(self.index.keys())
result = {'error': False, 'result': True}
return json.dumps(result)
