Merge branch 'freqtrade:develop' into develop

docs/requirements-docs.txt

@@ -1,6 +1,6 @@
 markdown==3.6
 mkdocs==1.6.0
-mkdocs-material==9.5.22
+mkdocs-material==9.5.23
 mdx_truly_sane_lists==1.3
 pymdown-extensions==10.8.1
 jinja2==3.1.4

freqtrade/exchange/bingx.py

@@ -17,4 +17,6 @@ class Bingx(Exchange):
 
     _ft_has: Dict = {
         "ohlcv_candle_limit": 1000,
+        "stoploss_on_exchange": False,
+        "stoploss_order_types": {"limit": "limit", "market": "market"},
     }

freqtrade/optimize/hyperopt_loss/hyperopt_loss_profit_drawdown.py

@@ -10,23 +10,26 @@ individual needs.
 
 from pandas import DataFrame
 
+from freqtrade.constants import Config
 from freqtrade.data.metrics import calculate_max_drawdown
 from freqtrade.optimize.hyperopt import IHyperOptLoss
 
 
-# higher numbers penalize drawdowns more severely
+# smaller numbers penalize drawdowns more severely
 DRAWDOWN_MULT = 0.075
 
 
 class ProfitDrawDownHyperOptLoss(IHyperOptLoss):
     @staticmethod
-    def hyperopt_loss_function(results: DataFrame, trade_count: int, *args, **kwargs) -> float:
+    def hyperopt_loss_function(results: DataFrame, config: Config, *args, **kwargs) -> float:
         total_profit = results["profit_abs"].sum()
 
         try:
-            drawdown = calculate_max_drawdown(results, value_col="profit_abs")
+            drawdown = calculate_max_drawdown(
+                results, starting_balance=config["dry_run_wallet"], value_col="profit_abs"
+            )
             relative_account_drawdown = drawdown.relative_account_drawdown
         except ValueError:
             relative_account_drawdown = 0
 
-        return -1 * (total_profit * (1 - relative_account_drawdown * DRAWDOWN_MULT))
+        return -1 * (total_profit - (relative_account_drawdown * total_profit) / DRAWDOWN_MULT)

freqtrade/optimize/hyperopt_tools.py

@@ -358,14 +358,15 @@ class HyperoptTools:
         )
 
     @staticmethod
-    def prepare_trials_columns(trials: pd.DataFrame, has_drawdown: bool) -> pd.DataFrame:
+    def prepare_trials_columns(trials: pd.DataFrame) -> pd.DataFrame:
         trials["Best"] = ""
 
         if "results_metrics.winsdrawslosses" not in trials.columns:
             # Ensure compatibility with older versions of hyperopt results
             trials["results_metrics.winsdrawslosses"] = "N/A"
 
-        if not has_drawdown:
+        has_account_drawdown = "results_metrics.max_drawdown_account" in trials.columns
+        if not has_account_drawdown:
             # Ensure compatibility with older versions of hyperopt results
             trials["results_metrics.max_drawdown_account"] = None
         if "is_random" not in trials.columns:
@@ -389,7 +390,6 @@ class HyperoptTools:
                 "results_metrics.profit_total_abs",
                 "results_metrics.profit_total",
                 "results_metrics.holding_avg",
-                "results_metrics.max_drawdown",
                 "results_metrics.max_drawdown_account",
                 "results_metrics.max_drawdown_abs",
                 "loss",
@@ -408,7 +408,6 @@ class HyperoptTools:
             "Total profit",
             "Profit",
             "Avg duration",
-            "max_drawdown",
             "max_drawdown_account",
             "max_drawdown_abs",
             "Objective",
@@ -437,9 +436,7 @@ class HyperoptTools:
         tabulate.PRESERVE_WHITESPACE = True
         trials = json_normalize(results, max_level=1)
 
-        has_account_drawdown = "results_metrics.max_drawdown_account" in trials.columns
-
-        trials = HyperoptTools.prepare_trials_columns(trials, has_account_drawdown)
+        trials = HyperoptTools.prepare_trials_columns(trials)
 
         trials["is_profit"] = False
         trials.loc[trials["is_initial_point"] | trials["is_random"], "Best"] = "*     "
@@ -471,23 +468,19 @@ class HyperoptTools:
 
         stake_currency = config["stake_currency"]
 
-        trials[f"Max Drawdown{' (Acct)' if has_account_drawdown else ''}"] = trials.apply(
+        trials["Max Drawdown (Acct)"] = trials.apply(
             lambda x: (
                 "{} {}".format(
                     fmt_coin(x["max_drawdown_abs"], stake_currency, keep_trailing_zeros=True),
-                    (
-                        f"({x['max_drawdown_account']:,.2%})"
-                        if has_account_drawdown
-                        else f"({x['max_drawdown']:,.2%})"
-                    ).rjust(10, " "),
+                    (f"({x['max_drawdown_account']:,.2%})").rjust(10, " "),
                 ).rjust(25 + len(stake_currency))
-                if x["max_drawdown"] != 0.0 or x["max_drawdown_account"] != 0.0
+                if x["max_drawdown_account"] != 0.0
                 else "--".rjust(25 + len(stake_currency))
             ),
             axis=1,
         )
 
-        trials = trials.drop(columns=["max_drawdown_abs", "max_drawdown", "max_drawdown_account"])
+        trials = trials.drop(columns=["max_drawdown_abs", "max_drawdown_account"])
 
         trials["Profit"] = trials.apply(
             lambda x: (

freqtrade/optimize/optimize_reports/optimize_reports.py

@@ -497,7 +497,6 @@ def generate_strategy_stats(
     }
 
     try:
-        max_drawdown_legacy = calculate_max_drawdown(results, value_col="profit_ratio")
         drawdown = calculate_max_drawdown(
             results, value_col="profit_abs", starting_balance=start_balance
         )
@@ -508,7 +507,6 @@ def generate_strategy_stats(
 
         strat_stats.update(
             {
-                "max_drawdown": max_drawdown_legacy.drawdown_abs,  # Deprecated - do not use
                 "max_drawdown_account": drawdown.relative_account_drawdown,
                 "max_relative_drawdown": underwater.relative_account_drawdown,
                 "max_drawdown_abs": drawdown.drawdown_abs,
@@ -527,7 +525,6 @@ def generate_strategy_stats(
     except ValueError:
         strat_stats.update(
             {
-                "max_drawdown": 0.0,
                 "max_drawdown_account": 0.0,
                 "max_relative_drawdown": 0.0,
                 "max_drawdown_abs": 0.0,

freqtrade/rpc/api_server/webserver.py

@@ -1,5 +1,5 @@
 import logging
-from ipaddress import IPv4Address
+from ipaddress import ip_address
 from typing import Any, Optional
 
 import orjson
@@ -180,7 +180,7 @@ class ApiServer(RPCHandler):
         rest_port = self._config["api_server"]["listen_port"]
 
         logger.info(f"Starting HTTP Server at {rest_ip}:{rest_port}")
-        if not IPv4Address(rest_ip).is_loopback and not running_in_docker():
+        if not ip_address(rest_ip).is_loopback and not running_in_docker():
             logger.warning("SECURITY WARNING - Local Rest Server listening to external connections")
             logger.warning(
                 "SECURITY WARNING - This is insecure please set to your loopback,"

ft_client/requirements.txt

@@ -1,3 +1,3 @@
 # Requirements for freqtrade client library
 requests==2.31.0
-python-rapidjson==1.16
+python-rapidjson==1.17

requirements-dev.txt

@@ -6,12 +6,12 @@
 -r requirements-freqai-rl.txt
 -r docs/requirements-docs.txt
 
-coveralls==4.0.0
+coveralls==4.0.1
 ruff==0.4.4
 mypy==1.10.0
 pre-commit==3.7.1
-pytest==8.2.0
-pytest-asyncio==0.23.6
+pytest==8.2.1
+pytest-asyncio==0.23.7
 pytest-cov==5.0.0
 pytest-mock==3.14.0
 pytest-random-order==1.1.1

requirements.txt

@@ -2,7 +2,7 @@ numpy==1.26.4
 pandas==2.2.2
 pandas-ta==0.3.14b
 
-ccxt==4.3.24
+ccxt==4.3.27
 cryptography==42.0.7
 aiohttp==3.9.5
 SQLAlchemy==2.0.30
@@ -22,13 +22,13 @@ jinja2==3.1.4
 tables==3.9.1
 joblib==1.4.2
 rich==13.7.1
-pyarrow==16.0.0; platform_machine != 'armv7l'
+pyarrow==16.1.0; platform_machine != 'armv7l'
 
 # find first, C search in arrays
 py_find_1st==1.1.6
 
 # Load ticker files 30% faster
-python-rapidjson==1.16
+python-rapidjson==1.17
 # Properly format api responses
 orjson==3.10.3
 

tests/commands/test_commands.py

@@ -54,6 +54,7 @@ from tests.conftest import (
     patch_exchange,
     patched_configuration_load_config_file,
 )
+from tests.conftest_hyperopt import hyperopt_test_result
 from tests.conftest_trades import MOCK_TRADE_COUNT
 
 
@@ -1137,7 +1138,8 @@ def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys):
         pytest.fail(f"Expected well formed JSON, but failed to parse: {captured.out}")
 
 
-def test_hyperopt_list(mocker, capsys, caplog, saved_hyperopt_results, tmp_path):
+def test_hyperopt_list(mocker, capsys, caplog, tmp_path):
+    saved_hyperopt_results = hyperopt_test_result()
     csv_file = tmp_path / "test.csv"
     mocker.patch(
         "freqtrade.optimize.hyperopt_tools.HyperoptTools._test_hyperopt_results_exist",
@@ -1507,7 +1509,8 @@ def test_hyperopt_list(mocker, capsys, caplog, saved_hyperopt_results, tmp_path)
     csv_file.unlink()
 
 
-def test_hyperopt_show(mocker, capsys, saved_hyperopt_results):
+def test_hyperopt_show(mocker, capsys):
+    saved_hyperopt_results = hyperopt_test_result()
     mocker.patch(
         "freqtrade.optimize.hyperopt_tools.HyperoptTools._test_hyperopt_results_exist",
         return_value=True,

tests/optimize/test_hyperopt.py

@@ -47,7 +47,7 @@ def generate_result_metrics():
         "profit_total_abs": 0.001,
         "profit_total": 0.01,
         "holding_avg": timedelta(minutes=20),
-        "max_drawdown": 0.001,
+        "max_drawdown_account": 0.001,
         "max_drawdown_abs": 0.001,
         "loss": 0.001,
         "is_initial_point": 0.001,

tests/strategy/strats/hyperoptable_strategy.py

@@ -52,7 +52,7 @@ class HyperoptableStrategy(StrategyTestV3):
     bot_loop_started = False
     bot_started = False
 
-    def bot_loop_start(self):
+    def bot_loop_start(self, **kwargs):
         self.bot_loop_started = True
 
     def bot_start(self, **kwargs) -> None:

tests/strategy/strats/hyperoptable_strategy_v2.py

@@ -48,7 +48,7 @@ class HyperoptableStrategyV2(StrategyTestV2):
 
     bot_loop_started = False
 
-    def bot_loop_start(self):
+    def bot_loop_start(self, **kwargs):
         self.bot_loop_started = True
 
     def bot_start(self, **kwargs) -> None: