907 lines
34 KiB
Python
907 lines
34 KiB
Python
# pragma pylint: disable=missing-docstring,W0212,C0103
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from datetime import datetime
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from pathlib import Path
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from unittest.mock import ANY, MagicMock
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import pandas as pd
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import pytest
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from arrow import Arrow
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from filelock import Timeout
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from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_hyperopt
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from freqtrade.data.history import load_data
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from freqtrade.enums import RunMode, SellType
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from freqtrade.exceptions import OperationalException
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from freqtrade.optimize.hyperopt import Hyperopt
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from freqtrade.optimize.hyperopt_auto import HyperOptAuto
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from freqtrade.optimize.hyperopt_tools import HyperoptTools
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from freqtrade.optimize.optimize_reports import generate_strategy_stats
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from freqtrade.optimize.space import SKDecimal
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from freqtrade.strategy.hyper import IntParameter
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from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
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patched_configuration_load_config_file)
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def test_setup_hyperopt_configuration_without_arguments(mocker, default_conf, caplog) -> None:
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patched_configuration_load_config_file(mocker, default_conf)
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args = [
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'hyperopt',
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'--config', 'config.json',
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'--strategy', 'HyperoptableStrategy',
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]
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config = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
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assert 'max_open_trades' in config
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assert 'stake_currency' in config
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assert 'stake_amount' in config
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assert 'exchange' in config
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assert 'pair_whitelist' in config['exchange']
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assert 'datadir' in config
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assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
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assert 'timeframe' in config
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assert not log_has_re('Parameter -i/--ticker-interval detected .*', caplog)
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assert 'position_stacking' not in config
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assert not log_has('Parameter --enable-position-stacking detected ...', caplog)
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assert 'timerange' not in config
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assert 'runmode' in config
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assert config['runmode'] == RunMode.HYPEROPT
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def test_setup_hyperopt_configuration_with_arguments(mocker, default_conf, caplog) -> None:
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patched_configuration_load_config_file(mocker, default_conf)
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mocker.patch(
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'freqtrade.configuration.configuration.create_datadir',
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lambda c, x: x
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)
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args = [
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'hyperopt',
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'--config', 'config.json',
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'--strategy', 'HyperoptableStrategy',
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'--datadir', '/foo/bar',
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'--timeframe', '1m',
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'--timerange', ':100',
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'--enable-position-stacking',
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'--disable-max-market-positions',
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'--epochs', '1000',
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'--spaces', 'default',
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'--print-all'
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]
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config = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
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assert 'max_open_trades' in config
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assert 'stake_currency' in config
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assert 'stake_amount' in config
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assert 'exchange' in config
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assert 'pair_whitelist' in config['exchange']
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assert 'datadir' in config
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assert config['runmode'] == RunMode.HYPEROPT
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assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
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assert 'timeframe' in config
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assert log_has('Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
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caplog)
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assert 'position_stacking' in config
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assert log_has('Parameter --enable-position-stacking detected ...', caplog)
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assert 'use_max_market_positions' in config
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assert log_has('Parameter --disable-max-market-positions detected ...', caplog)
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assert log_has('max_open_trades set to unlimited ...', caplog)
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assert 'timerange' in config
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assert log_has('Parameter --timerange detected: {} ...'.format(config['timerange']), caplog)
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assert 'epochs' in config
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assert log_has('Parameter --epochs detected ... Will run Hyperopt with for 1000 epochs ...',
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caplog)
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assert 'spaces' in config
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assert log_has('Parameter -s/--spaces detected: {}'.format(config['spaces']), caplog)
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assert 'print_all' in config
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assert log_has('Parameter --print-all detected ...', caplog)
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def test_setup_hyperopt_configuration_stake_amount(mocker, default_conf) -> None:
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patched_configuration_load_config_file(mocker, default_conf)
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args = [
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'hyperopt',
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'--config', 'config.json',
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'--strategy', 'HyperoptableStrategy',
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'--stake-amount', '1',
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'--starting-balance', '2'
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]
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conf = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
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assert isinstance(conf, dict)
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args = [
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'hyperopt',
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'--config', 'config.json',
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'--strategy', 'StrategyTestV2',
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'--stake-amount', '1',
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'--starting-balance', '0.5'
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]
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with pytest.raises(OperationalException, match=r"Starting balance .* smaller .*"):
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setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
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def test_start_not_installed(mocker, default_conf, import_fails) -> None:
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start_mock = MagicMock()
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patched_configuration_load_config_file(mocker, default_conf)
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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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'hyperopt',
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'--config', 'config.json',
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'--strategy', 'HyperoptableStrategy',
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'--epochs', '5',
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'--hyperopt-loss', 'SharpeHyperOptLossDaily',
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]
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pargs = get_args(args)
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with pytest.raises(OperationalException, match=r"Please ensure that the hyperopt dependencies"):
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start_hyperopt(pargs)
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def test_start_no_hyperopt_allowed(mocker, hyperopt_conf, caplog) -> None:
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start_mock = MagicMock()
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patched_configuration_load_config_file(mocker, hyperopt_conf)
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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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'hyperopt',
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'--config', 'config.json',
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'--hyperopt', 'HyperoptTestSepFile',
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'--hyperopt-loss', 'SharpeHyperOptLossDaily',
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'--epochs', '5'
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]
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pargs = get_args(args)
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with pytest.raises(OperationalException, match=r"Using separate Hyperopt files has been.*"):
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start_hyperopt(pargs)
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def test_start_no_data(mocker, hyperopt_conf) -> None:
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patched_configuration_load_config_file(mocker, hyperopt_conf)
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mocker.patch('freqtrade.data.history.load_pair_history', MagicMock(return_value=pd.DataFrame))
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mocker.patch(
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'freqtrade.optimize.hyperopt.get_timerange',
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MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
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)
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patch_exchange(mocker)
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# TODO: migrate to strategy-based hyperopt
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args = [
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'hyperopt',
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'--config', 'config.json',
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'--strategy', 'HyperoptableStrategy',
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'--hyperopt-loss', 'SharpeHyperOptLossDaily',
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'--epochs', '5'
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]
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pargs = get_args(args)
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with pytest.raises(OperationalException, match='No data found. Terminating.'):
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start_hyperopt(pargs)
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def test_start_filelock(mocker, hyperopt_conf, caplog) -> None:
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hyperopt_mock = MagicMock(side_effect=Timeout(Hyperopt.get_lock_filename(hyperopt_conf)))
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patched_configuration_load_config_file(mocker, hyperopt_conf)
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mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.__init__', hyperopt_mock)
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patch_exchange(mocker)
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args = [
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'hyperopt',
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'--config', 'config.json',
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'--strategy', 'HyperoptableStrategy',
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'--hyperopt-loss', 'SharpeHyperOptLossDaily',
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'--epochs', '5'
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]
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pargs = get_args(args)
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start_hyperopt(pargs)
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assert log_has("Another running instance of freqtrade Hyperopt detected.", caplog)
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def test_log_results_if_loss_improves(hyperopt, capsys) -> None:
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hyperopt.current_best_loss = 2
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hyperopt.total_epochs = 2
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hyperopt.print_results(
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{
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'loss': 1,
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'results_metrics':
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{
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'trade_count': 1,
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'avg_profit': 0.1,
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'total_profit': 0.001,
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'profit': 1.0,
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'duration': 20.0
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},
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'total_profit': 0,
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'current_epoch': 2, # This starts from 1 (in a human-friendly manner)
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'is_initial_point': False,
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'is_best': True
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}
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)
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out, err = capsys.readouterr()
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assert all(x in out
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for x in ["Best", "2/2", " 1", "0.10%", "0.00100000 BTC (1.00%)", "20.0 m"])
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def test_no_log_if_loss_does_not_improve(hyperopt, caplog) -> None:
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hyperopt.current_best_loss = 2
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hyperopt.print_results(
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{
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'is_best': False,
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'loss': 3,
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'current_epoch': 1,
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}
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)
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assert caplog.record_tuples == []
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def test_roi_table_generation(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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assert hyperopt.custom_hyperopt.generate_roi_table(params) == {0: 6, 15: 3, 25: 1, 30: 0}
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def test_params_no_optimize_details(hyperopt) -> None:
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hyperopt.config['spaces'] = ['buy']
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res = hyperopt._get_no_optimize_details()
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assert isinstance(res, dict)
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assert "trailing" in res
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assert res["trailing"]['trailing_stop'] is False
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assert "roi" in res
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assert res['roi']['0'] == 0.04
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assert "stoploss" in res
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assert res['stoploss']['stoploss'] == -0.1
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def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
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dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
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dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
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mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
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mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
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MagicMock(return_value=(MagicMock(), None)))
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mocker.patch(
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'freqtrade.optimize.hyperopt.get_timerange',
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MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
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)
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parallel = mocker.patch(
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'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
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MagicMock(return_value=[{
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'loss': 1, 'results_explanation': 'foo result',
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'params': {'buy': {}, 'sell': {}, 'roi': {}, 'stoploss': 0.0},
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'results_metrics':
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{
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'trade_count': 1,
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'avg_profit': 0.1,
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'total_profit': 0.001,
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'profit': 1.0,
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'duration': 20.0
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},
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}])
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)
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patch_exchange(mocker)
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# Co-test loading timeframe from strategy
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del hyperopt_conf['timeframe']
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hyperopt = Hyperopt(hyperopt_conf)
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hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
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hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
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hyperopt.start()
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parallel.assert_called_once()
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out, err = capsys.readouterr()
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assert 'Best result:\n\n* 1/1: foo result Objective: 1.00000\n' in out
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# Should be called for historical candle data
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assert dumper.call_count == 1
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assert dumper2.call_count == 1
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assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
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assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
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assert hasattr(hyperopt, "max_open_trades")
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assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
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assert hasattr(hyperopt, "position_stacking")
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def test_hyperopt_format_results(hyperopt):
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bt_result = {
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'results': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
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"UNITTEST/BTC", "UNITTEST/BTC"],
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"profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780],
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"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
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"open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
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Arrow(2017, 11, 14, 21, 36, 00).datetime,
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Arrow(2017, 11, 14, 22, 12, 00).datetime,
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Arrow(2017, 11, 14, 22, 44, 00).datetime],
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"close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
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Arrow(2017, 11, 14, 22, 10, 00).datetime,
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Arrow(2017, 11, 14, 22, 43, 00).datetime,
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Arrow(2017, 11, 14, 22, 58, 00).datetime],
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"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
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"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
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"trade_duration": [123, 34, 31, 14],
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"is_open": [False, False, False, True],
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"stake_amount": [0.01, 0.01, 0.01, 0.01],
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"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
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SellType.ROI, SellType.FORCE_SELL]
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}),
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'config': hyperopt.config,
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'locks': [],
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'final_balance': 0.02,
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'rejected_signals': 2,
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'backtest_start_time': 1619718665,
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'backtest_end_time': 1619718665,
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}
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results_metrics = generate_strategy_stats({'XRP/BTC': None}, '', bt_result,
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Arrow(2017, 11, 14, 19, 32, 00),
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Arrow(2017, 12, 14, 19, 32, 00), market_change=0)
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results_explanation = HyperoptTools.format_results_explanation_string(results_metrics, 'BTC')
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total_profit = results_metrics['profit_total_abs']
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results = {
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'loss': 0.0,
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'params_dict': None,
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'params_details': None,
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'results_metrics': results_metrics,
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'results_explanation': results_explanation,
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'total_profit': total_profit,
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'current_epoch': 1,
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'is_initial_point': True,
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}
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result = HyperoptTools._format_explanation_string(results, 1)
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assert ' 0.71%' in result
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assert 'Total profit 0.00003100 BTC' in result
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assert '0:50:00 min' in result
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def test_populate_indicators(hyperopt, testdatadir) -> None:
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data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], fill_up_missing=True)
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dataframes = hyperopt.backtesting.strategy.advise_all_indicators(data)
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dataframe = 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 'macd' in dataframe
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assert 'rsi' in dataframe
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def test_generate_optimizer(mocker, hyperopt_conf) -> None:
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hyperopt_conf.update({'spaces': 'all',
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'hyperopt_min_trades': 1,
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})
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backtest_result = {
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'results': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
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"UNITTEST/BTC", "UNITTEST/BTC"],
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"profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780],
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"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
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"open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
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Arrow(2017, 11, 14, 21, 36, 00).datetime,
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Arrow(2017, 11, 14, 22, 12, 00).datetime,
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Arrow(2017, 11, 14, 22, 44, 00).datetime],
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"close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
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Arrow(2017, 11, 14, 22, 10, 00).datetime,
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Arrow(2017, 11, 14, 22, 43, 00).datetime,
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Arrow(2017, 11, 14, 22, 58, 00).datetime],
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"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
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"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
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"trade_duration": [123, 34, 31, 14],
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"is_open": [False, False, False, True],
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"stake_amount": [0.01, 0.01, 0.01, 0.01],
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"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
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SellType.ROI, SellType.FORCE_SELL]
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}),
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'config': hyperopt_conf,
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'locks': [],
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'rejected_signals': 20,
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'final_balance': 1000,
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}
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mocker.patch('freqtrade.optimize.hyperopt.Backtesting.backtest', return_value=backtest_result)
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mocker.patch('freqtrade.optimize.hyperopt.get_timerange',
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return_value=(Arrow(2017, 12, 10), Arrow(2017, 12, 13)))
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patch_exchange(mocker)
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mocker.patch.object(Path, 'open')
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mocker.patch('freqtrade.optimize.hyperopt.load', return_value={'XRP/BTC': None})
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optimizer_param = {
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'buy_plusdi': 0.02,
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'buy_rsi': 35,
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'sell_minusdi': 0.02,
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'sell_rsi': 75,
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'protection_cooldown_lookback': 20,
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'protection_enabled': True,
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'roi_t1': 60.0,
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'roi_t2': 30.0,
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'roi_t3': 20.0,
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'roi_p1': 0.01,
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'roi_p2': 0.01,
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'roi_p3': 0.1,
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'stoploss': -0.4,
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'trailing_stop': True,
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'trailing_stop_positive': 0.02,
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'trailing_stop_positive_offset_p1': 0.05,
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'trailing_only_offset_is_reached': False,
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}
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response_expected = {
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'loss': 1.9147239021396234,
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'results_explanation': (' 4 trades. 4/0/0 Wins/Draws/Losses. '
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'Avg profit 0.77%. Median profit 0.71%. Total profit '
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'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_sell")
|
|
assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
|
|
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) -> 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.start()
|
|
|
|
|
|
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_sell")
|
|
assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
|
|
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_sell")
|
|
assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
|
|
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]
|