Warning
This document is for an in-development version of Galaxy. You can alternatively view this page in the latest release if it exists or view the top of the latest release's documentation.
Source code for galaxy.managers.collections
from __future__ import absolute_import
import logging
from collections import OrderedDict
from galaxy import model
from galaxy.exceptions import (
ItemAccessibilityException,
MessageException,
RequestParameterInvalidException
)
from galaxy.managers import (
hdas,
histories,
lddas,
)
from galaxy.managers.collections_util import validate_input_element_identifiers
from galaxy.model import tags
from galaxy.model.dataset_collections import builder
from galaxy.model.dataset_collections.matching import MatchingCollections
from galaxy.model.dataset_collections.registry import DATASET_COLLECTION_TYPES_REGISTRY
from galaxy.model.dataset_collections.type_description import COLLECTION_TYPE_DESCRIPTION_FACTORY
from galaxy.util import (
validation
)
log = logging.getLogger(__name__)
ERROR_INVALID_ELEMENTS_SPECIFICATION = "Create called with invalid parameters, must specify element identifiers."
ERROR_NO_COLLECTION_TYPE = "Create called without specifying a collection type."
[docs]class DatasetCollectionManager(object):
"""
Abstraction for interfacing with dataset collections instance - ideally abstracts
out model and plugin details.
"""
ELEMENTS_UNINITIALIZED = object()
[docs] def __init__(self, app):
self.type_registry = DATASET_COLLECTION_TYPES_REGISTRY
self.collection_type_descriptions = COLLECTION_TYPE_DESCRIPTION_FACTORY
self.model = app.model
self.security = app.security
self.hda_manager = hdas.HDAManager(app)
self.history_manager = histories.HistoryManager(app)
self.tag_handler = tags.GalaxyTagHandler(app.model.context)
self.ldda_manager = lddas.LDDAManager(app)
[docs] def precreate_dataset_collection_instance(self, trans, parent, name, structure, implicit_inputs=None, implicit_output_name=None, tags=None):
# TODO: prebuild all required HIDs and send them in so no need to flush in between.
dataset_collection = self.precreate_dataset_collection(structure, allow_unitialized_element=implicit_output_name is not None)
instance = self._create_instance_for_collection(
trans, parent, name, dataset_collection, implicit_inputs=implicit_inputs, implicit_output_name=implicit_output_name, flush=False, tags=tags
)
return instance
[docs] def precreate_dataset_collection(self, structure, allow_unitialized_element=True):
has_structure = not structure.is_leaf and structure.children_known
if not has_structure and allow_unitialized_element:
dataset_collection = model.DatasetCollectionElement.UNINITIALIZED_ELEMENT
elif not has_structure:
collection_type_description = structure.collection_type_description
dataset_collection = model.DatasetCollection(populated=False)
dataset_collection.collection_type = collection_type_description.collection_type
else:
collection_type_description = structure.collection_type_description
dataset_collection = model.DatasetCollection(populated=False)
dataset_collection.collection_type = collection_type_description.collection_type
elements = []
for index, (identifier, substructure) in enumerate(structure.children):
# TODO: Open question - populate these now or later?
if substructure.is_leaf:
element = model.DatasetCollectionElement.UNINITIALIZED_ELEMENT
else:
element = self.precreate_dataset_collection(substructure, allow_unitialized_element=allow_unitialized_element)
element = model.DatasetCollectionElement(
element=element,
element_identifier=identifier,
element_index=index,
)
elements.append(element)
dataset_collection.elements = elements
dataset_collection.element_count = len(elements)
return dataset_collection
[docs] def create(self, trans, parent, name, collection_type, element_identifiers=None,
elements=None, implicit_collection_info=None, trusted_identifiers=None,
hide_source_items=False, tags=None, copy_elements=False, history=None):
"""
PRECONDITION: security checks on ability to add to parent
occurred during load.
"""
# Trust embedded, newly created objects created by tool subsystem.
if trusted_identifiers is None:
trusted_identifiers = implicit_collection_info is not None
if element_identifiers and not trusted_identifiers:
validate_input_element_identifiers(element_identifiers)
dataset_collection = self.create_dataset_collection(
trans=trans,
collection_type=collection_type,
element_identifiers=element_identifiers,
elements=elements,
hide_source_items=hide_source_items,
copy_elements=copy_elements,
history=history,
)
implicit_inputs = []
if implicit_collection_info:
implicit_inputs = implicit_collection_info.get('implicit_inputs', [])
implicit_output_name = None
if implicit_collection_info:
implicit_output_name = implicit_collection_info["implicit_output_name"]
return self._create_instance_for_collection(
trans, parent, name, dataset_collection, implicit_inputs=implicit_inputs, implicit_output_name=implicit_output_name, tags=tags
)
def _create_instance_for_collection(self, trans, parent, name, dataset_collection, implicit_output_name=None, implicit_inputs=None, tags=None, flush=True):
if isinstance(parent, model.History):
dataset_collection_instance = self.model.HistoryDatasetCollectionAssociation(
collection=dataset_collection,
name=name,
)
if implicit_inputs:
for input_name, input_collection in implicit_inputs:
dataset_collection_instance.add_implicit_input_collection(input_name, input_collection)
if implicit_output_name:
dataset_collection_instance.implicit_output_name = implicit_output_name
log.debug("Created collection with %d elements" % (len(dataset_collection_instance.collection.elements)))
# Handle setting hid
parent.add_dataset_collection(dataset_collection_instance)
elif isinstance(parent, model.LibraryFolder):
dataset_collection_instance = self.model.LibraryDatasetCollectionAssociation(
collection=dataset_collection,
folder=parent,
name=name,
)
else:
message = "Internal logic error - create called with unknown parent type %s" % type(parent)
log.exception(message)
raise MessageException(message)
# Tags may be coming in as a dictionary of tag model objects if copying them from other
# existing Galaxy objects or as a list of strings if the tags are coming from user supplied
# values.
if isinstance(tags, list):
assert implicit_inputs is None, implicit_inputs
tags = self.tag_handler.add_tags_from_list(trans.user, dataset_collection_instance, tags)
else:
tags = self._append_tags(dataset_collection_instance, implicit_inputs, tags)
return self.__persist(dataset_collection_instance, flush=flush)
[docs] def create_dataset_collection(self, trans, collection_type, element_identifiers=None, elements=None,
hide_source_items=None, copy_elements=False, history=None):
# Make sure at least one of these is None.
assert element_identifiers is None or elements is None
if element_identifiers is None and elements is None:
raise RequestParameterInvalidException(ERROR_INVALID_ELEMENTS_SPECIFICATION)
if not collection_type:
raise RequestParameterInvalidException(ERROR_NO_COLLECTION_TYPE)
collection_type_description = self.collection_type_descriptions.for_collection_type(collection_type)
has_subcollections = collection_type_description.has_subcollections()
# If we have elements, this is an internal request, don't need to load
# objects from identifiers.
if elements is None:
elements = self._element_identifiers_to_elements(trans,
collection_type_description=collection_type_description,
element_identifiers=element_identifiers,
hide_source_items=hide_source_items,
copy_elements=copy_elements,
history=history)
else:
if has_subcollections:
# Nested collection - recursively create collections as needed.
self.__recursively_create_collections_for_elements(trans, elements, hide_source_items, copy_elements=copy_elements, history=history)
# else if elements is set, it better be an ordered dict!
if elements is not self.ELEMENTS_UNINITIALIZED:
type_plugin = collection_type_description.rank_type_plugin()
dataset_collection = builder.build_collection(type_plugin, elements)
else:
dataset_collection = model.DatasetCollection(populated=False)
dataset_collection.collection_type = collection_type
return dataset_collection
def _element_identifiers_to_elements(self,
trans,
collection_type_description,
element_identifiers,
hide_source_items=False,
copy_elements=False,
history=None):
if collection_type_description.has_subcollections():
# Nested collection - recursively create collections and update identifiers.
self.__recursively_create_collections_for_identifiers(trans, element_identifiers, hide_source_items, copy_elements)
new_collection = False
for element_identifier in element_identifiers:
if element_identifier.get("src") == "new_collection" and element_identifier.get('collection_type') == '':
new_collection = True
elements = self.__load_elements(trans=trans,
element_identifiers=element_identifier['element_identifiers'],
hide_source_items=hide_source_items,
copy_elements=copy_elements,
history=history)
if not new_collection:
elements = self.__load_elements(trans=trans,
element_identifiers=element_identifiers,
hide_source_items=hide_source_items,
copy_elements=copy_elements,
history=history)
return elements
def _append_tags(self, dataset_collection_instance, implicit_inputs=None, tags=None):
tags = tags or {}
implicit_inputs = implicit_inputs or []
for _, v in implicit_inputs:
for tag in v.auto_propagated_tags:
tags[tag.value] = tag
for _, tag in tags.items():
dataset_collection_instance.tags.append(tag.copy(cls=model.HistoryDatasetCollectionTagAssociation))
[docs] def set_collection_elements(self, dataset_collection, dataset_instances):
if dataset_collection.populated:
raise Exception("Cannot reset elements of an already populated dataset collection.")
collection_type = dataset_collection.collection_type
collection_type_description = self.collection_type_descriptions.for_collection_type(collection_type)
type_plugin = collection_type_description.rank_type_plugin()
builder.set_collection_elements(dataset_collection, type_plugin, dataset_instances)
dataset_collection.mark_as_populated()
return dataset_collection
[docs] def collection_builder_for(self, dataset_collection):
return builder.BoundCollectionBuilder(dataset_collection)
[docs] def delete(self, trans, instance_type, id, recursive=False, purge=False):
dataset_collection_instance = self.get_dataset_collection_instance(trans, instance_type, id, check_ownership=True)
dataset_collection_instance.deleted = True
trans.sa_session.add(dataset_collection_instance)
if recursive:
for dataset in dataset_collection_instance.collection.dataset_instances:
self.hda_manager.error_unless_owner(dataset, user=trans.get_user(), current_history=trans.history)
if not dataset.deleted:
dataset.deleted = True
if purge and not dataset.purged:
self.hda_manager.purge(dataset)
trans.sa_session.flush()
[docs] def update(self, trans, instance_type, id, payload):
dataset_collection_instance = self.get_dataset_collection_instance(trans, instance_type, id, check_ownership=True)
if trans.user is None:
anon_allowed_payload = {}
if 'deleted' in payload:
anon_allowed_payload['deleted'] = payload['deleted']
if 'visible' in payload:
anon_allowed_payload['visible'] = payload['visible']
payload = self._validate_and_parse_update_payload(anon_allowed_payload)
else:
payload = self._validate_and_parse_update_payload(payload)
changed = self._set_from_dict(trans, dataset_collection_instance, payload)
return changed
[docs] def copy(self, trans, parent, source, encoded_source_id, copy_elements=False):
"""
PRECONDITION: security checks on ability to add to parent occurred
during load.
"""
assert source == "hdca" # for now
source_hdca = self.__get_history_collection_instance(trans, encoded_source_id)
copy_kwds = {}
if copy_elements:
copy_kwds["element_destination"] = parent
new_hdca = source_hdca.copy(**copy_kwds)
tags_str = self.tag_handler.get_tags_str(source_hdca.tags)
self.tag_handler.apply_item_tags(trans.get_user(), new_hdca, tags_str)
parent.add_dataset_collection(new_hdca)
trans.sa_session.add(new_hdca)
trans.sa_session.flush()
return new_hdca
def _set_from_dict(self, trans, dataset_collection_instance, new_data):
# send what we can down into the model
changed = dataset_collection_instance.set_from_dict(new_data)
# the rest (often involving the trans) - do here
if 'annotation' in new_data.keys() and trans.get_user():
dataset_collection_instance.add_item_annotation(trans.sa_session, trans.get_user(), dataset_collection_instance, new_data['annotation'])
changed['annotation'] = new_data['annotation']
if 'tags' in new_data.keys() and trans.get_user():
# set_tags_from_list will flush on its own, no need to add to 'changed' here and incur a second flush.
self.tag_handler.set_tags_from_list(trans.get_user(), dataset_collection_instance, new_data['tags'])
if changed.keys():
trans.sa_session.flush()
return changed
def _validate_and_parse_update_payload(self, payload):
validated_payload = {}
for key, val in payload.items():
if val is None:
continue
if key in ('name'):
val = validation.validate_and_sanitize_basestring(key, val)
validated_payload[key] = val
if key in ('deleted', 'visible'):
validated_payload[key] = validation.validate_boolean(key, val)
elif key == 'tags':
validated_payload[key] = validation.validate_and_sanitize_basestring_list(key, val)
return validated_payload
[docs] def history_dataset_collections(self, history, query):
collections = history.active_dataset_collections
collections = list(filter(query.direct_match, collections))
return collections
def __persist(self, dataset_collection_instance, flush=True):
context = self.model.context
context.add(dataset_collection_instance)
if flush:
context.flush()
return dataset_collection_instance
def __recursively_create_collections_for_identifiers(self, trans, element_identifiers, hide_source_items, copy_elements):
for index, element_identifier in enumerate(element_identifiers):
try:
if element_identifier.get("src", None) != "new_collection":
# not a new collection, keep moving...
continue
except KeyError:
# Not a dictionary, just an id of an HDA - move along.
continue
# element identifier is a dict with src new_collection...
collection_type = element_identifier.get("collection_type", None)
collection = self.create_dataset_collection(
trans=trans,
collection_type=collection_type,
element_identifiers=element_identifier["element_identifiers"],
hide_source_items=hide_source_items,
copy_elements=copy_elements,
)
element_identifier["__object__"] = collection
return element_identifiers
def __recursively_create_collections_for_elements(self, trans, elements, hide_source_items, copy_elements, history=None):
if elements is self.ELEMENTS_UNINITIALIZED:
return
new_elements = OrderedDict()
for key, element in elements.items():
if isinstance(element, model.DatasetCollection):
continue
if element.get("src", None) != "new_collection":
continue
# element is a dict with src new_collection and
# and OrderedDict of named elements
collection_type = element.get("collection_type", None)
sub_elements = element["elements"]
collection = self.create_dataset_collection(
trans=trans,
collection_type=collection_type,
elements=sub_elements,
hide_source_items=hide_source_items,
copy_elements=copy_elements,
history=history,
)
new_elements[key] = collection
elements.update(new_elements)
def __load_elements(self, trans, element_identifiers, hide_source_items=False, copy_elements=False, history=None):
elements = OrderedDict()
for element_identifier in element_identifiers:
elements[element_identifier["name"]] = self.__load_element(trans,
element_identifier=element_identifier,
hide_source_items=hide_source_items,
copy_elements=copy_elements,
history=history)
return elements
def __load_element(self, trans, element_identifier, hide_source_items, copy_elements, history=None):
# if not isinstance( element_identifier, dict ):
# # Is allowing this to just be the id of an hda too clever? Somewhat
# # consistent with other API methods though.
# element_identifier = dict( src='hda', id=str( element_identifier ) )
# Previously created collection already found in request, just pass
# through as is.
if "__object__" in element_identifier:
the_object = element_identifier["__object__"]
if the_object is not None and the_object.id:
context = self.model.context
if the_object not in context:
the_object = context.query(type(the_object)).get(the_object.id)
return the_object
# dataset_identifier is dict {src=hda|ldda|hdca|new_collection, id=<encoded_id>}
try:
src_type = element_identifier.get('src', 'hda')
except AttributeError:
raise MessageException("Dataset collection element definition (%s) not dictionary-like." % element_identifier)
encoded_id = element_identifier.get('id', None)
if not src_type or not encoded_id:
message_template = "Problem decoding element identifier %s - must contain a 'src' and a 'id'."
message = message_template % element_identifier
raise RequestParameterInvalidException(message)
tags = element_identifier.pop('tags', None)
tag_str = ''
if tags:
tag_str = ",".join(str(_) for _ in tags)
if src_type == 'hda':
decoded_id = int(trans.app.security.decode_id(encoded_id))
hda = self.hda_manager.get_accessible(decoded_id, trans.user)
if copy_elements:
element = self.hda_manager.copy(hda, history=history or trans.history, hide_copy=True)
else:
element = hda
if hide_source_items and self.hda_manager.get_owned(hda.id, user=trans.user, current_history=history or trans.history):
hda.visible = False
self.tag_handler.apply_item_tags(user=trans.user, item=element, tags_str=tag_str)
elif src_type == 'ldda':
element = self.ldda_manager.get(trans, encoded_id, check_accessible=True)
element = element.to_history_dataset_association(history or trans.history, add_to_history=True, visible=not hide_source_items)
self.tag_handler.apply_item_tags(user=trans.user, item=element, tags_str=tag_str)
elif src_type == 'hdca':
# TODO: Option to copy? Force copy? Copy or allow if not owned?
element = self.__get_history_collection_instance(trans, encoded_id).collection
# TODO: ldca.
else:
raise RequestParameterInvalidException("Unknown src_type parameter supplied '%s'." % src_type)
return element
[docs] def match_collections(self, collections_to_match):
"""
May seem odd to place it here, but planning to grow sophistication and
get plugin types involved so it will likely make sense in the future.
"""
return MatchingCollections.for_collections(collections_to_match, self.collection_type_descriptions)
[docs] def get_dataset_collection_instance(self, trans, instance_type, id, **kwds):
"""
"""
if instance_type == "history":
return self.__get_history_collection_instance(trans, id, **kwds)
elif instance_type == "library":
return self.__get_library_collection_instance(trans, id, **kwds)
[docs] def get_dataset_collection(self, trans, encoded_id):
collection_id = int(trans.app.security.decode_id(encoded_id))
collection = trans.sa_session.query(trans.app.model.DatasetCollection).get(collection_id)
return collection
[docs] def apply_rules(self, hdca, rule_set, handle_dataset):
hdca_collection = hdca.collection
collection_type = hdca_collection.collection_type
elements = hdca_collection.elements
collection_type_description = self.collection_type_descriptions.for_collection_type(collection_type)
initial_data, initial_sources = self.__init_rule_data(elements, collection_type_description)
data, sources = rule_set.apply(initial_data, initial_sources)
collection_type = rule_set.collection_type
collection_type_description = self.collection_type_descriptions.for_collection_type(collection_type)
elements = self._build_elements_from_rule_data(collection_type_description, rule_set, data, sources, handle_dataset)
return elements
def _build_elements_from_rule_data(self, collection_type_description, rule_set, data, sources, handle_dataset):
identifier_columns = rule_set.identifier_columns
elements = OrderedDict()
for data_index, row_data in enumerate(data):
# For each row, find place in depth for this element.
collection_type_at_depth = collection_type_description
elements_at_depth = elements
for i, identifier_column in enumerate(identifier_columns):
identifier = row_data[identifier_column]
if i + 1 == len(identifier_columns):
# At correct final position in nested structure for this dataset.
if collection_type_at_depth.collection_type == "paired":
if identifier.lower() in ["f", "1", "r1", "forward"]:
identifier = "forward"
elif identifier.lower() in ["r", "2", "r2", "reverse"]:
identifier = "reverse"
else:
raise Exception("Unknown indicator of paired status encountered - only values of F, R, 1, 2, R1, R2, forward, or reverse are allowed.")
elements_at_depth[identifier] = handle_dataset(sources[data_index]["dataset"])
else:
collection_type_at_depth = collection_type_at_depth.child_collection_type_description()
found = False
if identifier in elements_at_depth:
elements_at_depth = elements_at_depth[identifier]["elements"]
found = True
if not found:
sub_collection = {}
sub_collection["src"] = "new_collection"
sub_collection["collection_type"] = collection_type_at_depth.collection_type
sub_collection["elements"] = OrderedDict()
elements_at_depth[identifier] = sub_collection
elements_at_depth = sub_collection["elements"]
return elements
def __init_rule_data(self, elements, collection_type_description, parent_identifiers=None):
parent_identifiers = parent_identifiers or []
data, sources = [], []
for element in elements:
element_object = element.element_object
identifiers = parent_identifiers + [element.element_identifier]
if not element.is_collection:
data.append([])
source = {"identifiers": identifiers, "dataset": element_object, "tags": element_object.make_tag_string_list()}
sources.append(source)
else:
child_collection_type_description = collection_type_description.child_collection_type_description()
element_data, element_sources = self.__init_rule_data(
element_object.elements, child_collection_type_description, identifiers
)
data.extend(element_data)
sources.extend(element_sources)
return data, sources
def __get_history_collection_instance(self, trans, id, check_ownership=False, check_accessible=True):
instance_id = int(trans.app.security.decode_id(id))
collection_instance = trans.sa_session.query(trans.app.model.HistoryDatasetCollectionAssociation).get(instance_id)
history = getattr(trans, 'history', collection_instance.history)
if check_ownership:
self.history_manager.error_unless_owner(collection_instance.history, trans.user, current_history=history)
if check_accessible:
self.history_manager.error_unless_accessible(collection_instance.history, trans.user, current_history=history)
return collection_instance
def __get_library_collection_instance(self, trans, id, check_ownership=False, check_accessible=True):
if check_ownership:
raise NotImplementedError("Functionality (getting library dataset collection with ownership check) unimplemented.")
instance_id = int(trans.security.decode_id(id))
collection_instance = trans.sa_session.query(trans.app.model.LibraryDatasetCollectionAssociation).get(instance_id)
if check_accessible:
if not trans.app.security_agent.can_access_library_item(trans.get_current_user_roles(), collection_instance, trans.user):
raise ItemAccessibilityException("LibraryDatasetCollectionAssociation is not accessible to the current user", type='error')
return collection_instance