214 lines
8.6 KiB
Python
214 lines
8.6 KiB
Python
"""
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IHyperStrategy interface, hyperoptable Parameter class.
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This module defines a base class for auto-hyperoptable strategies.
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"""
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import logging
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from abc import ABC, abstractmethod
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from contextlib import suppress
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from typing import Any, Iterator, Optional, Sequence, Tuple, Union
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with suppress(ImportError):
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from skopt.space import Integer, Real, Categorical
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from freqtrade.exceptions import OperationalException
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logger = logging.getLogger(__name__)
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class BaseParameter(ABC):
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"""
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Defines a parameter that can be optimized by hyperopt.
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"""
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category: Optional[str]
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default: Any
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value: Any
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opt_range: Sequence[Any]
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def __init__(self, *, opt_range: Sequence[Any], default: Any, space: Optional[str] = None,
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optimize: bool = True, load: bool = True, **kwargs):
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"""
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Initialize hyperopt-optimizable parameter.
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:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
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parameter field
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name is prefixed with 'buy_' or 'sell_'.
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:param optimize: Include parameter in hyperopt optimizations.
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:param load: Load parameter value from {space}_params.
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:param kwargs: Extra parameters to skopt.space.(Integer|Real|Categorical).
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"""
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if 'name' in kwargs:
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raise OperationalException(
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'Name is determined by parameter field name and can not be specified manually.')
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self.category = space
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self._space_params = kwargs
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self.value = default
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self.opt_range = opt_range
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self.optimize = optimize
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self.load = load
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def __repr__(self):
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return f'{self.__class__.__name__}({self.value})'
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@abstractmethod
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def get_space(self, name: str) -> Union['Integer', 'Real', 'Categorical']:
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"""
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Get-space - will be used by Hyperopt to get the hyperopt Space
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"""
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class IntParameter(BaseParameter):
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default: int
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value: int
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opt_range: Sequence[int]
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def __init__(self, low: Union[int, Sequence[int]], high: Optional[int] = None, *, default: int,
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space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs):
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"""
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Initialize hyperopt-optimizable parameter.
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:param low: Lower end (inclusive) of optimization space or [low, high].
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:param high: Upper end (inclusive) of optimization space.
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Must be none of entire range is passed first parameter.
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:param default: A default value.
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:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
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parameter fieldname is prefixed with 'buy_' or 'sell_'.
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:param optimize: Include parameter in hyperopt optimizations.
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:param load: Load parameter value from {space}_params.
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:param kwargs: Extra parameters to skopt.space.Integer.
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"""
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if high is not None and isinstance(low, Sequence):
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raise OperationalException('IntParameter space invalid.')
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if high is None or isinstance(low, Sequence):
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if not isinstance(low, Sequence) or len(low) != 2:
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raise OperationalException('IntParameter space must be [low, high]')
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opt_range = low
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else:
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opt_range = [low, high]
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super().__init__(opt_range=opt_range, default=default, space=space, optimize=optimize,
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load=load, **kwargs)
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def get_space(self, name: str) -> 'Integer':
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"""
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Create skopt optimization space.
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:param name: A name of parameter field.
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"""
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return Integer(*self.opt_range, name=name, **self._space_params)
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class FloatParameter(BaseParameter):
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default: float
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value: float
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opt_range: Sequence[float]
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def __init__(self, low: Union[float, Sequence[float]], high: Optional[float] = None, *,
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default: float, space: Optional[str] = None,
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optimize: bool = True, load: bool = True, **kwargs):
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"""
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Initialize hyperopt-optimizable parameter.
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:param low: Lower end (inclusive) of optimization space or [low, high].
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:param high: Upper end (inclusive) of optimization space.
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Must be none if entire range is passed first parameter.
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:param default: A default value.
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:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
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parameter fieldname is prefixed with 'buy_' or 'sell_'.
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:param optimize: Include parameter in hyperopt optimizations.
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:param load: Load parameter value from {space}_params.
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:param kwargs: Extra parameters to skopt.space.Real.
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"""
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if high is not None and isinstance(low, Sequence):
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raise OperationalException('FloatParameter space invalid.')
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if high is None or isinstance(low, Sequence):
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if not isinstance(low, Sequence) or len(low) != 2:
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raise OperationalException('FloatParameter space must be [low, high]')
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opt_range = low
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else:
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opt_range = [low, high]
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super().__init__(opt_range=opt_range, default=default, space=space, optimize=optimize,
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load=load, **kwargs)
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def get_space(self, name: str) -> 'Real':
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"""
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Create skopt optimization space.
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:param name: A name of parameter field.
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"""
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return Real(*self.opt_range, name=name, **self._space_params)
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class CategoricalParameter(BaseParameter):
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default: Any
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value: Any
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opt_range: Sequence[Any]
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def __init__(self, categories: Sequence[Any], *, default: Optional[Any] = None,
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space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs):
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"""
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Initialize hyperopt-optimizable parameter.
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:param categories: Optimization space, [a, b, ...].
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:param default: A default value. If not specified, first item from specified space will be
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used.
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:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
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parameter field
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name is prefixed with 'buy_' or 'sell_'.
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:param optimize: Include parameter in hyperopt optimizations.
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:param load: Load parameter value from {space}_params.
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:param kwargs: Extra parameters to skopt.space.Categorical.
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"""
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if len(categories) < 2:
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raise OperationalException(
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'CategoricalParameter space must be [a, b, ...] (at least two parameters)')
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super().__init__(opt_range=categories, default=default, space=space, optimize=optimize,
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load=load, **kwargs)
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def get_space(self, name: str) -> 'Categorical':
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"""
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Create skopt optimization space.
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:param name: A name of parameter field.
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"""
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return Categorical(self.opt_range, name=name, **self._space_params)
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class HyperStrategyMixin(object):
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"""
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A helper base class which allows HyperOptAuto class to reuse implementations of of buy/sell
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strategy logic.
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"""
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def __init__(self, *args, **kwargs):
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"""
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Initialize hyperoptable strategy mixin.
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"""
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self._load_params(getattr(self, 'buy_params', None))
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self._load_params(getattr(self, 'sell_params', None))
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def enumerate_parameters(self, category: str = None) -> Iterator[Tuple[str, BaseParameter]]:
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"""
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Find all optimizeable parameters and return (name, attr) iterator.
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:param category:
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:return:
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"""
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if category not in ('buy', 'sell', None):
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raise OperationalException('Category must be one of: "buy", "sell", None.')
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for attr_name in dir(self):
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if not attr_name.startswith('__'): # Ignore internals, not strictly necessary.
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attr = getattr(self, attr_name)
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if issubclass(attr.__class__, BaseParameter):
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if category is None or category == attr.category or \
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attr_name.startswith(category + '_'):
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yield attr_name, attr
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def _load_params(self, params: dict) -> None:
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"""
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Set optimizeable parameter values.
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:param params: Dictionary with new parameter values.
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"""
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if not params:
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return
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for attr_name, attr in self.enumerate_parameters():
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if attr_name in params:
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if attr.load:
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attr.value = params[attr_name]
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logger.info(f'attr_name = {attr.value}')
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else:
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logger.warning(f'Parameter "{attr_name}" exists, but is disabled. '
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f'Default value "{attr.value}" used.')
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