def workflow_restrict_column(column: Column) -> Optional[str]:
"""Set category of the column to the existing set of values.
Given a workflow and a column, modifies the column so that only the
values already present are allowed for future updates.
:param column: Column object to restrict
:return: String with error or None if correct
"""
# Load the data frame
data_frame = load_table(column.workflow.get_data_frame_table_name())
cat_values = set(data_frame[column.name].dropna())
if not cat_values:
# Column has no meaningful values. Nothing to do.
return _('Column has no meaningful values')
# Set categories
column.set_categories(list(cat_values))
column.save()
# Re-evaluate the operands in the workflow
column.workflow.set_query_builder_ops()
column.workflow.save()
# Correct execution
return None
def create(self, validated_data, **kwargs):
# Preliminary checks
data_type = validated_data.get('data_type', None)
if data_type is None or \
data_type not in pandas_datatype_names.values():
# The data type is not legal
raise Exception(_('Incorrect data type {0}.').format(data_type))
column_obj = None
try:
# Create the object, but point to the given workflow
column_obj = Column(
name=validated_data['name'],
description_text=validated_data.get('description_text', ''),
workflow=self.context['workflow'],
data_type=data_type,
is_key=validated_data.get('is_key', False),
position=validated_data.get('position', 0),
in_viz=validated_data.get('in_viz', True),
active_from=validated_data.get('active_from', None),
active_to=validated_data.get('active_to', None),
)
# Set the categories if they exists
column_obj.set_categories(validated_data.get('categories', []),
True)
if column_obj.active_from and column_obj.active_to and \
column_obj.active_from > column_obj.active_to:
raise Exception(
_('Incorrect date/times in the active window for '
'column {0}').format(validated_data['name']))
# TODO: Fix the position field when creating the columns
# All tests passed, proceed to save the object.
column_obj.save()
except Exception as e:
if column_obj:
column_obj.delete()
raise e
return column_obj