def detach_dataframe(workflow):
"""
Given a workflow object, delete its dataframe
:param workflow:
:return: Nothing, the workflow object is updated
"""
pandas_db.delete_table(workflow.id)
# Delete number of rows and columns
workflow.nrows = 0
workflow.ncols = 0
workflow.n_filterd_rows = -1
workflow.save()
# Delete the column_names, column_types and column_unique
Column.objects.filter(workflow__id=workflow.id).delete()
# Delete the info for QueryBuilder
workflow.set_query_builder_ops()
# Table name
workflow.data_frame_table_name = ''
# Save the workflow with the new fields.
workflow.save()
def delete(request, pk):
workflow = get_workflow(request, pk)
if not workflow:
# Workflow is not accessible. Go back to index page.
return JsonResponse({
'form_is_valid': True,
'html_redirect': reverse('workflow:index')
})
# Ajax result
data = dict()
# If the request is not done by the user, flat the error
if workflow.user != request.user:
messages.error(request,
_('You can only delete workflows that you created.'))
if request.is_ajax():
data['form_is_valid'] = True
data['html_redirect'] = reverse('workflow:index')
return JsonResponse(data)
return redirect('workflow:index')
if request.method == 'POST':
# Log the event
Log.objects.register(request.user, Log.WORKFLOW_DELETE, workflow, {
'id': workflow.id,
'name': workflow.name
})
# And drop the table
if pandas_db.is_wf_table_in_db(workflow):
pandas_db.delete_table(pk)
# Perform the delete operation
workflow.delete()
# In this case, the form is valid anyway
data['form_is_valid'] = True
data['html_redirect'] = reverse('workflow:index')
else:
data['html_form'] = \
render_to_string('workflow/includes/partial_workflow_delete.html',
{'workflow': workflow},
request=request)
return JsonResponse(data)
def flush_workflow(workflow):
"""
Flush all the data from the workflow and propagate changes throughout the
relations with columns, conditions, filters, etc. These steps require:
1) Delete the data frame from the database
2) Delete all the columns attached to the workflow
3) Delete all the conditions attached to the actions
4) Reflect the number of selected columns to -1 for all actions
:param workflow: Workflow object
:return: Reflected in the DB
"""
# Step 1: Delete the data frame from the database
pandas_db.delete_table(workflow.id)
# Reset some of the workflow fields
workflow.nrows = 0
workflow.ncols = 0
workflow.n_filterd_rows = -1
workflow.set_query_builder_ops()
workflow.data_frame_table_name = ''
# Step 2: Delete the column_names, column_types and column_unique
Column.objects.filter(workflow__id=workflow.id).delete()
# Step 3: Delete the conditions attached to all the actions attached to the
# workflow.
Condition.objects.filter(action__workflow=workflow).delete()
# Step 4: Reset selected columns from all actions
for action in Action.objects.filter(workflow=workflow):
action.n_selected_rows = -1
action.save()
# Save the workflow with the new fields.
workflow.save()
def flush(self):
"""
Flush all the data from the workflow and propagate changes throughout the
relations with columns, conditions, filters, etc. These steps require:
1) Delete the data frame from the database
2) Delete all the columns attached to the workflow
3) Delete all the conditions attached to the actions
4) Delete all the views attached to the workflow
:return: Reflected in the DB
"""
# Step 1: Delete the data frame from the database
pandas_db.delete_table(self.id)
# Reset some of the workflow fields
self.nrows = 0
self.ncols = 0
self.n_filterd_rows = -1
self.set_query_builder_ops()
self.data_frame_table_name = ''
# Step 2: Delete the column_names, column_types and column_unique
self.columns.all().delete()
# Step 3: Delete the conditions attached to all the actions attached
# to the workflow.
self.actions.all().delete()
# Step 4: Delete all the views attached to the workflow
self.views.all().delete()
# Save the workflow with the new fields.
self.save()
def create(self, validated_data, **kwargs):
# Initial values
workflow_obj = None
try:
workflow_obj = Workflow(
user=self.context['user'],
name=self.context['name'],
description_text=validated_data['description_text'],
nrows=0,
ncols=0,
attributes=validated_data['attributes'],
query_builder_ops=validated_data.get('query_builder_ops', {}))
workflow_obj.save()
# Create the columns
column_data = ColumnSerializer(data=validated_data.get(
'columns', []),
many=True,
context={'workflow': workflow_obj})
# And save its content
if column_data.is_valid():
column_data.save()
else:
raise Exception('Unable to save column information')
# If there is any column with position = 0, recompute (this is to
# guarantee backward compatibility.
if workflow_obj.columns.filter(position=0).exists():
for idx, c in enumerate(workflow_obj.columns.all()):
c.position = idx + 1
c.save()
# Load the data frame
data_frame = validated_data.get('data_frame', None)
if data_frame is not None:
ops.store_dataframe_in_db(data_frame, workflow_obj.id)
# Reconcile now the information in workflow and columns with the
# one loaded
workflow_obj.data_frame_table_name = \
pandas_db.create_table_name(workflow_obj.pk)
workflow_obj.ncols = validated_data['ncols']
workflow_obj.nrows = validated_data['nrows']
workflow_obj.save()
# Create the actions pointing to the workflow
action_data = ActionSerializer(data=validated_data.get(
'actions', []),
many=True,
context={'workflow': workflow_obj})
if action_data.is_valid():
action_data.save()
else:
raise Exception('Unable to save column information')
# Create the views pointing to the workflow
view_data = ViewSerializer(data=validated_data.get('views', []),
many=True,
context={'workflow': workflow_obj})
if view_data.is_valid():
view_data.save()
else:
raise Exception('Unable to save column information')
except Exception:
# Get rid of the objects created
if workflow_obj:
if workflow_obj.has_data_frame():
pandas_db.delete_table(workflow_obj.id)
if workflow_obj.id:
workflow_obj.delete()
raise
return workflow_obj
