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Simplify calling backtesting by returning the proper result

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This commit is contained in:
Matthias 2021-04-30 07:31:57 +02:00
parent e2e1d34828
commit f2e182002d
4 changed files with 83 additions and 66 deletions
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20
freqtrade/optimize/backtesting.py
View File

@ -330,7 +330,7 @@ class Backtesting:
def backtest(self, processed: Dict,
start_date: datetime, end_date: datetime,
max_open_trades: int = 0, position_stacking: bool = False,
enable_protections: bool = False) -> DataFrame:
enable_protections: bool = False) -> Dict[str, Any]:
"""
Implement backtesting functionality
@ -417,7 +417,13 @@ class Backtesting:
trades += self.handle_left_open(open_trades, data=data)
self.wallets.update()
return trade_list_to_dataframe(trades)
results = trade_list_to_dataframe(trades)
return {
'results': results,
'config': self.strategy.config,
'locks': PairLocks.get_all_locks(),
'final_balance': self.wallets.get_total(self.strategy.config['stake_currency']),
}
def backtest_one_strategy(self, strat: IStrategy, data: Dict[str, Any], timerange: TimeRange):
logger.info("Running backtesting for Strategy %s", strat.get_strategy_name())
@ -457,14 +463,12 @@ class Backtesting:
enable_protections=self.config.get('enable_protections', False),
)
backtest_end_time = datetime.now(timezone.utc)
self.all_results[self.strategy.get_strategy_name()] = {
'results': results,
'config': self.strategy.config,
'locks': PairLocks.get_all_locks(),
'final_balance': self.wallets.get_total(self.strategy.config['stake_currency']),
results.update({
'backtest_start_time': int(backtest_start_time.timestamp()),
'backtest_end_time': int(backtest_end_time.timestamp()),
}
})
self.all_results[self.strategy.get_strategy_name()] = results
return min_date, max_date
def start(self) -> None:

16
freqtrade/optimize/hyperopt.py
View File

@ -31,7 +31,6 @@ from freqtrade.optimize.hyperopt_interface import IHyperOpt # noqa: F401
from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss # noqa: F401
from freqtrade.optimize.hyperopt_tools import HyperoptTools
from freqtrade.optimize.optimize_reports import generate_strategy_stats
from freqtrade.persistence.pairlock_middleware import PairLocks
from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver, HyperOptResolver
from freqtrade.strategy import IStrategy
@ -279,7 +278,7 @@ class Hyperopt:
min_date, max_date = get_timerange(processed)
backtesting_results = self.backtesting.backtest(
bt_results = self.backtesting.backtest(
processed=processed,
start_date=min_date.datetime,
end_date=max_date.datetime,
@ -288,17 +287,12 @@ class Hyperopt:
enable_protections=self.config.get('enable_protections', False),
)
backtest_end_time = datetime.now(timezone.utc)
bt_result = {
'results': backtesting_results,
'config': self.backtesting.strategy.config,
'locks': PairLocks.get_all_locks(),
'final_balance': self.backtesting.wallets.get_total(
self.backtesting.strategy.config['stake_currency']),
bt_results.update({
'backtest_start_time': int(backtest_start_time.timestamp()),
'backtest_end_time': int(backtest_end_time.timestamp()),
}
return self._get_results_dict(bt_result, min_date, max_date,
})
return self._get_results_dict(bt_results, min_date, max_date,
params_dict, params_details,
processed=processed)

2
freqtrade/optimize/optimize_reports.py
View File

@ -274,7 +274,7 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
"""
results: Dict[str, DataFrame] = content['results']
if not isinstance(results, DataFrame):
return
return {}
config = content['config']
max_open_trades = min(config['max_open_trades'], len(btdata.keys()))
starting_balance = config['dry_run_wallet']

111
tests/optimize/test_backtesting.py
View File

@ -514,13 +514,14 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
timerange=timerange)
processed = backtesting.strategy.ohlcvdata_to_dataframe(data)
min_date, max_date = get_timerange(processed)
results = backtesting.backtest(
result = backtesting.backtest(
processed=processed,
start_date=min_date,
end_date=max_date,
max_open_trades=10,
position_stacking=False,
)
results = result['results']
assert not results.empty
assert len(results) == 2
@ -583,8 +584,8 @@ def test_backtest_1min_timeframe(default_conf, fee, mocker, testdatadir) -> None
max_open_trades=1,
position_stacking=False,
)
assert not results.empty
assert len(results) == 1
assert not results['results'].empty
assert len(results['results']) == 1
def test_processed(default_conf, mocker, testdatadir) -> None:
@ -623,7 +624,7 @@ def test_backtest_pricecontours_protections(default_conf, fee, mocker, testdatad
# While buy-signals are unrealistic, running backtesting
# over and over again should not cause different results
for [contour, numres] in tests:
assert len(simple_backtest(default_conf, contour, mocker, testdatadir)) == numres
assert len(simple_backtest(default_conf, contour, mocker, testdatadir)['results']) == numres
@pytest.mark.parametrize('protections,contour,expected', [
@ -648,7 +649,7 @@ def test_backtest_pricecontours(default_conf, fee, mocker, testdatadir,
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
# While buy-signals are unrealistic, running backtesting
# over and over again should not cause different results
assert len(simple_backtest(default_conf, contour, mocker, testdatadir)) == expected
assert len(simple_backtest(default_conf, contour, mocker, testdatadir)['results']) == expected
def test_backtest_clash_buy_sell(mocker, default_conf, testdatadir):
@ -662,8 +663,8 @@ def test_backtest_clash_buy_sell(mocker, default_conf, testdatadir):
backtesting = Backtesting(default_conf)
backtesting.strategy.advise_buy = fun # Override
backtesting.strategy.advise_sell = fun # Override
results = backtesting.backtest(**backtest_conf)
assert results.empty
result = backtesting.backtest(**backtest_conf)
assert result['results'].empty
def test_backtest_only_sell(mocker, default_conf, testdatadir):
@ -677,8 +678,8 @@ def test_backtest_only_sell(mocker, default_conf, testdatadir):
backtesting = Backtesting(default_conf)
backtesting.strategy.advise_buy = fun # Override
backtesting.strategy.advise_sell = fun # Override
results = backtesting.backtest(**backtest_conf)
assert results.empty
result = backtesting.backtest(**backtest_conf)
assert result['results'].empty
def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir):
@ -690,10 +691,11 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir):
backtesting = Backtesting(default_conf)
backtesting.strategy.advise_buy = _trend_alternate # Override
backtesting.strategy.advise_sell = _trend_alternate # Override
results = backtesting.backtest(**backtest_conf)
result = backtesting.backtest(**backtest_conf)
# 200 candles in backtest data
# won't buy on first (shifted by 1)
# 100 buys signals
results = result['results']
assert len(results) == 100
# One trade was force-closed at the end
assert len(results.loc[results['is_open']]) == 0
@ -745,9 +747,9 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
results = backtesting.backtest(**backtest_conf)
# Make sure we have parallel trades
assert len(evaluate_result_multi(results, '5m', 2)) > 0
assert len(evaluate_result_multi(results['results'], '5m', 2)) > 0
# make sure we don't have trades with more than configured max_open_trades
assert len(evaluate_result_multi(results, '5m', 3)) == 0
assert len(evaluate_result_multi(results['results'], '5m', 3)) == 0
backtest_conf = {
'processed': processed,
@ -757,7 +759,7 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
'position_stacking': False,
}
results = backtesting.backtest(**backtest_conf)
assert len(evaluate_result_multi(results, '5m', 1)) == 0
assert len(evaluate_result_multi(results['results'], '5m', 1)) == 0
def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir):
@ -803,7 +805,12 @@ def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir):
def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
patch_exchange(mocker)
backtestmock = MagicMock(return_value=pd.DataFrame(columns=BT_DATA_COLUMNS))
backtestmock = MagicMock(return_value={
'results': pd.DataFrame(columns=BT_DATA_COLUMNS),
'config': default_conf,
'locks': [],
'final_balance': 1000,
})
mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist',
PropertyMock(return_value=['UNITTEST/BTC']))
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock)
@ -867,39 +874,51 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdatadir, capsys):
patch_exchange(mocker)
result1 = pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC'],
'profit_ratio': [0.0, 0.0],
'profit_abs': [0.0, 0.0],
'open_date': pd.to_datetime(['2018-01-29 18:40:00',
'2018-01-30 03:30:00', ], utc=True
),
'close_date': pd.to_datetime(['2018-01-29 20:45:00',
'2018-01-30 05:35:00', ], utc=True),
'trade_duration': [235, 40],
'is_open': [False, False],
'stake_amount': [0.01, 0.01],
'open_rate': [0.104445, 0.10302485],
'close_rate': [0.104969, 0.103541],
'sell_reason': [SellType.ROI, SellType.ROI]
})
result2 = pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC', 'ETH/BTC'],
'profit_ratio': [0.03, 0.01, 0.1],
'profit_abs': [0.01, 0.02, 0.2],
'open_date': pd.to_datetime(['2018-01-29 18:40:00',
'2018-01-30 03:30:00',
'2018-01-30 05:30:00'], utc=True
),
'close_date': pd.to_datetime(['2018-01-29 20:45:00',
'2018-01-30 05:35:00',
'2018-01-30 08:30:00'], utc=True),
'trade_duration': [47, 40, 20],
'is_open': [False, False, False],
'stake_amount': [0.01, 0.01, 0.01],
'open_rate': [0.104445, 0.10302485, 0.122541],
'close_rate': [0.104969, 0.103541, 0.123541],
'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
})
backtestmock = MagicMock(side_effect=[
pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC'],
'profit_ratio': [0.0, 0.0],
'profit_abs': [0.0, 0.0],
'open_date': pd.to_datetime(['2018-01-29 18:40:00',
'2018-01-30 03:30:00', ], utc=True
),
'close_date': pd.to_datetime(['2018-01-29 20:45:00',
'2018-01-30 05:35:00', ], utc=True),
'trade_duration': [235, 40],
'is_open': [False, False],
'stake_amount': [0.01, 0.01],
'open_rate': [0.104445, 0.10302485],
'close_rate': [0.104969, 0.103541],
'sell_reason': [SellType.ROI, SellType.ROI]
}),
pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC', 'ETH/BTC'],
'profit_ratio': [0.03, 0.01, 0.1],
'profit_abs': [0.01, 0.02, 0.2],
'open_date': pd.to_datetime(['2018-01-29 18:40:00',
'2018-01-30 03:30:00',
'2018-01-30 05:30:00'], utc=True
),
'close_date': pd.to_datetime(['2018-01-29 20:45:00',
'2018-01-30 05:35:00',
'2018-01-30 08:30:00'], utc=True),
'trade_duration': [47, 40, 20],
'is_open': [False, False, False],
'stake_amount': [0.01, 0.01, 0.01],
'open_rate': [0.104445, 0.10302485, 0.122541],
'close_rate': [0.104969, 0.103541, 0.123541],
'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
}),
{
'results': result1,
'config': default_conf,
'locks': [],
'final_balance': 1000,
},
{
'results': result2,
'config': default_conf,
'locks': [],
'final_balance': 1000,
}
])
mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist',
PropertyMock(return_value=['UNITTEST/BTC']))