merged with feat/short after feat/short added styling and comment changes PR

freqtrade/optimize/backtesting.py

@@ -232,10 +232,7 @@ class Backtesting:
                     pair_data.loc[:, 'buy_tag'] = None  # cleanup if buy_tag is exist
 
             df_analyzed = self.strategy.advise_sell(
-                self.strategy.advise_buy(
-                    pair_data,
-                    {'pair': pair}
-                ),
+                self.strategy.advise_buy(pair_data, {'pair': pair}),
                 {'pair': pair}
             ).copy()
             # Trim startup period from analyzed dataframe

freqtrade/optimize/hyperopt.py

@@ -285,13 +285,11 @@ class Hyperopt:
         # Apply parameters
         if HyperoptTools.has_space(self.config, 'buy'):
             self.backtesting.strategy.advise_buy = (  # type: ignore
-                self.custom_hyperopt.buy_strategy_generator(params_dict)
-            )
+                self.custom_hyperopt.buy_strategy_generator(params_dict))
 
         if HyperoptTools.has_space(self.config, 'sell'):
             self.backtesting.strategy.advise_sell = (  # type: ignore
-                self.custom_hyperopt.sell_strategy_generator(params_dict)
-            )
+                self.custom_hyperopt.sell_strategy_generator(params_dict))
 
         if HyperoptTools.has_space(self.config, 'protection'):
             for attr_name, attr in self.backtesting.strategy.enumerate_parameters('protection'):

freqtrade/resolvers/strategy_resolver.py

@@ -193,11 +193,13 @@ class StrategyResolver(IResolver):
                 # register temp path with the bot
                 abs_paths.insert(0, temp.resolve())
 
-        strategy = StrategyResolver._load_object(paths=abs_paths,
-                                                 object_name=strategy_name,
-                                                 add_source=True,
-                                                 kwargs={'config': config},
-                                                 )
+        strategy = StrategyResolver._load_object(
+            paths=abs_paths,
+            object_name=strategy_name,
+            add_source=True,
+            kwargs={'config': config},
+        )
+
         if strategy:
             strategy._populate_fun_len = len(getfullargspec(strategy.populate_indicators).args)
             strategy._buy_fun_len = len(getfullargspec(strategy.populate_buy_trend).args)

freqtrade/strategy/interface.py

@@ -553,15 +553,22 @@ class IStrategy(ABC, HyperStrategyMixin):
         logger.debug(f'trigger: %s (pair=%s) {enter_type.value}=%s {exit_type.value}=%s',
                      latest['date'], pair, str(enter), str(exit))
         timeframe_seconds = timeframe_to_seconds(timeframe)
-        if self.ignore_expired_candle(latest_date=latest_date,
-                                      current_time=datetime.now(timezone.utc),
-                                      timeframe_seconds=timeframe_seconds,
-                                      enter=enter):
+        if self.ignore_expired_candle(
+            latest_date=latest_date,
+            current_time=datetime.now(timezone.utc),
+            timeframe_seconds=timeframe_seconds,
+            enter=enter
+        ):
             return False, exit, enter_tag_value
         return enter, exit, enter_tag_value
 
-    def ignore_expired_candle(self, latest_date: datetime, current_time: datetime,
-                              timeframe_seconds: int, enter: bool):
+    def ignore_expired_candle(
+        self,
+        latest_date: datetime,
+        current_time: datetime,
+        timeframe_seconds: int,
+        enter: bool
+    ):
         if self.ignore_buying_expired_candle_after and enter:
             time_delta = current_time - (latest_date + timedelta(seconds=timeframe_seconds))
             return time_delta.total_seconds() > self.ignore_buying_expired_candle_after

freqtrade/templates/sample_hyperopt.py

@@ -46,7 +46,7 @@ class SampleHyperOpt(IHyperOpt):
     """
 
     @staticmethod
-    def buy_indicator_space() -> List[Dimension]:
+    def indicator_space() -> List[Dimension]:
         """
         Define your Hyperopt space for searching buy strategy parameters.
         """
@@ -63,8 +63,7 @@ class SampleHyperOpt(IHyperOpt):
             Categorical([True, False], name='fastd-enabled'),
             Categorical([True, False], name='adx-enabled'),
             Categorical([True, False], name='rsi-enabled'),
-            Categorical(['boll', 'macd_cross_signal', 'sar_reversal'], name='trigger'),
-
+            Categorical(['boll', 'macd_cross_signal', 'sar_reversal'], name='trigger')
         ]
 
     @staticmethod
@@ -157,7 +156,7 @@ class SampleHyperOpt(IHyperOpt):
                          'sell-macd_cross_signal',
                          'sell-sar_reversal'],
                         name='sell-trigger'
-                        ),
+                        )
         ]
 
     @staticmethod

tests/strategy/test_interface.py

@@ -750,6 +750,7 @@ def test_auto_hyperopt_interface(default_conf):
     # TODO-lev: Should these be 4,4 and 10?
     assert len(all_params['buy']) == 4
     assert len(all_params['sell']) == 4
+    # Number of Hyperoptable parameters
     assert all_params['count'] == 10
 
     strategy.__class__.sell_rsi = IntParameter([0, 10], default=5, space='buy')

tests/strategy/test_strategy_loading.py

@@ -385,13 +385,13 @@ def test_call_deprecated_function(result, monkeypatch, default_conf, caplog):
     assert isinstance(indicator_df, DataFrame)
     assert 'adx' in indicator_df.columns
 
-    buydf = strategy.advise_buy(result, metadata=metadata)
-    assert isinstance(buydf, DataFrame)
-    assert 'buy' in buydf.columns
+    enterdf = strategy.advise_buy(result, metadata=metadata)
+    assert isinstance(enterdf, DataFrame)
+    assert 'buy' in enterdf.columns
 
-    selldf = strategy.advise_sell(result, metadata=metadata)
-    assert isinstance(selldf, DataFrame)
-    assert 'sell' in selldf
+    exitdf = strategy.advise_sell(result, metadata=metadata)
+    assert isinstance(exitdf, DataFrame)
+    assert 'sell' in exitdf
 
     assert log_has("DEPRECATED: Please migrate to using 'timeframe' instead of 'ticker_interval'.",
                    caplog)