Package: senaite.api
SENAITE.API:The Swiss-Army-Knife for SENAITE Core and Add-on developersAboutSENAITE API is the Swiss-Army-Knife for SENAITE Core and Add-on developers. It
provides a sane interface for common tasks in SENAITE, like e.g. object
creation, lookup by ID/UID, search etc.Please see the doctests for further details and usage:Core API DocumentationAnalysis API DocumentationInstallationPlease follow the installations instructions forPlone 4andsenaite.lims.To install SENAITE API, you have to addsenaite.apiinto theeggslist inside the[buildout]section of yourbuildout.cfg:[buildout]
parts =
    instance
extends =
    http://dist.plone.org/release/4.3.17/versions.cfg
find-links =
    http://dist.plone.org/release/4.3.17
    http://dist.plone.org/thirdparty
eggs =
    Plone
    Pillow
    senaite.lims
    senaite.api
zcml =
eggs-directory = ${buildout:directory}/eggs

[instance]
recipe = plone.recipe.zope2instance
user = admin:admin
http-address = 0.0.0.0:8080
eggs =
    ${buildout:eggs}
zcml =
    ${buildout:zcml}

[versions]
setuptools =
zc.buildout =NoteThe above example works for the buildout created by the unified
installer. If you however have a custom buildout you might need to add
the egg to theeggslist in the[instance]section rather than
adding it in the[buildout]section.Also see this section of the Plone documentation for further details:https://docs.plone.org/4/en/manage/installing/installing_addons.htmlImportantFor the changes to take effect you need to re-run buildout from your
console:bin/buildoutSENAITE API DOCTESTThe SENAITE LIMS API provides single functions for single purposes.
This Test builds completely on the API without any further imports needed.Running this test from the buildout directory:bin/test test_doctests -t APIIntroductionThe purpose of this API is to help coders to follow the DRY principle (Don’t
Repeat Yourself). It also ensures that the most effective and efficient method is
used to achieve a task.Import it first:>>> from senaite import apiGetting the PortalThe Portal is the SENAITE LIMS root object:>>> portal = api.get_portal()
>>> portal
<PloneSite at /plone>Getting the Setup objectThe Setup object gives access to all of the Bika configuration settings:>>> bika_setup = api.get_setup()
>>> bika_setup
<BikaSetup at /plone/bika_setup>Creating new ContentCreating new contents in Bika LIMS requires some special knowledge.
This function helps to do it right and creates a content for you.Here we create a newClientin theplone/clientsfolder:>>> client = api.create(portal.clients, "Client", title="Test Client")
>>> client
<Client at /plone/clients/client-1>

 >>> client.Title()
 'Test Client'Getting a ToolThere are many ways to get a tool in Bika LIMS / Plone. This function
centralizes this functionality and makes it painless:>>> api.get_tool("bika_setup_catalog")
<BikaSetupCatalog at /plone/bika_setup_catalog>Trying to fetch an non-existing tool raises a customSenaiteAPIError:>>> api.get_tool("NotExistingTool")
Traceback (most recent call last):
[...]
SenaiteAPIError: No tool named 'NotExistingTool' found.This error can also be used for custom methods with thefailfunction:>>> api.fail("This failed badly")
Traceback (most recent call last):
[...]
SenaiteAPIError: This failed badlyGetting an ObjectGetting a tool from a catalog brain is a common task in Bika LIMS. This function
provides an unified interface to portal objectsandbrains.
Furthermore it is idempotent, so it can be called multiple times in a row.We will demonstrate the usage on the client object we created above:>>> api.get_object(client)
<Client at /plone/clients/client-1>

>>> api.get_object(api.get_object(client))
<Client at /plone/clients/client-1>Now we show it with catalog results:>>> portal_catalog = api.get_tool("portal_catalog")
>>> brains = portal_catalog(portal_type="Client")
>>> brains
[<Products.ZCatalog.Catalog.mybrains object at 0x...>]

>>> brain = brains[0]

>>> api.get_object(brain)
<Client at /plone/clients/client-1>

>>> api.get_object(api.get_object(brain))
<Client at /plone/clients/client-1>No supported objects raise an error:>>> api.get_object(object())
Traceback (most recent call last):
[...]
SenaiteAPIError: <object object at 0x...> is not supported.To check if an object is supported, e.g. is an ATCT, Dexterity, ZCatalog or
Portal object, we can use theis_objectfunction:>>> api.is_object(client)
  True

  >>> api.is_object(brain)
  True

  >>> api.is_object(api.get_portal())
  True

  >>> api.is_object(None)
  False

>>> api.is_object(object())
  FalseChecking if an Object is the PortalSometimes it can be handy to check if the current object is the portal:>>> api.is_portal(portal)
True

>>> api.is_portal(client)
False

>>> api.is_portal(object())
FalseChecking if an Object is a Catalog BrainKnowing if we have an object or a brain can be handy. This function checks this for you:>>> api.is_brain(brain)
True

>>> api.is_brain(api.get_object(brain))
False

>>> api.is_brain(object())
FalseChecking if an Object is a Dexterity ContentThis function checks if an object is aDexteritycontent type:>>> api.is_dexterity_content(client)
False

>>> api.is_dexterity_content(portal)
FalseWe currently have noDexteritycontents, so testing this comes later…Checking if an Object is an AT ContentThis function checks if an object is anArchetypescontent type:>>> api.is_at_content(client)
True

>>> api.is_at_content(portal)
False

>>> api.is_at_content(object())
FalseGetting the Schema of a ContentThe schema contains the fields of a content object. Getting the schema is a
common task, but differs betweenATContentTypebased objects andDexteritybased objects. This function brings it under one umbrella:>>> schema = api.get_schema(client)
>>> schema
<Products.Archetypes.Schema.Schema object at 0x...>Catalog brains are also supported:>>> api.get_schema(brain)
<Products.Archetypes.Schema.Schema object at 0x...>Getting the Fields of a ContentThe fields contain all the values that an object holds and are therefore
responsible for getting and setting the information.This function returns the fields as a dictionary mapping of{“key”: value}:>>> fields = api.get_fields(client)
>>> fields.get("ClientID")
<Field ClientID(string:rw)>Catalog brains are also supported:>>> api.get_fields(brain).get("ClientID")
<Field ClientID(string:rw)>Getting the ID of a ContentGetting the ID is a common task in Bika LIMS.
This function takes care that catalog brains are not waked up for this task:>>> api.get_id(portal)
'plone'

>>> api.get_id(client)
'client-1'

>>> api.get_id(brain)
'client-1'Getting the Title of a ContentGetting the Title is a common task in Bika LIMS.
This function takes care that catalog brains are not waked up for this task:>>> api.get_title(portal)
u'Plone site'

>>> api.get_title(client)
'Test Client'

>>> api.get_title(brain)
'Test Client'Getting the Description of a ContentGetting the Description is a common task in Bika LIMS.
This function takes care that catalog brains are not waked up for this task:>>> api.get_description(portal)
''

>>> api.get_description(client)
''

>>> api.get_description(brain)
''Getting the UID of a ContentGetting the UID is a common task in Bika LIMS.
This function takes care that catalog brains are not waked up for this task.The portal object actually has no UID. This funciton defines it therfore to be0:>>> api.get_uid(portal)
'0'

>>> uid_client = api.get_uid(client)
>>> uid_client_brain = api.get_uid(brain)
>>> uid_client is uid_client_brain
TrueGetting the URL of a ContentGetting the URL is a common task in Bika LIMS.
This function takes care that catalog brains are not waked up for this task:>>> api.get_url(portal)
'http://nohost/plone'

>>> api.get_url(client)
'http://nohost/plone/clients/client-1'

>>> api.get_url(brain)
'http://nohost/plone/clients/client-1'Getting the Icon of a Content>>> api.get_icon(client)
'<img width="16" height="16" src="http://nohost/plone/++resource++bika.lims.images/client.png" title="Test Client" />'

>>> api.get_icon(brain)
'<img width="16" height="16" src="http://nohost/plone/++resource++bika.lims.images/client.png" title="Test Client" />'

>>> api.get_icon(client, html_tag=False)
'http://nohost/plone/++resource++bika.lims.images/client.png'

>>> api.get_icon(client, html_tag=False)
'http://nohost/plone/++resource++bika.lims.images/client.png'Getting an object by UIDThis function finds an object by its uinique ID (UID).
The portal object with the defined UId of ‘0’ is also supported:>>> api.get_object_by_uid('0')
<PloneSite at /plone>

>>> api.get_object_by_uid(uid_client)
<Client at /plone/clients/client-1>

>>> api.get_object_by_uid(uid_client_brain)
<Client at /plone/clients/client-1>If a default value is provided, the function will never fail.  Any exception
or error will result in the default value being returned:>>> api.get_object_by_uid('invalid uid', 'default')
'default'

>>> api.get_object_by_uid(None, 'default')
'default'Getting an object by PathThis function finds an object by its physical path:>>> api.get_object_by_path('/plone')
<PloneSite at /plone>

>>> api.get_object_by_path('/plone/clients/client-1')
<Client at /plone/clients/client-1>Paths outside the portal raise an error:>>> api.get_object_by_path('/root')
Traceback (most recent call last):
[...]
SenaiteAPIError: Not a physical path inside the portal.Any exception returns default value:>>> api.get_object_by_path('/invaid/path', 'default')
'default'

>>> api.get_object_by_path(None, 'default')
'default'Getting the Physical Path of an ObjectThe physical path describes exactly where an object is located inside the portal.
This function unifies the different approaches to get the physical path and does
so in the most efficient way:>>> api.get_path(portal)
'/plone'

>>> api.get_path(client)
'/plone/clients/client-1'

>>> api.get_path(brain)
'/plone/clients/client-1'

>>> api.get_path(object())
Traceback (most recent call last):
[...]
SenaiteAPIError: <object object at 0x...> is not supported.Getting the Physical Parent Path of an ObjectThis function returns the physical path of the parent object:>>> api.get_parent_path(client)
'/plone/clients'

>>> api.get_parent_path(brain)
'/plone/clients'However, this function goes only up to the portal object:>>> api.get_parent_path(portal)
'/plone'Like with the other functions, only portal objects are supported:>>> api.get_parent_path(object())
Traceback (most recent call last):
[...]
SenaiteAPIError: <object object at 0x...> is not supported.Getting the Parent ObjectThis function returns the parent object:>>> api.get_parent(client)
<ClientFolder at /plone/clients>Brains are also supported:>>> api.get_parent(brain)
<ClientFolder at /plone/clients>The function can also use a catalog query on theportal_catalogand return a
brain, if the passed parametercatalog_searchwas set to true.>>> api.get_parent(client, catalog_search=True)
<Products.ZCatalog.Catalog.mybrains object at 0x...>

>>> api.get_parent(brain, catalog_search=True)
<Products.ZCatalog.Catalog.mybrains object at 0x...>However, this function goes only up to the portal object:>>> api.get_parent(portal)
<PloneSite at /plone>Like with the other functions, only portal objects are supported:>>> api.get_parent(object())
Traceback (most recent call last):
[...]
SenaiteAPIError: <object object at 0x...> is not supported.Searching ObjectsSearching in Bika LIMS requires knowledge in which catalog the object is indexed.
This function unifies all Bika LIMS catalog to a single search interface:>>> results = api.search({'portal_type': 'Client'})
>>> results
[<Products.ZCatalog.Catalog.mybrains object at 0x...>]Multiple content types are also supported:>>> results = api.search({'portal_type': ['Client', 'ClientFolder'], 'sort_on': 'getId'})
>>> map(api.get_id, results)
['client-1', 'clients']Now we create some objects which are located in thebika_setup_catalog:>>> instruments = bika_setup.bika_instruments
>>> instrument1 = api.create(instruments, "Instrument", title="Instrument-1")
>>> instrument2 = api.create(instruments, "Instrument", title="Instrument-2")
>>> instrument3 = api.create(instruments, "Instrument", title="Instrument-3")

>>> results = api.search({'portal_type': 'Instrument', 'sort_on': 'getId'})
>>> len(results)
3

>>> map(api.get_id, results)
['instrument-1', 'instrument-2', 'instrument-3']Queries which result in multiple catalogs will be refused, as it would require
manual merging and sorting of the results afterwards. Thus, we fail here:>>> results = api.search({'portal_type': ['Client', 'ClientFolder', 'Instrument'], 'sort_on': 'getId'})
Traceback (most recent call last):
[...]
SenaiteAPIError: Multi Catalog Queries are not supported, please specify a catalog.Catalog queries w/o anyportal_type, default to theportal_catalog, which
will not find the following items:>>> analysiscategories = bika_setup.bika_analysiscategories
>>> analysiscategory1 = api.create(analysiscategories, "AnalysisCategory", title="AC-1")
>>> analysiscategory2 = api.create(analysiscategories, "AnalysisCategory", title="AC-2")
>>> analysiscategory3 = api.create(analysiscategories, "AnalysisCategory", title="AC-3")

>>> results = api.search({"id": "analysiscategory-1"})
>>> len(results)
0Would we add theportal_type, the search function would ask thearchetype_toolfor the right catalog, and it would return a result:>>> results = api.search({"portal_type": "AnalysisCategory", "id": "analysiscategory-1"})
>>> len(results)
1We could also explicitly define a catalog to achieve the same:>>> results = api.search({"id": "analysiscategory-1"}, catalog="bika_setup_catalog")
>>> len(results)
1To see inactive or dormant items, we must explicitly query them of filter them
afterwars manually:>>> results = api.search({"portal_type": "AnalysisCategory", "id": "analysiscategory-1"})
>>> len(results)
1Now we deactivate the item:>>> analysiscategory1 = api.do_transition_for(analysiscategory1, 'deactivate')
>>> api.is_active(analysiscategory1)
FalseThe search will still find the item:>>> results = api.search({"portal_type": "AnalysisCategory", "id": "analysiscategory-1"})
>>> len(results)
1Unless we filter it out manually:>>> len(filter(api.is_active, results))
0Or provide a correct query:>>> results = api.search({"portal_type": "AnalysisCategory", "id": "analysiscategory-1", "inactive_status": "active"})
>>> len(results)
1Getting the registered CatalogsBika LIMS uses multiple catalogs registered via the Archetype Tool. This
function returns a list of registered catalogs for a brain or object:>>> api.get_catalogs_for(client)
[<CatalogTool at /plone/portal_catalog>]

>>> api.get_catalogs_for(instrument1)
[<BikaSetupCatalog at /plone/bika_setup_catalog>, <CatalogTool at /plone/portal_catalog>]

>>> api.get_catalogs_for(analysiscategory1)
[<BikaSetupCatalog at /plone/bika_setup_catalog>]Getting an Attribute of an ObjectThis function handles attributes and methods the same and returns their value.
It also handles security and is able to return a default value instead of
raising anUnauthorizederror:>>> uid_brain = api.safe_getattr(brain, "UID")
>>> uid_obj = api.safe_getattr(client, "UID")

>>> uid_brain == uid_obj
True

>>> api.safe_getattr(brain, "review_state")
'active'

>>> api.safe_getattr(brain, "NONEXISTING")
Traceback (most recent call last):
[...]
SenaiteAPIError: Attribute 'NONEXISTING' not found.

>>> api.safe_getattr(brain, "NONEXISTING", "")
''Getting the Portal CatalogThis tool is needed so often, that this function just returns it:>>> api.get_portal_catalog()
<CatalogTool at /plone/portal_catalog>Getting the Review History of an ObjectThe review history gives information about the objects’ workflow changes:>>> review_history = api.get_review_history(client)
>>> sorted(review_history[0].items())
[('action', None), ('actor', 'test_user_1_'), ('comments', ''), ('review_state', 'active'), ('time', DateTime('...'))]Getting the Revision History of an ObjectThe review history gives information about the objects’ workflow changes:>>> revision_history = api.get_revision_history(client)
>>> sorted(revision_history[0])
['action', 'actor', 'actor_home', 'actorid', 'comments', 'review_state', 'state_title', 'time', 'transition_title', 'type']
>>> revision_history[0]["transition_title"]
u'Create'Getting the assigned Workflows of an ObjectThis function returns all assigned workflows for a given object:>>> api.get_workflows_for(bika_setup)
('bika_one_state_workflow',)

>>> api.get_workflows_for(client)
('bika_client_workflow', 'bika_inactive_workflow')This function also supports the portal_type as parameter:>>> api.get_workflows_for(api.get_portal_type(client))
('bika_client_workflow', 'bika_inactive_workflow')Getting the Workflow Status of an ObjectThis function returns the state of a given object:>>> api.get_workflow_status_of(client)
'active'It is also capable to get the state of another state variable:>>> api.get_workflow_status_of(client, "inactive_state")
'active'Deactivate the client:>>> api.do_transition_for(client, "deactivate")
<Client at /plone/clients/client-1>

>>> api.get_workflow_status_of(client, "inactive_state")
'inactive'

>>> api.get_workflow_status_of(client)
'active'Reactivate the client:>>> api.do_transition_for(client, "activate")
<Client at /plone/clients/client-1>

>>> api.get_workflow_status_of(client, "inactive_state")
'active'Getting the available transitions for an objectThis function returns all possible transitions from all workflows in the
object’s workflow chain.Let’s create a Batch. It should allow us to invoke transitions from two
workflows; ‘close’ from the bika_batch_workflow, and ‘cancel’ from the
bika_cancellation_workflow:>>> batch1 = api.create(portal.batches, "Batch", title="Test Batch")
>>> transitions = api.get_transitions_for(batch1)
>>> len(transitions)
2The transitions are returned as a list of dictionaries. Since we cannot rely on
the order of dictionary keys, we will have to satisfy ourselves here with
checking that the two expected transitions are present in the return value:>>> 'Close' in [t['title'] for t in transitions]
True
>>> 'Cancel' in [t['title'] for t in transitions]
TrueGetting the creation date of an objectThis function returns the creation date of a given object:>>> created = api.get_creation_date(client)
>>> created
DateTime('...')Getting the modification date of an objectThis function returns the modification date of a given object:>>> modified = api.get_modification_date(client)
>>> modified
DateTime('...')Getting the review state of an objectThis function returns the review state of a given object:>>> review_state = api.get_review_status(client)
>>> review_state
'active'It should also work for catalog brains:>>> portal_catalog = api.get_tool("portal_catalog")
>>> results = portal_catalog({"portal_type": "Client", "UID": api.get_uid(client)})
>>> len(results)
1
>>> api.get_review_status(results[0]) == review_state
TrueGetting the registered Catalogs of an ObjectThis function returns a list of all registered catalogs within thearchetype_toolfor a given portal_type or object:>>> api.get_catalogs_for(client)
[<CatalogTool at /plone/portal_catalog>]It also supports theportal_typeas a parameter:>>> api.get_catalogs_for("Analysis")
[<BikaAnalysisCatalog at /plone/bika_analysis_catalog>]Transitioning an ObjectThis function performs a workflow transition and returns the object:>>> client = api.do_transition_for(client, "deactivate")
>>> api.is_active(client)
False

>>> client = api.do_transition_for(client, "activate")
>>> api.is_active(client)
TrueGetting inactive/cancellation state of different workflowsThere are two workflows allowing an object to be set inactive.  We provide
the is_active function to return False if an item is set inactive with either
of these workflows.In the search() test above, the is_active function’s handling of brain states
is tested.  Here, I just want to test if object states are handled correctly.For setup types, we use bika_inctive_workflow:>>> method1 = api.create(portal.methods, "Method", title="Test Method")
>>> api.is_active(method1)
True
>>> method1 = api.do_transition_for(method1, 'deactivate')
>>> api.is_active(method1)
FalseFor transactional types, bika_cancellation_workflow is used:>>> batch1 = api.create(portal.batches, "Batch", title="Test Batch")
>>> api.is_active(batch1)
True
>>> batch1 = api.do_transition_for(batch1, 'cancel')
>>> api.is_active(batch1)
FalseGetting the granted Roles for a certain Permission on an ObjectThis function returns a list of Roles, which are granted the given Permission
for the passed in object:>>> api.get_roles_for_permission("Modify portal content", bika_setup)
['LabManager', 'Manager']Checking if an Object is VersionableSome contents in Bika LIMS support versioning. This function checks this for you.Instruments are not versionable:>>> api.is_versionable(instrument1)
FalseAnalysisservices are versionable:>>> analysisservices = bika_setup.bika_analysisservices
>>> analysisservice1 = api.create(analysisservices, "AnalysisService", title="AnalysisService-1")
>>> analysisservice2 = api.create(analysisservices, "AnalysisService", title="AnalysisService-2")
>>> analysisservice3 = api.create(analysisservices, "AnalysisService", title="AnalysisService-3")

>>> api.is_versionable(analysisservice1)
TrueGetting the Version of an ObjectThis function returns the version as an integer:>>> api.get_version(analysisservice1)
0CallingprocessFormbumps the version:>>> analysisservice1.processForm()
>>> api.get_version(analysisservice1)
1Getting a Browser ViewGetting a browser view is a common task in Bika LIMS:>>> api.get_view("plone")
<Products.Five.metaclass.Plone object at 0x...>

>>> api.get_view("workflow_action")
<Products.Five.metaclass.WorkflowAction object at 0x...>Getting the RequestThis function will return the global request object:>>> api.get_request()
<HTTPRequest, URL=http://nohost>Getting a GroupUsers in Bika LIMS are managed in groups. A common group is theClientsgroup,
where all users of client contacts are grouped.
This function gives easy access and is also idempotent:>>> clients_group = api.get_group("Clients")
>>> clients_group
<GroupData at /plone/portal_groupdata/Clients used for /plone/acl_users/source_groups>

>>> api.get_group(clients_group)
<GroupData at /plone/portal_groupdata/Clients used for /plone/acl_users/source_groups>Non-existing groups are not found:>>> api.get_group("NonExistingGroup")Getting a UserUsers can be fetched by their user id. The function is idempotent and handles
user objects as well:>>> from plone.app.testing import TEST_USER_ID
>>> user = api.get_user(TEST_USER_ID)
>>> user
<MemberData at /plone/portal_memberdata/test_user_1_ used for /plone/acl_users>

>>> api.get_user(api.get_user(TEST_USER_ID))
<MemberData at /plone/portal_memberdata/test_user_1_ used for /plone/acl_users>Non-existing users are not found:>>> api.get_user("NonExistingUser")Getting User PropertiesUser properties, like the email or full name, are stored as user properties.
This means that they are not on the user object. This function retrieves these
properties for you:>>> properties = api.get_user_properties(TEST_USER_ID)
>>> sorted(properties.items())
[('description', ''), ('email', ''), ('error_log_update', 0.0), ('ext_editor', False), ...]

>>> sorted(api.get_user_properties(user).items())
[('description', ''), ('email', ''), ('error_log_update', 0.0), ('ext_editor', False), ...]An empty property dict is returned if no user could be found:>>> api.get_user_properties("NonExistingUser")
{}

>>> api.get_user_properties(None)
{}Getting Users by their Roles>>> from operator import methodcallerRoles in Bika LIMS are basically a name for one or more permissions. For
example, aLabManagerdescribes a role which is granted the most permissions.To see which users are granted a certain role, you can use this function:>>> labmanagers = api.get_users_by_roles(["LabManager"])
>>> sorted(labmanagers, key=methodcaller('getId'))
[<PloneUser 'test_labmanager'>, <PloneUser 'test_labmanager1'>, <PloneUser 'test-user'>]A single value can also be passed into this function:>>> sorted(api.get_users_by_roles("LabManager"), key=methodcaller('getId'))
[<PloneUser 'test_labmanager'>, <PloneUser 'test_labmanager1'>, <PloneUser 'test-user'>]Getting the Current UserGetting the current logged in user:>>> api.get_current_user()
<MemberData at /plone/portal_memberdata/test_user_1_ used for /plone/acl_users>Getting the Contact associated to a Plone userGetting a Plone user previously registered with no contact assigned:>>> user = api.get_user('test_labmanager1')
>>> contact = api.get_user_contact(user)
>>> contact is None
TrueAssign a new contact to this user:>>> labcontacts = bika_setup.bika_labcontacts
>>> labcontact = api.create(labcontacts, "LabContact", Firstname="Lab", Lastname="Manager")
>>> labcontact.setUser(user)
TrueAnd get the contact associated to the user:>>> api.get_user_contact(user)
<LabContact at /plone/bika_setup/bika_labcontacts/labcontact-1>As well as if we specify onlyLabContacttype:>>> api.get_user_contact(user, ['LabContact'])
<LabContact at /plone/bika_setup/bika_labcontacts/labcontact-1>But fails if we specify onlyContacttype:>>> nuser = api.get_user_contact(user, ['Contact'])
>>> nuser is None
TrueCreating a Cache KeyThis function creates a good cache key for a generic object or brain:>>> key1 = api.get_cache_key(client)
>>> key1
'Client-client-1-...'This can be also done for a catalog result brain:>>> portal_catalog = api.get_tool("portal_catalog")
>>> brains = portal_catalog({"portal_type": "Client", "UID": api.get_uid(client)})
>>> key2 = api.get_cache_key(brains[0])
>>> key2
'Client-client-1-...'The two keys should be equal:>>> key1 == key2
TrueThe key should change when the object get modified:>>> from zope.lifecycleevent import modified
>>> client.setClientID("TESTCLIENT")
>>> modified(client)
>>> portal.aq_parent._p_jar.sync()
>>> key3 = api.get_cache_key(client)
>>> key3 != key1
TrueImportantWorkflow changes do not change the modification date!
A custom event subscriber will update it therefore.A workflow transition should also change the cache key:>>> _ = api.do_transition_for(client, transition="deactivate")
>>> api.get_inactive_status(client)
'inactive'
>>> key4 = api.get_cache_key(client)
>>> key4 != key3
TrueCache Key decoratorThis decorator can be used forplone.memoizecache decorators in classes.
The decorator expects that the first argument is the class instance (self) and
the second argument a brain or object:>>> from plone.memoize.volatile import cache

>>> class BikaClass(object):
...     @cache(api.bika_cache_key_decorator)
...     def get_very_expensive_calculation(self, obj):
...         print "very expensive calculation"
...         return "calculation result"Calling the (expensive) method of the class does the calculation just once:>>> instance = BikaClass()
>>> instance.get_very_expensive_calculation(client)
very expensive calculation
'calculation result'
>>> instance.get_very_expensive_calculation(client)
'calculation result'The decorator can also handle brains:>>> instance = BikaClass()
>>> portal_catalog = api.get_tool("portal_catalog")
>>> brain = portal_catalog(portal_type="Client")[0]
>>> instance.get_very_expensive_calculation(brain)
very expensive calculation
'calculation result'
>>> instance.get_very_expensive_calculation(brain)
'calculation result'ID NormalizerNormalizes a string to be usable as a system ID:>>> api.normalize_id("My new ID")
'my-new-id'

>>> api.normalize_id("Really/Weird:Name;")
'really-weird-name'

>>> api.normalize_id(None)
Traceback (most recent call last):
[...]
SenaiteAPIError: Type of argument must be string, found '<type 'NoneType'>'File NormalizerNormalizes a string to be usable as a file name:>>> api.normalize_filename("My new ID")
'My new ID'

>>> api.normalize_filename("Really/Weird:Name;")
'Really-Weird-Name'

>>> api.normalize_filename(None)
Traceback (most recent call last):
[...]
SenaiteAPIError: Type of argument must be string, found '<type 'NoneType'>'Check if an UID is validChecks if an UID is a valid 23 alphanumeric uid:>>> api.is_uid("ajw2uw9")
False

>>> api.is_uid(None)
False

>>> api.is_uid("")
False

>>> api.is_uid("0")
False

>>> api.is_uid('0e1dfc3d10d747bf999948a071bc161e')
TrueChecks if an UID is a valid 23 alphanumeric uid and with a brain:>>> api.is_uid("ajw2uw9", validate=True)
False

>>> api.is_uid(None, validate=True)
False

>>> api.is_uid("", validate=True)
False

>>> api.is_uid("0", validate=True)
False

>>> api.is_uid('0e1dfc3d10d747bf999948a071bc161e', validate=True)
False

>>> asfolder = self.portal.bika_setup.bika_analysisservices
>>> serv = api.create(asfolder, "AnalysisService", title="AS test")
>>> serv.setKeyword("as_test")
>>> uid = serv.UID()
>>> api.is_uid(uid, validate=True)
TrueCheck if a Date is validDo some imports first:>>> from datetime import datetime
>>> from DateTime import DateTimeChecks if a DateTime is valid:>>> now = DateTime()
>>> api.is_date(now)
True

>>> now = datetime.now()
>>> api.is_date(now)
True

>>> now = DateTime(now)
>>> api.is_date(now)
True

>>> api.is_date(None)
False

>>> api.is_date('2018-04-23')
FalseTry conversions to DateTry to convert to DateTime:>>> now = DateTime()
>>> zpdt = api.to_date(now)
>>> zpdt.ISO8601() == now.ISO8601()
True

>>> now = datetime.now()
>>> zpdt = api.to_date(now)
>>> pydt = zpdt.asdatetime()Note that here, for the comparison between dates, we convert DateTime to python
datetime, cause DateTime.strftime() is broken for timezones (always looks at
system time zone, ignores the timezone and offset of the DateTime instance
itself):>>> pydt.strftime('%Y-%m-%dT%H:%M:%S') == now.strftime('%Y-%m-%dT%H:%M:%S')
TrueTry the same, but with utcnow() instead:>>> now = datetime.utcnow()
>>> zpdt = api.to_date(now)
>>> pydt = zpdt.asdatetime()
>>> pydt.strftime('%Y-%m-%dT%H:%M:%S') == now.strftime('%Y-%m-%dT%H:%M:%S')
TrueNow we convert just a string formatted date:>>> strd = "2018-12-01 17:50:34"
>>> zpdt = api.to_date(strd)
>>> zpdt.ISO8601()
'2018-12-01T17:50:34'Now we convert just a string formatted date, but with timezone:>>> strd = "2018-12-01 17:50:34 GMT+1"
>>> zpdt = api.to_date(strd)
>>> zpdt.ISO8601()
'2018-12-01T17:50:34+01:00'We also check a bad date here (note the month is 13):>>> strd = "2018-13-01 17:50:34"
>>> zpdt = api.to_date(strd)
>>> api.is_date(zpdt)
FalseAnd with European format:>>> strd = "01.12.2018 17:50:34"
>>> zpdt = api.to_date(strd)
>>> zpdt.ISO8601()
'2018-12-01T17:50:34'

>>> zpdt = api.to_date(None)
>>> zpdt is None
TrueUse a string formatted date as fallback:>>> strd = "2018-13-01 17:50:34"
>>> default_date = "2018-01-01 19:30:30"
>>> zpdt = api.to_date(strd, default_date)
>>> zpdt.ISO8601()
'2018-01-01T19:30:30'Use a DateTime object as fallback:>>> strd = "2018-13-01 17:50:34"
>>> default_date = "2018-01-01 19:30:30"
>>> default_date = api.to_date(default_date)
>>> zpdt = api.to_date(strd, default_date)
>>> zpdt.ISO8601() == default_date.ISO8601()
TrueUse a datetime object as fallback:>>> strd = "2018-13-01 17:50:34"
>>> default_date = datetime.now()
>>> zpdt = api.to_date(strd, default_date)
>>> dzpdt = api.to_date(default_date)
>>> zpdt.ISO8601() == dzpdt.ISO8601()
TrueUse a non-conversionable value as fallback:>>> strd = "2018-13-01 17:50:34"
>>> default_date = "something wrong here"
>>> zpdt = api.to_date(strd, default_date)
>>> zpdt is None
TrueCheck if floatable>>> api.is_floatable(None)
False

>>> api.is_floatable("")
False

>>> api.is_floatable("31")
True

>>> api.is_floatable("31.23")
True

>>> api.is_floatable("-13")
True

>>> api.is_floatable("12,35")
FalseConvert to a float number>>> api.to_float("2")
2.0

>>> api.to_float("2.234")
2.234With default fallback:>>> api.to_float(None, 2)
2.0

>>> api.to_float(None, "2")
2.0

>>> api.to_float("", 2)
2.0

>>> api.to_float("", "2")
2.0

>>> api.to_float(2.1, 2)
2.1

>>> api.to_float("2.1", 2)
2.1

>>> api.to_float("2.1", "2")
2.1API AnalysisThe api_analysis provides single functions for single purposes especifically
related with analyses.Running this test from the buildout directory:bin/test test_textual_doctests -t API_analysisTest SetupNeeded Imports:>>> import re
>>> from AccessControl.PermissionRole import rolesForPermissionOn
>>> from bika.lims import api
>>> from bika.lims.api.analysis import is_out_of_range
>>> from bika.lims.content.analysisrequest import AnalysisRequest
>>> from bika.lims.content.sample import Sample
>>> from bika.lims.content.samplepartition import SamplePartition
>>> from bika.lims.utils.analysisrequest import create_analysisrequest
>>> from bika.lims.utils.sample import create_sample
>>> from bika.lims.utils import tmpID
>>> from bika.lims.workflow import doActionFor
>>> from bika.lims.workflow import getCurrentState
>>> from bika.lims.workflow import getAllowedTransitions
>>> from DateTime import DateTime
>>> from plone.app.testing import TEST_USER_ID
>>> from plone.app.testing import TEST_USER_PASSWORD
>>> from plone.app.testing import setRolesFunctional Helpers:>>> def start_server():
...     from Testing.ZopeTestCase.utils import startZServer
...     ip, port = startZServer()
...     return "http://{}:{}/{}".format(ip, port, portal.id)Variables:>>> portal = self.portal
>>> request = self.request
>>> bikasetup = portal.bika_setupWe need to create some basic objects for the test:>>> setRoles(portal, TEST_USER_ID, ['LabManager',])
>>> date_now = DateTime().strftime("%Y-%m-%d")
>>> date_future = (DateTime() + 5).strftime("%Y-%m-%d")
>>> client = api.create(portal.clients, "Client", Name="Happy Hills", ClientID="HH", MemberDiscountApplies=True)
>>> contact = api.create(client, "Contact", Firstname="Rita", Lastname="Mohale")
>>> sampletype = api.create(bikasetup.bika_sampletypes, "SampleType", title="Water", Prefix="W")
>>> labcontact = api.create(bikasetup.bika_labcontacts, "LabContact", Firstname="Lab", Lastname="Manager")
>>> department = api.create(bikasetup.bika_departments, "Department", title="Chemistry", Manager=labcontact)
>>> category = api.create(bikasetup.bika_analysiscategories, "AnalysisCategory", title="Metals", Department=department)
>>> supplier = api.create(bikasetup.bika_suppliers, "Supplier", Name="Naralabs")
>>> Cu = api.create(bikasetup.bika_analysisservices, "AnalysisService", title="Copper", Keyword="Cu", Price="15", Category=category.UID(), DuplicateVariation="0.5")
>>> Fe = api.create(bikasetup.bika_analysisservices, "AnalysisService", title="Iron", Keyword="Fe", Price="10", Category=category.UID(), DuplicateVariation="0.5")
>>> Au = api.create(bikasetup.bika_analysisservices, "AnalysisService", title="Gold", Keyword="Au", Price="20", Category=category.UID(), DuplicateVariation="0.5")
>>> Mg = api.create(bikasetup.bika_analysisservices, "AnalysisService", title="Magnesium", Keyword="Mg", Price="20", Category=category.UID(), DuplicateVariation="0.5")
>>> service_uids = [api.get_uid(an) for an in [Cu, Fe, Au, Mg]]Create an Analysis Specification forWater:>>> sampletype_uid = api.get_uid(sampletype)
>>> rr1 = {"keyword": "Au", "min": "-5", "max":  "5", "warn_min": "-5.5", "warn_max": "5.5"}
>>> rr2 = {"keyword": "Cu", "min": "10", "max": "20", "warn_min":  "9.5", "warn_max": "20.5"}
>>> rr3 = {"keyword": "Fe", "min":  "0", "max": "10", "warn_min": "-0.5", "warn_max": "10.5"}
>>> rr4 = {"keyword": "Mg", "min": "10", "max": "10"}
>>> rr = [rr1, rr2, rr3, rr4]
>>> specification = api.create(bikasetup.bika_analysisspecs, "AnalysisSpec", title="Lab Water Spec", SampleType=sampletype_uid, ResultsRange=rr)
>>> spec_uid = api.get_uid(specification)Create a Reference Definition for blank:>>> blankdef = api.create(bikasetup.bika_referencedefinitions, "ReferenceDefinition", title="Blank definition", Blank=True)
>>> blank_refs = [{'uid': Au.UID(), 'result': '0', 'min': '0', 'max': '0'},]
>>> blankdef.setReferenceResults(blank_refs)And for control:>>> controldef = api.create(bikasetup.bika_referencedefinitions, "ReferenceDefinition", title="Control definition")
>>> control_refs = [{'uid': Au.UID(), 'result': '10', 'min': '9.99', 'max': '10.01'},
...                 {'uid': Cu.UID(), 'result': '-0.9','min': '-1.08', 'max': '-0.72'},]
>>> controldef.setReferenceResults(control_refs)

>>> blank = api.create(supplier, "ReferenceSample", title="Blank",
...                    ReferenceDefinition=blankdef,
...                    Blank=True, ExpiryDate=date_future,
...                    ReferenceResults=blank_refs)
>>> control = api.create(supplier, "ReferenceSample", title="Control",
...                      ReferenceDefinition=controldef,
...                      Blank=False, ExpiryDate=date_future,
...                      ReferenceResults=control_refs)Create an Analysis Request:>>> values = {
...     'Client': api.get_uid(client),
...     'Contact': api.get_uid(contact),
...     'DateSampled': date_now,
...     'SampleType': sampletype_uid,
...     'Specification': spec_uid,
...     'Priority': '1',
... }

>>> ar = create_analysisrequest(client, request, values, service_uids)
>>> success = doActionFor(ar, 'receive')Create a new Worksheet and add the analyses:>>> worksheet = api.create(portal.worksheets, "Worksheet")
>>> analyses = map(api.get_object, ar.getAnalyses())
>>> for analysis in analyses:
...     worksheet.addAnalysis(analysis)Add a duplicate forCu:>>> position = worksheet.get_slot_position(ar, 'a')
>>> duplicates = worksheet.addDuplicateAnalyses(position)
>>> duplicates.sort(key=lambda analysis: analysis.getKeyword(), reverse=False)Add a blank and a control:>>> blanks = worksheet.addReferenceAnalyses(blank, service_uids)
>>> blanks.sort(key=lambda analysis: analysis.getKeyword(), reverse=False)
>>> controls = worksheet.addReferenceAnalyses(control, service_uids)
>>> controls.sort(key=lambda analysis: analysis.getKeyword(), reverse=False)Check if results are out of rangeFirst, get the analyses from slot 1 and sort them asc:>>> analyses = worksheet.get_analyses_at(1)
>>> analyses.sort(key=lambda analysis: analysis.getKeyword(), reverse=False)Set results for analysisAu(min: -5, max: 5, warn_min: -5.5, warn_max: 5.5):>>> au_analysis = analyses[0]
>>> au_analysis.setResult(2)
>>> is_out_of_range(au_analysis)
(False, False)

>>> au_analysis.setResult(-2)
>>> is_out_of_range(au_analysis)
(False, False)

>>> au_analysis.setResult(-5)
>>> is_out_of_range(au_analysis)
(False, False)

>>> au_analysis.setResult(5)
>>> is_out_of_range(au_analysis)
(False, False)

>>> au_analysis.setResult(10)
>>> is_out_of_range(au_analysis)
(True, True)

>>> au_analysis.setResult(-10)
>>> is_out_of_range(au_analysis)
(True, True)Results in shoulders?:>>> au_analysis.setResult(-5.2)
>>> is_out_of_range(au_analysis)
(True, False)

>>> au_analysis.setResult(-5.5)
>>> is_out_of_range(au_analysis)
(True, False)

>>> au_analysis.setResult(-5.6)
>>> is_out_of_range(au_analysis)
(True, True)

>>> au_analysis.setResult(5.2)
>>> is_out_of_range(au_analysis)
(True, False)

>>> au_analysis.setResult(5.5)
>>> is_out_of_range(au_analysis)
(True, False)

>>> au_analysis.setResult(5.6)
>>> is_out_of_range(au_analysis)
(True, True)Check if results for duplicates are out of rangeGet the first duplicate analysis that comes fromAu:>>> duplicate = duplicates[0]A Duplicate will be considered out of range if its result does not match with
the result set to the analysis that was duplicated from, with the Duplicate
Variation in % as the margin error. The Duplicate Variation assigned in the
Analysis ServiceAuis 0.5%:>>> dup_variation = au_analysis.getDuplicateVariation()
>>> dup_variation = api.to_float(dup_variation)
>>> dup_variation
0.5Set an in-range result (between -5 and 5) for routine analysis and check all
variants on it’s duplicate. Given that the duplicate variation is 0.5, the
valid range for the duplicate must beAu +-0.5%:>>> result = 2.0
>>> au_analysis.setResult(result)
>>> is_out_of_range(au_analysis)
(False, False)

>>> duplicate.setResult(result)
>>> is_out_of_range(duplicate)
(False, False)

>>> dup_min_range = result - (result*(dup_variation/100))
>>> duplicate.setResult(dup_min_range)
>>> is_out_of_range(duplicate)
(False, False)

>>> duplicate.setResult(dup_min_range - 0.5)
>>> is_out_of_range(duplicate)
(True, True)

>>> dup_max_range = result + (result*(dup_variation/100))
>>> duplicate.setResult(dup_max_range)
>>> is_out_of_range(duplicate)
(False, False)

>>> duplicate.setResult(dup_max_range + 0.5)
>>> is_out_of_range(duplicate)
(True, True)Set an out-of-range result, but within shoulders, for routine analysis and check
all variants on it’s duplicate. Given that the duplicate variation is 0.5, the
valid range for the duplicate must beAu +-0.5%:>>> result = 5.5
>>> au_analysis.setResult(result)
>>> is_out_of_range(au_analysis)
(True, False)

>>> duplicate.setResult(result)
>>> is_out_of_range(duplicate)
(False, False)

>>> dup_min_range = result - (result*(dup_variation/100))
>>> duplicate.setResult(dup_min_range)
>>> is_out_of_range(duplicate)
(False, False)

>>> duplicate.setResult(dup_min_range - 0.5)
>>> is_out_of_range(duplicate)
(True, True)

>>> dup_max_range = result + (result*(dup_variation/100))
>>> duplicate.setResult(dup_max_range)
>>> is_out_of_range(duplicate)
(False, False)

>>> duplicate.setResult(dup_max_range + 0.5)
>>> is_out_of_range(duplicate)
(True, True)Set an out-of-range and out-of-shoulders result, for routine analysis and check
all variants on it’s duplicate. Given that the duplicate variation is 0.5, the
valid range for the duplicate must beAu +-0.5%:>>> result = -7.0
>>> au_analysis.setResult(result)
>>> is_out_of_range(au_analysis)
(True, True)

>>> duplicate.setResult(result)
>>> is_out_of_range(duplicate)
(False, False)

>>> dup_min_range = result - (abs(result)*(dup_variation/100))
>>> duplicate.setResult(dup_min_range)
>>> is_out_of_range(duplicate)
(False, False)

>>> duplicate.setResult(dup_min_range - 0.5)
>>> is_out_of_range(duplicate)
(True, True)

>>> dup_max_range = result + (abs(result)*(dup_variation/100))
>>> duplicate.setResult(dup_max_range)
>>> is_out_of_range(duplicate)
(False, False)

>>> duplicate.setResult(dup_max_range + 0.5)
>>> is_out_of_range(duplicate)
(True, True)Check if results for Reference Analyses (blanks + controls) are out of rangeReference Analyses (controls and blanks) do not use the result ranges defined in
the specifications, rather they use the result range defined in the Reference
Sample they have been generated from. In turn, the result ranges defined in
Reference Samples can be set manually or acquired from the Reference Definition
they might be associated with. Another difference from routine analyses is that
reference analyses don’t expect a valid range, rather a discrete value, so
shoulders are built based on % error.Blank AnalysesThe first blank analysis corresponds toAu:>>> au_blank = blanks[0]ForAublank, as per the reference definition used above, the expected result
is 0 +/- 0.1%. Since the expected result is 0, no shoulders will be considered
regardless of the % of error. Thus, result will always be “out-of-shoulders”
when out of range:>>> au_blank.setResult(0.0)
>>> is_out_of_range(au_blank)
(False, False)

>>> au_blank.setResult("0")
>>> is_out_of_range(au_blank)
(False, False)

>>> au_blank.setResult(0.0001)
>>> is_out_of_range(au_blank)
(True, True)

>>> au_blank.setResult("0.0001")
>>> is_out_of_range(au_blank)
(True, True)

>>> au_blank.setResult(-0.0001)
>>> is_out_of_range(au_blank)
(True, True)

>>> au_blank.setResult("-0.0001")
>>> is_out_of_range(au_blank)
(True, True)Control AnalysesThe first control analysis corresponds toAu:>>> au_control = controls[0]ForAucontrol, as per the reference definition used above, the expected
result is 10 +/- 0.1% = 10 +/- 0.01First, check for in-range values:>>> au_control.setResult(10)
>>> is_out_of_range(au_control)
(False, False)

>>> au_control.setResult(10.0)
>>> is_out_of_range(au_control)
(False, False)

>>> au_control.setResult("10")
>>> is_out_of_range(au_control)
(False, False)

>>> au_control.setResult("10.0")
>>> is_out_of_range(au_control)
(False, False)

>>> au_control.setResult(9.995)
>>> is_out_of_range(au_control)
(False, False)

>>> au_control.setResult("9.995")
>>> is_out_of_range(au_control)
(False, False)

>>> au_control.setResult(10.005)
>>> is_out_of_range(au_control)
(False, False)

>>> au_control.setResult("10.005")
>>> is_out_of_range(au_control)
(False, False)

>>> au_control.setResult(9.99)
>>> is_out_of_range(au_control)
(False, False)

>>> au_control.setResult("9.99")
>>> is_out_of_range(au_control)
(False, False)

>>> au_control.setResult(10.01)
>>> is_out_of_range(au_control)
(False, False)

>>> au_control.setResult("10.01")
>>> is_out_of_range(au_control)
(False, False)Now, check for out-of-range results:>>> au_control.setResult(9.98)
>>> is_out_of_range(au_control)
(True, True)

>>> au_control.setResult("9.98")
>>> is_out_of_range(au_control)
(True, True)

>>> au_control.setResult(10.011)
>>> is_out_of_range(au_control)
(True, True)

>>> au_control.setResult("10.011")
>>> is_out_of_range(au_control)
(True, True)And do the same with the control forCuthat expects -0.9 +/- 20%:>>> cu_control = controls[1]First, check for in-range values:>>> cu_control.setResult(-0.9)
>>> is_out_of_range(cu_control)
(False, False)

>>> cu_control.setResult("-0.9")
>>> is_out_of_range(cu_control)
(False, False)

>>> cu_control.setResult(-1.08)
>>> is_out_of_range(cu_control)
(False, False)

>>> cu_control.setResult("-1.08")
>>> is_out_of_range(cu_control)
(False, False)

>>> cu_control.setResult(-1.07)
>>> is_out_of_range(cu_control)
(False, False)

>>> cu_control.setResult("-1.07")
>>> is_out_of_range(cu_control)
(False, False)

>>> cu_control.setResult(-0.72)
>>> is_out_of_range(cu_control)
(False, False)

>>> cu_control.setResult("-0.72")
>>> is_out_of_range(cu_control)
(False, False)

>>> cu_control.setResult(-0.73)
>>> is_out_of_range(cu_control)
(False, False)

>>> cu_control.setResult("-0.73")
>>> is_out_of_range(cu_control)
(False, False)Now, check for out-of-range results:>>> cu_control.setResult(0)
>>> is_out_of_range(cu_control)
(True, True)

>>> cu_control.setResult("0")
>>> is_out_of_range(cu_control)
(True, True)

>>> cu_control.setResult(-0.71)
>>> is_out_of_range(cu_control)
(True, True)

>>> cu_control.setResult("-0.71")
>>> is_out_of_range(cu_control)
(True, True)

>>> cu_control.setResult(-1.09)
>>> is_out_of_range(cu_control)
(True, True)

>>> cu_control.setResult("-1.09")
>>> is_out_of_range(cu_control)
(True, True)Changelog1.2.3 (2018-06-23)More PyPI fixtures1.2.2 (2018-06-23)PyPI Documentation Page fixtures1.2.1 (2018-06-23)Better Documentation Page for PyPIFixed formatting of Doctests1.2.0 (2018-06-23)AddedAddedis_uidfunctionRemovedChangedAdded SENAITE CORE API functionsFixedFixed TestsSecurity1.1.0 (2018-01-03)AddedRemovedChangedLicense changed to GPLv2Integration to SENAITE COREFixedFixed TestsSecurity1.0.2 (2017-11-24)#397(bika.lims) Fix Issue-396: AttributeError: uid_catalog on AR publication1.0.1 (2017-09-30)Fixed broken release (missing MANIFEST.in)1.0.0 (2017-09-30)First release