SerializedDatasetRef

class lsst.daf.butler.SerializedDatasetRef

Bases: pydantic.main.BaseModel

Simplified model of a DatasetRef suitable for serialization.

Attributes Summary

copy	Duplicate a model, optionally choose which fields to include, exclude and change.
dict	Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
json	Generate a JSON representation of the model, include and exclude arguments as per dict().

Methods Summary

construct(_fields_set, **values)	Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
direct(*, id, int, None] = None, …)	Construct a SerializedDatasetRef directly without validators.
from_orm(obj)
parse_file(path, pathlib.Path], *, …)
parse_obj(obj)
parse_raw(b, bytes], *, content_type, …)
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 Documentation

copy

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

dict

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

json

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().

Methods Documentation

classmethod construct(_fields_set: Optional[SetStr] = None, **values) → 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

classmethod direct(*, id: Union[str, int, None] = None, datasetType: Optional[Dict[str, Any]] = None, dataId: Optional[Dict[str, Any]] = None, run: Optional[str] = None, component: Optional[str] = None) → lsst.daf.butler.core.datasets.ref.SerializedDatasetRef

Construct a SerializedDatasetRef directly without validators.

This differs from the pydantic “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.

classmethod from_orm(obj: Any) → Model

classmethod parse_file(path: Union[str, pathlib.Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model

classmethod parse_obj(obj: Any) → Model

classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model

classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny

classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs) → unicode

classmethod update_forward_refs(**localns) → None

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

classmethod validate(value: Any) → Model