Merge branch 'hummingbot:master' into master

.coveragerc

@@ -30,6 +30,7 @@ omit =
         hummingbot/strategy/dev*
         hummingbot/user/user_balances.py
         hummingbot/connector/exchange/cube/cube_ws_protobufs/*
+        hummingbot/strategy_v2/backtesting/*
 dynamic_context = test_function
 branch = true
 

controllers/directional_trading/bollinger_v1.py

@@ -1,13 +1,11 @@
 from typing import List
 
-import pandas as pd
 import pandas_ta as ta  # noqa: F401
 from pydantic import Field, validator
 
 from hummingbot.client.config.config_data_types import ClientFieldData
-from hummingbot.client.ui.interface_utils import format_df_for_printout
-from hummingbot.data_feed.candles_feed.candles_factory import CandlesConfig
-from hummingbot.smart_components.controllers.directional_trading_controller_base import (
+from hummingbot.data_feed.candles_feed.data_types import CandlesConfig
+from hummingbot.strategy_v2.controllers.directional_trading_controller_base import (
     DirectionalTradingControllerBase,
     DirectionalTradingControllerConfigBase,
 )
@@ -68,7 +66,6 @@ def set_candles_trading_pair(cls, v, values):
 
 
 class BollingerV1Controller(DirectionalTradingControllerBase):
-
     def __init__(self, config: BollingerV1ControllerConfig, *args, **kwargs):
         self.config = config
         self.max_records = self.config.bb_length
@@ -81,27 +78,24 @@ def __init__(self, config: BollingerV1ControllerConfig, *args, **kwargs):
             )]
         super().__init__(config, *args, **kwargs)
 
-    def get_signal(self) -> int:
-        return self.get_processed_data()["signal"].iloc[-1]
-
-    def get_processed_data(self) -> pd.DataFrame:
+    async def update_processed_data(self):
         df = self.market_data_provider.get_candles_df(connector_name=self.config.candles_connector,
                                                       trading_pair=self.config.candles_trading_pair,
                                                       interval=self.config.interval,
                                                       max_records=self.max_records)
         # Add indicators
         df.ta.bbands(length=self.config.bb_length, std=self.config.bb_std, append=True)
+        bbp = df[f"BBP_{self.config.bb_length}_{self.config.bb_std}"]
 
         # Generate signal
-        long_condition = df[f"BBP_{self.config.bb_length}_{self.config.bb_std}"] < self.config.bb_long_threshold
-        short_condition = df[f"BBP_{self.config.bb_length}_{self.config.bb_std}"] > self.config.bb_short_threshold
+        long_condition = bbp < self.config.bb_long_threshold
+        short_condition = bbp > self.config.bb_short_threshold
 
         # Generate signal
         df["signal"] = 0
         df.loc[long_condition, "signal"] = 1
         df.loc[short_condition, "signal"] = -1
-        return df
 
-    def to_format_status(self) -> List[str]:
-        df = self.get_processed_data()
-        return [format_df_for_printout(df.tail(5), table_format="psql", )]
+        # Update processed data
+        self.processed_data["signal"] = df["signal"].iloc[-1]
+        self.processed_data["features"] = df

controllers/directional_trading/dman_v3.py

@@ -2,19 +2,18 @@
 from decimal import Decimal
 from typing import List, Optional, Tuple
 
-import pandas as pd
 import pandas_ta as ta  # noqa: F401
 from pydantic import Field, validator
 
 from hummingbot.client.config.config_data_types import ClientFieldData
 from hummingbot.core.data_type.common import TradeType
-from hummingbot.data_feed.candles_feed.candles_factory import CandlesConfig
-from hummingbot.smart_components.controllers.directional_trading_controller_base import (
+from hummingbot.data_feed.candles_feed.data_types import CandlesConfig
+from hummingbot.strategy_v2.controllers.directional_trading_controller_base import (
     DirectionalTradingControllerBase,
     DirectionalTradingControllerConfigBase,
 )
-from hummingbot.smart_components.executors.dca_executor.data_types import DCAExecutorConfig, DCAMode
-from hummingbot.smart_components.executors.position_executor.data_types import TrailingStop
+from hummingbot.strategy_v2.executors.dca_executor.data_types import DCAExecutorConfig, DCAMode
+from hummingbot.strategy_v2.executors.position_executor.data_types import TrailingStop
 
 
 class DManV3ControllerConfig(DirectionalTradingControllerConfigBase):
@@ -164,10 +163,7 @@ def __init__(self, config: DManV3ControllerConfig, *args, **kwargs):
             )]
         super().__init__(config, *args, **kwargs)
 
-    def get_signal(self) -> int:
-        return self.get_processed_data()["signal"].iloc[-1]
-
-    def get_processed_data(self) -> pd.DataFrame:
+    async def update_processed_data(self):
         df = self.market_data_provider.get_candles_df(connector_name=self.config.candles_connector,
                                                       trading_pair=self.config.candles_trading_pair,
                                                       interval=self.config.interval,
@@ -183,11 +179,14 @@ def get_processed_data(self) -> pd.DataFrame:
         df["signal"] = 0
         df.loc[long_condition, "signal"] = 1
         df.loc[short_condition, "signal"] = -1
-        return df
+
+        # Update processed data
+        self.processed_data["signal"] = df["signal"].iloc[-1]
+        self.processed_data["features"] = df
 
     def get_spread_multiplier(self) -> Decimal:
         if self.config.dynamic_order_spread:
-            df = self.get_processed_data()
+            df = self.processed_data["features"]
             bb_width = df[f"BBB_{self.config.bb_length}_{self.config.bb_std}"].iloc[-1]
             return Decimal(bb_width / 200)
         else:

controllers/directional_trading/macd_bb_v1.py

@@ -1,13 +1,11 @@
 from typing import List
 
-import pandas as pd
 import pandas_ta as ta  # noqa: F401
 from pydantic import Field, validator
 
 from hummingbot.client.config.config_data_types import ClientFieldData
-from hummingbot.client.ui.interface_utils import format_df_for_printout
-from hummingbot.data_feed.candles_feed.candles_factory import CandlesConfig
-from hummingbot.smart_components.controllers.directional_trading_controller_base import (
+from hummingbot.data_feed.candles_feed.data_types import CandlesConfig
+from hummingbot.strategy_v2.controllers.directional_trading_controller_base import (
     DirectionalTradingControllerBase,
     DirectionalTradingControllerConfigBase,
 )
@@ -96,10 +94,7 @@ def __init__(self, config: MACDBBV1ControllerConfig, *args, **kwargs):
             )]
         super().__init__(config, *args, **kwargs)
 
-    def get_signal(self) -> int:
-        return self.get_processed_data()["signal"].iloc[-1]
-
-    def get_processed_data(self) -> pd.DataFrame:
+    async def update_processed_data(self):
         df = self.market_data_provider.get_candles_df(connector_name=self.config.candles_connector,
                                                       trading_pair=self.config.candles_trading_pair,
                                                       interval=self.config.interval,
@@ -120,8 +115,6 @@ def get_processed_data(self) -> pd.DataFrame:
         df.loc[long_condition, "signal"] = 1
         df.loc[short_condition, "signal"] = -1
 
-        return df
-
-    def to_format_status(self) -> List[str]:
-        df = self.get_processed_data()
-        return [format_df_for_printout(df.tail(5), table_format="psql",)]
+        # Update processed data
+        self.processed_data["signal"] = df["signal"].iloc[-1]
+        self.processed_data["features"] = df

controllers/directional_trading/supertrend_v1.py

@@ -0,0 +1,70 @@
+from typing import List, Optional
+
+import pandas_ta as ta  # noqa: F401
+from pydantic import Field, validator
+
+from hummingbot.client.config.config_data_types import ClientFieldData
+from hummingbot.data_feed.candles_feed.data_types import CandlesConfig
+from hummingbot.strategy_v2.controllers.directional_trading_controller_base import (
+    DirectionalTradingControllerBase,
+    DirectionalTradingControllerConfigBase,
+)
+
+
+class SuperTrendConfig(DirectionalTradingControllerConfigBase):
+    controller_name: str = "supertrend_v1"
+    candles_config: List[CandlesConfig] = []
+    candles_connector: Optional[str] = Field(default=None, client_data=ClientFieldData(prompt_on_new=True, prompt=lambda mi: "Enter the connector for the candles data, leave empty to use the same exchange as the connector: ", ))
+    candles_trading_pair: Optional[str] = Field(default=None, client_data=ClientFieldData(prompt_on_new=True, prompt=lambda mi: "Enter the trading pair for the candles data, leave empty to use the same trading pair as the connector: ", ))
+    interval: str = Field(default="3m", client_data=ClientFieldData(prompt=lambda mi: "Enter the candle interval (e.g., 1m, 5m, 1h, 1d): ", prompt_on_new=False))
+    length: int = Field(default=20, client_data=ClientFieldData(prompt=lambda mi: "Enter the supertrend length: ", prompt_on_new=True))
+    multiplier: float = Field(default=4.0, client_data=ClientFieldData(prompt=lambda mi: "Enter the supertrend multiplier: ", prompt_on_new=True))
+    percentage_threshold: float = Field(default=0.01, client_data=ClientFieldData(prompt=lambda mi: "Enter the percentage threshold: ", prompt_on_new=True))
+
+    @validator("candles_connector", pre=True, always=True)
+    def set_candles_connector(cls, v, values):
+        if v is None or v == "":
+            return values.get("connector_name")
+        return v
+
+    @validator("candles_trading_pair", pre=True, always=True)
+    def set_candles_trading_pair(cls, v, values):
+        if v is None or v == "":
+            return values.get("trading_pair")
+        return v
+
+
+class SuperTrend(DirectionalTradingControllerBase):
+    def __init__(self, config: SuperTrendConfig, *args, **kwargs):
+        self.config = config
+        self.max_records = config.length + 10
+        if len(self.config.candles_config) == 0:
+            self.config.candles_config = [CandlesConfig(
+                connector=config.candles_connector,
+                trading_pair=config.candles_trading_pair,
+                interval=config.interval,
+                max_records=self.max_records
+            )]
+        super().__init__(config, *args, **kwargs)
+
+    async def update_processed_data(self):
+        df = self.market_data_provider.get_candles_df(connector_name=self.config.candles_connector,
+                                                      trading_pair=self.config.candles_trading_pair,
+                                                      interval=self.config.interval,
+                                                      max_records=self.max_records)
+        # Add indicators
+        df.ta.supertrend(length=self.config.length, multiplier=self.config.multiplier, append=True)
+        df["percentage_distance"] = abs(df["close"] - df[f"SUPERT_{self.config.length}_{self.config.multiplier}"]) / df["close"]
+
+        # Generate long and short conditions
+        long_condition = (df[f"SUPERTd_{self.config.length}_{self.config.multiplier}"] == 1) & (df["percentage_distance"] < self.config.percentage_threshold)
+        short_condition = (df[f"SUPERTd_{self.config.length}_{self.config.multiplier}"] == -1) & (df["percentage_distance"] < self.config.percentage_threshold)
+
+        # Choose side
+        df['signal'] = 0
+        df.loc[long_condition, 'signal'] = 1
+        df.loc[short_condition, 'signal'] = -1
+
+        # Update processed data
+        self.processed_data["signal"] = df["signal"].iloc[-1]
+        self.processed_data["features"] = df