DatasetType

class lsst.daf.butler.DatasetType(name: str, dimensions: DimensionGroup | Iterable[str], storageClass: StorageClass | str, parentStorageClass: StorageClass | str | None = None, *, universe: DimensionUniverse | None = None, isCalibration: bool = False)

Bases: object

A named category of Datasets.

Defines how they are organized, related, and stored.

A concrete, final class whose instances represent a DatasetType. DatasetType instances may be constructed without a Registry, but they must be registered via Registry.registerDatasetType() before corresponding Datasets may be added. DatasetType instances are immutable.

Parameters:

namestr

A string name for the Dataset; must correspond to the same DatasetType across all Registries. Names must start with an upper or lowercase letter, and may contain only letters, numbers, and underscores. Component dataset types should contain a single period separating the base dataset type name from the component name (and may be recursive).

dimensionsDimensionGroup or Iterable [ str ]

Dimensions used to label and relate instances of this DatasetType. If not a DimensionGroup, universe must be provided as well.

storageClassStorageClass or str

Instance of a StorageClass or name of StorageClass that defines how this DatasetType is persisted.

parentStorageClassStorageClass or str, optional

Instance of a StorageClass or name of StorageClass that defines how the composite parent is persisted. Must be None if this is not a component.

universeDimensionUniverse, optional

Set of all known dimensions, used to normalize dimensions if it is not already a DimensionGroup.

isCalibrationbool, optional

If True, this dataset type may be included in CALIBRATION collections.

Notes

See also Organizing and identifying datasets.

Attributes Summary

VALID_NAME_REGEX
dimensions	Return the dimensions of this dataset type (DimensionGroup).
name	Return a string name for the Dataset.
parentStorageClass	Return the storage class of the composite containing this component.
storageClass	Return StorageClass instance associated with this dataset type.
storageClass_name	Return the storage class name.

Methods Summary

component()	Return the component name (if defined).
componentTypeName(component)	Derive a component dataset type from a composite.
from_json(json_str[, universe, registry])	Convert from JSON to a pydantic model.
from_simple(simple[, universe, registry])	Construct a new object from the simplified form.
isCalibration()	Return if datasets of this type can be in calibration collections.
isComponent()	Return whether this DatasetType refers to a component.
isComposite()	Return whether this DatasetType is a composite.
is_compatible_with(other)	Determine if the given DatasetType is compatible with this one.
makeAllComponentDatasetTypes()	Return all component dataset types for this composite.
makeComponentDatasetType(component)	Return a component dataset type from a composite.
makeCompositeDatasetType()	Return a composite dataset type from the component.
nameAndComponent()	Return the root name of this dataset type and any component.
nameWithComponent(datasetTypeName, componentName)	Form a valid DatasetTypeName from a parent and component.
overrideStorageClass(storageClass)	Create a new DatasetType from this one but with an updated StorageClass.
splitDatasetTypeName(datasetTypeName)	Return the root name and the component from a composite name.
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.

Attributes Documentation

VALID_NAME_REGEX = re.compile('^[a-zA-Z_][a-zA-Z0-9_]*(\\.[a-zA-Z_][a-zA-Z0-9_]*)*$')

dimensions

Return the dimensions of this dataset type (DimensionGroup).

The dimensions of a define the keys of its datasets’ data IDs..

name

Return a string name for the Dataset.

Must correspond to the same DatasetType across all Registries.

parentStorageClass

Return the storage class of the composite containing this component.

Note that if DatasetType was constructed with a name of a StorageClass then Butler has to be initialized before using this property. Can be None if this is not a component of a composite. Must be defined if this is a component.

storageClass

Return StorageClass instance associated with this dataset type.

The StorageClass defines how this DatasetType is persisted. Note that if DatasetType was constructed with a name of a StorageClass then Butler has to be initialized before using this property.

storageClass_name

Return the storage class name.

This will never force the storage class to be imported.

Methods Documentation

component() → str | None

Return the component name (if defined).

Returns:

compstr

Name of component part of DatasetType name. None if this DatasetType is not associated with a component.

componentTypeName(component: str) → str

Derive a component dataset type from a composite.

Parameters:

componentstr

Name of component.

Returns:

derivedstr

Compound name of this DatasetType and the component.

Raises:

KeyError

Requested component is not supported by this DatasetType.

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

Convert from JSON to a pydantic model.

Parameters:

cls_type of SupportsSimple

The Python type being created.

json_strstr

The JSON string representing this object.

universeDimensionUniverse or None, optional

The universe required to instantiate some models. Required if registry is None.

registryRegistry or None, optional

Registry from which to obtain the dimension universe if an explicit universe has not been given.

Returns:

modelSupportsSimple

Pydantic model constructed from JSON and validated.

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

Construct a new object from the simplified form.

This is usually data returned from the to_simple method.

Parameters:

simpleSerializedDatasetType

The value returned by to_simple().

universeDimensionUniverse

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

registrylsst.daf.butler.Registry, optional

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

Returns:

datasetTypeDatasetType

Newly-constructed object.

isCalibration() → bool

Return if datasets of this type can be in calibration collections.

Returns:

flagbool

True if datasets of this type may be included in calibration collections.

isComponent() → bool

Return whether this DatasetType refers to a component.

Returns:

isComponentbool

True if this DatasetType is a component, False otherwise.

isComposite() → bool

Return whether this DatasetType is a composite.

Returns:

isCompositebool

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

is_compatible_with(other: DatasetType) → bool

Determine if the given DatasetType is compatible with this one.

Compatibility requires a matching name and dimensions and a storage class for this dataset type that can convert the python type associated with the other storage class to this python type. Parent storage class compatibility is not checked at all for components.

Parameters:

otherDatasetType

Dataset type to check.

Returns:

is_compatiblebool

Returns True if the other dataset type is either the same as this or the storage class associated with the other can be converted to this.

makeAllComponentDatasetTypes() → list[lsst.daf.butler._dataset_type.DatasetType]

Return all component dataset types for this composite.

Returns:

alllist of DatasetType

All the component dataset types. If this is not a composite then returns an empty list.

makeComponentDatasetType(component: str) → DatasetType

Return a component dataset type from a composite.

Assumes the same dimensions as the parent.

Parameters:

componentstr

Name of component.

Returns:

datasetTypeDatasetType

A new DatasetType instance.

makeCompositeDatasetType() → DatasetType

Return a composite dataset type from the component.

Returns:

compositeDatasetType

The composite dataset type.

Raises:

RuntimeError

Raised if this dataset type is not a component dataset type.

nameAndComponent() → tuple[str, str | None]

Return the root name of this dataset type and any component.

Returns:

rootNamestr

Root name for this DatasetType without any components.

componentNamestr

The component if it has been specified, else None.

static nameWithComponent(datasetTypeName: str, componentName: str) → str

Form a valid DatasetTypeName from a parent and component.

No validation is performed.

Parameters:

datasetTypeNamestr

Base type name.

componentNamestr

Name of component.

Returns:

compTypeNamestr

Name to use for component DatasetType.

overrideStorageClass(storageClass: str | StorageClass) → DatasetType

Create a new DatasetType from this one but with an updated StorageClass.

Parameters:

storageClassstr or StorageClass

The new storage class.

Returns:

modifiedDatasetType

A dataset type that is the same as the current one but with a different storage class. Will be self if the given storage class is the current one.

Notes

If this is a component dataset type, the parent storage class will be retained.

static splitDatasetTypeName(datasetTypeName: str) → tuple[str, str | None]

Return the root name and the component from a composite name.

Parameters:

datasetTypeNamestr

The name of the dataset type, can include a component using a “.”-separator.

Returns:

rootNamestr

Root name without any components.

componentNamestr

The component if it has been specified, else None.

Notes

If the dataset type name is a.b.c this method will return a root name of a and a component name of b.c.

to_json(minimal: bool = False) → str

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

Parameters:

minimalbool

Return minimal possible representation.

to_simple(minimal: bool = False) → SerializedDatasetType

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:

simpleSerializedDatasetType

The object converted to a class suitable for serialization.