Address points stated in comments

freqtrade/commands/list_commands.py

@@ -41,18 +41,21 @@ def start_list_exchanges(args: Dict[str, Any]) -> None:
 def _print_objs_tabular(objs: List, print_colorized: bool) -> None:
     if print_colorized:
         colorama_init(autoreset=True)
+        red = Fore.RED
+        yellow = Fore.YELLOW
+        reset = Style.RESET_ALL
+    else:
+        red = ''
+        yellow = ''
+        reset = ''
 
     names = [s['name'] for s in objs]
     objss_to_print = [{
         'name': s['name'] if s['name'] else "--",
         'location': s['location'].name,
-        'status': (((Fore.RED if print_colorized else '') +
-                    "LOAD FAILED" + (Style.RESET_ALL if print_colorized else ''))
-                   if s['class'] is None
+        'status': (red + "LOAD FAILED" + reset if s['class'] is None
                    else "OK" if names.count(s['name']) == 1
-                   else ((Fore.YELLOW if print_colorized else '') +
-                         "DUPLICATE NAME" +
-                         (Style.RESET_ALL if print_colorized else '')))
+                   else yellow + "DUPLICATE NAME" + reset)
     } for s in objs]
 
     print(tabulate(objss_to_print, headers='keys', tablefmt='pipe'))

freqtrade/resolvers/iresolver.py

@@ -87,7 +87,7 @@ class IResolver:
                 continue
             module_path = entry.resolve()
 
-            obj = next(cls._get_valid_object(module_path, object_name), None)  # noqa
+            obj = next(cls._get_valid_object(module_path, object_name), None)
 
             if obj:
                 return (obj, module_path)

tests/strategy/failing_strategy.py

@@ -1,87 +1,9 @@
-
-# --- Do not remove these libs ---
-from freqtrade.strategy.interface import IStrategy
-from pandas import DataFrame
-# --------------------------------
-
-# Add your lib to import here
-import talib.abstract as ta
+# The strategy which fails to load due to non-existent dependency
 
 import nonexiting_module  # noqa
 
+from freqtrade.strategy.interface import IStrategy
+
 
-# This class is a sample. Feel free to customize it.
 class TestStrategyLegacy(IStrategy):
-    """
-    This is a test strategy using the legacy function headers, which will be
-    removed in a future update.
-    Please do not use this as a template, but refer to user_data/strategy/sample_strategy.py
-    for a uptodate version of this template.
-    """
-
-    # Minimal ROI designed for the strategy.
-    # This attribute will be overridden if the config file contains "minimal_roi"
-    minimal_roi = {
-        "40": 0.0,
-        "30": 0.01,
-        "20": 0.02,
-        "0": 0.04
-    }
-
-    # Optimal stoploss designed for the strategy
-    # This attribute will be overridden if the config file contains "stoploss"
-    stoploss = -0.10
-
-    # Optimal ticker interval for the strategy
-    ticker_interval = '5m'
-
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
-        """
-        Adds several different TA indicators to the given DataFrame
-
-        Performance Note: For the best performance be frugal on the number of indicators
-        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.
-        """
-
-        # Momentum Indicator
-        # ------------------------------------
-
-        # ADX
-        dataframe['adx'] = ta.ADX(dataframe)
-
-        # TEMA - Triple Exponential Moving Average
-        dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
-
-        return dataframe
-
-    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
-        """
-        dataframe.loc[
-            (
-                (dataframe['adx'] > 30) &
-                (dataframe['tema'] > dataframe['tema'].shift(1)) &
-                (dataframe['volume'] > 0)
-            ),
-            'buy'] = 1
-
-        return dataframe
-
-    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
-        """
-        dataframe.loc[
-            (
-                (dataframe['adx'] > 70) &
-                (dataframe['tema'] < dataframe['tema'].shift(1)) &
-                (dataframe['volume'] > 0)
-            ),
-            'sell'] = 1
-        return dataframe
+    pass