perf(qav3): readd properly some caching

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

diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
index 2a8b9d5b3bbec1e036898ebc9b29f784ad5ba45b..049e202acbd78c91d614978c4197ce63f4268072 100644 (file)
--- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
+++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
@@ -74,6 +74,19 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
             **self.freqai_info.get("optuna_hyperopt", {}),
         }
 
+    @cached_property
+    def _optuna_label_candle_pool_full(self) -> list[int]:
+        n_pairs = len(self.pairs)
+        label_frequency_candles = max(
+            2, 2 * n_pairs, int(self.ft_params.get("label_frequency_candles", 12))
+        )
+        min_offset = -int(label_frequency_candles / 2)
+        max_offset = int(label_frequency_candles / 2)
+        return [
+            max(1, label_frequency_candles + offset)
+            for offset in range(min_offset, max_offset + 1)
+        ]
+
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
         self.pairs = self.config.get("exchange", {}).get("pair_whitelist")
@@ -189,20 +202,8 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
         else:
             raise ValueError(f"Invalid namespace: {namespace}")
 
-    def build_optuna_label_candle_pool(self) -> list[int]:
-        n_pairs = len(self.pairs)
-        label_frequency_candles = max(
-            2, 2 * n_pairs, int(self.ft_params.get("label_frequency_candles", 12))
-        )
-        min_offset = -int(label_frequency_candles / 2)
-        max_offset = int(label_frequency_candles / 2)
-        return [
-            max(1, label_frequency_candles + offset)
-            for offset in range(min_offset, max_offset + 1)
-        ]
-
     def init_optuna_label_candle_pool(self) -> None:
-        self._optuna_label_candle_pool = self.build_optuna_label_candle_pool()
+        self._optuna_label_candle_pool = self._optuna_label_candle_pool_full
         random.shuffle(self._optuna_label_candle_pool)
         if len(self._optuna_label_candle_pool) == 0:
             raise RuntimeError("Failed to initialize optuna label candle pool")
@@ -212,7 +213,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
             logger.warning(
                 "Optuna label candle pool is empty, reinitializing it ("
                 f"{self._optuna_label_candle_pool=} ,"
-                f"{self.build_optuna_label_candle_pool()=} ,"
+                f"{self._optuna_label_candle_pool_full=} ,"
                 f"{self._optuna_label_candle.values()=} ,"
                 f"{self._optuna_label_candles.values()=} ,"
                 f"{self._optuna_label_incremented_pairs=})"
@@ -237,7 +238,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
         self._optuna_label_candle[pair] = optuna_label_candle
         self._optuna_label_candle_pool.remove(optuna_label_candle)
         optuna_label_available_candles = (
-            set(self.build_optuna_label_candle_pool())
+            set(self._optuna_label_candle_pool_full)
             - set(self._optuna_label_candle_pool)
             - set(self._optuna_label_candle.values())
         )

diff --git a/quickadapter/user_data/strategies/QuickAdapterV3.py b/quickadapter/user_data/strategies/QuickAdapterV3.py
index 5a9ff18fe7efeaae3bdf3dffef7d4a2ed1986a51..8801f757c436dffa5459f1f61c50c2d01a1107d3 100644 (file)
--- a/quickadapter/user_data/strategies/QuickAdapterV3.py
+++ b/quickadapter/user_data/strategies/QuickAdapterV3.py
@@ -149,6 +149,18 @@ class QuickAdapterV3(IStrategy):
         # Match the predictions warmup period
         return self.freqai_info.get("fit_live_predictions_candles", 100)
 
+    @cached_property
+    def max_open_trades_per_side(self) -> int:
+        max_open_trades = self.config.get("max_open_trades")
+        if max_open_trades < 0:
+            return -1
+        if self.is_short_allowed():
+            if max_open_trades % 2 == 1:
+                max_open_trades += 1
+            return int(max_open_trades / 2)
+        else:
+            return max_open_trades
+
     def bot_start(self, **kwargs) -> None:
         self.pairs = self.config.get("exchange", {}).get("pair_whitelist")
         if not self.pairs:
@@ -819,7 +831,7 @@ class QuickAdapterV3(IStrategy):
     ) -> bool:
         if Trade.get_open_trade_count() >= self.config.get("max_open_trades"):
             return False
-        max_open_trades_per_side = self.max_open_trades_per_side()
+        max_open_trades_per_side = self.max_open_trades_per_side
         if max_open_trades_per_side >= 0:
             open_trades = Trade.get_open_trades()
             trades_per_side = sum(1 for trade in open_trades if trade.enter_tag == side)
@@ -860,17 +872,6 @@ class QuickAdapterV3(IStrategy):
             )
         return False
 
-    def max_open_trades_per_side(self) -> int:
-        max_open_trades = self.config.get("max_open_trades")
-        if max_open_trades < 0:
-            return -1
-        if self.is_short_allowed():
-            if max_open_trades % 2 == 1:
-                max_open_trades += 1
-            return int(max_open_trades / 2)
-        else:
-            return max_open_trades
-
     def is_short_allowed(self) -> bool:
         trading_mode = self.config.get("trading_mode")
         if trading_mode == "margin" or trading_mode == "futures":