def create_requests_from_partitions(analysis_request):
"""If more than one SamplePartition is set for the given AnalysisRequest,
creates a new internal AR for every single SamplePartition, assign the
primary sample to children and removes the analyses from the primary AR.
"""
logger.info("*** Creating new requests from partitions ***")
partitions = analysis_request.getPartitions()
if len(partitions) < 2:
# Only one partition, do not create new requests
return list()
created = list()
client = analysis_request.getClient()
primary_sample = analysis_request.getSample()
primary_sample_uid = api.get_uid(primary_sample)
ar_proxies = analysis_request.Schema().fields()
ar_proxies = filter(lambda field: IProxyField.providedBy(field),
ar_proxies)
ar_proxies = map(lambda field: field.getName(), ar_proxies)
skip_fields = [
"Client", "Sample", "PrimarySample", "Template", "Profile", "Profiles",
"Analyses", "ParentAnalysisRequest", "PrimaryAnalysisRequest",
"RejectionReasons", "Remarks"
]
skip_fields.extend(ar_proxies)
for part in partitions:
analyses = part.getAnalyses()
analyses = map(lambda an: api.get_object(an), analyses)
# Create the new derivative sample (~partition)
field_values = dict(PrimarySample=primary_sample_uid, InternalUse=True)
sample_copy = copy(primary_sample,
container=client,
new_field_values=field_values)
#sample_copy.id = part.id
sample_uid = api.get_uid(sample_copy)
# Create a new Analysis Request for this Sample and analyses
field_values = dict(Sample=sample_uid,
Analyses=analyses,
PrimaryAnalysisRequest=analysis_request)
ar_copy = copy(analysis_request,
container=client,
skip_fields=skip_fields,
new_field_values=field_values)
# Create sample partition
services = map(lambda an: an.getAnalysisService(), analyses)
partition = dict(services=services,
part_id="{}-P1".format(sample_copy.getId()))
create_samplepartition(sample_copy, partition, analyses)
# Force all items to be in received state
force_receive(ar_copy)
created.append(ar_copy)
return created
def create_analysisrequest(
context,
request,
values, # {field: value, ...}
analyses=[],
# uid, service or analysis; list of uids, services or analyses
partitions=None,
# list of dictionaries with container, preservation etc)
specifications=None,
prices=None):
"""This is meant for general use and should do everything necessary to
create and initialise the AR and it's requirements.
XXX The ar-add form's ajaxAnalysisRequestSubmit should be calling this.
"""
# Gather neccesary tools
workflow = getToolByName(context, 'portal_workflow')
bc = getToolByName(context, 'bika_catalog')
# It's necessary to modify these and we don't want to pollute the
# parent's data
values = values.copy()
# 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
if ISample.providedBy(values['Sample']):
sample = values['Sample']
else:
brains = bc(UID=values['Sample'])
if brains:
sample = brains[0].getObject()
if not sample:
raise RuntimeError("create_analysisrequest No sample. values=%s" %
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
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)
analyses = ar.setAnalyses(service_uids,
prices=prices,
specs=specifications)
if secondary:
# Only 'sample_due' and 'sample_recieved' samples can be selected
# for secondary analyses
api.content.transition(obj=ar, to_state='sampled')
api.content.transition(obj=ar, to_state='sample_due')
sample_state = workflow.getInfoFor(sample, 'review_state')
if sample_state == 'sample_received':
doActionFor(ar, 'receive')
for analysis in ar.getAnalyses(full_objects=1):
doActionFor(analysis, 'sample')
doActionFor(analysis, 'sample_due')
analysis_transition_ids = [
t['id'] for t in workflow.getTransitionsFor(analysis)
]
if 'receive' in analysis_transition_ids and sample_state == 'sample_received':
doActionFor(analysis, 'receive')
if not secondary:
# Create sample partitions
if not partitions:
partitions = [{'services': analyses}]
for n, partition in enumerate(partitions):
# Calculate partition id
partition_prefix = sample.getId() + "-P"
partition_id = '%s%s' % (partition_prefix, n + 1)
partition['part_id'] = partition_id
# Point to or create sample partition
if partition_id in sample.objectIds():
partition['object'] = sample[partition_id]
else:
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')
# Return the newly created Analysis Request
return ar
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')
# It's necessary to modify these and we don't want to pollute the
# parent's data
values = values.copy()
analyses = analyses if analyses else values.get('Analyses', [])
if not analyses:
raise RuntimeError(
"create_analysisrequest: no analyses 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
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)
analyses = ar.setAnalyses(service_uids, prices=prices, specs=specifications)
# 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:
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 = [{'services': analyses}]
for n, partition in enumerate(partitions):
# Calculate partition id
partition_prefix = sample.getId() + "-P"
partition_id = '%s%s' % (partition_prefix, n + 1)
partition['part_id'] = partition_id
# Point to or create sample partition
if partition_id in sample.objectIds():
partition['object'] = sample[partition_id]
else:
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')
# Return the newly created Analysis Request
return ar
def create_analysisrequest(context, request, values):
"""Create an AR.
:param context the container in which the AR will be created (Client)
:param request the request object
:param values a dictionary containing fieldname/value pairs, which
will be applied. Some fields will have specific code to handle them,
and others will be directly written to the schema.
:return the new AR instance
Special keys present (or required) in the values dict, which are not present
in the schema:
- Partitions: data about partitions to be created, and the
analyses that are to be assigned to each.
- Prices: custom prices set in the HTML form.
- ResultsRange: Specification values entered in the HTML form.
"""
# Gather neccesary tools
workflow = getToolByName(context, 'portal_workflow')
bc = getToolByName(context, 'bika_catalog')
# Create new sample or locate the existing for secondary AR
if values['Sample']:
secondary = True
if ISample.providedBy(values['Sample']):
sample = values['Sample']
else:
sample = bc(UID=values['Sample'])[0].getObject()
samplingworkflow_enabled = sample.getSamplingWorkflowEnabled()
else:
secondary = False
samplingworkflow_enabled = context.bika_setup.getSamplingWorkflowEnabled()
sample = create_sample(context, request, values)
# Create the Analysis Request
ar = _createObjectByType('AnalysisRequest', context, tmpID())
ar.setSample(sample)
# processform renames the sample, this requires values to contain the Sample.
values['Sample'] = sample
ar.processForm(REQUEST=request, values=values)
# Object has been renamed
ar.edit(RequestID=ar.getId())
# Set initial AR state
workflow_action = 'sampling_workflow' if samplingworkflow_enabled \
else 'no_sampling_workflow'
workflow.doActionFor(ar, workflow_action)
# We need to send a list of service UIDS to setAnalyses function.
# But we may have received a list of titles, list of UIDS,
# list of keywords or list of service objects!
service_uids = []
for obj in values['Analyses']:
uid = False
# service objects
if hasattr(obj, 'portal_type') and obj.portal_type == 'AnalysisService':
uid = obj.UID()
# Analysis objects (shortcut for eg copying analyses from other AR)
elif hasattr(obj, 'portal_type') and obj.portal_type == 'Analysis':
uid = obj.getService()
# Maybe already UIDs.
if not uid:
bsc = getToolByName(context, 'bika_setup_catalog')
brains = bsc(portal_type='AnalysisService', UID=obj)
if brains:
uid = brains[0].UID
# Maybe already UIDs.
if not uid:
bsc = getToolByName(context, 'bika_setup_catalog')
brains = bsc(portal_type='AnalysisService', title=obj)
if brains:
uid = brains[0].UID
if uid:
service_uids.append(uid)
else:
logger.info("In analysisrequest.add.create_analysisrequest: cannot "
"find uid of this service: %s" % obj)
# Set analysis request analyses
ar.setAnalyses(service_uids,
prices=values.get("Prices", []),
specs=values.get('ResultsRange', []))
analyses = ar.getAnalyses(full_objects=True)
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')
for analysis in analyses:
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
partitions = []
for n, partition in enumerate(values['Partitions']):
# Calculate partition id
partition_prefix = sample.getId() + "-P"
partition_id = '%s%s' % (partition_prefix, n + 1)
partition['part_id'] = partition_id
# Point to or create sample partition
if partition_id in sample.objectIds():
partition['object'] = sample[partition_id]
else:
partition['object'] = create_samplepartition(
sample,
partition
)
# now assign analyses to this partition.
obj = partition['object']
for analysis in analyses:
if analysis.getService().UID() in partition['services']:
analysis.setSamplePartition(obj)
partitions.append(partition)
# If Preservation is required for some partitions,
# and the SamplingWorkflow is disabled, we need
# to transition to to_be_preserved manually.
if not samplingworkflow_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')
# Return the newly created Analysis Request
return ar
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 create_analysisrequest(context,
request,
values,
analyses=[],
partitions=None,
specifications=None,
prices=None):
# Gather neccesary tools
workflow = getToolByName(context, 'portal_workflow')
bc = getToolByName(context, 'bika_catalog')
# Create new sample or locate the existing for secondary AR
if values.get('Sample'):
secondary = True
if ISample.providedBy(values['Sample']):
sample = values['Sample']
else:
sample = bc(UID=values['Sample'])[0].getObject()
workflow_enabled = sample.getSamplingWorkflowEnabled()
else:
secondary = False
workflow_enabled = context.bika_setup.getSamplingWorkflowEnabled()
sample = create_sample(context, request, values)
# Create the Analysis Request
ar = _createObjectByType('AnalysisRequest', context, tmpID())
ar.setSample(sample)
# processform renames the sample, this requires values to contain the Sample.
values['Sample'] = sample
ar.processForm(REQUEST=request, values=values)
# Object has been renamed
ar.edit(RequestID=ar.getId())
# Set initial AR state
workflow_action = 'sampling_workflow' if workflow_enabled \
else 'no_sampling_workflow'
workflow.doActionFor(ar, workflow_action)
# Set analysis request analyses
analyses = ar.setAnalyses(analyses, prices=prices, specs=specifications)
if secondary:
# Only 'sample_due' and 'sample_recieved' samples can be selected
# for secondary analyses
doActionFor(ar, 'sample')
doActionFor(ar, 'sample_due')
sample_state = workflow.getInfoFor(sample, 'review_state')
if sample_state == 'sample_received':
doActionFor(ar, 'receive')
for analysis in ar.getAnalyses(full_objects=1):
doActionFor(analysis, 'sample')
doActionFor(analysis, 'sample_due')
analysis_transition_ids = [
t['id'] for t in workflow.getTransitionsFor(analysis)
]
if 'receive' in analysis_transition_ids and sample_state == 'sample_received':
doActionFor(analysis, 'receive')
if not secondary:
# Create sample partitions
if not partitions:
partitions = [{'services': analyses}]
for n, partition in enumerate(partitions):
# Calculate partition id
partition_prefix = sample.getId() + "-P"
partition_id = '%s%s' % (partition_prefix, n + 1)
partition['part_id'] = partition_id
# Point to or create sample partition
if partition_id in sample.objectIds():
partition['object'] = sample[partition_id]
else:
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')
# Return the newly created Analysis Request
return ar
def create_analysisrequest(
context,
request,
values,
analyses=[],
partitions=None,
specifications=None,
prices=None
):
# Gather neccesary tools
workflow = getToolByName(context, 'portal_workflow')
bc = getToolByName(context, 'bika_catalog')
# Create new sample or locate the existing for secondary AR
if values['Sample']:
secondary = True
if ISample.providedBy(values['Sample']):
sample = values['Sample']
else:
sample = bc(UID=values['Sample'])[0].getObject()
workflow_enabled = sample.getSamplingWorkflowEnabled()
else:
secondary = False
workflow_enabled = context.bika_setup.getSamplingWorkflowEnabled()
sample = create_sample(context, request, values)
# Create the Analysis Request
ar = _createObjectByType('AnalysisRequest', context, tmpID())
ar.setSample(sample)
# processform renames the sample, this requires values to contain the Sample.
values['Sample'] = sample
ar.processForm(REQUEST=request, values=values)
# Object has been renamed
ar.edit(RequestID=ar.getId())
# Set initial AR state
workflow_action = 'sampling_workflow' if workflow_enabled \
else 'no_sampling_workflow'
workflow.doActionFor(ar, workflow_action)
# Set analysis request analyses
analyses = ar.setAnalyses(analyses, prices=prices, specs=specifications)
if secondary:
# Only 'sample_due' and 'sample_recieved' samples can be selected
# for secondary analyses
doActionFor(ar, 'sample')
doActionFor(ar, 'sample_due')
sample_state = workflow.getInfoFor(sample, 'review_state')
if sample_state == 'sample_received':
doActionFor(ar, 'receive')
for analysis in ar.getAnalyses(full_objects=1):
doActionFor(analysis, 'sample')
doActionFor(analysis, 'sample_due')
analysis_transition_ids = [t['id'] for t in workflow.getTransitionsFor(analysis)]
if 'receive' in analysis_transition_ids and sample_state == 'sample_received':
doActionFor(analysis, 'receive')
if not secondary:
# Create sample partitions
for n, partition in enumerate(partitions):
# Calculate partition id
partition_prefix = sample.getId() + "-P"
partition_id = '%s%s' % (partition_prefix, n + 1)
partition['part_id'] = partition_id
# Point to or create sample partition
if partition_id in sample.objectIds():
partition['object'] = sample[partition_id]
else:
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')
# Return the newly created Analysis Request
return ar
def create_analysisrequest(client, 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 client:
The container (Client) 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.
"""
# Don't pollute the dict param passed in
values = deepcopy(values)
# Create new sample or locate the existing for secondary AR
secondary = False
sample = None
if not values.get('Sample', False):
sample = create_sample(client, request, values)
else:
sample = get_sample_from_values(client, values)
secondary = True
# Create the Analysis Request
ar = _createObjectByType('AnalysisRequest', client, tmpID())
# Set some required fields manually before processForm is called
ar.setSample(sample)
values['Sample'] = sample
ar.processForm(REQUEST=request, values=values)
ar.edit(RequestID=ar.getId())
# Set analysis request analyses. 'Analyses' param are analyses services
analyses = analyses if analyses else []
service_uids = get_services_uids(
context=client, analyses_serv=analyses, values=values)
# 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)
analyses = ar.getAnalyses(full_objects=True)
# Create sample partitions
if not partitions:
partitions = values.get('Partitions',
[{'services': service_uids}])
part_num = 0
prefix = sample.getId() + "-P"
if secondary:
# Always create new partitions if is a Secondary AR, cause it does
# not make sense to reuse the partitions used in a previous AR!
sparts = sample.getSamplePartitions()
for spart in sparts:
spartnum = int(spart.getId().split(prefix)[1])
if spartnum > part_num:
part_num = spartnum
for n, partition in enumerate(partitions):
# Calculate partition id
partition_id = '%s%s' % (prefix, part_num + 1)
partition['part_id'] = partition_id
# Point to or create sample partition
if partition_id in sample.objectIds():
partition['object'] = sample[partition_id]
else:
partition['object'] = create_samplepartition(
sample,
partition,
analyses
)
part_num += 1
# At this point, we have a fully created AR, with a Sample, Partitions and
# Analyses, but the state of all them is the initial ("sample_registered").
# We can now transition the whole thing (instead of doing it manually for
# each object we created). After and Before transitions will take care of
# cascading and promoting the transitions in all the objects "associated"
# to this Analysis Request.
sampling_workflow_enabled = sample.getSamplingWorkflowEnabled()
action = 'no_sampling_workflow'
if sampling_workflow_enabled:
action = 'sampling_workflow'
# Transition the Analysis Request and related objects to "sampled" (if
# sampling workflow not enabled) or to "to_be_sampled" statuses.
doActionFor(ar, action)
if secondary:
# If secondary AR, then we need to manually transition the AR (and its
# children) to fit with the Sample Partition's current state
sampleactions = getReviewHistoryActionsList(sample)
doActionsFor(ar, sampleactions)
# We need a workaround here in order to transition partitions.
# auto_no_preservation_required and auto_preservation_required are
# auto transitions applied to analysis requests, but partitions don't
# have them, so we need to replace them by the sample_workflow
# equivalent.
if 'auto_no_preservation_required' in sampleactions:
index = sampleactions.index('auto_no_preservation_required')
sampleactions[index] = 'sample_due'
elif 'auto_preservation_required' in sampleactions:
index = sampleactions.index('auto_preservation_required')
sampleactions[index] = 'to_be_preserved'
# We need to transition the partition manually
# Transition pre-preserved partitions
for partition in partitions:
part = partition['object']
doActionsFor(part, sampleactions)
# Transition pre-preserved partitions
for p in partitions:
if 'prepreserved' in p and p['prepreserved']:
part = p['object']
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')
return ar
def create_analysisrequest(
context,
request,
values,
analyses=[],
partitions=None,
specifications=None,
prices=None
):
# Gather neccesary tools
portal_workflow = context.portal_workflow
# Determine if the sampling workflow is enabled
workflow_enabled = context.bika_setup.getSamplingWorkflowEnabled()
# Create the sample
sample = create_sample(context, request, values)
values['Sample'] = sample
values['Sample_uid'] = sample.UID()
# Create the Analysis Request
ar = _createObjectByType('AnalysisRequest', context, tmpID())
ar.setSample(sample)
ar.processForm(REQUEST=request, values=values)
# Object has been renamed
ar.edit(RequestID=ar.getId())
# Set analysis request analyses
analyses = ar.setAnalyses(analyses, prices=prices, specs=specifications)
# Create sample partitions
for n, partition in enumerate(partitions):
# Calculate partition id
partition_prefix = sample.getId() + "-P"
partition_id = '%s%s' % (partition_prefix, n + 1)
partition['part_id'] = partition_id
# Point to or create sample partition
if partition_id in sample.objectIds():
partition['object'] = sample[partition_id]
else:
partition['object'] = create_samplepartition(
sample,
partition,
analyses
)
# Perform the appropriate workflow action
workflow_action = 'sampling_workflow' if workflow_enabled \
else 'no_sampling_workflow'
portal_workflow.doActionFor(ar, workflow_action)
# 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)
# Receive secondary AR
if values.get('Sample_uid', ''):
doActionFor(ar, 'sampled')
doActionFor(ar, 'sample_due')
not_receive = [
'to_be_sampled', 'sample_due', 'sampled', 'to_be_preserved'
]
sample_state = portal_workflow.getInfoFor(sample, 'review_state')
if sample_state not in not_receive:
doActionFor(ar, 'receive')
for analysis in ar.getAnalyses(full_objects=1):
doActionFor(analysis, 'sampled')
doActionFor(analysis, 'sample_due')
if sample_state not in not_receive:
doActionFor(analysis, 'receive')
# Transition pre-preserved partitions
for p in partitions:
if 'prepreserved' in p and p['prepreserved']:
part = p['object']
state = portal_workflow.getInfoFor(part, 'review_state')
if state == 'to_be_preserved':
portal_workflow.doActionFor(part, 'preserve')
# Return the newly created Analysis Request
return ar
def create_analysisrequest(context, request, values, analyses=None,
partitions=None, specifications=None, prices=None):
"""Override the one in bika.lims
"""
# 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
values['SampleType'] = sample.getSampleType()
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 = [{'services': service_uids}]
for n, partition in enumerate(partitions):
# Calculate partition id
partition_prefix = sample.getId() + "-P"
partition_id = '%s%s' % (partition_prefix, n + 1)
partition['part_id'] = partition_id
# Point to or create sample partition
if partition_id in sample.objectIds():
partition['object'] = sample[partition_id]
else:
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')
# Return the newly created Analysis Request
return ar
def create_analysisrequest(
context,
request,
values, # {field: value, ...}
analyses=[],
# uid, service or analysis; list of uids, services or analyses
partitions=None,
# list of dictionaries with container, preservation etc)
specifications=None,
prices=None):
"""This is meant for general use and should do everything necessary to
create and initialise the AR and it's requirements.
XXX The ar-add form's ajaxAnalysisRequestSubmit should be calling this.
"""
# Gather neccesary tools
workflow = getToolByName(context, 'portal_workflow')
bc = getToolByName(context, 'bika_catalog')
# It's necessary to modify these and we don't want to pollute the
# parent's data
values = values.copy()
# 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
if ISample.providedBy(values['Sample']):
sample = values['Sample']
else:
brains = bc(UID=values['Sample'])
if brains:
sample = brains[0].getObject()
if not sample:
raise RuntimeError(
"create_analysisrequest No sample. values=%s" % 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
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)
analyses = ar.setAnalyses(service_uids, prices=prices, specs=specifications)
if secondary:
# Only 'sample_due' and 'sample_recieved' samples can be selected
# for secondary analyses
api.content.transition(obj=ar, to_state='sampled')
api.content.transition(obj=ar, to_state='sample_due')
sample_state = workflow.getInfoFor(sample, 'review_state')
if sample_state == 'sample_received':
doActionFor(ar, 'receive')
for analysis in ar.getAnalyses(full_objects=1):
doActionFor(analysis, 'sample')
doActionFor(analysis, 'sample_due')
analysis_transition_ids = [t['id'] for t in
workflow.getTransitionsFor(analysis)]
if 'receive' in analysis_transition_ids and sample_state == 'sample_received':
doActionFor(analysis, 'receive')
if not secondary:
# Create sample partitions
if not partitions:
partitions = [{'services': analyses}]
for n, partition in enumerate(partitions):
# Calculate partition id
partition_prefix = sample.getId() + "-P"
partition_id = '%s%s' % (partition_prefix, n + 1)
partition['part_id'] = partition_id
# Point to or create sample partition
if partition_id in sample.objectIds():
partition['object'] = sample[partition_id]
else:
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')
# Return the newly created Analysis Request
return ar
def create_analysisrequest(context, request, values):
"""Create an AR.
:param context the container in which the AR will be created (Client)
:param request the request object
:param values a dictionary containing fieldname/value pairs, which
will be applied. Some fields will have specific code to handle them,
and others will be directly written to the schema.
:return the new AR instance
Special keys present (or required) in the values dict, which are not present
in the schema:
- Partitions: data about partitions to be created, and the
analyses that are to be assigned to each.
- Prices: custom prices set in the HTML form.
- ResultsRange: Specification values entered in the HTML form.
"""
# Gather neccesary tools
workflow = getToolByName(context, 'portal_workflow')
bc = getToolByName(context, 'bika_catalog')
# Create new sample or locate the existing for secondary AR
sample = False
if values['Sample']:
if ISample.providedBy(values['Sample']):
secondary = True
sample = values['Sample']
samplingworkflow_enabled = sample.getSamplingWorkflowEnabled()
else:
brains = bc(UID=values['Sample'])
if brains:
secondary = True
sample = brains[0].getObject()
samplingworkflow_enabled = sample.getSamplingWorkflowEnabled()
if not sample:
secondary = False
sample = create_sample(context, request, values)
samplingworkflow_enabled = context.bika_setup.getSamplingWorkflowEnabled()
# Create the Analysis Request
ar = _createObjectByType('AnalysisRequest', context, tmpID())
ar.setSample(sample)
# processform renames the sample, this requires values to contain the Sample.
values['Sample'] = sample
ar.processForm(REQUEST=request, values=values)
# Object has been renamed
ar.edit(RequestID=ar.getId())
# Set initial AR state
workflow_action = 'sampling_workflow' if samplingworkflow_enabled \
else 'no_sampling_workflow'
workflow.doActionFor(ar, workflow_action)
# We need to send a list of service UIDS to setAnalyses function.
# But we may have received a list of titles, list of UIDS,
# list of keywords or list of service objects!
service_uids = []
for obj in values['Analyses']:
uid = False
# service objects
if hasattr(obj, 'portal_type') and obj.portal_type == 'AnalysisService':
uid = obj.UID()
# Analysis objects (shortcut for eg copying analyses from other AR)
elif hasattr(obj, 'portal_type') and obj.portal_type == 'Analysis':
uid = obj.getService()
# Maybe already UIDs.
if not uid:
bsc = getToolByName(context, 'bika_setup_catalog')
brains = bsc(portal_type='AnalysisService', UID=obj)
if brains:
uid = brains[0].UID
# Maybe already UIDs.
if not uid:
bsc = getToolByName(context, 'bika_setup_catalog')
brains = bsc(portal_type='AnalysisService', title=obj)
if brains:
uid = brains[0].UID
if uid:
service_uids.append(uid)
else:
logger.info("In analysisrequest.add.create_analysisrequest: cannot "
"find uid of this service: %s" % obj)
# Set analysis request analyses
ar.setAnalyses(service_uids,
prices=values.get("Prices", []),
specs=values.get('ResultsRange', []))
analyses = ar.getAnalyses(full_objects=True)
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')
for analysis in analyses:
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
partitions = []
for n, partition in enumerate(values['Partitions']):
# Calculate partition id
partition_prefix = sample.getId() + "-P"
partition_id = '%s%s' % (partition_prefix, n + 1)
partition['part_id'] = partition_id
# Point to or create sample partition
if partition_id in sample.objectIds():
partition['object'] = sample[partition_id]
else:
partition['object'] = create_samplepartition(
sample,
partition
)
# now assign analyses to this partition.
obj = partition['object']
for analysis in analyses:
if analysis.getService().UID() in partition['services']:
analysis.setSamplePartition(obj)
partitions.append(partition)
# If Preservation is required for some partitions,
# and the SamplingWorkflow is disabled, we need
# to transition to to_be_preserved manually.
if not samplingworkflow_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')
# Return the newly created Analysis Request
return ar