Python InstructorTask.create_output_for_failure方法代码示例

# 需要导入模块: from lms.djangoapps.instructor_task.models import InstructorTask [as 别名]
# 或者: from lms.djangoapps.instructor_task.models.InstructorTask import create_output_for_failure [as 别名]
    def on_failure(self, exc, task_id, args, kwargs, einfo):
        """
        Update InstructorTask object corresponding to this task with info about failure.

        Fetches and updates exception and traceback information on failure.

        If an exception is raised internal to the task, it is caught by celery and provided here.
        The information is recorded in the InstructorTask object as a JSON-serialized dict
        stored in the task_output column.  It contains the following keys:

               'exception':  type of exception object
               'message': error message from exception object
               'traceback': traceback information (truncated if necessary)

        Note that there is no way to record progress made within the task (e.g. attempted,
        succeeded, etc.) when such failures occur.
        """
        TASK_LOG.debug(u'Task %s: failure returned', task_id)
        entry_id = args[0]
        try:
            entry = InstructorTask.objects.get(pk=entry_id)
        except InstructorTask.DoesNotExist:
            # if the InstructorTask object does not exist, then there's no point
            # trying to update it.
            TASK_LOG.error(u"Task (%s) has no InstructorTask object for id %s", task_id, entry_id)
        else:
            TASK_LOG.warning(u"Task (%s) failed", task_id, exc_info=True)
            entry.task_output = InstructorTask.create_output_for_failure(einfo.exception, einfo.traceback)
            entry.task_state = FAILURE
            entry.save_now()

# 需要导入模块: from lms.djangoapps.instructor_task.models import InstructorTask [as 别名]
# 或者: from lms.djangoapps.instructor_task.models.InstructorTask import create_output_for_failure [as 别名]
def _update_instructor_task(instructor_task, task_result):
    """
    Updates and possibly saves a InstructorTask entry based on a task Result.

    Used when updated status is requested.

    The `instructor_task` that is passed in is updated in-place, but
    is usually not saved.  In general, tasks that have finished (either with
    success or failure) should have their entries updated by the task itself,
    so are not updated here.  Tasks that are still running are not updated
    and saved while they run.  The one exception to the no-save rule are tasks that
    are in a "revoked" state.  This may mean that the task never had the
    opportunity to update the InstructorTask entry.

    Tasks that are in progress and have subtasks doing the processing do not look
    to the task's AsyncResult object.  When subtasks are running, the
    InstructorTask object itself is updated with the subtasks' progress,
    not any AsyncResult object.  In this case, the InstructorTask is
    not updated at all.

    Calculates json to store in "task_output" field of the `instructor_task`,
    as well as updating the task_state.

    For a successful task, the json contains the output of the task result.
    For a failed task, the json contains "exception", "message", and "traceback"
    keys.   A revoked task just has a "message" stating it was revoked.
    """
    # Pull values out of the result object as close to each other as possible.
    # If we wait and check the values later, the values for the state and result
    # are more likely to have changed.  Pull the state out first, and
    # then code assuming that the result may not exactly match the state.
    task_id = task_result.task_id
    result_state = task_result.state
    returned_result = task_result.result
    result_traceback = task_result.traceback

    # Assume we don't always save the InstructorTask entry if we don't have to,
    # but that in most cases we will update the InstructorTask in-place with its
    # current progress.
    entry_needs_updating = True
    entry_needs_saving = False
    task_output = None

    if instructor_task.task_state == PROGRESS and len(instructor_task.subtasks) > 0:
        # This happens when running subtasks:  the result object is marked with SUCCESS,
        # meaning that the subtasks have successfully been defined.  However, the InstructorTask
        # will be marked as in PROGRESS, until the last subtask completes and marks it as SUCCESS.
        # We want to ignore the parent SUCCESS if subtasks are still running, and just trust the
        # contents of the InstructorTask.
        entry_needs_updating = False
    elif result_state in [PROGRESS, SUCCESS]:
        # construct a status message directly from the task result's result:
        # it needs to go back with the entry passed in.
        log.info("background task (%s), state %s:  result: %s", task_id, result_state, returned_result)
        task_output = InstructorTask.create_output_for_success(returned_result)
    elif result_state == FAILURE:
        # on failure, the result's result contains the exception that caused the failure
        exception = returned_result
        traceback = result_traceback if result_traceback is not None else ''
        log.warning("background task (%s) failed: %s %s", task_id, returned_result, traceback)
        task_output = InstructorTask.create_output_for_failure(exception, result_traceback)
    elif result_state == REVOKED:
        # on revocation, the result's result doesn't contain anything
        # but we cannot rely on the worker thread to set this status,
        # so we set it here.
        entry_needs_saving = True
        log.warning("background task (%s) revoked.", task_id)
        task_output = InstructorTask.create_output_for_revoked()

    # save progress and state into the entry, even if it's not being saved:
    # when celery is run in "ALWAYS_EAGER" mode, progress needs to go back
    # with the entry passed in.
    if entry_needs_updating:
        instructor_task.task_state = result_state
        if task_output is not None:
            instructor_task.task_output = task_output

        if entry_needs_saving:
            instructor_task.save()