def test_basic_computation(self):
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.2,1.0,0.8\n'
'0.1,0.8,1.0')
with self.swap(
jobs_registry, 'ALL_CONTINUOUS_COMPUTATION_MANAGERS',
self.ALL_CONTINUOUS_COMPUTATION_MANAGERS_FOR_TESTS):
ModifiedExplorationRecommendationsAggregator.start_computation()
self.assertEqual(
self.count_jobs_in_taskqueue(
queue_name=taskqueue_services.QUEUE_NAME_DEFAULT),
1)
self.process_and_flush_pending_tasks()
recommendations = (
recommendations_services.get_exploration_recommendations(
'exp_id_1'))
self.assertEqual(
recommendations, ['exp_id_4', 'exp_id_2', 'exp_id_3'])
recommendations = (
recommendations_services.get_exploration_recommendations(
'exp_id_4'))
self.assertEqual(
recommendations, ['exp_id_1', 'exp_id_2', 'exp_id_3'])
def test_basic_computation(self):
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.2,1.0,0.8\n'
'0.1,0.8,1.0')
with self.swap(
jobs_registry, 'ALL_CONTINUOUS_COMPUTATION_MANAGERS',
self.ALL_CC_MANAGERS_FOR_TESTS
):
ModifiedExplorationRecommendationsAggregator.start_computation()
self.assertEqual(
self.count_jobs_in_taskqueue(
queue_name=taskqueue_services.QUEUE_NAME_DEFAULT),
1)
self.process_and_flush_pending_tasks()
recommendations = (
recommendations_services.get_exploration_recommendations(
'exp_id_1'))
self.assertEqual(
recommendations, ['exp_id_4', 'exp_id_2', 'exp_id_3'])
recommendations = (
recommendations_services.get_exploration_recommendations(
'exp_id_4'))
self.assertEqual(
recommendations, ['exp_id_1', 'exp_id_2', 'exp_id_3'])
def test_basic_computation(self):
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.2,1.0,0.8\n'
'0.1,0.8,1.0')
with self.swap(
jobs_registry, 'ONE_OFF_JOB_MANAGERS',
self.ONE_OFF_JOB_MANAGERS_FOR_TESTS
):
self.job_class.enqueue(self.job_class.create_new())
self.assertEqual(
self.count_jobs_in_taskqueue(
queue_name=taskqueue_services.QUEUE_NAME_DEFAULT),
1)
self.process_and_flush_pending_tasks()
recommendations = (
recommendations_services.get_exploration_recommendations(
'exp_id_1'))
self.assertEqual(
recommendations, ['exp_id_4', 'exp_id_2', 'exp_id_3'])
recommendations = (
recommendations_services.get_exploration_recommendations(
'exp_id_4'))
self.assertEqual(
recommendations, ['exp_id_1', 'exp_id_2', 'exp_id_3'])
def test_basic_computation(self):
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.2,1.0,0.8\n'
'0.1,0.8,1.0')
with self.swap(
jobs_registry, 'ONE_OFF_JOB_MANAGERS',
self.ONE_OFF_JOB_MANAGERS_FOR_TESTS
):
self.job_class.enqueue(self.job_class.create_new())
self.assertEqual(
self.count_jobs_in_mapreduce_taskqueue(
taskqueue_services.QUEUE_NAME_ONE_OFF_JOBS), 1)
self.process_and_flush_pending_mapreduce_tasks()
recommendations = (
recommendations_services.get_exploration_recommendations(
'exp_id_1'))
self.assertEqual(
recommendations, ['exp_id_4', 'exp_id_2', 'exp_id_3'])
recommendations = (
recommendations_services.get_exploration_recommendations(
'exp_id_4'))
self.assertEqual(
recommendations, ['exp_id_1', 'exp_id_2', 'exp_id_3'])
def post(self):
"""Handles POST requests."""
try:
if self.payload.get('action') == 'reload_exploration':
exploration_id = self.payload.get('exploration_id')
self._reload_exploration(exploration_id)
elif self.payload.get('action') == 'reload_collection':
collection_id = self.payload.get('collection_id')
self._reload_collection(collection_id)
elif self.payload.get('action') == 'clear_search_index':
exp_services.clear_search_index()
elif self.payload.get('action') == 'save_config_properties':
new_config_property_values = self.payload.get(
'new_config_property_values')
logging.info('[ADMIN] %s saved config property values: %s' %
(self.user_id, new_config_property_values))
for (name, value) in new_config_property_values.iteritems():
config_services.set_property(self.user_id, name, value)
elif self.payload.get('action') == 'revert_config_property':
config_property_id = self.payload.get('config_property_id')
logging.info('[ADMIN] %s reverted config property: %s' %
(self.user_id, config_property_id))
config_services.revert_property(self.user_id,
config_property_id)
elif self.payload.get('action') == 'start_new_job':
for klass in jobs_registry.ONE_OFF_JOB_MANAGERS:
if klass.__name__ == self.payload.get('job_type'):
klass.enqueue(klass.create_new())
break
elif self.payload.get('action') == 'cancel_job':
job_id = self.payload.get('job_id')
job_type = self.payload.get('job_type')
for klass in jobs_registry.ONE_OFF_JOB_MANAGERS:
if klass.__name__ == job_type:
klass.cancel(job_id, self.user_id)
break
elif self.payload.get('action') == 'start_computation':
computation_type = self.payload.get('computation_type')
for klass in jobs_registry.ALL_CONTINUOUS_COMPUTATION_MANAGERS:
if klass.__name__ == computation_type:
klass.start_computation()
break
elif self.payload.get('action') == 'stop_computation':
computation_type = self.payload.get('computation_type')
for klass in jobs_registry.ALL_CONTINUOUS_COMPUTATION_MANAGERS:
if klass.__name__ == computation_type:
klass.stop_computation(self.user_id)
break
elif self.payload.get('action') == 'upload_topic_similarities':
data = self.payload.get('data')
recommendations_services.update_topic_similarities(data)
self.render_json({})
except Exception as e:
self.render_json({'error': unicode(e)})
raise
def post(self):
"""Handles POST requests."""
try:
if self.payload.get('action') == 'reload_exploration':
exploration_id = self.payload.get('exploration_id')
self._reload_exploration(exploration_id)
elif self.payload.get('action') == 'reload_collection':
collection_id = self.payload.get('collection_id')
self._reload_collection(collection_id)
elif self.payload.get('action') == 'clear_search_index':
exp_services.clear_search_index()
elif self.payload.get('action') == 'save_config_properties':
new_config_property_values = self.payload.get(
'new_config_property_values')
logging.info('[ADMIN] %s saved config property values: %s' %
(self.user_id, new_config_property_values))
for (name, value) in new_config_property_values.iteritems():
config_services.set_property(self.user_id, name, value)
elif self.payload.get('action') == 'revert_config_property':
config_property_id = self.payload.get('config_property_id')
logging.info('[ADMIN] %s reverted config property: %s' %
(self.user_id, config_property_id))
config_services.revert_property(
self.user_id, config_property_id)
elif self.payload.get('action') == 'start_new_job':
for klass in jobs_registry.ONE_OFF_JOB_MANAGERS:
if klass.__name__ == self.payload.get('job_type'):
klass.enqueue(klass.create_new())
break
elif self.payload.get('action') == 'cancel_job':
job_id = self.payload.get('job_id')
job_type = self.payload.get('job_type')
for klass in jobs_registry.ONE_OFF_JOB_MANAGERS:
if klass.__name__ == job_type:
klass.cancel(job_id, self.user_id)
break
elif self.payload.get('action') == 'start_computation':
computation_type = self.payload.get('computation_type')
for klass in jobs_registry.ALL_CONTINUOUS_COMPUTATION_MANAGERS:
if klass.__name__ == computation_type:
klass.start_computation()
break
elif self.payload.get('action') == 'stop_computation':
computation_type = self.payload.get('computation_type')
for klass in jobs_registry.ALL_CONTINUOUS_COMPUTATION_MANAGERS:
if klass.__name__ == computation_type:
klass.stop_computation(self.user_id)
break
elif self.payload.get('action') == 'upload_topic_similarities':
data = self.payload.get('data')
recommendations_services.update_topic_similarities(data)
self.render_json({})
except Exception as e:
self.render_json({'error': unicode(e)})
raise
def test_get_topic_similarity(self):
self.assertEqual(recommendations_services.get_topic_similarity("Art", "Biology"), 0.1)
self.assertEqual(recommendations_services.get_topic_similarity("Art", "Art"), feconf.SAME_TOPIC_SIMILARITY)
self.assertEqual(
recommendations_services.get_topic_similarity("Topic 1", "Topic 2"), feconf.DEFAULT_TOPIC_SIMILARITY
)
self.assertEqual(recommendations_services.get_topic_similarity("Topic", "Topic"), feconf.SAME_TOPIC_SIMILARITY)
recommendations_services.update_topic_similarities(
"Art,Biology,Chemistry\n" "1.0,0.2,0.1\n" "0.2,1.0,0.8\n" "0.1,0.8,1.0"
)
self.assertEqual(recommendations_services.get_topic_similarity("Art", "Biology"), 0.2)
def test_get_topic_similarities_as_csv(self):
# The splitlines() is needed because a carriage return is added in
# the returned string
self.assertEqual(
recommendations_services.get_topic_similarities_as_csv().splitlines(),
self.TOPIC_SIMILARITIES_DEFAULT.splitlines())
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.2,1.0,0.8\n'
'0.1,0.8,1.0')
self.assertEqual(
recommendations_services.get_topic_similarities_as_csv().splitlines(),
self.TOPIC_SIMILARITIES_UPDATED.splitlines())
def test_get_topic_similarities_as_csv(self):
# The splitlines() is needed because a carriage return is added in
# the returned string
self.assertEqual(
recommendations_services.get_topic_similarities_as_csv().
splitlines(), self.TOPIC_SIMILARITIES_DEFAULT.splitlines())
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.2,1.0,0.8\n'
'0.1,0.8,1.0')
self.assertEqual(
recommendations_services.get_topic_similarities_as_csv().
splitlines(), self.TOPIC_SIMILARITIES_UPDATED.splitlines())
def test_get_topic_similarity(self):
self.assertEqual(recommendations_services.get_topic_similarity(
'Art', 'Biology'), 0.1)
self.assertEqual(recommendations_services.get_topic_similarity(
'Art', 'Art'), feconf.SAME_TOPIC_SIMILARITY)
self.assertEqual(recommendations_services.get_topic_similarity(
'Topic 1', 'Topic 2'), feconf.DEFAULT_TOPIC_SIMILARITY)
self.assertEqual(recommendations_services.get_topic_similarity(
'Topic', 'Topic'), feconf.SAME_TOPIC_SIMILARITY)
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.2,1.0,0.8\n'
'0.1,0.8,1.0')
self.assertEqual(recommendations_services.get_topic_similarity(
'Art', 'Biology'), 0.2)
def test_get_topic_similarity(self):
self.assertEqual(recommendations_services.get_topic_similarity(
'Art', 'Biology'), 0.1)
self.assertEqual(recommendations_services.get_topic_similarity(
'Art', 'Art'), feconf.SAME_TOPIC_SIMILARITY)
self.assertEqual(recommendations_services.get_topic_similarity(
'Topic 1', 'Topic 2'), feconf.DEFAULT_TOPIC_SIMILARITY)
self.assertEqual(recommendations_services.get_topic_similarity(
'Topic', 'Topic'), feconf.SAME_TOPIC_SIMILARITY)
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.2,1.0,0.8\n'
'0.1,0.8,1.0')
self.assertEqual(recommendations_services.get_topic_similarity(
'Art', 'Biology'), 0.2)
def post(self):
"""Handles POST requests."""
try:
result = {}
if self.payload.get('action') == 'reload_exploration':
exploration_id = self.payload.get('exploration_id')
self._reload_exploration(exploration_id)
elif self.payload.get('action') == 'reload_collection':
collection_id = self.payload.get('collection_id')
self._reload_collection(collection_id)
elif self.payload.get('action') == 'generate_dummy_explorations':
num_dummy_exps_to_generate = self.payload.get(
'num_dummy_exps_to_generate')
num_dummy_exps_to_publish = self.payload.get(
'num_dummy_exps_to_publish')
if not isinstance(num_dummy_exps_to_generate, int):
raise self.InvalidInputException(
'%s is not a number' % num_dummy_exps_to_generate)
elif not isinstance(num_dummy_exps_to_publish, int):
raise self.InvalidInputException('%s is not a number' %
num_dummy_exps_to_publish)
elif num_dummy_exps_to_generate < num_dummy_exps_to_publish:
raise self.InvalidInputException(
'Generate count cannot be less than publish count')
else:
self._generate_dummy_explorations(
num_dummy_exps_to_generate, num_dummy_exps_to_publish)
elif self.payload.get('action') == 'clear_search_index':
search_services.clear_collection_search_index()
search_services.clear_exploration_search_index()
elif (self.payload.get('action') ==
'generate_dummy_new_structures_data'):
self._load_dummy_new_structures_data()
elif self.payload.get('action') == (
'flush_migration_bot_contribution_data'):
user_services.flush_migration_bot_contributions_model()
elif self.payload.get('action') == 'save_config_properties':
new_config_property_values = self.payload.get(
'new_config_property_values')
logging.info('[ADMIN] %s saved config property values: %s' %
(self.user_id, new_config_property_values))
for (name, value) in new_config_property_values.items():
config_services.set_property(self.user_id, name, value)
elif self.payload.get('action') == 'revert_config_property':
config_property_id = self.payload.get('config_property_id')
logging.info('[ADMIN] %s reverted config property: %s' %
(self.user_id, config_property_id))
config_services.revert_property(self.user_id,
config_property_id)
elif self.payload.get('action') == 'start_new_job':
for klass in (jobs_registry.ONE_OFF_JOB_MANAGERS +
(jobs_registry.AUDIT_JOB_MANAGERS)):
if klass.__name__ == self.payload.get('job_type'):
klass.enqueue(klass.create_new())
break
elif self.payload.get('action') == 'cancel_job':
job_id = self.payload.get('job_id')
job_type = self.payload.get('job_type')
for klass in (jobs_registry.ONE_OFF_JOB_MANAGERS +
(jobs_registry.AUDIT_JOB_MANAGERS)):
if klass.__name__ == job_type:
klass.cancel(job_id, self.user_id)
break
elif self.payload.get('action') == 'start_computation':
computation_type = self.payload.get('computation_type')
for klass in jobs_registry.ALL_CONTINUOUS_COMPUTATION_MANAGERS:
if klass.__name__ == computation_type:
klass.start_computation()
break
elif self.payload.get('action') == 'stop_computation':
computation_type = self.payload.get('computation_type')
for klass in jobs_registry.ALL_CONTINUOUS_COMPUTATION_MANAGERS:
if klass.__name__ == computation_type:
klass.stop_computation(self.user_id)
break
elif self.payload.get('action') == 'upload_topic_similarities':
data = self.payload.get('data')
recommendations_services.update_topic_similarities(data)
elif self.payload.get('action') == (
'regenerate_topic_related_opportunities'):
topic_id = self.payload.get('topic_id')
opportunities_count = (
opportunity_services.
regenerate_opportunities_related_to_topic(
topic_id, delete_existing_opportunities=True))
result = {'opportunities_count': opportunities_count}
self.render_json(result)
except Exception as e:
self.render_json({'error': python_utils.UNICODE(e)})
raise
def post(self):
"""Handles POST requests."""
action = self.normalized_payload.get('action')
try:
result = {}
if action == 'reload_exploration':
exploration_id = self.normalized_payload.get('exploration_id')
self._reload_exploration(exploration_id)
elif action == 'reload_collection':
collection_id = self.normalized_payload.get('collection_id')
self._reload_collection(collection_id)
elif action == 'generate_dummy_explorations':
num_dummy_exps_to_generate = self.normalized_payload.get(
'num_dummy_exps_to_generate')
num_dummy_exps_to_publish = self.normalized_payload.get(
'num_dummy_exps_to_publish')
if num_dummy_exps_to_generate < num_dummy_exps_to_publish:
raise self.InvalidInputException(
'Generate count cannot be less than publish count')
else:
self._generate_dummy_explorations(
num_dummy_exps_to_generate, num_dummy_exps_to_publish)
elif action == 'clear_search_index':
search_services.clear_collection_search_index()
search_services.clear_exploration_search_index()
elif action == 'generate_dummy_new_structures_data':
self._load_dummy_new_structures_data()
elif action == 'generate_dummy_new_skill_data':
self._generate_dummy_skill_and_questions()
elif action == 'save_config_properties':
new_config_property_values = self.normalized_payload.get(
'new_config_property_values')
logging.info('[ADMIN] %s saved config property values: %s' %
(self.user_id, new_config_property_values))
for (name, value) in new_config_property_values.items():
config_services.set_property(self.user_id, name, value)
elif action == 'revert_config_property':
config_property_id = self.normalized_payload.get(
'config_property_id')
logging.info('[ADMIN] %s reverted config property: %s' %
(self.user_id, config_property_id))
config_services.revert_property(self.user_id,
config_property_id)
elif action == 'upload_topic_similarities':
data = self.normalized_payload.get('data')
recommendations_services.update_topic_similarities(data)
elif action == 'regenerate_topic_related_opportunities':
topic_id = self.normalized_payload.get('topic_id')
opportunities_count = (
opportunity_services.
regenerate_opportunities_related_to_topic(
topic_id, delete_existing_opportunities=True))
result = {'opportunities_count': opportunities_count}
elif action == 'update_feature_flag_rules':
feature_name = self.normalized_payload.get('feature_name')
new_rule_dicts = self.normalized_payload.get('new_rules')
commit_message = self.normalized_payload.get('commit_message')
try:
feature_services.update_feature_flag_rules(
feature_name, self.user_id, commit_message,
new_rule_dicts)
except (utils.ValidationError,
feature_services.FeatureFlagNotFoundException) as e:
raise self.InvalidInputException(e)
logging.info('[ADMIN] %s updated feature %s with new rules: '
'%s.' %
(self.user_id, feature_name, new_rule_dicts))
self.render_json(result)
except Exception as e:
logging.exception('[ADMIN] %s', e)
self.render_json({'error': python_utils.UNICODE(e)})
python_utils.reraise_exception()
def test_update_topic_similarities(self):
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.2,1.0,0.8\n'
'0.1,0.8,1.0')
with self.assertRaisesRegexp(
Exception,
('Length of topic similarities columns: 2 does not match '
'length of topic list: 3.')):
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.2,1.0,0.8')
with self.assertRaisesRegexp(
Exception,
('Length of topic similarities rows: 2 does not match '
'length of topic list: 3.')):
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.2,1.0\n'
'0.1,0.8,1.0')
with self.assertRaisesRegexp(
ValueError,
'Expected similarity to be between 0.0 and 1.0, received 800'):
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.2,1.0,800\n'
'0.1,0.8,1.0')
with self.assertRaisesRegexp(
ValueError,
'Expected similarity to be a float, received string'):
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'string,0.2,0.1\n'
'0.2,1.0,0.8\n'
'0.1,0.8,1.0')
with self.assertRaisesRegexp(
Exception, 'Topic Fake Topic not in list of known topics.'):
recommendations_services.update_topic_similarities(
'Fake Topic,Biology,Chemistry\n'
'string,0.2,0.1\n'
'0.2,1.0,0.8\n'
'0.1,0.8,1.0')
with self.assertRaisesRegexp(
Exception, 'Expected topic similarities to be symmetric.'):
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.3,1.0,0.8\n'
'0.8,0.1,1.0')
def test_update_topic_similarities(self):
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.2,1.0,0.8\n'
'0.1,0.8,1.0')
with self.assertRaisesRegexp(
Exception,
'Length of topic similarities columns does not match topic list.'
):
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.2,1.0,0.8')
with self.assertRaisesRegexp(
Exception,
'Length of topic similarities rows does not match topic list.'
):
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.2,1.0\n'
'0.1,0.8,1.0')
with self.assertRaisesRegexp(
ValueError,
'Expected similarity to be between 0.0 and 1.0, received 800'
):
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.2,1.0,800\n'
'0.1,0.8,1.0')
with self.assertRaisesRegexp(
ValueError,
'Expected similarity to be a float, received string'
):
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'string,0.2,0.1\n'
'0.2,1.0,0.8\n'
'0.1,0.8,1.0')
with self.assertRaisesRegexp(
Exception, 'Topic Fake Topic not in list of known topics.'
):
recommendations_services.update_topic_similarities(
'Fake Topic,Biology,Chemistry\n'
'string,0.2,0.1\n'
'0.2,1.0,0.8\n'
'0.1,0.8,1.0')
with self.assertRaisesRegexp(
Exception, 'Expected topic similarities to be symmetric.'
):
recommendations_services.update_topic_similarities(
'Art,Biology,Chemistry\n'
'1.0,0.2,0.1\n'
'0.3,1.0,0.8\n'
'0.8,0.1,1.0')
def post(self):
"""Handles POST requests."""
try:
result = {}
if self.payload.get('action') == 'reload_exploration':
exploration_id = self.payload.get('exploration_id')
self._reload_exploration(exploration_id)
elif self.payload.get('action') == 'reload_collection':
collection_id = self.payload.get('collection_id')
self._reload_collection(collection_id)
elif self.payload.get('action') == 'generate_dummy_explorations':
num_dummy_exps_to_generate = self.payload.get(
'num_dummy_exps_to_generate')
num_dummy_exps_to_publish = self.payload.get(
'num_dummy_exps_to_publish')
if not isinstance(num_dummy_exps_to_generate, int):
raise self.InvalidInputException(
'%s is not a number' % num_dummy_exps_to_generate)
elif not isinstance(num_dummy_exps_to_publish, int):
raise self.InvalidInputException('%s is not a number' %
num_dummy_exps_to_publish)
elif num_dummy_exps_to_generate < num_dummy_exps_to_publish:
raise self.InvalidInputException(
'Generate count cannot be less than publish count')
else:
self._generate_dummy_explorations(
num_dummy_exps_to_generate, num_dummy_exps_to_publish)
elif self.payload.get('action') == 'clear_search_index':
search_services.clear_collection_search_index()
search_services.clear_exploration_search_index()
elif (self.payload.get('action') ==
'generate_dummy_new_structures_data'):
self._load_dummy_new_structures_data()
elif (self.payload.get('action') == 'generate_dummy_new_skill_data'
):
self._generate_dummy_skill_and_questions()
elif self.payload.get('action') == 'save_config_properties':
new_config_property_values = self.payload.get(
'new_config_property_values')
logging.info('[ADMIN] %s saved config property values: %s' %
(self.user_id, new_config_property_values))
for (name, value) in new_config_property_values.items():
config_services.set_property(self.user_id, name, value)
elif self.payload.get('action') == 'revert_config_property':
config_property_id = self.payload.get('config_property_id')
logging.info('[ADMIN] %s reverted config property: %s' %
(self.user_id, config_property_id))
config_services.revert_property(self.user_id,
config_property_id)
elif self.payload.get('action') == 'start_new_job':
for klass in (jobs_registry.ONE_OFF_JOB_MANAGERS +
(jobs_registry.AUDIT_JOB_MANAGERS)):
if klass.__name__ == self.payload.get('job_type'):
klass.enqueue(klass.create_new())
break
elif self.payload.get('action') == 'cancel_job':
job_id = self.payload.get('job_id')
job_type = self.payload.get('job_type')
for klass in (jobs_registry.ONE_OFF_JOB_MANAGERS +
(jobs_registry.AUDIT_JOB_MANAGERS)):
if klass.__name__ == job_type:
klass.cancel(job_id, self.user_id)
break
elif self.payload.get('action') == 'start_computation':
computation_type = self.payload.get('computation_type')
for klass in jobs_registry.ALL_CONTINUOUS_COMPUTATION_MANAGERS:
if klass.__name__ == computation_type:
klass.start_computation()
break
elif self.payload.get('action') == 'stop_computation':
computation_type = self.payload.get('computation_type')
for klass in jobs_registry.ALL_CONTINUOUS_COMPUTATION_MANAGERS:
if klass.__name__ == computation_type:
klass.stop_computation(self.user_id)
break
elif self.payload.get('action') == 'upload_topic_similarities':
data = self.payload.get('data')
recommendations_services.update_topic_similarities(data)
elif self.payload.get('action') == (
'regenerate_topic_related_opportunities'):
topic_id = self.payload.get('topic_id')
opportunities_count = (
opportunity_services.
regenerate_opportunities_related_to_topic(
topic_id, delete_existing_opportunities=True))
result = {'opportunities_count': opportunities_count}
elif self.payload.get('action') == 'update_feature_flag_rules':
feature_name = self.payload.get('feature_name')
new_rule_dicts = self.payload.get('new_rules')
commit_message = self.payload.get('commit_message')
if not isinstance(feature_name, python_utils.BASESTRING):
raise self.InvalidInputException(
'feature_name should be string, received \'%s\'.' %
(feature_name))
elif not isinstance(commit_message, python_utils.BASESTRING):
raise self.InvalidInputException(
'commit_message should be string, received \'%s\'.' %
(commit_message))
elif (not isinstance(new_rule_dicts, list) or not all([
isinstance(rule_dict, dict)
for rule_dict in new_rule_dicts
])):
raise self.InvalidInputException(
'new_rules should be a list of dicts, received'
' \'%s\'.' % new_rule_dicts)
try:
feature_services.update_feature_flag_rules(
feature_name, self.user_id, commit_message,
new_rule_dicts)
except (utils.ValidationError,
feature_services.FeatureFlagNotFoundException) as e:
raise self.InvalidInputException(e)
logging.info('[ADMIN] %s updated feature %s with new rules: '
'%s.' %
(self.user_id, feature_name, new_rule_dicts))
self.render_json(result)
except Exception as e:
logging.error('[ADMIN] %s', e)
self.render_json({'error': python_utils.UNICODE(e)})
python_utils.reraise_exception()
def test_update_topic_similarities(self):
recommendations_services.update_topic_similarities(
"Art,Biology,Chemistry\n" "1.0,0.2,0.1\n" "0.2,1.0,0.8\n" "0.1,0.8,1.0"
)
with self.assertRaisesRegexp(Exception, "Length of topic similarities columns does not" " match topic list."):
recommendations_services.update_topic_similarities("Art,Biology,Chemistry\n" "1.0,0.2,0.1\n" "0.2,1.0,0.8")
with self.assertRaisesRegexp(Exception, "Length of topic similarities rows does not match" " topic list."):
recommendations_services.update_topic_similarities(
"Art,Biology,Chemistry\n" "1.0,0.2,0.1\n" "0.2,1.0\n" "0.1,0.8,1.0"
)
with self.assertRaisesRegexp(ValueError, "Expected similarity to be between 0.0 and 1.0," " received 800"):
recommendations_services.update_topic_similarities(
"Art,Biology,Chemistry\n" "1.0,0.2,0.1\n" "0.2,1.0,800\n" "0.1,0.8,1.0"
)
with self.assertRaisesRegexp(ValueError, "Expected similarity to be a float, received" " string"):
recommendations_services.update_topic_similarities(
"Art,Biology,Chemistry\n" "string,0.2,0.1\n" "0.2,1.0,0.8\n" "0.1,0.8,1.0"
)
with self.assertRaisesRegexp(Exception, "Topic Fake Topic not in list of known topics."):
recommendations_services.update_topic_similarities(
"Fake Topic,Biology,Chemistry\n" "string,0.2,0.1\n" "0.2,1.0,0.8\n" "0.1,0.8,1.0"
)
with self.assertRaisesRegexp(Exception, "Expected topic similarities to be symmetric."):
recommendations_services.update_topic_similarities(
"Art,Biology,Chemistry\n" "1.0,0.2,0.1\n" "0.3,1.0,0.8\n" "0.8,0.1,1.0"
)