add strategy to the freqai object
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@ -142,7 +142,7 @@ class BaseReinforcementLearningModel(IFreqaiModel):
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current_profit = 0
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current_profit = 0
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for trade in open_trades:
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for trade in open_trades:
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if trade.pair == pair:
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if trade.pair == pair:
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current_value = self.strategy.dp._exchange.get_rate(pair, refresh=False)
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current_value = self.strategy.dp._exchange.get_rate(pair, refresh=False) #, side="buy", is_short=True)
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openrate = trade.open_rate
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openrate = trade.open_rate
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if 'long' in trade.enter_tag:
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if 'long' in trade.enter_tag:
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market_side = 1
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market_side = 1
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@ -7,7 +7,7 @@ import time
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from abc import ABC, abstractmethod
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from abc import ABC, abstractmethod
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from pathlib import Path
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from pathlib import Path
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from threading import Lock
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from threading import Lock
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from typing import Any, Dict, Tuple
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from typing import Any, Dict, Tuple, Optional
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import numpy as np
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import numpy as np
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import pandas as pd
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import pandas as pd
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@ -90,6 +90,7 @@ class IFreqaiModel(ABC):
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self.begin_time: float = 0
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self.begin_time: float = 0
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self.begin_time_train: float = 0
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self.begin_time_train: float = 0
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self.base_tf_seconds = timeframe_to_seconds(self.config['timeframe'])
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self.base_tf_seconds = timeframe_to_seconds(self.config['timeframe'])
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self.strategy: Optional[IStrategy] = None
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def assert_config(self, config: Dict[str, Any]) -> None:
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def assert_config(self, config: Dict[str, Any]) -> None:
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@ -152,6 +152,7 @@ class IStrategy(ABC, HyperStrategyMixin):
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self.freqai = FreqaiModelResolver.load_freqaimodel(self.config)
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self.freqai = FreqaiModelResolver.load_freqaimodel(self.config)
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self.freqai_info = self.config["freqai"]
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self.freqai_info = self.config["freqai"]
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self.freqai.strategy = self
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else:
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else:
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# Gracious failures if freqAI is disabled but "start" is called.
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# Gracious failures if freqAI is disabled but "start" is called.
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class DummyClass():
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class DummyClass():
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