538 lines
16 KiB
Python
538 lines
16 KiB
Python
# pragma pylint: disable=missing-docstring,W0212,C0103
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import os
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import signal
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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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import pytest
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from freqtrade.optimize.__init__ import load_tickerdata_file
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from freqtrade.optimize.hyperopt import Hyperopt, start
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from freqtrade.strategy.resolver import StrategyResolver
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from freqtrade.tests.conftest import log_has, patch_exchange
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from freqtrade.tests.optimize.test_backtesting import get_args
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# Avoid to reinit the same object again and again
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_HYPEROPT_INITIALIZED = False
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_HYPEROPT = None
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@pytest.fixture(scope='function')
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def init_hyperopt(default_conf, mocker):
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global _HYPEROPT_INITIALIZED, _HYPEROPT
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if not _HYPEROPT_INITIALIZED:
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patch_exchange(mocker)
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_HYPEROPT = Hyperopt(default_conf)
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_HYPEROPT_INITIALIZED = True
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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.path.getsize', return_value=1)
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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_start(mocker, default_conf, caplog) -> None:
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"""
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Test start() function
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"""
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start_mock = MagicMock()
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mocker.patch(
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'freqtrade.configuration.Configuration._load_config_file',
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lambda *args, **kwargs: default_conf
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)
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mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
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patch_exchange(mocker)
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args = [
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'--config', 'config.json',
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'--strategy', 'DefaultStrategy',
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'hyperopt',
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'--epochs', '5'
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]
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args = get_args(args)
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StrategyResolver({'strategy': 'DefaultStrategy'})
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start(args)
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import pprint
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pprint.pprint(caplog.record_tuples)
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assert log_has(
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'Starting freqtrade in Hyperopt mode',
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caplog.record_tuples
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)
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assert start_mock.call_count == 1
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def test_loss_calculation_prefer_correct_trade_count(init_hyperopt) -> 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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StrategyResolver({'strategy': 'DefaultStrategy'})
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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(init_hyperopt) -> 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(init_hyperopt) -> 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(init_hyperopt, capsys) -> 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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out, err = capsys.readouterr()
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assert ' 1/2: foo. Loss 1.00000'in out
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def test_no_log_if_loss_does_not_improve(init_hyperopt, 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, init_hyperopt, 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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patch_exchange(mocker)
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StrategyResolver({'strategy': 'DefaultStrategy'})
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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, init_hyperopt, 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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patch_exchange(mocker)
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StrategyResolver({'strategy': 'DefaultStrategy'})
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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, init_hyperopt, 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({'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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patch_exchange(mocker)
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StrategyResolver({'strategy': 'DefaultStrategy'})
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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, init_hyperopt, 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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trials_file = os.path.join('freqtrade', 'tests', 'optimize', 'ut_trials.pickle')
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assert log_has(
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'Saving Trials to \'{}\''.format(trials_file),
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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, init_hyperopt, 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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trials_file = os.path.join('freqtrade', 'tests', 'optimize', 'ut_trials.pickle')
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assert log_has(
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'Reading Trials from \'{}\''.format(trials_file),
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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(init_hyperopt) -> 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, init_hyperopt, 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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patch_exchange(mocker)
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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({'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_format_results(init_hyperopt):
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"""
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Test Hyperopt.format_results()
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"""
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# Test with BTC as stake_currency
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trades = [
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('ETH/BTC', 2, 2, 123),
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('LTC/BTC', 1, 1, 123),
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('XPR/BTC', -1, -2, -246)
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]
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labels = ['currency', 'profit_percent', 'profit_abs', 'trade_duration']
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df = pd.DataFrame.from_records(trades, columns=labels)
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result = _HYPEROPT.format_results(df)
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assert result.find(' 66.67%')
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assert result.find('Total profit 1.00000000 BTC')
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assert result.find('2.0000Σ %')
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# Test with EUR as stake_currency
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trades = [
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('ETH/EUR', 2, 2, 123),
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('LTC/EUR', 1, 1, 123),
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('XPR/EUR', -1, -2, -246)
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]
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df = pd.DataFrame.from_records(trades, columns=labels)
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result = _HYPEROPT.format_results(df)
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assert result.find('Total profit 1.00000000 EUR')
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def test_signal_handler(mocker, init_hyperopt):
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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(signal.SIGTERM, None)
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assert m.call_count == 3
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def test_has_space(init_hyperopt):
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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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def test_populate_indicators(init_hyperopt) -> None:
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"""
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Test Hyperopt.populate_indicators()
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"""
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tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m')
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tickerlist = {'UNITTEST/BTC': tick}
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dataframes = _HYPEROPT.tickerdata_to_dataframe(tickerlist)
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dataframe = _HYPEROPT.populate_indicators(dataframes['UNITTEST/BTC'])
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# Check if some indicators are generated. We will not test all of them
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assert 'adx' in dataframe
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assert 'ao' in dataframe
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assert 'cci' in dataframe
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def test_buy_strategy_generator(init_hyperopt) -> None:
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"""
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Test Hyperopt.buy_strategy_generator()
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"""
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tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m')
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tickerlist = {'UNITTEST/BTC': tick}
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dataframes = _HYPEROPT.tickerdata_to_dataframe(tickerlist)
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dataframe = _HYPEROPT.populate_indicators(dataframes['UNITTEST/BTC'])
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populate_buy_trend = _HYPEROPT.buy_strategy_generator(
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{
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'uptrend_long_ema': {
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'enabled': True
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},
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'macd_below_zero': {
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'enabled': True
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},
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'uptrend_short_ema': {
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'enabled': True
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},
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'mfi': {
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'enabled': True,
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'value': 20
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},
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'fastd': {
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'enabled': True,
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'value': 20
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},
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'adx': {
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'enabled': True,
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'value': 20
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},
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'rsi': {
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'enabled': True,
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'value': 20
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},
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'over_sar': {
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'enabled': True,
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},
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'green_candle': {
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'enabled': True,
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},
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'uptrend_sma': {
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'enabled': True,
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},
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'trigger': {
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'type': 'lower_bb'
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}
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}
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)
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result = populate_buy_trend(dataframe)
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# Check if some indicators are generated. We will not test all of them
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assert 'buy' in result
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assert 1 in result['buy']
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def test_generate_optimizer(mocker, init_hyperopt, default_conf) -> None:
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"""
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Test Hyperopt.generate_optimizer() function
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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({'timerange': None})
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conf.update({'spaces': 'all'})
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trades = [
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('POWR/BTC', 0.023117, 0.000233, 100)
|
|
]
|
|
labels = ['currency', 'profit_percent', 'profit_abs', 'trade_duration']
|
|
backtest_result = pd.DataFrame.from_records(trades, columns=labels)
|
|
|
|
mocker.patch(
|
|
'freqtrade.optimize.hyperopt.Hyperopt.backtest',
|
|
MagicMock(return_value=backtest_result)
|
|
)
|
|
patch_exchange(mocker)
|
|
|
|
optimizer_param = {
|
|
'adx': {'enabled': False},
|
|
'fastd': {'enabled': True, 'value': 35.0},
|
|
'green_candle': {'enabled': True},
|
|
'macd_below_zero': {'enabled': True},
|
|
'mfi': {'enabled': False},
|
|
'over_sar': {'enabled': False},
|
|
'roi_p1': 0.01,
|
|
'roi_p2': 0.01,
|
|
'roi_p3': 0.1,
|
|
'roi_t1': 60.0,
|
|
'roi_t2': 30.0,
|
|
'roi_t3': 20.0,
|
|
'rsi': {'enabled': False},
|
|
'stoploss': -0.4,
|
|
'trigger': {'type': 'macd_cross_signal'},
|
|
'uptrend_long_ema': {'enabled': False},
|
|
'uptrend_short_ema': {'enabled': True},
|
|
'uptrend_sma': {'enabled': True}
|
|
}
|
|
|
|
response_expected = {
|
|
'loss': 1.9840569076926293,
|
|
'result': ' 1 trades. Avg profit 2.31%. Total profit 0.00023300 BTC '
|
|
'(0.0231Σ%). Avg duration 100.0 mins.',
|
|
'status': 'ok'
|
|
}
|
|
|
|
hyperopt = Hyperopt(conf)
|
|
generate_optimizer_value = hyperopt.generate_optimizer(optimizer_param)
|
|
assert generate_optimizer_value == response_expected
|