def _get_relevance(
category: diagnostic_pb2.DiagnosticCategory, project: scoring.ScoringProject) \
-> Tuple['diagnostic_pb2.CategoryRelevance', Set[str]]:
try:
if project.check_filters(category.filters):
return diagnostic_pb2.NEEDS_ATTENTION, set()
missing_fields: Set[str] = set()
except scoring.NotEnoughDataException as err:
# We don't have enough info about this category for the project,
# so we let the relevance model decide.
missing_fields = err.fields
return _get_relevance_from_its_model(category, project,
bool(missing_fields)), missing_fields
def _get_relevance(
main_challenge: diagnostic_pb2.DiagnosticMainChallenge, project: scoring.ScoringProject,
should_be_neutral: bool) \
-> Tuple['diagnostic_pb2.MainChallengeRelevance.V', Set[str]]:
try:
if project.check_filters(main_challenge.filters):
if should_be_neutral:
return diagnostic_pb2.NEUTRAL_RELEVANCE, set()
return diagnostic_pb2.NEEDS_ATTENTION, set()
missing_fields: Set[str] = set()
except scoring.NotEnoughDataException as err:
# We don't have enough info about this main challenge for the project,
# so we let the relevance model decide.
missing_fields = err.fields
return _get_relevance_from_its_model(main_challenge, project,
bool(missing_fields),
should_be_neutral), missing_fields