rename to buy_tag

docs/strategy-advanced.md

@@ -114,7 +114,7 @@ class AwesomeStrategy(IStrategy):
 
 See [Dataframe access](#dataframe-access) for more information about dataframe use in strategy callbacks.
 
-## Buy Signal Name
+## Buy Tag
 
 When your strategy has multiple buy signal, you can name it.
 Then you can access you buy signal on `custom_sell`
@@ -126,7 +126,7 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
             (dataframe['rsi'] < 35) &
             (dataframe['volume'] > 0)
         ),
-        ['buy', 'buy_signal_name']] = 1, 'buy_signal_rsi'
+        ['buy', 'buy_tag']] = 1, 'buy_signal_rsi'
 
     return dataframe
 
@@ -134,7 +134,7 @@ def custom_sell(self, pair: str, trade: Trade, current_time: datetime, current_r
                     current_profit: float, **kwargs):
     dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
     last_candle = dataframe.iloc[-1].squeeze()
-    if trade.buy_signal_name == 'buy_signal_rsi' and last_candle['rsi'] > 80:
+    if trade.buy_tag == 'buy_signal_rsi' and last_candle['rsi'] > 80:
         return 'sell_signal_rsi'
     return None
 

freqtrade/data/btanalysis.py

@@ -30,7 +30,7 @@ BT_DATA_COLUMNS = ['pair', 'stake_amount', 'amount', 'open_date', 'close_date',
                    'fee_open', 'fee_close', 'trade_duration',
                    'profit_ratio', 'profit_abs', 'sell_reason',
                    'initial_stop_loss_abs', 'initial_stop_loss_ratio', 'stop_loss_abs',
-                   'stop_loss_ratio', 'min_rate', 'max_rate', 'is_open', 'buy_signal_name']
+                   'stop_loss_ratio', 'min_rate', 'max_rate', 'is_open', 'buy_tag']
 
 
 def get_latest_optimize_filename(directory: Union[Path, str], variant: str) -> str:

freqtrade/enums/__init__.py

@@ -3,5 +3,5 @@ from freqtrade.enums.backteststate import BacktestState
 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 SignalNameType, SignalType
+from freqtrade.enums.signaltype import SignalTagType, SignalType
 from freqtrade.enums.state import State

freqtrade/enums/signaltype.py

@@ -9,8 +9,8 @@ class SignalType(Enum):
     SELL = "sell"
 
 
-class SignalNameType(Enum):
+class SignalTagType(Enum):
     """
     Enum for signal columns
     """
-    BUY_SIGNAL_NAME = "buy_signal_name"
+    BUY_TAG = "buy_tag"

freqtrade/freqtradebot.py

@@ -420,7 +420,7 @@ class FreqtradeBot(LoggingMixin):
             return False
 
         # running get_signal on historical data fetched
-        (buy, sell, buy_signal_name) = self.strategy.get_signal(
+        (buy, sell, buy_tag) = self.strategy.get_signal(
             pair,
             self.strategy.timeframe,
             analyzed_df
@@ -433,11 +433,11 @@ 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, buy_signal_name=buy_signal_name)
+                    return self.execute_buy(pair, stake_amount, buy_tag=buy_tag)
                 else:
                     return False
 
-            return self.execute_buy(pair, stake_amount, buy_signal_name=buy_signal_name)
+            return self.execute_buy(pair, stake_amount, buy_tag=buy_tag)
         else:
             return False
 
@@ -466,7 +466,7 @@ class FreqtradeBot(LoggingMixin):
             return False
 
     def execute_buy(self, pair: str, stake_amount: float, price: Optional[float] = None,
-                    forcebuy: bool = False, buy_signal_name: str = '') -> bool:
+                    forcebuy: bool = False, buy_tag: str = '') -> bool:
         """
         Executes a limit buy for the given pair
         :param pair: pair for which we want to create a LIMIT_BUY
@@ -569,7 +569,7 @@ class FreqtradeBot(LoggingMixin):
             exchange=self.exchange.id,
             open_order_id=order_id,
             strategy=self.strategy.get_strategy_name(),
-            buy_signal_name=buy_signal_name,
+            buy_tag=buy_tag,
             timeframe=timeframe_to_minutes(self.config['timeframe'])
         )
         trade.orders.append(order_obj)

freqtrade/optimize/backtesting.py

@@ -43,7 +43,7 @@ CLOSE_IDX = 3
 SELL_IDX = 4
 LOW_IDX = 5
 HIGH_IDX = 6
-BUY_SIGNAL_NAME_IDX = 7
+buy_tag_IDX = 7
 
 
 class Backtesting:
@@ -210,7 +210,7 @@ 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', 'buy_signal_name']
+        headers = ['date', 'buy', 'open', 'close', 'sell', 'low', 'high', 'buy_tag']
         data: Dict = {}
         self.progress.init_step(BacktestState.CONVERT, len(processed))
 
@@ -221,7 +221,7 @@ class Backtesting:
             if not pair_data.empty:
                 pair_data.loc[:, 'buy'] = 0  # cleanup if buy_signal is exist
                 pair_data.loc[:, 'sell'] = 0  # cleanup if sell_signal is exist
-                pair_data.loc[:, 'buy_signal_name'] = ''  # cleanup if buy_signal_name is exist
+                pair_data.loc[:, 'buy_tag'] = ''  # cleanup if buy_tag is exist
 
             df_analyzed = self.strategy.advise_sell(
                 self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()
@@ -230,7 +230,7 @@ class Backtesting:
             # from the previous candle
             df_analyzed.loc[:, 'buy'] = df_analyzed.loc[:, 'buy'].shift(1)
             df_analyzed.loc[:, 'sell'] = df_analyzed.loc[:, 'sell'].shift(1)
-            df_analyzed.loc[:, 'buy_signal_name'] = df_analyzed.loc[:, 'buy_signal_name'].shift(1)
+            df_analyzed.loc[:, 'buy_tag'] = df_analyzed.loc[:, 'buy_tag'].shift(1)
 
             df_analyzed.drop(df_analyzed.head(1).index, inplace=True)
 
@@ -370,7 +370,7 @@ class Backtesting:
                 fee_open=self.fee,
                 fee_close=self.fee,
                 is_open=True,
-                buy_signal_name=row[BUY_SIGNAL_NAME_IDX],
+                buy_tag=row[buy_tag_IDX],
                 exchange='backtesting',
             )
             return trade

freqtrade/persistence/migrations.py

@@ -47,7 +47,7 @@ def migrate_trades_table(decl_base, inspector, engine, table_back_name: str, col
     min_rate = get_column_def(cols, 'min_rate', 'null')
     sell_reason = get_column_def(cols, 'sell_reason', 'null')
     strategy = get_column_def(cols, 'strategy', 'null')
-    buy_signal_name = get_column_def(cols, 'buy_signal_name', 'null')
+    buy_tag = get_column_def(cols, 'buy_tag', 'null')
     # If ticker-interval existed use that, else null.
     if has_column(cols, 'ticker_interval'):
         timeframe = get_column_def(cols, 'timeframe', 'ticker_interval')
@@ -81,7 +81,7 @@ def migrate_trades_table(decl_base, inspector, engine, table_back_name: str, col
             stake_amount, amount, amount_requested, open_date, close_date, open_order_id,
             stop_loss, stop_loss_pct, initial_stop_loss, initial_stop_loss_pct,
             stoploss_order_id, stoploss_last_update,
-            max_rate, min_rate, sell_reason, sell_order_status, strategy, buy_signal_name,
+            max_rate, min_rate, sell_reason, sell_order_status, strategy, buy_tag,
             timeframe, open_trade_value, close_profit_abs
             )
         select id, lower(exchange),
@@ -104,7 +104,7 @@ def migrate_trades_table(decl_base, inspector, engine, table_back_name: str, col
             {stoploss_order_id} stoploss_order_id, {stoploss_last_update} stoploss_last_update,
             {max_rate} max_rate, {min_rate} min_rate, {sell_reason} sell_reason,
             {sell_order_status} sell_order_status,
-            {strategy} strategy, {buy_signal_name} buy_signal_name, {timeframe} timeframe,
+            {strategy} strategy, {buy_tag} buy_tag, {timeframe} timeframe,
             {open_trade_value} open_trade_value, {close_profit_abs} close_profit_abs
             from {table_back_name}
             """))
@@ -168,7 +168,7 @@ def check_migrate(engine, decl_base, previous_tables) -> None:
         inspector = inspect(engine)
         cols = inspector.get_columns('trades')
 
-    if not has_column(cols, 'buy_signal_name'):
+    if not has_column(cols, 'buy_tag'):
         logger.info(f'Running database migration for trades - backup: {table_back_name}')
         migrate_trades_table(decl_base, inspector, engine, table_back_name, cols)
         # Reread columns - the above recreated the table!

freqtrade/persistence/models.py

@@ -257,7 +257,7 @@ class LocalTrade():
     sell_reason: str = ''
     sell_order_status: str = ''
     strategy: str = ''
-    buy_signal_name: str = ''
+    buy_tag: str = ''
     timeframe: Optional[int] = None
 
     def __init__(self, **kwargs):
@@ -289,7 +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,
+            'buy_tag': self.buy_tag,
             'timeframe': self.timeframe,
 
             'fee_open': self.fee_open,
@@ -705,7 +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)
+    buy_tag = 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, SignalNameType, SignalType
+from freqtrade.enums import SellType, SignalTagType, SignalType
 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
@@ -422,7 +422,7 @@ class IStrategy(ABC, HyperStrategyMixin):
             logger.debug("Skipping TA Analysis for already analyzed candle")
             dataframe['buy'] = 0
             dataframe['sell'] = 0
-            dataframe['buy_signal_name'] = ''
+            dataframe['buy_tag'] = ''
 
         # Other Defs in strategy that want to be called every loop here
         # twitter_sell = self.watch_twitter_feed(dataframe, metadata)
@@ -525,9 +525,9 @@ class IStrategy(ABC, HyperStrategyMixin):
             )
             return False, False, ''
 
-        (buy, sell, buy_signal_name) = latest[SignalType.BUY.value] == 1,\
+        (buy, sell, buy_tag) = latest[SignalType.BUY.value] == 1,\
             latest[SignalType.SELL.value] == 1,\
-            latest.get(SignalNameType.BUY_SIGNAL_NAME.value, '')
+            latest.get(SignalTagType.BUY_TAG.value, '')
         logger.debug('trigger: %s (pair=%s) buy=%s sell=%s',
                      latest['date'], pair, str(buy), str(sell))
         timeframe_seconds = timeframe_to_seconds(timeframe)
@@ -535,8 +535,8 @@ class IStrategy(ABC, HyperStrategyMixin):
                                       current_time=datetime.now(timezone.utc),
                                       timeframe_seconds=timeframe_seconds,
                                       buy=buy):
-            return False, sell, buy_signal_name
+            return False, sell, buy_tag
-        return buy, sell, buy_signal_name
+        return buy, sell, buy_tag
 
     def ignore_expired_candle(self, latest_date: datetime, current_time: datetime,
                               timeframe_seconds: int, buy: bool):

tests/optimize/__init__.py

@@ -18,7 +18,7 @@ class BTrade(NamedTuple):
     sell_reason: SellType
     open_tick: int
     close_tick: int
-    buy_signal_name: Optional[str] = ''
+    buy_tag: Optional[str] = ''
 
 
 class BTContainer(NamedTuple):
@@ -44,7 +44,7 @@ def _get_frame_time_from_offset(offset):
 
 
 def _build_backtest_dataframe(data):
-    columns = ['date', 'open', 'high', 'low', 'close', 'volume', 'buy', 'sell', 'buy_signal_name']
+    columns = ['date', 'open', 'high', 'low', 'close', 'volume', 'buy', 'sell', 'buy_tag']
 
     frame = DataFrame.from_records(data, columns=columns)
     frame['date'] = frame['date'].apply(_get_frame_time_from_offset)

tests/optimize/test_backtest_detail.py

@@ -532,7 +532,7 @@ tc33 = BTContainer(data=[
         sell_reason=SellType.TRAILING_STOP_LOSS,
         open_tick=1,
         close_tick=1,
-        buy_signal_name='buy_signal_01'
+        buy_tag='buy_signal_01'
     )]
 )
 
@@ -619,6 +619,6 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
     for c, trade in enumerate(data.trades):
         res = results.iloc[c]
         assert res.sell_reason == trade.sell_reason.value
-        assert res.buy_signal_name == trade.buy_signal_name
+        assert res.buy_tag == trade.buy_tag
         assert res.open_date == _get_frame_time_from_offset(trade.open_tick)
         assert res.close_date == _get_frame_time_from_offset(trade.close_tick)

tests/optimize/test_backtesting.py

@@ -584,7 +584,7 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
          'min_rate': [0.1038, 0.10302485],
          'max_rate': [0.10501, 0.1038888],
          'is_open': [False, False],
-         'buy_signal_name': ['', ''],
+         'buy_tag': ['', ''],
          })
     pd.testing.assert_frame_equal(results, expected)
     data_pair = processed[pair]

tests/rpc/test_rpc.py

@@ -69,7 +69,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
         'min_rate': ANY,
         'max_rate': ANY,
         'strategy': ANY,
-        'buy_signal_name': ANY,
+        'buy_tag': ANY,
         'timeframe': 5,
         'open_order_id': ANY,
         'close_date': None,
@@ -136,7 +136,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
         'min_rate': ANY,
         'max_rate': ANY,
         'strategy': ANY,
-        'buy_signal_name': ANY,
+        'buy_tag': ANY,
         'timeframe': ANY,
         'open_order_id': ANY,
         'close_date': None,

tests/strategy/test_interface.py

@@ -49,7 +49,7 @@ def test_returns_latest_signal(mocker, default_conf, ohlcv_history):
     assert _STRATEGY.get_signal('ETH/BTC', '5m', mocked_history) == (False, False, '')
     mocked_history.loc[1, 'sell'] = 0
     mocked_history.loc[1, 'buy'] = 1
-    mocked_history.loc[1, 'buy_signal_name'] = 'buy_signal_01'
+    mocked_history.loc[1, 'buy_tag'] = 'buy_signal_01'
 
     assert _STRATEGY.get_signal('ETH/BTC', '5m', mocked_history) == (True, False, 'buy_signal_01')
 

tests/test_persistence.py

@@ -861,7 +861,7 @@ def test_to_json(default_conf, fee):
         open_date=arrow.utcnow().shift(hours=-2).datetime,
         open_rate=0.123,
         exchange='binance',
-        buy_signal_name='',
+        buy_tag='',
         open_order_id='dry_run_buy_12345'
     )
     result = trade.to_json()
@@ -911,7 +911,7 @@ def test_to_json(default_conf, fee):
                       'min_rate': None,
                       'max_rate': None,
                       'strategy': None,
-                      'buy_signal_name': '',
+                      'buy_tag': '',
                       'timeframe': None,
                       'exchange': 'binance',
                       }
@@ -928,7 +928,7 @@ def test_to_json(default_conf, fee):
         close_date=arrow.utcnow().shift(hours=-1).datetime,
         open_rate=0.123,
         close_rate=0.125,
-        buy_signal_name='buys_signal_001',
+        buy_tag='buys_signal_001',
         exchange='binance',
     )
     result = trade.to_json()
@@ -978,7 +978,7 @@ def test_to_json(default_conf, fee):
                       'sell_reason': None,
                       'sell_order_status': None,
                       'strategy': None,
-                      'buy_signal_name': 'buys_signal_001',
+                      'buy_tag': 'buys_signal_001',
                       'timeframe': None,
                       'exchange': 'binance',
                       }