# pragma pylint: disable=missing-docstring,W0212,C0103 from datetime import datetime, timedelta from pathlib import Path from unittest.mock import ANY, MagicMock import pandas as pd import pytest from arrow import Arrow from filelock import Timeout from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_hyperopt from freqtrade.data.history import load_data from freqtrade.enums import RunMode, SellType 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.hyper import IntParameter from tests.conftest import (CURRENT_TEST_STRATEGY, get_args, 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_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 not log_has_re('Parameter -i/--ticker-interval detected .*', caplog) 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) -> None: hyperopt_conf['user_data_dir'] = Path("tests") 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) # TODO: migrate to strategy-based hyperopt 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_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 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.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 hasattr(hyperopt, "max_open_trades") assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades'] assert hasattr(hyperopt, "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], "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, '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], "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', 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, } 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}}, '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() hyperopt.dimensions = hyperopt.dimensions 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.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} }, '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}' ) 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.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.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.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 hasattr(hyperopt, "max_open_trades") assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades'] assert hasattr(hyperopt, "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.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 hasattr(hyperopt, "max_open_trades") assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades'] assert hasattr(hyperopt, "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.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 hasattr(hyperopt, "max_open_trades") assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades'] assert hasattr(hyperopt, "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('freqtrade.exchange.Exchange.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) assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto) assert isinstance(hyperopt.backtesting.strategy.buy_rsi, IntParameter) 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() # 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 hyperopt.custom_hyperopt.generate_estimator = lambda *args, **kwargs: 'ET1' with pytest.raises(OperationalException, match="Estimator ET1 not supported."): hyperopt.get_optimizer([], 2) 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]