Adding the pair name when populating indicators allowing the strategy to have customized context for a pair

docs/bot-optimization.md

@@ -51,7 +51,7 @@ update your buy strategy.
 
 Sample from `user_data/strategies/test_strategy.py`:  
 ```python
-def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+def populate_buy_trend(self, dataframe: DataFrame, pair : str) -> DataFrame:
     """
     Based on TA indicators, populates the buy signal for the given dataframe
     :param dataframe: DataFrame
@@ -74,7 +74,7 @@ update your sell strategy.
 
 Sample from `user_data/strategies/test_strategy.py`:  
 ```python
-def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+def populate_sell_trend(self, dataframe: DataFrame, pair : str) -> DataFrame:
     """
     Based on TA indicators, populates the sell signal for the given dataframe
     :param dataframe: DataFrame
@@ -97,7 +97,7 @@ the method `populate_indicators()` from your strategy file.
 
 Sample:
 ```python
-def populate_indicators(dataframe: DataFrame) -> DataFrame:
+def populate_indicators(dataframe: DataFrame, pair : str) -> DataFrame:
     """
     Adds several different TA indicators to the given DataFrame
     """

docs/hyperopt.md

@@ -42,7 +42,7 @@ If you have updated the buy strategy, means change the content of
 
 As for an example if your `populate_buy_trend()` method is:
 ```python
-def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
+def populate_buy_trend(dataframe: DataFrame, pair: str) -> DataFrame:
     dataframe.loc[
         (dataframe['rsi'] < 35) &
         (dataframe['adx'] > 65),
@@ -81,7 +81,7 @@ space = {
 
 ... 
 
-def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+def populate_buy_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
         conditions = []
         # GUARDS AND TRENDS
         if params['adx']['enabled']:
@@ -280,7 +280,7 @@ at `adx`-block, that translates to the following code block:
 So translating your whole hyperopt result to as the new buy-signal 
 would be the following:
 ```
-def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+def populate_buy_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
     dataframe.loc[
         (
             (dataframe['adx'] > 15.0) & # adx-value

freqtrade/analyze.py

@@ -37,7 +37,7 @@ def parse_ticker_dataframe(ticker: list) -> DataFrame:
     return frame
 
 
-def populate_indicators(dataframe: DataFrame) -> DataFrame:
+def populate_indicators(dataframe: DataFrame, pair: str) -> DataFrame:
     """
     Adds several different TA indicators to the given DataFrame
 
@@ -46,39 +46,39 @@ def populate_indicators(dataframe: DataFrame) -> DataFrame:
     or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
     """
     strategy = Strategy()
-    return strategy.populate_indicators(dataframe=dataframe)
+    return strategy.populate_indicators(dataframe=dataframe, pair=pair)
 
 
-def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
+def populate_buy_trend(dataframe: DataFrame, pair: str) -> DataFrame:
     """
     Based on TA indicators, populates the buy signal for the given dataframe
     :param dataframe: DataFrame
     :return: DataFrame with buy column
     """
     strategy = Strategy()
-    return strategy.populate_buy_trend(dataframe=dataframe)
+    return strategy.populate_buy_trend(dataframe=dataframe, pair=pair)
 
 
-def populate_sell_trend(dataframe: DataFrame) -> DataFrame:
+def populate_sell_trend(dataframe: DataFrame, pair: str) -> DataFrame:
     """
     Based on TA indicators, populates the sell signal for the given dataframe
     :param dataframe: DataFrame
     :return: DataFrame with buy column
     """
     strategy = Strategy()
-    return strategy.populate_sell_trend(dataframe=dataframe)
+    return strategy.populate_sell_trend(dataframe=dataframe, pair=pair)
 
 
-def analyze_ticker(ticker_history: List[Dict]) -> DataFrame:
+def analyze_ticker(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 = parse_ticker_dataframe(ticker_history)
-    dataframe = populate_indicators(dataframe)
+    dataframe = populate_indicators(dataframe, pair)
-    dataframe = populate_buy_trend(dataframe)
+    dataframe = populate_buy_trend(dataframe, pair)
-    dataframe = populate_sell_trend(dataframe)
+    dataframe = populate_sell_trend(dataframe, pair)
     return dataframe
 
 
@@ -96,7 +96,7 @@ def get_signal(pair: str, interval: int) -> (bool, bool):
         return (False, False)  # return False ?
 
     try:
-        dataframe = analyze_ticker(ticker_hist)
+        dataframe = analyze_ticker(ticker_hist, pair)
     except ValueError as ex:
         logger.warning('Unable to analyze ticker for pair %s: %s', pair, str(ex))
         return (False, False)  # return False ?

freqtrade/optimize/__init__.py

@@ -91,7 +91,7 @@ def tickerdata_to_dataframe(data):
 
 def preprocess(tickerdata: Dict[str, List]) -> Dict[str, DataFrame]:
     """Creates a dataframe and populates indicators for given ticker data"""
-    return {pair: populate_indicators(parse_ticker_dataframe(pair_data))
+    return {pair: populate_indicators(parse_ticker_dataframe(pair_data), pair)
             for pair, pair_data in tickerdata.items()}
 
 

freqtrade/optimize/backtesting.py

@@ -117,7 +117,7 @@ def backtest(args) -> DataFrame:
     exchange._API = Bittrex({'key': '', 'secret': ''})
     for pair, pair_data in processed.items():
         pair_data['buy'], pair_data['sell'] = 0, 0
-        ticker = populate_sell_trend(populate_buy_trend(pair_data))
+        ticker = populate_sell_trend(populate_buy_trend(pair_data, pair), pair)
         # for each buy point
         lock_pair_until = None
         headers = ['buy', 'open', 'close', 'date', 'sell']

freqtrade/optimize/hyperopt.py

@@ -61,7 +61,7 @@ TRIALS = Trials()
 main._CONF = OPTIMIZE_CONFIG
 
 
-def populate_indicators(dataframe: DataFrame) -> DataFrame:
+def populate_indicators(dataframe: DataFrame, pair: str) -> DataFrame:
     """
     Adds several different TA indicators to the given DataFrame
     """
@@ -320,7 +320,7 @@ def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
     """
     Define the buy strategy parameters to be used by hyperopt
     """
-    def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(dataframe: DataFrame, pair: str) -> DataFrame:
         conditions = []
         # GUARDS AND TRENDS
         if 'uptrend_long_ema' in params and params['uptrend_long_ema']['enabled']:

freqtrade/strategy/default_strategy.py

@@ -29,7 +29,7 @@ class DefaultStrategy(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = 5
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, pair: str) -> DataFrame:
         """
         Adds several different TA indicators to the given DataFrame
 
@@ -196,7 +196,7 @@ class DefaultStrategy(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
@@ -217,7 +217,7 @@ class DefaultStrategy(IStrategy):
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame

freqtrade/strategy/interface.py

@@ -19,7 +19,7 @@ class IStrategy(ABC):
     """
 
     @abstractmethod
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, pair: str) -> 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()
@@ -27,7 +27,7 @@ class IStrategy(ABC):
         """
 
     @abstractmethod
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
@@ -36,7 +36,7 @@ class IStrategy(ABC):
         """
 
     @abstractmethod
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame

freqtrade/strategy/strategy.py

@@ -143,27 +143,27 @@ class Strategy(object):
 
         return path
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, pair: str) -> 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
         """
-        return self.custom_strategy.populate_indicators(dataframe)
+        return self.custom_strategy.populate_indicators(dataframe, pair)
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
         :return: DataFrame with buy column
         :return:
         """
-        return self.custom_strategy.populate_buy_trend(dataframe)
+        return self.custom_strategy.populate_buy_trend(dataframe, pair)
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame
         :return: DataFrame with buy column
         """
-        return self.custom_strategy.populate_sell_trend(dataframe)
+        return self.custom_strategy.populate_sell_trend(dataframe, pair)

freqtrade/tests/strategy/test_default_strategy.py

@@ -30,7 +30,7 @@ def test_default_strategy(result):
     assert type(strategy.minimal_roi) is dict
     assert type(strategy.stoploss) is float
     assert type(strategy.ticker_interval) is int
-    indicators = strategy.populate_indicators(result)
+    indicators = strategy.populate_indicators(result, None)
     assert type(indicators) is DataFrame
-    assert type(strategy.populate_buy_trend(indicators)) is DataFrame
+    assert type(strategy.populate_buy_trend(indicators, None)) is DataFrame
-    assert type(strategy.populate_sell_trend(indicators)) is DataFrame
+    assert type(strategy.populate_sell_trend(indicators, None)) is DataFrame

freqtrade/tests/strategy/test_strategy.py

@@ -37,7 +37,7 @@ def test_load_strategy(result):
     assert not hasattr(Strategy, 'custom_strategy')
 
     assert hasattr(strategy.custom_strategy, 'populate_indicators')
-    assert 'adx' in strategy.populate_indicators(result)
+    assert 'adx' in strategy.populate_indicators(result, None)
 
 
 def test_strategy(result):
@@ -51,14 +51,14 @@ def test_strategy(result):
     assert strategy.stoploss == -0.10
 
     assert hasattr(strategy.custom_strategy, 'populate_indicators')
-    assert 'adx' in strategy.populate_indicators(result)
+    assert 'adx' in strategy.populate_indicators(result, None)
 
     assert hasattr(strategy.custom_strategy, 'populate_buy_trend')
-    dataframe = strategy.populate_buy_trend(strategy.populate_indicators(result))
+    dataframe = strategy.populate_buy_trend(strategy.populate_indicators(result, None), None)
     assert 'buy' in dataframe.columns
 
     assert hasattr(strategy.custom_strategy, 'populate_sell_trend')
-    dataframe = strategy.populate_sell_trend(strategy.populate_indicators(result))
+    dataframe = strategy.populate_sell_trend(strategy.populate_indicators(result, None), None)
     assert 'sell' in dataframe.columns
 
 

freqtrade/tests/test_analyze.py

@@ -26,7 +26,7 @@ def test_populates_buy_trend(result):
     # Load the default strategy for the unit test, because this logic is done in main.py
     Strategy().init({'strategy': 'default_strategy'})
 
-    dataframe = populate_buy_trend(populate_indicators(result))
+    dataframe = populate_buy_trend(populate_indicators(result, None), None)
     assert 'buy' in dataframe.columns
 
 
@@ -34,7 +34,7 @@ def test_populates_sell_trend(result):
     # Load the default strategy for the unit test, because this logic is done in main.py
     Strategy().init({'strategy': 'default_strategy'})
 
-    dataframe = populate_sell_trend(populate_indicators(result))
+    dataframe = populate_sell_trend(populate_indicators(result, None), None)
     assert 'sell' in dataframe.columns
 
 

freqtrade/tests/test_dataframe.py

@@ -12,7 +12,7 @@ def load_dataframe_pair(pairs):
     assert isinstance(ld, dict)
     assert isinstance(pairs[0], str)
     dataframe = ld[pairs[0]]
-    dataframe = analyze.analyze_ticker(dataframe)
+    dataframe = analyze.analyze_ticker(dataframe, pairs[0])
     return dataframe
 
 

user_data/strategies/test_strategy.py

@@ -47,7 +47,7 @@ class TestStrategy(IStrategy):
     # Optimal ticker interval for the strategy
     ticker_interval = 5
 
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, pair: str) -> DataFrame:
         """
         Adds several different TA indicators to the given DataFrame
 
@@ -214,7 +214,7 @@ class TestStrategy(IStrategy):
 
         return dataframe
 
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
         """
         Based on TA indicators, populates the buy signal for the given dataframe
         :param dataframe: DataFrame
@@ -230,7 +230,7 @@ class TestStrategy(IStrategy):
 
         return dataframe
 
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, pair: str) -> DataFrame:
         """
         Based on TA indicators, populates the sell signal for the given dataframe
         :param dataframe: DataFrame