def do_action(self, action, objects):
"""Performs the workflow transition passed in and returns the list of
objects that have been successfully transitioned
"""
transitioned = []
ActionHandlerPool.get_instance().queue_pool()
for obj in objects:
obj = api.get_object(obj)
success, message = do_action_for(obj, action)
if success:
transitioned.append(obj)
ActionHandlerPool.get_instance().resume()
return transitioned
def submitTransition(self, action, came_from, items):
"""Performs the action's transition for the specified items
Returns (numtransitions, destination), where:
- numtransitions: the number of objects successfully transitioned.
If no objects have been successfully transitioned, gets 0 value
- destination: the destination url to be loaded immediately
"""
transitioned = []
actions = ActionHandlerPool.get_instance()
actions.queue_pool()
for item in items:
success, message = doActionFor(item, action)
if success:
transitioned.append(item.UID())
else:
self.addPortalMessage(message, 'error')
actions.resume()
# automatic label printing
dest = None
auto_stickers_action = self.portal.bika_setup.getAutoPrintStickers()
if transitioned and action == auto_stickers_action:
self.request.form['uids'] = transitioned
self.workflow_action_print_stickers()
dest = self.destination_url
return len(transitioned), dest
def create_retest(ar):
"""Creates a retest (Analysis Request) from an invalidated Analysis Request
:param ar: The invalidated Analysis Request
:type ar: IAnalysisRequest
:rtype: IAnalysisRequest
"""
if not ar:
raise ValueError("Source Analysis Request cannot be None")
if not IAnalysisRequest.providedBy(ar):
raise ValueError("Type not supported: {}".format(repr(type(ar))))
if ar.getRetest():
# Do not allow the creation of another retest!
raise ValueError("Retest already set")
if not ar.isInvalid():
# Analysis Request must be in 'invalid' state
raise ValueError("Cannot do a retest from an invalid Analysis Request"
.format(repr(ar)))
# 0. Open the actions pool
actions_pool = ActionHandlerPool.get_instance()
actions_pool.queue_pool()
# 1. Create the Retest (Analysis Request)
ignore = ['Analyses', 'DatePublished', 'Invalidated', 'Sample']
retest = _createObjectByType("AnalysisRequest", ar.aq_parent, tmpID())
retest.setSample(ar.getSample())
copy_field_values(ar, retest, ignore_fieldnames=ignore)
renameAfterCreation(retest)
# 2. Copy the analyses from the source
intermediate_states = ['retracted', 'reflexed']
for an in ar.getAnalyses(full_objects=True):
if (api.get_workflow_status_of(an) in intermediate_states):
# Exclude intermediate analyses
continue
nan = _createObjectByType("Analysis", retest, an.getKeyword())
# Make a copy
ignore_fieldnames = ['DataAnalysisPublished']
copy_field_values(an, nan, ignore_fieldnames=ignore_fieldnames)
nan.unmarkCreationFlag()
push_reindex_to_actions_pool(nan)
# 3. Assign the source to retest
retest.setInvalidated(ar)
# 4. Transition the retest to "sample_received"!
changeWorkflowState(retest, 'bika_ar_workflow', 'sample_received')
# 5. Reindex and other stuff
push_reindex_to_actions_pool(retest)
push_reindex_to_actions_pool(retest.aq_parent)
# 6. Resume the actions pool
actions_pool.resume()
return retest
def do_action(self, action, objects):
"""Performs the workflow transition passed in and returns the list of
objects that have been successfully transitioned
"""
start = time.time()
transitioned = []
ActionHandlerPool.get_instance().queue_pool()
for obj in objects:
obj = api.get_object(obj)
success, message = do_action_for(obj, action)
if success:
transitioned.append(obj)
ActionHandlerPool.get_instance().resume()
end = time.time()
logger.info("Action '{}' for {} objects took {:.2f}s".format(
action, len(transitioned), end - start))
return transitioned
def do_unassign(self, analysis_uids):
actions = ActionHandlerPool.get_instance()
actions.queue_pool()
# Remove duplicates first
query = dict(UID=analysis_uids, portal_type="DuplicateAnalysis")
for brain in api.search(query, CATALOG_ANALYSIS_LISTING):
doActionFor(api.get_object(brain), "unassign")
# Now remove the rest
query = dict(UID=analysis_uids)
for brain in api.search(query, CATALOG_ANALYSIS_LISTING):
doActionFor(api.get_object(brain), "unassign")
actions.resume()
message = _("Changes saved.")
self.context.plone_utils.addPortalMessage(message, 'info')
self.destination_url = self.context.absolute_url()
self.request.response.redirect(self.destination_url)
def do_assign(self, analysis_uids):
actions = ActionHandlerPool.get_instance()
actions.queue_pool()
# We retrieve the analyses from the database sorted by AR ID
# ascending, so the positions of the ARs inside the WS are
# consistent with the order of the ARs
catalog = api.get_tool(CATALOG_ANALYSIS_LISTING)
brains = catalog({
"UID": analysis_uids,
"sort_on": "getRequestID"})
# Now, we need the analyses within a request ID to be sorted by
# sortkey (sortable_title index), so it will appear in the same
# order as they appear in Analyses list from AR view
curr_arid = None
curr_brains = []
sorted_brains = []
for brain in brains:
arid = brain.getRequestID
if curr_arid != arid:
# Sort the brains we've collected until now, that
# belong to the same Analysis Request
curr_brains.sort(key=attrgetter("getPrioritySortkey"))
sorted_brains.extend(curr_brains)
curr_arid = arid
curr_brains = []
# Now we are inside the same AR
curr_brains.append(brain)
continue
# Sort the last set of brains we've collected
curr_brains.sort(key=attrgetter('getPrioritySortkey'))
sorted_brains.extend(curr_brains)
# Add analyses into the worksheet
self.context.addAnalyses(sorted_brains)
actions.resume()
self.destination_url = self.context.absolute_url()
self.request.response.redirect(self.destination_url)
def create_partition(analysis_request,
request,
analyses,
sample_type=None,
container=None,
preservation=None,
skip_fields=None,
internal_use=True):
"""
Creates a partition for the analysis_request (primary) passed in
:param analysis_request: uid/brain/object of IAnalysisRequest type
:param request: the current request object
:param analyses: uids/brains/objects of IAnalysis type
:param sampletype: uid/brain/object of SampleType
:param container: uid/brain/object of Container
:param preservation: uid/brain/object of Preservation
:param skip_fields: names of fields to be skipped on copy from primary
:return: the new partition
"""
partition_skip_fields = [
"Analyses",
"Attachment",
"Client",
"DetachedFrom",
"Profile",
"Profiles",
"RejectionReasons",
"Remarks",
"ResultsInterpretation",
"ResultsInterpretationDepts",
"Sample",
"Template",
"creation_date",
"id",
"modification_date",
"ParentAnalysisRequest",
"PrimaryAnalysisRequest",
]
if skip_fields:
partition_skip_fields.extend(skip_fields)
partition_skip_fields = list(set(partition_skip_fields))
# Copy field values from the primary analysis request
ar = api.get_object(analysis_request)
record = fields_to_dict(ar, partition_skip_fields)
# Update with values that are partition-specific
record.update({
"InternalUse": internal_use,
"ParentAnalysisRequest": api.get_uid(ar),
})
if sample_type is not None:
record["SampleType"] = sample_type and api.get_uid(sample_type) or ""
if container is not None:
record["Container"] = container and api.get_uid(container) or ""
if preservation is not None:
record["Preservation"] = preservation and api.get_uid(
preservation) or ""
# Create the Partition
client = ar.getClient()
analyses = list(set(map(api.get_object, analyses)))
services = map(lambda an: an.getAnalysisService(), analyses)
# Populate the root's ResultsRanges to partitions
results_ranges = ar.getResultsRange() or []
partition = create_analysisrequest(client,
request=request,
values=record,
analyses=services,
results_ranges=results_ranges)
# Reindex Parent Analysis Request
ar.reindexObject(idxs=["isRootAncestor"])
# Manually set the Date Received to match with its parent. This is
# necessary because crar calls to processForm, so DateReceived is not
# set because the partition has not been received yet
partition.setDateReceived(ar.getDateReceived())
partition.reindexObject(idxs="getDateReceived")
# Force partition to same status as the primary
status = api.get_workflow_status_of(ar)
changeWorkflowState(partition, "bika_ar_workflow", status)
if IReceived.providedBy(ar):
alsoProvides(partition, IReceived)
# And initialize the analyses the partition contains. This is required
# here because the transition "initialize" of analyses rely on a guard,
# so the initialization can only be performed when the sample has been
# received (DateReceived is set)
ActionHandlerPool.get_instance().queue_pool()
for analysis in partition.getAnalyses(full_objects=True):
doActionFor(analysis, "initialize")
ActionHandlerPool.get_instance().resume()
return partition
