Add sqlite config

Add sqlite to report_score

experimentation/.myconfig.dist

@@ -2,4 +2,5 @@ host=<server>
 port=tunnel
 user=stree
 password=<password>
-database=stree_experiments
+database=stree_experiments
+sqlite=None

experimentation/Database.py

@@ -42,13 +42,21 @@ class MySQL:
         if self._tunnel:
             self._server.start()
             self._config_db["port"] = self._server.local_bind_port
-        self._database = mysql.connector.connect(**self._config_db)
+        if self._config_db["sqlite"] == "None":
+            del self._config_db["sqlite"]
+            self._config_db["buffered"] = True
+            self._database = mysql.connector.connect(**self._config_db)
+        else:
+            self._database = sqlite3.connect(self._config_db["sqlite"])
+            # return dict as a result of select
+            self._database.row_factory = sqlite3.Row
+
         return self._database
 
     def find_best(
         self, dataset, classifier="any", experiment="any", time_info=False
     ):
-        cursor = self._database.cursor(buffered=True)
+        cursor = self._database.cursor()
         date_from = "2021-01-20"
         # date_to = "2021-04-07"
         command = (

experimentation/mysql/.myconfig

@@ -0,0 +1,6 @@
+host=127.0.0.1
+port=3306
+user=stree
+password=xtree
+database=stree
+sqlite=None

experimentation/mysql/.tunnel

@@ -0,0 +1,5 @@
+ssh_address_or_host=('atenea.rmontanana.es', 31427)
+ssh_username=rmontanana
+ssh_private_key=/home/rmontanana/.ssh/id_rsa
+remote_bind_address=('127.0.0.1', 3306)
+enabled=1

experimentation/sqlite/.myconfig

@@ -0,0 +1,6 @@
+host=127.0.0.1
+port=3306
+user=stree
+password=xtree
+database=stree
+sqlite=./data/stree.sqlite

experimentation/sqlite/.tunnel

@@ -0,0 +1,5 @@
+ssh_address_or_host=('atenea.rmontanana.es', 31427)
+ssh_username=rmontanana
+ssh_private_key=/home/rmontanana/.ssh/id_rsa
+remote_bind_address=('127.0.0.1', 3306)
+enabled=0

report_score.py

@@ -126,11 +126,13 @@ def process_dataset(dataset, verbose, model, params):
         record = dbh.find_best(dataset, model, "gridsearch")
         hyperparameters = json.loads(record[8] if record[8] != "" else "{}")
         hyperparameters.pop("random_state", None)
+        print("*" * 100)
     for random_state in random_seeds:
         random.seed(random_state)
         np.random.seed(random_state)
         kfold = KFold(shuffle=True, random_state=random_state, n_splits=5)
         clf = get_classifier(model, random_state, hyperparameters)
+        print(hyperparameters)
         res = cross_validate(clf, X, y, cv=kfold, return_estimator=True)
         scores.append(res["test_score"])
         times.append(res["fit_time"])
@@ -361,7 +363,7 @@ standardize = False
     excel,
     discretize,
 ) = parse_arguments()
-# parameters = '{"splitter":"cfs","max_features":"auto"}'
+# parameters = '{"kernel":"rbf","max_features":"auto"}'
 dbh = MySQL()
 if sql:
     sql_output = open(f"{model}.sql", "w")