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Inject additional analyses fields (#87)
* Allow to select fields * Added doctest * Changelog updated * Additional Analyses Fields * changelog updated * Added doctest --------- Co-authored-by: Jordi Puiggené <jp@naralabs.com>
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‎docs/changelog.rst‎

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2.7.0 (unreleased)
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------------------
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- #87 Inject additional analyses fields
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- #85 Allow field projection
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- #81 Support second-level precision on searches against DateIndex
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- #83 Fetch multiple items by UID

‎src/senaite/jsonapi/configure.zcml‎

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factory=".dataproviders.DexterityDataProvider"
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/>
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<!-- Data provider for Analysis content types (computed fields) -->
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<adapter
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name="senaite.jsonapi.dataproviders.AnalysisDataProvider"
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factory=".dataproviders.AnalysisDataProvider"
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/>
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<!-- DATA MANAGERS
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Context level interface to get and set values (by name) and get a JSON compatible

‎src/senaite/jsonapi/dataproviders.py‎

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from AccessControl import Unauthorized
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from Acquisition import aq_base
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from bika.lims.interfaces import IAnalysis
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from plone.dexterity.interfaces import IDexterityContent
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from Products.Archetypes.interfaces import IBaseObject
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from Products.CMFCore.interfaces import ISiteRoot
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self.keys = schema.keys()
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class AnalysisDataProvider(Base):
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"""Data provider for Analysis content types.
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Supplements the standard ATDataProvider with computed fields that are
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implemented as methods rather than AT schema fields and therefore not
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picked up automatically.
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"""
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interface.implements(IInfo)
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component.adapts(IAnalysis)
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def __init__(self, context):
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super(AnalysisDataProvider, self).__init__(context)
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# No schema keys – this provider only adds computed fields via
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# the attributes mapping below.
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self.keys = []
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self.attributes = {}
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def to_dict(self):
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"""Return computed analysis fields."""
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out = {}
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get_formatted = getattr(self.context, "getFormattedResult", None)
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if callable(get_formatted):
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out["getFormattedResult"] = get_formatted(html=False)
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is_retest = getattr(self.context, "isRetest", None)
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if callable(is_retest):
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out["isRetest"] = is_retest()
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return out
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class SiteRootDataProvider(Base):
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""" Site Root Adapter
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"""

‎src/senaite/jsonapi/tests/doctests/analysis_data_provider.rst‎

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ANALYSIS DATA PROVIDER
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----------------------
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Running this test from the buildout directory:
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bin/test test_doctests -t analysis_data_provider
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Test Setup
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~~~~~~~~~~
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Needed Imports:
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>>> import json
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>>> import transaction
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>>> import urllib
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>>> from DateTime import DateTime
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>>> from plone.app.testing import setRoles
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>>> from plone.app.testing import TEST_USER_ID
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>>> from bika.lims import api
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Functional Helpers:
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>>> def get(url):
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... browser.open("{}/{}".format(api_url, url))
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... return browser.contents
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>>> def post(url, data):
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... url = "{}/{}".format(api_url, url)
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... browser.post(url, urllib.urlencode(data, doseq=True))
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... return browser.contents
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>>> def create(data):
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... response = post("create", data)
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... assert("items" in response)
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... response = json.loads(response)
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... items = response.get("items")
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... assert(len(items)==1)
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... item = response.get("items")[0]
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... assert("uid" in item)
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... return api.get_object(item["uid"])
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Variables:
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>>> portal = self.portal
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>>> portal_url = portal.absolute_url()
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>>> api_url = "{}/@@API/senaite/v1".format(portal_url)
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>>> setup = api.get_setup()
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>>> browser = self.getBrowser()
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>>> setRoles(portal, TEST_USER_ID, ["LabManager", "Manager"])
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>>> transaction.commit()
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Create test data
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~~~~~~~~~~~~~~~~
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Create the required setup objects:
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>>> client = create({
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... "portal_type": "Client",
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... "parent_path": api.get_path(portal.clients),
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... "title": "Test Client",
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... "ClientID": "TC"})
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>>> contact = create({
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... "portal_type": "Contact",
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... "parent_path": api.get_path(client),
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... "Firstname": "Jane",
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... "Surname": "Doe"})
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>>> sample_type = create({
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... "portal_type": "SampleType",
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... "parent_path": api.get_path(portal.setup.sampletypes),
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... "title": "Water",
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... "MinimumVolume": "100 ml",
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... "Prefix": "WA"})
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>>> lab_contact = create({
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... "portal_type": "LabContact",
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... "parent_path": api.get_path(setup.bika_labcontacts),
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... "Firstname": "Lab",
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... "Surname": "Manager"})
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>>> department = create({
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... "portal_type": "Department",
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... "DepartmentID": "CH",
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... "parent_path": api.get_path(portal.setup.departments),
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... "title": "Chemistry",
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... "Manager": api.get_uid(lab_contact)})
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>>> category = create({
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... "portal_type": "AnalysisCategory",
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... "parent_path": api.get_path(portal.setup.analysiscategories),
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... "title": "Metals",
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... "Department": api.get_uid(department)})
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>>> service = create({
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... "portal_type": "AnalysisService",
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... "parent_path": api.get_path(setup.bika_analysisservices),
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... "title": "Calcium",
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... "Keyword": "Ca",
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... "Price": 10,
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... "Category": api.get_uid(category)})
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Create a Sample with one analysis:
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>>> sample = create({
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... "portal_type": "AnalysisRequest",
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... "parent_uid": api.get_uid(client),
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... "Contact": api.get_uid(contact),
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... "DateSampled": DateTime().ISO8601(),
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... "SampleType": api.get_uid(sample_type),
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... "Analyses": [api.get_uid(service)]})
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>>> analyses = sample.getAnalyses(full_objects=True)
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>>> len(analyses)
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1
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>>> analysis = analyses[0]
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>>> analysis_uid = api.get_uid(analysis)
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Analysis fields via the API
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~~~~~~~~~~~~~~~~~~~~~~~~~~~
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When fetching an analysis with ``complete=1``, the response includes the
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computed fields ``getFormattedResult`` and ``isRetest`` injected by the
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``AnalysisDataProvider``:
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>>> response = get("analysis/{}?complete=1".format(analysis_uid))
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>>> data = json.loads(response)
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>>> items = data.get("items")
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>>> len(items)
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1
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>>> item = items[0]
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The ``getFormattedResult`` field is present. Since no result has been
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submitted yet, it returns an empty string:
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>>> "getFormattedResult" in item
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True
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>>> item["getFormattedResult"]
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u''
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The ``isRetest`` field is present and ``False`` for a regular analysis:
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>>> "isRetest" in item
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True
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>>> item["isRetest"]
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False
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Formatted result after submitting a value
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Receive the sample and submit a result for the analysis:
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>>> from bika.lims.workflow import doActionFor as do_action_for
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>>> transitioned = do_action_for(sample, "receive")
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>>> analysis.setResult("42")
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>>> transaction.commit()
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The formatted result now reflects the submitted value:
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>>> response = get("analysis/{}?complete=1".format(analysis_uid))
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>>> data = json.loads(response)
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>>> item = data["items"][0]
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>>> item["getFormattedResult"]
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u'42'
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>>> item["isRetest"]
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False
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Formatted result with ResultOptions
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Create a service with predefined result options (select type):
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>>> service_ro = create({
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... "portal_type": "AnalysisService",
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... "parent_path": api.get_path(setup.bika_analysisservices),
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... "title": "Color",
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... "Keyword": "Color",
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... "Price": 5,
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... "Category": api.get_uid(category)})
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>>> options = [
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... {"ResultValue": "0", "ResultText": "Colorless"},
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... {"ResultValue": "1", "ResultText": "Yellow"},
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... {"ResultValue": "2", "ResultText": "Brown"},
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... ]
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>>> service_ro.setResultOptions(options)
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>>> service_ro.setResultType("select")
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>>> transaction.commit()
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Create a sample with this service:
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>>> sample2 = create({
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... "portal_type": "AnalysisRequest",
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... "parent_uid": api.get_uid(client),
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... "Contact": api.get_uid(contact),
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... "DateSampled": DateTime().ISO8601(),
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... "SampleType": api.get_uid(sample_type),
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... "Analyses": [api.get_uid(service_ro)]})
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>>> analyses2 = sample2.getAnalyses(full_objects=True)
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>>> an_color = analyses2[0]
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>>> an_color_uid = api.get_uid(an_color)
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Receive the sample and set a result using one of the option values:
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>>> transitioned = do_action_for(sample2, "receive")
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>>> an_color.setResult("1")
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>>> transaction.commit()
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The formatted result returns the display text, not the raw value:
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>>> response = get("analysis/{}?complete=1".format(an_color_uid))
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>>> data = json.loads(response)
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>>> item = data["items"][0]
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>>> item["getFormattedResult"]
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u'Yellow'
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>>> item["isRetest"]
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False
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Retest analysis
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~~~~~~~~~~~~~~~
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Submit the first analysis and then retract it to create a retest:
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>>> transitioned = do_action_for(analysis, "submit")
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>>> transitioned = do_action_for(analysis, "retract")
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>>> transaction.commit()
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The retracted analysis now has a retest. Fetch the retest:
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>>> retest = analysis.getRetest()
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>>> retest_uid = api.get_uid(retest)
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The retest is flagged as such via the API:
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>>> response = get("analysis/{}?complete=1".format(retest_uid))
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>>> data = json.loads(response)
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>>> item = data["items"][0]
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>>> item["isRetest"]
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True
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The original retracted analysis is not a retest:
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>>> response = get("analysis/{}?complete=1".format(analysis_uid))
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>>> data = json.loads(response)
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>>> item = data["items"][0]
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>>> item["isRetest"]
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False

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