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condensed strategy methods down to 2

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This commit is contained in:
Sam Germain
2021-08-18 04:19:17 -06:00
parent d4a7d2d444
commit 092780df9d
22 changed files with 451 additions and 773 deletions
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267
tests/optimize/hyperopts/default_hyperopt.py
View File

@@ -54,36 +54,57 @@ class DefaultHyperOpt(IHyperOpt):
"""
Buy strategy Hyperopt will build and use.
"""
conditions = []
long_conditions = []
short_conditions = []
# GUARDS AND TRENDS
if 'mfi-enabled' in params and params['mfi-enabled']:
conditions.append(dataframe['mfi'] < params['mfi-value'])
long_conditions.append(dataframe['mfi'] < params['mfi-value'])
short_conditions.append(dataframe['mfi'] > params['short-mfi-value'])
if 'fastd-enabled' in params and params['fastd-enabled']:
conditions.append(dataframe['fastd'] < params['fastd-value'])
long_conditions.append(dataframe['fastd'] < params['fastd-value'])
short_conditions.append(dataframe['fastd'] > params['short-fastd-value'])
if 'adx-enabled' in params and params['adx-enabled']:
conditions.append(dataframe['adx'] > params['adx-value'])
long_conditions.append(dataframe['adx'] > params['adx-value'])
short_conditions.append(dataframe['adx'] < params['short-adx-value'])
if 'rsi-enabled' in params and params['rsi-enabled']:
conditions.append(dataframe['rsi'] < params['rsi-value'])
long_conditions.append(dataframe['rsi'] < params['rsi-value'])
short_conditions.append(dataframe['rsi'] > params['short-rsi-value'])
# TRIGGERS
if 'trigger' in params:
if params['trigger'] == 'bb_lower':
conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
if params['trigger'] == 'boll':
long_conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
short_conditions.append(dataframe['close'] > dataframe['bb_upperband'])
if params['trigger'] == 'macd_cross_signal':
conditions.append(qtpylib.crossed_above(
dataframe['macd'], dataframe['macdsignal']
long_conditions.append(qtpylib.crossed_above(
dataframe['macd'],
dataframe['macdsignal']
))
short_conditions.append(qtpylib.crossed_below(
dataframe['macd'],
dataframe['macdsignal']
))
if params['trigger'] == 'sar_reversal':
conditions.append(qtpylib.crossed_above(
dataframe['close'], dataframe['sar']
long_conditions.append(qtpylib.crossed_above(
dataframe['close'],
dataframe['sar']
))
short_conditions.append(qtpylib.crossed_below(
dataframe['close'],
dataframe['sar']
))
if conditions:
if long_conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
reduce(lambda x, y: x & y, long_conditions),
'buy'] = 1
if short_conditions:
dataframe.loc[
reduce(lambda x, y: x & y, short_conditions),
'enter_short'] = 1
return dataframe
return populate_buy_trend
@@ -98,71 +119,15 @@ class DefaultHyperOpt(IHyperOpt):
Integer(15, 45, name='fastd-value'),
Integer(20, 50, name='adx-value'),
Integer(20, 40, name='rsi-value'),
Integer(75, 90, name='short-mfi-value'),
Integer(55, 85, name='short-fastd-value'),
Integer(50, 80, name='short-adx-value'),
Integer(60, 80, name='short-rsi-value'),
Categorical([True, False], name='mfi-enabled'),
Categorical([True, False], name='fastd-enabled'),
Categorical([True, False], name='adx-enabled'),
Categorical([True, False], name='rsi-enabled'),
Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger')
]
@staticmethod
def short_strategy_generator(params: Dict[str, Any]) -> Callable:
"""
Define the short strategy parameters to be used by Hyperopt.
"""
def populate_short_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Buy strategy Hyperopt will build and use.
"""
conditions = []
# GUARDS AND TRENDS
if 'mfi-enabled' in params and params['mfi-enabled']:
conditions.append(dataframe['mfi'] > params['mfi-value'])
if 'fastd-enabled' in params and params['fastd-enabled']:
conditions.append(dataframe['fastd'] > params['fastd-value'])
if 'adx-enabled' in params and params['adx-enabled']:
conditions.append(dataframe['adx'] < params['adx-value'])
if 'rsi-enabled' in params and params['rsi-enabled']:
conditions.append(dataframe['rsi'] > params['rsi-value'])
# TRIGGERS
if 'trigger' in params:
if params['trigger'] == 'bb_upper':
conditions.append(dataframe['close'] > dataframe['bb_upperband'])
if params['trigger'] == 'macd_cross_signal':
conditions.append(qtpylib.crossed_below(
dataframe['macd'], dataframe['macdsignal']
))
if params['trigger'] == 'sar_reversal':
conditions.append(qtpylib.crossed_below(
dataframe['close'], dataframe['sar']
))
if conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
'short'] = 1
return dataframe
return populate_short_trend
@staticmethod
def short_indicator_space() -> List[Dimension]:
"""
Define your Hyperopt space for searching short strategy parameters.
"""
return [
Integer(75, 90, name='mfi-value'),
Integer(55, 85, name='fastd-value'),
Integer(50, 80, name='adx-value'),
Integer(60, 80, name='rsi-value'),
Categorical([True, False], name='mfi-enabled'),
Categorical([True, False], name='fastd-enabled'),
Categorical([True, False], name='adx-enabled'),
Categorical([True, False], name='rsi-enabled'),
Categorical(['bb_upper', 'macd_cross_signal', 'sar_reversal'], name='trigger')
Categorical(['boll', 'macd_cross_signal', 'sar_reversal'], name='trigger')
]
@staticmethod
@@ -174,83 +139,61 @@ class DefaultHyperOpt(IHyperOpt):
"""
Sell strategy Hyperopt will build and use.
"""
conditions = []
exit_long_conditions = []
exit_short_conditions = []
# GUARDS AND TRENDS
if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']:
conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
exit_long_conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
exit_short_conditions.append(dataframe['mfi'] < params['exit-short-mfi-value'])
if 'sell-fastd-enabled' in params and params['sell-fastd-enabled']:
conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
exit_long_conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
exit_short_conditions.append(dataframe['fastd'] < params['exit-short-fastd-value'])
if 'sell-adx-enabled' in params and params['sell-adx-enabled']:
conditions.append(dataframe['adx'] < params['sell-adx-value'])
exit_long_conditions.append(dataframe['adx'] < params['sell-adx-value'])
exit_short_conditions.append(dataframe['adx'] > params['exit-short-adx-value'])
if 'sell-rsi-enabled' in params and params['sell-rsi-enabled']:
conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
exit_long_conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
exit_short_conditions.append(dataframe['rsi'] < params['exit-short-rsi-value'])
# TRIGGERS
if 'sell-trigger' in params:
if params['sell-trigger'] == 'sell-bb_upper':
conditions.append(dataframe['close'] > dataframe['bb_upperband'])
if params['sell-trigger'] == 'sell-boll':
exit_long_conditions.append(dataframe['close'] > dataframe['bb_upperband'])
exit_short_conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
if params['sell-trigger'] == 'sell-macd_cross_signal':
conditions.append(qtpylib.crossed_above(
dataframe['macdsignal'], dataframe['macd']
exit_long_conditions.append(qtpylib.crossed_above(
dataframe['macdsignal'],
dataframe['macd']
))
exit_short_conditions.append(qtpylib.crossed_below(
dataframe['macdsignal'],
dataframe['macd']
))
if params['sell-trigger'] == 'sell-sar_reversal':
conditions.append(qtpylib.crossed_above(
dataframe['sar'], dataframe['close']
exit_long_conditions.append(qtpylib.crossed_above(
dataframe['sar'],
dataframe['close']
))
exit_short_conditions.append(qtpylib.crossed_below(
dataframe['sar'],
dataframe['close']
))
if conditions:
if exit_long_conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
reduce(lambda x, y: x & y, exit_long_conditions),
'sell'] = 1
if exit_short_conditions:
dataframe.loc[
reduce(lambda x, y: x & y, exit_short_conditions),
'exit-short'] = 1
return dataframe
return populate_sell_trend
@staticmethod
def exit_short_strategy_generator(params: Dict[str, Any]) -> Callable:
"""
Define the exit_short strategy parameters to be used by Hyperopt.
"""
def populate_exit_short_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Exit_short strategy Hyperopt will build and use.
"""
conditions = []
# GUARDS AND TRENDS
if 'exit-short-mfi-enabled' in params and params['exit-short-mfi-enabled']:
conditions.append(dataframe['mfi'] < params['exit-short-mfi-value'])
if 'exit-short-fastd-enabled' in params and params['exit-short-fastd-enabled']:
conditions.append(dataframe['fastd'] < params['exit-short-fastd-value'])
if 'exit-short-adx-enabled' in params and params['exit-short-adx-enabled']:
conditions.append(dataframe['adx'] > params['exit-short-adx-value'])
if 'exit-short-rsi-enabled' in params and params['exit-short-rsi-enabled']:
conditions.append(dataframe['rsi'] < params['exit-short-rsi-value'])
# TRIGGERS
if 'exit-short-trigger' in params:
if params['exit-short-trigger'] == 'exit-short-bb_lower':
conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
if params['exit-short-trigger'] == 'exit-short-macd_cross_signal':
conditions.append(qtpylib.crossed_below(
dataframe['macdsignal'], dataframe['macd']
))
if params['exit-short-trigger'] == 'exit-short-sar_reversal':
conditions.append(qtpylib.crossed_below(
dataframe['sar'], dataframe['close']
))
if conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
'exit_short'] = 1
return dataframe
return populate_exit_short_trend
@staticmethod
def sell_indicator_space() -> List[Dimension]:
"""
@@ -261,32 +204,18 @@ class DefaultHyperOpt(IHyperOpt):
Integer(50, 100, name='sell-fastd-value'),
Integer(50, 100, name='sell-adx-value'),
Integer(60, 100, name='sell-rsi-value'),
Integer(1, 25, name='exit-short-mfi-value'),
Integer(1, 50, name='exit-short-fastd-value'),
Integer(1, 50, name='exit-short-adx-value'),
Integer(1, 40, name='exit-short-rsi-value'),
Categorical([True, False], name='sell-mfi-enabled'),
Categorical([True, False], name='sell-fastd-enabled'),
Categorical([True, False], name='sell-adx-enabled'),
Categorical([True, False], name='sell-rsi-enabled'),
Categorical(['sell-bb_upper',
Categorical(['sell-boll',
'sell-macd_cross_signal',
'sell-sar_reversal'], name='sell-trigger')
]
@staticmethod
def exit_short_indicator_space() -> List[Dimension]:
"""
Define your Hyperopt space for searching exit short strategy parameters.
"""
return [
Integer(1, 25, name='exit_short-mfi-value'),
Integer(1, 50, name='exit_short-fastd-value'),
Integer(1, 50, name='exit_short-adx-value'),
Integer(1, 40, name='exit_short-rsi-value'),
Categorical([True, False], name='exit_short-mfi-enabled'),
Categorical([True, False], name='exit_short-fastd-enabled'),
Categorical([True, False], name='exit_short-adx-enabled'),
Categorical([True, False], name='exit_short-rsi-enabled'),
Categorical(['exit_short-bb_lower',
'exit_short-macd_cross_signal',
'exit_short-sar_reversal'], name='exit_short-trigger')
'sell-sar_reversal'],
name='sell-trigger')
]
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@@ -304,6 +233,15 @@ class DefaultHyperOpt(IHyperOpt):
),
'buy'] = 1
dataframe.loc[
(
(dataframe['close'] > dataframe['bb_upperband']) &
(dataframe['mfi'] < 84) &
(dataframe['adx'] > 75) &
(dataframe['rsi'] < 79)
),
'enter_short'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@@ -321,31 +259,6 @@ class DefaultHyperOpt(IHyperOpt):
),
'sell'] = 1
return dataframe
def populate_short_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators. Should be a copy of same method from strategy.
Must align to populate_indicators in this file.
Only used when --spaces does not include short space.
"""
dataframe.loc[
(
(dataframe['close'] > dataframe['bb_upperband']) &
(dataframe['mfi'] < 84) &
(dataframe['adx'] > 75) &
(dataframe['rsi'] < 79)
),
'buy'] = 1
return dataframe
def populate_exit_short_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators. Should be a copy of same method from strategy.
Must align to populate_indicators in this file.
Only used when --spaces does not include exit_short space.
"""
dataframe.loc[
(
(qtpylib.crossed_below(
@@ -353,6 +266,6 @@ class DefaultHyperOpt(IHyperOpt):
)) &
(dataframe['fastd'] < 46)
),
'sell'] = 1
'exit_short'] = 1
return dataframe

4
tests/optimize/test_backtest_detail.py
View File

@@ -597,8 +597,8 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
backtesting.required_startup = 0
backtesting.strategy.advise_enter = lambda a, m: frame
backtesting.strategy.advise_exit = lambda a, m: frame
backtesting.strategy.advise_buy = lambda a, m: frame
backtesting.strategy.advise_sell = lambda a, m: frame
backtesting.strategy.use_custom_stoploss = data.use_custom_stoploss
caplog.set_level(logging.DEBUG)

20
tests/optimize/test_backtesting.py
View File

@@ -290,8 +290,8 @@ def test_backtesting_init(mocker, default_conf, order_types) -> None:
assert backtesting.config == default_conf
assert backtesting.timeframe == '5m'
assert callable(backtesting.strategy.ohlcvdata_to_dataframe)
assert callable(backtesting.strategy.advise_enter)
assert callable(backtesting.strategy.advise_exit)
assert callable(backtesting.strategy.advise_buy)
assert callable(backtesting.strategy.advise_sell)
assert isinstance(backtesting.strategy.dp, DataProvider)
get_fee.assert_called()
assert backtesting.fee == 0.5
@@ -700,8 +700,8 @@ def test_backtest_clash_buy_sell(mocker, default_conf, testdatadir):
backtest_conf = _make_backtest_conf(mocker, conf=default_conf, datadir=testdatadir)
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
backtesting.strategy.advise_enter = fun # Override
backtesting.strategy.advise_exit = fun # Override
backtesting.strategy.advise_buy = fun # Override
backtesting.strategy.advise_sell = fun # Override
result = backtesting.backtest(**backtest_conf)
assert result['results'].empty
@@ -716,8 +716,8 @@ def test_backtest_only_sell(mocker, default_conf, testdatadir):
backtest_conf = _make_backtest_conf(mocker, conf=default_conf, datadir=testdatadir)
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
backtesting.strategy.advise_enter = fun # Override
backtesting.strategy.advise_exit = fun # Override
backtesting.strategy.advise_buy = fun # Override
backtesting.strategy.advise_sell = fun # Override
result = backtesting.backtest(**backtest_conf)
assert result['results'].empty
@@ -731,8 +731,8 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir):
backtesting = Backtesting(default_conf)
backtesting.required_startup = 0
backtesting._set_strategy(backtesting.strategylist[0])
backtesting.strategy.advise_enter = _trend_alternate # Override
backtesting.strategy.advise_exit = _trend_alternate # Override
backtesting.strategy.advise_buy = _trend_alternate # Override
backtesting.strategy.advise_sell = _trend_alternate # Override
result = backtesting.backtest(**backtest_conf)
# 200 candles in backtest data
# won't buy on first (shifted by 1)
@@ -777,8 +777,8 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
backtesting.strategy.advise_enter = _trend_alternate_hold # Override
backtesting.strategy.advise_exit = _trend_alternate_hold # Override
backtesting.strategy.advise_buy = _trend_alternate_hold # Override
backtesting.strategy.advise_sell = _trend_alternate_hold # Override
processed = backtesting.strategy.ohlcvdata_to_dataframe(data)
min_date, max_date = get_timerange(processed)

40
tests/optimize/test_hyperopt.py
View File

@@ -366,8 +366,8 @@ def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
# Should be called for historical candle data
assert dumper.call_count == 1
assert dumper2.call_count == 1
assert hasattr(hyperopt.backtesting.strategy, "advise_exit")
assert hasattr(hyperopt.backtesting.strategy, "advise_enter")
assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
assert hasattr(hyperopt, "max_open_trades")
assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
assert hasattr(hyperopt, "position_stacking")
@@ -451,6 +451,10 @@ def test_buy_strategy_generator(hyperopt, testdatadir) -> None:
'fastd-value': 20,
'mfi-value': 20,
'rsi-value': 20,
'short-adx-value': 80,
'short-fastd-value': 80,
'short-mfi-value': 80,
'short-rsi-value': 80,
'adx-enabled': True,
'fastd-enabled': True,
'mfi-enabled': True,
@@ -476,6 +480,10 @@ def test_sell_strategy_generator(hyperopt, testdatadir) -> None:
'sell-fastd-value': 75,
'sell-mfi-value': 80,
'sell-rsi-value': 20,
'exit-short-adx-value': 80,
'exit-short-fastd-value': 25,
'exit-short-mfi-value': 20,
'exit-short-rsi-value': 80,
'sell-adx-enabled': True,
'sell-fastd-enabled': True,
'sell-mfi-enabled': True,
@@ -534,6 +542,10 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
'fastd-value': 35,
'mfi-value': 0,
'rsi-value': 0,
'short-adx-value': 100,
'short-fastd-value': 65,
'short-mfi-value': 100,
'short-rsi-value': 100,
'adx-enabled': False,
'fastd-enabled': True,
'mfi-enabled': False,
@@ -543,6 +555,10 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
'sell-fastd-value': 75,
'sell-mfi-value': 0,
'sell-rsi-value': 0,
'exit-short-adx-value': 100,
'exit-short-fastd-value': 25,
'exit-short-mfi-value': 100,
'exit-short-rsi-value': 100,
'sell-adx-enabled': False,
'sell-fastd-enabled': True,
'sell-mfi-enabled': False,
@@ -569,12 +585,16 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
),
'params_details': {'buy': {'adx-enabled': False,
'adx-value': 0,
'short-adx-value': 100,
'fastd-enabled': True,
'fastd-value': 35,
'short-fastd-value': 65,
'mfi-enabled': False,
'mfi-value': 0,
'short-mfi-value': 100,
'rsi-enabled': False,
'rsi-value': 0,
'short-rsi-value': 100,
'trigger': 'macd_cross_signal'},
'roi': {"0": 0.12000000000000001,
"20.0": 0.02,
@@ -583,12 +603,16 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
'protection': {},
'sell': {'sell-adx-enabled': False,
'sell-adx-value': 0,
'exit-short-adx-value': 100,
'sell-fastd-enabled': True,
'sell-fastd-value': 75,
'exit-short-fastd-value': 25,
'sell-mfi-enabled': False,
'sell-mfi-value': 0,
'exit-short-mfi-value': 100,
'sell-rsi-enabled': False,
'sell-rsi-value': 0,
'exit-short-rsi-value': 100,
'sell-trigger': 'macd_cross_signal'},
'stoploss': {'stoploss': -0.4},
'trailing': {'trailing_only_offset_is_reached': False,
@@ -825,8 +849,8 @@ def test_simplified_interface_roi_stoploss(mocker, hyperopt_conf, capsys) -> Non
assert dumper.call_count == 1
assert dumper2.call_count == 1
assert hasattr(hyperopt.backtesting.strategy, "advise_exit")
assert hasattr(hyperopt.backtesting.strategy, "advise_enter")
assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
assert hasattr(hyperopt, "max_open_trades")
assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
assert hasattr(hyperopt, "position_stacking")
@@ -906,8 +930,8 @@ def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
assert dumper.called
assert dumper.call_count == 1
assert dumper2.call_count == 1
assert hasattr(hyperopt.backtesting.strategy, "advise_exit")
assert hasattr(hyperopt.backtesting.strategy, "advise_enter")
assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
assert hasattr(hyperopt, "max_open_trades")
assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
assert hasattr(hyperopt, "position_stacking")
@@ -960,8 +984,8 @@ def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None:
assert dumper.called
assert dumper.call_count == 1
assert dumper2.call_count == 1
assert hasattr(hyperopt.backtesting.strategy, "advise_exit")
assert hasattr(hyperopt.backtesting.strategy, "advise_enter")
assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
assert hasattr(hyperopt, "max_open_trades")
assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
assert hasattr(hyperopt, "position_stacking")

2
tests/rpc/test_rpc_apiserver.py
View File

@@ -264,7 +264,7 @@ def test_api_UvicornServer(mocker):
assert thread_mock.call_count == 1
s.cleanup()
assert s.should_sell is True
assert s.should_exit is True
def test_api_UvicornServer_run(mocker):

44
tests/strategy/strats/default_strategy.py
View File

@@ -130,6 +130,19 @@ class DefaultStrategy(IStrategy):
),
'buy'] = 1
dataframe.loc[
(
(dataframe['rsi'] > 65) &
(dataframe['fastd'] > 65) &
(dataframe['adx'] < 70) &
(dataframe['plus_di'] < 0.5) # TODO-lev: What to do here
) |
(
(dataframe['adx'] < 35) &
(dataframe['plus_di'] < 0.5) # TODO-lev: What to do here
),
'enter_short'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@@ -153,37 +166,7 @@ class DefaultStrategy(IStrategy):
(dataframe['minus_di'] > 0.5)
),
'sell'] = 1
return dataframe
def populate_short_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the short signal for the given dataframe
:param dataframe: DataFrame
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with short column
"""
dataframe.loc[
(
(dataframe['rsi'] > 65) &
(dataframe['fastd'] > 65) &
(dataframe['adx'] < 70) &
(dataframe['plus_di'] < 0.5) # TODO-lev: What to do here
) |
(
(dataframe['adx'] < 35) &
(dataframe['plus_di'] < 0.5) # TODO-lev: What to do here
),
'short'] = 1
return dataframe
def populate_exit_short_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the exit_short signal for the given dataframe
:param dataframe: DataFrame
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with exit_short column
"""
dataframe.loc[
(
(
@@ -198,4 +181,5 @@ class DefaultStrategy(IStrategy):
(dataframe['minus_di'] < 0.5) # TODO-lev: what to do here
),
'exit_short'] = 1
return dataframe

50
tests/strategy/strats/hyperoptable_strategy.py
View File

@@ -60,7 +60,7 @@ class HyperoptableStrategy(IStrategy):
'sell_minusdi': 0.4
}
short_params = {
enter_short_params = {
'short_rsi': 65,
}
@@ -87,8 +87,8 @@ class HyperoptableStrategy(IStrategy):
})
return prot
short_rsi = IntParameter([50, 100], default=70, space='sell')
short_plusdi = RealParameter(low=0, high=1, default=0.5, space='sell')
enter_short_rsi = IntParameter([50, 100], default=70, space='sell')
enter_short_plusdi = RealParameter(low=0, high=1, default=0.5, space='sell')
exit_short_rsi = IntParameter(low=0, high=50, default=30, space='buy')
exit_short_minusdi = DecimalParameter(low=0, high=1, default=0.4999, decimals=3, space='buy',
load=False)
@@ -175,6 +175,19 @@ class HyperoptableStrategy(IStrategy):
),
'buy'] = 1
dataframe.loc[
(
(dataframe['rsi'] > self.enter_short_rsi.value) &
(dataframe['fastd'] > 65) &
(dataframe['adx'] < 70) &
(dataframe['plus_di'] < self.enter_short_plusdi.value)
) |
(
(dataframe['adx'] < 35) &
(dataframe['plus_di'] < self.enter_short_plusdi.value)
),
'enter_short'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@@ -198,37 +211,7 @@ class HyperoptableStrategy(IStrategy):
(dataframe['minus_di'] > self.sell_minusdi.value)
),
'sell'] = 1
return dataframe
def populate_short_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the short signal for the given dataframe
:param dataframe: DataFrame
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with short column
"""
dataframe.loc[
(
(dataframe['rsi'] > self.short_rsi.value) &
(dataframe['fastd'] > 65) &
(dataframe['adx'] < 70) &
(dataframe['plus_di'] < self.short_plusdi.value)
) |
(
(dataframe['adx'] < 35) &
(dataframe['plus_di'] < self.short_plusdi.value)
),
'short'] = 1
return dataframe
def populate_exit_short_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the exit_short signal for the given dataframe
:param dataframe: DataFrame
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with exit_short column
"""
dataframe.loc[
(
(
@@ -243,4 +226,5 @@ class HyperoptableStrategy(IStrategy):
(dataframe['minus_di'] < self.exit_short_minusdi.value)
),
'exit_short'] = 1
return dataframe

30
tests/strategy/strats/legacy_strategy.py
View File

@@ -84,35 +84,5 @@ class TestStrategyLegacy(IStrategy):
(dataframe['volume'] > 0)
),
'sell'] = 1
return dataframe
def populate_short_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_exit_short_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

27
tests/strategy/test_default_strategy.py
View File

@@ -14,8 +14,6 @@ def test_default_strategy_structure():
assert hasattr(DefaultStrategy, 'populate_indicators')
assert hasattr(DefaultStrategy, 'populate_buy_trend')
assert hasattr(DefaultStrategy, 'populate_sell_trend')
assert hasattr(DefaultStrategy, 'populate_short_trend')
assert hasattr(DefaultStrategy, 'populate_exit_short_trend')
def test_default_strategy(result, fee):
@@ -29,10 +27,6 @@ def test_default_strategy(result, fee):
assert type(indicators) is DataFrame
assert type(strategy.populate_buy_trend(indicators, metadata)) is DataFrame
assert type(strategy.populate_sell_trend(indicators, metadata)) is DataFrame
# TODO-lev: I think these two should be commented out in the strategy by default
# TODO-lev: so they can be tested, but the tests can't really remain
assert type(strategy.populate_short_trend(indicators, metadata)) is DataFrame
assert type(strategy.populate_exit_short_trend(indicators, metadata)) is DataFrame
trade = Trade(
open_rate=19_000,
@@ -43,28 +37,11 @@ def test_default_strategy(result, fee):
assert strategy.confirm_trade_entry(pair='ETH/BTC', order_type='limit', amount=0.1,
rate=20000, time_in_force='gtc',
is_short=False, current_time=datetime.utcnow()) is True
current_time=datetime.utcnow()) is True
assert strategy.confirm_trade_exit(pair='ETH/BTC', trade=trade, order_type='limit', amount=0.1,
rate=20000, time_in_force='gtc', sell_reason='roi',
is_short=False, current_time=datetime.utcnow()) is True
current_time=datetime.utcnow()) is True
# TODO-lev: Test for shorts?
assert strategy.custom_stoploss(pair='ETH/BTC', trade=trade, current_time=datetime.now(),
current_rate=20_000, current_profit=0.05) == strategy.stoploss
short_trade = Trade(
open_rate=21_000,
amount=0.1,
pair='ETH/BTC',
fee_open=fee.return_value
)
assert strategy.confirm_trade_entry(pair='ETH/BTC', order_type='limit', amount=0.1,
rate=20000, time_in_force='gtc',
is_short=True, current_time=datetime.utcnow()) is True
assert strategy.confirm_trade_exit(pair='ETH/BTC', trade=short_trade, order_type='limit',
amount=0.1, rate=20000, time_in_force='gtc',
sell_reason='roi', is_short=True,
current_time=datetime.utcnow()) is True

32
tests/strategy/test_interface.py
View File

@@ -482,20 +482,20 @@ def test_custom_sell(default_conf, fee, caplog) -> None:
def test_analyze_ticker_default(ohlcv_history, mocker, caplog) -> None:
caplog.set_level(logging.DEBUG)
ind_mock = MagicMock(side_effect=lambda x, meta: x)
enter_mock = MagicMock(side_effect=lambda x, meta, is_short: x)
exit_mock = MagicMock(side_effect=lambda x, meta, is_short: x)
buy_mock = MagicMock(side_effect=lambda x, meta: x)
sell_mock = MagicMock(side_effect=lambda x, meta: x)
mocker.patch.multiple(
'freqtrade.strategy.interface.IStrategy',
advise_indicators=ind_mock,
advise_enter=enter_mock,
advise_exit=exit_mock,
advise_buy=buy_mock,
advise_sell=sell_mock,
)
strategy = DefaultStrategy({})
strategy.analyze_ticker(ohlcv_history, {'pair': 'ETH/BTC'})
assert ind_mock.call_count == 1
assert enter_mock.call_count == 2
assert enter_mock.call_count == 2
assert buy_mock.call_count == 1
assert buy_mock.call_count == 1
assert log_has('TA Analysis Launched', caplog)
assert not log_has('Skipping TA Analysis for already analyzed candle', caplog)
@@ -504,8 +504,8 @@ def test_analyze_ticker_default(ohlcv_history, mocker, caplog) -> None:
strategy.analyze_ticker(ohlcv_history, {'pair': 'ETH/BTC'})
# No analysis happens as process_only_new_candles is true
assert ind_mock.call_count == 2
assert enter_mock.call_count == 4
assert enter_mock.call_count == 4
assert buy_mock.call_count == 2
assert buy_mock.call_count == 2
assert log_has('TA Analysis Launched', caplog)
assert not log_has('Skipping TA Analysis for already analyzed candle', caplog)
@@ -513,13 +513,13 @@ def test_analyze_ticker_default(ohlcv_history, mocker, caplog) -> None:
def test__analyze_ticker_internal_skip_analyze(ohlcv_history, mocker, caplog) -> None:
caplog.set_level(logging.DEBUG)
ind_mock = MagicMock(side_effect=lambda x, meta: x)
enter_mock = MagicMock(side_effect=lambda x, meta, is_short: x)
exit_mock = MagicMock(side_effect=lambda x, meta, is_short: x)
buy_mock = MagicMock(side_effect=lambda x, meta: x)
sell_mock = MagicMock(side_effect=lambda x, meta: x)
mocker.patch.multiple(
'freqtrade.strategy.interface.IStrategy',
advise_indicators=ind_mock,
advise_enter=enter_mock,
advise_exit=exit_mock,
advise_buy=buy_mock,
advise_sell=sell_mock,
)
strategy = DefaultStrategy({})
@@ -532,8 +532,8 @@ def test__analyze_ticker_internal_skip_analyze(ohlcv_history, mocker, caplog) ->
assert 'close' in ret.columns
assert isinstance(ret, DataFrame)
assert ind_mock.call_count == 1
assert enter_mock.call_count == 2 # Once for buy, once for short
assert enter_mock.call_count == 2
assert buy_mock.call_count == 1
assert buy_mock.call_count == 1
assert log_has('TA Analysis Launched', caplog)
assert not log_has('Skipping TA Analysis for already analyzed candle', caplog)
caplog.clear()
@@ -541,8 +541,8 @@ def test__analyze_ticker_internal_skip_analyze(ohlcv_history, mocker, caplog) ->
ret = strategy._analyze_ticker_internal(ohlcv_history, {'pair': 'ETH/BTC'})
# No analysis happens as process_only_new_candles is true
assert ind_mock.call_count == 1
assert enter_mock.call_count == 2
assert enter_mock.call_count == 2
assert buy_mock.call_count == 1
assert buy_mock.call_count == 1
# only skipped analyze adds buy and sell columns, otherwise it's all mocked
assert 'buy' in ret.columns
assert 'sell' in ret.columns

52
tests/strategy/test_strategy_loading.py
View File

@@ -117,16 +117,12 @@ def test_strategy(result, default_conf):
df_indicators = strategy.advise_indicators(result, metadata=metadata)
assert 'adx' in df_indicators
dataframe = strategy.advise_enter(df_indicators, metadata=metadata, is_short=False)
dataframe = strategy.advise_buy(df_indicators, metadata=metadata)
assert 'buy' in dataframe.columns
assert 'enter_short' in dataframe.columns
dataframe = strategy.advise_exit(df_indicators, metadata=metadata, is_short=False)
dataframe = strategy.advise_sell(df_indicators, metadata=metadata)
assert 'sell' in dataframe.columns
dataframe = strategy.advise_enter(df_indicators, metadata=metadata, is_short=True)
assert 'short' in dataframe.columns
dataframe = strategy.advise_exit(df_indicators, metadata=metadata, is_short=True)
assert 'exit_short' in dataframe.columns
@@ -352,7 +348,7 @@ def test_deprecate_populate_indicators(result, default_conf):
with warnings.catch_warnings(record=True) as w:
# Cause all warnings to always be triggered.
warnings.simplefilter("always")
strategy.advise_enter(indicators, {'pair': 'ETH/BTC'}, is_short=False) # TODO-lev
strategy.advise_buy(indicators, {'pair': 'ETH/BTC'})
assert len(w) == 1
assert issubclass(w[-1].category, DeprecationWarning)
assert "deprecated - check out the Sample strategy to see the current function headers!" \
@@ -361,7 +357,7 @@ def test_deprecate_populate_indicators(result, default_conf):
with warnings.catch_warnings(record=True) as w:
# Cause all warnings to always be triggered.
warnings.simplefilter("always")
strategy.advise_exit(indicators, {'pair': 'ETH_BTC'}, is_short=False) # TODO-lev
strategy.advise_sell(indicators, {'pair': 'ETH_BTC'})
assert len(w) == 1
assert issubclass(w[-1].category, DeprecationWarning)
assert "deprecated - check out the Sample strategy to see the current function headers!" \
@@ -381,8 +377,6 @@ def test_call_deprecated_function(result, monkeypatch, default_conf, caplog):
assert strategy._populate_fun_len == 2
assert strategy._buy_fun_len == 2
assert strategy._sell_fun_len == 2
# assert strategy._short_fun_len == 2
# assert strategy._exit_short_fun_len == 2
assert strategy.INTERFACE_VERSION == 1
assert strategy.timeframe == '5m'
assert strategy.ticker_interval == '5m'
@@ -391,22 +385,14 @@ def test_call_deprecated_function(result, monkeypatch, default_conf, caplog):
assert isinstance(indicator_df, DataFrame)
assert 'adx' in indicator_df.columns
buydf = strategy.advise_enter(result, metadata=metadata, is_short=False)
buydf = strategy.advise_buy(result, metadata=metadata)
assert isinstance(buydf, DataFrame)
assert 'buy' in buydf.columns
selldf = strategy.advise_exit(result, metadata=metadata, is_short=False)
selldf = strategy.advise_sell(result, metadata=metadata)
assert isinstance(selldf, DataFrame)
assert 'sell' in selldf
# shortdf = strategy.advise_enter(result, metadata=metadata, is_short=True)
# assert isinstance(shortdf, DataFrame)
# assert 'short' in shortdf.columns
# exit_shortdf = strategy.advise_exit(result, metadata=metadata, is_short=True)
# assert isinstance(exit_shortdf, DataFrame)
# assert 'exit_short' in exit_shortdf
assert log_has("DEPRECATED: Please migrate to using 'timeframe' instead of 'ticker_interval'.",
caplog)
@@ -420,26 +406,18 @@ def test_strategy_interface_versioning(result, monkeypatch, default_conf):
assert strategy._populate_fun_len == 3
assert strategy._buy_fun_len == 3
assert strategy._sell_fun_len == 3
assert strategy._short_fun_len == 3
assert strategy._exit_short_fun_len == 3
assert strategy.INTERFACE_VERSION == 2
indicator_df = strategy.advise_indicators(result, metadata=metadata)
assert isinstance(indicator_df, DataFrame)
assert 'adx' in indicator_df.columns
buydf = strategy.advise_enter(result, metadata=metadata, is_short=False)
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
assert 'enter_short' in enterdf.columns
selldf = strategy.advise_exit(result, metadata=metadata, is_short=False)
assert isinstance(selldf, DataFrame)
assert 'sell' in selldf
shortdf = strategy.advise_enter(result, metadata=metadata, is_short=True)
assert isinstance(shortdf, DataFrame)
assert 'short' in shortdf.columns
exit_shortdf = strategy.advise_exit(result, metadata=metadata, is_short=True)
assert isinstance(exit_shortdf, DataFrame)
assert 'exit_short' in exit_shortdf
exitdf = strategy.advise_sell(result, metadata=metadata)
assert isinstance(exitdf, DataFrame)
assert 'sell' in exitdf
assert 'exit_short' in exitdf.columns