Merge pull request #2024 from freqtrade/custom_hyperopt_loss

Custom hyperopt loss function (and sharpe-ratio)

freqtrade/resolvers/hyperopt_resolver.py

@@ -8,8 +8,9 @@ from pathlib import Path
 from typing import Optional, Dict
 
 from freqtrade import OperationalException
-from freqtrade.constants import DEFAULT_HYPEROPT
+from freqtrade.constants import DEFAULT_HYPEROPT, DEFAULT_HYPEROPT_LOSS
 from freqtrade.optimize.hyperopt_interface import IHyperOpt
+from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss
 from freqtrade.resolvers import IResolver
 
 logger = logging.getLogger(__name__)
@@ -54,7 +55,7 @@ class HyperOptResolver(IResolver):
         current_path = Path(__file__).parent.parent.joinpath('optimize').resolve()
 
         abs_paths = [
-            current_path.parent.parent.joinpath('user_data/hyperopts'),
+            Path.cwd().joinpath('user_data/hyperopts'),
             current_path,
         ]
 
@@ -77,3 +78,66 @@ class HyperOptResolver(IResolver):
             f"Impossible to load Hyperopt '{hyperopt_name}'. This class does not exist "
             "or contains Python code errors."
         )
+
+
+class HyperOptLossResolver(IResolver):
+    """
+    This class contains all the logic to load custom hyperopt loss class
+    """
+
+    __slots__ = ['hyperoptloss']
+
+    def __init__(self, config: Optional[Dict] = None) -> None:
+        """
+        Load the custom class from config parameter
+        :param config: configuration dictionary or None
+        """
+        config = config or {}
+
+        # Verify the hyperopt is in the configuration, otherwise fallback to the default hyperopt
+        hyperopt_name = config.get('hyperopt_loss') or DEFAULT_HYPEROPT_LOSS
+        self.hyperoptloss = self._load_hyperoptloss(
+            hyperopt_name, extra_dir=config.get('hyperopt_path'))
+
+        # Assign ticker_interval to be used in hyperopt
+        self.hyperoptloss.__class__.ticker_interval = str(config['ticker_interval'])
+
+        if not hasattr(self.hyperoptloss, 'hyperopt_loss_function'):
+            raise OperationalException(
+                f"Found hyperopt {hyperopt_name} does not implement `hyperopt_loss_function`.")
+
+    def _load_hyperoptloss(
+            self, hyper_loss_name: str, extra_dir: Optional[str] = None) -> IHyperOptLoss:
+        """
+        Search and loads the specified hyperopt loss class.
+        :param hyper_loss_name: name of the module to import
+        :param extra_dir: additional directory to search for the given hyperopt
+        :return: HyperOptLoss instance or None
+        """
+        current_path = Path(__file__).parent.parent.joinpath('optimize').resolve()
+
+        abs_paths = [
+            Path.cwd().joinpath('user_data/hyperopts'),
+            current_path,
+        ]
+
+        if extra_dir:
+            # Add extra hyperopt directory on top of search paths
+            abs_paths.insert(0, Path(extra_dir))
+
+        for _path in abs_paths:
+            try:
+                (hyperoptloss, module_path) = self._search_object(directory=_path,
+                                                                  object_type=IHyperOptLoss,
+                                                                  object_name=hyper_loss_name)
+                if hyperoptloss:
+                    logger.info(
+                        f"Using resolved hyperopt {hyper_loss_name} from '{module_path}'...")
+                    return hyperoptloss
+            except FileNotFoundError:
+                logger.warning('Path "%s" does not exist.', _path.relative_to(Path.cwd()))
+
+        raise OperationalException(
+            f"Impossible to load HyperoptLoss '{hyper_loss_name}'. This class does not exist "
+            "or contains Python code errors."
+        )