1114 lines
43 KiB
Python
1114 lines
43 KiB
Python
# pragma pylint: disable=missing-docstring,W0212,C0103
|
|
from datetime import datetime, timedelta
|
|
from functools import wraps
|
|
from pathlib import Path
|
|
from unittest.mock import ANY, MagicMock, PropertyMock
|
|
|
|
import pandas as pd
|
|
import pytest
|
|
from arrow import Arrow
|
|
from filelock import Timeout
|
|
from skopt.space import Integer
|
|
|
|
from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_hyperopt
|
|
from freqtrade.data.history import load_data
|
|
from freqtrade.enums import ExitType, RunMode
|
|
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.strategy import IntParameter
|
|
from tests.conftest import (CURRENT_TEST_STRATEGY, EXMS, get_args, get_markets, log_has, log_has_re,
|
|
patch_exchange, patched_configuration_load_config_file)
|
|
|
|
|
|
def generate_result_metrics():
|
|
return {
|
|
'trade_count': 1,
|
|
'total_trades': 1,
|
|
'avg_profit': 0.1,
|
|
'total_profit': 0.001,
|
|
'profit': 0.01,
|
|
'duration': 20.0,
|
|
'wins': 1,
|
|
'draws': 0,
|
|
'losses': 0,
|
|
'profit_mean': 0.01,
|
|
'profit_total_abs': 0.001,
|
|
'profit_total': 0.01,
|
|
'holding_avg': timedelta(minutes=20),
|
|
'max_drawdown': 0.001,
|
|
'max_drawdown_abs': 0.001,
|
|
'loss': 0.001,
|
|
'is_initial_point': 0.001,
|
|
'is_random': False,
|
|
'is_best': 1,
|
|
}
|
|
|
|
|
|
def test_setup_hyperopt_configuration_without_arguments(mocker, default_conf, caplog) -> None:
|
|
patched_configuration_load_config_file(mocker, default_conf)
|
|
|
|
args = [
|
|
'hyperopt',
|
|
'--config', 'config.json',
|
|
'--strategy', 'HyperoptableStrategy',
|
|
]
|
|
|
|
config = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
|
|
assert 'max_open_trades' in config
|
|
assert 'stake_currency' in config
|
|
assert 'stake_amount' in config
|
|
assert 'exchange' in config
|
|
assert 'pair_whitelist' in config['exchange']
|
|
assert 'datadir' in config
|
|
assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
|
|
assert 'timeframe' in config
|
|
|
|
assert 'position_stacking' not in config
|
|
assert not log_has('Parameter --enable-position-stacking detected ...', caplog)
|
|
|
|
assert 'timerange' not in config
|
|
assert 'runmode' in config
|
|
assert config['runmode'] == RunMode.HYPEROPT
|
|
|
|
|
|
def test_setup_hyperopt_configuration_with_arguments(mocker, default_conf, caplog) -> None:
|
|
patched_configuration_load_config_file(mocker, default_conf)
|
|
mocker.patch(
|
|
'freqtrade.configuration.configuration.create_datadir',
|
|
lambda c, x: x
|
|
)
|
|
|
|
args = [
|
|
'hyperopt',
|
|
'--config', 'config.json',
|
|
'--strategy', 'HyperoptableStrategy',
|
|
'--datadir', '/foo/bar',
|
|
'--timeframe', '1m',
|
|
'--timerange', ':100',
|
|
'--enable-position-stacking',
|
|
'--disable-max-market-positions',
|
|
'--epochs', '1000',
|
|
'--spaces', 'default',
|
|
'--print-all'
|
|
]
|
|
|
|
config = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
|
|
assert 'max_open_trades' in config
|
|
assert 'stake_currency' in config
|
|
assert 'stake_amount' in config
|
|
assert 'exchange' in config
|
|
assert 'pair_whitelist' in config['exchange']
|
|
assert 'datadir' in config
|
|
assert config['runmode'] == RunMode.HYPEROPT
|
|
|
|
assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
|
|
assert 'timeframe' in config
|
|
assert log_has('Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
|
|
caplog)
|
|
|
|
assert 'position_stacking' in config
|
|
assert log_has('Parameter --enable-position-stacking detected ...', caplog)
|
|
|
|
assert 'use_max_market_positions' in config
|
|
assert log_has('Parameter --disable-max-market-positions detected ...', caplog)
|
|
assert log_has('max_open_trades set to unlimited ...', caplog)
|
|
|
|
assert 'timerange' in config
|
|
assert log_has('Parameter --timerange detected: {} ...'.format(config['timerange']), caplog)
|
|
|
|
assert 'epochs' in config
|
|
assert log_has('Parameter --epochs detected ... Will run Hyperopt with for 1000 epochs ...',
|
|
caplog)
|
|
|
|
assert 'spaces' in config
|
|
assert log_has('Parameter -s/--spaces detected: {}'.format(config['spaces']), caplog)
|
|
assert 'print_all' in config
|
|
assert log_has('Parameter --print-all detected ...', caplog)
|
|
|
|
|
|
def test_setup_hyperopt_configuration_stake_amount(mocker, default_conf) -> None:
|
|
|
|
patched_configuration_load_config_file(mocker, default_conf)
|
|
|
|
args = [
|
|
'hyperopt',
|
|
'--config', 'config.json',
|
|
'--strategy', 'HyperoptableStrategy',
|
|
'--stake-amount', '1',
|
|
'--starting-balance', '2'
|
|
]
|
|
conf = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
|
|
assert isinstance(conf, dict)
|
|
|
|
args = [
|
|
'hyperopt',
|
|
'--config', 'config.json',
|
|
'--strategy', CURRENT_TEST_STRATEGY,
|
|
'--stake-amount', '1',
|
|
'--starting-balance', '0.5'
|
|
]
|
|
with pytest.raises(OperationalException, match=r"Starting balance .* smaller .*"):
|
|
setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
|
|
|
|
|
|
def test_start_not_installed(mocker, default_conf, import_fails) -> None:
|
|
start_mock = MagicMock()
|
|
patched_configuration_load_config_file(mocker, default_conf)
|
|
|
|
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
|
|
patch_exchange(mocker)
|
|
|
|
args = [
|
|
'hyperopt',
|
|
'--config', 'config.json',
|
|
'--strategy', 'HyperoptableStrategy',
|
|
'--epochs', '5',
|
|
'--hyperopt-loss', 'SharpeHyperOptLossDaily',
|
|
]
|
|
pargs = get_args(args)
|
|
|
|
with pytest.raises(OperationalException, match=r"Please ensure that the hyperopt dependencies"):
|
|
start_hyperopt(pargs)
|
|
|
|
|
|
def test_start_no_hyperopt_allowed(mocker, hyperopt_conf, caplog) -> None:
|
|
start_mock = MagicMock()
|
|
patched_configuration_load_config_file(mocker, hyperopt_conf)
|
|
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
|
|
patch_exchange(mocker)
|
|
|
|
args = [
|
|
'hyperopt',
|
|
'--config', 'config.json',
|
|
'--hyperopt', 'HyperoptTestSepFile',
|
|
'--hyperopt-loss', 'SharpeHyperOptLossDaily',
|
|
'--epochs', '5'
|
|
]
|
|
pargs = get_args(args)
|
|
with pytest.raises(OperationalException, match=r"Using separate Hyperopt files has been.*"):
|
|
start_hyperopt(pargs)
|
|
|
|
|
|
def test_start_no_data(mocker, hyperopt_conf, tmpdir) -> None:
|
|
hyperopt_conf['user_data_dir'] = Path(tmpdir)
|
|
patched_configuration_load_config_file(mocker, hyperopt_conf)
|
|
mocker.patch('freqtrade.data.history.load_pair_history', MagicMock(return_value=pd.DataFrame))
|
|
mocker.patch(
|
|
'freqtrade.optimize.hyperopt.get_timerange',
|
|
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
|
|
)
|
|
|
|
patch_exchange(mocker)
|
|
args = [
|
|
'hyperopt',
|
|
'--config', 'config.json',
|
|
'--strategy', 'HyperoptableStrategy',
|
|
'--hyperopt-loss', 'SharpeHyperOptLossDaily',
|
|
'--epochs', '5'
|
|
]
|
|
pargs = get_args(args)
|
|
with pytest.raises(OperationalException, match='No data found. Terminating.'):
|
|
start_hyperopt(pargs)
|
|
|
|
# Cleanup since that failed hyperopt start leaves a lockfile.
|
|
try:
|
|
Path(Hyperopt.get_lock_filename(hyperopt_conf)).unlink()
|
|
except Exception:
|
|
pass
|
|
|
|
|
|
def test_start_filelock(mocker, hyperopt_conf, caplog) -> None:
|
|
hyperopt_mock = MagicMock(side_effect=Timeout(Hyperopt.get_lock_filename(hyperopt_conf)))
|
|
patched_configuration_load_config_file(mocker, hyperopt_conf)
|
|
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.__init__', hyperopt_mock)
|
|
patch_exchange(mocker)
|
|
|
|
args = [
|
|
'hyperopt',
|
|
'--config', 'config.json',
|
|
'--strategy', 'HyperoptableStrategy',
|
|
'--hyperopt-loss', 'SharpeHyperOptLossDaily',
|
|
'--epochs', '5'
|
|
]
|
|
pargs = get_args(args)
|
|
start_hyperopt(pargs)
|
|
assert log_has("Another running instance of freqtrade Hyperopt detected.", caplog)
|
|
|
|
|
|
def test_log_results_if_loss_improves(hyperopt, capsys) -> None:
|
|
hyperopt.current_best_loss = 2
|
|
hyperopt.total_epochs = 2
|
|
|
|
hyperopt.print_results(
|
|
{
|
|
'loss': 1,
|
|
'results_metrics': generate_result_metrics(),
|
|
'total_profit': 0,
|
|
'current_epoch': 2, # This starts from 1 (in a human-friendly manner)
|
|
'is_initial_point': False,
|
|
'is_random': False,
|
|
'is_best': True
|
|
}
|
|
)
|
|
out, err = capsys.readouterr()
|
|
assert all(x in out
|
|
for x in ["Best", "2/2", " 1", "0.10%", "0.00100000 BTC (1.00%)", "00:20:00"])
|
|
|
|
|
|
def test_no_log_if_loss_does_not_improve(hyperopt, caplog) -> None:
|
|
hyperopt.current_best_loss = 2
|
|
hyperopt.print_results(
|
|
{
|
|
'is_best': False,
|
|
'loss': 3,
|
|
'current_epoch': 1,
|
|
}
|
|
)
|
|
assert caplog.record_tuples == []
|
|
|
|
|
|
def test_roi_table_generation(hyperopt) -> None:
|
|
params = {
|
|
'roi_t1': 5,
|
|
'roi_t2': 10,
|
|
'roi_t3': 15,
|
|
'roi_p1': 1,
|
|
'roi_p2': 2,
|
|
'roi_p3': 3,
|
|
}
|
|
|
|
assert hyperopt.custom_hyperopt.generate_roi_table(params) == {0: 6, 15: 3, 25: 1, 30: 0}
|
|
|
|
|
|
def test_params_no_optimize_details(hyperopt) -> None:
|
|
hyperopt.config['spaces'] = ['buy']
|
|
res = hyperopt._get_no_optimize_details()
|
|
assert isinstance(res, dict)
|
|
assert "trailing" in res
|
|
assert res["trailing"]['trailing_stop'] is False
|
|
assert "roi" in res
|
|
assert res['roi']['0'] == 0.04
|
|
assert "stoploss" in res
|
|
assert res['stoploss']['stoploss'] == -0.1
|
|
assert "max_open_trades" in res
|
|
assert res['max_open_trades']['max_open_trades'] == 1
|
|
|
|
|
|
def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
|
|
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
|
|
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
|
|
mocker.patch('freqtrade.optimize.hyperopt.calculate_market_change', return_value=1.5)
|
|
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
|
|
|
|
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
|
|
MagicMock(return_value=(MagicMock(), None)))
|
|
mocker.patch(
|
|
'freqtrade.optimize.hyperopt.get_timerange',
|
|
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
|
|
)
|
|
|
|
parallel = mocker.patch(
|
|
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
|
|
MagicMock(return_value=[{
|
|
'loss': 1, 'results_explanation': 'foo result',
|
|
'params': {'buy': {}, 'sell': {}, 'roi': {}, 'stoploss': 0.0},
|
|
'results_metrics': generate_result_metrics(),
|
|
}])
|
|
)
|
|
patch_exchange(mocker)
|
|
# Co-test loading timeframe from strategy
|
|
del hyperopt_conf['timeframe']
|
|
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
|
|
hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
|
|
|
|
hyperopt.start()
|
|
|
|
parallel.assert_called_once()
|
|
|
|
out, err = capsys.readouterr()
|
|
assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
|
|
# 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_entry")
|
|
assert hyperopt.backtesting.strategy.max_open_trades == hyperopt_conf['max_open_trades']
|
|
assert hasattr(hyperopt.backtesting, "_position_stacking")
|
|
|
|
|
|
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],
|
|
"is_short": [False, False, False, False],
|
|
"stake_amount": [0.01, 0.01, 0.01, 0.01],
|
|
"exit_reason": [ExitType.ROI, ExitType.STOP_LOSS,
|
|
ExitType.ROI, ExitType.FORCE_EXIT]
|
|
}),
|
|
'config': hyperopt.config,
|
|
'locks': [],
|
|
'final_balance': 0.02,
|
|
'rejected_signals': 2,
|
|
'timedout_entry_orders': 0,
|
|
'timedout_exit_orders': 0,
|
|
'canceled_trade_entries': 0,
|
|
'canceled_entry_orders': 0,
|
|
'replaced_entry_orders': 0,
|
|
'backtest_start_time': 1619718665,
|
|
'backtest_end_time': 1619718665,
|
|
}
|
|
results_metrics = generate_strategy_stats(['XRP/BTC'], '', 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,
|
|
'params_dict': None,
|
|
'params_details': None,
|
|
'results_metrics': results_metrics,
|
|
'results_explanation': results_explanation,
|
|
'total_profit': total_profit,
|
|
'current_epoch': 1,
|
|
'is_initial_point': True,
|
|
}
|
|
|
|
result = HyperoptTools._format_explanation_string(results, 1)
|
|
assert ' 0.71%' in result
|
|
assert 'Total profit 0.00003100 BTC' in result
|
|
assert '0:50:00 min' in result
|
|
|
|
|
|
def test_populate_indicators(hyperopt, testdatadir) -> None:
|
|
data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], fill_up_missing=True)
|
|
dataframes = hyperopt.backtesting.strategy.advise_all_indicators(data)
|
|
dataframe = dataframes['UNITTEST/BTC']
|
|
|
|
# Check if some indicators are generated. We will not test all of them
|
|
assert 'adx' in dataframe
|
|
assert 'macd' in dataframe
|
|
assert 'rsi' in dataframe
|
|
|
|
|
|
def test_generate_optimizer(mocker, hyperopt_conf) -> None:
|
|
hyperopt_conf.update({'spaces': 'all',
|
|
'hyperopt_min_trades': 1,
|
|
})
|
|
|
|
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],
|
|
"is_short": [False, False, False, False],
|
|
"stake_amount": [0.01, 0.01, 0.01, 0.01],
|
|
"exit_reason": [ExitType.ROI, ExitType.STOP_LOSS,
|
|
ExitType.ROI, ExitType.FORCE_EXIT]
|
|
}),
|
|
'config': hyperopt_conf,
|
|
'locks': [],
|
|
'rejected_signals': 20,
|
|
'timedout_entry_orders': 0,
|
|
'timedout_exit_orders': 0,
|
|
'canceled_trade_entries': 0,
|
|
'canceled_entry_orders': 0,
|
|
'replaced_entry_orders': 0,
|
|
'final_balance': 1000,
|
|
}
|
|
|
|
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.object(Path, 'open')
|
|
mocker.patch('freqtrade.configuration.config_validation.validate_config_schema')
|
|
mocker.patch('freqtrade.optimize.hyperopt.load', return_value={'XRP/BTC': None})
|
|
|
|
optimizer_param = {
|
|
'buy_plusdi': 0.02,
|
|
'buy_rsi': 35,
|
|
'sell_minusdi': 0.02,
|
|
'sell_rsi': 75,
|
|
'protection_cooldown_lookback': 20,
|
|
'protection_enabled': True,
|
|
'roi_t1': 60.0,
|
|
'roi_t2': 30.0,
|
|
'roi_t3': 20.0,
|
|
'roi_p1': 0.01,
|
|
'roi_p2': 0.01,
|
|
'roi_p3': 0.1,
|
|
'stoploss': -0.4,
|
|
'trailing_stop': True,
|
|
'trailing_stop_positive': 0.02,
|
|
'trailing_stop_positive_offset_p1': 0.05,
|
|
'trailing_only_offset_is_reached': False,
|
|
'max_open_trades': 3,
|
|
}
|
|
response_expected = {
|
|
'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': {'buy_plusdi': 0.02,
|
|
'buy_rsi': 35,
|
|
},
|
|
'roi': {"0": 0.12000000000000001,
|
|
"20.0": 0.02,
|
|
"50.0": 0.01,
|
|
"110.0": 0},
|
|
'protection': {'protection_cooldown_lookback': 20,
|
|
'protection_enabled': True,
|
|
},
|
|
'sell': {'sell_minusdi': 0.02,
|
|
'sell_rsi': 75,
|
|
},
|
|
'stoploss': {'stoploss': -0.4},
|
|
'trailing': {'trailing_only_offset_is_reached': False,
|
|
'trailing_stop': True,
|
|
'trailing_stop_positive': 0.02,
|
|
'trailing_stop_positive_offset': 0.07},
|
|
'max_open_trades': {'max_open_trades': 3}
|
|
},
|
|
'params_dict': optimizer_param,
|
|
'params_not_optimized': {'buy': {}, 'protection': {}, 'sell': {}},
|
|
'results_metrics': ANY,
|
|
'total_profit': 3.1e-08
|
|
}
|
|
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
hyperopt.min_date = Arrow(2017, 12, 10)
|
|
hyperopt.max_date = Arrow(2017, 12, 13)
|
|
hyperopt.init_spaces()
|
|
generate_optimizer_value = hyperopt.generate_optimizer(list(optimizer_param.values()))
|
|
assert generate_optimizer_value == response_expected
|
|
|
|
|
|
def test_clean_hyperopt(mocker, hyperopt_conf, caplog):
|
|
patch_exchange(mocker)
|
|
|
|
mocker.patch("freqtrade.strategy.hyper.HyperStrategyMixin.load_params_from_file",
|
|
MagicMock(return_value={}))
|
|
mocker.patch("freqtrade.optimize.hyperopt.Path.is_file", MagicMock(return_value=True))
|
|
unlinkmock = mocker.patch("freqtrade.optimize.hyperopt.Path.unlink", MagicMock())
|
|
h = Hyperopt(hyperopt_conf)
|
|
|
|
assert unlinkmock.call_count == 2
|
|
assert log_has(f"Removing `{h.data_pickle_file}`.", caplog)
|
|
|
|
|
|
def test_print_json_spaces_all(mocker, hyperopt_conf, capsys) -> None:
|
|
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.hyperopt.calculate_market_change', return_value=1.5)
|
|
|
|
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
|
|
MagicMock(return_value=(MagicMock(), None)))
|
|
mocker.patch(
|
|
'freqtrade.optimize.hyperopt.get_timerange',
|
|
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
|
|
)
|
|
|
|
parallel = mocker.patch(
|
|
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
|
|
MagicMock(return_value=[{
|
|
'loss': 1, 'results_explanation': 'foo result', 'params': {},
|
|
'params_details': {
|
|
'buy': {'mfi-value': None},
|
|
'sell': {'sell-mfi-value': None},
|
|
'roi': {}, 'stoploss': {'stoploss': None},
|
|
'trailing': {'trailing_stop': None},
|
|
'max_open_trades': {'max_open_trades': None}
|
|
},
|
|
'results_metrics': generate_result_metrics(),
|
|
}])
|
|
)
|
|
patch_exchange(mocker)
|
|
|
|
hyperopt_conf.update({'spaces': 'all',
|
|
'hyperopt_jobs': 1,
|
|
'print_json': True,
|
|
})
|
|
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
|
|
hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
|
|
|
|
hyperopt.start()
|
|
|
|
parallel.assert_called_once()
|
|
|
|
out, err = capsys.readouterr()
|
|
result_str = (
|
|
'{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi"'
|
|
':{},"stoploss":null,"trailing_stop":null,"max_open_trades":null}'
|
|
)
|
|
assert result_str in out # noqa: E501
|
|
# 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')
|
|
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
|
|
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
|
|
mocker.patch('freqtrade.optimize.hyperopt.calculate_market_change', return_value=1.5)
|
|
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
|
|
MagicMock(return_value=(MagicMock(), None)))
|
|
mocker.patch(
|
|
'freqtrade.optimize.hyperopt.get_timerange',
|
|
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
|
|
)
|
|
|
|
parallel = mocker.patch(
|
|
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
|
|
MagicMock(return_value=[{
|
|
'loss': 1, 'results_explanation': 'foo result', 'params': {},
|
|
'params_details': {
|
|
'buy': {'mfi-value': None},
|
|
'sell': {'sell-mfi-value': None},
|
|
'roi': {}, 'stoploss': {'stoploss': None}
|
|
},
|
|
'results_metrics': generate_result_metrics(),
|
|
}])
|
|
)
|
|
patch_exchange(mocker)
|
|
|
|
hyperopt_conf.update({'print_json': True})
|
|
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
|
|
hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
|
|
|
|
hyperopt.start()
|
|
|
|
parallel.assert_called_once()
|
|
|
|
out, err = capsys.readouterr()
|
|
assert '{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi":{},"stoploss":null}' in out # noqa: E501
|
|
# 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')
|
|
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
|
|
mocker.patch('freqtrade.optimize.hyperopt.calculate_market_change', return_value=1.5)
|
|
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
|
|
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
|
|
MagicMock(return_value=(MagicMock(), None)))
|
|
mocker.patch(
|
|
'freqtrade.optimize.hyperopt.get_timerange',
|
|
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
|
|
)
|
|
|
|
parallel = mocker.patch(
|
|
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
|
|
MagicMock(return_value=[{
|
|
'loss': 1, 'results_explanation': 'foo result', 'params': {},
|
|
'params_details': {'roi': {}, 'stoploss': {'stoploss': None}},
|
|
'results_metrics': generate_result_metrics(),
|
|
}])
|
|
)
|
|
patch_exchange(mocker)
|
|
|
|
hyperopt_conf.update({'spaces': 'roi stoploss',
|
|
'hyperopt_jobs': 1,
|
|
'print_json': True,
|
|
})
|
|
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
|
|
hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
|
|
|
|
hyperopt.start()
|
|
|
|
parallel.assert_called_once()
|
|
|
|
out, err = capsys.readouterr()
|
|
assert '{"minimal_roi":{},"stoploss":null}' in out
|
|
|
|
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')
|
|
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
|
|
mocker.patch('freqtrade.optimize.hyperopt.calculate_market_change', return_value=1.5)
|
|
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
|
|
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
|
|
MagicMock(return_value=(MagicMock(), None)))
|
|
mocker.patch(
|
|
'freqtrade.optimize.hyperopt.get_timerange',
|
|
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
|
|
)
|
|
|
|
parallel = mocker.patch(
|
|
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
|
|
MagicMock(return_value=[{
|
|
'loss': 1, 'results_explanation': 'foo result', 'params': {'stoploss': 0.0},
|
|
'results_metrics': generate_result_metrics(),
|
|
}])
|
|
)
|
|
patch_exchange(mocker)
|
|
|
|
hyperopt_conf.update({'spaces': 'roi stoploss'})
|
|
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
|
|
hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
|
|
|
|
hyperopt.start()
|
|
|
|
parallel.assert_called_once()
|
|
|
|
out, err = capsys.readouterr()
|
|
assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
|
|
assert dumper.call_count == 1
|
|
assert dumper2.call_count == 1
|
|
|
|
assert hasattr(hyperopt.backtesting.strategy, "advise_exit")
|
|
assert hasattr(hyperopt.backtesting.strategy, "advise_entry")
|
|
assert hyperopt.backtesting.strategy.max_open_trades == hyperopt_conf['max_open_trades']
|
|
assert hasattr(hyperopt.backtesting, "_position_stacking")
|
|
|
|
|
|
def test_simplified_interface_all_failed(mocker, hyperopt_conf, caplog) -> None:
|
|
mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
|
|
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
|
|
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
|
|
MagicMock(return_value=(MagicMock(), None)))
|
|
mocker.patch(
|
|
'freqtrade.optimize.hyperopt.get_timerange',
|
|
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
|
|
)
|
|
|
|
patch_exchange(mocker)
|
|
|
|
hyperopt_conf.update({'spaces': 'all', })
|
|
|
|
mocker.patch('freqtrade.optimize.hyperopt_auto.HyperOptAuto._generate_indicator_space',
|
|
return_value=[])
|
|
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
|
|
hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
|
|
|
|
with pytest.raises(OperationalException, match=r"The 'protection' space is included into *"):
|
|
hyperopt.init_spaces()
|
|
|
|
hyperopt.config['hyperopt_ignore_missing_space'] = True
|
|
caplog.clear()
|
|
hyperopt.init_spaces()
|
|
assert log_has_re(r"The 'protection' space is included into *", caplog)
|
|
assert hyperopt.protection_space == []
|
|
|
|
|
|
def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
|
|
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
|
|
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
|
|
mocker.patch('freqtrade.optimize.hyperopt.calculate_market_change', return_value=1.5)
|
|
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
|
|
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
|
|
MagicMock(return_value=(MagicMock(), None)))
|
|
mocker.patch(
|
|
'freqtrade.optimize.hyperopt.get_timerange',
|
|
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
|
|
)
|
|
|
|
parallel = mocker.patch(
|
|
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
|
|
MagicMock(return_value=[{
|
|
'loss': 1, 'results_explanation': 'foo result', 'params': {},
|
|
'results_metrics': generate_result_metrics(),
|
|
}])
|
|
)
|
|
patch_exchange(mocker)
|
|
|
|
hyperopt_conf.update({'spaces': 'buy'})
|
|
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
|
|
hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
|
|
|
|
hyperopt.start()
|
|
|
|
parallel.assert_called_once()
|
|
|
|
out, err = capsys.readouterr()
|
|
assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
|
|
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_entry")
|
|
assert hyperopt.backtesting.strategy.max_open_trades == hyperopt_conf['max_open_trades']
|
|
assert hasattr(hyperopt.backtesting, "_position_stacking")
|
|
|
|
|
|
def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None:
|
|
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
|
|
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
|
|
mocker.patch('freqtrade.optimize.hyperopt.calculate_market_change', return_value=1.5)
|
|
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
|
|
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
|
|
MagicMock(return_value=(MagicMock(), None)))
|
|
mocker.patch(
|
|
'freqtrade.optimize.hyperopt.get_timerange',
|
|
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
|
|
)
|
|
|
|
parallel = mocker.patch(
|
|
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
|
|
MagicMock(return_value=[{
|
|
'loss': 1, 'results_explanation': 'foo result', 'params': {},
|
|
'results_metrics': generate_result_metrics(),
|
|
}])
|
|
)
|
|
patch_exchange(mocker)
|
|
|
|
hyperopt_conf.update({'spaces': 'sell', })
|
|
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
|
|
hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
|
|
|
|
hyperopt.start()
|
|
|
|
parallel.assert_called_once()
|
|
|
|
out, err = capsys.readouterr()
|
|
assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
|
|
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_entry")
|
|
assert hyperopt.backtesting.strategy.max_open_trades == hyperopt_conf['max_open_trades']
|
|
assert hasattr(hyperopt.backtesting, "_position_stacking")
|
|
|
|
|
|
@pytest.mark.parametrize("space", [
|
|
('buy'),
|
|
('sell'),
|
|
('protection'),
|
|
])
|
|
def test_simplified_interface_failed(mocker, hyperopt_conf, space) -> None:
|
|
mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
|
|
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
|
|
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
|
|
MagicMock(return_value=(MagicMock(), None)))
|
|
mocker.patch(
|
|
'freqtrade.optimize.hyperopt.get_timerange',
|
|
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
|
|
)
|
|
mocker.patch('freqtrade.optimize.hyperopt_auto.HyperOptAuto._generate_indicator_space',
|
|
return_value=[])
|
|
|
|
patch_exchange(mocker)
|
|
|
|
hyperopt_conf.update({'spaces': space})
|
|
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
|
|
hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
|
|
|
|
with pytest.raises(OperationalException, match=f"The '{space}' space is included into *"):
|
|
hyperopt.start()
|
|
|
|
|
|
def test_in_strategy_auto_hyperopt(mocker, hyperopt_conf, tmpdir, fee) -> None:
|
|
patch_exchange(mocker)
|
|
mocker.patch(f'{EXMS}.get_fee', fee)
|
|
(Path(tmpdir) / 'hyperopt_results').mkdir(parents=True)
|
|
# No hyperopt needed
|
|
hyperopt_conf.update({
|
|
'strategy': 'HyperoptableStrategy',
|
|
'user_data_dir': Path(tmpdir),
|
|
'hyperopt_random_state': 42,
|
|
'spaces': ['all'],
|
|
})
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
hyperopt.backtesting.exchange.get_max_leverage = MagicMock(return_value=1.0)
|
|
assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto)
|
|
assert isinstance(hyperopt.backtesting.strategy.buy_rsi, IntParameter)
|
|
assert hyperopt.backtesting.strategy.bot_loop_started is True
|
|
|
|
assert hyperopt.backtesting.strategy.buy_rsi.in_space is True
|
|
assert hyperopt.backtesting.strategy.buy_rsi.value == 35
|
|
assert hyperopt.backtesting.strategy.sell_rsi.value == 74
|
|
assert hyperopt.backtesting.strategy.protection_cooldown_lookback.value == 30
|
|
assert hyperopt.backtesting.strategy.max_open_trades == 1
|
|
buy_rsi_range = hyperopt.backtesting.strategy.buy_rsi.range
|
|
assert isinstance(buy_rsi_range, range)
|
|
# Range from 0 - 50 (inclusive)
|
|
assert len(list(buy_rsi_range)) == 51
|
|
|
|
hyperopt.start()
|
|
# All values should've changed.
|
|
assert hyperopt.backtesting.strategy.protection_cooldown_lookback.value != 30
|
|
assert hyperopt.backtesting.strategy.buy_rsi.value != 35
|
|
assert hyperopt.backtesting.strategy.sell_rsi.value != 74
|
|
assert hyperopt.backtesting.strategy.max_open_trades != 1
|
|
|
|
hyperopt.custom_hyperopt.generate_estimator = lambda *args, **kwargs: 'ET1'
|
|
with pytest.raises(OperationalException, match="Estimator ET1 not supported."):
|
|
hyperopt.get_optimizer([], 2)
|
|
|
|
|
|
def test_in_strategy_auto_hyperopt_with_parallel(mocker, hyperopt_conf, tmpdir, fee) -> None:
|
|
mocker.patch(f'{EXMS}.validate_config', MagicMock())
|
|
mocker.patch(f'{EXMS}.get_fee', fee)
|
|
mocker.patch(f'{EXMS}._load_markets')
|
|
mocker.patch(f'{EXMS}.markets',
|
|
PropertyMock(return_value=get_markets()))
|
|
(Path(tmpdir) / 'hyperopt_results').mkdir(parents=True)
|
|
# No hyperopt needed
|
|
hyperopt_conf.update({
|
|
'strategy': 'HyperoptableStrategy',
|
|
'user_data_dir': Path(tmpdir),
|
|
'hyperopt_random_state': 42,
|
|
'spaces': ['all'],
|
|
# Enforce parallelity
|
|
'epochs': 2,
|
|
'hyperopt_jobs': 2,
|
|
'fee': fee.return_value,
|
|
})
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
hyperopt.backtesting.exchange.get_max_leverage = lambda *x, **xx: 1.0
|
|
hyperopt.backtesting.exchange.get_min_pair_stake_amount = lambda *x, **xx: 0.00001
|
|
hyperopt.backtesting.exchange.get_max_pair_stake_amount = lambda *x, **xx: 100.0
|
|
hyperopt.backtesting.exchange._markets = get_markets()
|
|
|
|
assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto)
|
|
assert isinstance(hyperopt.backtesting.strategy.buy_rsi, IntParameter)
|
|
assert hyperopt.backtesting.strategy.bot_loop_started is True
|
|
|
|
assert hyperopt.backtesting.strategy.buy_rsi.in_space is True
|
|
assert hyperopt.backtesting.strategy.buy_rsi.value == 35
|
|
assert hyperopt.backtesting.strategy.sell_rsi.value == 74
|
|
assert hyperopt.backtesting.strategy.protection_cooldown_lookback.value == 30
|
|
buy_rsi_range = hyperopt.backtesting.strategy.buy_rsi.range
|
|
assert isinstance(buy_rsi_range, range)
|
|
# Range from 0 - 50 (inclusive)
|
|
assert len(list(buy_rsi_range)) == 51
|
|
|
|
hyperopt.start()
|
|
|
|
|
|
def test_in_strategy_auto_hyperopt_per_epoch(mocker, hyperopt_conf, tmpdir, fee) -> None:
|
|
patch_exchange(mocker)
|
|
mocker.patch(f'{EXMS}.get_fee', fee)
|
|
(Path(tmpdir) / 'hyperopt_results').mkdir(parents=True)
|
|
|
|
hyperopt_conf.update({
|
|
'strategy': 'HyperoptableStrategy',
|
|
'user_data_dir': Path(tmpdir),
|
|
'hyperopt_random_state': 42,
|
|
'spaces': ['all'],
|
|
'epochs': 3,
|
|
'analyze_per_epoch': True,
|
|
})
|
|
go = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.generate_optimizer',
|
|
return_value={
|
|
'loss': 0.05,
|
|
'results_explanation': 'foo result', 'params': {},
|
|
'results_metrics': generate_result_metrics(),
|
|
})
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
hyperopt.backtesting.exchange.get_max_leverage = MagicMock(return_value=1.0)
|
|
assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto)
|
|
assert isinstance(hyperopt.backtesting.strategy.buy_rsi, IntParameter)
|
|
assert hyperopt.backtesting.strategy.bot_loop_started is True
|
|
|
|
assert hyperopt.backtesting.strategy.buy_rsi.in_space is True
|
|
assert hyperopt.backtesting.strategy.buy_rsi.value == 35
|
|
assert hyperopt.backtesting.strategy.sell_rsi.value == 74
|
|
assert hyperopt.backtesting.strategy.protection_cooldown_lookback.value == 30
|
|
buy_rsi_range = hyperopt.backtesting.strategy.buy_rsi.range
|
|
assert isinstance(buy_rsi_range, range)
|
|
# Range from 0 - 50 (inclusive)
|
|
assert len(list(buy_rsi_range)) == 51
|
|
|
|
hyperopt.start()
|
|
# backtesting should be called 3 times (once per epoch)
|
|
assert go.call_count == 3
|
|
|
|
|
|
def test_SKDecimal():
|
|
space = SKDecimal(1, 2, decimals=2)
|
|
assert 1.5 in space
|
|
assert 2.5 not in space
|
|
assert space.low == 100
|
|
assert space.high == 200
|
|
|
|
assert space.inverse_transform([200]) == [2.0]
|
|
assert space.inverse_transform([100]) == [1.0]
|
|
assert space.inverse_transform([150, 160]) == [1.5, 1.6]
|
|
|
|
assert space.transform([1.5]) == [150]
|
|
assert space.transform([2.0]) == [200]
|
|
assert space.transform([1.0]) == [100]
|
|
assert space.transform([1.5, 1.6]) == [150, 160]
|
|
|
|
|
|
def test_stake_amount_unlimited_max_open_trades(mocker, hyperopt_conf, tmpdir, fee) -> None:
|
|
# This test is to ensure that unlimited max_open_trades are ignored for the backtesting
|
|
# if we have an unlimited stake amount
|
|
patch_exchange(mocker)
|
|
mocker.patch(f'{EXMS}.get_fee', fee)
|
|
(Path(tmpdir) / 'hyperopt_results').mkdir(parents=True)
|
|
hyperopt_conf.update({
|
|
'strategy': 'HyperoptableStrategy',
|
|
'user_data_dir': Path(tmpdir),
|
|
'hyperopt_random_state': 42,
|
|
'spaces': ['trades'],
|
|
'stake_amount': 'unlimited'
|
|
})
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._get_params_dict',
|
|
return_value={
|
|
'max_open_trades': -1
|
|
})
|
|
|
|
assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto)
|
|
|
|
assert hyperopt.backtesting.strategy.max_open_trades == 1
|
|
|
|
hyperopt.start()
|
|
|
|
assert hyperopt.backtesting.strategy.max_open_trades == 1
|
|
|
|
|
|
def test_max_open_trades_dump(mocker, hyperopt_conf, tmpdir, fee, capsys) -> None:
|
|
# This test is to ensure that after hyperopting, max_open_trades is never
|
|
# saved as inf in the output json params
|
|
patch_exchange(mocker)
|
|
mocker.patch(f'{EXMS}.get_fee', fee)
|
|
(Path(tmpdir) / 'hyperopt_results').mkdir(parents=True)
|
|
hyperopt_conf.update({
|
|
'strategy': 'HyperoptableStrategy',
|
|
'user_data_dir': Path(tmpdir),
|
|
'hyperopt_random_state': 42,
|
|
'spaces': ['trades'],
|
|
})
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._get_params_dict',
|
|
return_value={
|
|
'max_open_trades': -1
|
|
})
|
|
|
|
assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto)
|
|
|
|
hyperopt.start()
|
|
|
|
out, err = capsys.readouterr()
|
|
|
|
assert 'max_open_trades = -1' in out
|
|
assert 'max_open_trades = inf' not in out
|
|
|
|
##############
|
|
|
|
hyperopt_conf.update({'print_json': True})
|
|
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._get_params_dict',
|
|
return_value={
|
|
'max_open_trades': -1
|
|
})
|
|
|
|
assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto)
|
|
|
|
hyperopt.start()
|
|
|
|
out, err = capsys.readouterr()
|
|
|
|
assert '"max_open_trades":-1' in out
|
|
|
|
|
|
def test_max_open_trades_consistency(mocker, hyperopt_conf, tmpdir, fee) -> None:
|
|
# This test is to ensure that max_open_trades is the same across all functions needing it
|
|
# after it has been changed from the hyperopt
|
|
patch_exchange(mocker)
|
|
mocker.patch(f'{EXMS}.get_fee', return_value=0)
|
|
|
|
(Path(tmpdir) / 'hyperopt_results').mkdir(parents=True)
|
|
hyperopt_conf.update({
|
|
'strategy': 'HyperoptableStrategy',
|
|
'user_data_dir': Path(tmpdir),
|
|
'hyperopt_random_state': 42,
|
|
'spaces': ['trades'],
|
|
'stake_amount': 'unlimited',
|
|
'dry_run_wallet': 8,
|
|
'available_capital': 8,
|
|
'dry_run': True,
|
|
'epochs': 1
|
|
})
|
|
hyperopt = Hyperopt(hyperopt_conf)
|
|
|
|
assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto)
|
|
|
|
hyperopt.custom_hyperopt.max_open_trades_space = lambda: [
|
|
Integer(1, 10, name='max_open_trades')]
|
|
|
|
first_time_evaluated = False
|
|
|
|
def stake_amount_interceptor(func):
|
|
@wraps(func)
|
|
def wrapper(*args, **kwargs):
|
|
nonlocal first_time_evaluated
|
|
stake_amount = func(*args, **kwargs)
|
|
if first_time_evaluated is False:
|
|
assert stake_amount == 1
|
|
first_time_evaluated = True
|
|
return stake_amount
|
|
return wrapper
|
|
|
|
hyperopt.backtesting.wallets._calculate_unlimited_stake_amount = stake_amount_interceptor(
|
|
hyperopt.backtesting.wallets._calculate_unlimited_stake_amount)
|
|
|
|
hyperopt.start()
|
|
|
|
assert hyperopt.backtesting.strategy.max_open_trades == 8
|
|
assert hyperopt.config['max_open_trades'] == 8
|