breeder - correct archive db query templating

Let's not use sqlalchemy to generate the archive db interacting sql
queries because that has led to complications. bindparams was not
working as expect for String/Text type.

breeder/linux_network_stack/effectuation.py

@@ -72,14 +72,9 @@ def run_push_optimization(ti=None):
             metric_data = dict(metric=metric_value)
             msg = asyncio.run(send_msg_via_nats(subject=f'recon_{identifier}', data_dict=metric_data))
 
+            breeder_table_name = config.get("name")
 
-            breeder_table_name = f"from_dag_name" # TBD local dag id based name
-
-            query  = text("INSERT INTO :table_name VALUES (:setting_id, :setting_full, :setting_result )")
-            query = query.bindparams(bindparam("table_name", breeder_table_name, type_=String),
-                                     bindparam("setting_id", setting_id, type_=String),
-                                     bindparam("setting_full", settings_full, type_=String),
-                                     bindparam("setting_result", metric_data, type_=String))
+            query = f"INSERT INTO {breeder_table_name} VALUES ({setting_id}, {setting_full}, {setting_result});"
 
             archive_db_engine.execute(query)
 

breeder/linux_network_stack/objective.py

@@ -1,6 +1,6 @@
 
 
-def objective(trial, identifier, archive_db_url):
+def objective(trial, identifier, archive_db_url, breeder_name):
 
 ###--- definition coroutines ---###
 ### We have to keep to coroutines in the objective function,
@@ -33,11 +33,8 @@ def objective(trial, identifier, archive_db_url):
     is_setting_explored = False
     setting_id = hashlib.sha256(str.encode(settings_full)).hexdigest()[0:6]
 
-    breeder_table_name = f"from_breeder_name" # TBD global knowledge db table nam
-    query = text("SELECT * FROM :table_name WHERE :table_name.setting_id == :setting_id")
-
-    query = query.bindparams(bindparam("table_name", breeder_table_name, type_=String),
-                             bindparam("setting_id", setting_id, type_=String))
+    breeder_table_name = f"{breeder_name}"
+    query = f"SELECT * FROM {breeder_table_name} WHERE {breeder_table_name}.setting_id = '{setting_id}';"
 
     archive_db_data = archive_db_engine.execute(query).fetchall()
 

breeder/linux_network_stack/optimization.py

@@ -37,7 +37,7 @@ def run_optimization():
                 # Create a study using Dask-compatible storage
                 storage = DaskStorage(InMemoryStorage())
                 study = optuna.create_study(directions=__directions, storage=storage)
-                objective_wrapped = lambda trial: objective(trial,identifier, archive_db_url)
+                objective_wrapped = lambda trial: objective(trial,identifier, archive_db_url, config.get('name'))
                 # Optimize in parallel on your Dask cluster
                 futures = [
                     client.submit(study.optimize, objective_wrapped, n_trials=10, pure=False)