Initial step towards implementing proposed code

freqtrade/pairlist/PerformanceFilter.py

@@ -0,0 +1,61 @@
+"""
+Performance pair list filter
+"""
+import logging
+import random
+from typing import Any, Dict, List
+
+import pandas as pd
+from pandas import DataFrame, Series
+
+from freqtrade.pairlist.IPairList import IPairList
+
+from freqtrade.persistence import Trade
+from datetime import timedelta, datetime, timezone
+
+logger = logging.getLogger(__name__)
+
+class PerformanceFilter(IPairList):
+
+    def __init__(self, exchange, pairlistmanager,
+                 config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+                 pairlist_pos: int) -> None:
+        super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
+
+
+    @property
+    def needstickers(self) -> bool:
+        """
+        Boolean property defining if tickers are necessary.
+        If no Pairlist requries tickers, an empty List is passed
+        as tickers argument to filter_pairlist
+        """
+        return False
+
+    def short_desc(self) -> str:
+        """
+        Short whitelist method description - used for startup-messages
+        """
+        return f"{self.name} - Sorting pairs by performance."
+
+    def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
+        """
+        Filters and sorts pairlist and returns the whitelist again.
+        Called on each bot iteration - please use internal caching if necessary
+        :param pairlist: pairlist to filter or sort
+        :param tickers: Tickers (from exchange.get_tickers()). May be cached.
+        :return: new whitelist
+        """
+
+        # Get the trading performance for pairs from database
+        perf = pd.DataFrame(Trade.get_overall_performance())
+        # update pairlist with values from performance dataframe
+        # set initial value for pairs with no trades to 0
+        # and sort the list using performance and count
+        list_df = pd.DataFrame({'pair':pairlist})
+        sorted_df = list_df.join(perf.set_index('pair'), on='pair')\
+            .fillna(0).sort_values(by=['profit', 'count'], ascending=False)
+        pairlist = sorted_df['pair'].tolist()
+        
+
+        return pairlist