def decouple_analyses_from_sample_workflow(portal):
logger.info("Decoupling analyses from sample workflow ...")
add_index(portal,
catalog_id=CATALOG_ANALYSIS_LISTING,
index_name="isSampleReceived",
index_attribute="isSampleReceived",
index_metatype="BooleanIndex")
wf_id = "bika_analysis_workflow"
affected_rs = [
"sample_registered", "to_be_sampled", "sampled", "sample_due",
"sample_received", "to_be_preserved", "not_requested", "registered"
]
wf_tool = api.get_tool("portal_workflow")
workflow = wf_tool.getWorkflowById(wf_id)
query = dict(portal_type=["Analysis", "DuplicateAnalysis"],
review_state=affected_rs)
brains = api.search(query, CATALOG_ANALYSIS_LISTING)
total = len(brains)
for num, brain in enumerate(brains):
# Set state
analysis = api.get_object(brain)
target_state = analysis.getWorksheet() and "assigned" or "unassigned"
if num % 100 == 0:
logger.info("Restoring state to '{}': {}/{}".format(
target_state, num, total))
changeWorkflowState(analysis, wf_id, target_state)
# Update role mappings
workflow.updateRoleMappingsFor(analysis)
# Reindex
analysis.reindexObject()
def remove_orphan_reference_analyses(portal):
logger.info("Removing orphan reference analyses ...")
wf_id = "bika_referenceanalysis_workflow"
wf_tool = api.get_tool("portal_workflow")
workflow = wf_tool.getWorkflowById(wf_id)
query = dict(portal_type="ReferenceAnalysis", review_state="unassigned")
brains = api.search(query, CATALOG_ANALYSIS_LISTING)
total = len(brains)
for num, brain in enumerate(brains):
orphan = api.get_object(brain)
worksheet = orphan.getWorksheet()
if worksheet:
logger.info("Reassigning orphan reference: {}/{}".format(
num, total))
# This one has a worksheet! reindex and do nothing
changeWorkflowState(orphan, wf_id, "assigned")
# Update role mappings
workflow.updateRoleMappingsFor(orphan)
# Reindex
orphan.reindexObject()
continue
elif orphan.getInstrument():
# This is a calibration test, do nothing!
if not brain.getInstrumentUID:
orphan.reindexObject()
total -= 1
continue
if num % 100 == 0:
logger.info("Removing orphan reference analysis: {}/{}".format(
num, total))
# Remove the duplicate
orphan.aq_parent.manage_delObjects([orphan.getId()])
def after_no_sampling_workflow(analysis_request):
""" Event fired for no_sampling_workflow that makes the status of the
Analysis request or Sample to become sample_ordered
"""
if not analysis_request.isPartition():
# Generate the delivery pdf
generate_requisition_pdf(analysis_request)
# Set specifications by default
sample_type = analysis_request.getSampleType()
specs = api.get_field_value(sample_type, "DefaultAnalysisSpecifications",
None)
if specs:
analysis_request.setSpecification(api.get_object(specs))
else:
# Find out suitable specs by Sample Type name
sample_type_title = sample_type.Title()
specs_title = "{} - calculated".format(sample_type_title)
query = dict(portal_type="AnalysisSpec", title=specs_title)
specs = api.search(query, 'bika_setup_catalog')
if specs:
analysis_request.setSpecification(api.get_object(specs[0]))
if analysis_request.isPartition():
# Change workflow state to "at_reception"
wf.changeWorkflowState(analysis_request,
wf_id="bika_ar_workflow",
state_id="sample_at_reception")
def create_partition_for_storage(sample_obj_brain_or_uid):
"""Creates an empty partition suitable for storage from the given sample
If the sample passed in is a partition, generates a copy of the same
partition without analyses set, but keeping the same parent.
If the sample passed in is a primary sample, generates a new partition, but
without analyses
"""
sample = get_object(sample_obj_brain_or_uid)
logger.info("Creating partition for storage: {}".format(get_id(sample)))
PARTITION_SKIP_FIELDS = [
"Analyses",
"Attachment",
"Client",
"Profile",
"Profiles",
"RejectionReasons",
"Remarks",
"ResultsInterpretation",
"ResultsInterpretationDepts",
"Sample",
"Template",
"creation_date",
"id",
"modification_date",
"ParentAnalysisRequest",
]
primary = sample
if sample.isPartition():
primary = sample.getParentAnalysisRequest()
# Set the basic fields for the Partition
record = {
"ParentAnalysisRequest": get_uid(primary),
}
# Copy all fields
for fieldname, field in get_fields(sample).items():
if field.type == "computed":
logger.info("Skipping computed field {}".format(fieldname))
continue
if fieldname in PARTITION_SKIP_FIELDS:
logger.info("Skipping field {}".format(fieldname))
continue
fieldvalue = field.get(sample)
record[fieldname] = fieldvalue
logger.info("Update record '{}': {}".format(fieldname,
repr(fieldvalue)))
client = sample.getClient()
partition = crar(client, request={}, values=record)
# Force status to "stored"
wf.changeWorkflowState(partition, "bika_ar_workflow", "stored")
# Reindex the primary AR
primary.reindexObject(idxs=["isRootAncestor"])
return partition
def fix_cancelled_analyses_inconsistencies(portal):
logger.info("Resolving cancelled analyses inconsistencies ...")
wf_id = "bika_analysis_workflow"
wf_tool = api.get_tool("portal_workflow")
workflow = wf_tool.getWorkflowById(wf_id)
query = dict(portal_type="Analysis", cancellation_state="cancelled")
brains = api.search(query, CATALOG_ANALYSIS_LISTING)
total = len(brains)
for num, brain in enumerate(brains):
if brain.review_state == "cancelled":
continue
if num % 100 == 0:
logger.info("Resolving state to 'cancelled': {}/{}".format(
num, total))
# Set state
analysis = api.get_object(brain)
changeWorkflowState(analysis, wf_id, "cancelled")
# Update role mappings
workflow.updateRoleMappingsFor(analysis)
# Reindex
analysis.reindexObject(idxs=["cancellation_state"])
def remove_attachment_due_from_analysis_workflow(portal):
logger.info("Removing attachment_due state from analysis workflow ...")
wf_id = "bika_analysis_workflow"
affected_rs = ["attachment_due"]
wf_tool = api.get_tool("portal_workflow")
workflow = wf_tool.getWorkflowById(wf_id)
query = dict(review_state=affected_rs)
brains = api.search(query, CATALOG_ANALYSIS_LISTING)
total = len(brains)
for num, brain in enumerate(brains):
analysis = api.get_object(brain)
target_state = analysis.getWorksheet() and "assigned" or "unassigned"
if num % 100 == 0:
logger.info("Restoring state to '{}': {}/{}".format(
target_state, num, total))
changeWorkflowState(analysis, wf_id, target_state)
# Update role mappings
workflow.updateRoleMappingsFor(analysis)
# Reindex
analysis.reindexObject()