def test_run_executes_the_query_and_caches_the_results(self):
""" Verify that run executes the query and caches the results."""
course_1 = CourseFactory()
run_1 = CourseRunFactory(title='foo',
pacing_type='self_paced',
hidden=True,
course=course_1)
run_2 = CourseRunFactory(title='foo',
pacing_type='self_paced',
hidden=True,
course=course_1)
course_2 = CourseFactory()
run_3 = CourseRunFactory(title='foo',
pacing_type='instructor_paced',
hidden=False,
course=course_2)
CourseRunFactory(title='bar',
pacing_type='instructor_paced',
hidden=False,
course=course_2)
queryset = DistinctCountsSearchQuerySet(
index=CourseRunDocument._index._name).filter('term', title='foo')
queryset.aggregation_key = 'aggregation_key'
facet_field = 'pacing_type'
agg_filter = ESDSLQ('match_all')
agg = TermsFacet(field=facet_field)
queryset.aggs.bucket('_filter_' + facet_field,
'filter',
filter=agg_filter).bucket(facet_field,
agg.get_aggregation())
queryset.aggs.bucket('_query_{0}'.format('hidden'),
'filter',
filter=ESDSLQ('bool',
filter=ESDSLQ('term', hidden=True)))
assert queryset._distinct_result_count is None
assert not hasattr(self, '_response')
queryset.execute()
expected_results = sorted([run_1.key, run_2.key, run_3.key])
actual_results = sorted([run.key for run in queryset._response.hits])
assert queryset._distinct_result_count == 2
assert queryset._response.hits.total['value'] == 3
assert expected_results == actual_results
facet_counts = queryset._response.facets
for field_val, count, distinct_count in facet_counts['fields'][
'pacing_type']:
assert field_val in {'self_paced', 'instructor_paced'}
if field_val == 'self_paced':
assert count == 2 and distinct_count == 1
elif field_val == 'instructor_paced':
assert count == 1 and distinct_count == 1
count, distinct_count = facet_counts['queries']['hidden']
assert count == 2 and distinct_count == 1
def test_get_distinct_count_runs_query_when_cache_empty(self):
""" Verify that distinct_count runs the query and caches/returns the distinct_count."""
course = CourseFactory()
CourseRunFactory(title='foo', course=course)
CourseRunFactory(title='foo', course=course)
queryset = DistinctCountsSearchQuerySet(
index=CourseRunDocument._index._name).filter('term', title='foo')
queryset.aggregation_key = 'aggregation_key'
assert queryset._distinct_result_count is None
assert queryset.distinct_count() == 1
assert queryset._distinct_result_count == 1
def test_clone_with_different_class(self):
""" Verify that clone does not copy aggregation_key and distinct_result_count when using different class."""
queryset = DistinctCountsSearchQuerySet()
facet_field = 'pacing_type'
agg_filter = ESDSLQ('match_all')
agg = TermsFacet(field=facet_field)
queryset.aggs.bucket('_filter_' + facet_field,
'filter',
filter=agg_filter).bucket(facet_field,
agg.get_aggregation())
queryset.aggregation_key = 'aggregation_key'
queryset._distinct_result_count = 123
clone = queryset._clone(klass=Search)
assert isinstance(clone, Search)
assert queryset.to_dict() == clone.to_dict()
assert not hasattr(clone, 'aggregation_key')
assert not hasattr(clone, '_distinct_result_count')
def test_clone(self):
""" Verify that clone copies all fields, including the aggregation_key and distinct_hit_count."""
queryset = DistinctCountsSearchQuerySet()
facet_field = 'pacing_type'
agg_filter = ESDSLQ('match_all')
agg = TermsFacet(field=facet_field)
queryset.aggs.bucket('_filter_' + facet_field,
'filter',
filter=agg_filter).bucket(facet_field,
agg.get_aggregation())
queryset.aggregation_key = 'aggregation_key'
queryset._distinct_result_count = 123
clone = queryset._clone()
assert queryset.to_dict() == clone.to_dict()
assert queryset.aggregation_key == clone.aggregation_key
assert queryset._distinct_result_count == clone._distinct_result_count
def test_validate_raises_when_configured_with_facet_with_unsupported_options(
self):
""" Verify that validate raises when Query configured with facet with unsupported options."""
# The add date facet action on DistinctCountsSearchQuerySet raises when unsupported options are passed,
# so configure a field facet with those options on a normal FacetedSearch or Search and then clone
# it to a DistinctCountsSearchQuery.
queryset = DistinctCountsSearchQuerySet(
index=CourseRunDocument._index._name)
facet_field = 'pacing_type'
agg_filter = ESDSLQ('match_all')
agg = TermsFacet(field=facet_field, order='term')
queryset.aggs.bucket('_filter_' + facet_field,
'filter',
filter=agg_filter).bucket(facet_field,
agg.get_aggregation())
queryset = queryset._clone(klass=DistinctCountsSearchQuerySet)
queryset.aggregation_key = 'aggregation_key'
with pytest.raises(RuntimeError) as err:
queryset.validate()
assert 'only supports a limited set of field facet options' in str(
err.value)
def test_run_handles_pagination(self):
""" Verify that run supports paginated queries. """
course_1 = CourseFactory()
for _ in range(5):
CourseRunFactory(title='foo', course=course_1)
queryset = DistinctCountsSearchQuerySet(
index=CourseRunDocument._index._name).filter('term', title='foo')
queryset.aggregation_key = 'aggregation_key'
queryset.execute()
all_results = queryset._response.hits
assert len(all_results) == 5
del queryset._response
queryset = queryset.query().extra(from_=1, size=2)
queryset.execute()
paginated_results = queryset._response.hits
assert len(paginated_results) == 2
expected = sorted([run.key for run in all_results[1:3]])
actual = sorted([run.key for run in paginated_results])
assert expected == actual
