class PosixDatastore(Datastore):
"""Basic POSIX filesystem backed Datastore.
Attributes
----------
config : `DatastoreConfig`
Configuration used to create Datastore.
registry : `Registry`
`Registry` to use when recording the writing of Datasets.
root : `str`
Root directory of this `Datastore`.
locationFactory : `LocationFactory`
Factory for creating locations relative to this root.
formatterFactory : `FormatterFactory`
Factory for creating instances of formatters.
storageClassFactory : `StorageClassFactory`
Factory for creating storage class instances from name.
templates : `FileTemplates`
File templates that can be used by this `Datastore`.
name : `str`
Label associated with this Datastore.
Parameters
----------
config : `DatastoreConfig` or `str`
Configuration.
Raises
------
ValueError
If root location does not exist and ``create`` is `False` in the
configuration.
"""
defaultConfigFile = "datastores/posixDatastore.yaml"
"""Path to configuration defaults. Relative to $DAF_BUTLER_DIR/config or
absolute path. Can be None if no defaults specified.
"""
RecordTuple = namedtuple(
"PosixDatastoreRecord",
["formatter", "path", "storage_class", "checksum", "file_size"])
@classmethod
def setConfigRoot(cls, root, config, full, overwrite=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 from ``full`` to ``config``.
overwrite : `bool`, optional
If `False`, do not modify a value in ``config`` if the value
already exists. Default is always to overwrite with the provided
``root``.
Notes
-----
If a keyword is explicitly defined in the supplied ``config`` it
will not be overridden by this method if ``overwrite`` is `False`.
This allows explicit values set in external configs to be retained.
"""
Config.updateParameters(DatastoreConfig,
config,
full,
toUpdate={"root": root},
toCopy=("cls", ("records", "table")),
overwrite=overwrite)
def __init__(self, config, registry, butlerRoot=None):
super().__init__(config, registry)
if "root" not in self.config:
raise ValueError("No root directory specified in configuration")
# Name ourselves either using an explicit name or a name
# derived from the (unexpanded) root
if "name" in self.config:
self.name = self.config["name"]
else:
self.name = "POSIXDatastore@{}".format(self.config["root"])
# Support repository relocation in config
self.root = replaceRoot(self.config["root"], butlerRoot)
if not os.path.isdir(self.root):
if "create" not in self.config or not self.config["create"]:
raise ValueError(f"No valid root at: {self.root}")
safeMakeDir(self.root)
self.locationFactory = LocationFactory(self.root)
self.formatterFactory = FormatterFactory()
self.storageClassFactory = StorageClassFactory()
# Now associate formatters with storage classes
self.formatterFactory.registerFormatters(
self.config["formatters"], universe=self.registry.dimensions)
# Read the file naming templates
self.templates = FileTemplates(self.config["templates"],
universe=self.registry.dimensions)
# And read the constraints list
constraintsConfig = self.config.get("constraints")
self.constraints = Constraints(constraintsConfig,
universe=self.registry.dimensions)
# Storage of paths and formatters, keyed by dataset_id
types = {
"path": str,
"formatter": str,
"storage_class": str,
"file_size": int,
"checksum": str,
"dataset_id": int
}
lengths = {
"path": 256,
"formatter": 128,
"storage_class": 64,
"checksum": 128
}
self.records = DatabaseDict.fromConfig(self.config["records"],
types=types,
value=self.RecordTuple,
key="dataset_id",
lengths=lengths,
registry=registry)
def __str__(self):
return self.root
def addStoredFileInfo(self, ref, info):
"""Record internal storage information associated with this
`DatasetRef`
Parameters
----------
ref : `DatasetRef`
The Dataset that has been stored.
info : `StoredFileInfo`
Metadata associated with the stored Dataset.
"""
self.records[ref.id] = self.RecordTuple(
formatter=info.formatter,
path=info.path,
storage_class=info.storageClass.name,
checksum=info.checksum,
file_size=info.size)
def removeStoredFileInfo(self, ref):
"""Remove information about the file associated with this dataset.
Parameters
----------
ref : `DatasetRef`
The Dataset that has been removed.
"""
del self.records[ref.id]
def getStoredFileInfo(self, ref):
"""Retrieve information associated with file stored in this
`Datastore`.
Parameters
----------
ref : `DatasetRef`
The Dataset that is to be queried.
Returns
-------
info : `StoredFileInfo`
Stored information about this file and its formatter.
Raises
------
KeyError
Dataset with that id can not be found.
"""
record = self.records.get(ref.id, None)
if record is None:
raise KeyError(
"Unable to retrieve formatter associated with Dataset {}".
format(ref.id))
# Convert name of StorageClass to instance
storageClass = self.storageClassFactory.getStorageClass(
record.storage_class)
return StoredFileInfo(record.formatter,
record.path,
storageClass,
checksum=record.checksum,
size=record.file_size)
def exists(self, ref):
"""Check if the dataset exists in the datastore.
Parameters
----------
ref : `DatasetRef`
Reference to the required dataset.
Returns
-------
exists : `bool`
`True` if the entity exists in the `Datastore`.
"""
# Get the file information (this will fail if no file)
try:
storedFileInfo = self.getStoredFileInfo(ref)
except KeyError:
return False
# Use the path to determine the location
location = self.locationFactory.fromPath(storedFileInfo.path)
return os.path.exists(location.path)
def get(self, ref, parameters=None):
"""Load an InMemoryDataset from the store.
Parameters
----------
ref : `DatasetRef`
Reference to the required Dataset.
parameters : `dict`
`StorageClass`-specific parameters that specify, for example,
a slice of the Dataset to be loaded.
Returns
-------
inMemoryDataset : `object`
Requested Dataset or slice thereof as an InMemoryDataset.
Raises
------
FileNotFoundError
Requested dataset can not be retrieved.
TypeError
Return value from formatter has unexpected type.
ValueError
Formatter failed to process the dataset.
"""
log.debug("Retrieve %s from %s with parameters %s", ref, self.name,
parameters)
# Get file metadata and internal metadata
try:
storedFileInfo = self.getStoredFileInfo(ref)
except KeyError:
raise FileNotFoundError(
"Could not retrieve Dataset {}".format(ref))
# Use the path to determine the location
location = self.locationFactory.fromPath(storedFileInfo.path)
# Too expensive to recalculate the checksum on fetch
# but we can check size and existence
if not os.path.exists(location.path):
raise FileNotFoundError(
"Dataset with Id {} does not seem to exist at"
" expected location of {}".format(ref.id, location.path))
stat = os.stat(location.path)
size = stat.st_size
if size != storedFileInfo.size:
raise RuntimeError(
"Integrity failure in Datastore. Size of file {} ({}) does not"
" match recorded size of {}".format(location.path, size,
storedFileInfo.size))
# We have a write storage class and a read storage class and they
# can be different for concrete composites.
readStorageClass = ref.datasetType.storageClass
writeStorageClass = storedFileInfo.storageClass
# Check that the supplied parameters are suitable for the type read
readStorageClass.validateParameters(parameters)
# Is this a component request?
component = ref.datasetType.component()
formatter = getInstanceOf(storedFileInfo.formatter)
formatterParams, assemblerParams = formatter.segregateParameters(
parameters)
try:
result = formatter.read(FileDescriptor(
location,
readStorageClass=readStorageClass,
storageClass=writeStorageClass,
parameters=parameters),
component=component)
except Exception as e:
raise ValueError(
"Failure from formatter for Dataset {}: {}".format(ref.id, e))
# Process any left over parameters
if parameters:
result = readStorageClass.assembler().handleParameters(
result, assemblerParams)
# Validate the returned data type matches the expected data type
pytype = readStorageClass.pytype
if pytype and not isinstance(result, pytype):
raise TypeError(
"Got type {} from formatter but expected {}".format(
type(result), pytype))
return result
@transactional
def put(self, inMemoryDataset, ref):
"""Write a InMemoryDataset with a given `DatasetRef` to the store.
Parameters
----------
inMemoryDataset : `object`
The Dataset to store.
ref : `DatasetRef`
Reference to the associated Dataset.
Raises
------
TypeError
Supplied object and storage class are inconsistent.
DatasetTypeNotSupportedError
The associated `DatasetType` is not handled by this datastore.
Notes
-----
If the datastore is configured to reject certain dataset types it
is possible that the put will fail and raise a
`DatasetTypeNotSupportedError`. The main use case for this is to
allow `ChainedDatastore` to put to multiple datastores without
requiring that every datastore accepts the dataset.
"""
datasetType = ref.datasetType
storageClass = datasetType.storageClass
# Sanity check
if not isinstance(inMemoryDataset, storageClass.pytype):
raise TypeError("Inconsistency between supplied object ({}) "
"and storage class type ({})".format(
type(inMemoryDataset), storageClass.pytype))
# Confirm that we can accept this dataset
if not self.constraints.isAcceptable(ref):
# Raise rather than use boolean return value.
raise DatasetTypeNotSupportedError(
f"Dataset {ref} has been rejected by this datastore via"
" configuration.")
# Work out output file name
try:
template = self.templates.getTemplate(ref)
except KeyError as e:
raise DatasetTypeNotSupportedError(
f"Unable to find template for {ref}") from e
location = self.locationFactory.fromPath(template.format(ref))
# Get the formatter based on the storage class
try:
formatter = self.formatterFactory.getFormatter(ref)
except KeyError as e:
raise DatasetTypeNotSupportedError(
f"Unable to find formatter for {ref}") from e
storageDir = os.path.dirname(location.path)
if not os.path.isdir(storageDir):
with self._transaction.undoWith("mkdir", os.rmdir, storageDir):
safeMakeDir(storageDir)
# Write the file
predictedFullPath = os.path.join(self.root,
formatter.predictPath(location))
if os.path.exists(predictedFullPath):
raise FileExistsError(
f"Cannot write file for ref {ref} as "
f"output file {predictedFullPath} already exists")
with self._transaction.undoWith("write", os.remove, predictedFullPath):
path = formatter.write(
inMemoryDataset,
FileDescriptor(location, storageClass=storageClass))
assert predictedFullPath == os.path.join(self.root, path)
log.debug("Wrote file to %s", path)
self.ingest(path, ref, formatter=formatter)
@transactional
def ingest(self, path, ref, formatter=None, transfer=None):
"""Add an on-disk file with the given `DatasetRef` to the store,
possibly transferring it.
The caller is responsible for ensuring that the given (or predicted)
Formatter is consistent with how the file was written; `ingest` will
in general silently ignore incorrect formatters (as it cannot
efficiently verify their correctness), deferring errors until ``get``
is first called on the ingested dataset.
Parameters
----------
path : `str`
File path. Treated as relative to the repository root if not
absolute.
ref : `DatasetRef`
Reference to the associated Dataset.
formatter : `Formatter` (optional)
Formatter that should be used to retreive the Dataset. If not
provided, the formatter will be constructed according to
Datastore configuration.
transfer : str (optional)
If not None, must be one of 'move', 'copy', 'hardlink', or
'symlink' indicating how to transfer the file. The new
filename and location will be determined via template substitution,
as with ``put``. If the file is outside the datastore root, it
must be transferred somehow.
Raises
------
RuntimeError
Raised if ``transfer is None`` and path is outside the repository
root.
FileNotFoundError
Raised if the file at ``path`` does not exist.
FileExistsError
Raised if ``transfer is not None`` but a file already exists at the
location computed from the template.
DatasetTypeNotSupportedError
The associated `DatasetType` is not handled by this datastore.
"""
# Confirm that we can accept this dataset
if not self.constraints.isAcceptable(ref):
# Raise rather than use boolean return value.
raise DatasetTypeNotSupportedError(
f"Dataset {ref} has been rejected by this datastore via"
" configuration.")
if formatter is None:
formatter = self.formatterFactory.getFormatter(ref)
fullPath = os.path.normpath(os.path.join(self.root, path))
if not os.path.exists(fullPath):
raise FileNotFoundError(
"File at '{}' does not exist; note that paths to ingest are "
"assumed to be relative to self.root unless they are absolute."
.format(fullPath))
if transfer is None:
if os.path.isabs(path):
absRoot = os.path.abspath(self.root)
if os.path.commonpath([absRoot, path]) != absRoot:
raise RuntimeError(
"'{}' is not inside repository root '{}'".format(
path, self.root))
path = os.path.relpath(path, absRoot)
elif path.startswith(os.path.pardir):
raise RuntimeError(
f"'{path}' is outside repository root '{self.root}'")
else:
template = self.templates.getTemplate(ref)
location = self.locationFactory.fromPath(template.format(ref))
newPath = formatter.predictPath(location)
newFullPath = os.path.join(self.root, newPath)
if os.path.exists(newFullPath):
raise FileExistsError(
"File '{}' already exists".format(newFullPath))
storageDir = os.path.dirname(newFullPath)
if not os.path.isdir(storageDir):
with self._transaction.undoWith("mkdir", os.rmdir, storageDir):
safeMakeDir(storageDir)
if transfer == "move":
with self._transaction.undoWith("move", shutil.move,
newFullPath, fullPath):
shutil.move(fullPath, newFullPath)
elif transfer == "copy":
with self._transaction.undoWith("copy", os.remove,
newFullPath):
shutil.copy(fullPath, newFullPath)
elif transfer == "hardlink":
with self._transaction.undoWith("hardlink", os.unlink,
newFullPath):
os.link(fullPath, newFullPath)
elif transfer == "symlink":
with self._transaction.undoWith("symlink", os.unlink,
newFullPath):
os.symlink(fullPath, newFullPath)
else:
raise NotImplementedError(
"Transfer type '{}' not supported.".format(transfer))
path = newPath
fullPath = newFullPath
# Create Storage information in the registry
checksum = self.computeChecksum(fullPath)
stat = os.stat(fullPath)
size = stat.st_size
self.registry.addDatasetLocation(ref, self.name)
# Associate this dataset with the formatter for later read.
fileInfo = StoredFileInfo(formatter,
path,
ref.datasetType.storageClass,
size=size,
checksum=checksum)
# TODO: this is only transactional if the DatabaseDict uses
# self.registry internally. Probably need to add
# transactions to DatabaseDict to do better than that.
self.addStoredFileInfo(ref, fileInfo)
# Register all components with same information
for compRef in ref.components.values():
self.registry.addDatasetLocation(compRef, self.name)
self.addStoredFileInfo(compRef, fileInfo)
def getUri(self, ref, predict=False):
"""URI to the Dataset.
Parameters
----------
ref : `DatasetRef`
Reference to the required Dataset.
predict : `bool`
If `True`, allow URIs to be returned of datasets that have not
been written.
Returns
-------
uri : `str`
URI string pointing to the Dataset within the datastore. If the
Dataset does not exist in the datastore, and if ``predict`` is
`True`, the URI will be a prediction and will include a URI
fragment "#predicted".
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.
Raises
------
FileNotFoundError
A URI has been requested for a dataset that does not exist and
guessing is not allowed.
"""
# if this has never been written then we have to guess
if not self.exists(ref):
if not predict:
raise FileNotFoundError(
"Dataset {} not in this datastore".format(ref))
template = self.templates.getTemplate(ref)
location = self.locationFactory.fromPath(
template.format(ref) + "#predicted")
else:
# If this is a ref that we have written we can get the path.
# Get file metadata and internal metadata
storedFileInfo = self.getStoredFileInfo(ref)
# Use the path to determine the location
location = self.locationFactory.fromPath(storedFileInfo.path)
return location.uri
def remove(self, ref):
"""Indicate to the Datastore that a Dataset can be removed.
.. warning::
This method does not support transactions; removals are
immediate, cannot be undone, and are not guaranteed to
be atomic if deleting either the file or the internal
database records fails.
Parameters
----------
ref : `DatasetRef`
Reference to the required Dataset.
Raises
------
FileNotFoundError
Attempt to remove a dataset that does not exist.
"""
# Get file metadata and internal metadata
try:
storedFileInfo = self.getStoredFileInfo(ref)
except KeyError:
raise FileNotFoundError(
"Requested dataset ({}) does not exist".format(ref))
location = self.locationFactory.fromPath(storedFileInfo.path)
if not os.path.exists(location.path):
raise FileNotFoundError("No such file: {0}".format(location.uri))
os.remove(location.path)
# Remove rows from registries
self.removeStoredFileInfo(ref)
self.registry.removeDatasetLocation(self.name, ref)
for compRef in ref.components.values():
self.registry.removeDatasetLocation(self.name, compRef)
self.removeStoredFileInfo(compRef)
def transfer(self, inputDatastore, ref):
"""Retrieve a Dataset from an input `Datastore`,
and store the result in this `Datastore`.
Parameters
----------
inputDatastore : `Datastore`
The external `Datastore` from which to retreive the Dataset.
ref : `DatasetRef`
Reference to the required Dataset in the input data store.
"""
assert inputDatastore is not self # unless we want it for renames?
inMemoryDataset = inputDatastore.get(ref)
return self.put(inMemoryDataset, ref)
def validateConfiguration(self, entities, logFailures=False):
"""Validate some of the configuration for this datastore.
Parameters
----------
entities : iterable of `DatasetRef`, `DatasetType`, or `StorageClass`
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.
All the problems are reported in a single exception.
Notes
-----
This method checks that all the supplied entities have valid file
templates and also have formatters defined.
"""
templateFailed = None
try:
self.templates.validateTemplates(entities, logFailures=logFailures)
except FileTemplateValidationError as e:
templateFailed = str(e)
formatterFailed = []
for entity in entities:
try:
self.formatterFactory.getFormatter(entity)
except KeyError as e:
formatterFailed.append(str(e))
if logFailures:
log.fatal("Formatter failure: %s", e)
if templateFailed or formatterFailed:
messages = []
if templateFailed:
messages.append(templateFailed)
if formatterFailed:
messages.append(",".join(formatterFailed))
msg = ";\n".join(messages)
raise DatastoreValidationError(msg)
def getLookupKeys(self):
# Docstring is inherited from base class
return self.templates.getLookupKeys() | self.formatterFactory.getLookupKeys() | \
self.constraints.getLookupKeys()
def validateKey(self, lookupKey, entity):
# Docstring is inherited from base class
# The key can be valid in either formatters or templates so we can
# only check the template if it exists
if lookupKey in self.templates:
try:
self.templates[lookupKey].validateTemplate(entity)
except FileTemplateValidationError as e:
raise DatastoreValidationError(e) from e
@staticmethod
def computeChecksum(filename, algorithm="blake2b", block_size=8192):
"""Compute the checksum of the supplied file.
Parameters
----------
filename : `str`
Name of file to calculate checksum from.
algorithm : `str`, optional
Name of algorithm to use. Must be one of the algorithms supported
by :py:class`hashlib`.
block_size : `int`
Number of bytes to read from file at one time.
Returns
-------
hexdigest : `str`
Hex digest of the file.
"""
if algorithm not in hashlib.algorithms_guaranteed:
raise NameError(
"The specified algorithm '{}' is not supported by hashlib".
format(algorithm))
hasher = hashlib.new(algorithm)
with open(filename, "rb") as f:
for chunk in iter(lambda: f.read(block_size), b""):
hasher.update(chunk)
return hasher.hexdigest()
class InMemoryDatastore(Datastore):
"""Basic Datastore for writing to an in memory cache.
This datastore is ephemeral in that the contents of the datastore
disappear when the Python process completes. This also means that
other processes can not access this datastore.
Attributes
----------
config : `DatastoreConfig`
Configuration used to create Datastore.
storageClassFactory : `StorageClassFactory`
Factory for creating storage class instances from name.
name : `str`
Label associated with this Datastore.
Parameters
----------
config : `DatastoreConfig` or `str`
Configuration.
"""
defaultConfigFile = "datastores/inMemoryDatastore.yaml"
"""Path to configuration defaults. Relative to $DAF_BUTLER_DIR/config or
absolute path. Can be None if no defaults specified.
"""
isEphemeral = True
"""A new datastore is created every time and datasets disappear when
the process shuts down."""
def __init__(self, config, registry=None, butlerRoot=None):
super().__init__(config, registry)
self.storageClassFactory = StorageClassFactory()
# Name ourselves with the timestamp the datastore
# was created.
self.name = "InMemoryDatastore@{}".format(time.time())
log.debug("Creating datastore %s", self.name)
# Storage of datasets, keyed by dataset_id
self.datasets = {}
# Records is distinct in order to track concrete composite components
# where we register multiple components for a single dataset.
self.records = {}
# And read the constraints list
constraintsConfig = self.config.get("constraints")
self.constraints = Constraints(constraintsConfig,
universe=self.registry.dimensions)
def __str__(self):
return "InMemory"
@classmethod
def setConfigRoot(cls, root, config, full, overwrite=True):
"""Set any filesystem-dependent config options for this Datastore to
be appropriate for a new empty repository with the given root.
Does nothing in this implementation.
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 from ``full`` to ``config``.
overwrite : `bool`, optional
If `False`, do not modify a value in ``config`` if the value
already exists. Default is always to overwrite with the provided
``root``.
Notes
-----
If a keyword is explicitly defined in the supplied ``config`` it
will not be overridden by this method if ``overwrite`` is `False`.
This allows explicit values set in external configs to be retained.
"""
return
def addStoredItemInfo(self, ref, info):
"""Record internal storage information associated with this
`DatasetRef`.
Parameters
----------
ref : `DatasetRef`
The Dataset that has been stored.
info : `StoredItemInfo`
Metadata associated with the stored Dataset.
Raises
------
KeyError
An entry with this DatasetRef already exists.
"""
if ref.id in self.records:
raise KeyError("Attempt to store item info with ID {}"
" when that ID exists as '{}'".format(
ref.id, self.records[ref.id]))
self.records[ref.id] = info
def removeStoredItemInfo(self, ref):
"""Remove information about the object associated with this dataset.
Parameters
----------
ref : `DatasetRef`
The Dataset that has been removed.
"""
del self.records[ref.id]
def getStoredItemInfo(self, ref):
"""Retrieve information associated with object stored in this
`Datastore`.
Parameters
----------
ref : `DatasetRef`
The Dataset that is to be queried.
Returns
-------
info : `StoredItemInfo`
Stored information about the internal location of this file
and its formatter.
Raises
------
KeyError
Dataset with that id can not be found.
"""
record = self.records.get(ref.id, None)
if record is None:
raise KeyError(
"Unable to retrieve information associated with Dataset {}".
format(ref.id))
return record
def exists(self, ref):
"""Check if the dataset exists in the datastore.
Parameters
----------
ref : `DatasetRef`
Reference to the required dataset.
Returns
-------
exists : `bool`
`True` if the entity exists in the `Datastore`.
"""
# Get the stored information (this will fail if no dataset)
try:
storedItemInfo = self.getStoredItemInfo(ref)
except KeyError:
return False
# The actual ID for the requested dataset might be that of a parent
# if this is a composite
thisref = ref.id
if storedItemInfo.parentID is not None:
thisref = storedItemInfo.parentID
return thisref in self.datasets
def get(self, ref, parameters=None):
"""Load an InMemoryDataset from the store.
Parameters
----------
ref : `DatasetRef`
Reference to the required Dataset.
parameters : `dict`
`StorageClass`-specific parameters that specify, for example,
a slice of the Dataset to be loaded.
Returns
-------
inMemoryDataset : `object`
Requested Dataset or slice thereof as an InMemoryDataset.
Raises
------
FileNotFoundError
Requested dataset can not be retrieved.
TypeError
Return value from formatter has unexpected type.
ValueError
Formatter failed to process the dataset.
"""
log.debug("Retrieve %s from %s with parameters %s", ref, self.name,
parameters)
if not self.exists(ref):
raise FileNotFoundError(
"Could not retrieve Dataset {}".format(ref))
# We have a write storage class and a read storage class and they
# can be different for concrete composites.
readStorageClass = ref.datasetType.storageClass
storedItemInfo = self.getStoredItemInfo(ref)
writeStorageClass = storedItemInfo.storageClass
# Check that the supplied parameters are suitable for the type read
readStorageClass.validateParameters(parameters)
# We might need a parent if we are being asked for a component
# of a concrete composite
thisID = ref.id
if storedItemInfo.parentID is not None:
thisID = storedItemInfo.parentID
inMemoryDataset = self.datasets[thisID]
# Different storage classes implies a component request
if readStorageClass != writeStorageClass:
component = ref.datasetType.component()
if component is None:
raise ValueError(
"Storage class inconsistency ({} vs {}) but no"
" component requested".format(readStorageClass.name,
writeStorageClass.name))
# Concrete composite written as a single object (we hope)
inMemoryDataset = writeStorageClass.assembler().getComponent(
inMemoryDataset, component)
# Handle parameters
if parameters:
inMemoryDataset = readStorageClass.assembler().handleParameters(
inMemoryDataset, parameters)
# Validate the returned data type matches the expected data type
pytype = readStorageClass.pytype
if pytype and not isinstance(inMemoryDataset, pytype):
raise TypeError("Got Python type {} (datasetType '{}')"
" but expected {}".format(type(inMemoryDataset),
ref.datasetType.name,
pytype))
return inMemoryDataset
def put(self, inMemoryDataset, ref):
"""Write a InMemoryDataset with a given `DatasetRef` to the store.
Parameters
----------
inMemoryDataset : `object`
The Dataset to store.
ref : `DatasetRef`
Reference to the associated Dataset.
Raises
------
TypeError
Supplied object and storage class are inconsistent.
DatasetTypeNotSupportedError
The associated `DatasetType` is not handled by this datastore.
Notes
-----
If the datastore is configured to reject certain dataset types it
is possible that the put will fail and raise a
`DatasetTypeNotSupportedError`. The main use case for this is to
allow `ChainedDatastore` to put to multiple datastores without
requiring that every datastore accepts the dataset.
"""
datasetType = ref.datasetType
storageClass = datasetType.storageClass
# Sanity check
if not isinstance(inMemoryDataset, storageClass.pytype):
raise TypeError("Inconsistency between supplied object ({}) "
"and storage class type ({})".format(
type(inMemoryDataset), storageClass.pytype))
# Confirm that we can accept this dataset
if not self.constraints.isAcceptable(ref):
# Raise rather than use boolean return value.
raise DatasetTypeNotSupportedError(
f"Dataset {ref} has been rejected by this datastore via"
" configuration.")
self.datasets[ref.id] = inMemoryDataset
log.debug("Store %s in %s", ref, self.name)
# We have to register this content with registry.
# Currently this assumes we have a file so we need to use stub entries
# TODO: Add to ephemeral part of registry
self.registry.addDatasetLocation(ref, self.name)
# Store time we received this content, to allow us to optionally
# expire it. Instead of storing a filename here, we include the
# ID of this datasetRef so we can find it from components.
itemInfo = StoredItemInfo(time.time(),
ref.datasetType.storageClass,
parentID=ref.id)
self.addStoredItemInfo(ref, itemInfo)
# Register all components with same information
for compRef in ref.components.values():
self.registry.addDatasetLocation(compRef, self.name)
self.addStoredItemInfo(compRef, itemInfo)
if self._transaction is not None:
self._transaction.registerUndo("put", self.remove, ref)
def getUri(self, ref, predict=False):
"""URI to the Dataset.
Always uses "mem://" URI prefix.
Parameters
----------
ref : `DatasetRef`
Reference to the required Dataset.
predict : `bool`
If `True`, allow URIs to be returned of datasets that have not
been written.
Returns
-------
uri : `str`
URI string pointing to the Dataset within the datastore. If the
Dataset does not exist in the datastore, and if ``predict`` is
`True`, the URI will be a prediction and will include a URI
fragment "#predicted".
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.
Raises
------
FileNotFoundError
A URI has been requested for a dataset that does not exist and
guessing is not allowed.
"""
# if this has never been written then we have to guess
if not self.exists(ref):
if not predict:
raise FileNotFoundError(
"Dataset {} not in this datastore".format(ref))
name = "{}#predicted".format(ref.datasetType.name)
else:
name = '{}'.format(id(self.datasets[ref.id]))
return "mem://{}".format(name)
def remove(self, ref):
"""Indicate to the Datastore that a Dataset can be removed.
Parameters
----------
ref : `DatasetRef`
Reference to the required Dataset.
Raises
------
FileNotFoundError
Attempt to remove a dataset that does not exist.
"""
if ref.id not in self.datasets:
raise FileNotFoundError(
"No such file dataset in memory: {}".format(ref))
del self.datasets[ref.id]
# Remove rows from registries
self.removeStoredItemInfo(ref)
self.registry.removeDatasetLocation(self.name, ref)
for compRef in ref.components.values():
self.registry.removeDatasetLocation(self.name, compRef)
self.removeStoredItemInfo(compRef)
def transfer(self, inputDatastore, ref):
"""Retrieve a Dataset from an input `Datastore`,
and store the result in this `Datastore`.
Parameters
----------
inputDatastore : `Datastore`
The external `Datastore` from which to retreive the Dataset.
ref : `DatasetRef`
Reference to the required Dataset in the input data store.
"""
assert inputDatastore is not self # unless we want it for renames?
inMemoryDataset = inputDatastore.get(ref)
return self.put(inMemoryDataset, ref)
def validateConfiguration(self, entities, logFailures=False):
"""Validate some of the configuration for this datastore.
Parameters
----------
entities : iterable of `DatasetRef`, `DatasetType`, or `StorageClass`
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.
All the problems are reported in a single exception.
Notes
-----
This method is a no-op.
"""
return
def validateKey(self, lookupKey, entity):
# Docstring is inherited from base class
return
def getLookupKeys(self):
# Docstring is inherited from base class
return self.constraints.getLookupKeys()
