def execute(self, net, color_descriptor, active_tokens, service_interfaces):
workflow_data = io.extract_workflow_data(net, active_tokens)
parallel_id = ParallelIdentifier(workflow_data.get('parallel_id', []))
outputs = self.converge_inputs(net=net, parallel_id=parallel_id)
io.store_outputs(net=net, operation_id=self.args['operation_id'],
outputs=outputs, parallel_id=list(parallel_id))
output_token = net.create_token(color=color_descriptor.color,
color_group_idx=color_descriptor.group.idx,
data={'workflow_data': workflow_data})
return [output_token], defer.succeed(None)
def store_outputs_then_load_inputs(self, store_parallel_id,
load_parallel_id):
spi = ParallelIdentifier(store_parallel_id)
lpi = ParallelIdentifier(load_parallel_id)
outputs = {
'bar1': 'value A',
'bar2': 'value B'
}
input_connections = {
self.output_operation_id: {
'foo1': 'bar1',
'foo2': 'bar2',
}
}
io.store_outputs(net=self.net, operation_id=self.output_operation_id,
outputs=outputs, parallel_id=spi)
expected_inputs = {
'foo1': 'value A',
'foo2': 'value B',
}
self.assertEqual(expected_inputs, io.load_inputs(net=self.net,
input_connections=input_connections, parallel_id=lpi))
def read_and_store_outputs(file_obj, net, operation_id, parallel_id):
outputs = json.load(file_obj)
io.store_outputs(net=net, operation_id=operation_id, outputs=outputs, parallel_id=parallel_id)
