106 lines
3.1 KiB
Python
106 lines
3.1 KiB
Python
"""
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IHyperOpt interface
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This module defines the interface to apply for hyperopts
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"""
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from abc import ABC, abstractmethod
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from typing import Dict, Any, Callable, List
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from pandas import DataFrame
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from skopt.space import Dimension, Integer, Real
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class IHyperOpt(ABC):
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"""
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Interface for freqtrade hyperopts
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Defines the mandatory structure must follow any custom strategies
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Attributes you can use:
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minimal_roi -> Dict: Minimal ROI designed for the strategy
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stoploss -> float: optimal stoploss designed for the strategy
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ticker_interval -> int: value of the ticker interval to use for the strategy
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"""
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ticker_interval: str
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@staticmethod
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@abstractmethod
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def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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Populate indicators that will be used in the Buy and Sell strategy.
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:param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe().
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:return: A Dataframe with all mandatory indicators for the strategies.
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"""
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@staticmethod
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@abstractmethod
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def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
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"""
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Create a buy strategy generator.
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"""
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@staticmethod
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@abstractmethod
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def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
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"""
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Create a sell strategy generator.
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"""
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@staticmethod
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@abstractmethod
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def indicator_space() -> List[Dimension]:
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"""
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Create an indicator space.
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"""
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@staticmethod
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@abstractmethod
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def sell_indicator_space() -> List[Dimension]:
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"""
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Create a sell indicator space.
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"""
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@staticmethod
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def generate_roi_table(params: Dict) -> Dict[int, float]:
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"""
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Create a ROI table.
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Generates the ROI table that will be used by Hyperopt.
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You may override it in your custom Hyperopt class.
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"""
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roi_table = {}
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roi_table[0] = params['roi_p1'] + params['roi_p2'] + params['roi_p3']
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roi_table[params['roi_t3']] = params['roi_p1'] + params['roi_p2']
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roi_table[params['roi_t3'] + params['roi_t2']] = params['roi_p1']
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roi_table[params['roi_t3'] + params['roi_t2'] + params['roi_t1']] = 0
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return roi_table
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@staticmethod
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def stoploss_space() -> List[Dimension]:
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"""
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Create a stoploss space.
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Defines range of stoploss values to search.
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You may override it in your custom Hyperopt class.
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"""
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return [
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Real(-0.5, -0.02, name='stoploss'),
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]
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@staticmethod
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def roi_space() -> List[Dimension]:
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"""
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Create a ROI space.
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Defines values to search for each ROI steps.
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You may override it in your custom Hyperopt class.
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"""
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return [
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Integer(10, 120, name='roi_t1'),
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Integer(10, 60, name='roi_t2'),
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Integer(10, 40, name='roi_t3'),
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Real(0.01, 0.04, name='roi_p1'),
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Real(0.01, 0.07, name='roi_p2'),
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Real(0.01, 0.20, name='roi_p3'),
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]
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