def _prepare_and_launch_sync_burst(self):
"""
Private method to launch a dummy burst. Return the burst loaded after the launch finished
as well as the workflow steps that initially formed the burst.
NOTE: the burst launched by this method is a `dummy` one, meaning we do not use an actual
simulation, but instead test adapters.
"""
burst_config = TestFactory.store_burst(self.test_project.id)
workflow_step_list = []
stored_dt = datatypes_factory.DatatypesFactory()._store_datatype(
Datatype1())
first_step_algorithm = self.flow_service.get_algorithm_by_module_and_class(
"tvb.tests.framework.adapters.testadapter1",
"TestAdapterDatatypeInput")
metadata = {DataTypeMetaData.KEY_BURST: burst_config.id}
kwargs = {"test_dt_input": stored_dt.gid, 'test_non_dt_input': '0'}
operations, group = self.operation_service.prepare_operations(
self.test_user.id, self.test_project, first_step_algorithm,
first_step_algorithm.algorithm_category, metadata, **kwargs)
### Now fire the workflow and also update and store the burst configuration ##
self.operation_service.launch_operation(operations[0].id, False)
loaded_burst, _ = self.burst_service.load_burst(burst_config.id)
import_operation = dao.get_operation_by_id(stored_dt.fk_from_operation)
dao.remove_entity(import_operation.__class__, import_operation.id)
dao.remove_datatype(stored_dt.gid)
return loaded_burst, workflow_step_list
def remove_datatype(self, project_id, datatype_gid, skip_validation=False):
"""
Method used for removing a dataType. If the given dataType is a DatatypeGroup
or a dataType from a DataTypeGroup than this method will remove the entire group.
The operation(s) used for creating the dataType(s) will also be removed.
"""
datatype = dao.get_datatype_by_gid(datatype_gid)
if datatype is None:
self.logger.warning(
"Attempt to delete DT[%s] which no longer exists." %
datatype_gid)
return
is_datatype_group = False
if dao.is_datatype_group(datatype_gid):
is_datatype_group = True
elif datatype.fk_datatype_group is not None:
is_datatype_group = True
datatype = dao.get_datatype_by_id(datatype.fk_datatype_group)
operations_set = [datatype.fk_from_operation]
correct = True
if is_datatype_group:
self.logger.debug("Removing datatype group %s" % datatype)
data_list = dao.get_datatypes_from_datatype_group(datatype.id)
for adata in data_list:
self._remove_project_node_files(project_id, adata.gid,
skip_validation)
if adata.fk_from_operation not in operations_set:
operations_set.append(adata.fk_from_operation)
datatype_group = dao.get_datatype_group_by_gid(datatype.gid)
dao.remove_datatype(datatype_gid)
correct = correct and dao.remove_entity(
model.OperationGroup, datatype_group.fk_operation_group)
else:
self.logger.debug("Removing datatype %s" % datatype)
self._remove_project_node_files(project_id, datatype.gid,
skip_validation)
## Remove Operation entity in case no other DataType needs them.
project = dao.get_project_by_id(project_id)
for operation_id in operations_set:
dependent_dt = dao.get_generic_entity(model.DataType, operation_id,
"fk_from_operation")
if len(dependent_dt) > 0:
### Do not remove Operation in case DataType still exist referring it.
continue
correct = correct and dao.remove_entity(model.Operation,
operation_id)
## Make sure Operation folder is removed
self.structure_helper.remove_operation_data(
project.name, datatype.fk_from_operation)
if not correct:
raise RemoveDataTypeException("Could not remove DataType " +
str(datatype_gid))
def remove_datatype(self, project_id, datatype_gid, skip_validation=False):
"""
Method used for removing a dataType. If the given dataType is a DatatypeGroup
or a dataType from a DataTypeGroup than this method will remove the entire group.
The operation(s) used for creating the dataType(s) will also be removed.
"""
datatype = dao.get_datatype_by_gid(datatype_gid)
if datatype is None:
self.logger.warning("Attempt to delete DT[%s] which no longer exists." % datatype_gid)
return
user = dao.get_user_for_datatype(datatype.id)
freed_space = datatype.disk_size or 0
is_datatype_group = False
if dao.is_datatype_group(datatype_gid):
is_datatype_group = True
freed_space = dao.get_datatype_group_disk_size(datatype.id)
elif datatype.fk_datatype_group is not None:
is_datatype_group = True
datatype = dao.get_datatype_by_id(datatype.fk_datatype_group)
freed_space = dao.get_datatype_group_disk_size(datatype.id)
operations_set = [datatype.fk_from_operation]
correct = True
if is_datatype_group:
self.logger.debug("Removing datatype group %s" % datatype)
data_list = dao.get_datatypes_from_datatype_group(datatype.id)
for adata in data_list:
self._remove_project_node_files(project_id, adata.gid, skip_validation)
if adata.fk_from_operation not in operations_set:
operations_set.append(adata.fk_from_operation)
datatype_group = dao.get_datatype_group_by_gid(datatype.gid)
dao.remove_datatype(datatype_gid)
correct = correct and dao.remove_entity(model.OperationGroup, datatype_group.fk_operation_group)
else:
self.logger.debug("Removing datatype %s" % datatype)
self._remove_project_node_files(project_id, datatype.gid, skip_validation)
## Remove Operation entity in case no other DataType needs them.
project = dao.get_project_by_id(project_id)
for operation_id in operations_set:
dependent_dt = dao.get_generic_entity(model.DataType, operation_id, "fk_from_operation")
if len(dependent_dt) > 0:
### Do not remove Operation in case DataType still exist referring it.
continue
correct = correct and dao.remove_entity(model.Operation, operation_id)
## Make sure Operation folder is removed
self.structure_helper.remove_operation_data(project.name, datatype.fk_from_operation)
if not correct:
raise RemoveDataTypeException("Could not remove DataType " + str(datatype_gid))
user.used_disk_space = user.used_disk_space - freed_space
dao.store_entity(user)
def _prepare_and_launch_sync_burst(self):
"""
Private method to launch a dummy burst. Return the burst loaded after the launch finished
as well as the workflow steps that initially formed the burst.
NOTE: the burst launched by this method is a `dummy` one, meaning we do not use an actual
simulation, but instead test adapters.
"""
burst_config = TestFactory.store_burst(self.test_project.id)
workflow_step_list = []
test_portlet = dao.get_portlet_by_identifier(self.PORTLET_ID)
stored_dt = datatypes_factory.DatatypesFactory()._store_datatype(Datatype1())
first_step_algorithm = self.flow_service.get_algorithm_by_module_and_class(
"tvb.tests.framework.adapters.testadapter1", "TestAdapterDatatypeInput")
metadata = {DataTypeMetaData.KEY_BURST: burst_config.id}
kwargs = {"test_dt_input": stored_dt.gid, 'test_non_dt_input': '0'}
operations, group = self.operation_service.prepare_operations(self.test_user.id, self.test_project.id,
first_step_algorithm,
first_step_algorithm.algorithm_category,
metadata, **kwargs)
view_step = TestFactory.create_workflow_step("tvb.tests.framework.adapters.testadapter2", "TestAdapter2",
{"test2": 2}, {}, 0, 0, 0, 0, is_view_step=True)
view_step.fk_portlet = test_portlet.id
workflow_step_list.append(view_step)
workflows = self.workflow_service.create_and_store_workflow(self.test_project.id, burst_config.id, 0,
first_step_algorithm.id, operations)
self.operation_service.prepare_operations_for_workflowsteps(workflow_step_list, workflows, self.test_user.id,
burst_config.id, self.test_project.id, group,
operations)
### Now fire the workflow and also update and store the burst configuration ##
self.operation_service.launch_operation(operations[0].id, False)
loaded_burst, _ = self.burst_service.load_burst(burst_config.id)
import_operation = dao.get_operation_by_id(stored_dt.fk_from_operation)
dao.remove_entity(import_operation.__class__, import_operation.id)
dao.remove_datatype(stored_dt.gid)
return loaded_burst, workflow_step_list
def remove_datatype(self, skip_validation=False):
"""
Perform basic operation, should overwrite in specific implementations.
"""
dao.remove_datatype(self.handled_datatype.gid)
