def _test_calculator(self):
self.dframe = self.dataset.dframe()
columns = self.dframe.columns.tolist()
self.start_num_cols = len(columns)
self.added_num_cols = 0
column_labels_to_slugs = {
column_attrs[Dataset.LABEL]: (column_name) for
(column_name, column_attrs) in self.dataset.schema.items()
}
self.label_list, self.slugified_key_list = [
list(ary) for ary in zip(*column_labels_to_slugs.items())
]
for idx, formula in enumerate(self.calculations):
name = 'test-%s' % idx
self.parser.validate_formula(formula)
calculator = Calculator(self.dataset)
calculation = Calculation()
calculation.save(self.dataset, formula, name, self.group)
calculator.calculate_columns([calculation])
self.column_labels_to_slugs = self.dataset.schema.labels_to_slugs
self._test_calculation_results(name, formula)
def calculate_task(calculations, dataset):
"""Background task to run a calculation.
Set calculation to failed and raise if an exception occurs.
:param calculation: Calculation to run.
:param dataset: Dataset to run calculation on.
"""
# block until other calculations for this dataset are finished
calculations[0].restart_if_has_pending(dataset, calculations[1:])
calculator = Calculator(dataset)
calculator.calculate_columns(calculations)
for calculation in calculations:
calculation.add_dependencies(dataset, calculator.dependent_columns)
if calculation.aggregation is not None:
aggregated_id = dataset.aggregated_datasets_dict[calculation.group]
calculation.set_aggregation_id(aggregated_id)
calculation.ready()
