Remove unused test-strategy

tests/rpc/test_rpc_apiserver.py

@@ -1402,7 +1402,6 @@ def test_api_strategies(botclient):
         'InformativeDecoratorTest',
         'StrategyTestV2',
         'StrategyTestV3',
-        'StrategyTestV3Analysis',
         'StrategyTestV3Futures'
     ]}
 

tests/strategy/strats/strategy_test_v3_analysis.py

@@ -1,175 +0,0 @@
-# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
-
-import talib.abstract as ta
-from pandas import DataFrame
-
-import freqtrade.vendor.qtpylib.indicators as qtpylib
-from freqtrade.strategy import (BooleanParameter, DecimalParameter, IntParameter, IStrategy,
-                                RealParameter)
-
-
-class StrategyTestV3Analysis(IStrategy):
-    """
-    Strategy used by tests freqtrade bot.
-    Please do not modify this strategy, it's  intended for internal use only.
-    Please look at the SampleStrategy in the user_data/strategy directory
-    or strategy repository https://github.com/freqtrade/freqtrade-strategies
-    for samples and inspiration.
-    """
-    INTERFACE_VERSION = 3
-
-    # Minimal ROI designed for the strategy
-    minimal_roi = {
-        "40": 0.0,
-        "30": 0.01,
-        "20": 0.02,
-        "0": 0.04
-    }
-
-    # Optimal stoploss designed for the strategy
-    stoploss = -0.10
-
-    # Optimal timeframe for the strategy
-    timeframe = '5m'
-
-    # Optional order type mapping
-    order_types = {
-        'entry': 'limit',
-        'exit': 'limit',
-        'stoploss': 'limit',
-        'stoploss_on_exchange': False
-    }
-
-    # Number of candles the strategy requires before producing valid signals
-    startup_candle_count: int = 20
-
-    # Optional time in force for orders
-    order_time_in_force = {
-        'entry': 'gtc',
-        'exit': 'gtc',
-    }
-
-    buy_params = {
-        'buy_rsi': 35,
-        # Intentionally not specified, so "default" is tested
-        # 'buy_plusdi': 0.4
-    }
-
-    sell_params = {
-        'sell_rsi': 74,
-        'sell_minusdi': 0.4
-    }
-
-    buy_rsi = IntParameter([0, 50], default=30, space='buy')
-    buy_plusdi = RealParameter(low=0, high=1, default=0.5, space='buy')
-    sell_rsi = IntParameter(low=50, high=100, default=70, space='sell')
-    sell_minusdi = DecimalParameter(low=0, high=1, default=0.5001, decimals=3, space='sell',
-                                    load=False)
-    protection_enabled = BooleanParameter(default=True)
-    protection_cooldown_lookback = IntParameter([0, 50], default=30)
-
-    # TODO: Can this work with protection tests? (replace HyperoptableStrategy implicitly ... )
-    # @property
-    # def protections(self):
-    #     prot = []
-    #     if self.protection_enabled.value:
-    #         prot.append({
-    #             "method": "CooldownPeriod",
-    #             "stop_duration_candles": self.protection_cooldown_lookback.value
-    #         })
-    #     return prot
-
-    bot_started = False
-
-    def bot_start(self):
-        self.bot_started = True
-
-    def informative_pairs(self):
-
-        return []
-
-    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-
-        # Momentum Indicator
-        # ------------------------------------
-
-        # ADX
-        dataframe['adx'] = ta.ADX(dataframe)
-
-        # MACD
-        macd = ta.MACD(dataframe)
-        dataframe['macd'] = macd['macd']
-        dataframe['macdsignal'] = macd['macdsignal']
-        dataframe['macdhist'] = macd['macdhist']
-
-        # Minus Directional Indicator / Movement
-        dataframe['minus_di'] = ta.MINUS_DI(dataframe)
-
-        # Plus Directional Indicator / Movement
-        dataframe['plus_di'] = ta.PLUS_DI(dataframe)
-
-        # RSI
-        dataframe['rsi'] = ta.RSI(dataframe)
-
-        # Stoch fast
-        stoch_fast = ta.STOCHF(dataframe)
-        dataframe['fastd'] = stoch_fast['fastd']
-        dataframe['fastk'] = stoch_fast['fastk']
-
-        # Bollinger bands
-        bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
-        dataframe['bb_lowerband'] = bollinger['lower']
-        dataframe['bb_middleband'] = bollinger['mid']
-        dataframe['bb_upperband'] = bollinger['upper']
-
-        # EMA - Exponential Moving Average
-        dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
-
-        return dataframe
-
-    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-
-        dataframe.loc[
-            (
-                (dataframe['rsi'] < self.buy_rsi.value) &
-                (dataframe['fastd'] < 35) &
-                (dataframe['adx'] > 30) &
-                (dataframe['plus_di'] > self.buy_plusdi.value)
-            ) |
-            (
-                (dataframe['adx'] > 65) &
-                (dataframe['plus_di'] > self.buy_plusdi.value)
-            ),
-            ['enter_long', 'enter_tag']] = 1, 'enter_tag_long'
-
-        dataframe.loc[
-            (
-                qtpylib.crossed_below(dataframe['rsi'], self.sell_rsi.value)
-            ),
-            ['enter_short', 'enter_tag']] = 1, 'enter_tag_short'
-
-        return dataframe
-
-    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-        dataframe.loc[
-            (
-                (
-                    (qtpylib.crossed_above(dataframe['rsi'], self.sell_rsi.value)) |
-                    (qtpylib.crossed_above(dataframe['fastd'], 70))
-                ) &
-                (dataframe['adx'] > 10) &
-                (dataframe['minus_di'] > 0)
-            ) |
-            (
-                (dataframe['adx'] > 70) &
-                (dataframe['minus_di'] > self.sell_minusdi.value)
-            ),
-            ['exit_long', 'exit_tag']] = 1, 'exit_tag_long'
-
-        dataframe.loc[
-            (
-                qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)
-            ),
-            ['exit_long', 'exit_tag']] = 1, 'exit_tag_short'
-
-        return dataframe

tests/strategy/test_strategy_loading.py

@@ -34,7 +34,7 @@ def test_search_all_strategies_no_failed():
     directory = Path(__file__).parent / "strats"
     strategies = StrategyResolver.search_all_objects(directory, enum_failed=False)
     assert isinstance(strategies, list)
-    assert len(strategies) == 7
+    assert len(strategies) == 6
     assert isinstance(strategies[0], dict)
 
 
@@ -42,10 +42,10 @@ def test_search_all_strategies_with_failed():
     directory = Path(__file__).parent / "strats"
     strategies = StrategyResolver.search_all_objects(directory, enum_failed=True)
     assert isinstance(strategies, list)
-    assert len(strategies) == 8
+    assert len(strategies) == 7
     # with enum_failed=True search_all_objects() shall find 2 good strategies
     # and 1 which fails to load
-    assert len([x for x in strategies if x['class'] is not None]) == 7
+    assert len([x for x in strategies if x['class'] is not None]) == 6
     assert len([x for x in strategies if x['class'] is None]) == 1