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In addition to the Python functions described in Functions, Exceptions, Types, and Constants, the following functions are available for Unit Tests.
Python Module and use in the unit test.
does not include any native assert functionality, this functionality can be found in the common python libraries. Add the...
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def addFinalizer(func, *args, **kwargs) |
Parameter | Description |
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func | A |
function | |
*args | Positional |
arguments |
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be |
passed |
to |
the |
function | |
**kwargs | Keyword |
arguments |
to |
be |
passed |
to |
the |
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Returns | An |
object |
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a |
remove() |
method |
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Example - addFinalizer
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A Python context manager that defines an extra finalization scope. There are two pre-defined finalization scopes; one on the module level and one for each test function. These two scopes should be enough for normal use.
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Example - finalizers
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class SkipException(message=None) |
Parameter | Type |
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message | str |
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title | Example - SkipException
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def logSearch(fromDate=None, toDate=None, severities=None, areas=None, wfName=None, wfGroupName=None, agentName=None, userName=None, message=None) |
Parameter | Type |
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fromDate | drdate |
toDate | drdate |
severities | list[str] |
areas | list[str] |
wfName | str |
wfGroupName | str |
agentName | str |
userName | str |
message | str |
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Example - logSearch
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def logRemove(id) |
Parameter | Type |
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id | str |
Workflow functions
These functions are event driven, meaning that an event is fired when the function is called. This means that if you use wfStart and immediately call wfIsRunning after it might return false as the workflow has yet to start. It might be necessary to loop over some of these functions while waiting for the status to changed.
wfAdd
Adds a new workflow to an existing workflow template.
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def wfAdd(wfName, parameters=None) |
Parameter | Type |
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wfName | str |
parameters | dict[str, |
any] |
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Example - wfAdd
or
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wfDelete
Deletes a workflow.
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def wfDelete(wfName) |
Parameter | Type |
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wfName | str |
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Example - wfDelete
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wfExists
Returns True if the workflow exists.
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def wfExists(wfName) |
Parameter | Type |
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wfName | str |
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Example - wfExists
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wfStart
Starts the workflow. If successful, the workflow has been started but may not yet be running.
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def wfStart(wfName, ec=None) |
Parameter | Type |
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wfName | str |
ec | str |
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Example - wfStart
or
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wfSetDebugMode
Sets the workflow debug mode.
Debug mode can be set before starting the workflow or after it has become running.
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def wfSetDebugMode(wfName, on) |
Parameter | Type |
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wfName | str |
on | bool |
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Example - wfSetDebugMode
or
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wfIsCompleted
Returns True if the workflow completed.
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def wfIsCompleted(wfName) |
Parameter | Type |
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wfName | str |
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Example - wfIsCompleted
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wfIsRunning
Returns True if the workflow is running.
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def wfIsRunning(wfName) |
Parameter | Type |
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wfName | str |
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Example - wfIsRunning
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wfIsAborted
Returns True if the workflow aborted.
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def wfIsAborted(wfName) |
Parameter | Type |
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wfName | str |
wfAbortMessage
Returns the workflow abort message, if any.
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def wfAbortMessage(wfName) |
Parameter | Type |
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wfName | str |
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Example - wfAbortMessage
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Event functions
Below is a general example for all event functions.
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For information on how to format the filter see: Event Types(3.0).
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Example - Event functions
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eventBufferCreate
Creates an event buffer where events matching filter are stored in memory for later inspection.
Returns the event buffer to be used in calls to other event buffer functions.
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def eventBufferCreate(filter=None, ttl=None, maxSize=None) |
Parameter | Type |
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filter | dict[str, |
any] | |
ttl | float |
maxSize | int |
eventBufferDestroy
Destroys the event buffer and releases any resources associated with it.
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def eventBufferDestroy(buffer) |
Parameter | Type |
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buffer | object |
eventBufferSearch
Searches for events in the event buffer matching filter.
Returns an iterator with all currently matching events, with most recent event first.
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def eventBufferSearch(buffer, filter=None) |
Parameter | Type |
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buffer | object |
filter | dict[str, |
any] |