67 lines
2.3 KiB
Python
67 lines
2.3 KiB
Python
"""
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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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import pandas as pd
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from freqtrade.persistence import Trade
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from freqtrade.plugins.pairlist.IPairList import IPairList
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logger = logging.getLogger(__name__)
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class PerformanceFilter(IPairList):
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@property
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def needstickers(self) -> bool:
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"""
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Boolean property defining if tickers are necessary.
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If no Pairlist requries tickers, an empty List is passed
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as tickers argument to filter_pairlist
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"""
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return False
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def short_desc(self) -> str:
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"""
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Short allowlist method description - used for startup-messages
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"""
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return f"{self.name} - Sorting pairs by performance."
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def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
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"""
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Filters and sorts pairlist and returns the allowlist again.
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Called on each bot iteration - please use internal caching if necessary
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:param pairlist: pairlist to filter or sort
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:param tickers: Tickers (from exchange.get_tickers()). May be cached.
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:return: new allowlist
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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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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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return pairlist
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# Skip performance-based sorting if no performance data is available
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if len(performance) == 0:
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return pairlist
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# Get pairlist from performance dataframe values
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list_df = pd.DataFrame({'pair': pairlist})
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# Set initial value for pairs with no trades to 0
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# Sort the list using:
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# - primarily performance (high to low)
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# - then count (low to high, so as to favor same performance with fewer trades)
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# - then pair name alphametically
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sorted_df = list_df.merge(performance, on='pair', how='left')\
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.fillna(0).sort_values(by=['count', 'pair'], ascending=True)\
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.sort_values(by=['profit'], ascending=False)
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pairlist = sorted_df['pair'].tolist()
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return pairlist
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