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)
# Set analysis request analyses
ar.setAnalyses(values['Analyses'],
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):
"""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)
# Set analysis request analyses
ar.setAnalyses(values['Analyses'],
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=[],
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
