Source code for galaxy.managers.datasets

Manager and Serializer for Datasets.

import glob
import logging
import os
from typing import (

from sqlalchemy import select

from galaxy import (
from galaxy.datatypes import sniff
from galaxy.managers import (
from galaxy.model import (
from galaxy.model.base import transaction
from galaxy.schema.tasks import (
from galaxy.structured_app import MinimalManagerApp
from galaxy.util.hash_util import memory_bound_hexdigest

log = logging.getLogger(__name__)

T = TypeVar("T")

[docs]class DatasetManager(base.ModelManager[model.Dataset], secured.AccessibleManagerMixin, deletable.PurgableManagerMixin): """ Manipulate datasets: the components contained in DatasetAssociations/DatasetInstances/HDAs/LDDAs """ model_class = model.Dataset foreign_key_name = "dataset" app: MinimalManagerApp # TODO:?? get + error_if_uploading is common pattern, should upload check be worked into access/owed?
[docs] def __init__(self, app: MinimalManagerApp): super().__init__(app) self.permissions = DatasetRBACPermissions(app) # needed for admin test self.user_manager = users.UserManager(app) self.quota_agent = app.quota_agent self.security_agent = app.model.security_agent
[docs] def create(self, manage_roles=None, access_roles=None, flush=True, **kwargs): """ Create and return a new Dataset object. """ # default to NEW state on new datasets kwargs.update(dict(state=(kwargs.get("state", model.Dataset.states.NEW)))) dataset = model.Dataset(**kwargs) self.session().add(dataset) self.permissions.set(dataset, manage_roles, access_roles, flush=False) if flush: session = self.session() with transaction(session): session.commit() return dataset
[docs] def copy(self, dataset, **kwargs): raise exceptions.NotImplemented("Datasets cannot be copied")
[docs] def purge(self, dataset, flush=True): """ Remove the object_store/file for this dataset from storage and mark as purged. :raises exceptions.ConfigDoesNotAllowException: if the instance doesn't allow """ self.error_unless_dataset_purge_allowed(dataset) # the following also marks dataset as purged and deleted dataset.full_delete() self.session().add(dataset) if flush: session = self.session() with transaction(session): session.commit() return dataset
[docs] def purge_datasets(self, request: PurgeDatasetsTaskRequest): """ Caution: any additional security checks must be done before executing this action. Completely removes a set of object_store/files associated with the datasets from storage and marks them as purged. They might not be removed if there are still un-purged associations to the dataset. """ self.error_unless_dataset_purge_allowed() with self.session().begin(): for dataset_id in request.dataset_ids: dataset: Dataset = self.session().get(Dataset, dataset_id) if dataset.user_can_purge: try: dataset.full_delete() except Exception: log.exception(f"Unable to purge dataset ({})")
# TODO: this may be more conv. somewhere else # TODO: how to allow admin bypass?
[docs] def error_unless_dataset_purge_allowed(self, msg=None): if not msg = msg or "This instance does not allow user dataset purging" raise exceptions.ConfigDoesNotAllowException(msg)
# .... accessibility # datasets can implement the accessible interface, but accessibility is checked in an entirely different way # than those resources that have a user attribute (histories, pages, etc.)
[docs] def is_accessible(self, item: Any, user: Optional[model.User], **kwargs) -> bool: """ Is this dataset readable/viewable to user? """ if self.user_manager.is_admin(user, trans=kwargs.get("trans")): return True if self.has_access_permission(item, user): return True return False
[docs] def has_access_permission(self, dataset, user): """ Return T/F if the user has role-based access to the dataset. """ roles = user.all_roles_exploiting_cache() if user else [] return, dataset)
[docs] def update_object_store_id(self, trans, dataset, object_store_id: str): device_source_map = old_object_store_id = dataset.object_store_id new_object_store_id = object_store_id if old_object_store_id == new_object_store_id: return None old_device_id = device_source_map.get_device_id(old_object_store_id) new_device_id = device_source_map.get_device_id(new_object_store_id) if old_device_id != new_device_id: raise exceptions.RequestParameterInvalidException( "Cannot swap object store IDs for object stores that don't share a device ID." ) if not self.security_agent.can_change_object_store_id(trans.user, dataset): # TODO: probably want separate exceptions for doesn't own the dataset and dataset # has been shared. raise exceptions.InsufficientPermissionsException("Cannot change dataset permissions...") quota_source_map = if quota_source_map: old_label = quota_source_map.get_quota_source_label(old_object_store_id) new_label = quota_source_map.get_quota_source_label(new_object_store_id) if old_label != new_label: self.quota_agent.relabel_quota_for_dataset(dataset, old_label, new_label) sa_session = with transaction(sa_session): dataset.object_store_id = new_object_store_id sa_session.add(dataset) sa_session.commit()
[docs] def compute_hash(self, request: ComputeDatasetHashTaskRequest): # For files in extra_files_path dataset = self.by_id(request.dataset_id) extra_files_path = request.extra_files_path if extra_files_path: extra_dir = dataset.extra_files_path_name file_path =, extra_dir=extra_dir, alt_name=extra_files_path) else: file_path = dataset.get_file_name() hash_function = request.hash_function calculated_hash_value = memory_bound_hexdigest(hash_func_name=hash_function, path=file_path) extra_files_path = request.extra_files_path dataset_hash = model.DatasetHash( hash_function=hash_function, hash_value=calculated_hash_value, extra_files_path=extra_files_path, ) dataset_hash.dataset = dataset # TODO: replace/update if the combination of dataset_id/hash_function has already # been stored. sa_session = self.session() hash = get_dataset_hash(sa_session,, hash_function, extra_files_path) if hash is None: sa_session.add(dataset_hash) with transaction(sa_session): sa_session.commit() else: old_hash_value = hash.hash_value if old_hash_value != calculated_hash_value: log.warning( f"Re-calculated dataset hash for dataset [{}] and new hash value [{calculated_hash_value}] does not equal previous hash value [{old_hash_value}]." ) else: log.debug("Duplicated dataset hash request, no update to the database.")
# TODO: implement above for groups # TODO: datatypes? # .... data, object_store # TODO: SecurityAgentDatasetRBACPermissions( object ):
[docs]class DatasetRBACPermissions:
[docs] def __init__(self, app): = app self.access = rbac_secured.AccessDatasetRBACPermission(app) self.manage = rbac_secured.ManageDatasetRBACPermission(app)
# TODO: temporary facade over security_agent
[docs] def available_roles(self, trans, dataset, controller="root"): return, dataset, controller)
[docs] def get(self, dataset, flush=True): manage = self.manage.by_dataset(dataset) access = self.access.by_dataset(dataset) return (manage, access)
[docs] def set(self, dataset, manage_roles, access_roles, flush=True): manage = self.manage.set(dataset, manage_roles or [], flush=False) access = self.access.set(dataset, access_roles or [], flush=flush) return (manage, access)
# ---- conv. settings
[docs] def set_public_with_single_manager(self, dataset, user, flush=True): manage = self.manage.grant(dataset, user, flush=flush) self.access.clear(dataset, flush=False) return ([manage], [])
[docs] def set_private_to_one_user(self, dataset, user, flush=True): manage = self.manage.grant(dataset, user, flush=False) access = self.access.set_private(dataset, user, flush=flush) return ([manage], access)
[docs]class DatasetSerializer(base.ModelSerializer[DatasetManager], deletable.PurgableSerializerMixin): model_manager_class = DatasetManager
[docs] def __init__(self, app: MinimalManagerApp, user_manager: users.UserManager): super().__init__(app) self.dataset_manager = self.manager # needed for admin test self.user_manager = user_manager self.default_view = "summary" self.add_view( "summary", [ "id", "create_time", "update_time", "state", "deleted", "purged", "purgable", # 'object_store_id', # 'external_filename', # 'extra_files_path', "file_size", "total_size", "uuid", ], )
# could do visualizations and/or display_apps
[docs] def add_serializers(self): super().add_serializers() deletable.PurgableSerializerMixin.add_serializers(self) serializers: Dict[str, base.Serializer] = { "create_time": self.serialize_date, "update_time": self.serialize_date, "uuid": lambda item, key, **context: str(item.uuid) if item.uuid else None, "file_name": self.serialize_file_name, "extra_files_path": self.serialize_extra_files_path, "permissions": self.serialize_permissions, "total_size": lambda item, key, **context: int(item.get_total_size()), "file_size": lambda item, key, **context: int(item.get_size(calculate_size=False)), } self.serializers.update(serializers)
[docs] def serialize_file_name(self, item, key, user=None, **context): """ If the config allows or the user is admin, return the file name of the file that contains this dataset's data. """ dataset = item is_admin = self.user_manager.is_admin(user, trans=context.get("trans")) # expensive: allow config option due to cost of operation if is_admin or if not dataset.purged: return dataset.get_file_name(sync_cache=False) self.skip()
[docs] def serialize_extra_files_path(self, item, key, user=None, **context): """ If the config allows or the user is admin, return the file path. """ dataset = item is_admin = self.user_manager.is_admin(user, trans=context.get("trans")) # expensive: allow config option due to cost of operation if is_admin or if not dataset.purged: return dataset.extra_files_path self.skip()
[docs] def serialize_permissions(self, item, key, user=None, **context): """ """ dataset = item trans = context.get("trans") if not self.dataset_manager.permissions.manage.is_permitted(dataset, user, trans=trans): self.skip() management_permissions = self.dataset_manager.permissions.manage.by_dataset(dataset) access_permissions = self.dataset_manager.permissions.access.by_dataset(dataset) permissions = { "manage": [ for perm in management_permissions], "access": [ for perm in access_permissions], } return permissions
# ============================================================================= AKA DatasetInstanceManager
[docs]class DatasetAssociationManager( base.ModelManager[model.DatasetInstance], secured.AccessibleManagerMixin, secured.OwnableManagerMixin, deletable.PurgableManagerMixin, ): """ DatasetAssociation/DatasetInstances are intended to be working proxies to a Dataset, associated with either a library or a user/history (HistoryDatasetAssociation). """ # DA's were meant to be proxies - but were never fully implemented as them # Instead, a dataset association HAS a dataset but contains metadata specific to a library (lda) or user (hda) app: MinimalManagerApp # NOTE: model_manager_class should be set in HDA/LDA subclasses
[docs] def __init__(self, app): super().__init__(app) self.dataset_manager = DatasetManager(app)
[docs] def is_accessible(self, item, user: Optional[model.User], **kwargs: Any) -> bool: """ Is this DA accessible to `user`? """ # defer to the dataset return self.dataset_manager.is_accessible(item.dataset, user, **kwargs)
[docs] def delete(self, item, flush: bool = True, stop_job: bool = False, **kwargs): """ Marks this dataset association as deleted. If `stop_job` is True, will stop the creating job if all other outputs are deleted. """ super().delete(item, flush=flush) if stop_job: self.stop_creating_job(item, flush=flush) return item
[docs] def purge(self, dataset_assoc, flush=True): """ Purge this DatasetInstance and the dataset underlying it. """ # error here if disallowed - before jobs are stopped # TODO: this check may belong in the controller self.dataset_manager.error_unless_dataset_purge_allowed() # We need to ignore a potential flush=False here if jobs are not tracked in the database, # so that job cleanup associated with stop_creating_job will see # the dataset as purged. flush_required = not super().purge(dataset_assoc, flush=flush or flush_required) # stop any jobs outputing the dataset_assoc self.stop_creating_job(dataset_assoc, flush=True) # more importantly, purge underlying dataset as well if dataset_assoc.dataset.user_can_purge: self.dataset_manager.purge(dataset_assoc.dataset) return dataset_assoc
[docs] def by_user(self, user): raise exceptions.NotImplemented("Abstract Method")
# .... associated job
[docs] def creating_job(self, dataset_assoc): """ Return the `Job` that created this dataset or None if not found. """ # TODO: is this needed? Can't you use the dataset_assoc.creating_job attribute? When is this None? # TODO: this would be even better if outputs and inputs were the underlying datasets job = None for job_output_assoc in dataset_assoc.creating_job_associations: job = job_output_assoc.job break return job
[docs] def stop_creating_job(self, dataset_assoc, flush=False): """ Stops an dataset_assoc's creating job if all the job's other outputs are deleted. """ # Optimize this to skip other checks if this dataset is terminal - we can infer the # job is already complete. if dataset_assoc.state in model.Dataset.terminal_states: return False if dataset_assoc.parent_id is None and len(dataset_assoc.creating_job_associations) > 0: # Mark associated job for deletion job = dataset_assoc.creating_job_associations[0].job if not job.finished: # Are *all* of the job's other output datasets deleted? if job.check_if_output_datasets_deleted(): track_jobs_in_database = job.mark_deleted(track_jobs_in_database) if not track_jobs_in_database: if flush: session = self.session() with transaction(session): session.commit() return True return False
[docs] def is_composite(self, dataset_assoc): """ Return True if this hda/ldda is a composite type dataset. .. note:: see also (whereever we keep information on composite datatypes?) """ return dataset_assoc.extension in
[docs] def extra_files(self, dataset_assoc): """Return a list of file paths for composite files, an empty list otherwise.""" if not self.is_composite(dataset_assoc): return [] return glob.glob(os.path.join(dataset_assoc.dataset.extra_files_path, "*"))
[docs] def serialize_dataset_association_roles(self, trans, dataset_assoc): if hasattr(dataset_assoc, "library_dataset_dataset_association"): library_dataset = dataset_assoc dataset = library_dataset.library_dataset_dataset_association.dataset else: library_dataset = None dataset = dataset_assoc.dataset # Omit duplicated roles by converting to set security_agent = access_roles = set(dataset.get_access_roles(security_agent)) manage_roles = set(dataset.get_manage_permissions_roles(security_agent)) access_dataset_role_list = [ (, for access_role in access_roles ] manage_dataset_role_list = [ (, for manage_role in manage_roles ] rval = dict(access_dataset_roles=access_dataset_role_list, manage_dataset_roles=manage_dataset_role_list) if library_dataset is not None: modify_roles = set( security_agent.get_roles_for_action( library_dataset, ) ) modify_item_role_list = [ (, for modify_role in modify_roles ] rval["modify_item_roles"] = modify_item_role_list return rval
[docs] def ensure_dataset_on_disk(self, trans, dataset): # Not a guarantee data is really present, but excludes a lot of expected cases if dataset.purged or dataset.dataset.purged: raise exceptions.ItemDeletionException("The dataset you are attempting to view has been purged.") elif dataset.deleted and not (trans.user_is_admin or self.is_owner(dataset, trans.get_user())): raise exceptions.ItemDeletionException("The dataset you are attempting to view has been deleted.") elif dataset.state == Dataset.states.UPLOAD: raise exceptions.Conflict("Please wait until this dataset finishes uploading before attempting to view it.") elif dataset.state == Dataset.states.DISCARDED: raise exceptions.ItemDeletionException("The dataset you are attempting to view has been discarded.") elif dataset.state == Dataset.states.DEFERRED: raise exceptions.Conflict( "The dataset you are attempting to view has deferred data. You can only use this dataset as input for jobs." ) elif dataset.state == Dataset.states.PAUSED: raise exceptions.Conflict( "The dataset you are attempting to view is in paused state. One of the inputs for the job that creates this dataset has failed." )
[docs] def ensure_can_change_datatype(self, dataset: model.DatasetInstance, raiseException: bool = True) -> bool: if not dataset.datatype.is_datatype_change_allowed(): if not raiseException: return False raise exceptions.InsufficientPermissionsException( f'Changing datatype "{dataset.extension}" is not allowed.' ) return True
[docs] def ensure_can_set_metadata(self, dataset: model.DatasetInstance, raiseException: bool = True) -> bool: if not dataset.ok_to_edit_metadata(): if not raiseException: return False raise exceptions.ItemAccessibilityException( "This dataset is currently being used as input or output. You cannot change datatype until the jobs have completed or you have canceled them." ) return True
[docs] def detect_datatype(self, trans, dataset_assoc): """Sniff and assign the datatype to a given dataset association (ldda or hda)""" data = trans.sa_session.get(self.model_class, self.ensure_can_change_datatype(data) self.ensure_can_set_metadata(data) path = data.dataset.get_file_name() datatype = sniff.guess_ext(path,, datatype) with transaction(trans.sa_session): trans.sa_session.commit() self.set_metadata(trans, dataset_assoc)
[docs] def set_metadata(self, trans, dataset_assoc, overwrite=False, validate=True): """Trigger a job that detects and sets metadata on a given dataset association (ldda or hda)""" data = trans.sa_session.get(self.model_class, self.ensure_can_set_metadata(data) if overwrite: self.overwrite_metadata(data) job, *_ =, trans, incoming={"input1": data, "validate": validate}, overwrite=overwrite, ),
[docs] def overwrite_metadata(self, data): for name, spec in data.metadata.spec.items(): # We need to be careful about the attributes we are resetting if name not in ["name", "info", "dbkey", "base_name"]: if spec.get("default"): setattr(data.metadata, name, spec.unwrap(spec.get("default")))
[docs] def update_permissions(self, trans, dataset_assoc, **kwd): action = kwd.get("action", "set_permissions") if action not in ["remove_restrictions", "make_private", "set_permissions"]: raise exceptions.RequestParameterInvalidException( 'The mandatory parameter "action" has an invalid value. ' 'Allowed values are: "remove_restrictions", "make_private", "set_permissions"' ) if hasattr(dataset_assoc, "library_dataset_dataset_association"): library_dataset = dataset_assoc dataset = library_dataset.library_dataset_dataset_association.dataset else: library_dataset = None dataset = dataset_assoc.dataset current_user_roles = trans.get_current_user_roles() can_manage =, dataset) or trans.user_is_admin if not can_manage: raise exceptions.InsufficientPermissionsException( "You do not have proper permissions to manage permissions on this dataset." ) if action == "remove_restrictions": if not raise exceptions.InternalServerError("An error occurred while making dataset public.") elif action == "make_private": if not, dataset): private_role = dp =, dataset, private_role ) trans.sa_session.add(dp) with transaction(trans.sa_session): trans.sa_session.commit() if not, dataset): # Check again and inform the user if dataset is not private. raise exceptions.InternalServerError("An error occurred and the dataset is NOT private.") elif action == "set_permissions": def parameters_roles_or_none(role_type): return kwd.get(role_type, kwd.get(f"{role_type}_ids[]")) access_roles = parameters_roles_or_none("access") manage_roles = parameters_roles_or_none("manage") modify_roles = parameters_roles_or_none("modify") role_ids_dict = { "DATASET_MANAGE_PERMISSIONS": manage_roles, "DATASET_ACCESS": access_roles, } if library_dataset is not None: role_ids_dict["LIBRARY_MODIFY"] = modify_roles self._set_permissions(trans, dataset_assoc, role_ids_dict)
def _set_permissions(self, trans, dataset_assoc, roles_dict): raise exceptions.NotImplemented()
class _UnflattenedMetadataDatasetAssociationSerializer(base.ModelSerializer[T], deletable.PurgableSerializerMixin): def __init__(self, app): self.dataset_serializer = app[DatasetSerializer] super().__init__(app) def add_serializers(self): super().add_serializers() deletable.PurgableSerializerMixin.add_serializers(self) serializers: Dict[str, base.Serializer] = { "create_time": self.serialize_date, "update_time": self.serialize_date, # underlying dataset "dataset": lambda item, key, **context: self.dataset_serializer.serialize_to_view( item.dataset, view="summary", **context ), "dataset_id": self._proxy_to_dataset(proxy_key="id"), # TODO: why is this named uuid!? The da doesn't have a uuid - it's the underlying dataset's uuid! "uuid": self._proxy_to_dataset(proxy_key="uuid"), # 'dataset_uuid': self._proxy_to_dataset( key='uuid' ), "file_name": self._proxy_to_dataset(serializer=self.dataset_serializer.serialize_file_name), "extra_files_path": self._proxy_to_dataset(serializer=self.dataset_serializer.serialize_extra_files_path), "permissions": self._proxy_to_dataset(serializer=self.dataset_serializer.serialize_permissions), # TODO: do the sizes proxy accurately/in the same way? "size": lambda item, key, **context: int(item.get_size(calculate_size=False)), "file_size": lambda item, key, **context: self.serializers["size"](item, key, **context), "nice_size": lambda item, key, **context: item.get_size(nice_size=True, calculate_size=False), # common to lddas and hdas - from "copied_from_history_dataset_association_id": self.serialize_id, "copied_from_library_dataset_dataset_association_id": self.serialize_id, "info": lambda item, key, **context: if isinstance(, str) else, "blurb": lambda item, key, **context: item.blurb, "peek": lambda item, key, **context: item.display_peek() if item.peek and item.peek != "no peek" else None, "meta_files": self.serialize_meta_files, "metadata": self.serialize_metadata, "creating_job": self.serialize_creating_job, "rerunnable": self.serialize_rerunnable, "parent_id": self.serialize_id, "designation": lambda item, key, **context: item.designation, # 'extended_metadata': self.serialize_extended_metadata, # 'extended_metadata_id': self.serialize_id, # remapped # TODO: Replace string cast with on 24.1 "genome_build": lambda item, key, **context: str(item.dbkey) if item.dbkey is not None else None, # derived (not mapped) attributes "data_type": lambda item, key, **context: f"{item.datatype.__class__.__module__}.{item.datatype.__class__.__name__}", "converted": self.serialize_converted_datasets, # TODO: metadata/extra files } self.serializers.update(serializers) # this an abstract superclass, so no views created # because of that: we need to add a few keys that will use the default serializer self.serializable_keyset.update(["name", "state", "tool_version", "extension", "visible", "dbkey"]) def _proxy_to_dataset(self, serializer: Optional[base.Serializer] = None, proxy_key: Optional[str] = None): # dataset associations are (rough) proxies to datasets - access their serializer using this remapping fn # remapping done by either kwarg key: IOW dataset attr key (e.g. uuid) # or by kwarg serializer: a function that's passed in (e.g. permissions) if proxy_key: serializer = self.dataset_serializer.serializers.get(proxy_key) if serializer: return lambda item, key, **context: serializer(item.dataset, proxy_key or key, **context) raise TypeError("kwarg serializer or key needed") def serialize_meta_files(self, item, key, **context): """ Cycle through meta files and return them as a list of dictionaries. """ dataset_assoc = item meta_files = [] for meta_type in dataset_assoc.metadata_file_types: if getattr(dataset_assoc.metadata, meta_type, None): meta_files.append( dict( file_type=meta_type, download_url=self.url_for( "get_metadata_file",,, query_params={"metadata_file": meta_type}, context=context, ), ) ) return meta_files def serialize_metadata(self, item, key, excluded=None, **context): """ Cycle through metadata and return as dictionary. """ dataset_assoc = item # dbkey is a repeat actually (metadata_dbkey == genome_build) # excluded = [ 'dbkey' ] if excluded is None else excluded excluded = [] if excluded is None else excluded metadata = {} for name, spec in dataset_assoc.metadata.spec.items(): if name in excluded: continue val = dataset_assoc.metadata.get(name) # NOTE: no files if isinstance(val, model.MetadataFile): # only when explicitly set: fetching filepaths can be expensive if not continue val = val.get_file_name() # TODO:? possibly split this off? # If no value for metadata, look in datatype for metadata. elif val is None and hasattr(dataset_assoc.datatype, name): val = getattr(dataset_assoc.datatype, name) if val is None and spec.get("optional"): continue metadata[name] = val return metadata def serialize_creating_job(self, item, key, **context): """ Return the id of the Job that created this dataset (or its original) or None if no `creating_job` is found. """ dataset = item if dataset.creating_job: return self.serialize_id(dataset.creating_job, "id") else: return None def serialize_rerunnable(self, item, key, **context): """ Return False if this tool that created this dataset can't be re-run (e.g. upload). """ dataset = item if dataset.creating_job: tool =, dataset.creating_job.tool_version) if tool and tool.is_workflow_compatible: return True return False def serialize_converted_datasets(self, item, key, **context): """ Return a file extension -> converted dataset encoded id map with all the existing converted datasets associated with this instance. This filters out deleted associations. """ dataset_assoc = item id_map = {} for converted in dataset_assoc.implicitly_converted_datasets: if not converted.deleted and converted.dataset: id_map[converted.type] = self.serialize_id(converted.dataset, "id") return id_map
[docs]class DatasetAssociationSerializer(_UnflattenedMetadataDatasetAssociationSerializer[T]): # TODO: remove this class - metadata should be a sub-object instead as in the superclass
[docs] def add_serializers(self): super().add_serializers() # remove the single nesting key here del self.serializers["metadata"]
[docs] def serialize(self, dataset_assoc, keys, **context): """ Override to add metadata as flattened keys on the serialized DatasetInstance. """ # if 'metadata' isn't removed from keys here serialize will retrieve the un-serializable MetadataCollection # TODO: remove these when metadata is sub-object KEYS_HANDLED_SEPARATELY = ("metadata",) left_to_handle = self._pluck_from_list(keys, KEYS_HANDLED_SEPARATELY) serialized = super().serialize(dataset_assoc, keys, **context) # add metadata directly to the dict instead of as a sub-object if "metadata" in left_to_handle: metadata = self._prefixed_metadata(dataset_assoc) serialized.update(metadata) return serialized
# TODO: this is more util/gen. use def _pluck_from_list(self, list_, elems): """ Removes found elems from list list_ and returns list of found elems if found. """ found = [] for elem in elems: try: index = list_.index(elem) found.append(list_.pop(index)) except ValueError: pass return found def _prefixed_metadata(self, dataset_assoc): """ Adds (a prefixed version of) the DatasetInstance metadata to the dict, prefixing each key with 'metadata_'. """ # build the original, nested dictionary metadata = self.serialize_metadata(dataset_assoc, "metadata") # prefix each key within and return prefixed = {} for key, val in metadata.items(): prefixed_key = f"metadata_{key}" prefixed[prefixed_key] = val return prefixed
[docs]class DatasetAssociationDeserializer(base.ModelDeserializer, deletable.PurgableDeserializerMixin):
[docs] def add_deserializers(self): super().add_deserializers() deletable.PurgableDeserializerMixin.add_deserializers(self) self.deserializers.update( { "name": self.deserialize_basestring, "info": self.deserialize_basestring, "datatype": self.deserialize_datatype, } ) self.deserializable_keyset.update(self.deserializers.keys())
# TODO: untested
[docs] def deserialize_metadata(self, dataset_assoc, metadata_key, metadata_dict, **context): """ """ self.validate.matches_type(metadata_key, metadata_dict, dict) returned = {} for key, val in metadata_dict.items(): returned[key] = self.deserialize_metadatum(dataset_assoc, key, val, **context) return returned
[docs] def deserialize_metadatum(self, dataset_assoc, key, val, **context): """ """ if key not in dataset_assoc.datatype.metadata_spec: return metadata_specification = dataset_assoc.datatype.metadata_spec[key] if metadata_specification.get("readonly"): return unwrapped_val = metadata_specification.unwrap(val) setattr(dataset_assoc.metadata, key, unwrapped_val) # ...? return unwrapped_val
[docs] def deserialize_datatype(self, item, key, val, **context): if not item.datatype.is_datatype_change_allowed(): raise exceptions.RequestParameterInvalidException("The current datatype does not allow datatype changes.") target_datatype = if not target_datatype: raise exceptions.RequestParameterInvalidException("The target datatype does not exist.") if not target_datatype.is_datatype_change_allowed(): raise exceptions.RequestParameterInvalidException("The target datatype does not allow datatype changes.") if not item.ok_to_edit_metadata(): raise exceptions.RequestParameterInvalidException( "Dataset metadata could not be updated because it is used as input or output of a running job." ) item.change_datatype(val) sa_session = with transaction(sa_session): sa_session.commit() trans = context.get("trans") assert ( trans ), "Logic error in Galaxy, deserialize_datatype not send a transation object" # TODO: restructure this for stronger typing job, *_ =, trans, incoming={"input1": item}, overwrite=False ) # overwrite is False as per existing behavior, return item.datatype
[docs]class DatasetAssociationFilterParser(base.ModelFilterParser, deletable.PurgableFiltersMixin): def _add_parsers(self): super()._add_parsers() deletable.PurgableFiltersMixin._add_parsers(self) self.orm_filter_parsers.update( { "name": {"op": ("eq", "contains", "like")}, "state": {"column": "_state", "op": ("eq", "in")}, "visible": {"op": ("eq"), "val": base.parse_bool}, } ) self.fn_filter_parsers.update( { "genome_build": self.string_standard_ops("dbkey"), "data_type": {"op": {"eq": self.eq_datatype, "isinstance": self.isinstance_datatype}}, } )
[docs] def eq_datatype(self, dataset_assoc, class_str): """ Is the `dataset_assoc` datatype equal to the registered datatype `class_str`? """ comparison_class = return comparison_class and dataset_assoc.datatype.__class__ == comparison_class
[docs] def isinstance_datatype(self, dataset_assoc, class_strs): """ Is the `dataset_assoc` datatype derived from any of the registered datatypes in the comma separated string `class_strs`? """ parse_datatype_fn = comparison_classes: List[Type] = [] for class_str in class_strs.split(","): datatype_class = parse_datatype_fn(class_str) if datatype_class: comparison_classes.append(datatype_class) return comparison_classes and isinstance(dataset_assoc.datatype, tuple(comparison_classes))
[docs]def get_dataset_hash(session, dataset_id, hash_function, extra_files_path): stmt = ( select(DatasetHash) .where(DatasetHash.dataset_id == dataset_id) .where(DatasetHash.hash_function == hash_function) .where(DatasetHash.extra_files_path == extra_files_path) ) return session.scalars(stmt).one_or_none()