SerializedDatasetType¶
- class lsst.daf.butler.SerializedDatasetType(*, name: str, storageClass: str | None = None, dimensions: Annotated[str, Strict(strict=True)]] | None = None, parentStorageClass: str | None = None, isCalibration: bool = False)¶
Bases:
BaseModel
Simplified model of a
DatasetType
suitable for serialization.Attributes Summary
Configuration for the model, should be a dictionary conforming to [
ConfigDict
][pydantic.config.ConfigDict].Metadata about the fields defined on the model, mapping of field names to [
FieldInfo
][pydantic.fields.FieldInfo].Methods Summary
direct
(*, name[, storageClass, dimensions, ...])Construct a
SerializedDatasetType
directly without validators.Attributes Documentation
- model_config: ClassVar[ConfigDict] = {}¶
Configuration for the model, should be a dictionary conforming to [
ConfigDict
][pydantic.config.ConfigDict].
- model_fields: ClassVar[dict[str, FieldInfo]] = {'dimensions': FieldInfo(annotation=Union[SerializedDimensionGraph, list[Annotated[str, Strict(strict=True)]], NoneType], required=False), 'isCalibration': FieldInfo(annotation=bool, required=False, default=False, metadata=[Strict(strict=True)]), 'name': FieldInfo(annotation=str, required=True, metadata=[Strict(strict=True)]), 'parentStorageClass': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False), 'storageClass': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False)}¶
Metadata about the fields defined on the model, mapping of field names to [
FieldInfo
][pydantic.fields.FieldInfo].This replaces
Model.__fields__
from Pydantic V1.
Methods Documentation
- classmethod direct(*, name: str, storageClass: str | None = None, dimensions: list | dict | None = None, parentStorageClass: str | None = None, isCalibration: bool = False) SerializedDatasetType ¶
Construct a
SerializedDatasetType
directly without validators.This differs from Pydantic’s model_construct method in that the arguments are explicitly what the model requires, and it will recurse through members, constructing them from their corresponding
direct
methods.This method should only be called when the inputs are trusted.
- Parameters:
- name
str
The name of the dataset type.
- storageClass
str
orNone
The name of the storage class.
- dimensions
list
ordict
orNone
The dimensions associated with this dataset type.
- parentStorageClass
str
orNone
The parent storage class name if this is a component.
- isCalibration
bool
Whether this dataset type represents calibrations.
- name
- Returns:
SerializedDatasetType
A Pydantic model representing a dataset type.