From: Jérôme Benoit <jerome.benoit@piment-noir.org>
Date: Thu, 20 Feb 2025 15:16:16 +0000 (+0100)
Subject: refactor(qav3): factor out optuna storage handling ops
X-Git-Url: https://git.piment-noir.org/?a=commitdiff_plain;h=5de92b120cfa972712a89f7817556a8e462ebc20;p=freqai-strategies.git

refactor(qav3): factor out optuna storage handling ops

Signed-off-by: Jérôme Benoit <jerome.benoit@piment-noir.org>
---

diff --git a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py
index 34a3ace..dee1983 100644
--- a/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py
+++ b/quickadapter/user_data/freqaimodels/LightGBMRegressorQuickAdapterV35.py
@@ -305,7 +305,8 @@ class LightGBMRegressorQuickAdapterV35(BaseRegressionModel):
         study_name = f"hp-{dk.pair}"
         storage = self.optuna_storage(dk)
         pruner = optuna.pruners.HyperbandPruner()
-        previous_study = self.optuna_study_load_and_cleanup(study_name, storage)
+        previous_study = self.optuna_study_load(study_name, storage)
+        self.optuna_study_delete(study_name, storage)
         study = optuna.create_study(
             study_name=study_name,
             sampler=optuna.samplers.TPESampler(
@@ -375,7 +376,8 @@ class LightGBMRegressorQuickAdapterV35(BaseRegressionModel):
         study_name = f"period-{dk.pair}"
         storage = self.optuna_storage(dk)
         pruner = optuna.pruners.HyperbandPruner()
-        previous_study = self.optuna_study_load_and_cleanup(study_name, storage)
+        previous_study = self.optuna_study_load(study_name, storage)
+        self.optuna_study_delete(study_name, storage)
         study = optuna.create_study(
             study_name=study_name,
             sampler=optuna.samplers.TPESampler(
@@ -443,17 +445,17 @@ class LightGBMRegressorQuickAdapterV35(BaseRegressionModel):
                 return json.load(read_file)
         return None
 
-    def optuna_study_load_and_cleanup(
-        self, study_name: str, storage
-    ) -> optuna.study.Study | None:
-        try:
-            study = optuna.load_study(study_name=study_name, storage=storage)
-        except Exception:
-            study = None
+    def optuna_study_delete(self, study_name: str, storage) -> None:
         try:
             optuna.delete_study(study_name=study_name, storage=storage)
         except Exception:
             pass
+
+    def optuna_study_load(self, study_name: str, storage) -> optuna.study.Study | None:
+        try:
+            study = optuna.load_study(study_name=study_name, storage=storage)
+        except Exception:
+            study = None
         return study
 
     def optuna_study_has_best_params(self, study: optuna.study.Study | None) -> bool:
diff --git a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py
index b22cbe1..2568a5b 100644
--- a/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py
+++ b/quickadapter/user_data/freqaimodels/XGBoostRegressorQuickAdapterV35.py
@@ -306,7 +306,8 @@ class XGBoostRegressorQuickAdapterV35(BaseRegressionModel):
         study_name = f"hp-{dk.pair}"
         storage = self.optuna_storage(dk)
         pruner = optuna.pruners.HyperbandPruner()
-        previous_study = self.optuna_study_load_and_cleanup(study_name, storage)
+        previous_study = self.optuna_study_load(study_name, storage)
+        self.optuna_study_delete(study_name, storage)
         study = optuna.create_study(
             study_name=study_name,
             sampler=optuna.samplers.TPESampler(
@@ -376,7 +377,8 @@ class XGBoostRegressorQuickAdapterV35(BaseRegressionModel):
         study_name = f"period-{dk.pair}"
         storage = self.optuna_storage(dk)
         pruner = optuna.pruners.HyperbandPruner()
-        previous_study = self.optuna_study_load_and_cleanup(study_name, storage)
+        previous_study = self.optuna_study_load(study_name, storage)
+        self.optuna_study_delete(study_name, storage)
         study = optuna.create_study(
             study_name=study_name,
             sampler=optuna.samplers.TPESampler(
@@ -444,17 +446,17 @@ class XGBoostRegressorQuickAdapterV35(BaseRegressionModel):
                 return json.load(read_file)
         return None
 
-    def optuna_study_load_and_cleanup(
-        self, study_name: str, storage
-    ) -> optuna.study.Study | None:
-        try:
-            study = optuna.load_study(study_name=study_name, storage=storage)
-        except Exception:
-            study = None
+    def optuna_study_delete(self, study_name: str, storage) -> None:
         try:
             optuna.delete_study(study_name=study_name, storage=storage)
         except Exception:
             pass
+
+    def optuna_study_load(self, study_name: str, storage) -> optuna.study.Study | None:
+        try:
+            study = optuna.load_study(study_name=study_name, storage=storage)
+        except Exception:
+            study = None
         return study
 
     def optuna_study_has_best_params(self, study: optuna.study.Study | None) -> bool: