623 lines
26 KiB
Python
623 lines
26 KiB
Python
# pragma pylint: disable=missing-docstring, C0103
|
|
import logging
|
|
from datetime import datetime, timedelta, timezone
|
|
from unittest.mock import MagicMock
|
|
|
|
import arrow
|
|
import pytest
|
|
from pandas import DataFrame
|
|
|
|
from freqtrade.configuration import TimeRange
|
|
from freqtrade.data.dataprovider import DataProvider
|
|
from freqtrade.data.history import load_data
|
|
from freqtrade.exceptions import OperationalException, StrategyError
|
|
from freqtrade.persistence import PairLocks, Trade
|
|
from freqtrade.resolvers import StrategyResolver
|
|
from freqtrade.strategy.hyper import (BaseParameter, CategoricalParameter, DecimalParameter,
|
|
IntParameter, RealParameter)
|
|
from freqtrade.strategy.interface import SellCheckTuple, SellType
|
|
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
|
|
from tests.conftest import log_has, log_has_re
|
|
|
|
from .strats.default_strategy import DefaultStrategy
|
|
|
|
|
|
# Avoid to reinit the same object again and again
|
|
_STRATEGY = DefaultStrategy(config={})
|
|
_STRATEGY.dp = DataProvider({}, None, None)
|
|
|
|
|
|
def test_returns_latest_signal(mocker, default_conf, ohlcv_history):
|
|
ohlcv_history.loc[1, 'date'] = arrow.utcnow()
|
|
# Take a copy to correctly modify the call
|
|
mocked_history = ohlcv_history.copy()
|
|
mocked_history['sell'] = 0
|
|
mocked_history['buy'] = 0
|
|
mocked_history.loc[1, 'sell'] = 1
|
|
|
|
assert _STRATEGY.get_signal('ETH/BTC', '5m', mocked_history) == (False, True)
|
|
mocked_history.loc[1, 'sell'] = 0
|
|
mocked_history.loc[1, 'buy'] = 1
|
|
|
|
assert _STRATEGY.get_signal('ETH/BTC', '5m', mocked_history) == (True, False)
|
|
mocked_history.loc[1, 'sell'] = 0
|
|
mocked_history.loc[1, 'buy'] = 0
|
|
|
|
assert _STRATEGY.get_signal('ETH/BTC', '5m', mocked_history) == (False, False)
|
|
|
|
|
|
def test_analyze_pair_empty(default_conf, mocker, caplog, ohlcv_history):
|
|
mocker.patch.object(_STRATEGY.dp, 'ohlcv', return_value=ohlcv_history)
|
|
mocker.patch.object(
|
|
_STRATEGY, '_analyze_ticker_internal',
|
|
return_value=DataFrame([])
|
|
)
|
|
mocker.patch.object(_STRATEGY, 'assert_df')
|
|
|
|
_STRATEGY.analyze_pair('ETH/BTC')
|
|
|
|
assert log_has('Empty dataframe for pair ETH/BTC', caplog)
|
|
|
|
|
|
def test_get_signal_empty(default_conf, mocker, caplog):
|
|
assert (False, False) == _STRATEGY.get_signal('foo', default_conf['timeframe'], DataFrame())
|
|
assert log_has('Empty candle (OHLCV) data for pair foo', caplog)
|
|
caplog.clear()
|
|
|
|
assert (False, False) == _STRATEGY.get_signal('bar', default_conf['timeframe'], None)
|
|
assert log_has('Empty candle (OHLCV) data for pair bar', caplog)
|
|
caplog.clear()
|
|
|
|
assert (False, False) == _STRATEGY.get_signal('baz', default_conf['timeframe'], DataFrame([]))
|
|
assert log_has('Empty candle (OHLCV) data for pair baz', caplog)
|
|
|
|
|
|
def test_get_signal_exception_valueerror(default_conf, mocker, caplog, ohlcv_history):
|
|
caplog.set_level(logging.INFO)
|
|
mocker.patch.object(_STRATEGY.dp, 'ohlcv', return_value=ohlcv_history)
|
|
mocker.patch.object(
|
|
_STRATEGY, '_analyze_ticker_internal',
|
|
side_effect=ValueError('xyz')
|
|
)
|
|
_STRATEGY.analyze_pair('foo')
|
|
assert log_has_re(r'Strategy caused the following exception: xyz.*', caplog)
|
|
caplog.clear()
|
|
|
|
mocker.patch.object(
|
|
_STRATEGY, 'analyze_ticker',
|
|
side_effect=Exception('invalid ticker history ')
|
|
)
|
|
_STRATEGY.analyze_pair('foo')
|
|
assert log_has_re(r'Strategy caused the following exception: xyz.*', caplog)
|
|
|
|
|
|
def test_get_signal_old_dataframe(default_conf, mocker, caplog, ohlcv_history):
|
|
# default_conf defines a 5m interval. we check interval * 2 + 5m
|
|
# this is necessary as the last candle is removed (partial candles) by default
|
|
ohlcv_history.loc[1, 'date'] = arrow.utcnow().shift(minutes=-16)
|
|
# Take a copy to correctly modify the call
|
|
mocked_history = ohlcv_history.copy()
|
|
mocked_history['sell'] = 0
|
|
mocked_history['buy'] = 0
|
|
mocked_history.loc[1, 'buy'] = 1
|
|
|
|
caplog.set_level(logging.INFO)
|
|
mocker.patch.object(_STRATEGY, 'assert_df')
|
|
|
|
assert (False, False) == _STRATEGY.get_signal('xyz', default_conf['timeframe'], mocked_history)
|
|
assert log_has('Outdated history for pair xyz. Last tick is 16 minutes old', caplog)
|
|
|
|
|
|
def test_ignore_expired_candle(default_conf):
|
|
default_conf.update({'strategy': 'DefaultStrategy'})
|
|
strategy = StrategyResolver.load_strategy(default_conf)
|
|
strategy.ignore_buying_expired_candle_after = 60
|
|
|
|
latest_date = datetime(2020, 12, 30, 7, 0, 0, tzinfo=timezone.utc)
|
|
# Add 1 candle length as the "latest date" defines candle open.
|
|
current_time = latest_date + timedelta(seconds=80 + 300)
|
|
|
|
assert strategy.ignore_expired_candle(latest_date=latest_date,
|
|
current_time=current_time,
|
|
timeframe_seconds=300,
|
|
buy=True) is True
|
|
|
|
current_time = latest_date + timedelta(seconds=30 + 300)
|
|
|
|
assert not strategy.ignore_expired_candle(latest_date=latest_date,
|
|
current_time=current_time,
|
|
timeframe_seconds=300,
|
|
buy=True) is True
|
|
|
|
|
|
def test_assert_df_raise(mocker, caplog, ohlcv_history):
|
|
ohlcv_history.loc[1, 'date'] = arrow.utcnow().shift(minutes=-16)
|
|
# Take a copy to correctly modify the call
|
|
mocked_history = ohlcv_history.copy()
|
|
mocked_history['sell'] = 0
|
|
mocked_history['buy'] = 0
|
|
mocked_history.loc[1, 'buy'] = 1
|
|
|
|
caplog.set_level(logging.INFO)
|
|
mocker.patch.object(_STRATEGY.dp, 'ohlcv', return_value=ohlcv_history)
|
|
mocker.patch.object(_STRATEGY.dp, 'get_analyzed_dataframe', return_value=(mocked_history, 0))
|
|
mocker.patch.object(
|
|
_STRATEGY, 'assert_df',
|
|
side_effect=StrategyError('Dataframe returned...')
|
|
)
|
|
_STRATEGY.analyze_pair('xyz')
|
|
assert log_has('Unable to analyze candle (OHLCV) data for pair xyz: Dataframe returned...',
|
|
caplog)
|
|
|
|
|
|
def test_assert_df(ohlcv_history, caplog):
|
|
df_len = len(ohlcv_history) - 1
|
|
# Ensure it's running when passed correctly
|
|
_STRATEGY.assert_df(ohlcv_history, len(ohlcv_history),
|
|
ohlcv_history.loc[df_len, 'close'], ohlcv_history.loc[df_len, 'date'])
|
|
|
|
with pytest.raises(StrategyError, match=r"Dataframe returned from strategy.*length\."):
|
|
_STRATEGY.assert_df(ohlcv_history, len(ohlcv_history) + 1,
|
|
ohlcv_history.loc[df_len, 'close'], ohlcv_history.loc[df_len, 'date'])
|
|
|
|
with pytest.raises(StrategyError,
|
|
match=r"Dataframe returned from strategy.*last close price\."):
|
|
_STRATEGY.assert_df(ohlcv_history, len(ohlcv_history),
|
|
ohlcv_history.loc[df_len, 'close'] + 0.01,
|
|
ohlcv_history.loc[df_len, 'date'])
|
|
with pytest.raises(StrategyError,
|
|
match=r"Dataframe returned from strategy.*last date\."):
|
|
_STRATEGY.assert_df(ohlcv_history, len(ohlcv_history),
|
|
ohlcv_history.loc[df_len, 'close'], ohlcv_history.loc[0, 'date'])
|
|
|
|
_STRATEGY.disable_dataframe_checks = True
|
|
caplog.clear()
|
|
_STRATEGY.assert_df(ohlcv_history, len(ohlcv_history),
|
|
ohlcv_history.loc[2, 'close'], ohlcv_history.loc[0, 'date'])
|
|
assert log_has_re(r"Dataframe returned from strategy.*last date\.", caplog)
|
|
# reset to avoid problems in other tests due to test leakage
|
|
_STRATEGY.disable_dataframe_checks = False
|
|
|
|
|
|
def test_ohlcvdata_to_dataframe(default_conf, testdatadir) -> None:
|
|
default_conf.update({'strategy': 'DefaultStrategy'})
|
|
strategy = StrategyResolver.load_strategy(default_conf)
|
|
|
|
timerange = TimeRange.parse_timerange('1510694220-1510700340')
|
|
data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
|
|
fill_up_missing=True)
|
|
processed = strategy.ohlcvdata_to_dataframe(data)
|
|
assert len(processed['UNITTEST/BTC']) == 102 # partial candle was removed
|
|
|
|
|
|
def test_ohlcvdata_to_dataframe_copy(mocker, default_conf, testdatadir) -> None:
|
|
default_conf.update({'strategy': 'DefaultStrategy'})
|
|
strategy = StrategyResolver.load_strategy(default_conf)
|
|
aimock = mocker.patch('freqtrade.strategy.interface.IStrategy.advise_indicators')
|
|
timerange = TimeRange.parse_timerange('1510694220-1510700340')
|
|
data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
|
|
fill_up_missing=True)
|
|
strategy.ohlcvdata_to_dataframe(data)
|
|
assert aimock.call_count == 1
|
|
# Ensure that a copy of the dataframe is passed to advice_indicators
|
|
assert aimock.call_args_list[0][0][0] is not data
|
|
|
|
|
|
def test_min_roi_reached(default_conf, fee) -> None:
|
|
|
|
# Use list to confirm sequence does not matter
|
|
min_roi_list = [{20: 0.05, 55: 0.01, 0: 0.1},
|
|
{0: 0.1, 20: 0.05, 55: 0.01}]
|
|
for roi in min_roi_list:
|
|
default_conf.update({'strategy': 'DefaultStrategy'})
|
|
strategy = StrategyResolver.load_strategy(default_conf)
|
|
strategy.minimal_roi = roi
|
|
trade = Trade(
|
|
pair='ETH/BTC',
|
|
stake_amount=0.001,
|
|
amount=5,
|
|
open_date=arrow.utcnow().shift(hours=-1).datetime,
|
|
fee_open=fee.return_value,
|
|
fee_close=fee.return_value,
|
|
exchange='bittrex',
|
|
open_rate=1,
|
|
)
|
|
|
|
assert not strategy.min_roi_reached(trade, 0.02, arrow.utcnow().shift(minutes=-56).datetime)
|
|
assert strategy.min_roi_reached(trade, 0.12, arrow.utcnow().shift(minutes=-56).datetime)
|
|
|
|
assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-39).datetime)
|
|
assert strategy.min_roi_reached(trade, 0.06, arrow.utcnow().shift(minutes=-39).datetime)
|
|
|
|
assert not strategy.min_roi_reached(trade, -0.01, arrow.utcnow().shift(minutes=-1).datetime)
|
|
assert strategy.min_roi_reached(trade, 0.02, arrow.utcnow().shift(minutes=-1).datetime)
|
|
|
|
|
|
def test_min_roi_reached2(default_conf, fee) -> None:
|
|
|
|
# test with ROI raising after last interval
|
|
min_roi_list = [{20: 0.07,
|
|
30: 0.05,
|
|
55: 0.30,
|
|
0: 0.1
|
|
},
|
|
{0: 0.1,
|
|
20: 0.07,
|
|
30: 0.05,
|
|
55: 0.30
|
|
},
|
|
]
|
|
for roi in min_roi_list:
|
|
default_conf.update({'strategy': 'DefaultStrategy'})
|
|
strategy = StrategyResolver.load_strategy(default_conf)
|
|
strategy.minimal_roi = roi
|
|
trade = Trade(
|
|
pair='ETH/BTC',
|
|
stake_amount=0.001,
|
|
amount=5,
|
|
open_date=arrow.utcnow().shift(hours=-1).datetime,
|
|
fee_open=fee.return_value,
|
|
fee_close=fee.return_value,
|
|
exchange='bittrex',
|
|
open_rate=1,
|
|
)
|
|
|
|
assert not strategy.min_roi_reached(trade, 0.02, arrow.utcnow().shift(minutes=-56).datetime)
|
|
assert strategy.min_roi_reached(trade, 0.12, arrow.utcnow().shift(minutes=-56).datetime)
|
|
|
|
assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-39).datetime)
|
|
assert strategy.min_roi_reached(trade, 0.071, arrow.utcnow().shift(minutes=-39).datetime)
|
|
|
|
assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-26).datetime)
|
|
assert strategy.min_roi_reached(trade, 0.06, arrow.utcnow().shift(minutes=-26).datetime)
|
|
|
|
# Should not trigger with 20% profit since after 55 minutes only 30% is active.
|
|
assert not strategy.min_roi_reached(trade, 0.20, arrow.utcnow().shift(minutes=-2).datetime)
|
|
assert strategy.min_roi_reached(trade, 0.31, arrow.utcnow().shift(minutes=-2).datetime)
|
|
|
|
|
|
def test_min_roi_reached3(default_conf, fee) -> None:
|
|
|
|
# test for issue #1948
|
|
min_roi = {20: 0.07,
|
|
30: 0.05,
|
|
55: 0.30,
|
|
}
|
|
default_conf.update({'strategy': 'DefaultStrategy'})
|
|
strategy = StrategyResolver.load_strategy(default_conf)
|
|
strategy.minimal_roi = min_roi
|
|
trade = Trade(
|
|
pair='ETH/BTC',
|
|
stake_amount=0.001,
|
|
amount=5,
|
|
open_date=arrow.utcnow().shift(hours=-1).datetime,
|
|
fee_open=fee.return_value,
|
|
fee_close=fee.return_value,
|
|
exchange='bittrex',
|
|
open_rate=1,
|
|
)
|
|
|
|
assert not strategy.min_roi_reached(trade, 0.02, arrow.utcnow().shift(minutes=-56).datetime)
|
|
assert not strategy.min_roi_reached(trade, 0.12, arrow.utcnow().shift(minutes=-56).datetime)
|
|
|
|
assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-39).datetime)
|
|
assert strategy.min_roi_reached(trade, 0.071, arrow.utcnow().shift(minutes=-39).datetime)
|
|
|
|
assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-26).datetime)
|
|
assert strategy.min_roi_reached(trade, 0.06, arrow.utcnow().shift(minutes=-26).datetime)
|
|
|
|
# Should not trigger with 20% profit since after 55 minutes only 30% is active.
|
|
assert not strategy.min_roi_reached(trade, 0.20, arrow.utcnow().shift(minutes=-2).datetime)
|
|
assert strategy.min_roi_reached(trade, 0.31, arrow.utcnow().shift(minutes=-2).datetime)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
'profit,adjusted,expected,trailing,custom,profit2,adjusted2,expected2,custom_stop', [
|
|
# Profit, adjusted stoploss(absolute), profit for 2nd call, enable trailing,
|
|
# enable custom stoploss, expected after 1st call, expected after 2nd call
|
|
(0.2, 0.9, SellType.NONE, False, False, 0.3, 0.9, SellType.NONE, None),
|
|
(0.2, 0.9, SellType.NONE, False, False, -0.2, 0.9, SellType.STOP_LOSS, None),
|
|
(0.2, 1.14, SellType.NONE, True, False, 0.05, 1.14, SellType.TRAILING_STOP_LOSS, None),
|
|
(0.01, 0.96, SellType.NONE, True, False, 0.05, 1, SellType.NONE, None),
|
|
(0.05, 1, SellType.NONE, True, False, -0.01, 1, SellType.TRAILING_STOP_LOSS, None),
|
|
# Default custom case - trails with 10%
|
|
(0.05, 0.95, SellType.NONE, False, True, -0.02, 0.95, SellType.NONE, None),
|
|
(0.05, 0.95, SellType.NONE, False, True, -0.06, 0.95, SellType.TRAILING_STOP_LOSS, None),
|
|
(0.05, 1, SellType.NONE, False, True, -0.06, 1, SellType.TRAILING_STOP_LOSS,
|
|
lambda **kwargs: -0.05),
|
|
(0.05, 1, SellType.NONE, False, True, 0.09, 1.04, SellType.NONE,
|
|
lambda **kwargs: -0.05),
|
|
(0.05, 0.95, SellType.NONE, False, True, 0.09, 0.98, SellType.NONE,
|
|
lambda current_profit, **kwargs: -0.1 if current_profit < 0.6 else -(current_profit * 2)),
|
|
# Error case - static stoploss in place
|
|
(0.05, 0.9, SellType.NONE, False, True, 0.09, 0.9, SellType.NONE,
|
|
lambda **kwargs: None),
|
|
])
|
|
def test_stop_loss_reached(default_conf, fee, profit, adjusted, expected, trailing, custom,
|
|
profit2, adjusted2, expected2, custom_stop) -> None:
|
|
|
|
default_conf.update({'strategy': 'DefaultStrategy'})
|
|
|
|
strategy = StrategyResolver.load_strategy(default_conf)
|
|
trade = Trade(
|
|
pair='ETH/BTC',
|
|
stake_amount=0.01,
|
|
amount=1,
|
|
open_date=arrow.utcnow().shift(hours=-1).datetime,
|
|
fee_open=fee.return_value,
|
|
fee_close=fee.return_value,
|
|
exchange='bittrex',
|
|
open_rate=1,
|
|
)
|
|
trade.adjust_min_max_rates(trade.open_rate)
|
|
strategy.trailing_stop = trailing
|
|
strategy.trailing_stop_positive = -0.05
|
|
strategy.use_custom_stoploss = custom
|
|
original_stopvalue = strategy.custom_stoploss
|
|
if custom_stop:
|
|
strategy.custom_stoploss = custom_stop
|
|
|
|
now = arrow.utcnow().datetime
|
|
sl_flag = strategy.stop_loss_reached(current_rate=trade.open_rate * (1 + profit), trade=trade,
|
|
current_time=now, current_profit=profit,
|
|
force_stoploss=0, high=None)
|
|
assert isinstance(sl_flag, SellCheckTuple)
|
|
assert sl_flag.sell_type == expected
|
|
if expected == SellType.NONE:
|
|
assert sl_flag.sell_flag is False
|
|
else:
|
|
assert sl_flag.sell_flag is True
|
|
assert round(trade.stop_loss, 2) == adjusted
|
|
|
|
sl_flag = strategy.stop_loss_reached(current_rate=trade.open_rate * (1 + profit2), trade=trade,
|
|
current_time=now, current_profit=profit2,
|
|
force_stoploss=0, high=None)
|
|
assert sl_flag.sell_type == expected2
|
|
if expected2 == SellType.NONE:
|
|
assert sl_flag.sell_flag is False
|
|
else:
|
|
assert sl_flag.sell_flag is True
|
|
assert round(trade.stop_loss, 2) == adjusted2
|
|
|
|
strategy.custom_stoploss = original_stopvalue
|
|
|
|
|
|
def test_analyze_ticker_default(ohlcv_history, mocker, caplog) -> None:
|
|
caplog.set_level(logging.DEBUG)
|
|
ind_mock = MagicMock(side_effect=lambda x, meta: 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_buy=buy_mock,
|
|
advise_sell=sell_mock,
|
|
|
|
)
|
|
strategy = DefaultStrategy({})
|
|
strategy.analyze_ticker(ohlcv_history, {'pair': 'ETH/BTC'})
|
|
assert ind_mock.call_count == 1
|
|
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()
|
|
|
|
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 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)
|
|
|
|
|
|
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)
|
|
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_buy=buy_mock,
|
|
advise_sell=sell_mock,
|
|
|
|
)
|
|
strategy = DefaultStrategy({})
|
|
strategy.dp = DataProvider({}, None, None)
|
|
strategy.process_only_new_candles = True
|
|
|
|
ret = strategy._analyze_ticker_internal(ohlcv_history, {'pair': 'ETH/BTC'})
|
|
assert 'high' in ret.columns
|
|
assert 'low' in ret.columns
|
|
assert 'close' in ret.columns
|
|
assert isinstance(ret, DataFrame)
|
|
assert ind_mock.call_count == 1
|
|
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()
|
|
|
|
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 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
|
|
assert ret['buy'].sum() == 0
|
|
assert ret['sell'].sum() == 0
|
|
assert not log_has('TA Analysis Launched', caplog)
|
|
assert log_has('Skipping TA Analysis for already analyzed candle', caplog)
|
|
|
|
|
|
@pytest.mark.usefixtures("init_persistence")
|
|
def test_is_pair_locked(default_conf):
|
|
default_conf.update({'strategy': 'DefaultStrategy'})
|
|
PairLocks.timeframe = default_conf['timeframe']
|
|
strategy = StrategyResolver.load_strategy(default_conf)
|
|
# No lock should be present
|
|
assert len(PairLocks.get_pair_locks(None)) == 0
|
|
|
|
pair = 'ETH/BTC'
|
|
assert not strategy.is_pair_locked(pair)
|
|
strategy.lock_pair(pair, arrow.now(timezone.utc).shift(minutes=4).datetime)
|
|
# ETH/BTC locked for 4 minutes
|
|
assert strategy.is_pair_locked(pair)
|
|
|
|
# XRP/BTC should not be locked now
|
|
pair = 'XRP/BTC'
|
|
assert not strategy.is_pair_locked(pair)
|
|
|
|
# Unlocking a pair that's not locked should not raise an error
|
|
strategy.unlock_pair(pair)
|
|
|
|
# Unlock original pair
|
|
pair = 'ETH/BTC'
|
|
strategy.unlock_pair(pair)
|
|
assert not strategy.is_pair_locked(pair)
|
|
|
|
pair = 'BTC/USDT'
|
|
# Lock until 14:30
|
|
lock_time = datetime(2020, 5, 1, 14, 30, 0, tzinfo=timezone.utc)
|
|
# Subtract 2 seconds, as locking rounds up to the next candle.
|
|
strategy.lock_pair(pair, lock_time - timedelta(seconds=2))
|
|
|
|
assert not strategy.is_pair_locked(pair)
|
|
# latest candle is from 14:20, lock goes to 14:30
|
|
assert strategy.is_pair_locked(pair, lock_time + timedelta(minutes=-10))
|
|
assert strategy.is_pair_locked(pair, lock_time + timedelta(minutes=-50))
|
|
|
|
# latest candle is from 14:25 (lock should be lifted)
|
|
# Since this is the "new candle" available at 14:30
|
|
assert not strategy.is_pair_locked(pair, lock_time + timedelta(minutes=-4))
|
|
|
|
# Should not be locked after time expired
|
|
assert not strategy.is_pair_locked(pair, lock_time + timedelta(minutes=10))
|
|
|
|
# Change timeframe to 15m
|
|
strategy.timeframe = '15m'
|
|
# Candle from 14:14 - lock goes until 14:30
|
|
assert strategy.is_pair_locked(pair, lock_time + timedelta(minutes=-16))
|
|
assert strategy.is_pair_locked(pair, lock_time + timedelta(minutes=-15, seconds=-2))
|
|
# Candle from 14:15 - lock goes until 14:30
|
|
assert not strategy.is_pair_locked(pair, lock_time + timedelta(minutes=-15))
|
|
|
|
|
|
def test_is_informative_pairs_callback(default_conf):
|
|
default_conf.update({'strategy': 'TestStrategyLegacy'})
|
|
strategy = StrategyResolver.load_strategy(default_conf)
|
|
# Should return empty
|
|
# Uses fallback to base implementation
|
|
assert [] == strategy.informative_pairs()
|
|
|
|
|
|
@pytest.mark.parametrize('error', [
|
|
ValueError, KeyError, Exception,
|
|
])
|
|
def test_strategy_safe_wrapper_error(caplog, error):
|
|
def failing_method():
|
|
raise error('This is an error.')
|
|
|
|
def working_method(argumentpassedin):
|
|
return argumentpassedin
|
|
|
|
with pytest.raises(StrategyError, match=r'This is an error.'):
|
|
strategy_safe_wrapper(failing_method, message='DeadBeef')()
|
|
|
|
assert log_has_re(r'DeadBeef.*', caplog)
|
|
ret = strategy_safe_wrapper(failing_method, message='DeadBeef', default_retval=True)()
|
|
|
|
assert isinstance(ret, bool)
|
|
assert ret
|
|
|
|
caplog.clear()
|
|
# Test supressing error
|
|
ret = strategy_safe_wrapper(failing_method, message='DeadBeef', supress_error=True)()
|
|
assert log_has_re(r'DeadBeef.*', caplog)
|
|
|
|
|
|
@pytest.mark.parametrize('value', [
|
|
1, 22, 55, True, False, {'a': 1, 'b': '112'},
|
|
[1, 2, 3, 4], (4, 2, 3, 6)
|
|
])
|
|
def test_strategy_safe_wrapper(value):
|
|
|
|
def working_method(argumentpassedin):
|
|
return argumentpassedin
|
|
|
|
ret = strategy_safe_wrapper(working_method, message='DeadBeef')(value)
|
|
|
|
assert type(ret) == type(value)
|
|
assert ret == value
|
|
|
|
|
|
def test_hyperopt_parameters():
|
|
from skopt.space import Categorical, Integer, Real
|
|
with pytest.raises(OperationalException, match=r"Name is determined.*"):
|
|
IntParameter(low=0, high=5, default=1, name='hello')
|
|
|
|
with pytest.raises(OperationalException, match=r"IntParameter space must be.*"):
|
|
IntParameter(low=0, default=5, space='buy')
|
|
|
|
with pytest.raises(OperationalException, match=r"RealParameter space must be.*"):
|
|
RealParameter(low=0, default=5, space='buy')
|
|
|
|
with pytest.raises(OperationalException, match=r"DecimalParameter space must be.*"):
|
|
DecimalParameter(low=0, default=5, space='buy')
|
|
|
|
with pytest.raises(OperationalException, match=r"IntParameter space invalid\."):
|
|
IntParameter([0, 10], high=7, default=5, space='buy')
|
|
|
|
with pytest.raises(OperationalException, match=r"RealParameter space invalid\."):
|
|
RealParameter([0, 10], high=7, default=5, space='buy')
|
|
|
|
with pytest.raises(OperationalException, match=r"DecimalParameter space invalid\."):
|
|
DecimalParameter([0, 10], high=7, default=5, space='buy')
|
|
|
|
with pytest.raises(OperationalException, match=r"CategoricalParameter space must.*"):
|
|
CategoricalParameter(['aa'], default='aa', space='buy')
|
|
|
|
with pytest.raises(TypeError):
|
|
BaseParameter(opt_range=[0, 1], default=1, space='buy')
|
|
|
|
intpar = IntParameter(low=0, high=5, default=1, space='buy')
|
|
assert intpar.value == 1
|
|
assert isinstance(intpar.get_space(''), Integer)
|
|
|
|
fltpar = RealParameter(low=0.0, high=5.5, default=1.0, space='buy')
|
|
assert isinstance(fltpar.get_space(''), Real)
|
|
assert fltpar.value == 1
|
|
|
|
fltpar = DecimalParameter(low=0.0, high=5.5, default=1.0004, decimals=3, space='buy')
|
|
assert isinstance(fltpar.get_space(''), Integer)
|
|
assert fltpar.value == 1
|
|
|
|
catpar = CategoricalParameter(['buy_rsi', 'buy_macd', 'buy_none'],
|
|
default='buy_macd', space='buy')
|
|
assert isinstance(catpar.get_space(''), Categorical)
|
|
assert catpar.value == 'buy_macd'
|
|
|
|
|
|
def test_auto_hyperopt_interface(default_conf):
|
|
default_conf.update({'strategy': 'HyperoptableStrategy'})
|
|
PairLocks.timeframe = default_conf['timeframe']
|
|
strategy = StrategyResolver.load_strategy(default_conf)
|
|
|
|
assert strategy.buy_rsi.value == strategy.buy_params['buy_rsi']
|
|
# PlusDI is NOT in the buy-params, so default should be used
|
|
assert strategy.buy_plusdi.value == 0.5
|
|
assert strategy.sell_rsi.value == strategy.sell_params['sell_rsi']
|
|
|
|
# Parameter is disabled - so value from sell_param dict will NOT be used.
|
|
assert strategy.sell_minusdi.value == 0.5
|
|
|
|
strategy.sell_rsi = IntParameter([0, 10], default=5, space='buy')
|
|
|
|
with pytest.raises(OperationalException, match=r"Inconclusive parameter.*"):
|
|
[x for x in strategy.enumerate_parameters('sell')]
|