FmuNode

class pystclient.models.FmuNode(*, label: str, fmu: str | None = None, model_type: str | None = None, model_id: ~typing.Annotated[str | ~uuid.UUID, ~pydantic.functional_serializers.PlainSerializer(func=str, return_type=str, when_used=always)] | None = None, id: str = <factory>, position: ~typing.Annotated[tuple[float, float], ~pydantic.functional_validators.BeforeValidator(func=~pystclient.models.position_transformer, json_schema_input_type=PydanticUndefined)] = (1000, 1000), type: str = 'io-node')

Bases: BaseModel

FMU node configuration.

__init__(**kwargs: Any) → None

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

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Methods

__init__(**kwargs)	Create a new model by parsing and validating input data from keyword arguments.
construct([_fields_set])
copy(*[, include, exclude, update, deep])	Returns a copy of the model.
dict(*[, include, exclude, by_alias, ...])
from_orm(obj)
json(*[, include, exclude, by_alias, ...])
model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])	!!! abstract "Usage Documentation"
model_dump(*[, mode, include, exclude, ...])	!!! abstract "Usage Documentation"
model_dump_json(*[, indent, ensure_ascii, ...])	!!! abstract "Usage Documentation"
model_json_schema([by_alias, ref_template, ...])	Generates a JSON schema for a model class.
model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
model_post_init(context, /)	Override this method to perform additional initialization after __init__ and model_construct.
model_rebuild(*[, force, raise_errors, ...])	Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, extra, ...])	Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])	!!! abstract "Usage Documentation"
model_validate_strings(obj, *[, strict, ...])	Validate the given object with string data against the Pydantic model.
model_validator()	Validate that either fmu or model_id is set.
parse_file(path, *[, content_type, ...])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, ...])
position_serializer(position)	Serialize position to dictionary.
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
update_forward_refs(**localns)
validate(value)

Attributes

data	Compute data field for serialization.
model_computed_fields
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extra	Get extra fields set during validation.
model_fields
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
instance
fmu
model_type
model_id
id
position
type

model_validator() → Self

Validate that either fmu or model_id is set.

position_serializer(position: tuple[float, float]) → dict[str, float]

Serialize position to dictionary.

property data: dict[str, Any]

Compute data field for serialization.

fmu: Annotated[str | None, FieldInfo(annotation=NoneType, required=True, exclude=True)]

id: str

instance: str

model_config = {'populate_by_name': True, 'validate_by_alias': True, 'validate_by_name': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_id: Annotated[Annotated[str | UUID, PlainSerializer(func=str, return_type=str, when_used=always)] | None, FieldInfo(annotation=NoneType, required=True, alias='model-id', alias_priority=2, exclude=True)]

model_type: Annotated[str | None, FieldInfo(annotation=NoneType, required=True, alias='model-type', alias_priority=2, exclude=True)]

position: Annotated[tuple[float, float], BeforeValidator(func=position_transformer, json_schema_input_type=PydanticUndefined)]

type: str