def execute(self, net, color_descriptor, active_tokens, service_interfaces):
operation_id = self.args['operation_id']
op = factory.load_operation(net, operation_id)
parallel_size = color_descriptor.group.size
workflow_data = io.extract_workflow_data(net, active_tokens)
parallel_id = _parallel_id_from_workflow_data(workflow_data)
parent_parallel_id = parallel_id.parent_identifier
for property_name in op.output_properties:
array_value = self.collect_array_output(net=net,
operation=op,
parallel_size=parallel_size,
property_name=property_name,
parallel_id=parent_parallel_id)
op.store_output(property_name, value=array_value,
parallel_id=parent_parallel_id)
workflow_data['parallel_id'] = list(parent_parallel_id)
token = net.create_token(color=color_descriptor.group.parent_color,
color_group_idx=color_descriptor.group.parent_color_group_idx,
data={'workflow_data': workflow_data})
return [token], defer.succeed(None)
def write_outputs(self, net, operation_id, output_properties, outputs_file):
if outputs_file:
op = factory.load_operation(net=net, operation_id=operation_id)
outputs = op.load_outputs(parallel_id=ParallelIdentifier())
with open(outputs_file, 'w') as f:
json.dump(outputs, f)
def converge_inputs(self, net, parallel_id):
operation = factory.load_operation(net, self.args['operation_id'])
inputs = operation.load_inputs(parallel_id=parallel_id)
return order_outputs(inputs,
input_property_order=self.args['input_property_order'],
output_properties=self.args['output_properties'])
def _load_operation(self, net_key, operation_id):
cache_key = (net_key, int(operation_id))
if cache_key not in self._cached_operations:
self._cached_operations[cache_key] = load_operation(
net=Net(self._connection, key=net_key), operation_id=operation_id
)
return self._cached_operations[cache_key]
def write_inputs(file_object, net, parallel_id, operation_id):
operation = factory.load_operation(net, operation_id)
inputs = operation.load_inputs(parallel_id)
LOG.debug("Inputs: %s", inputs)
json.dump(inputs, file_object)
file_object.flush()
def create_operation(self, operation_id, name, **kwargs):
fop = future_operation.FutureOperation(
operation_class='direct_storage',
operation_id=operation_id,
name=name,
parent=future_operation.NullFutureOperation(),
log_dir='/exciting/log/dir',
**kwargs)
fop.save(self.net)
return factory.load_operation(self.net, operation_id)
def execute(self, net, color_descriptor, active_tokens, service_interfaces):
workflow_data = io.extract_workflow_data(net, active_tokens)
parallel_property = self.args['parallel_property']
parallel_id = _parallel_id_from_workflow_data(workflow_data)
operation = factory.load_operation(net=net,
operation_id=self.args['operation_id'])
parallel_input = operation.load_input(
name=parallel_property,
parallel_id=parallel_id)
self.store_parallel_input(operation=operation,
parallel_input=parallel_input,
parallel_property=parallel_property,
parallel_id=parallel_id)
tokens = self._create_tokens(num_tokens=len(parallel_input),
color_descriptor=color_descriptor,
workflow_data=workflow_data, net=net)
return tokens, defer.succeed(None)
def _get_operation(self, net):
return factory.load_operation(net, self.args['operation_id'])