def test_validate_table(self):
"""Test that an instance of DataTransformations is blocked when the table parameter is invalid
"""
with self.assertRaises(LookupError):
DatasetTransformations(INVALID_TABLE)
with self.assertRaises(TypeError):
DatasetTransformations({"dimensions": True})
def dataset_transformations(connector: NomisApiConnector, exists: bool,
data: Tuple[pyjstat.Dataset, List[str]]) -> None:
"""
Function containing the dataset transformation operations.
:param connector: An open, initialised instance of `NomisApiConnector`.
:param exists: A bool indicating whether or not the dataset currently exists; if `True`, then the function will
handle for updating an existing dataset. Conversely, the function will create a new dataset if exists is
`False`.
:param data: A tuple containing the required data. That is, a pyjstat dataset corresponding with the query made to
cantabular, and the list of variables to be assigned to the dataset.
"""
logger.info("Commencing dataset transformations.")
table, variables = data
# Check variables against known geographies. If geography then remove from list and make key.
geography_variables = config.get_geography()
key = None
geography_flag = False
table_geography = None
for variable in variables:
if variable in geography_variables:
geography_flag = True
key = variable
table_geography = copy.deepcopy(table)
del table["dimension"][variable]
table["id"].remove(variable)
variables.remove(variable)
# If no variables are geography then make first variable key
if geography_flag is False:
key = variables[0]
transformations = DatasetTransformations(table, geography_flag,
table_geography)
# Create the dataset if it doesn't exist, otherwise retrieve the non-assigned variables
if not exists:
non_assigned_variables = variables
create_dataset(connector, transformations)
handle_variables(connector, transformations, non_assigned_variables)
else:
are_dimensions_same = check_dataset_dimensions(connector, variables)
if are_dimensions_same is False:
raise KeyError(
"ERROR: Dimensions are not the same as existing dataset.")
handle_dimensions(connector, transformations, key)
handle_observations(connector, transformations)
def setUp(self) -> None:
"""Set up a valid instance of DatasetTransformation."""
self.valid_dataset_transformations = DatasetTransformations(
VALID_TABLE)