DatasetRef¶
-
class
lsst.daf.butler.
DatasetRef
(datasetType: lsst.daf.butler.core.datasets.type.DatasetType, dataId: lsst.daf.butler.core.dimensions._coordinate.DataCoordinate, *, id: Optional[int] = None, run: Optional[str] = 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: - datasetType :
DatasetType
The
DatasetType
for this Dataset.- dataId :
DataCoordinate
A mapping of dimensions that labels the Dataset within a Collection.
- id :
int
, optional The unique integer identifier assigned when the dataset is created.
- run :
str
, optional The name of the run this dataset was associated with when it was created. Must be provided if
id
is.- conform :
bool
, optional If
True
(default), callDataCoordinate.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 passFalse
if it can guarantee that the dimensions are already consistent.
Raises: - ValueError
Raised if
run
is provided butid
is not, or ifid
is provided butrun
is not.
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 ( int
orNone
).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)Return new class from JSON string. from_simple
(simple, universe, registry)Construct a new object from simplified form. getCheckedId
()Return self.id
, or raise if it isNone
.groupByType
(refs)Group an iterable of DatasetRef
byDatasetType
.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.resolved
(id, run)Return resolved DatasetRef
.to_json
(minimal)Convert this class to JSON form. to_simple
(minimal)Convert this class to a simple python type. unresolved
()Return unresolved DatasetRef
.Attributes Documentation
-
dataId
¶ A mapping of
Dimension
primary key values that labels the dataset within a Collection (DataCoordinate
).Cannot be changed after a
DatasetRef
is constructed.
-
datasetType
¶ The definition of this dataset (
DatasetType
).Cannot be changed after a
DatasetRef
is constructed.
-
dimensions
¶ Dimensions associated with the underlying
DatasetType
.
-
id
¶ Primary key of the dataset (
int
orNone
).Cannot be changed after a
DatasetRef
is constructed; useresolved
orunresolved
to add or remove this information when creating a newDatasetRef
.
-
run
¶ The name of the run that produced the dataset.
Cannot be changed after a
DatasetRef
is constructed; useresolved
orunresolved
to add or remove this information when creating a newDatasetRef
.
Methods Documentation
-
expanded
(dataId: lsst.daf.butler.core.dimensions._coordinate.DataCoordinate) → lsst.daf.butler.core.datasets.ref.DatasetRef¶ Return a new
DatasetRef
with the given expanded data ID.Parameters: - dataId :
DataCoordinate
Data ID for the new
DatasetRef
. Must compare equal to the original data ID.
Returns: - ref :
DatasetRef
A new
DatasetRef
with the given data ID.
- dataId :
-
classmethod
from_json
(json_str: str, universe: Optional[DimensionUniverse] = None, registry: Optional[Registry] = None) → SupportsSimple¶ Return new class from JSON string.
Converts a JSON string created by
to_json
and return something of the supplied class.Parameters: - json_str :
str
Representation of the dimensions in JSON format as created by
to_json()
.- universe :
DimensionUniverse
, optional The special graph of all known dimensions. Passed directly to
from_simple()
.- registry :
lsst.daf.butler.Registry
, optional Registry to use to convert simple name of a DatasetType to a full
DatasetType
. Passed directly tofrom_simple()
.
Returns: - constructed : Any
Newly-constructed object.
- json_str :
-
classmethod
from_simple
(simple: Dict, universe: Optional[DimensionUniverse] = None, registry: Optional[Registry] = None) → DatasetRef¶ Construct a new object from simplified form.
Generally this is data returned from the
to_simple
method.Parameters: - simple :
dict
of [str
,Any
] The value returned by
to_simple()
.- universe :
DimensionUniverse
The special graph of all known dimensions. Can be
None
if a registry is provided.- registry :
lsst.daf.butler.Registry
, optional Registry to use to convert simple form of a DatasetRef to a full
DatasetRef
. Can beNone
if a full description of the type is provided along with a universe.
Returns: - ref :
DatasetRef
Newly-constructed object.
- simple :
-
getCheckedId
() → int¶ Return
self.id
, or raise if it isNone
.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: Raises: - AmbiguousDatasetError
Raised if
ref.id
isNone
.
-
static
groupByType
(refs: Iterable[lsst.daf.butler.core.datasets.ref.DatasetRef]) → lsst.daf.butler.core.named.NamedKeyDict[lsst.daf.butler.core.datasets.type.DatasetType, typing.List[lsst.daf.butler.core.datasets.ref.DatasetRef]][lsst.daf.butler.core.datasets.type.DatasetType, List[lsst.daf.butler.core.datasets.ref.DatasetRef]]¶ Group an iterable of
DatasetRef
byDatasetType
.Parameters: - refs :
Iterable
[DatasetRef
] DatasetRef
instances to group.
Returns: - grouped :
NamedKeyDict
[DatasetType
,list
[DatasetRef
] ] Grouped
DatasetRef
instances.
- refs :
-
isComponent
() → bool¶ Indicate whether this
DatasetRef
refers to a component.Returns: - isComponent :
bool
True
if thisDatasetRef
is a component,False
otherwise.
- isComponent :
-
isComposite
() → bool¶ Boolean indicating whether this
DatasetRef
is a composite type.Returns: - isComposite :
bool
True
if thisDatasetRef
is a composite type,False
otherwise.
- isComposite :
-
makeComponentRef
(name: str) → lsst.daf.butler.core.datasets.ref.DatasetRef¶ Create a
DatasetRef
that corresponds to a component.Parameters: - name :
str
Name of the component.
Returns: - ref :
DatasetRef
A
DatasetRef
with a dataset type that corresponds to the given component, and the same ID and run (which may beNone
, if they areNone
inself
).
- name :
-
makeCompositeRef
() → lsst.daf.butler.core.datasets.ref.DatasetRef¶ Create a
DatasetRef
of the composite from a component ref.Requires that this
DatasetRef
is a component.Returns: - ref :
DatasetRef
A
DatasetRef
with a dataset type that corresponds to the composite parent of this component, and the same ID and run (which may beNone
, if they areNone
inself
).
- ref :
-
resolved
(id: int, run: str) → lsst.daf.butler.core.datasets.ref.DatasetRef¶ Return resolved
DatasetRef
.This is a new
DatasetRef
with the same data ID and dataset type and the given ID and run.Parameters: Returns: - ref :
DatasetRef
A new
DatasetRef
.
- ref :
-
to_json
(minimal: bool = False) → str¶ Convert this class to JSON form.
The class type is not recorded in the JSON so the JSON decoder must know which class is represented.
Parameters: - minimal :
bool
, optional Use minimal serialization. Requires Registry to convert back to a full type.
Returns: - json :
str
The class in JSON string format.
- minimal :
-
to_simple
(minimal: bool = False) → Dict[KT, VT]¶ Convert this class to a simple python type.
This makes it suitable for serialization.
Parameters: - minimal :
bool
, optional Use minimal serialization. Requires Registry to convert back to a full type.
Returns: - minimal :
-
unresolved
() → lsst.daf.butler.core.datasets.ref.DatasetRef¶ Return unresolved
DatasetRef
.This is a new
DatasetRef
with the same data ID and dataset type, but no ID or run.Returns: - ref :
DatasetRef
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(): ...
- ref :
- datasetType :