import logging import re from pathlib import Path from typing import Dict, List import numpy as np import pytest import rapidjson from freqtrade.constants import FTHYPT_FILEVERSION from freqtrade.exceptions import OperationalException from freqtrade.optimize.hyperopt_tools import HyperoptTools, hyperopt_serializer from tests.conftest import log_has # Functions for recurrent object patching def create_results() -> List[Dict]: return [{'loss': 1, 'result': 'foo', 'params': {}, 'is_best': True}] def test_save_results_saves_epochs(hyperopt, tmpdir, caplog) -> None: # Test writing to temp dir and reading again epochs = create_results() hyperopt.results_file = Path(tmpdir / 'ut_results.fthypt') caplog.set_level(logging.DEBUG) for epoch in epochs: hyperopt._save_result(epoch) assert log_has(f"1 epoch saved to '{hyperopt.results_file}'.", caplog) hyperopt._save_result(epochs[0]) assert log_has(f"2 epochs saved to '{hyperopt.results_file}'.", caplog) hyperopt_epochs = HyperoptTools.load_previous_results(hyperopt.results_file) assert len(hyperopt_epochs) == 2 def test_load_previous_results2(mocker, testdatadir, caplog) -> None: results_file = testdatadir / 'hyperopt_results_SampleStrategy.pickle' with pytest.raises(OperationalException, match=r"Legacy hyperopt results are no longer supported.*"): HyperoptTools.load_previous_results(results_file) @pytest.mark.parametrize("spaces, expected_results", [ (['buy'], {'buy': True, 'sell': False, 'roi': False, 'stoploss': False, 'trailing': False}), (['sell'], {'buy': False, 'sell': True, 'roi': False, 'stoploss': False, 'trailing': False}), (['roi'], {'buy': False, 'sell': False, 'roi': True, 'stoploss': False, 'trailing': False}), (['stoploss'], {'buy': False, 'sell': False, 'roi': False, 'stoploss': True, 'trailing': False}), (['trailing'], {'buy': False, 'sell': False, 'roi': False, 'stoploss': False, 'trailing': True}), (['buy', 'sell', 'roi', 'stoploss'], {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}), (['buy', 'sell', 'roi', 'stoploss', 'trailing'], {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}), (['buy', 'roi'], {'buy': True, 'sell': False, 'roi': True, 'stoploss': False, 'trailing': False}), (['all'], {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}), (['default'], {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}), (['default', 'trailing'], {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}), (['all', 'buy'], {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}), (['default', 'buy'], {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}), ]) def test_has_space(hyperopt_conf, spaces, expected_results): for s in ['buy', 'sell', 'roi', 'stoploss', 'trailing']: hyperopt_conf.update({'spaces': spaces}) assert HyperoptTools.has_space(hyperopt_conf, s) == expected_results[s] def test_show_epoch_details(capsys): test_result = { 'params_details': { 'trailing': { 'trailing_stop': True, 'trailing_stop_positive': 0.02, 'trailing_stop_positive_offset': 0.04, 'trailing_only_offset_is_reached': True }, 'roi': { 0: 0.18, 90: 0.14, 225: 0.05, 430: 0}, }, 'results_explanation': 'foo result', 'is_initial_point': False, 'total_profit': 0, 'current_epoch': 2, # This starts from 1 (in a human-friendly manner) 'is_best': True } HyperoptTools.show_epoch_details(test_result, 5, False, no_header=True) captured = capsys.readouterr() assert '# Trailing stop:' in captured.out # re.match(r"Pairs for .*", captured.out) assert re.search(r'^\s+trailing_stop = True$', captured.out, re.MULTILINE) assert re.search(r'^\s+trailing_stop_positive = 0.02$', captured.out, re.MULTILINE) assert re.search(r'^\s+trailing_stop_positive_offset = 0.04$', captured.out, re.MULTILINE) assert re.search(r'^\s+trailing_only_offset_is_reached = True$', captured.out, re.MULTILINE) assert '# ROI table:' in captured.out assert re.search(r'^\s+minimal_roi = \{$', captured.out, re.MULTILINE) assert re.search(r'^\s+\"90\"\:\s0.14,\s*$', captured.out, re.MULTILINE) def test__pprint_dict(): params = {'buy_std': 1.2, 'buy_rsi': 31, 'buy_enable': True, 'buy_what': 'asdf'} non_params = {'buy_notoptimied': 55} x = HyperoptTools._pprint_dict(params, non_params) assert x == """{ "buy_std": 1.2, "buy_rsi": 31, "buy_enable": True, "buy_what": "asdf", "buy_notoptimied": 55, # value loaded from strategy }""" def test_get_strategy_filename(default_conf): x = HyperoptTools.get_strategy_filename(default_conf, 'DefaultStrategy') assert isinstance(x, Path) assert x == Path(__file__).parents[1] / 'strategy/strats/default_strategy.py' x = HyperoptTools.get_strategy_filename(default_conf, 'NonExistingStrategy') assert x is None def test_export_params(tmpdir): filename = Path(tmpdir) / "DefaultStrategy.json" assert not filename.is_file() params = { "params_details": { "buy": { "buy_rsi": 30 }, "sell": { "sell_rsi": 70 }, "roi": { "0": 0.528, "346": 0.08499, "507": 0.049, "1595": 0 } }, "params_not_optimized": { "stoploss": -0.05, "trailing": { "trailing_stop": False, "trailing_stop_positive": 0.05, "trailing_stop_positive_offset": 0.1, "trailing_only_offset_is_reached": True }, } } HyperoptTools.export_params(params, "DefaultStrategy", filename) assert filename.is_file() content = rapidjson.load(filename.open('r')) assert content['strategy_name'] == 'DefaultStrategy' assert 'params' in content assert "buy" in content["params"] assert "sell" in content["params"] assert "roi" in content["params"] assert "stoploss" in content["params"] assert "trailing" in content["params"] def test_try_export_params(default_conf, tmpdir, caplog, mocker): default_conf['disableparamexport'] = False export_mock = mocker.patch("freqtrade.optimize.hyperopt_tools.HyperoptTools.export_params") filename = Path(tmpdir) / "DefaultStrategy.json" assert not filename.is_file() params = { "params_details": { "buy": { "buy_rsi": 30 }, "sell": { "sell_rsi": 70 }, "roi": { "0": 0.528, "346": 0.08499, "507": 0.049, "1595": 0 } }, "params_not_optimized": { "stoploss": -0.05, "trailing": { "trailing_stop": False, "trailing_stop_positive": 0.05, "trailing_stop_positive_offset": 0.1, "trailing_only_offset_is_reached": True }, }, FTHYPT_FILEVERSION: 2, } HyperoptTools.try_export_params(default_conf, "DefaultStrategy22", params) assert log_has("Strategy not found, not exporting parameter file.", caplog) assert export_mock.call_count == 0 caplog.clear() HyperoptTools.try_export_params(default_conf, "DefaultStrategy", params) assert export_mock.call_count == 1 assert export_mock.call_args_list[0][0][1] == 'DefaultStrategy' assert export_mock.call_args_list[0][0][2].name == 'default_strategy.json' def test_params_print(capsys): params = { "buy": { "buy_rsi": 30 }, "sell": { "sell_rsi": 70 }, } non_optimized = { "buy": { "buy_adx": 44 }, "sell": { "sell_adx": 65 }, "stoploss": { "stoploss": -0.05, }, "roi": { "0": 0.05, "20": 0.01, }, "trailing": { "trailing_stop": False, "trailing_stop_positive": 0.05, "trailing_stop_positive_offset": 0.1, "trailing_only_offset_is_reached": True }, } HyperoptTools._params_pretty_print(params, 'buy', 'No header', non_optimized) captured = capsys.readouterr() assert re.search("# No header", captured.out) assert re.search('"buy_rsi": 30,\n', captured.out) assert re.search('"buy_adx": 44, # value loaded.*\n', captured.out) assert not re.search("sell", captured.out) HyperoptTools._params_pretty_print(params, 'sell', 'Sell Header', non_optimized) captured = capsys.readouterr() assert re.search("# Sell Header", captured.out) assert re.search('"sell_rsi": 70,\n', captured.out) assert re.search('"sell_adx": 65, # value loaded.*\n', captured.out) HyperoptTools._params_pretty_print(params, 'roi', 'ROI Table:', non_optimized) captured = capsys.readouterr() assert re.search("# ROI Table: # value loaded.*\n", captured.out) assert re.search('minimal_roi = {\n', captured.out) assert re.search('"20": 0.01\n', captured.out) HyperoptTools._params_pretty_print(params, 'trailing', 'Trailing stop:', non_optimized) captured = capsys.readouterr() assert re.search("# Trailing stop:", captured.out) assert re.search('trailing_stop = False # value loaded.*\n', captured.out) assert re.search('trailing_stop_positive = 0.05 # value loaded.*\n', captured.out) assert re.search('trailing_stop_positive_offset = 0.1 # value loaded.*\n', captured.out) assert re.search('trailing_only_offset_is_reached = True # value loaded.*\n', captured.out) def test_hyperopt_serializer(): assert isinstance(hyperopt_serializer(np.int_(5)), int) assert isinstance(hyperopt_serializer(np.bool_(True)), bool) assert isinstance(hyperopt_serializer(np.bool_(False)), bool)