CollectionSummary

class lsst.daf.butler.registry.CollectionSummary(dataset_types: lsst.daf.butler.core.named.NamedValueSet[lsst.daf.butler.core.datasets.type.DatasetType] = <factory>, governors: dict = <factory>)

Bases: object

A summary of the datasets that can be found in a collection.

Methods Summary

add_data_ids(dataset_type, data_ids)	Include the given dataset type and data IDs in the summary.
add_data_ids_generator(dataset_type, data_ids)	Include the given dataset type and data IDs in the summary, yielding them back as a generator.
add_datasets(refs)	Include the given datasets in the summary.
add_datasets_generator(refs)	Include the given datasets in the summary, yielding them back as a generator.
copy()	Return a deep copy of this object.
is_compatible_with(dataset_type, dimensions, …)	Test whether the collection summarized by this object should be queried for a given dataset type and governor dimension values.
union()	Construct a summary that contains all dataset types and governor dimension values in any of the inputs.
update(*args)	Update this summary with dataset types and governor dimension values from other summaries.

Methods Documentation

add_data_ids(dataset_type: lsst.daf.butler.core.datasets.type.DatasetType, data_ids: Iterable[lsst.daf.butler.core.dimensions._coordinate.DataCoordinate]) → None

Include the given dataset type and data IDs in the summary.

Parameters:

dataset_type : DatasetType

Dataset type to include.

data_ids : Iterable [ DataCoordinate ]

Data IDs to include.

add_data_ids_generator(dataset_type: lsst.daf.butler.core.datasets.type.DatasetType, data_ids: Iterable[lsst.daf.butler.core.dimensions._coordinate.DataCoordinate]) → Generator[lsst.daf.butler.core.dimensions._coordinate.DataCoordinate, None, None]

Include the given dataset type and data IDs in the summary, yielding them back as a generator.

Parameters:

dataset_type : DatasetType

Dataset type to include.

data_ids : Iterable [ DataCoordinate ]

Data IDs to include.

Yields:

data_id : DataCoordinate

The same data IDs originally passed in.

Notes

As a generator, this method does nothing if its return iterator is not used. Call add_data_ids instead to avoid this; this method is intended for the case where the given iterable may be single-pass and a copy is not desired, but other processing needs to be done on its elements.

add_datasets(refs: Iterable[lsst.daf.butler.core.datasets.ref.DatasetRef]) → None

Include the given datasets in the summary.

Parameters:

refs : Iterable [ DatasetRef ]

Datasets to include.

add_datasets_generator(refs: Iterable[lsst.daf.butler.core.datasets.ref.DatasetRef]) → Generator[lsst.daf.butler.core.datasets.ref.DatasetRef, None, None]

Include the given datasets in the summary, yielding them back as a generator.

Parameters:

refs : Iterable [ DatasetRef ]

Datasets to include.

Yields:

ref : DatasetRef

The same dataset references originally passed in.

Notes

As a generator, this method does nothing if its return iterator is not used. Call add_datasets instead to avoid this; this method is intended for the case where the given iterable may be single-pass and a copy is not desired, but other processing needs to be done on its elements.

copy() → lsst.daf.butler.registry._collection_summary.CollectionSummary

Return a deep copy of this object.

Returns:

copy : CollectionSummary

A copy of self that can be modified without modifying self at all.

is_compatible_with(dataset_type: lsst.daf.butler.core.datasets.type.DatasetType, dimensions: Mapping[str, AbstractSet[str]], rejections: Optional[List[str], None] = None, name: Optional[str, None] = None) → bool

Test whether the collection summarized by this object should be queried for a given dataset type and governor dimension values.

Parameters:

dataset_type : DatasetType

Dataset type being queried. If this collection has no instances of this dataset type (or its parent dataset type, if it is a component), False will always be returned.

dimensions : Mapping

Bounds on the values governor dimensions can take in the query, usually from a WHERE expression, as a mapping from dimension name to a set of str governor dimension values.

rejections : list [ str ], optional

If provided, a list that will be populated with a log- or exception-friendly message explaining why this dataset is incompatible with this collection when False is returned.

name : str, optional

Name of the collection this object summarizes, for use in messages appended to rejections. Ignored if rejections is None.

Returns:

compatible : bool

True if the dataset query described by this summary and the given arguments might yield non-empty results; False if the result from such a query is definitely empty.

union() → lsst.daf.butler.registry._collection_summary.CollectionSummary

Construct a summary that contains all dataset types and governor dimension values in any of the inputs.

Parameters:

*args : CollectionSummary

Summaries to combine.

Returns:

unioned : CollectionSummary

New summary object that represents the union of the given ones.

update(*args) → None

Update this summary with dataset types and governor dimension values from other summaries.

Parameters:

*args : CollectionSummary

Summaries to include in self.