def _deserialize(cls, encoded_var: Any) -> Any: # pylint: disable=too-many-return-statements
"""Helper function of depth first search for deserialization."""
# JSON primitives (except for dict) are not encoded.
if cls._is_primitive(encoded_var):
return encoded_var
elif isinstance(encoded_var, list):
return [cls._deserialize(v) for v in encoded_var]
if not isinstance(encoded_var, dict):
raise ValueError(
f"The encoded_var should be dict and is {type(encoded_var)}")
var = encoded_var[Encoding.VAR]
type_ = encoded_var[Encoding.TYPE]
if type_ == DAT.DICT:
return {k: cls._deserialize(v) for k, v in var.items()}
elif type_ == DAT.DAG:
return SerializedDAG.deserialize_dag(var)
elif type_ == DAT.OP:
return SerializedBaseOperator.deserialize_operator(var)
elif type_ == DAT.DATETIME:
return pendulum.from_timestamp(var)
elif type_ == DAT.POD:
if not HAS_KUBERNETES:
raise RuntimeError(
"Cannot deserialize POD objects without kubernetes libraries installed!"
)
pod = PodGenerator.deserialize_model_dict(var)
return pod
elif type_ == DAT.TIMEDELTA:
return datetime.timedelta(seconds=var)
elif type_ == DAT.TIMEZONE:
return Timezone(var)
elif type_ == DAT.RELATIVEDELTA:
if 'weekday' in var:
var['weekday'] = relativedelta.weekday(
*var['weekday']) # type: ignore
return relativedelta.relativedelta(**var)
elif type_ == DAT.SET:
return {cls._deserialize(v) for v in var}
elif type_ == DAT.TUPLE:
return tuple([cls._deserialize(v) for v in var])
else:
raise TypeError(
'Invalid type {!s} in deserialization.'.format(type_))
def _deserialize(cls, encoded_var: Any) -> Any:
"""Helper function of depth first search for deserialization."""
# JSON primitives (except for dict) are not encoded.
if cls._is_primitive(encoded_var):
return encoded_var
elif isinstance(encoded_var, list):
return [cls._deserialize(v) for v in encoded_var]
if not isinstance(encoded_var, dict):
raise ValueError(
f"The encoded_var should be dict and is {type(encoded_var)}")
var = encoded_var[Encoding.VAR]
type_ = encoded_var[Encoding.TYPE]
if type_ == DAT.DICT:
return {k: cls._deserialize(v) for k, v in var.items()}
elif type_ == DAT.DAG:
return SerializedDAG.deserialize_dag(var)
elif type_ == DAT.OP:
return SerializedBaseOperator.deserialize_operator(var)
elif type_ == DAT.DATETIME:
return pendulum.from_timestamp(var)
elif type_ == DAT.POD:
if not HAS_KUBERNETES:
raise RuntimeError(
"Cannot deserialize POD objects without kubernetes libraries installed!"
)
pod = PodGenerator.deserialize_model_dict(var)
return pod
elif type_ == DAT.TIMEDELTA:
return datetime.timedelta(seconds=var)
elif type_ == DAT.TIMEZONE:
return decode_timezone(var)
elif type_ == DAT.RELATIVEDELTA:
return decode_relativedelta(var)
elif type_ == DAT.SET:
return {cls._deserialize(v) for v in var}
elif type_ == DAT.TUPLE:
return tuple(cls._deserialize(v) for v in var)
elif type_ == DAT.PARAM:
param_class = import_string(var['_type'])
del var['_type']
return param_class(**var)
else:
raise TypeError(f'Invalid type {type_!s} in deserialization.')
