feat: add buy signal name

freqtrade/enums/__init__.py

@@ -2,5 +2,5 @@
 from freqtrade.enums.rpcmessagetype import RPCMessageType
 from freqtrade.enums.runmode import NON_UTIL_MODES, OPTIMIZE_MODES, TRADING_MODES, RunMode
 from freqtrade.enums.selltype import SellType
-from freqtrade.enums.signaltype import SignalType
+from freqtrade.enums.signaltype import SignalType, SignalNameType
 from freqtrade.enums.state import State

freqtrade/enums/signaltype.py

@@ -7,3 +7,10 @@ class SignalType(Enum):
     """
     BUY = "buy"
     SELL = "sell"
+
+
+class SignalNameType(Enum):
+    """
+    Enum to distinguish between buy and sell signals
+    """
+    BUY_SIGNAL_NAME = "buy_signal_name"

freqtrade/freqtradebot.py

@@ -420,7 +420,7 @@ class FreqtradeBot(LoggingMixin):
             return False
 
         # running get_signal on historical data fetched
-        (buy, sell) = self.strategy.get_signal(pair, self.strategy.timeframe, analyzed_df)
+        (buy, sell, buy_signal_name) = self.strategy.get_signal(pair, self.strategy.timeframe, analyzed_df)
 
         if buy and not sell:
             stake_amount = self.wallets.get_trade_stake_amount(pair, self.edge)
@@ -435,11 +435,11 @@ class FreqtradeBot(LoggingMixin):
             if ((bid_check_dom.get('enabled', False)) and
                     (bid_check_dom.get('bids_to_ask_delta', 0) > 0)):
                 if self._check_depth_of_market_buy(pair, bid_check_dom):
-                    return self.execute_buy(pair, stake_amount)
+                    return self.execute_buy(pair, stake_amount, buy_signal_name=buy_signal_name)
                 else:
                     return False
 
-            return self.execute_buy(pair, stake_amount)
+            return self.execute_buy(pair, stake_amount, buy_signal_name=buy_signal_name)
         else:
             return False
 
@@ -468,7 +468,7 @@ class FreqtradeBot(LoggingMixin):
             return False
 
     def execute_buy(self, pair: str, stake_amount: float, price: Optional[float] = None,
-                    forcebuy: bool = False) -> bool:
+                    forcebuy: bool = False, buy_signal_name: str = '') -> bool:
         """
         Executes a limit buy for the given pair
         :param pair: pair for which we want to create a LIMIT_BUY
@@ -562,6 +562,7 @@ class FreqtradeBot(LoggingMixin):
             exchange=self.exchange.id,
             open_order_id=order_id,
             strategy=self.strategy.get_strategy_name(),
+            buy_signal_name=buy_signal_name,
             timeframe=timeframe_to_minutes(self.config['timeframe'])
         )
         trade.orders.append(order_obj)

freqtrade/optimize/backtesting.py

@@ -42,6 +42,7 @@ CLOSE_IDX = 3
 SELL_IDX = 4
 LOW_IDX = 5
 HIGH_IDX = 6
+BUY_SIGNAL_NAME_IDX = 7
 
 
 class Backtesting:
@@ -189,7 +190,7 @@ class Backtesting:
         """
         # Every change to this headers list must evaluate further usages of the resulting tuple
         # and eventually change the constants for indexes at the top
-        headers = ['date', 'buy', 'open', 'close', 'sell', 'low', 'high']
+        headers = ['date', 'buy', 'open', 'close', 'sell', 'low', 'high', 'buy_signal_name']
         data: Dict = {}
         # Create dict with data
         for pair, pair_data in processed.items():
@@ -332,6 +333,7 @@ class Backtesting:
                 fee_open=self.fee,
                 fee_close=self.fee,
                 is_open=True,
+                buy_signal_name=row[BUY_SIGNAL_NAME_IDX],
                 exchange='backtesting',
             )
             return trade

freqtrade/persistence/models.py

@@ -257,6 +257,7 @@ class LocalTrade():
     sell_reason: str = ''
     sell_order_status: str = ''
     strategy: str = ''
+    buy_signal_name: str = ''
     timeframe: Optional[int] = None
 
     def __init__(self, **kwargs):
@@ -288,6 +289,7 @@ class LocalTrade():
             'amount_requested': round(self.amount_requested, 8) if self.amount_requested else None,
             'stake_amount': round(self.stake_amount, 8),
             'strategy': self.strategy,
+            'buy_signal_name': self.buy_signal_name,
             'timeframe': self.timeframe,
 
             'fee_open': self.fee_open,
@@ -703,6 +705,7 @@ class Trade(_DECL_BASE, LocalTrade):
     sell_reason = Column(String(100), nullable=True)
     sell_order_status = Column(String(100), nullable=True)
     strategy = Column(String(100), nullable=True)
+    buy_signal_name = Column(String(100), nullable=True)
     timeframe = Column(Integer, nullable=True)
 
     def __init__(self, **kwargs):

freqtrade/strategy/interface.py

@@ -13,7 +13,7 @@ from pandas import DataFrame
 
 from freqtrade.constants import ListPairsWithTimeframes
 from freqtrade.data.dataprovider import DataProvider
-from freqtrade.enums import SellType, SignalType
+from freqtrade.enums import SellType, SignalType, SignalNameType
 from freqtrade.exceptions import OperationalException, StrategyError
 from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
 from freqtrade.exchange.exchange import timeframe_to_next_date
@@ -506,7 +506,9 @@ class IStrategy(ABC, HyperStrategyMixin):
             )
             return False, False
 
-        (buy, sell) = latest[SignalType.BUY.value] == 1, latest[SignalType.SELL.value] == 1
+        (buy, sell, buy_signal_name) = latest[SignalType.BUY.value] == 1,\
+            latest[SignalType.SELL.value] == 1,\
+            latest.get(SignalNameType.BUY_SIGNAL_NAME.value, '')
         logger.debug('trigger: %s (pair=%s) buy=%s sell=%s',
                      latest['date'], pair, str(buy), str(sell))
         timeframe_seconds = timeframe_to_seconds(timeframe)
@@ -514,8 +516,8 @@ class IStrategy(ABC, HyperStrategyMixin):
                                       current_time=datetime.now(timezone.utc),
                                       timeframe_seconds=timeframe_seconds,
                                       buy=buy):
-            return False, sell
+            return False, sell, buy_signal_name
-        return buy, sell
+        return buy, sell, buy_signal_name
 
     def ignore_expired_candle(self, latest_date: datetime, current_time: datetime,
                               timeframe_seconds: int, buy: bool):