Update a few missed ruff format updates

build_helpers/freqtrade_client_version_align.py

@@ -1,7 +1,6 @@
 #!/usr/bin/env python3
-from freqtrade_client import __version__ as client_version
-
 from freqtrade import __version__ as ft_version
+from freqtrade_client import __version__ as client_version
 
 
 def main():

freqtrade/freqai/RL/BaseReinforcementLearningModel.py

@@ -197,9 +197,9 @@ class BaseReinforcementLearningModel(IFreqaiModel):
             "df_raw": self.df_raw,
         }
         if self.data_provider:
-            env_info["fee"] = self.data_provider._exchange.get_fee(
+            env_info["fee"] = self.data_provider._exchange.get_fee(  # type: ignore
                 symbol=self.data_provider.current_whitelist()[0]
-            )  # type: ignore
+            )
 
         return env_info
 

freqtrade/freqai/prediction_models/LightGBMRegressorMultiTarget.py

@@ -42,8 +42,8 @@ class LightGBMRegressorMultiTarget(BaseRegressionModel):
             eval_weights = [data_dictionary["test_weights"]]
             eval_sets = [(None, None)] * data_dictionary["test_labels"].shape[1]  # type: ignore
             for i in range(data_dictionary["test_labels"].shape[1]):
-                eval_sets[i] = [
-                    (  # type: ignore
+                eval_sets[i] = [  # type: ignore
+                    (
                         data_dictionary["test_features"],
                         data_dictionary["test_labels"].iloc[:, i],
                     )

freqtrade/freqai/prediction_models/XGBoostRegressorMultiTarget.py

@@ -41,8 +41,8 @@ class XGBoostRegressorMultiTarget(BaseRegressionModel):
         if self.freqai_info.get("data_split_parameters", {}).get("test_size", 0.1) != 0:
             eval_weights = [data_dictionary["test_weights"]]
             for i in range(data_dictionary["test_labels"].shape[1]):
-                eval_sets[i] = [
-                    (  # type: ignore
+                eval_sets[i] = [  # type: ignore
+                    (
                         data_dictionary["test_features"],
                         data_dictionary["test_labels"].iloc[:, i],
                     )

freqtrade/optimize/backtesting.py

@@ -873,9 +873,9 @@ class Backtesting:
             enter = row[SHORT_IDX] if trade.is_short else row[LONG_IDX]
             exit_sig = row[ESHORT_IDX] if trade.is_short else row[ELONG_IDX]
             exits = self.strategy.should_exit(
-                trade,
+                trade,  # type: ignore
                 row[OPEN_IDX],
-                row[DATE_IDX].to_pydatetime(),  # type: ignore
+                row[DATE_IDX].to_pydatetime(),
                 enter=enter,
                 exit_=exit_sig,
                 low=row[LOW_IDX],

freqtrade/optimize/optimize_reports/bt_output.py

@@ -334,7 +334,10 @@ def text_table_add_metrics(strat_results: Dict) -> str:
             ("Avg. Duration Loser", f"{strat_results['loser_holding_avg']}"),
             (
                 "Max Consecutive Wins / Loss",
-                f"{strat_results['max_consecutive_wins']} / {strat_results['max_consecutive_losses']}"
+                (
+                    f"{strat_results['max_consecutive_wins']} / "
+                    f"{strat_results['max_consecutive_losses']}"
+                )
                 if "max_consecutive_losses" in strat_results
                 else "N/A",
             ),

freqtrade/rpc/telegram.py

@@ -765,7 +765,8 @@ class Telegram(RPCHandler):
                 if r.get("realized_profit"):
                     lines.extend(
                         [
-                            "*Realized Profit:* `{realized_profit_ratio:.2%} ({realized_profit_r})`",
+                            "*Realized Profit:* `{realized_profit_ratio:.2%} "
+                            "({realized_profit_r})`",
                             "*Total Profit:* `{total_profit_ratio:.2%} ({total_profit_abs_r})`",
                         ]
                     )