code: def load(self, name, *, arguments=None, validate_arguments=True, strict_dag=False):
          
          arguments = {} if arguments is None else arguments
  
          try:
              workflow_module = importlib.import_module(name)
  
              dag_present = False
  
              # extract objects of specific types from the workflow module
              for key, obj in workflow_module.__dict__.items():
                  if isinstance(obj, Dag):
                      self._dags_blueprint[obj.name] = obj
                      dag_present = True
                  elif isinstance(obj, Parameters):
                      self._parameters.extend(obj)
  
              self._name = name
              self._docstring = inspect.getdoc(workflow_module)
              del sys.modules[name]
  
              if strict_dag and not dag_present:
                  raise WorkflowImportError(
                      'Workflow does not include a dag {}'.format(name))
  
              if validate_arguments:
                  missing_parameters = self._parameters.check_missing(arguments)
                  if len(missing_parameters) > 0:
                      raise WorkflowArgumentError(
                          'The following parameters are required ' +
                          'by the workflow, but are missing: {}'.format(
                              ', '.join(missing_parameters)))
  
              self._provided_arguments = arguments
  
          except (TypeError, ImportError):
              logger.error('Cannot import workflow {}'.format(name))
              raise WorkflowImportError('Cannot import workflow {}'.format(name))
docs: Import the workflow script and load all known objects.
  
          The workflow script is treated like a module and imported
          into the Python namespace. After the import, the method looks
          for instances of known classes and stores a reference for further
          use in the workflow object.
  
          Args:
              name (str): The name of the workflow script.
              arguments (dict): Dictionary of additional arguments that are ingested
                                into the data store prior to the execution of the workflow.
              validate_arguments (bool): Whether to check that all required arguments have
                                         been supplied.
              strict_dag (bool): If true then the loaded workflow module must contain an
                                 instance of Dag.
  
          Raises:
              WorkflowArgumentError: If the workflow requires arguments to be set that
                                     were not supplied to the workflow.
              WorkflowImportError: If the import of the workflow fails.