def handle(self, *args, **options):
def _to_hit_group_class(results):
for result in results:
doc = result['document']
prob = result['probabilities']
yield HitGroupClass(group_id=doc['group_id'],
classes=NaiveBayesClassifier.most_likely(result),
probabilities=json.dumps(prob))
if options['clear_all']:
logger.info('Removing all existing classification')
# HitGroupClass.objects.all().delete()
execute_sql('DELETE FROM main_hitgroupclass;', commit=True)
return
if options['begin'] and options['end']:
# XXX it can be slow.
query = ''' SELECT group_id, title, description, keywords
FROM main_hitgroupcontent as content
JOIN hits_mv
ON content.group_id = hits_mv.group_id
WHERE
NOT EXISTS(
SELECT * FROM main_hitgroupclass as class
WHERE content.group_id = class.group_id
) AND
hits_mv.start_time >= {} AND
hits_mv.start_time < {}
GROUP BY group_id
LIMIT {};
'''.format(options['begin'], options['end'], self.BATCH_SIZE)
else:
query = ''' SELECT group_id, title, description, keywords
FROM main_hitgroupcontent as content
WHERE NOT EXISTS(
SELECT * FROM main_hitgroupclass as class
WHERE content.group_id = class.group_id
) LIMIT {};
'''.format(self.BATCH_SIZE)
if not options['classifier_path']:
try:
options['classifier_path'] = settings.CLASSIFIER_PATH
except AttributeError:
raise ImproperlyConfigured('Classifier path is not specified '
'neither in the settings file'
'nor in the command line')
with open(options['classifier_path'], 'r') as file:
probabilities = json.load(file)
classifier = NaiveBayesClassifier(probabilities=probabilities)
logger.info('Classification of hit groups started. Processing in '\
'batches size of {}'.format(self.BATCH_SIZE))
while True:
models = query_to_dicts(query)
logger.info('Batch classification started')
try:
results = _to_hit_group_class(classifier.classify_batch(models))
HitGroupClass.objects.bulk_create(results)
except EmptyBatchException:
logger.info('Batch is empty no hit groups to classify')
break
logger.info('Batch classified successfully')
def _to_hit_group_class(results):
for result in results:
doc = result['document']
prob = result['probabilities']
yield HitGroupClass(group_id=doc['group_id'],
classes=NaiveBayesClassifier.most_likely(result),
probabilities=json.dumps(prob))
def hit_group_details(request, hit_group_id):
try:
hit_group = HitGroupContent.objects.get(group_id=hit_group_id)
if RequesterProfile.objects.filter(requester_id=hit_group.requester_id,
is_public=False):
raise HitGroupContent.DoesNotExist()
except HitGroupContent.DoesNotExist:
messages.info(request, 'Hitgroup with id "{0}" was not found!'.format(
hit_group_id))
return redirect('haystack_search')
try:
hit_group_class = HitGroupClass.objects.get(group_id=hit_group_id)
except ObjectDoesNotExist:
# TODO classification should be done on all models.
hit_group_class = None
try:
with open(settings.CLASSIFIER_PATH, "r") as file:
classifier = NaiveBayesClassifier(
probabilities=json.load(file)
)
classified = classifier.classify(hit_group)
most_likely = classifier.most_likely(classified)
document = classified["document"]
hit_group_class = HitGroupClass(
group_id=document.group_id,
classes=most_likely,
probabilities=classified["probabilities"])
hit_group_class.save()
except IOError:
# We do not want make hit group details page unavailable when
# classifier file does not exist.
pass
if hit_group_class is not None:
hit_group_class_label = NaiveBayesClassifier.label(
hit_group_class.classes
)
else:
hit_group_class_label = NaiveBayesClassifier.label()
params = {
'multichart': False,
'columns': HIT_DETAILS_COLUMNS,
'title': '#Hits',
'class': hit_group_class_label,
}
def hit_group_details_data_formater(input):
for cc in input:
yield {
'date': cc['start_time'],
'row': (str(cc['hits_available']),),
}
dicts = query_to_dicts(
""" select start_time, hits_available from hits_mv
where group_id = '{}' order by start_time asc """
.format(hit_group_id))
data = hit_group_details_data_formater(dicts)
params['date_from'] = hit_group.occurrence_date
params['date_to'] = datetime.datetime.utcnow()
params['data'] = data
params['hit_group'] = hit_group
return direct_to_template(request, 'main/hit_group_details.html', params)
