# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement import logging from pandas import DataFrame from strategy_test_v3 import StrategyTestV3 import freqtrade.vendor.qtpylib.indicators as qtpylib from freqtrade.strategy import BooleanParameter, DecimalParameter, IntParameter, RealParameter logger = logging.getLogger(__name__) class HyperoptableStrategy(StrategyTestV3): """ Default Strategy provided by freqtrade bot. Please do not modify this strategy, it's intended for internal use only. Please look at the SampleStrategy in the user_data/strategy directory or strategy repository https://github.com/freqtrade/freqtrade-strategies for samples and inspiration. """ INTERFACE_VERSION = 3 buy_params = { "buy_rsi": 35, # Intentionally not specified, so "default" is tested # 'buy_plusdi': 0.4 } sell_params = {"sell_rsi": 74, "sell_minusdi": 0.4} buy_plusdi = RealParameter(low=0, high=1, default=0.5, space="buy") sell_rsi = IntParameter(low=50, high=100, default=70, space="sell") sell_minusdi = DecimalParameter( low=0, high=1, default=0.5001, decimals=3, space="sell", load=False ) protection_enabled = BooleanParameter(default=True) protection_cooldown_lookback = IntParameter([0, 50], default=30) # Invalid plot config ... plot_config = { "main_plot": {}, } @property def protections(self): prot = [] if self.protection_enabled.value: prot.append( { "method": "CooldownPeriod", "stop_duration_candles": self.protection_cooldown_lookback.value, } ) return prot bot_loop_started = False bot_started = False def bot_loop_start(self, **kwargs): self.bot_loop_started = True logger.info("Test: Bot loop started") def bot_start(self, **kwargs) -> None: self.bot_started = True self.buy_rsi = IntParameter([0, 50], default=30, space="buy") def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe["rsi"] < self.buy_rsi.value) & (dataframe["fastd"] < 35) & (dataframe["adx"] > 30) & (dataframe["plus_di"] > self.buy_plusdi.value) ) | ((dataframe["adx"] > 65) & (dataframe["plus_di"] > self.buy_plusdi.value)), "enter_long", ] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( ( (qtpylib.crossed_above(dataframe["rsi"], self.sell_rsi.value)) | (qtpylib.crossed_above(dataframe["fastd"], 70)) ) & (dataframe["adx"] > 10) & (dataframe["minus_di"] > 0) ) | ((dataframe["adx"] > 70) & (dataframe["minus_di"] > self.sell_minusdi.value)), "exit_long", ] = 1 return dataframe