def import_course(bundle, repo_id, user_id, static_dir):
"""
Import a course from an XBundle object.
Args:
bundle (xbundle.XBundle): Course as xbundle XML
repo_id (int): Primary key of repository course belongs to
user_id (int): Primary key of Django user doing the import
static_dir (unicode): location of static files
Returns:
learningresources.models.Course
"""
src = bundle.course
course = create_course(
org=src.attrib["org"],
repo_id=repo_id,
course_number=src.attrib["course"],
run=src.attrib["semester"],
user_id=user_id,
)
import_static_assets(course, static_dir)
import_children(course, src, None, '')
populate_xanalytics_fields.delay(course.id)
# This triggers a bulk indexing of all LearningResource instances
# for the course at once.
index_resources(
get_resources(repo_id).filter(course__id=course.id))
return course
def test_index_exception(self):
"""
Ensure that an exception is thrown if we have not indexed properly.
"""
# Delete the index
remove_index()
search_url = "/api/v1/repositories/{repo}/search/".format(
repo=self.repo.slug)
with self.assertRaises(ReindexException):
self.client.get(search_url)
# Create a mapping
with self.assertRaises(ReindexException):
# Mapping doesn't exist yet
get_conn()
conn = get_conn(verify=False)
conn.indices.create(INDEX_NAME)
conn.indices.refresh()
create_mapping()
resp = self.client.get(search_url)
self.assertEqual(resp.status_code, HTTP_200_OK)
self.assertEqual(json.loads(resp.content.decode('utf-8'))['count'], 0)
# Reindex all resources
resource_ids = LearningResource.objects.values_list("id", flat=True)
index_resources(resource_ids)
resp = self.client.get(search_url)
self.assertEqual(resp.status_code, HTTP_200_OK)
self.assertEqual(
json.loads(resp.content.decode('utf-8'))['count'],
len(resource_ids))
def import_course(bundle, repo_id, user_id, static_dir):
"""
Import a course from an XBundle object.
Args:
bundle (xbundle.XBundle): Course as xbundle XML
repo_id (int): Primary key of repository course belongs to
user_id (int): Primary key of Django user doing the import
static_dir (unicode): location of static files
Returns:
learningresources.models.Course
"""
src = bundle.course
course = create_course(
org=src.attrib["org"],
repo_id=repo_id,
course_number=src.attrib["course"],
run=src.attrib["semester"],
user_id=user_id,
)
import_static_assets(course, static_dir)
import_children(course, src, None, '')
populate_xanalytics_fields.delay(course.id)
# This triggers a bulk indexing of all LearningResource instances
# for the course at once.
index_resources(
get_resources(repo_id).filter(course__id=course.id).values_list(
"id", flat=True))
return course
def handle_m2m_save(sender, **kwargs):
"""Update index when taxonomies are updated."""
from search.search_indexes import get_vocabs
instance = kwargs.pop("instance")
if instance.__class__.__name__ != "LearningResource":
return
# Update cache for the LearningResource if it's already set.
get_vocabs(instance.id)
# Update Elasticsearch index:
from search.utils import index_resources
index_resources([instance.id])
def handle_resource_update(sender, **kwargs):
"""Update index when a LearningResource is updated."""
if kwargs["created"]:
# Don't index upon create because we handle this in bulk
# in the importer, the only place we allow creation to happen.
return
instance = kwargs.pop("instance")
if instance.__class__.__name__ != "LearningResource":
return
from search.utils import index_resources
index_resources([instance.id])
def handle_resource_update(sender, **kwargs):
"""Update index when a LearningResource is updated."""
if kwargs["created"]:
# Don't index upon create because we handle this in bulk
# in the importer, the only place we allow creation to happen.
return
instance = kwargs.pop("instance")
if instance.__class__.__name__ != "LearningResource":
return
from search.utils import index_resources
index_resources([instance.id])
def handle_m2m_save(sender, **kwargs):
"""Update index when taxonomies are updated."""
from search.search_indexes import get_vocabs
instance = kwargs.pop("instance")
if instance.__class__.__name__ != "LearningResource":
return
# Update cache for the LearningResource if it's already set.
get_vocabs(instance.id)
# Update Elasticsearch index:
from search.utils import index_resources
index_resources([instance.id])
def test_index_exception(self):
"""
Ensure that an exception is thrown if we have not indexed properly.
"""
# Delete the index
remove_index()
search_url = "/api/v1/repositories/{repo}/search/".format(
repo=self.repo.slug
)
with self.assertRaises(ReindexException):
self.client.get(search_url)
# Create a mapping
with self.assertRaises(ReindexException):
# Mapping doesn't exist yet
get_conn()
conn = get_conn(verify=False)
conn.indices.create(INDEX_NAME)
conn.indices.refresh()
create_mapping()
resp = self.client.get(search_url)
self.assertEqual(resp.status_code, HTTP_200_OK)
self.assertEqual(json.loads(resp.content.decode('utf-8'))['count'], 0)
# Reindex all resources
resource_ids = LearningResource.objects.values_list("id", flat=True)
index_resources(resource_ids)
resp = self.client.get(search_url)
self.assertEqual(resp.status_code, HTTP_200_OK)
self.assertEqual(
json.loads(resp.content.decode('utf-8'))['count'],
len(resource_ids)
)
def test_sorting(self):
"""Test sorting for search"""
# remove the default resource to control the environment
self.resource.delete()
# create some resources
res1 = self.create_resource(**dict(resource_type="example",
title="silly example 1",
content_xml="<blah>blah 1</blah>",
mpath="/blah1",
xa_nr_views=1001,
xa_nr_attempts=99,
xa_avg_grade=9.9))
res2 = self.create_resource(**dict(resource_type="example",
title="silly example 2",
content_xml="<blah>blah 2</blah>",
mpath="/blah2",
xa_nr_views=1003,
xa_nr_attempts=98,
xa_avg_grade=6.8))
res3 = self.create_resource(**dict(resource_type="example",
title="silly example 3",
content_xml="<blah>blah 3</blah>",
mpath="/blah3",
xa_nr_views=1002,
xa_nr_attempts=101,
xa_avg_grade=7.3))
res4 = self.create_resource(**dict(resource_type="example",
title="silly example 4",
content_xml="<blah>blah 4</blah>",
mpath="/blah3",
xa_nr_views=1003,
xa_nr_attempts=101,
xa_avg_grade=9.9))
index_resources([res1.id, res2.id, res3.id, res4.id])
refresh_index()
self.assertEqual(self.count_results(), 4)
# sorting by number of views
results = self.search(query=None,
sorting="-{0}".format(
LoreSortingFields.SORT_BY_NR_VIEWS[0]))
# expected position res2, res4
top_res = results[0]
sec_res = results[1]
self.assertEqual(top_res.id, res2.id)
self.assertEqual(sec_res.id, res4.id)
# sorting by number of attempts
results = self.search(query=None,
sorting="-{0}".format(
LoreSortingFields.SORT_BY_NR_ATTEMPTS[0]))
# expected position res3, res4
top_res = results[0]
sec_res = results[1]
self.assertEqual(top_res.id, res3.id)
self.assertEqual(sec_res.id, res4.id)
# sorting by average grade
results = self.search(query=None,
sorting="-{0}".format(
LoreSortingFields.SORT_BY_AVG_GRADE[0]))
# expected position res1, res4
top_res = results[0]
sec_res = results[1]
self.assertEqual(top_res.id, res1.id)
self.assertEqual(sec_res.id, res4.id)
def test_sorting(self):
"""Test sorting for search"""
# remove the default resource to control the environment
self.resource.delete()
# create some resources
res1 = self.create_resource(**dict(
resource_type="example",
title="silly example 1",
content_xml="<blah>blah 1</blah>",
mpath="/blah1",
xa_nr_views=1001,
xa_nr_attempts=99,
xa_avg_grade=9.9
))
res2 = self.create_resource(**dict(
resource_type="example",
title="silly example 2",
content_xml="<blah>blah 2</blah>",
mpath="/blah2",
xa_nr_views=1003,
xa_nr_attempts=98,
xa_avg_grade=6.8
))
res3 = self.create_resource(**dict(
resource_type="example",
title="silly example 3",
content_xml="<blah>blah 3</blah>",
mpath="/blah3",
xa_nr_views=1002,
xa_nr_attempts=101,
xa_avg_grade=7.3
))
res4 = self.create_resource(**dict(
resource_type="example",
title="silly example 4",
content_xml="<blah>blah 4</blah>",
mpath="/blah3",
xa_nr_views=1003,
xa_nr_attempts=101,
xa_avg_grade=9.9
))
index_resources([res1.id, res2.id, res3.id, res4.id])
refresh_index()
self.assertEqual(self.count_results(), 4)
# sorting by number of views
results = self.search(
query=None,
sorting="-{0}".format(LoreSortingFields.SORT_BY_NR_VIEWS[0])
)
# expected position res2, res4
top_res = results[0]
sec_res = results[1]
self.assertEqual(
top_res.id,
res2.id
)
self.assertEqual(
sec_res.id,
res4.id
)
# sorting by number of attempts
results = self.search(
query=None,
sorting="-{0}".format(LoreSortingFields.SORT_BY_NR_ATTEMPTS[0])
)
# expected position res3, res4
top_res = results[0]
sec_res = results[1]
self.assertEqual(
top_res.id,
res3.id
)
self.assertEqual(
sec_res.id,
res4.id
)
# sorting by average grade
results = self.search(
query=None,
sorting="-{0}".format(LoreSortingFields.SORT_BY_AVG_GRADE[0])
)
# expected position res1, res4
top_res = results[0]
sec_res = results[1]
self.assertEqual(
top_res.id,
res1.id
)
self.assertEqual(
sec_res.id,
res4.id
)
def handle(self, *args, **options):
"""Refreshes the Elasticsearch index."""
create_mapping()
index_resources(LearningResource.objects.values_list("id", flat=True))
