374 lines
12 KiB
Python
374 lines
12 KiB
Python
# pragma pylint: disable=missing-docstring,W0212,C0103
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import os
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from copy import deepcopy
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from unittest.mock import MagicMock
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import pandas as pd
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from freqtrade.optimize.hyperopt import Hyperopt
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from freqtrade.tests.conftest import default_conf, log_has
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# Avoid to reinit the same object again and again
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_HYPEROPT = Hyperopt(default_conf())
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# Functions for recurrent object patching
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def create_trials(mocker) -> None:
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"""
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When creating trials, mock the hyperopt Trials so that *by default*
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- we don't create any pickle'd files in the filesystem
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- we might have a pickle'd file so make sure that we return
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false when looking for it
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"""
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_HYPEROPT.trials_file = os.path.join('freqtrade', 'tests', 'optimize', 'ut_trials.pickle')
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mocker.patch('freqtrade.optimize.hyperopt.os.path.exists', return_value=False)
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mocker.patch('freqtrade.optimize.hyperopt.os.remove', return_value=True)
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mocker.patch('freqtrade.optimize.hyperopt.pickle.dump', return_value=None)
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return mocker.Mock(
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results=[
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{
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'loss': 1,
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'result': 'foo',
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'status': 'ok'
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}
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],
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best_trial={'misc': {'vals': {'adx': 999}}}
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)
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# Unit tests
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def test_loss_calculation_prefer_correct_trade_count() -> None:
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"""
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Test Hyperopt.calculate_loss()
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"""
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hyperopt = _HYPEROPT
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correct = hyperopt.calculate_loss(1, hyperopt.target_trades, 20)
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over = hyperopt.calculate_loss(1, hyperopt.target_trades + 100, 20)
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under = hyperopt.calculate_loss(1, hyperopt.target_trades - 100, 20)
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assert over > correct
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assert under > correct
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def test_loss_calculation_prefer_shorter_trades() -> None:
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"""
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Test Hyperopt.calculate_loss()
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"""
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hyperopt = _HYPEROPT
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shorter = hyperopt.calculate_loss(1, 100, 20)
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longer = hyperopt.calculate_loss(1, 100, 30)
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assert shorter < longer
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def test_loss_calculation_has_limited_profit() -> None:
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hyperopt = _HYPEROPT
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correct = hyperopt.calculate_loss(hyperopt.expected_max_profit, hyperopt.target_trades, 20)
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over = hyperopt.calculate_loss(hyperopt.expected_max_profit * 2, hyperopt.target_trades, 20)
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under = hyperopt.calculate_loss(hyperopt.expected_max_profit / 2, hyperopt.target_trades, 20)
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assert over == correct
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assert under > correct
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def test_log_results_if_loss_improves(caplog) -> None:
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hyperopt = _HYPEROPT
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hyperopt.current_best_loss = 2
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hyperopt.log_results(
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{
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'loss': 1,
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'current_tries': 1,
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'total_tries': 2,
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'result': 'foo'
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}
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)
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assert log_has(' 1/2: foo. Loss 1.00000', caplog.record_tuples)
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def test_no_log_if_loss_does_not_improve(caplog) -> None:
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hyperopt = _HYPEROPT
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hyperopt.current_best_loss = 2
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hyperopt.log_results(
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{
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'loss': 3,
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}
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)
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assert caplog.record_tuples == []
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def test_fmin_best_results(mocker, default_conf, caplog) -> None:
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fmin_result = {
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"macd_below_zero": 0,
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"adx": 1,
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"adx-value": 15.0,
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"fastd": 1,
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"fastd-value": 40.0,
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"green_candle": 1,
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"mfi": 0,
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"over_sar": 0,
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"rsi": 1,
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"rsi-value": 37.0,
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"trigger": 2,
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"uptrend_long_ema": 1,
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"uptrend_short_ema": 0,
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"uptrend_sma": 0,
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"stoploss": -0.1,
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"roi_t1": 1,
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"roi_t2": 2,
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"roi_t3": 3,
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"roi_p1": 1,
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"roi_p2": 2,
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"roi_p3": 3,
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}
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conf = deepcopy(default_conf)
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conf.update({'config': 'config.json.example'})
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conf.update({'epochs': 1})
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conf.update({'timerange': None})
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conf.update({'spaces': 'all'})
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mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
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mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value=fmin_result)
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mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
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mocker.patch('freqtrade.logger.Logger.set_format', MagicMock())
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hyperopt = Hyperopt(conf)
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hyperopt.trials = create_trials(mocker)
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hyperopt.tickerdata_to_dataframe = MagicMock()
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hyperopt.start()
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exists = [
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'Best parameters:',
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'"adx": {\n "enabled": true,\n "value": 15.0\n },',
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'"fastd": {\n "enabled": true,\n "value": 40.0\n },',
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'"green_candle": {\n "enabled": true\n },',
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'"macd_below_zero": {\n "enabled": false\n },',
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'"mfi": {\n "enabled": false\n },',
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'"over_sar": {\n "enabled": false\n },',
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'"roi_p1": 1.0,',
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'"roi_p2": 2.0,',
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'"roi_p3": 3.0,',
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'"roi_t1": 1.0,',
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'"roi_t2": 2.0,',
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'"roi_t3": 3.0,',
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'"rsi": {\n "enabled": true,\n "value": 37.0\n },',
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'"stoploss": -0.1,',
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'"trigger": {\n "type": "faststoch10"\n },',
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'"uptrend_long_ema": {\n "enabled": true\n },',
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'"uptrend_short_ema": {\n "enabled": false\n },',
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'"uptrend_sma": {\n "enabled": false\n }',
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'ROI table:\n{0: 6.0, 3.0: 3.0, 5.0: 1.0, 6.0: 0}',
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'Best Result:\nfoo'
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]
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for line in exists:
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assert line in caplog.text
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def test_fmin_throw_value_error(mocker, default_conf, caplog) -> None:
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mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
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mocker.patch('freqtrade.optimize.hyperopt.fmin', side_effect=ValueError())
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conf = deepcopy(default_conf)
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conf.update({'config': 'config.json.example'})
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conf.update({'epochs': 1})
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conf.update({'timerange': None})
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conf.update({'spaces': 'all'})
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mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
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mocker.patch('freqtrade.logger.Logger.set_format', MagicMock())
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hyperopt = Hyperopt(conf)
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hyperopt.trials = create_trials(mocker)
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hyperopt.tickerdata_to_dataframe = MagicMock()
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hyperopt.start()
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exists = [
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'Best Result:',
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'Sorry, Hyperopt was not able to find good parameters. Please try with more epochs '
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'(param: -e).',
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]
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for line in exists:
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assert line in caplog.text
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def test_resuming_previous_hyperopt_results_succeeds(mocker, default_conf) -> None:
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trials = create_trials(mocker)
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conf = deepcopy(default_conf)
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conf.update({'config': 'config.json.example'})
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conf.update({'epochs': 1})
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conf.update({'mongodb': False})
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conf.update({'timerange': None})
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conf.update({'spaces': 'all'})
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mocker.patch('freqtrade.optimize.hyperopt.os.path.exists', return_value=True)
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mocker.patch('freqtrade.optimize.hyperopt.len', return_value=len(trials.results))
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mock_read = mocker.patch(
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'freqtrade.optimize.hyperopt.Hyperopt.read_trials',
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return_value=trials
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)
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mock_save = mocker.patch(
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'freqtrade.optimize.hyperopt.Hyperopt.save_trials',
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return_value=None
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)
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mocker.patch('freqtrade.optimize.hyperopt.sorted', return_value=trials.results)
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mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
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mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
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mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
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mocker.patch('freqtrade.logger.Logger.set_format', MagicMock())
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hyperopt = Hyperopt(conf)
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hyperopt.trials = trials
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hyperopt.tickerdata_to_dataframe = MagicMock()
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hyperopt.start()
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mock_read.assert_called_once()
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mock_save.assert_called_once()
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current_tries = hyperopt.current_tries
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total_tries = hyperopt.total_tries
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assert current_tries == len(trials.results)
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assert total_tries == (current_tries + len(trials.results))
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def test_save_trials_saves_trials(mocker, caplog) -> None:
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create_trials(mocker)
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mock_dump = mocker.patch('freqtrade.optimize.hyperopt.pickle.dump', return_value=None)
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hyperopt = _HYPEROPT
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mocker.patch('freqtrade.optimize.hyperopt.open', return_value=hyperopt.trials_file)
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hyperopt.save_trials()
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assert log_has(
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'Saving Trials to \'freqtrade/tests/optimize/ut_trials.pickle\'',
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caplog.record_tuples
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)
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mock_dump.assert_called_once()
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def test_read_trials_returns_trials_file(mocker, default_conf, caplog) -> None:
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trials = create_trials(mocker)
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mock_load = mocker.patch('freqtrade.optimize.hyperopt.pickle.load', return_value=trials)
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mock_open = mocker.patch('freqtrade.optimize.hyperopt.open', return_value=mock_load)
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hyperopt = _HYPEROPT
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hyperopt_trial = hyperopt.read_trials()
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assert log_has(
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'Reading Trials from \'freqtrade/tests/optimize/ut_trials.pickle\'',
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caplog.record_tuples
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)
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assert hyperopt_trial == trials
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mock_open.assert_called_once()
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mock_load.assert_called_once()
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def test_roi_table_generation() -> None:
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params = {
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'roi_t1': 5,
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'roi_t2': 10,
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'roi_t3': 15,
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'roi_p1': 1,
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'roi_p2': 2,
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'roi_p3': 3,
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}
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hyperopt = _HYPEROPT
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assert hyperopt.generate_roi_table(params) == {0: 6, 15: 3, 25: 1, 30: 0}
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def test_start_calls_fmin(mocker, default_conf) -> None:
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trials = create_trials(mocker)
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mocker.patch('freqtrade.optimize.hyperopt.sorted', return_value=trials.results)
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mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
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mock_fmin = mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
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conf = deepcopy(default_conf)
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conf.update({'config': 'config.json.example'})
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conf.update({'epochs': 1})
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conf.update({'mongodb': False})
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conf.update({'timerange': None})
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conf.update({'spaces': 'all'})
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hyperopt = Hyperopt(conf)
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hyperopt.trials = trials
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hyperopt.tickerdata_to_dataframe = MagicMock()
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hyperopt.start()
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mock_fmin.assert_called_once()
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def test_start_uses_mongotrials(mocker, default_conf) -> None:
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mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
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mock_fmin = mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
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mock_mongotrials = mocker.patch(
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'freqtrade.optimize.hyperopt.MongoTrials',
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return_value=create_trials(mocker)
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)
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conf = deepcopy(default_conf)
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conf.update({'config': 'config.json.example'})
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conf.update({'epochs': 1})
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conf.update({'mongodb': True})
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conf.update({'timerange': None})
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conf.update({'spaces': 'all'})
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mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
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hyperopt = Hyperopt(conf)
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hyperopt.tickerdata_to_dataframe = MagicMock()
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hyperopt.start()
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mock_mongotrials.assert_called_once()
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mock_fmin.assert_called_once()
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# test log_trials_result
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# test buy_strategy_generator def populate_buy_trend
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# test optimizer if 'ro_t1' in params
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def test_format_results():
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"""
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Test Hyperopt.format_results()
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"""
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trades = [
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('BTC_ETH', 2, 2, 123),
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('BTC_LTC', 1, 1, 123),
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('BTC_XRP', -1, -2, -246)
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]
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labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']
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df = pd.DataFrame.from_records(trades, columns=labels)
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x = Hyperopt.format_results(df)
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assert x.find(' 66.67%')
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def test_signal_handler(mocker):
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"""
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Test Hyperopt.signal_handler()
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"""
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m = MagicMock()
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mocker.patch('sys.exit', m)
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mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.save_trials', m)
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mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.log_trials_result', m)
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hyperopt = _HYPEROPT
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hyperopt.signal_handler(9, None)
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assert m.call_count == 3
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def test_has_space():
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"""
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Test Hyperopt.has_space() method
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"""
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_HYPEROPT.config.update({'spaces': ['buy', 'roi']})
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assert _HYPEROPT.has_space('roi')
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assert _HYPEROPT.has_space('buy')
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assert not _HYPEROPT.has_space('stoploss')
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_HYPEROPT.config.update({'spaces': ['all']})
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assert _HYPEROPT.has_space('buy')
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