DatasetRef

class lsst.daf.butler.DatasetRef(datasetType: DatasetType, dataId: DataCoordinate, *, id: int | UUID | None = None, run: str | None = None, conform: bool = True)

Bases: object

Reference to a Dataset in a Registry.

A DatasetRef may point to a Dataset that currently does not yet exist (e.g., because it is a predicted input for provenance).

Parameters:

datasetTypeDatasetType

The DatasetType for this Dataset.

dataIdDataCoordinate

A mapping of dimensions that labels the Dataset within a Collection.

idDatasetId, optional

The unique identifier assigned when the dataset is created.

runstr, optional

The name of the run this dataset was associated with when it was created. Must be provided if id is.

conformbool, optional

If True (default), call DataCoordinate.standardize to ensure that the data ID’s dimensions are consistent with the dataset type’s. DatasetRef instances for which those dimensions are not equal should not be created in new code, but are still supported for backwards compatibility. New code should only pass False if it can guarantee that the dimensions are already consistent.

Raises:

ValueError

Raised if run is provided but id is not, or if id is provided but run is not.

See also

Organizing and identifying datasets

Attributes Summary

dataId	A mapping of Dimension primary key values that labels the dataset within a Collection (DataCoordinate).
datasetType	The definition of this dataset (DatasetType).
dimensions	Dimensions associated with the underlying DatasetType.
id	Primary key of the dataset (DatasetId or None).
run	The name of the run that produced the dataset.

Methods Summary

expanded(dataId)	Return a new DatasetRef with the given expanded data ID.
from_json(json_str[, universe, registry])	Convert from JSON to a pydantic model.
from_simple(simple[, universe, registry, ...])	Construct a new object from simplified form.
getCheckedId()	Return self.id, or raise if it is None.
groupByType(refs)	Group an iterable of DatasetRef by DatasetType.
isComponent()	Indicate whether this DatasetRef refers to a component.
isComposite()	Boolean indicating whether this DatasetRef is a composite type.
makeComponentRef(name)	Create a DatasetRef that corresponds to a component.
makeCompositeRef()	Create a DatasetRef of the composite from a component ref.
overrideStorageClass(storageClass)	Create a new DatasetRef from this one, but with a modified DatasetType that has a different StorageClass.
resolved(id, run)	Return resolved DatasetRef.
to_json([minimal])	Convert this class to JSON assuming that the to_simple() returns a pydantic model.
to_simple([minimal])	Convert this class to a simple python type.
unresolved()	Return unresolved DatasetRef.

Attributes Documentation

dataId: DataCoordinate

A mapping of Dimension primary key values that labels the dataset within a Collection (DataCoordinate).

Cannot be changed after a DatasetRef is constructed.

datasetType: DatasetType

The definition of this dataset (DatasetType).

Cannot be changed after a DatasetRef is constructed.

dimensions

Dimensions associated with the underlying DatasetType.

id: int | UUID | None

Primary key of the dataset (DatasetId or None).

Cannot be changed after a DatasetRef is constructed; use resolved or unresolved to add or remove this information when creating a new DatasetRef.

run: str | None

The name of the run that produced the dataset.

Cannot be changed after a DatasetRef is constructed; use resolved or unresolved to add or remove this information when creating a new DatasetRef.

Methods Documentation

expanded(dataId: DataCoordinate) → DatasetRef

Return a new DatasetRef with the given expanded data ID.

Parameters:

dataIdDataCoordinate

Data ID for the new DatasetRef. Must compare equal to the original data ID.

Returns:

refDatasetRef

A new DatasetRef with the given data ID.

classmethod from_json(json_str: str, universe: DimensionUniverse | None = None, registry: Registry | None = None) → SupportsSimple

Convert from JSON to a pydantic model.

classmethod from_simple(simple: SerializedDatasetRef, universe: DimensionUniverse | None = None, registry: Registry | None = None, datasetType: DatasetType | None = None) → DatasetRef

Construct a new object from simplified form.

Generally this is data returned from the to_simple method.

Parameters:

simpledict of [str, Any]

The value returned by to_simple().

universeDimensionUniverse

The special graph of all known dimensions. Can be None if a registry is provided.

registrylsst.daf.butler.Registry, optional

Registry to use to convert simple form of a DatasetRef to a full DatasetRef. Can be None if a full description of the type is provided along with a universe.

datasetTypeDatasetType, optional

If datasetType is supplied, this will be used as the datasetType object in the resulting DatasetRef instead of being read from the SerializedDatasetRef. This is useful when many refs share the same type as memory can be saved. Defaults to None.

Returns:

refDatasetRef

Newly-constructed object.

getCheckedId() → int | UUID

Return self.id, or raise if it is None.

This trivial method exists to allow operations that would otherwise be natural list comprehensions to check that the ID is not None as well.

Returns:

idDatasetId

self.id if it is not None.

Raises:

AmbiguousDatasetError

Raised if ref.id is None.

static groupByType(refs: Iterable[DatasetRef]) → NamedKeyDict[DatasetType, List[DatasetRef]]

Group an iterable of DatasetRef by DatasetType.

Parameters:

refsIterable [ DatasetRef ]

DatasetRef instances to group.

Returns:

groupedNamedKeyDict [ DatasetType, list [ DatasetRef ] ]

Grouped DatasetRef instances.

isComponent() → bool

Indicate whether this DatasetRef refers to a component.

Returns:

isComponentbool

True if this DatasetRef is a component, False otherwise.

isComposite() → bool

Boolean indicating whether this DatasetRef is a composite type.

Returns:

isCompositebool

True if this DatasetRef is a composite type, False otherwise.

makeComponentRef(name: str) → DatasetRef

Create a DatasetRef that corresponds to a component.

Parameters:

namestr

Name of the component.

Returns:

refDatasetRef

A DatasetRef with a dataset type that corresponds to the given component, and the same ID and run (which may be None, if they are None in self).

makeCompositeRef() → DatasetRef

Create a DatasetRef of the composite from a component ref.

Requires that this DatasetRef is a component.

Returns:

refDatasetRef

A DatasetRef with a dataset type that corresponds to the composite parent of this component, and the same ID and run (which may be None, if they are None in self).

overrideStorageClass(storageClass: str | StorageClass) → DatasetRef

Create a new DatasetRef from this one, but with a modified DatasetType that has a different StorageClass.

Parameters:

storageClassstr or StorageClass

The new storage class.

Returns:

modifiedDatasetRef

A new dataset reference that is the same as the current one but with a different storage class in the DatasetType.

resolved(id: int | UUID, run: str) → DatasetRef

Return resolved DatasetRef.

This is a new DatasetRef with the same data ID and dataset type and the given ID and run.

Parameters:

idDatasetId

The unique identifier assigned when the dataset is created.

runstr

The run this dataset was associated with when it was created.

Returns:

refDatasetRef

A new DatasetRef.

to_json(minimal: bool = False) → str

Convert this class to JSON assuming that the to_simple() returns a pydantic model.

to_simple(minimal: bool = False) → SerializedDatasetRef

Convert this class to a simple python type.

This makes it suitable for serialization.

Parameters:

minimalbool, optional

Use minimal serialization. Requires Registry to convert back to a full type.

Returns:

simpledict or int

The object converted to a dictionary.

unresolved() → DatasetRef

Return unresolved DatasetRef.

This is a new DatasetRef with the same data ID and dataset type, but no ID or run.

Returns:

refDatasetRef

A new DatasetRef.

Notes

This can be used to compare only the data ID and dataset type of a pair of DatasetRef instances, regardless of whether either is resolved:

if ref1.unresolved() == ref2.unresolved():
    ...