[pull] develop from freqtrade:develop

docs/exchanges.md

@@ -145,7 +145,7 @@ To use BNFCR futures, you will have to have the following combination of setting
 
 The `stake_currency` setting defines the markets the bot will be operating in. This choice is really arbitrary.
 
-On the exchange, you'll have to use "Multi-asset Mode" - and "Position Mode set to "One-way Mode".
+On the exchange, you'll have to use "Multi-asset Mode" - and "Position Mode set to "One-way Mode".  
 Freqtrade will check these settings on startup, but won't attempt to change them.
 
 ## Bingx

freqtrade/data/history/history_utils.py

@@ -679,11 +679,17 @@ def download_data(
                 )
         else:
             if not exchange.get_option("ohlcv_has_history", True):
-                raise OperationalException(
-                    f"Historic klines not available for {exchange.name}. "
-                    "Please use `--dl-trades` instead for this exchange "
-                    "(will unfortunately take a long time)."
-                )
+                if not exchange.get_option("trades_has_history", True):
+                    raise OperationalException(
+                        f"Historic data not available for {exchange.name}. "
+                        f"{exchange.name} does not support downloading trades or ohlcv data."
+                    )
+                else:
+                    raise OperationalException(
+                        f"Historic klines not available for {exchange.name}. "
+                        "Please use `--dl-trades` instead for this exchange "
+                        "(will unfortunately take a long time)."
+                    )
             migrate_data(config, exchange)
             pairs_not_available = refresh_backtest_ohlcv_data(
                 exchange,

freqtrade/freqai/freqai_interface.py

@@ -773,7 +773,7 @@ def _set_train_queue(self):
         """
         current_pairlist = self.config.get("exchange", {}).get("pair_whitelist")
         if not self.dd.pair_dict:
-            logger.info("Set fresh train queue from whitelist. Queue: {current_pairlist}")
+            logger.info(f"Set fresh train queue from whitelist. Queue: {current_pairlist}")
             return deque(current_pairlist)
 
         best_queue = deque()
@@ -789,7 +789,7 @@ def _set_train_queue(self):
                 best_queue.appendleft(pair)
 
         logger.info(
-            "Set existing queue from trained timestamps. Best approximation queue: {best_queue}"
+            f"Set existing queue from trained timestamps. Best approximation queue: {best_queue}"
         )
         return best_queue
 

freqtrade/optimize/backtesting.py

@@ -855,7 +855,7 @@ def _exit_trade(
             amount=amount,
             filled=0,
             remaining=amount,
-            cost=amount * close_rate,
+            cost=amount * close_rate * (1 + self.fee),
             ft_order_tag=exit_reason,
         )
         order._trade_bt = trade

freqtrade/optimize/optimize_reports/optimize_reports.py

@@ -108,7 +108,14 @@ def _generate_result_line(
     }
 
 
-def generate_pair_metrics(
+def calculate_trade_volume(trades_dict: list[dict[str, Any]]) -> float:
+    # Aggregate the total volume traded from orders.cost.
+    # Orders is a nested dictionary within the trades list.
+
+    return sum(sum(order["cost"] for order in trade.get("orders", [])) for trade in trades_dict)
+
+
+def generate_pair_metrics(  #
     pairlist: list[str],
     stake_currency: str,
     starting_balance: float,
@@ -368,7 +375,7 @@ def generate_strategy_stats(
     :param market_change: float indicating the market change
     :return: Dictionary containing results per strategy and a strategy summary.
     """
-    results: dict[str, DataFrame] = content["results"]
+    results: DataFrame = content["results"]
     if not isinstance(results, DataFrame):
         return {}
     config = content["config"]
@@ -431,8 +438,9 @@ def generate_strategy_stats(
 
     expectancy, expectancy_ratio = calculate_expectancy(results)
     backtest_days = (max_date - min_date).days or 1
+    trades_dict = results.to_dict(orient="records")
     strat_stats = {
-        "trades": results.to_dict(orient="records"),
+        "trades": trades_dict,
         "locks": [lock.to_json() for lock in content["locks"]],
         "best_pair": best_pair,
         "worst_pair": worst_pair,
@@ -444,7 +452,7 @@ def generate_strategy_stats(
         "total_trades": len(results),
         "trade_count_long": len(results.loc[~results["is_short"]]),
         "trade_count_short": len(results.loc[results["is_short"]]),
-        "total_volume": float(results["stake_amount"].sum()),
+        "total_volume": calculate_trade_volume(trades_dict),
         "avg_stake_amount": results["stake_amount"].mean() if len(results) > 0 else 0,
         "profit_mean": results["profit_ratio"].mean() if len(results) > 0 else 0,
         "profit_median": results["profit_ratio"].median() if len(results) > 0 else 0,

freqtrade/persistence/trade_model.py

@@ -270,6 +270,7 @@ def to_json(self, entry_side: str, minified: bool = False) -> dict[str, Any]:
             "order_filled_timestamp": dt_ts_none(self.order_filled_utc),
             "ft_is_entry": self.ft_order_side == entry_side,
             "ft_order_tag": self.ft_order_tag,
+            "cost": self.cost if self.cost else 0,
         }
         if not minified:
             resp.update(
@@ -278,7 +279,6 @@ def to_json(self, entry_side: str, minified: bool = False) -> dict[str, Any]:
                     "order_id": self.order_id,
                     "status": self.status,
                     "average": round(self.average, 8) if self.average else 0,
-                    "cost": self.cost if self.cost else 0,
                     "filled": self.filled,
                     "is_open": self.ft_is_open,
                     "order_date": (

tests/data/test_download_data.py

@@ -102,3 +102,16 @@ def test_download_data_main_data_invalid(mocker):
     )
     with pytest.raises(OperationalException, match=r"Historic klines not available for .*"):
         download_data_main(config)
+
+    patch_exchange(mocker, exchange="hyperliquid")
+    mocker.patch(f"{EXMS}.get_markets", return_value={"ETH/USDC": {}})
+    config2 = setup_utils_configuration({"exchange": "hyperliquid"}, RunMode.UTIL_EXCHANGE)
+    config2.update(
+        {
+            "days": 20,
+            "pairs": ["ETH/USDC", "XRP/USDC"],
+            "timeframes": ["5m", "1h"],
+        }
+    )
+    with pytest.raises(OperationalException, match=r"Historic data not available for .*"):
+        download_data_main(config2)

tests/optimize/test_backtesting.py

@@ -5,7 +5,7 @@
 from copy import deepcopy
 from datetime import datetime, timedelta, timezone
 from pathlib import Path
-from unittest.mock import MagicMock, PropertyMock
+from unittest.mock import ANY, MagicMock, PropertyMock
 
 import numpy as np
 import pandas as pd
@@ -795,6 +795,7 @@ def test_backtest_one(default_conf, mocker, testdatadir) -> None:
                         "order_filled_timestamp": 1517251200000,
                         "ft_is_entry": True,
                         "ft_order_tag": "",
+                        "cost": ANY,
                     },
                     {
                         "amount": 0.00957442,
@@ -803,6 +804,7 @@ def test_backtest_one(default_conf, mocker, testdatadir) -> None:
                         "order_filled_timestamp": 1517265300000,
                         "ft_is_entry": False,
                         "ft_order_tag": "roi",
+                        "cost": ANY,
                     },
                 ],
                 [
@@ -813,6 +815,7 @@ def test_backtest_one(default_conf, mocker, testdatadir) -> None:
                         "order_filled_timestamp": 1517283000000,
                         "ft_is_entry": True,
                         "ft_order_tag": "",
+                        "cost": ANY,
                     },
                     {
                         "amount": 0.0097064,
@@ -821,6 +824,7 @@ def test_backtest_one(default_conf, mocker, testdatadir) -> None:
                         "order_filled_timestamp": 1517285400000,
                         "ft_is_entry": False,
                         "ft_order_tag": "roi",
+                        "cost": ANY,
                     },
                 ],
             ],