# pragma pylint: disable=missing-docstring,W0212,C0103 from datetime import datetime 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 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': { 'trade_count': 1, 'avg_profit': 0.1, 'total_profit': 0.001, 'profit': 1.0, 'duration': 20.0 }, '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%)", "20.0 m"]) 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': { 'trade_count': 1, 'avg_profit': 0.1, 'total_profit': 0.001, 'profit': 1.0, 'duration': 20.0 }, }]) ) 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': { 'trade_count': 1, 'avg_profit': 0.1, 'total_profit': 0.001, 'profit': 1.0, 'duration': 20.0 } }]) ) 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': { 'trade_count': 1, 'avg_profit': 0.1, 'total_profit': 0.001, 'profit': 1.0, 'duration': 20.0 } }]) ) 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': { 'trade_count': 1, 'avg_profit': 0.1, 'total_profit': 0.001, 'profit': 1.0, 'duration': 20.0 } }]) ) 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': { 'trade_count': 1, 'avg_profit': 0.1, 'total_profit': 0.001, 'profit': 1.0, 'duration': 20.0 } }]) ) 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': { 'trade_count': 1, 'avg_profit': 0.1, 'total_profit': 0.001, 'profit': 1.0, 'duration': 20.0 } }]) ) 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': { 'trade_count': 1, 'avg_profit': 0.1, 'total_profit': 0.001, 'profit': 1.0, 'duration': 20.0 } }]) ) 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]