types: slightly improved typing

freqtrade/optimize/hyperopt/hyperopt_interface.py

@@ -9,7 +9,6 @@ from abc import ABC
 from typing import TypeAlias
 
 from sklearn.base import RegressorMixin
-from skopt.space import Dimension  # , Integer, Categorical,
 
 from freqtrade.constants import Config
 from freqtrade.exchange import timeframe_to_minutes
@@ -17,6 +16,7 @@ from freqtrade.misc import round_dict
 from freqtrade.optimize.space import SKDecimal
 from freqtrade.strategy import IStrategy
 from freqtrade.strategy.parameters import (
+    DimensionProtocol,
     ft_CategoricalDistribution,
     ft_IntDistribution,
 )
@@ -45,7 +45,7 @@ class IHyperOpt(ABC):
         # Assign timeframe to be used in hyperopt
         IHyperOpt.timeframe = str(config["timeframe"])
 
-    def generate_estimator(self, dimensions: list[Dimension], **kwargs) -> EstimatorType:
+    def generate_estimator(self, dimensions: list[DimensionProtocol], **kwargs) -> EstimatorType:
         """
         Return base_estimator.
         Can be any of "TPESampler", "GPSampler", "CmaEsSampler", "NSGAIISampler"
@@ -69,7 +69,7 @@ class IHyperOpt(ABC):
 
         return roi_table
 
-    def roi_space(self) -> list[Dimension]:
+    def roi_space(self) -> list[DimensionProtocol]:
         """
         Create a ROI space.
 
@@ -154,7 +154,7 @@ class IHyperOpt(ABC):
             ),
         ]
 
-    def stoploss_space(self) -> list[Dimension]:
+    def stoploss_space(self) -> list[DimensionProtocol]:
         """
         Create a stoploss space.
 
@@ -178,7 +178,7 @@ class IHyperOpt(ABC):
             "trailing_only_offset_is_reached": params["trailing_only_offset_is_reached"],
         }
 
-    def trailing_space(self) -> list[Dimension]:
+    def trailing_space(self) -> list[DimensionProtocol]:
         """
         Create a trailing stoploss space.
 
@@ -204,7 +204,7 @@ class IHyperOpt(ABC):
             ft_CategoricalDistribution("trailing_only_offset_is_reached", [True, False]),
         ]
 
-    def max_open_trades_space(self) -> list[Dimension]:
+    def max_open_trades_space(self) -> list[DimensionProtocol]:
         """
         Create a max open trades space.
 

freqtrade/optimize/hyperopt/hyperopt_optimizer.py

@@ -30,6 +30,7 @@ from freqtrade.optimize.hyperopt_loss.hyperopt_loss_interface import IHyperOptLo
 from freqtrade.optimize.hyperopt_tools import HyperoptStateContainer, HyperoptTools
 from freqtrade.optimize.optimize_reports import generate_strategy_stats
 from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver
+from freqtrade.strategy.parameters import DimensionProtocol
 from freqtrade.util.dry_run_wallet import get_dry_run_wallet
 
 
@@ -40,7 +41,6 @@ with warnings.catch_warnings():
     warnings.filterwarnings("ignore", category=FutureWarning)
     # warnings.filterwarnings("ignore", category=ExperimentalWarning)
     import optuna
-    from skopt.space import Dimension
 
     from freqtrade.optimize.space.decimalspace import SKDecimal
     from freqtrade.strategy.parameters import (
@@ -71,14 +71,14 @@ class HyperOptimizer:
     """
 
     def __init__(self, config: Config) -> None:
-        self.buy_space: list[Dimension] = []
-        self.sell_space: list[Dimension] = []
-        self.protection_space: list[Dimension] = []
-        self.roi_space: list[Dimension] = []
-        self.stoploss_space: list[Dimension] = []
-        self.trailing_space: list[Dimension] = []
-        self.max_open_trades_space: list[Dimension] = []
-        self.dimensions: list[Dimension] = []
+        self.buy_space: list[DimensionProtocol] = []
+        self.sell_space: list[DimensionProtocol] = []
+        self.protection_space: list[DimensionProtocol] = []
+        self.roi_space: list[DimensionProtocol] = []
+        self.stoploss_space: list[DimensionProtocol] = []
+        self.trailing_space: list[DimensionProtocol] = []
+        self.max_open_trades_space: list[DimensionProtocol] = []
+        self.dimensions: list[DimensionProtocol] = []
         self.o_dimensions: dict = {}
 
         self.config = config
@@ -146,7 +146,7 @@ class HyperOptimizer:
 
     def _get_params_dict(
         self,
-        dimensions: list[Dimension],
+        dimensions: list[DimensionProtocol],
         raw_params: dict[str, Any],
     ) -> dict[str, Any]:
         # logger.info(f"_get_params_dict: {raw_params}")
@@ -404,7 +404,7 @@ class HyperOptimizer:
             "total_profit": total_profit,
         }
 
-    def convert_dimensions_to_optuna_space(self, s_dimensions: list[Dimension]) -> dict:
+    def convert_dimensions_to_optuna_space(self, s_dimensions: list[DimensionProtocol]) -> dict:
         o_dimensions: dict[str, optuna.distributions.BaseDistribution] = {}
         for original_dim in s_dimensions:
             if isinstance(original_dim, SKDecimal):

freqtrade/strategy/parameters.py

@@ -7,7 +7,7 @@ import logging
 from abc import ABC, abstractmethod
 from collections.abc import Sequence
 from contextlib import suppress
-from typing import Any, Union
+from typing import Any, Protocol, Union
 
 from freqtrade.enums import HyperoptState
 from freqtrade.optimize.hyperopt_tools import HyperoptStateContainer
@@ -24,6 +24,10 @@ from freqtrade.exceptions import OperationalException
 logger = logging.getLogger(__name__)
 
 
+class DimensionProtocol(Protocol):
+    name: str
+
+
 class ft_CategoricalDistribution(CategoricalDistribution):
     def __init__(
         self,