Decouple strategy from analyse.py

freqtrade/strategy/interface.py

@@ -0,0 +1,56 @@
+from abc import ABC, abstractmethod
+from pandas import DataFrame
+from typing import Dict
+
+
+class IStrategy(ABC):
+    @property
+    def name(self) -> str:
+        """
+        Name of the strategy.
+        :return: str representation of the class name
+        """
+        return self.__class__.__name__
+
+    """
+    Attributes you can use:
+        minimal_roi -> Dict: Minimal ROI designed for the strategy
+        stoploss -> float: ptimal stoploss designed for the strategy
+    """
+
+    @abstractmethod
+    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+        """
+        Populate indicators that will be used in the Buy and Sell strategy
+        :param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
+        :return: a Dataframe with all mandatory indicators for the strategies
+        """
+
+    @abstractmethod
+    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+        """
+        Based on TA indicators, populates the buy signal for the given dataframe
+        :param dataframe: DataFrame
+        :return: DataFrame with buy column
+        :return:
+        """
+
+    @abstractmethod
+    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+        """
+        Based on TA indicators, populates the sell signal for the given dataframe
+        :param dataframe: DataFrame
+        :return: DataFrame with buy column
+        """
+
+    @abstractmethod
+    def hyperopt_space(self) -> Dict:
+        """
+        Define your Hyperopt space for the strategy
+        """
+
+    @abstractmethod
+    def buy_strategy_generator(self, params) -> None:
+        """
+        Define the buy strategy parameters to be used by hyperopt
+        """