Added days parameter to PerformanceFilter
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@ -2,7 +2,7 @@
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This module contains the class to persist trades into SQLite
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"""
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import logging
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from datetime import datetime, timezone
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from datetime import datetime, timezone, timedelta
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from decimal import Decimal
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from typing import Any, Dict, List, Optional
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@ -856,6 +856,32 @@ class Trade(_DECL_BASE, LocalTrade):
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for pair, profit, profit_abs, count in pair_rates
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]
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@staticmethod
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def get_performance(days: int) -> List[Dict[str, Any]]:
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"""
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Returns List of dicts containing all Trades, including profit and trade count
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NOTE: Not supported in Backtesting.
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"""
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start_date = datetime.today() - timedelta(days)
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pair_rates = Trade.query.with_entities(
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Trade.pair,
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func.sum(Trade.close_profit).label('profit_sum'),
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func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
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func.count(Trade.pair).label('count')
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).filter(Trade.is_open.is_(False) & (Trade.close_date >= start_date))\
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.group_by(Trade.pair) \
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.order_by(desc('profit_sum_abs')) \
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.all()
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return [
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{
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'pair': pair,
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'profit': profit,
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'profit_abs': profit_abs,
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'count': count
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}
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for pair, profit, profit_abs, count in pair_rates
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]
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@staticmethod
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def get_best_pair(start_date: datetime = datetime.fromtimestamp(0)):
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"""
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@ -2,11 +2,12 @@
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Performance pair list filter
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"""
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import logging
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from typing import Dict, List
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from typing import Dict, List, Any
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import pandas as pd
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from freqtrade.persistence import Trade
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from freqtrade.exceptions import OperationalException
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from freqtrade.plugins.pairlist.IPairList import IPairList
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@ -15,6 +16,13 @@ logger = logging.getLogger(__name__)
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class PerformanceFilter(IPairList):
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def __init__(self, exchange, pairlistmanager,
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config: Dict[str, Any], pairlistconfig: Dict[str, Any],
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pairlist_pos: int) -> None:
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super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
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self._days = pairlistconfig.get('days', 0)
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@property
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def needstickers(self) -> bool:
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"""
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@ -40,7 +48,10 @@ class PerformanceFilter(IPairList):
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"""
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# Get the trading performance for pairs from database
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try:
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performance = pd.DataFrame(Trade.get_overall_performance())
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if self._days > 0:
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performance = pd.DataFrame(Trade.get_performance(self._days))
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else:
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performance = pd.DataFrame(Trade.get_overall_performance())
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except AttributeError:
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# Performancefilter does not work in backtesting.
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self.log_once("PerformanceFilter is not available in this mode.", logger.warning)
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