def get_transitions_for(self, obj):
"""Get the allowed transitions for the given object
"""
return api.get_transitions_for(obj)
def create_analysisrequest(context,
request,
values,
analyses=None,
partitions=None,
specifications=None,
prices=None):
"""This is meant for general use and should do everything necessary to
create and initialise an AR and any other required auxilliary objects
(Sample, SamplePartition, Analysis...)
:param context:
The container in which the ARs will be created.
:param request:
The current Request object.
:param values:
a dict, where keys are AR|Sample schema field names.
:param analyses:
Analysis services list. If specified, augments the values in
values['Analyses']. May consist of service objects, UIDs, or Keywords.
:param partitions:
A list of dictionaries, if specific partitions are required. If not
specified, AR's sample is created with a single partition.
:param specifications:
These values augment those found in values['Specifications']
:param prices:
Allow different prices to be set for analyses. If not set, prices
are read from the associated analysis service.
"""
# Gather neccesary tools
workflow = getToolByName(context, 'portal_workflow')
bc = getToolByName(context, 'bika_catalog')
# Analyses are analyses services
analyses_services = analyses
analyses = []
# It's necessary to modify these and we don't want to pollute the
# parent's data
values = values.copy()
analyses_services = analyses_services if analyses_services else []
anv = values['Analyses'] if values.get('Analyses', None) else []
analyses_services = anv + analyses_services
if not analyses_services:
raise RuntimeError(
"create_analysisrequest: no analyses services provided")
# Create new sample or locate the existing for secondary AR
if not values.get('Sample', False):
secondary = False
workflow_enabled = context.bika_setup.getSamplingWorkflowEnabled()
sample = create_sample(context, request, values)
else:
secondary = True
sample = get_sample_from_values(context, values)
workflow_enabled = sample.getSamplingWorkflowEnabled()
# Create the Analysis Request
ar = _createObjectByType('AnalysisRequest', context, tmpID())
# Set some required fields manually before processForm is called
ar.setSample(sample)
values['Sample'] = sample
if values.get('DateSampled', False):
#Inject the timezone into a selection by
#datewidget which is timezone naive
#ie. DateSampled is '2017-05-15 01:05'
#but should be '2017/05/15 01:05:00 GMT+2'
#else processForm => reindexObject() sets it to GMT+0 which results in
#an incorrect date record.
tz = DateTime().timezone()
datesampled = DateTime(values['DateSampled'] + ' ' + tz)
values['DateSampled'] = datesampled
ar.processForm(REQUEST=request, values=values)
# Object has been renamed
ar.edit(RequestID=ar.getId())
# Set initial AR state
action = '{0}sampling_workflow'.format('' if workflow_enabled else 'no_')
workflow.doActionFor(ar, action)
# Set analysis request analyses
service_uids = _resolve_items_to_service_uids(analyses_services)
# processForm already has created the analyses, but here we create the
# analyses with specs and prices. This function, even it is called 'set',
# deletes the old analyses, so eventually we obtain the desired analyses.
ar.setAnalyses(service_uids, prices=prices, specs=specifications)
# Gettin the ar objects
analyses = ar.getAnalyses(full_objects=True)
# Continue to set the state of the AR
skip_receive = [
'to_be_sampled', 'sample_due', 'sampled', 'to_be_preserved'
]
if secondary:
# Only 'sample_due' and 'sample_recieved' samples can be selected
# for secondary analyses
doActionFor(ar, 'sampled')
doActionFor(ar, 'sample_due')
sample_state = workflow.getInfoFor(sample, 'review_state')
if sample_state not in skip_receive:
doActionFor(ar, 'receive')
# Set the state of analyses we created.
for analysis in analyses:
revers = analysis.getService().getNumberOfRequiredVerifications()
analysis.setNumberOfRequiredVerifications(revers)
doActionFor(analysis, 'sample_due')
analysis_state = workflow.getInfoFor(analysis, 'review_state')
if analysis_state not in skip_receive:
doActionFor(analysis, 'receive')
if not secondary:
# Create sample partitions
if not partitions:
partitions = values.get('Partitions', [{'services': service_uids}])
for n, partition in enumerate(partitions):
# Calculate partition id
partition['object'] = create_samplepartition(
sample, partition, analyses)
# If Preservation is required for some partitions,
# and the SamplingWorkflow is disabled, we need
# to transition to to_be_preserved manually.
if not workflow_enabled:
to_be_preserved = []
sample_due = []
lowest_state = 'sample_due'
for p in sample.objectValues('SamplePartition'):
if p.getPreservation():
lowest_state = 'to_be_preserved'
to_be_preserved.append(p)
else:
sample_due.append(p)
for p in to_be_preserved:
doActionFor(p, 'to_be_preserved')
for p in sample_due:
doActionFor(p, 'sample_due')
doActionFor(sample, lowest_state)
doActionFor(ar, lowest_state)
# Transition pre-preserved partitions
for p in partitions:
if 'prepreserved' in p and p['prepreserved']:
part = p['object']
state = workflow.getInfoFor(part, 'review_state')
if state == 'to_be_preserved':
workflow.doActionFor(part, 'preserve')
# Once the ar is fully created, check if there are rejection reasons
reject_field = values.get('RejectionReasons', '')
if reject_field and reject_field.get('checkbox', False):
doActionFor(ar, 'reject')
# If the Sampling Workflow field values are valid,
# and the SamplingWorkflow is enabled, we will
# automatically kick off the "sample" transition now
tids = [t['id'] for t in get_transitions_for(ar)]
if 'sample' in tids and ar.getSampler() and ar.getDateSampled():
do_transition_for(ar, 'sample')
# Return the newly created Analysis Request
return ar
def workflow_script_import(self):
"""Create objects from valid ARImport
"""
def convert_date_string(datestr):
return datestr.replace('-', '/')
def lookup_sampler_uid(import_user):
#Lookup sampler's uid
found = False
userid = None
user_ids = []
users = getUsers(self, ['LabManager', 'Sampler']).items()
for (samplerid, samplername) in users:
if import_user == samplerid:
found = True
userid = samplerid
break
if import_user == samplername:
user_ids.append(samplerid)
if found:
return userid
if len(user_ids) == 1:
return user_ids[0]
if len(user_ids) > 1:
#raise ValueError('Sampler %s is ambiguous' % import_user)
return ''
#Otherwise
#raise ValueError('Sampler %s not found' % import_user)
return ''
bsc = getToolByName(self, 'bika_setup_catalog')
workflow = getToolByName(self, 'portal_workflow')
client = self.aq_parent
title = _('Submitting AR Import')
description = _('Creating and initialising objects')
bar = ProgressBar(self, self.REQUEST, title, description)
notify(InitialiseProgressBar(bar))
profiles = [x.getObject() for x in bsc(portal_type='AnalysisProfile')]
gridrows = self.schema['SampleData'].get(self)
row_cnt = 0
for therow in gridrows:
row = therow.copy()
row_cnt += 1
# Create Sample
sample = _createObjectByType('Sample', client, tmpID())
sample.unmarkCreationFlag()
# First convert all row values into something the field can take
sample.edit(**row)
sample._renameAfterCreation()
event.notify(ObjectInitializedEvent(sample))
sample.at_post_create_script()
swe = self.bika_setup.getSamplingWorkflowEnabled()
if swe:
workflow.doActionFor(sample, 'sampling_workflow')
else:
workflow.doActionFor(sample, 'no_sampling_workflow')
part = _createObjectByType('SamplePartition', sample, 'part-1')
part.unmarkCreationFlag()
renameAfterCreation(part)
if swe:
workflow.doActionFor(part, 'sampling_workflow')
else:
workflow.doActionFor(part, 'no_sampling_workflow')
container = self.get_row_container(row)
if container:
part.edit(Container=container)
# Profiles are titles, profile keys, or UIDS: convert them to UIDs.
newprofiles = []
for title in row['Profiles']:
objects = [
x for x in profiles
if title in (x.getProfileKey(), x.UID(), x.Title())
]
for obj in objects:
newprofiles.append(obj.UID())
row['Profiles'] = newprofiles
# BBB in bika.lims < 3.1.9, only one profile is permitted
# on an AR. The services are all added, but only first selected
# profile name is stored.
row['Profile'] = newprofiles[0] if newprofiles else None
# Same for analyses
newanalyses = set(
self.get_row_services(row) +
self.get_row_profile_services(row))
row['Analyses'] = []
# get batch
batch = self.schema['Batch'].get(self)
if batch:
row['Batch'] = batch
# Add AR fields from schema into this row's data
row['ClientReference'] = self.getClientReference()
row['ClientOrderNumber'] = self.getClientOrderNumber()
row['Contact'] = self.getContact()
row['DateSampled'] = convert_date_string(row['DateSampled'])
if row['Sampler']:
row['Sampler'] = lookup_sampler_uid(row['Sampler'])
# Create AR
ar = _createObjectByType("AnalysisRequest", client, tmpID())
ar.setSample(sample)
ar.unmarkCreationFlag()
ar.edit(**row)
ar._renameAfterCreation()
ar.setAnalyses(list(newanalyses))
for analysis in ar.getAnalyses(full_objects=True):
analysis.setSamplePartition(part)
ar.at_post_create_script()
if swe:
workflow.doActionFor(ar, 'sampling_workflow')
else:
workflow.doActionFor(ar, 'no_sampling_workflow')
# If the Sampling Workflow field values are valid,
# and the SamplingWorkflow is enabled, we will
# automatically kick off the "sample" transition now
tids = [t['id'] for t in get_transitions_for(ar)]
if 'sample' in tids and ar.getSampler() and ar.getDateSampled():
do_transition_for(ar, 'sample')
progress_index = float(row_cnt) / len(gridrows) * 100
progress = ProgressState(self.REQUEST, progress_index)
notify(UpdateProgressEvent(progress))
# document has been written to, and redirect() fails here
self.REQUEST.response.write(
'<script>document.location.href="%s"</script>' %
(self.aq_parent.absolute_url()))