DatasetRecordStorage¶

class lsst.daf.butler.registry.interfaces.DatasetRecordStorage(datasetType: lsst.daf.butler.core.datasets.type.DatasetType)¶

Bases: abc.ABC

An interface that manages the records associated with a particular DatasetType.

Parameters:	datasetType : `DatasetType` Dataset type whose records this object manages.

Methods Summary

`associate`(collection, datasets)	Associate one or more datasets with a collection.
`certify`(collection, datasets, timespan, context)	Associate one or more datasets with a calibration collection and a validity range within it.
`decertify`(collection, timespan, *, dataIds, …)	Remove or adjust datasets to clear a validity range within a calibration collection.
`delete`(datasets)	Fully delete the given datasets from the registry.
`disassociate`(collection, datasets)	Remove one or more datasets from a collection.
`import_`(run, datasets, idGenerationMode, …)	Insert one or more dataset entries into the database.
`insert`(run, dataIds, idGenerationMode)	Insert one or more dataset entries into the database.
`make_relation`(*collections, columns, context)	Return a `sql.Relation` that represents a query for for this `DatasetType` in one or more collections.

Methods Documentation

associate(collection: CollectionRecord, datasets: Iterable[DatasetRef]) → None¶

Associate one or more datasets with a collection.

Parameters:	collection : `CollectionRecord` The record object describing the collection. `collection.type` must be `TAGGED`. datasets : `Iterable` [ `DatasetRef` ] Datasets to be associated. All datasets must be resolved and have the same `DatasetType` as `self`.
Raises:	AmbiguousDatasetError Raised if any of the given `DatasetRef` instances is unresolved.

Notes

Associating a dataset with into collection that already contains a different dataset with the same DatasetType and data ID will remove the existing dataset from that collection.

Associating the same dataset into a collection multiple times is a no-op, but is still not permitted on read-only databases.

certify(collection: CollectionRecord, datasets: Iterable[DatasetRef], timespan: Timespan, context: SqlQueryContext) → None¶

Associate one or more datasets with a calibration collection and a validity range within it.

Parameters:	collection : `CollectionRecord` The record object describing the collection. `collection.type` must be `CALIBRATION`. datasets : `Iterable` [ `DatasetRef` ] Datasets to be associated. All datasets must be resolved and have the same `DatasetType` as `self`. timespan : `Timespan` The validity range for these datasets within the collection.
Raises:	AmbiguousDatasetError Raised if any of the given `DatasetRef` instances is unresolved. ConflictingDefinitionError Raised if the collection already contains a different dataset with the same `DatasetType` and data ID and an overlapping validity range. CollectionTypeError Raised if `collection.type is not CollectionType.CALIBRATION` or if `self.datasetType.isCalibration() is False`.

decertify(collection: CollectionRecord, timespan: Timespan, *, dataIds: Iterable[DataCoordinate] | None = None, context: SqlQueryContext) → None¶

Remove or adjust datasets to clear a validity range within a calibration collection.

Parameters:

collection : CollectionRecord: The record object describing the collection. collection.type must be CALIBRATION.
timespan : Timespan: The validity range to remove datasets from within the collection. Datasets that overlap this range but are not contained by it will have their validity ranges adjusted to not overlap it, which may split a single dataset validity range into two.
dataIds : Iterable [ DataCoordinate ], optional: Data IDs that should be decertified within the given validity range If None, all data IDs for self.datasetType will be decertified.

Raises:

CollectionTypeError: Raised if collection.type is not CollectionType.CALIBRATION.

delete(datasets: collections.abc.Iterable[lsst.daf.butler.core.datasets.ref.DatasetRef]) → None¶

Fully delete the given datasets from the registry.

Parameters:	datasets : `Iterable` [ `DatasetRef` ] Datasets to be deleted. All datasets must be resolved and have the same `DatasetType` as `self`.
Raises:	AmbiguousDatasetError Raised if any of the given `DatasetRef` instances is unresolved.

disassociate(collection: CollectionRecord, datasets: Iterable[DatasetRef]) → None¶

Remove one or more datasets from a collection.

Parameters:	collection : `CollectionRecord` The record object describing the collection. `collection.type` must be `TAGGED`. datasets : `Iterable` [ `DatasetRef` ] Datasets to be disassociated. All datasets must be resolved and have the same `DatasetType` as `self`.
Raises:	AmbiguousDatasetError Raised if any of the given `DatasetRef` instances is unresolved.

import_(run: RunRecord, datasets: Iterable[DatasetRef], idGenerationMode: DatasetIdGenEnum = <DatasetIdGenEnum.UNIQUE: 0>, reuseIds: bool = False) → Iterator[DatasetRef]¶

Insert one or more dataset entries into the database.

Parameters:

run : RunRecord: The record object describing the RUN collection this dataset will be associated with.
datasets : Iterable of DatasetRef: Datasets to be inserted. Datasets can specify id attribute which will be used for inserted datasets. All dataset IDs must have the same type (int or uuid.UUID), if type of dataset IDs does not match type supported by this class then IDs will be ignored and new IDs will be generated by backend.
idGenerationMode : DatasetIdGenEnum: With UNIQUE each new dataset is inserted with its new unique ID. With non-UNIQUE mode ID is computed from some combination of dataset type, dataId, and run collection name; if the same ID is already in the database then new record is not inserted.
reuseIds : bool, optional: If True then forces re-use of imported dataset IDs for integer IDs which are normally generated as auto-incremented; exception will be raised if imported IDs clash with existing ones. This option has no effect on the use of globally-unique IDs which are always re-used (or generated if integer IDs are being imported).

Returns:

datasets : Iterable [ DatasetRef ]: References to the inserted or existing datasets.

Notes

The datasetType and run attributes of datasets are supposed to be identical across all datasets but this is not checked and it should be enforced by higher level registry code. This method does not need to use those attributes from datasets, only dataId and id are relevant.

insert(run: RunRecord, dataIds: Iterable[DataCoordinate], idGenerationMode: DatasetIdGenEnum = <DatasetIdGenEnum.UNIQUE: 0>) → Iterator[DatasetRef]¶

Insert one or more dataset entries into the database.

Parameters:

run : RunRecord: The record object describing the RUN collection this dataset will be associated with.
dataIds : Iterable [ DataCoordinate ]: Expanded data IDs (DataCoordinate instances) for the datasets to be added. The dimensions of all data IDs must be the same as self.datasetType.dimensions.
idMode : DatasetIdGenEnum: With UNIQUE each new dataset is inserted with its new unique ID. With non-UNIQUE mode ID is computed from some combination of dataset type, dataId, and run collection name; if the same ID is already in the database then new record is not inserted.

Returns:

datasets : Iterable [ DatasetRef ]: References to the inserted datasets.

make_relation(*collections, columns: Set[str], context: SqlQueryContext) → Relation¶

Return a sql.Relation that represents a query for for this DatasetType in one or more collections.

Parameters:

*collections : CollectionRecord

The record object(s) describing the collection(s) to query. May not be of type CollectionType.CHAINED. If multiple collections are passed, the query will search all of them in an unspecified order, and all collections must have the same type. Must include at least one collection.

columns : Set [ str ]

Columns to include in the relation. See Query.find_datasets for most options, but this method supports one more:

rank: a calculated integer column holding the index of the collection the dataset was found in, within the collections sequence given.

context : SqlQueryContext

The object that manages database connections, temporary tables and relation engines for this query.

Returns

——

relation : Relation

Representation of the query.

Navigation

DatasetRecordStorage¶