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Merge branch 'develop' into pr/Antreasgr/4838

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Matthias
2021-05-27 14:58:19 +02:00
parent 3014bc3467 cf39dd2163
commit a89364aa98
95 changed files with 2815 additions and 1369 deletions
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24
tests/optimize/test_backtest_detail.py
View File

@@ -185,7 +185,7 @@ tc11 = BTContainer(data=[
[0, 5000, 5050, 4950, 5000, 6172, 1, 0],
[1, 5000, 5050, 4950, 5100, 6172, 0, 0],
[2, 5100, 5251, 5100, 5100, 6172, 0, 0],
[3, 4850, 5050, 4650, 4750, 6172, 0, 0],
[3, 5000, 5150, 4650, 4750, 6172, 0, 0],
[4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
stop_loss=-0.10, roi={"0": 0.10}, profit_perc=0.019, trailing_stop=True,
trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05,
@@ -440,6 +440,23 @@ tc27 = BTContainer(data=[
trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=4)]
)
# Test 28: trailing_stop should raise so candle 3 causes a stoploss
# Same case than tc11 - but candle 3 "gaps down" - the stoploss will be above the candle,
# therefore "open" will be used
# stop-loss: 10%, ROI: 10% (should not apply), stoploss adjusted candle 2
tc28 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5050, 4950, 5000, 6172, 1, 0],
[1, 5000, 5050, 4950, 5100, 6172, 0, 0],
[2, 5100, 5251, 5100, 5100, 6172, 0, 0],
[3, 4850, 5050, 4650, 4750, 6172, 0, 0],
[4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.03, trailing_stop=True,
trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05,
trailing_stop_positive=0.03,
trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
)
TESTS = [
tc0,
tc1,
@@ -469,6 +486,7 @@ TESTS = [
tc25,
tc26,
tc27,
tc28,
]
@@ -493,6 +511,7 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
patch_exchange(mocker)
frame = _build_backtest_dataframe(data.data)
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
backtesting.strategy.advise_buy = lambda a, m: frame
backtesting.strategy.advise_sell = lambda a, m: frame
caplog.set_level(logging.DEBUG)
@@ -501,13 +520,14 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
# Dummy data as we mock the analyze functions
data_processed = {pair: frame.copy()}
min_date, max_date = get_timerange({pair: frame})
results = backtesting.backtest(
result = backtesting.backtest(
processed=data_processed,
start_date=min_date,
end_date=max_date,
max_open_trades=10,
)
results = result['results']
assert len(results) == len(data.trades)
assert round(results["profit_ratio"].sum(), 3) == round(data.profit_perc, 3)

159
tests/optimize/test_backtesting.py
View File

@@ -83,6 +83,7 @@ def simple_backtest(config, contour, mocker, testdatadir) -> None:
patch_exchange(mocker)
config['timeframe'] = '1m'
backtesting = Backtesting(config)
backtesting._set_strategy(backtesting.strategylist[0])
data = load_data_test(contour, testdatadir)
processed = backtesting.strategy.ohlcvdata_to_dataframe(data)
@@ -106,6 +107,7 @@ def _make_backtest_conf(mocker, datadir, conf=None, pair='UNITTEST/BTC'):
data = trim_dictlist(data, -201)
patch_exchange(mocker)
backtesting = Backtesting(conf)
backtesting._set_strategy(backtesting.strategylist[0])
processed = backtesting.strategy.ohlcvdata_to_dataframe(data)
min_date, max_date = get_timerange(processed)
return {
@@ -285,6 +287,7 @@ def test_backtesting_init(mocker, default_conf, order_types) -> None:
patch_exchange(mocker)
get_fee = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5))
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
assert backtesting.config == default_conf
assert backtesting.timeframe == '5m'
assert callable(backtesting.strategy.ohlcvdata_to_dataframe)
@@ -315,11 +318,13 @@ def test_data_with_fee(default_conf, mocker, testdatadir) -> None:
fee_mock = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5))
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
assert backtesting.fee == 0.1234
assert fee_mock.call_count == 0
default_conf['fee'] = 0.0
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
assert backtesting.fee == 0.0
assert fee_mock.call_count == 0
@@ -330,6 +335,7 @@ def test_data_to_dataframe_bt(default_conf, mocker, testdatadir) -> None:
data = history.load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
fill_up_missing=True)
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
processed = backtesting.strategy.ohlcvdata_to_dataframe(data)
assert len(processed['UNITTEST/BTC']) == 102
@@ -361,12 +367,13 @@ def test_backtesting_start(default_conf, mocker, testdatadir, caplog) -> None:
default_conf['timerange'] = '-1510694220'
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
backtesting.strategy.bot_loop_start = MagicMock()
backtesting.start()
# check the logs, that will contain the backtest result
exists = [
'Backtesting with data from 2017-11-14 21:17:00 '
'up to 2017-11-14 22:59:00 (0 days)..'
'up to 2017-11-14 22:59:00 (0 days).'
]
for line in exists:
assert log_has(line, caplog)
@@ -393,6 +400,7 @@ def test_backtesting_start_no_data(default_conf, mocker, caplog, testdatadir) ->
default_conf['timerange'] = '20180101-20180102'
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
with pytest.raises(OperationalException, match='No data found. Terminating.'):
backtesting.start()
@@ -465,6 +473,7 @@ def test_backtest__enter_trade(default_conf, fee, mocker) -> None:
default_conf['stake_amount'] = 'unlimited'
default_conf['max_open_trades'] = 2
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
pair = 'UNITTEST/BTC'
row = [
pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=0),
@@ -508,19 +517,21 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
patch_exchange(mocker)
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
pair = 'UNITTEST/BTC'
timerange = TimeRange('date', None, 1517227800, 0)
data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=['UNITTEST/BTC'],
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
@@ -569,6 +580,7 @@ def test_backtest_1min_timeframe(default_conf, fee, mocker, testdatadir) -> None
mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
patch_exchange(mocker)
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
# Run a backtesting for an exiting 1min timeframe
timerange = TimeRange.parse_timerange('1510688220-1510700340')
@@ -583,13 +595,14 @@ 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:
patch_exchange(mocker)
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
dict_of_tickerrows = load_data_test('raise', testdatadir)
dataframes = backtesting.strategy.ohlcvdata_to_dataframe(dict_of_tickerrows)
@@ -623,7 +636,7 @@ 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 +661,7 @@ 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):
@@ -660,10 +673,11 @@ 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_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):
@@ -675,10 +689,11 @@ 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_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):
@@ -688,12 +703,14 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir):
pair='UNITTEST/BTC', datadir=testdatadir)
default_conf['timeframe'] = '1m'
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
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
@@ -729,6 +746,7 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
default_conf['timeframe'] = '5m'
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
backtesting.strategy.advise_buy = _trend_alternate_hold # Override
backtesting.strategy.advise_sell = _trend_alternate_hold # Override
@@ -745,9 +763,9 @@ 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 +775,7 @@ 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):
@@ -789,9 +807,9 @@ def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir):
'Parameter --timerange detected: 1510694220-1510700340 ...',
f'Using data directory: {testdatadir} ...',
'Loading data from 2017-11-14 20:57:00 '
'up to 2017-11-14 22:58:00 (0 days)..',
'up to 2017-11-14 22:58:00 (0 days).',
'Backtesting with data from 2017-11-14 21:17:00 '
'up to 2017-11-14 22:58:00 (0 days)..',
'up to 2017-11-14 22:58:00 (0 days).',
'Parameter --enable-position-stacking detected ...'
]
@@ -802,8 +820,20 @@ def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir):
@pytest.mark.filterwarnings("ignore:deprecated")
def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
default_conf['ask_strategy'].update({
"use_sell_signal": True,
"sell_profit_only": False,
"sell_profit_offset": 0.0,
"ignore_roi_if_buy_signal": False,
})
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': [],
'rejected_signals': 20,
'final_balance': 1000,
})
mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist',
PropertyMock(return_value=['UNITTEST/BTC']))
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock)
@@ -817,7 +847,7 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
text_table_strategy=strattable_mock,
generate_pair_metrics=MagicMock(),
generate_sell_reason_stats=sell_reason_mock,
generate_strategy_metrics=strat_summary,
generate_strategy_comparison=strat_summary,
generate_daily_stats=MagicMock(),
)
patched_configuration_load_config_file(mocker, default_conf)
@@ -851,9 +881,9 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
'Parameter --timerange detected: 1510694220-1510700340 ...',
f'Using data directory: {testdatadir} ...',
'Loading data from 2017-11-14 20:57:00 '
'up to 2017-11-14 22:58:00 (0 days)..',
'up to 2017-11-14 22:58:00 (0 days).',
'Backtesting with data from 2017-11-14 21:17:00 '
'up to 2017-11-14 22:58:00 (0 days)..',
'up to 2017-11-14 22:58:00 (0 days).',
'Parameter --enable-position-stacking detected ...',
'Running backtesting for Strategy DefaultStrategy',
'Running backtesting for Strategy TestStrategyLegacy',
@@ -865,41 +895,60 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
@pytest.mark.filterwarnings("ignore:deprecated")
def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdatadir, capsys):
default_conf['ask_strategy'].update({
"use_sell_signal": True,
"sell_profit_only": False,
"sell_profit_offset": 0.0,
"ignore_roi_if_buy_signal": False,
})
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': [],
'rejected_signals': 20,
'final_balance': 1000,
},
{
'results': result2,
'config': default_conf,
'locks': [],
'rejected_signals': 20,
'final_balance': 1000,
}
])
mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist',
PropertyMock(return_value=['UNITTEST/BTC']))
@@ -930,9 +979,9 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
'Parameter --timerange detected: 1510694220-1510700340 ...',
f'Using data directory: {testdatadir} ...',
'Loading data from 2017-11-14 20:57:00 '
'up to 2017-11-14 22:58:00 (0 days)..',
'up to 2017-11-14 22:58:00 (0 days).',
'Backtesting with data from 2017-11-14 21:17:00 '
'up to 2017-11-14 22:58:00 (0 days)..',
'up to 2017-11-14 22:58:00 (0 days).',
'Parameter --enable-position-stacking detected ...',
'Running backtesting for Strategy DefaultStrategy',
'Running backtesting for Strategy TestStrategyLegacy',

318
tests/optimize/test_hyperopt.py
View File

@@ -4,7 +4,7 @@ import re
from datetime import datetime
from pathlib import Path
from typing import Dict, List
from unittest.mock import MagicMock
from unittest.mock import ANY, MagicMock
import pandas as pd
import pytest
@@ -17,10 +17,12 @@ from freqtrade.exceptions import OperationalException
from freqtrade.optimize.hyperopt import Hyperopt
from freqtrade.optimize.hyperopt_auto import HyperOptAuto
from freqtrade.optimize.hyperopt_tools import HyperoptTools
from freqtrade.optimize.optimize_reports import generate_strategy_stats
from freqtrade.optimize.space import SKDecimal
from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver
from freqtrade.state import RunMode
from freqtrade.strategy.hyper import IntParameter
from freqtrade.strategy.interface import SellType
from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
patched_configuration_load_config_file)
@@ -28,23 +30,7 @@ from .hyperopts.default_hyperopt import DefaultHyperOpt
# Functions for recurrent object patching
def create_results(mocker, hyperopt, testdatadir) -> List[Dict]:
"""
When creating results, mock the hyperopt so that *by default*
- we don't create any pickle'd files in the filesystem
- we might have a pickle'd file so make sure that we return
false when looking for it
"""
hyperopt.results_file = testdatadir / 'optimize/ut_results.pickle'
mocker.patch.object(Path, "is_file", MagicMock(return_value=False))
stat_mock = MagicMock()
stat_mock.st_size = 1
mocker.patch.object(Path, "stat", MagicMock(return_value=stat_mock))
mocker.patch.object(Path, "unlink", MagicMock(return_value=True))
mocker.patch('freqtrade.optimize.hyperopt.dump', return_value=None)
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
def create_results() -> List[Dict]:
return [{'loss': 1, 'result': 'foo', 'params': {}, 'is_best': True}]
@@ -318,54 +304,49 @@ def test_no_log_if_loss_does_not_improve(hyperopt, caplog) -> None:
assert caplog.record_tuples == []
def test_save_results_saves_epochs(mocker, hyperopt, testdatadir, caplog) -> None:
epochs = create_results(mocker, hyperopt, testdatadir)
mock_dump = mocker.patch('freqtrade.optimize.hyperopt.dump', return_value=None)
mock_dump_json = mocker.patch('freqtrade.optimize.hyperopt.file_dump_json', return_value=None)
results_file = testdatadir / 'optimize' / 'ut_results.pickle'
def test_save_results_saves_epochs(mocker, hyperopt, tmpdir, caplog) -> None:
# Test writing to temp dir and reading again
epochs = create_results()
hyperopt.results_file = Path(tmpdir / 'ut_results.fthypt')
caplog.set_level(logging.DEBUG)
hyperopt.epochs = epochs
hyperopt._save_results()
assert log_has(f"1 epoch saved to '{results_file}'.", caplog)
mock_dump.assert_called_once()
mock_dump_json.assert_called_once()
for epoch in epochs:
hyperopt._save_result(epoch)
assert log_has(f"1 epoch saved to '{hyperopt.results_file}'.", caplog)
hyperopt.epochs = epochs + epochs
hyperopt._save_results()
assert log_has(f"2 epochs saved to '{results_file}'.", caplog)
hyperopt._save_result(epochs[0])
assert log_has(f"2 epochs saved to '{hyperopt.results_file}'.", caplog)
hyperopt_epochs = HyperoptTools.load_previous_results(hyperopt.results_file)
assert len(hyperopt_epochs) == 2
def test_read_results_returns_epochs(mocker, hyperopt, testdatadir, caplog) -> None:
epochs = create_results(mocker, hyperopt, testdatadir)
mock_load = mocker.patch('freqtrade.optimize.hyperopt_tools.load', return_value=epochs)
results_file = testdatadir / 'optimize' / 'ut_results.pickle'
hyperopt_epochs = HyperoptTools._read_results(results_file)
assert log_has(f"Reading epochs from '{results_file}'", caplog)
assert hyperopt_epochs == epochs
mock_load.assert_called_once()
def test_load_previous_results(testdatadir, caplog) -> None:
def test_load_previous_results(mocker, hyperopt, testdatadir, caplog) -> None:
epochs = create_results(mocker, hyperopt, testdatadir)
mock_load = mocker.patch('freqtrade.optimize.hyperopt_tools.load', return_value=epochs)
mocker.patch.object(Path, 'is_file', MagicMock(return_value=True))
statmock = MagicMock()
statmock.st_size = 5
# mocker.patch.object(Path, 'stat', MagicMock(return_value=statmock))
results_file = testdatadir / 'optimize' / 'ut_results.pickle'
results_file = testdatadir / 'hyperopt_results_SampleStrategy.pickle'
hyperopt_epochs = HyperoptTools.load_previous_results(results_file)
assert hyperopt_epochs == epochs
mock_load.assert_called_once()
assert len(hyperopt_epochs) == 5
assert log_has_re(r"Reading pickled epochs from .*", caplog)
del epochs[0]['is_best']
mock_load = mocker.patch('freqtrade.optimize.hyperopt_tools.load', return_value=epochs)
caplog.clear()
with pytest.raises(OperationalException):
# Modern version
results_file = testdatadir / 'strategy_SampleStrategy.fthypt'
hyperopt_epochs = HyperoptTools.load_previous_results(results_file)
assert len(hyperopt_epochs) == 5
assert log_has_re(r"Reading epochs from .*", caplog)
def test_load_previous_results2(mocker, testdatadir, caplog) -> None:
mocker.patch('freqtrade.optimize.hyperopt_tools.HyperoptTools._read_results_pickle',
return_value=[{'asdf': '222'}])
results_file = testdatadir / 'hyperopt_results_SampleStrategy.pickle'
with pytest.raises(OperationalException, match=r"The file .* incompatible.*"):
HyperoptTools.load_previous_results(results_file)
@@ -383,7 +364,8 @@ def test_roi_table_generation(hyperopt) -> None:
def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
@@ -422,9 +404,9 @@ def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
out, err = capsys.readouterr()
assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
assert dumper.called
# Should be called twice, once for historical candle data, once to save evaluations
assert dumper.call_count == 2
# Should be called for historical candle data
assert dumper.call_count == 1
assert dumper2.call_count == 1
assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
assert hasattr(hyperopt, "max_open_trades")
@@ -432,18 +414,42 @@ def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
assert hasattr(hyperopt, "position_stacking")
def test_format_results(hyperopt):
# Test with BTC as stake_currency
trades = [
('ETH/BTC', 2, 2, 123),
('LTC/BTC', 1, 1, 123),
('XPR/BTC', -1, -2, -246)
]
labels = ['currency', 'profit_ratio', 'profit_abs', 'trade_duration']
df = pd.DataFrame.from_records(trades, columns=labels)
results_metrics = hyperopt._calculate_results_metrics(df)
results_explanation = hyperopt._format_results_explanation_string(results_metrics)
total_profit = results_metrics['total_profit']
def test_hyperopt_format_results(hyperopt):
bt_result = {
'results': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC", "UNITTEST/BTC"],
"profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
"open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime],
"close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"trade_duration": [123, 34, 31, 14],
"is_open": [False, False, False, True],
"stake_amount": [0.01, 0.01, 0.01, 0.01],
"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
SellType.ROI, SellType.FORCE_SELL]
}),
'config': hyperopt.config,
'locks': [],
'final_balance': 0.02,
'rejected_signals': 2,
'backtest_start_time': 1619718665,
'backtest_end_time': 1619718665,
}
results_metrics = generate_strategy_stats({'XRP/BTC': None}, '', bt_result,
Arrow(2017, 11, 14, 19, 32, 00),
Arrow(2017, 12, 14, 19, 32, 00), market_change=0)
results_explanation = HyperoptTools.format_results_explanation_string(results_metrics, 'BTC')
total_profit = results_metrics['profit_total_abs']
results = {
'loss': 0.0,
@@ -457,21 +463,9 @@ def test_format_results(hyperopt):
}
result = HyperoptTools._format_explanation_string(results, 1)
assert result.find(' 66.67%')
assert result.find('Total profit 1.00000000 BTC')
assert result.find('2.0000Σ %')
# Test with EUR as stake_currency
trades = [
('ETH/EUR', 2, 2, 123),
('LTC/EUR', 1, 1, 123),
('XPR/EUR', -1, -2, -246)
]
df = pd.DataFrame.from_records(trades, columns=labels)
results_metrics = hyperopt._calculate_results_metrics(df)
results['total_profit'] = results_metrics['total_profit']
result = HyperoptTools._format_explanation_string(results, 1)
assert result.find('Total profit 1.00000000 EUR')
assert ' 0.71%' in result
assert 'Total profit 0.00003100 BTC' in result
assert '0:50:00 min' in result
@pytest.mark.parametrize("spaces, expected_results", [
@@ -502,10 +496,10 @@ def test_format_results(hyperopt):
(['default', 'buy'],
{'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
])
def test_has_space(hyperopt, spaces, expected_results):
def test_has_space(hyperopt_conf, spaces, expected_results):
for s in ['buy', 'sell', 'roi', 'stoploss', 'trailing']:
hyperopt.config.update({'spaces': spaces})
assert hyperopt.has_space(s) == expected_results[s]
hyperopt_conf.update({'spaces': spaces})
assert HyperoptTools.has_space(hyperopt_conf, s) == expected_results[s]
def test_populate_indicators(hyperopt, testdatadir) -> None:
@@ -576,22 +570,39 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
'hyperopt_min_trades': 1,
})
trades = [
('TRX/BTC', 0.023117, 0.000233, 100)
]
labels = ['currency', 'profit_ratio', 'profit_abs', 'trade_duration']
backtest_result = pd.DataFrame.from_records(trades, columns=labels)
backtest_result = {
'results': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC", "UNITTEST/BTC"],
"profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
"open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime],
"close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"trade_duration": [123, 34, 31, 14],
"is_open": [False, False, False, True],
"stake_amount": [0.01, 0.01, 0.01, 0.01],
"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
SellType.ROI, SellType.FORCE_SELL]
}),
'config': hyperopt_conf,
'locks': [],
'rejected_signals': 20,
'final_balance': 1000,
}
mocker.patch(
'freqtrade.optimize.hyperopt.Backtesting.backtest',
MagicMock(return_value=backtest_result)
)
mocker.patch(
'freqtrade.optimize.hyperopt.get_timerange',
MagicMock(return_value=(Arrow(2017, 12, 10), Arrow(2017, 12, 13)))
)
mocker.patch('freqtrade.optimize.hyperopt.Backtesting.backtest', return_value=backtest_result)
mocker.patch('freqtrade.optimize.hyperopt.get_timerange',
return_value=(Arrow(2017, 12, 10), Arrow(2017, 12, 13)))
patch_exchange(mocker)
mocker.patch('freqtrade.optimize.hyperopt.load', MagicMock())
mocker.patch.object(Path, 'open')
mocker.patch('freqtrade.optimize.hyperopt.load', return_value={'XRP/BTC': None})
optimizer_param = {
'adx-value': 0,
@@ -625,11 +636,11 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
'trailing_only_offset_is_reached': False,
}
response_expected = {
'loss': 1.9840569076926293,
'results_explanation': (' 1 trades. 1/0/0 Wins/Draws/Losses. '
'Avg profit 2.31%. Median profit 2.31%. Total profit '
'0.00023300 BTC ( 2.31%). '
'Avg duration 100.0 min.'
'loss': 1.9147239021396234,
'results_explanation': (' 4 trades. 4/0/0 Wins/Draws/Losses. '
'Avg profit 0.77%. Median profit 0.71%. Total profit '
'0.00003100 BTC ( 0.00%). '
'Avg duration 0:50:00 min.'
),
'params_details': {'buy': {'adx-enabled': False,
'adx-value': 0,
@@ -640,10 +651,10 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
'rsi-enabled': False,
'rsi-value': 0,
'trigger': 'macd_cross_signal'},
'roi': {0: 0.12000000000000001,
20.0: 0.02,
50.0: 0.01,
110.0: 0},
'roi': {"0": 0.12000000000000001,
"20.0": 0.02,
"50.0": 0.01,
"110.0": 0},
'sell': {'sell-adx-enabled': False,
'sell-adx-value': 0,
'sell-fastd-enabled': True,
@@ -659,21 +670,16 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
'trailing_stop_positive': 0.02,
'trailing_stop_positive_offset': 0.07}},
'params_dict': optimizer_param,
'results_metrics': {'avg_profit': 2.3117,
'draws': 0,
'duration': 100.0,
'losses': 0,
'winsdrawslosses': ' 1 0 0',
'median_profit': 2.3117,
'profit': 2.3117,
'total_profit': 0.000233,
'trade_count': 1,
'wins': 1},
'total_profit': 0.00023300
'params_not_optimized': {'buy': {}, 'sell': {}},
'results_metrics': ANY,
'total_profit': 3.1e-08
}
hyperopt = Hyperopt(hyperopt_conf)
hyperopt.dimensions = hyperopt.hyperopt_space()
hyperopt.min_date = Arrow(2017, 12, 10)
hyperopt.max_date = Arrow(2017, 12, 13)
hyperopt.init_spaces()
hyperopt.dimensions = hyperopt.dimensions
generate_optimizer_value = hyperopt.generate_optimizer(list(optimizer_param.values()))
assert generate_optimizer_value == response_expected
@@ -690,7 +696,8 @@ def test_clean_hyperopt(mocker, hyperopt_conf, caplog):
def test_print_json_spaces_all(mocker, hyperopt_conf, capsys) -> None:
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
@@ -741,13 +748,14 @@ def test_print_json_spaces_all(mocker, hyperopt_conf, capsys) -> None:
':{},"stoploss":null,"trailing_stop":null}'
)
assert result_str in out # noqa: E501
assert dumper.called
# Should be called twice, once for historical candle data, once to save evaluations
assert dumper.call_count == 2
# Should be called for historical candle data
assert dumper.call_count == 1
assert dumper2.call_count == 1
def test_print_json_spaces_default(mocker, hyperopt_conf, capsys) -> None:
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
MagicMock(return_value=(MagicMock(), None)))
@@ -789,13 +797,14 @@ def test_print_json_spaces_default(mocker, hyperopt_conf, capsys) -> None:
out, err = capsys.readouterr()
assert '{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi":{},"stoploss":null}' in out # noqa: E501
assert dumper.called
# Should be called twice, once for historical candle data, once to save evaluations
assert dumper.call_count == 2
# Should be called for historical candle data
assert dumper.call_count == 1
assert dumper2.call_count == 1
def test_print_json_spaces_roi_stoploss(mocker, hyperopt_conf, capsys) -> None:
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
MagicMock(return_value=(MagicMock(), None)))
@@ -836,13 +845,14 @@ def test_print_json_spaces_roi_stoploss(mocker, hyperopt_conf, capsys) -> None:
out, err = capsys.readouterr()
assert '{"minimal_roi":{},"stoploss":null}' in out
assert dumper.called
# Should be called twice, once for historical candle data, once to save evaluations
assert dumper.call_count == 2
assert dumper.call_count == 1
assert dumper2.call_count == 1
def test_simplified_interface_roi_stoploss(mocker, hyperopt_conf, capsys) -> None:
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
MagicMock(return_value=(MagicMock(), None)))
@@ -884,9 +894,9 @@ def test_simplified_interface_roi_stoploss(mocker, hyperopt_conf, capsys) -> Non
out, err = capsys.readouterr()
assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
assert dumper.called
# Should be called twice, once for historical candle data, once to save evaluations
assert dumper.call_count == 2
assert dumper.call_count == 1
assert dumper2.call_count == 1
assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
assert hasattr(hyperopt, "max_open_trades")
@@ -922,7 +932,8 @@ def test_simplified_interface_all_failed(mocker, hyperopt_conf) -> None:
def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
MagicMock(return_value=(MagicMock(), None)))
@@ -965,8 +976,8 @@ def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
out, err = capsys.readouterr()
assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
assert dumper.called
# Should be called twice, once for historical candle data, once to save evaluations
assert dumper.call_count == 2
assert dumper.call_count == 1
assert dumper2.call_count == 1
assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
assert hasattr(hyperopt, "max_open_trades")
@@ -975,7 +986,8 @@ def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None:
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
MagicMock(return_value=(MagicMock(), None)))
@@ -1018,8 +1030,8 @@ def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None:
out, err = capsys.readouterr()
assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
assert dumper.called
# Should be called twice, once for historical candle data, once to save evaluations
assert dumper.call_count == 2
assert dumper.call_count == 1
assert dumper2.call_count == 1
assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
assert hasattr(hyperopt, "max_open_trades")
@@ -1107,7 +1119,7 @@ def test_in_strategy_auto_hyperopt(mocker, hyperopt_conf, tmpdir, fee) -> None:
assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto)
assert isinstance(hyperopt.backtesting.strategy.buy_rsi, IntParameter)
assert hyperopt.backtesting.strategy.buy_rsi.hyperopt is True
assert hyperopt.backtesting.strategy.buy_rsi.in_space is True
assert hyperopt.backtesting.strategy.buy_rsi.value == 35
buy_rsi_range = hyperopt.backtesting.strategy.buy_rsi.range
assert isinstance(buy_rsi_range, range)
@@ -1132,3 +1144,17 @@ def test_SKDecimal():
assert space.transform([2.0]) == [200]
assert space.transform([1.0]) == [100]
assert space.transform([1.5, 1.6]) == [150, 160]
def test___pprint():
params = {'buy_std': 1.2, 'buy_rsi': 31, 'buy_enable': True, 'buy_what': 'asdf'}
non_params = {'buy_notoptimied': 55}
x = HyperoptTools._pprint(params, non_params)
assert x == """{
"buy_std": 1.2,
"buy_rsi": 31,
"buy_enable": True,
"buy_what": "asdf",
"buy_notoptimied": 55, # value loaded from strategy
}"""

97
tests/optimize/test_optimize_reports.py
View File

@@ -1,5 +1,6 @@
import datetime
import re
from datetime import datetime, timedelta, timezone
from datetime import timedelta
from pathlib import Path
import pandas as pd
@@ -7,14 +8,15 @@ import pytest
from arrow import Arrow
from freqtrade.configuration import TimeRange
from freqtrade.constants import LAST_BT_RESULT_FN
from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN
from freqtrade.data import history
from freqtrade.data.btanalysis import get_latest_backtest_filename, load_backtest_data
from freqtrade.edge import PairInfo
from freqtrade.optimize.optimize_reports import (generate_backtest_stats, generate_daily_stats,
generate_edge_table, generate_pair_metrics,
generate_sell_reason_stats,
generate_strategy_metrics, store_backtest_stats,
generate_strategy_comparison,
generate_trading_stats, store_backtest_stats,
text_table_bt_results, text_table_sell_reason,
text_table_strategy)
from freqtrade.resolvers.strategy_resolver import StrategyResolver
@@ -26,25 +28,22 @@ def test_text_table_bt_results():
results = pd.DataFrame(
{
'pair': ['ETH/BTC', 'ETH/BTC'],
'profit_ratio': [0.1, 0.2],
'profit_abs': [0.2, 0.4],
'trade_duration': [10, 30],
'wins': [2, 0],
'draws': [0, 0],
'losses': [0, 0]
'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
'profit_ratio': [0.1, 0.2, -0.05],
'profit_abs': [0.2, 0.4, -0.1],
'trade_duration': [10, 30, 20],
}
)
result_str = (
'| Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC |'
' Tot Profit % | Avg Duration | Wins | Draws | Losses |\n'
'|---------+--------+----------------+----------------+------------------+'
'----------------+----------------+--------+---------+----------|\n'
'| ETH/BTC | 2 | 15.00 | 30.00 | 0.60000000 |'
' 15.00 | 0:20:00 | 2 | 0 | 0 |\n'
'| TOTAL | 2 | 15.00 | 30.00 | 0.60000000 |'
' 15.00 | 0:20:00 | 2 | 0 | 0 |'
'| Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % |'
' Avg Duration | Win Draw Loss Win% |\n'
'|---------+--------+----------------+----------------+------------------+----------------+'
'----------------+-------------------------|\n'
'| ETH/BTC | 3 | 8.33 | 25.00 | 0.50000000 | 12.50 |'
' 0:20:00 | 2 0 1 66.7 |\n'
'| TOTAL | 3 | 8.33 | 25.00 | 0.50000000 | 12.50 |'
' 0:20:00 | 2 0 1 66.7 |'
)
pair_results = generate_pair_metrics(data={'ETH/BTC': {}}, stake_currency='BTC',
@@ -80,6 +79,7 @@ def test_generate_backtest_stats(default_conf, testdatadir):
'config': default_conf,
'locks': [],
'final_balance': 1000.02,
'rejected_signals': 20,
'backtest_start_time': Arrow.utcnow().int_timestamp,
'backtest_end_time': Arrow.utcnow().int_timestamp,
}
@@ -96,8 +96,8 @@ def test_generate_backtest_stats(default_conf, testdatadir):
assert 'DefStrat' in stats['strategy']
assert 'strategy_comparison' in stats
strat_stats = stats['strategy']['DefStrat']
assert strat_stats['backtest_start'] == min_date.datetime
assert strat_stats['backtest_end'] == max_date.datetime
assert strat_stats['backtest_start'] == min_date.strftime(DATETIME_PRINT_FORMAT)
assert strat_stats['backtest_end'] == max_date.strftime(DATETIME_PRINT_FORMAT)
assert strat_stats['total_trades'] == len(results['DefStrat']['results'])
# Above sample had no loosing trade
assert strat_stats['max_drawdown'] == 0.0
@@ -127,6 +127,7 @@ def test_generate_backtest_stats(default_conf, testdatadir):
'config': default_conf,
'locks': [],
'final_balance': 1000.02,
'rejected_signals': 20,
'backtest_start_time': Arrow.utcnow().int_timestamp,
'backtest_end_time': Arrow.utcnow().int_timestamp,
}
@@ -140,8 +141,8 @@ def test_generate_backtest_stats(default_conf, testdatadir):
strat_stats = stats['strategy']['DefStrat']
assert strat_stats['max_drawdown'] == 0.013803
assert strat_stats['drawdown_start'] == datetime(2017, 11, 14, 22, 10, tzinfo=timezone.utc)
assert strat_stats['drawdown_end'] == datetime(2017, 11, 14, 22, 43, tzinfo=timezone.utc)
assert strat_stats['drawdown_start'] == '2017-11-14 22:10:00'
assert strat_stats['drawdown_end'] == '2017-11-14 22:43:00'
assert strat_stats['drawdown_end_ts'] == 1510699380000
assert strat_stats['drawdown_start_ts'] == 1510697400000
assert strat_stats['pairlist'] == ['UNITTEST/BTC']
@@ -226,8 +227,6 @@ def test_generate_daily_stats(testdatadir):
assert res['winning_days'] == 14
assert res['draw_days'] == 4
assert res['losing_days'] == 3
assert res['winner_holding_avg'] == timedelta(seconds=1440)
assert res['loser_holding_avg'] == timedelta(days=1, seconds=21420)
# Select empty dataframe!
res = generate_daily_stats(bt_data.loc[bt_data['open_date'] == '2000-01-01', :])
@@ -238,6 +237,23 @@ def test_generate_daily_stats(testdatadir):
assert res['losing_days'] == 0
def test_generate_trading_stats(testdatadir):
filename = testdatadir / "backtest-result_new.json"
bt_data = load_backtest_data(filename)
res = generate_trading_stats(bt_data)
assert isinstance(res, dict)
assert res['winner_holding_avg'] == timedelta(seconds=1440)
assert res['loser_holding_avg'] == timedelta(days=1, seconds=21420)
assert 'wins' in res
assert 'losses' in res
assert 'draws' in res
# Select empty dataframe!
res = generate_trading_stats(bt_data.loc[bt_data['open_date'] == '2000-01-01', :])
assert res['wins'] == 0
assert res['losses'] == 0
def test_text_table_sell_reason():
results = pd.DataFrame(
@@ -254,14 +270,14 @@ def test_text_table_sell_reason():
)
result_str = (
'| Sell Reason | Sells | Wins | Draws | Losses |'
' Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % |\n'
'|---------------+---------+--------+---------+----------+'
'----------------+----------------+------------------+----------------|\n'
'| roi | 2 | 2 | 0 | 0 |'
' 15 | 30 | 0.6 | 15 |\n'
'| stop_loss | 1 | 0 | 0 | 1 |'
' -10 | -10 | -0.2 | -5 |'
'| Sell Reason | Sells | Win Draws Loss Win% | Avg Profit % | Cum Profit % |'
' Tot Profit BTC | Tot Profit % |\n'
'|---------------+---------+--------------------------+----------------+----------------+'
'------------------+----------------|\n'
'| roi | 2 | 2 0 0 100 | 15 | 30 |'
' 0.6 | 15 |\n'
'| stop_loss | 1 | 0 0 1 0 | -10 | -10 |'
' -0.2 | -5 |'
)
sell_reason_stats = generate_sell_reason_stats(max_open_trades=2,
@@ -309,9 +325,12 @@ def test_text_table_strategy(default_conf):
default_conf['max_open_trades'] = 2
default_conf['dry_run_wallet'] = 3
results = {}
date = datetime.datetime(year=2020, month=1, day=1, hour=12, minute=30)
delta = datetime.timedelta(days=1)
results['TestStrategy1'] = {'results': pd.DataFrame(
{
'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
'close_date': [date, date + delta, date + delta * 2],
'profit_ratio': [0.1, 0.2, 0.3],
'profit_abs': [0.2, 0.4, 0.5],
'trade_duration': [10, 30, 10],
@@ -324,6 +343,7 @@ def test_text_table_strategy(default_conf):
results['TestStrategy2'] = {'results': pd.DataFrame(
{
'pair': ['LTC/BTC', 'LTC/BTC', 'LTC/BTC'],
'close_date': [date, date + delta, date + delta * 2],
'profit_ratio': [0.4, 0.2, 0.3],
'profit_abs': [0.4, 0.4, 0.5],
'trade_duration': [15, 30, 15],
@@ -335,18 +355,17 @@ def test_text_table_strategy(default_conf):
), 'config': default_conf}
result_str = (
'| Strategy | Buys | Avg Profit % | Cum Profit % | Tot'
' Profit BTC | Tot Profit % | Avg Duration | Wins | Draws | Losses |\n'
'| Strategy | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC |'
' Tot Profit % | Avg Duration | Win Draw Loss Win% | Drawdown |\n'
'|---------------+--------+----------------+----------------+------------------+'
'----------------+----------------+--------+---------+----------|\n'
'----------------+----------------+-------------------------+-----------------------|\n'
'| TestStrategy1 | 3 | 20.00 | 60.00 | 1.10000000 |'
' 36.67 | 0:17:00 | 3 | 0 | 0 |\n'
' 36.67 | 0:17:00 | 3 0 0 100 | 0.00000000 BTC 0.00% |\n'
'| TestStrategy2 | 3 | 30.00 | 90.00 | 1.30000000 |'
' 43.33 | 0:20:00 | 3 | 0 | 0 |'
' 43.33 | 0:20:00 | 3 0 0 100 | 0.00000000 BTC 0.00% |'
)
strategy_results = generate_strategy_metrics(all_results=results)
strategy_results = generate_strategy_comparison(all_results=results)
assert text_table_strategy(strategy_results, 'BTC') == result_str