diff --git a/.gitignore b/.gitignore
index 3545ad1..d823241 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,2 +1,3 @@
 .env
-*.pkl
\ No newline at end of file
+*.pkl
+__pycache__
\ No newline at end of file
diff --git a/module/query.py b/module/query.py
new file mode 100644
index 0000000..15a81bf
--- /dev/null
+++ b/module/query.py
@@ -0,0 +1,61 @@
+# INSERT
+INSERT_REG_MODEL = """
+            INSERT INTO reg_model (
+                model_name,
+                path
+            ) VALUES(
+                {},
+                {}
+            )
+        """
+
+INSERT_REG_MODEL_METADATA = """
+                INSERT INTO reg_model_metadata (
+                    experiment_name,
+                    reg_model_name,
+                    experimenter,
+                    version,
+                    train_mae,
+                    val_mae,
+                    train_mse,
+                    val_mse
+                    ) VALUES (
+                        {},
+                        {},
+                        {},
+                        {},
+                        {},
+                        {},
+                        {},
+                        {}
+                    )
+            """
+
+# UPDATE
+UPDATE_REG_MODEL_METADATA = """
+                    UPDATE reg_model_metadata
+                    SET 
+                        train_mae = {},
+                        val_mae = {},
+                        train_mse = {},
+                        val_mse = {}
+                    WHERE experiment_name = {}
+                """
+
+# pd READ_SQL
+ALL_INSURANCE = """
+            SELECT *
+            FROM insurance
+        """
+
+VAL_MAE = """
+        SELECT val_mae
+        FROM reg_model_metadata
+        WHERE reg_model_name = %s
+    """
+
+MODEL = """
+        SELECT *
+        FROM reg_model
+        WHERE model_name = %s
+    """
diff --git a/module/trial.py b/module/trial.py
index 43ec239..6b5919b 100644
--- a/module/trial.py
+++ b/module/trial.py
@@ -12,6 +12,8 @@
 from sqlalchemy.engine import create_engine
 from xgboost.sklearn import XGBRegressor
 
+from query import *
+
 load_dotenv(verbose=True)
 
 
@@ -106,65 +108,37 @@ def main(params, df, engine, experiment_info, connection):
     tr_mse_mean = np.mean(tr_mse)
     tr_mae_mean = np.mean(tr_mae)
 
-    best_model = pd.read_sql(f"""
-                    SELECT *
-                    FROM reg_model
-                    WHERE model_name = {model_name}
-                """, engine)
+    best_model = pd.read_sql(MODEL % (model_name), engine)
 
     if len(best_model) == 0:
 
         with open(f"{os.path.join(path, model_name)}.pkl".replace("'", ""), "wb") as f:
             pickle.dump(model, f)
-        connection.execute(f"""
-            INSERT INTO reg_model (
-                model_name,
-                path
-            ) VALUES(
-                {model_name},
-                {path}
-            )
-        """)
-        connection.execute(f"""
-            INSERT INTO reg_model_metadata (
-                experiment_name,
-                reg_model_name,
-                experimenter,
-                version,
-                train_mae,
-                val_mae,
-                train_mse,
-                val_mse
-                ) VALUES (
-                    {experiment_name},
-                    {model_name},
-                    {experimenter},
-                    {version},
-                    {tr_mae_mean},
-                    {tr_mse_mean},
-                    {cv_mae_mean},
-                    {cv_mse_mean}
-                )
-        """)
+        connection.execute(INSERT_REG_MODEL % (model_name, path))
+        connection.execute(INSERT_REG_MODEL_METADATA % (
+            experiment_name,
+            model_name,
+            experimenter,
+            version,
+            tr_mae_mean,
+            tr_mse_mean,
+            cv_mae_mean,
+            cv_mse_mean)
+        )
+
     else:
-        best_model_metadata = pd.read_sql(f"""
-                SELECT val_mae
-                FROM reg_model_metadata
-                WHERE reg_model_name = {model_name}
-            """, engine)
+        best_model_metadata = pd.read_sql(VAL_MAE % (model_name), engine)
         saved_score = best_model_metadata.values[0]
         if saved_score > valid_mae:
             with open(f"{os.path.join(path, model_name)}.pkl".replace("'", ""), "wb") as f:
                 pickle.dump(model, f)
-            connection.execute(f"""
-                UPDATE reg_model_metadata
-                SET 
-                    train_mae = {tr_mae_mean},
-                    val_mae = {cv_mae_mean},
-                    train_mse = {tr_mse_mean},
-                    val_mse = {cv_mse_mean}
-                WHERE experiment_name = {experiment_name}
-            """)
+            connection.execute(UPDATE_REG_MODEL_METADATA % (
+                tr_mae_mean,
+                cv_mae_mean,
+                tr_mse_mean,
+                cv_mse_mean,
+                experiment_name)
+            )
 
     nni.report_final_result(cv_mae_mean)
     print('Final result is %g', cv_mae_mean)
@@ -191,10 +165,7 @@ def main(params, df, engine, experiment_info, connection):
         'version': 0.1
     }
 
-    df = pd.read_sql("""
-        SELECT *
-        FROM insurance
-    """, engine)
+    df = pd.read_sql(ALL_INSURANCE, engine)
 
     with engine.connect() as connection:
         with connection.begin():