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
def workflow_delete_column(
workflow: Workflow,
column: Column,
cond_to_delete: Optional[List[Condition]] = None,
):
"""Remove column from workflow.
Given a workflow and a column, removes it from the workflow (and the
corresponding data frame
:param workflow: Workflow object
:param column: Column object to delete
:param cond_to_delete: List of conditions to delete after removing the
column
:return: Nothing. Effect reflected in the database
"""
# Drop the column from the DB table storing the data frame
df_drop_column(workflow.get_data_frame_table_name(), column.name)
# Reposition the columns above the one being deleted
workflow.reposition_columns(column.position, workflow.ncols + 1)
# Delete the column
column.delete()
# Update the information in the workflow
workflow.ncols = workflow.ncols - 1
workflow.save()
if not cond_to_delete:
# The conditions to delete are not given, so calculate them
# Get the conditions/actions attached to this workflow
cond_to_delete = [
cond
for cond in Condition.objects.filter(action__workflow=workflow, )
if column in cond.columns.all()
]
# If a column disappears, the conditions that contain that variable
# are removed
actions_without_filters = []
for condition in cond_to_delete:
if condition.is_filter:
actions_without_filters.append(condition.action)
# Formula has the name of the deleted column. Delete it
condition.delete()
# Traverse the actions for which the filter has been deleted and reassess
# all their conditions
# TODO: Explore how to do this asynchronously (or lazy)
map(lambda act: act.update_n_rows_selected(), actions_without_filters)
# If a column disappears, the views that contain only that column need to
# disappear as well as they are no longer relevant.
for view in workflow.views.all():
if view.columns.count() == 0:
view.delete()
