jade.extensions.generic_command.generic_command_parameters.GenericCommandParametersModel

class jade.extensions.generic_command.generic_command_parameters.GenericCommandParametersModel(*, name: str | None = None, use_multi_node_manager: bool = False, spark_config: SparkConfigModel | None = None, command: str, blocked_by: Set[str] = {}, cancel_on_blocking_job_failure: bool = False, estimated_run_minutes: int | None = None, submission_group: str = 'default', append_job_name: bool = False, append_output_dir: bool = False, ext: Dict = {}, job_id: int | None = None, extension: str = 'generic_command')

Bases: JadeBaseModel

Model definition for generic command parameters

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

Methods

construct([_fields_set])	Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
copy(*[, include, exclude, update, deep])	Duplicate a model, optionally choose which fields to include, exclude and change.
dict(*args, **kwargs)	Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
from_orm(obj)
handle_append_output_dir(value, values)
handle_blocked_by(value)
json(*[, include, exclude, by_alias, ...])	Generate a JSON representation of the model, include and exclude arguments as per dict().
load(path)	Load a model from a file.
parse_file(path, *[, content_type, ...])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, ...])
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
update_forward_refs(**localns)	Try to update ForwardRefs on fields based on this Model, globalns and localns.
validate(value)

Attributes

name
use_multi_node_manager
spark_config
command
blocked_by
cancel_on_blocking_job_failure
estimated_run_minutes
submission_group
append_job_name
append_output_dir
ext
job_id
extension

dict(*args, **kwargs)

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

classmethod construct(_fields_set: SetStr | None = None, **values: Any) → Model

Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

copy(*, include: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, update: DictStrAny | None = None, deep: bool = False) → Model

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:

• include – fields to include in new model

• exclude – fields to exclude from new model, as with values this takes precedence over include

• update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data

• deep – set to True to make a deep copy of the model

Returns:

new model instance

json(*, include: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, by_alias: bool = False, skip_defaults: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Callable[[Any], Any] | None = None, models_as_dict: bool = True, **dumps_kwargs: Any) → str

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

classmethod load(path: Path)

Load a model from a file.

classmethod update_forward_refs(**localns: Any) → None

Try to update ForwardRefs on fields based on this Model, globalns and localns.