def create(self, validated_data, **kwargs):
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:
workflow_obj.delete()
return None
# 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:
workflow_obj.delete()
return None
# 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:
workflow_obj.delete()
return None
# 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()
return workflow_obj
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
def create(self, validated_data, **kwargs):
"""Create the new workflow."""
wflow_name = self.context.get('name')
if not wflow_name:
wflow_name = self.validated_data.get('name')
if not wflow_name:
raise Exception(_('Unexpected empty workflow name.'))
if Workflow.objects.filter(name=wflow_name,
user=self.context['user']).exists():
raise Exception(
_('There is a workflow with this name. ' +
'Please provide a workflow name in the import page.'))
# Initial values
workflow_obj = None
try:
workflow_obj = Workflow(
user=self.context['user'],
name=wflow_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():
columns = 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 any(col.position == 0 for col in columns):
for idx, col in enumerate(columns):
col.position = idx + 1
col.save()
# Load the data frame
data_frame = validated_data.get('data_frame')
if data_frame is not None:
# Store the table in the DB
store_table(
data_frame,
workflow_obj.get_data_frame_table_name(),
dtype={
col.name: col.data_type
for col in workflow_obj.columns.all()
},
)
# Reconcile now the information in workflow and columns with
# the one loaded
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,
'columns': columns
})
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,
'columns': columns
})
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.id:
workflow_obj.delete()
raise
return workflow_obj