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Source code for galaxy.managers.datasets
"""
Manager and Serializer for Datasets.
"""
import glob
import logging
import os
from typing import (
Any,
Dict,
List,
Optional,
Type,
TypeVar,
)
from sqlalchemy import select
from galaxy import (
exceptions,
model,
)
from galaxy.datatypes import sniff
from galaxy.managers import (
base,
deletable,
rbac_secured,
secured,
users,
)
from galaxy.model import (
Dataset,
DatasetHash,
)
from galaxy.model.base import transaction
from galaxy.schema.tasks import (
ComputeDatasetHashTaskRequest,
PurgeDatasetsTaskRequest,
)
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)
[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 ({dataset.id})")
# 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 self.app.config.allow_user_dataset_purge:
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 self.app.security_agent.can_access_dataset(roles, dataset)
[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 = self.app.object_store.get_filename(dataset, 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.value,
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, dataset.id, 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 [{dataset.id}] 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):
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 self.app.security_agent.get_legitimate_roles(trans, 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 self.app.config.expose_dataset_path:
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 self.app.config.expose_dataset_path:
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": [self.app.security.encode_id(perm.role.id) for perm in management_permissions],
"access": [self.app.security.encode_id(perm.role.id) 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 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 self.app.config.track_jobs_in_database
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
# .... 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 = self.app.config.track_jobs_in_database
job.mark_deleted(track_jobs_in_database)
if not track_jobs_in_database:
self.app.job_manager.stop(job)
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 self.app.datatypes_registry.get_composite_extensions()
[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 = trans.app.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 = [
(access_role.name, trans.security.encode_id(access_role.id)) for access_role in access_roles
]
manage_dataset_role_list = [
(manage_role.name, trans.security.encode_id(manage_role.id)) 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, trans.app.security_agent.permitted_actions.LIBRARY_MODIFY
)
)
modify_item_role_list = [
(modify_role.name, trans.security.encode_id(modify_role.id)) for modify_role in modify_roles
]
rval["modify_item_roles"] = modify_item_role_list
return rval
[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, dataset_assoc.id)
self.ensure_can_change_datatype(data)
self.ensure_can_set_metadata(data)
path = data.dataset.get_file_name()
datatype = sniff.guess_ext(path, trans.app.datatypes_registry.sniff_order)
trans.app.datatypes_registry.change_datatype(data, 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, dataset_assoc.id)
self.ensure_can_set_metadata(data)
if overwrite:
self.overwrite_metadata(data)
job, *_ = self.app.datatypes_registry.set_external_metadata_tool.tool_action.execute(
self.app.datatypes_registry.set_external_metadata_tool,
trans,
incoming={"input1": data, "validate": validate},
overwrite=overwrite,
)
self.app.job_manager.enqueue(job, tool=self.app.datatypes_registry.set_external_metadata_tool)
[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 = trans.app.security_agent.can_manage_dataset(current_user_roles, 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":
trans.app.security_agent.make_dataset_public(dataset)
if not trans.app.security_agent.dataset_is_public(dataset):
raise exceptions.InternalServerError("An error occurred while making dataset public.")
elif action == "make_private":
if not trans.app.security_agent.dataset_is_private_to_user(trans, dataset):
private_role = trans.app.security_agent.get_private_user_role(trans.user)
dp = trans.app.model.DatasetPermissions(
trans.app.security_agent.permitted_actions.DATASET_ACCESS.action, dataset, private_role
)
trans.sa_session.add(dp)
with transaction(trans.sa_session):
trans.sa_session.commit()
if not trans.app.security_agent.dataset_is_private_to_user(trans, 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 mapping.py
"copied_from_history_dataset_association_id": self.serialize_id,
"copied_from_library_dataset_dataset_association_id": self.serialize_id,
"info": lambda item, key, **context: item.info.strip() if isinstance(item.info, str) else item.info,
"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
"genome_build": lambda item, key, **context: item.dbkey,
# 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",
history_id=self.app.security.encode_id(dataset_assoc.history_id),
history_content_id=self.app.security.encode_id(dataset_assoc.id),
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 self.app.config.expose_dataset_path:
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 = self.app.toolbox.get_tool(dataset.creating_job.tool_id, 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 = self.app.datatypes_registry.get_datatype_by_extension(val)
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 = self.app.model.context
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, *_ = self.app.datatypes_registry.set_external_metadata_tool.tool_action.execute(
self.app.datatypes_registry.set_external_metadata_tool, trans, incoming={"input1": item}, overwrite=False
) # overwrite is False as per existing behavior
trans.app.job_manager.enqueue(job, tool=trans.app.datatypes_registry.set_external_metadata_tool)
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 = self.app.datatypes_registry.get_datatype_class_by_name(class_str)
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 = self.app.datatypes_registry.get_datatype_class_by_name
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()