minor optimizations

freqtrade/analyze.py

@@ -65,7 +65,7 @@ class Analyze(object):
         frame.drop(frame.tail(1).index, inplace=True)  # eliminate partial candle
         return frame
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, pair: str = None) -> DataFrame:
         """
         Adds several different TA indicators to the given DataFrame
 
@@ -73,23 +73,23 @@ class Analyze(object):
         you are using. Let uncomment only the indicator you are using in your strategies
         or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
         """
-        return self.strategy.populate_indicators(dataframe=dataframe)
+        return self.strategy.advise_indicators(dataframe=dataframe, pair=pair)
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, pair: str = None) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
         :return: DataFrame with buy column
         """
-        return self.strategy.populate_buy_trend(dataframe=dataframe)
+        return self.strategy.advise_buy(dataframe=dataframe, pair=pair)
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, pair: str = None) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame
         :return: DataFrame with buy column
         """
-        return self.strategy.populate_sell_trend(dataframe=dataframe)
+        return self.strategy.advise_sell(dataframe=dataframe, pair=pair)
 
     def get_ticker_interval(self) -> str:
         """
@@ -98,16 +98,17 @@ class Analyze(object):
         """
         return self.strategy.ticker_interval
 
-    def analyze_ticker(self, ticker_history: List[Dict]) -> DataFrame:
+    def analyze_ticker(self, ticker_history: List[Dict], pair: str) -> DataFrame:
         """
         Parses the given ticker history and returns a populated DataFrame
         add several TA indicators and buy signal to it
         :return DataFrame with ticker data and indicator data
         """
+
         dataframe = self.parse_ticker_dataframe(ticker_history)
-        dataframe = self.populate_indicators(dataframe)
-        dataframe = self.populate_buy_trend(dataframe)
-        dataframe = self.populate_sell_trend(dataframe)
+        dataframe = self.populate_indicators(dataframe, pair)
+        dataframe = self.populate_buy_trend(dataframe, pair)
+        dataframe = self.populate_sell_trend(dataframe, pair)
         return dataframe
 
     def get_signal(self, pair: str, interval: str) -> Tuple[bool, bool]:
@@ -123,7 +124,7 @@ class Analyze(object):
             return False, False
 
         try:
-            dataframe = self.analyze_ticker(ticker_hist)
+            dataframe = self.analyze_ticker(ticker_hist, pair)
         except ValueError as error:
             logger.warning(
                 'Unable to analyze ticker for pair %s: %s',

freqtrade/strategy/interface.py

@@ -6,7 +6,7 @@ from typing import Dict
 from abc import ABC, abstractmethod
 
 from pandas import DataFrame
-
+import warnings
 
 class IStrategy(ABC):
     """
@@ -19,30 +19,80 @@ class IStrategy(ABC):
         ticker_interval -> str: value of the ticker interval to use for the strategy
     """
 
+    # associated minimal roi
     minimal_roi: Dict
+
+    # associated stoploss
     stoploss: float
+
+    # associated ticker interval
     ticker_interval: str
 
-    @abstractmethod
+    # configuration used, just in case the strategy want's to use it for something
+    config: dict = {}
+
     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
         """
+        warnings.warn("deprecated - please replace this method with advise_indicators!", DeprecationWarning)
+        return dataframe
 
-    @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
         """
+        warnings.warn("deprecated - please replace this method with advise_buy!", DeprecationWarning)
+        dataframe.loc[
+            (
+            ),
+            'buy'] = 0
+        return dataframe
 
-    @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 sell column
         """
+        warnings.warn("deprecated - please replace this method with advise_sell!", DeprecationWarning)
+        dataframe.loc[
+            (
+            ),
+            'sell'] = 0
+        return dataframe
+
+    def advise_indicators(self, dataframe: DataFrame, pair: str) -> DataFrame:
+        """
+
+        This wraps around the internal method
+
+        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()
+        :param pair: The currently traded pair
+        :return: a Dataframe with all mandatory indicators for the strategies
+        """
+        return self.populate_indicators(dataframe)
+
+    def advise_buy(self, dataframe: DataFrame, pair: str) -> DataFrame:
+        """
+        Based on TA indicators, populates the buy signal for the given dataframe
+        :param dataframe: DataFrame
+        :param pair: The currently traded pair
+        :return: DataFrame with buy column
+        """
+
+        return self.populate_buy_trend(dataframe)
+
+    def advise_sell(self, dataframe: DataFrame, pair: str) -> DataFrame:
+        """
+        Based on TA indicators, populates the sell signal for the given dataframe
+        :param dataframe: DataFrame
+        :param pair: The currently traded pair
+        :return: DataFrame with sell column
+        """
+        return self.populate_sell_trend(dataframe)

freqtrade/strategy/resolver.py

@@ -40,6 +40,8 @@ class StrategyResolver(object):
         self.strategy: IStrategy = self._load_strategy(strategy_name,
                                                        extra_dir=config.get('strategy_path'))
 
+        self.strategy.config = config
+
         # Set attributes
         # Check if we need to override configuration
         if 'minimal_roi' in config:

freqtrade/tests/test_dataframe.py

@@ -16,7 +16,7 @@ def load_dataframe_pair(pairs):
     dataframe = ld[pairs[0]]
 
     analyze = Analyze({'strategy': 'DefaultStrategy'})
-    dataframe = analyze.analyze_ticker(dataframe)
+    dataframe = analyze.analyze_ticker(dataframe, pairs[0])
     return dataframe