TMSS-2829: initial creation of copy subtask. todo: copy task settings, manage output if needed

SAS/TMSS/backend/src/tmss/tmssapp/subtasks.py

@@ -88,6 +88,7 @@ def create_or_update_subtasks_from_task_blueprint(task_blueprint: TaskBlueprint)
                                                      create_qaplots_subtask_from_task_blueprint],
                               'preprocessing pipeline': [create_preprocessing_subtask_from_task_blueprint],
                               'pulsar pipeline': [create_pulsar_pipeline_subtask_from_task_blueprint],
+                              'copy pipeline': [create_copy_pipeline_subtask_from_task_blueprint],
                               'ingest': [create_ingest_subtask_from_task_blueprint],
                               'cleanup': [create_cleanup_subtask_from_task_blueprint]}
         generators_mapping['calibrator observation'] = generators_mapping['target observation']
@@ -989,6 +990,50 @@ def create_cleanup_subtask_from_task_blueprint(task_blueprint: TaskBlueprint) ->
     return subtask
 
 
+def create_copy_pipeline_subtask_from_task_blueprint(task_blueprint: TaskBlueprint) -> Subtask:
+    # step 0: check pre-requisites
+    check_prerequities_for_subtask_creation(task_blueprint)
+
+    # step 1: create subtask in defining state, with filled-in subtask_template
+    copy_subtask_template = SubtaskTemplate.get_version_or_latest(name="copy pipeline")
+    copy_subtask_spec = copy_subtask_template.get_default_json_document_for_schema()
+    # copy_subtask_spec['']
+
+    copy_subtask_data = { "scheduled_start_time": None,
+                          "scheduled_stop_time": None,
+                          "state": SubtaskState.objects.get(value=SubtaskState.Choices.DEFINING.value),
+                          "task_blueprint": task_blueprint,
+                          "specifications_template": copy_subtask_template,
+                          "specifications_doc": copy_subtask_spec,
+                          "primary": True } #,
+                         #"cluster": observation_subtask.cluster}
+    copy_subtask = Subtask.objects.create(**copy_subtask_data)
+
+    # step 2: create and link subtask input/output
+    selection_template = TaskRelationSelectionTemplate.get_version_or_latest(name="all")
+    selection_doc = selection_template.get_default_json_document_for_schema()
+
+    # for obs_out in observation_subtask.outputs.filter(output_role__role__value=Role.Choices.CORRELATOR.value).all():
+    #     qafile_subtask_input = SubtaskInput.objects.create(subtask=qafile_subtask,
+    #                                                        producer=obs_out,  # TODO: determine proper producer based on spec in task_relation_blueprint
+    #                                                        input_role=None,   # TODO: determine proper role based on spec in task_relation_blueprint
+    #                                                        selection_doc=selection_doc,
+    #                                                        selection_template=selection_template)
+    #
+    # # create an internal SubtaskOutput (output_role=None), because we do not expose qa data yet at task level
+    # qafile_subtask_output = SubtaskOutput.objects.create(subtask=qafile_subtask, output_role=None, filesystem=_output_filesystem(qafile_subtask))
+
+    # step 3: set state to DEFINED
+    copy_subtask.state = SubtaskState.objects.get(value=SubtaskState.Choices.DEFINED.value)
+    copy_subtask.save()
+
+    # done, now return the subtask, and allow the system to wait for the predecessors to be finished before we schedule this copy_subtask
+    return copy_subtask
+
+
+
+
+
 # ==== various schedule* methods to schedule a Subtasks (if possible) ====
 
 # LOFAR needs to have a gap in between observations to (re)initialize hardware.