Datastore¶
-
class
lsst.daf.butler.
Datastore
(config, registry, butlerRoot=None)¶ Bases:
object
Datastore interface.
Parameters: - config :
DatastoreConfig
orstr
Load configuration either from an existing config instance or by referring to a configuration file.
- registry :
Registry
Registry to use for storing internal information about the datasets.
- butlerRoot :
str
, optional New datastore root to use to override the configuration value.
Attributes Summary
containerKey
Name of the key containing a list of subconfigurations that also need to be merged with defaults and will likely use different Python datastore classes (but all using DatastoreConfig). defaultConfigFile
Path to configuration defaults. isEphemeral
Indicate whether this Datastore is ephemeral or not. Methods Summary
exists
(datasetRef)Check if the dataset exists in the datastore. export
(refs, *, directory, transfer)Export datasets for transfer to another data repository. fromConfig
(config, registry, butlerRoot)Create datastore from type specified in config file. get
(datasetRef[, parameters])Load an InMemoryDataset
from the store.getLookupKeys
()Return all the lookup keys relevant to this datastore. getUri
(datasetRef)URI to the Dataset. ingest
(*datasets, transfer)Ingest one or more files into the datastore. put
(inMemoryDataset, datasetRef)Write a InMemoryDataset
with a givenDatasetRef
to the store.remove
(datasetRef)Indicate to the Datastore that a Dataset can be removed. setConfigRoot
(root, config, full, overwrite)Set any filesystem-dependent config options for this Datastore to be appropriate for a new empty repository with the given root. transaction
()Context manager supporting Datastore
transactions.transfer
(inputDatastore, datasetRef)Retrieve a Dataset from an input Datastore
, and store the result in thisDatastore
.validateConfiguration
(entities[, logFailures])Validate some of the configuration for this datastore. validateKey
(lookupKey, entity[, logFailures])Validate a specific look up key with supplied entity. Attributes Documentation
-
containerKey
= None¶ Name of the key containing a list of subconfigurations that also need to be merged with defaults and will likely use different Python datastore classes (but all using DatastoreConfig). Assumed to be a list of configurations that can be represented in a DatastoreConfig and containing a “cls” definition. None indicates that no containers are expected in this Datastore.
-
defaultConfigFile
= None¶ Path to configuration defaults. Relative to $DAF_BUTLER_DIR/config or absolute path. Can be None if no defaults specified.
-
isEphemeral
= False¶ Indicate whether this Datastore is ephemeral or not. An ephemeral datastore is one where the contents of the datastore will not exist across process restarts.
Methods Documentation
-
exists
(datasetRef)¶ Check if the dataset exists in the datastore.
Parameters: - datasetRef :
DatasetRef
Reference to the required dataset.
Returns: - datasetRef :
-
export
(refs: Iterable[DatasetRef], *, directory: Optional[str] = None, transfer: Optional[str] = None) → Iterable[FileDataset]¶ Export datasets for transfer to another data repository.
Parameters: - refs : iterable of
DatasetRef
Dataset references to be exported.
- directory :
str
, optional Path to a directory that should contain files corresponding to output datasets. Ignored if
transfer
isNone
.- transfer :
str
, optional Mode that should be used to move datasets out of the repository. Valid options are the same as those of the
transfer
argument toingest
, and datastores may similarly signal that a transfer mode is not supported by raisingNotImplementedError
.
Returns: - dataset : iterable of
DatasetTransfer
Structs containing information about the exported datasets, in the same order as
refs
.
Raises: - NotImplementedError
Raised if the given transfer mode is not supported.
- refs : iterable of
-
static
fromConfig
(config: lsst.daf.butler.core.config.Config, registry: lsst.daf.butler.core.registry.Registry, butlerRoot: Optional[str] = None) → Datastore¶ Create datastore from type specified in config file.
Parameters:
-
get
(datasetRef, parameters=None)¶ Load an
InMemoryDataset
from the store.Parameters: - datasetRef :
DatasetRef
Reference to the required Dataset.
- parameters :
dict
StorageClass
-specific parameters that specify a slice of the Dataset to be loaded.
Returns: - inMemoryDataset :
object
Requested Dataset or slice thereof as an InMemoryDataset.
- datasetRef :
-
getLookupKeys
()¶ Return all the lookup keys relevant to this datastore.
Returns: - keys :
set
ofLookupKey
The keys stored internally for looking up information based on
DatasetType
name orStorageClass
.
- keys :
-
getUri
(datasetRef)¶ URI to the Dataset.
Parameters: - datasetRef :
DatasetRef
Reference to the required Dataset.
Returns: - uri :
str
URI string pointing to the Dataset within the datastore. If the Dataset does not exist in the datastore, the URI may be a guess. If the datastore does not have entities that relate well to the concept of a URI the returned URI string will be descriptive. The returned URI is not guaranteed to be obtainable.
- datasetRef :
-
ingest
(*datasets, transfer: Optional[str] = None)¶ Ingest one or more files into the datastore.
Parameters: - datasets :
FileDataset
Each positional argument is a struct containing information about a file to be ingested, including its path (either absolute or relative to the datastore root, if applicable), a complete
DatasetRef
(withdataset_id not None
), and optionally a formatter class or its fully-qualified string name. If a formatter is not provided, the one the datastore would use forput
on that dataset is assumed.- transfer :
str
, optional How (and whether) the dataset should be added to the datastore. If
None
(default), the file must already be in a location appropriate for the datastore (e.g. within its root directory), and will not be modified. Other choices include “move”, “copy”, “symlink”, and “hardlink”. Most datastores do not support all transfer modes.
Raises: - NotImplementedError
Raised if the datastore does not support the given transfer mode (including the case where ingest is not supported at all).
- DatasetTypeNotSupportedError
Raised if one or more files to be ingested have a dataset type that is not supported by the datastore.
- FileNotFoundError
Raised if one of the given files does not exist.
- FileExistsError
Raised if transfer is not
None
but the (internal) location the file would be moved to is already occupied.
Notes
Subclasses should implement
_prepIngest
and_finishIngest
instead of implementingingest
directly. Datastores that hold and delegate to child datastores may want to call those methods as well.Subclasses are encouraged to document their supported transfer modes in their class documentation.
- datasets :
-
put
(inMemoryDataset, datasetRef)¶ Write a
InMemoryDataset
with a givenDatasetRef
to the store.Parameters: - inMemoryDataset :
InMemoryDataset
The Dataset to store.
- datasetRef :
DatasetRef
Reference to the associated Dataset.
- inMemoryDataset :
-
remove
(datasetRef)¶ Indicate to the Datastore that a Dataset can be removed.
Parameters: - datasetRef :
DatasetRef
Reference to the required Dataset.
Raises: - FileNotFoundError
When Dataset does not exist.
Notes
Some Datastores may implement this method as a silent no-op to disable Dataset deletion through standard interfaces.
- datasetRef :
-
classmethod
setConfigRoot
(root: str, config: lsst.daf.butler.core.config.Config, full: lsst.daf.butler.core.config.Config, overwrite: bool = True)¶ Set any filesystem-dependent config options for this Datastore to be appropriate for a new empty repository with the given root.
Parameters: - root :
str
Filesystem path to the root of the data repository.
- config :
Config
A
Config
to update. Only the subset understood by this component will be updated. Will not expand defaults.- full :
Config
A complete config with all defaults expanded that can be converted to a
DatastoreConfig
. Read-only and will not be modified by this method. Repository-specific options that should not be obtained from defaults when Butler instances are constructed should be copied fromfull
toconfig
.- overwrite :
bool
, optional If
False
, do not modify a value inconfig
if the value already exists. Default is always to overwrite with the providedroot
.
Notes
If a keyword is explicitly defined in the supplied
config
it will not be overridden by this method ifoverwrite
isFalse
. This allows explicit values set in external configs to be retained.- root :
-
transaction
()¶ Context manager supporting
Datastore
transactions.Transactions can be nested, and are to be used in combination with
Registry.transaction
.
-
transfer
(inputDatastore, datasetRef)¶ Retrieve a Dataset from an input
Datastore
, and store the result in thisDatastore
.Parameters: - inputDatastore :
Datastore
The external
Datastore
from which to retreive the Dataset.- datasetRef :
DatasetRef
Reference to the required Dataset.
- inputDatastore :
-
validateConfiguration
(entities, logFailures=False)¶ Validate some of the configuration for this datastore.
Parameters: - entities :
DatasetRef
,DatasetType
, orStorageClass
Entities to test against this configuration. Can be differing types.
- logFailures :
bool
, optional If
True
, output a log message for every validation error detected.
Raises: - DatastoreValidationError
Raised if there is a validation problem with a configuration.
Notes
Which parts of the configuration are validated is at the discretion of each Datastore implementation.
- entities :
-
validateKey
(lookupKey, entity, logFailures=False)¶ Validate a specific look up key with supplied entity.
Parameters: - lookupKey :
LookupKey
Key to use to retrieve information from the datastore configuration.
- entity :
DatasetRef
,DatasetType
, orStorageClass
Entity to compare with configuration retrieved using the specified lookup key.
Raises: - DatastoreValidationError
Raised if there is a problem with the combination of entity and lookup key.
Notes
Bypasses the normal selection priorities by allowing a key that would normally not be selected to be validated.
- lookupKey :
- config :