text: import os
  import inspect
  from typing import Dict, Any, Type, Set
  from functools import reduce
  
  from ..base import VersionedYAMLParser
  from ....executors import BaseExecutor, get_default_metas
  from ....executors.compound import CompoundExecutor
  
  
  class LegacyParser(VersionedYAMLParser):
      """Legacy parser for executor."""
      version = 'legacy'  # the version number this parser designed for
  
      @staticmethod
      def _get_all_arguments(class_):
          """
  
          :param class_: target class from which we want to retrieve arguments
          :return: all the arguments of all the classes from which `class_` inherits
          """
          def get_class_arguments(class_):
              """
              :param class_: the class to check
              :return: a list containing the arguments from `class_`
              """
              signature = inspect.signature(class_.__init__)
              class_arguments = [p.name for p in signature.parameters.values()]
              return class_arguments
  
          def accumulate_classes(cls) -> Set[Type]:
              """
              :param cls: the class to check
              :return: all classes from which cls inherits from
              """
              def _accumulate_classes(c, cs):
                  cs.append(c)
                  if cls == object:
                      return cs
                  for base in c.__bases__:
                      _accumulate_classes(base, cs)
                  return cs
              
              classes = []
              _accumulate_classes(cls, classes)
              return set(classes)
  
          all_classes = accumulate_classes(class_)
          args = list(map(lambda x: get_class_arguments(x), all_classes))
          return set(reduce(lambda x,y: x+y,args))
  
      @staticmethod
      def _get_dump_path_from_config(meta_config: Dict):
          if 'name' in meta_config:
              work_dir = meta_config['workspace']
              name = meta_config['name']
              pea_id = meta_config['pea_id']
              if work_dir:
                  # then try to see if it can be loaded from its regular expected workspace (ref_indexer)
                  dump_path = BaseExecutor.get_shard_workspace(work_dir, name, pea_id)
                  bin_dump_path = os.path.join(dump_path, f'{name}.bin')
                  if os.path.exists(bin_dump_path):
                      return bin_dump_path
  
              root_work_dir = meta_config['root_workspace']
              root_name = meta_config['root_name']
              if root_name != name:
                  # try to load from the corresponding file as if it was a CompoundExecutor, if the `.bin` does not exist,
                  # we should try to see if from its workspace can be loaded as it may be a `ref_indexer`
                  compound_work_dir = CompoundExecutor.get_component_workspace_from_compound_workspace(root_work_dir,
                                                                                                       root_name,
                                                                                                       pea_id)
                  dump_path = BaseExecutor.get_shard_workspace(compound_work_dir, name, pea_id)
                  bin_dump_path = os.path.join(dump_path, f'{name}.{"bin"}')
                  if os.path.exists(bin_dump_path):
                      return bin_dump_path
  
      def parse(self, cls: Type['BaseExecutor'], data: Dict) -> 'BaseExecutor':
          """
          :param cls: target class type to parse into, must be a :class:`JAMLCompatible` type
          :param data: flow yaml file loaded as python dict
          :return: the Flow YAML parser given the syntax version number
          """
          _meta_config = get_default_metas()
          _meta_config.update(data.get('metas', {}))
          if _meta_config:
              data['metas'] = _meta_config
  
          dump_path = self._get_dump_path_from_config(data.get('metas', {}))
          load_from_dump = False
          if dump_path:
              obj = cls.load(dump_path)
              obj.logger.success(f'restore {cls.__name__} from {dump_path}')
              # consider the case where `dump_path` is not based on `obj.workspace`. This is needed
              # for
              workspace_loaded_from = data.get('metas', {})['workspace']
              workspace_in_dump = getattr(obj, 'workspace', None)
              if workspace_in_dump != workspace_loaded_from:
                  obj.workspace = workspace_loaded_from
              load_from_dump = True
          else:
              cls._init_from_yaml = True
  
              if cls.store_args_kwargs:
                  p = data.get('with', {})  # type: Dict[str, Any]
                  a = p.pop('args') if 'args' in p else ()
                  k = p.pop('kwargs') if 'kwargs' in p else {}
                  # maybe there are some hanging kwargs in "parameters"
                  # tmp_a = (expand_env_var(v) for v in a)
                  # tmp_p = {kk: expand_env_var(vv) for kk, vv in {**k, **p}.items()}
                  tmp_a = a
                  tmp_p = {kk: vv for kk, vv in {**k, **p}.items()}
                  obj = cls(*tmp_a, **tmp_p, metas=data.get('metas', {}), requests=data.get('requests', {}))
              else:
                  # tmp_p = {kk: expand_env_var(vv) for kk, vv in data.get('with', {}).items()}
                  obj = cls(**data.get('with', {}), metas=data.get('metas', {}), requests=data.get('requests', {}))
              cls._init_from_yaml = False
  
              # check if the yaml file used to instanciate 'cls' has arguments that are not in 'cls'
              arguments_from_cls = LegacyParser._get_all_arguments(cls)
              arguments_from_yaml = set(data.get('with', {}))
              difference_set = arguments_from_yaml  - arguments_from_cls
              if any(difference_set):
                  obj.logger.warning(f'The arguments {difference_set} defined in the YAML are not expected in the '
                                     f'class {cls.__name__}')
  
              obj.logger.success(f'successfully built {cls.__name__} from a yaml config')
  
          # if node.tag in {'!CompoundExecutor'}:
          #     os.environ['JINA_WARN_UNNAMED'] = 'YES'
  
          if not _meta_config:
              obj.logger.warning(
                  '"metas" config is not found in this yaml file, '
                  'this map is important as it provides an unique identifier when '
                  'persisting the executor on disk.')
  
          # for compound executor
          if not load_from_dump and 'components' in data:
              obj.components = lambda: data['components']
  
          obj.is_updated = False
          return obj
  
      def dump(self, data: 'BaseExecutor') -> Dict:
          """
          :param data: versioned executor object
          :return: the dictionary given a versioned flow object
          """
          # note: we only save non-default property for the sake of clarity
          _defaults = get_default_metas()
          p = {k: getattr(data, k) for k, v in _defaults.items() if getattr(data, k) != v}
          a = {k: v for k, v in data._init_kwargs_dict.items() if k not in _defaults}
          r = {}
          if a:
              r['with'] = a
          if p:
              r['metas'] = p
  
          if hasattr(data, '_drivers'):
              r['requests'] = {'on': data._drivers}
  
          if hasattr(data, 'components'):
              r['components'] = data.components
          return r
  