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_recommendations_after_changes_in_rights(self):
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'])
rights_manager.unpublish_exploration(self.ADMIN_ID, 'exp_id_4')
ModifiedExplorationRecommendationsAggregator.stop_computation(
self.ADMIN_ID)
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_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_recommendations_after_changes_in_rights(self):
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'])
rights_manager.unpublish_exploration(self.admin_id, 'exp_id_4')
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_2', 'exp_id_3'])
def test_recommendations_after_changes_in_rights(self):
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'])
rights_manager.unpublish_exploration(self.admin_id, 'exp_id_4')
ModifiedExplorationRecommendationsAggregator.stop_computation(
self.admin_id)
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_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_recommendations_after_changes_in_rights(self):
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'])
rights_manager.unpublish_exploration(self.admin, 'exp_id_4')
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_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 test_get_and_set_exploration_recommendations(self):
recommended_exp_ids = ["exp_id_2", "exp_id_3"]
recommendations_services.set_recommendations("exp_id_1", recommended_exp_ids)
saved_recommendation_ids = recommendations_services.get_exploration_recommendations("exp_id_1")
self.assertEqual(recommended_exp_ids, saved_recommendation_ids)
recommended_exp_ids = ["exp_id_3"]
recommendations_services.set_recommendations("exp_id_1", recommended_exp_ids)
saved_recommendation_ids = recommendations_services.get_exploration_recommendations("exp_id_1")
self.assertEqual(recommended_exp_ids, saved_recommendation_ids)
def test_get_and_set_exploration_recommendations(self):
recommended_exp_ids = ['exp_id_2', 'exp_id_3']
recommendations_services.set_recommendations('exp_id_1',
recommended_exp_ids)
saved_recommendation_ids = (
recommendations_services.get_exploration_recommendations(
'exp_id_1'))
self.assertEqual(recommended_exp_ids, saved_recommendation_ids)
recommended_exp_ids = ['exp_id_3']
recommendations_services.set_recommendations('exp_id_1',
recommended_exp_ids)
saved_recommendation_ids = (
recommendations_services.get_exploration_recommendations(
'exp_id_1'))
self.assertEqual(recommended_exp_ids, saved_recommendation_ids)
def test_recommendations_with_invalid_exploration_summaries_would_be_empty(
self):
def _mock_get_non_private_exploration_summaries():
"""Return an invalid exploration summary dict."""
return {'new_exp_id': 'new_exploration_summary'}
with self.swap(
jobs_registry, 'ONE_OFF_JOB_MANAGERS',
self.ONE_OFF_JOB_MANAGERS_FOR_TESTS
):
# We need to swap here to make the recommendations an empty list
# (since 'get_exploration_recommendations()' returns a list of ids
# of at most 10 recommended explorations to play after completing
# the exploration).
with self.swap(
exp_services, 'get_non_private_exploration_summaries',
_mock_get_non_private_exploration_summaries):
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, [])
def test_get_and_set_exploration_recommendations(self):
recommended_exp_ids = ['exp_id_2', 'exp_id_3']
recommendations_services.set_recommendations(
'exp_id_1', recommended_exp_ids)
saved_recommendation_ids = (
recommendations_services.get_exploration_recommendations(
'exp_id_1'))
self.assertEqual(recommended_exp_ids, saved_recommendation_ids)
recommended_exp_ids = ['exp_id_3']
recommendations_services.set_recommendations(
'exp_id_1', recommended_exp_ids)
saved_recommendation_ids = (
recommendations_services.get_exploration_recommendations(
'exp_id_1'))
self.assertEqual(recommended_exp_ids, saved_recommendation_ids)
def get(self, exploration_id):
"""Handles GET requests."""
self.values.update({
'recommended_exp_ids': (
recommendations_services.get_exploration_recommendations(
exploration_id))
})
self.render_json(self.values)
def get(self, exploration_id):
"""Handles GET requests."""
self.values.update({
'recommended_exp_ids': (
recommendations_services.get_exploration_recommendations(
exploration_id))
})
self.render_json(self.values)
def get(self, exploration_id):
"""Handles GET requests."""
collection_id = self.request.get('collection_id')
include_system_recommendations = self.request.get(
'include_system_recommendations')
try:
author_recommended_exp_ids = json.loads(
self.request.get('stringified_author_recommended_ids'))
except Exception:
raise self.PageNotFoundException
auto_recommended_exp_ids = []
if self.user_id and collection_id:
next_exp_ids_in_collection = (
collection_services.
get_next_exploration_ids_to_complete_by_user( # pylint: disable=line-too-long
self.user_id, collection_id))
auto_recommended_exp_ids = list(
set(next_exp_ids_in_collection) -
set(author_recommended_exp_ids))
else:
next_exp_ids_in_collection = []
if collection_id:
collection = collection_services.get_collection_by_id(
collection_id)
next_exp_ids_in_collection = (
collection.get_next_exploration_ids_in_sequence(
exploration_id))
if next_exp_ids_in_collection:
auto_recommended_exp_ids = list(
set(next_exp_ids_in_collection) -
set(author_recommended_exp_ids))
elif include_system_recommendations:
system_chosen_exp_ids = (
recommendations_services.get_exploration_recommendations(
exploration_id))
filtered_exp_ids = list(
set(system_chosen_exp_ids) -
set(author_recommended_exp_ids))
auto_recommended_exp_ids = random.sample(
filtered_exp_ids,
min(MAX_SYSTEM_RECOMMENDATIONS, len(filtered_exp_ids)))
self.values.update({
'summaries':
(summary_services.get_displayable_exp_summary_dicts_matching_ids(
author_recommended_exp_ids + auto_recommended_exp_ids)),
})
self.render_json(self.values)
def get(self, exploration_id):
"""Handles GET requests."""
collection_id = self.request.get('collection_id')
include_system_recommendations = self.request.get(
'include_system_recommendations')
try:
author_recommended_exp_ids = json.loads(self.request.get(
'stringified_author_recommended_ids'))
except Exception:
raise self.PageNotFoundException
auto_recommended_exp_ids = []
if self.user_id and collection_id:
next_exp_ids_in_collection = (
collection_services.get_next_exploration_ids_to_complete_by_user( # pylint: disable=line-too-long
self.user_id, collection_id))
auto_recommended_exp_ids = list(
set(next_exp_ids_in_collection) -
set(author_recommended_exp_ids))
else:
next_exp_ids_in_collection = []
if collection_id:
collection = collection_services.get_collection_by_id(
collection_id)
next_exp_ids_in_collection = (
collection.get_next_exploration_ids_in_sequence(
exploration_id))
if next_exp_ids_in_collection:
auto_recommended_exp_ids = list(
set(next_exp_ids_in_collection) -
set(author_recommended_exp_ids))
elif include_system_recommendations:
system_chosen_exp_ids = (
recommendations_services.get_exploration_recommendations(
exploration_id))
filtered_exp_ids = list(
set(system_chosen_exp_ids) -
set(author_recommended_exp_ids))
auto_recommended_exp_ids = random.sample(
filtered_exp_ids,
min(MAX_SYSTEM_RECOMMENDATIONS, len(filtered_exp_ids)))
self.values.update({
'summaries': (
summary_services.get_displayable_exp_summary_dicts_matching_ids(
author_recommended_exp_ids + auto_recommended_exp_ids)),
})
self.render_json(self.values)
def get(self, exploration_id):
"""Handles GET requests."""
collection_id = self.request.get('collection_id')
recommended_exp_ids = []
if self.user_id and collection_id:
recommended_exp_ids = (
collection_services.
get_next_exploration_ids_to_complete_by_user(
self.user_id, collection_id))
else:
recommended_exp_ids = (
recommendations_services.get_exploration_recommendations(
exploration_id))
self.values.update({'recommended_exp_ids': recommended_exp_ids})
self.render_json(self.values)
def get(self, exploration_id):
"""Handles GET requests."""
collection_id = self.request.get('collection_id')
recommended_exp_ids = []
if self.user_id and collection_id:
recommended_exp_ids = (
collection_services.get_next_exploration_ids_to_complete_by_user(
self.user_id, collection_id))
else:
recommended_exp_ids = (
recommendations_services.get_exploration_recommendations(
exploration_id))
self.values.update({
'recommended_exp_ids': recommended_exp_ids
})
self.render_json(self.values)
