def infer_dataset(self):
user_dataset = self.user.dataset
collection_dataset = self.collection.dataset
if user_dataset != collection_dataset:
raise KolibriValidationError(
"Collection and user for a Membership object must be in same dataset."
)
return user_dataset
def infer_dataset(self):
user_dataset = self.user.dataset
collection_dataset = self.collection.dataset
if user_dataset != collection_dataset:
raise KolibriValidationError(
"The collection and user for a Role object must be in the same dataset."
)
return user_dataset
def ensure_dataset(self, *args, **kwargs):
"""
If no dataset has yet been specified, try to infer it. If a dataset has already been specified, to prevent
inconsistencies, make sure it matches the inferred dataset, otherwise raise a ``KolibriValidationError``.
If we have no dataset and it can't be inferred, we raise a ``KolibriValidationError`` exception as well.
"""
inferred_dataset = self.infer_dataset(*args, **kwargs)
if self.dataset_id:
# make sure currently stored dataset matches inferred dataset, if any
if inferred_dataset and inferred_dataset != self.dataset:
raise KolibriValidationError("This model is not associated with the correct FacilityDataset.")
else:
# use the inferred dataset, if there is one, otherwise throw an error
if inferred_dataset:
self.dataset = inferred_dataset
else:
raise KolibriValidationError("FacilityDataset ('dataset') not provided, and could not be inferred.")