From 590f0da5d3b751f7d94b5b9f4af4f523faeedb79 Mon Sep 17 00:00:00 2001
From: Matthias Tafelmeier <matthias.tafelmeier@gmx.net>
Date: Mon, 20 Nov 2023 13:46:33 +0100
Subject: [PATCH] have iter conditional to be in optimization dag

Reducing effectuation dag to endless loop only to be stopped once dag is
to be ended and cleaned up.
---
 breeder/linux_network_stack/effectuation.py | 30 +----------------
 breeder/linux_network_stack/optimization.py | 36 ++++++++++++++++++++-
 2 files changed, 36 insertions(+), 30 deletions(-)

diff --git a/breeder/linux_network_stack/effectuation.py b/breeder/linux_network_stack/effectuation.py
index be46b878..7cd2a5a3 100644
--- a/breeder/linux_network_stack/effectuation.py
+++ b/breeder/linux_network_stack/effectuation.py
@@ -106,41 +106,13 @@ def run_reconnaissance():
         )
 {% endraw %}
 
-        @dag.task(task_id="run_iter_count_step")
-        def run_iter_count(ti=None):
-            last_iteration =  ti.xcom_pull(task_ids="run_iter_count_step")
-            current_iteration = last_iteration + 1 if last_iteration else 0
-            return current_iteration
-
-        run_iter_count_step = run_iter_count()
-
-        @task.branch(task_id="stopping_decision_step")
-        def stopping_decision(max_iterations, ti=None):
-            task_logger.debug("Entering")
-            current_iteration = ti.xcom_pull(task_ids="run_iter_count_step")
-            def is_stop_criteria_reached(iteration):
-                if iteration >= max_iterations:
-                    return True
-                else:
-                    return False
-
-            task_logger.debug("Done")
-            if is_stop_criteria_reached(current_iteration):
-                return "stop_step"
-            else:
-                return "continue_step"
-
-        stopping_conditional_step = stopping_decision(config.get('run').get('iterations').get('max'))
-
         continue_step = TriggerDagRunOperator(
                 task_id='continue_step',
                 trigger_dag_id=interaction_dag.dag_id,
                 dag=interaction_dag
                 )
 
-        stop_step = EmptyOperator(task_id="stop_task", dag=interaction_dag)
-
-        pull_step >> effectuation_step >> recon_step >> push_step >> run_iter_count_step >> stopping_conditional_step >> [continue_step, stop_step]
+        pull_step >> effectuation_step >> recon_step >> push_step >> continue_step
 
     return dag
 
diff --git a/breeder/linux_network_stack/optimization.py b/breeder/linux_network_stack/optimization.py
index 1b81bae4..2ae865d2 100644
--- a/breeder/linux_network_stack/optimization.py
+++ b/breeder/linux_network_stack/optimization.py
@@ -47,6 +47,40 @@ def run_optimization():
 
         optimization_step = run_optimization()
 
-        noop >> optimization_step
+        @dag.task(task_id="run_iter_count_step")
+        def run_iter_count(ti=None):
+            last_iteration =  ti.xcom_pull(task_ids="run_iter_count_step")
+            current_iteration = last_iteration + 1 if last_iteration else 0
+            return current_iteration
+
+        run_iter_count_step = run_iter_count()
+
+        @task.branch(task_id="stopping_decision_step")
+        def stopping_decision(max_iterations, ti=None):
+            task_logger.debug("Entering")
+            current_iteration = ti.xcom_pull(task_ids="run_iter_count_step")
+            def is_stop_criteria_reached(iteration):
+                if iteration >= max_iterations:
+                    return True
+                else:
+                    return False
+
+            task_logger.debug("Done")
+            if is_stop_criteria_reached(current_iteration):
+                return "stop_step"
+            else:
+                return "continue_step"
+
+        continue_step = TriggerDagRunOperator(
+                task_id='continue_step',
+                trigger_dag_id=optimization_dag.dag_id,
+                dag=optimization_dag
+                )
+
+        stopping_conditional_step = stopping_decision(config.get('run').get('iterations').get('max'))
+
+        stop_step = EmptyOperator(task_id="stop_task", dag=optimization_dag)
+
+        optimization_step >> run_iter_count_step  >> stopping_conditional_step >> [continue_step, stop_step]
 
     return dag