EnsembleStrategyV2

from freqtrade.strategy import IStrategy, IntParameter, DecimalParameter
import logging
from pandas import DataFrame
from freqtrade.resolvers import StrategyResolver
from itertools import combinations
from functools import reduce
from freqtrade.persistence import Trade
from datetime import datetime
logger = logging.getLogger(__name__)
STRATEGIES = ['CombinedBinHAndCluc', 'CombinedBinHAndClucV2', 'CombinedBinHAndClucV5', 'CombinedBinHAndClucV7', 'CombinedBinHAndClucV8', 'SMAOffset', 'SMAOffsetV2', 'SMAOffsetProtectOptV0', 'SMAOffsetProtectOptV1', 'NostalgiaForInfinityV1', 'NostalgiaForInfinityV2', 'NostalgiaForInfinityV3', 'NostalgiaForInfinityV4', 'NostalgiaForInfinityV5', 'NostalgiaForInfinityV7']
STRAT_COMBINATIONS = reduce(lambda x, y: list(combinations(STRATEGIES, y)) + x, range(len(STRATEGIES) + 1), [])
MAX_COMBINATIONS = len(STRAT_COMBINATIONS) - 1

class EnsembleStrategyV2(IStrategy):
    INTERFACE_VERSION = 3
    loaded_strategies = {}
    use_exit_signal = True
    exit_profit_only = False
    ignore_roi_if_entry_signal = False
    informative_timeframe = '1h'
    entry_mean_threshold = DecimalParameter(0.0, 1, default=0.032, load=True)
    exit_mean_threshold = DecimalParameter(0.0, 1, default=0.059, load=True)
    entry_strategies = IntParameter(0, MAX_COMBINATIONS, default=30080, load=True)
    exit_strategies = IntParameter(0, MAX_COMBINATIONS, default=21678, load=True)
    # Buy hyperspace params:
    entry_params = {'entry_mean_threshold': 0.032, 'entry_strategies': 30080}
    # Sell hyperspace params:
    exit_params = {'exit_mean_threshold': 0.059, 'exit_strategies': 21678}
    # ROI table:
    minimal_roi = {'0': 0.22, '37': 0.073, '86': 0.016, '195': 0}
    # Stoploss:
    stoploss = -0.148
    # Trailing stop:
    trailing_stop = True
    trailing_stop_positive = 0.068
    trailing_stop_positive_offset = 0.081
    trailing_only_offset_is_reached = True

    def __init__(self, config: dict) -> None:
        super().__init__(config)
        logger.info(f'Buy stratrategies: {STRAT_COMBINATIONS[self.entry_strategies.value]}')
        logger.info(f'Sell stratrategies: {STRAT_COMBINATIONS[self.exit_strategies.value]}')

    def informative_pairs(self):
        pairs = self.dp.current_whitelist()
        informative_pairs = [(pair, self.informative_timeframe) for pair in pairs]
        return informative_pairs

    def get_strategy(self, strategy_name):
        strategy = self.loaded_strategies.get(strategy_name)
        if not strategy:
            config = self.config
            config['strategy'] = strategy_name
            strategy = StrategyResolver.load_strategy(config)
        strategy.dp = self.dp
        strategy.wallets = self.wallets
        self.loaded_strategies[strategy_name] = strategy
        return strategy

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # TODO: move all strats signals to here, add mean and difference mean for entry and exit
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        strategies = STRAT_COMBINATIONS[self.entry_strategies.value]
        for strategy_name in strategies:
            strategy = self.get_strategy(strategy_name)
            try:
                strategy_indicators = strategy.advise_indicators(dataframe, metadata)
                dataframe[f'strat_entry_signal_{strategy_name}'] = strategy.advise_entry(strategy_indicators, metadata)['enter_long']
            except Exception:
                pass
        dataframe['enter_long'] = (dataframe.filter(like='strat_entry_signal_').fillna(0).mean(axis=1) > self.entry_mean_threshold.value).astype(int)
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe['exit_long'] = 0
        return dataframe

    def custom_exit(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float, current_profit: float, **kwargs) -> float:
        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
        last_candle = dataframe.iloc[-1].squeeze()
        if last_candle is not None:
            strategies = STRAT_COMBINATIONS[self.exit_strategies.value]
            metadata = {'pair': pair}
            for strategy_name in strategies:
                strategy = self.get_strategy(strategy_name)
                try:
                    strategy_indicators = strategy.advise_indicators(dataframe, metadata)
                    dataframe[f'strat_exit_signal_{strategy_name}'] = strategy.advise_exit(strategy_indicators, metadata)['exit_long']
                except Exception:
                    pass
            dataframe['exit_long'] = (dataframe.filter(like='strat_exit_signal_').fillna(0).mean(axis=1) > self.exit_mean_threshold.value).astype(int)
            last_candle = dataframe.iloc[-1].squeeze()
            return last_candle.exit
        return None