stable/tests/optimize/test_hyperopt.py

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# pragma pylint: disable=missing-docstring,W0212,C0103
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from datetime import datetime, timedelta
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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
import pytest
from arrow import Arrow
from filelock import Timeout
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from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_hyperopt
from freqtrade.data.history import load_data
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from freqtrade.enums import ExitType, RunMode
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
from freqtrade.optimize.hyperopt_tools import HyperoptTools
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from freqtrade.optimize.optimize_reports import generate_strategy_stats
from freqtrade.optimize.space import SKDecimal
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from freqtrade.strategy.hyper import IntParameter
from tests.conftest import (CURRENT_TEST_STRATEGY, get_args, log_has, log_has_re, patch_exchange,
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patched_configuration_load_config_file)
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def generate_result_metrics():
return {
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'trade_count': 1,
'total_trades': 1,
'avg_profit': 0.1,
'total_profit': 0.001,
'profit': 0.01,
'duration': 20.0,
'wins': 1,
'draws': 0,
'losses': 0,
'profit_mean': 0.01,
'profit_total_abs': 0.001,
'profit_total': 0.01,
'holding_avg': timedelta(minutes=20),
'max_drawdown': 0.001,
'max_drawdown_abs': 0.001,
'loss': 0.001,
'is_initial_point': 0.001,
'is_random': False,
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'is_best': 1,
}
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def test_setup_hyperopt_configuration_without_arguments(mocker, default_conf, caplog) -> None:
patched_configuration_load_config_file(mocker, default_conf)
args = [
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'hyperopt',
'--config', 'config.json',
'--strategy', 'HyperoptableStrategy',
]
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config = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
assert 'max_open_trades' in config
assert 'stake_currency' in config
assert 'stake_amount' in config
assert 'exchange' in config
assert 'pair_whitelist' in config['exchange']
assert 'datadir' in config
assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
assert 'timeframe' in config
assert 'position_stacking' not in config
assert not log_has('Parameter --enable-position-stacking detected ...', caplog)
assert 'timerange' not in config
assert 'runmode' in config
assert config['runmode'] == RunMode.HYPEROPT
def test_setup_hyperopt_configuration_with_arguments(mocker, default_conf, caplog) -> None:
patched_configuration_load_config_file(mocker, default_conf)
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mocker.patch(
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'freqtrade.configuration.configuration.create_datadir',
lambda c, x: x
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)
args = [
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'hyperopt',
'--config', 'config.json',
'--strategy', 'HyperoptableStrategy',
'--datadir', '/foo/bar',
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'--timeframe', '1m',
'--timerange', ':100',
'--enable-position-stacking',
'--disable-max-market-positions',
'--epochs', '1000',
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'--spaces', 'default',
'--print-all'
]
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config = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
assert 'max_open_trades' in config
assert 'stake_currency' in config
assert 'stake_amount' in config
assert 'exchange' in config
assert 'pair_whitelist' in config['exchange']
assert 'datadir' in config
assert config['runmode'] == RunMode.HYPEROPT
assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
assert 'timeframe' in config
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assert log_has('Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
caplog)
assert 'position_stacking' in config
assert log_has('Parameter --enable-position-stacking detected ...', caplog)
assert 'use_max_market_positions' in config
assert log_has('Parameter --disable-max-market-positions detected ...', caplog)
assert log_has('max_open_trades set to unlimited ...', caplog)
assert 'timerange' in config
assert log_has('Parameter --timerange detected: {} ...'.format(config['timerange']), caplog)
assert 'epochs' in config
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assert log_has('Parameter --epochs detected ... Will run Hyperopt with for 1000 epochs ...',
caplog)
assert 'spaces' in config
assert log_has('Parameter -s/--spaces detected: {}'.format(config['spaces']), caplog)
assert 'print_all' in config
assert log_has('Parameter --print-all detected ...', caplog)
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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)
args = [
'hyperopt',
'--config', 'config.json',
'--strategy', 'HyperoptableStrategy',
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'--stake-amount', '1',
'--starting-balance', '2'
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]
conf = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
assert isinstance(conf, dict)
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args = [
'hyperopt',
'--config', 'config.json',
'--strategy', CURRENT_TEST_STRATEGY,
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'--stake-amount', '1',
'--starting-balance', '0.5'
]
with pytest.raises(OperationalException, match=r"Starting balance .* smaller .*"):
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()
patched_configuration_load_config_file(mocker, default_conf)
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
patch_exchange(mocker)
args = [
'hyperopt',
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'--config', 'config.json',
'--strategy', 'HyperoptableStrategy',
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'--epochs', '5',
'--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()
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 = [
'hyperopt',
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'--config', 'config.json',
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'--hyperopt', 'HyperoptTestSepFile',
'--hyperopt-loss', 'SharpeHyperOptLossDaily',
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'--epochs', '5'
]
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pargs = get_args(args)
with pytest.raises(OperationalException, match=r"Using separate Hyperopt files has been.*"):
start_hyperopt(pargs)
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def test_start_no_data(mocker, hyperopt_conf, tmpdir) -> None:
hyperopt_conf['user_data_dir'] = Path(tmpdir)
patched_configuration_load_config_file(mocker, hyperopt_conf)
mocker.patch('freqtrade.data.history.load_pair_history', MagicMock(return_value=pd.DataFrame))
mocker.patch(
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'freqtrade.optimize.hyperopt.get_timerange',
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
)
patch_exchange(mocker)
args = [
'hyperopt',
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'--config', 'config.json',
'--strategy', 'HyperoptableStrategy',
'--hyperopt-loss', 'SharpeHyperOptLossDaily',
'--epochs', '5'
]
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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)
# Cleanup since that failed hyperopt start leaves a lockfile.
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try:
Path(Hyperopt.get_lock_filename(hyperopt_conf)).unlink()
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except Exception:
pass
def test_start_filelock(mocker, hyperopt_conf, caplog) -> None:
hyperopt_mock = MagicMock(side_effect=Timeout(Hyperopt.get_lock_filename(hyperopt_conf)))
patched_configuration_load_config_file(mocker, hyperopt_conf)
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.__init__', hyperopt_mock)
patch_exchange(mocker)
args = [
'hyperopt',
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'--config', 'config.json',
'--strategy', 'HyperoptableStrategy',
'--hyperopt-loss', 'SharpeHyperOptLossDaily',
'--epochs', '5'
]
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pargs = get_args(args)
start_hyperopt(pargs)
assert log_has("Another running instance of freqtrade Hyperopt detected.", caplog)
def test_log_results_if_loss_improves(hyperopt, capsys) -> None:
hyperopt.current_best_loss = 2
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hyperopt.total_epochs = 2
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hyperopt.print_results(
{
'loss': 1,
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'results_metrics': generate_result_metrics(),
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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,
'is_random': False,
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'is_best': True
}
)
out, err = capsys.readouterr()
assert all(x in out
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for x in ["Best", "2/2", " 1", "0.10%", "0.00100000 BTC (1.00%)", "00:20:00"])
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def test_no_log_if_loss_does_not_improve(hyperopt, caplog) -> None:
hyperopt.current_best_loss = 2
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hyperopt.print_results(
{
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'is_best': False,
'loss': 3,
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'current_epoch': 1,
}
)
assert caplog.record_tuples == []
def test_roi_table_generation(hyperopt) -> None:
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params = {
'roi_t1': 5,
'roi_t2': 10,
'roi_t3': 15,
'roi_p1': 1,
'roi_p2': 2,
'roi_p3': 3,
}
assert hyperopt.custom_hyperopt.generate_roi_table(params) == {0: 6, 15: 3, 25: 1, 30: 0}
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def test_params_no_optimize_details(hyperopt) -> None:
hyperopt.config['spaces'] = ['buy']
res = hyperopt._get_no_optimize_details()
assert isinstance(res, dict)
assert "trailing" in res
assert res["trailing"]['trailing_stop'] is False
assert "roi" in res
assert res['roi']['0'] == 0.04
assert "stoploss" in res
assert res['stoploss']['stoploss'] == -0.1
def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
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dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
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',
MagicMock(return_value=(MagicMock(), None)))
mocker.patch(
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'freqtrade.optimize.hyperopt.get_timerange',
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
)
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parallel = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
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MagicMock(return_value=[{
'loss': 1, 'results_explanation': 'foo result',
'params': {'buy': {}, 'sell': {}, 'roi': {}, 'stoploss': 0.0},
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'results_metrics': generate_result_metrics(),
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}])
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)
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patch_exchange(mocker)
# Co-test loading timeframe from strategy
del hyperopt_conf['timeframe']
hyperopt = Hyperopt(hyperopt_conf)
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
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hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
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
assert dumper.call_count == 1
assert dumper2.call_count == 1
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assert hasattr(hyperopt.backtesting.strategy, "advise_exit")
assert hasattr(hyperopt.backtesting.strategy, "advise_entry")
assert hasattr(hyperopt, "max_open_trades")
assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
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assert hasattr(hyperopt, "position_stacking")
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def test_hyperopt_format_results(hyperopt):
bt_result = {
'results': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC", "UNITTEST/BTC"],
"profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
"open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime],
"close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"trade_duration": [123, 34, 31, 14],
"is_open": [False, False, False, True],
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"is_short": [False, False, False, False],
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"stake_amount": [0.01, 0.01, 0.01, 0.01],
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"exit_reason": [ExitType.ROI, ExitType.STOP_LOSS,
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ExitType.ROI, ExitType.FORCE_EXIT]
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}),
'config': hyperopt.config,
'locks': [],
'final_balance': 0.02,
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'rejected_signals': 2,
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'timedout_entry_orders': 0,
'timedout_exit_orders': 0,
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'backtest_start_time': 1619718665,
'backtest_end_time': 1619718665,
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}
results_metrics = generate_strategy_stats(['XRP/BTC'], '', bt_result,
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Arrow(2017, 11, 14, 19, 32, 00),
Arrow(2017, 12, 14, 19, 32, 00), market_change=0)
results_explanation = HyperoptTools.format_results_explanation_string(results_metrics, 'BTC')
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total_profit = results_metrics['profit_total_abs']
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results = {
'loss': 0.0,
'params_dict': None,
'params_details': None,
'results_metrics': results_metrics,
'results_explanation': results_explanation,
'total_profit': total_profit,
'current_epoch': 1,
'is_initial_point': True,
}
result = HyperoptTools._format_explanation_string(results, 1)
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assert ' 0.71%' in result
assert 'Total profit 0.00003100 BTC' in result
assert '0:50:00 min' in result
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def test_populate_indicators(hyperopt, testdatadir) -> None:
data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], fill_up_missing=True)
dataframes = hyperopt.backtesting.strategy.advise_all_indicators(data)
dataframe = dataframes['UNITTEST/BTC']
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# Check if some indicators are generated. We will not test all of them
assert 'adx' in dataframe
assert 'macd' in dataframe
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assert 'rsi' in dataframe
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def test_generate_optimizer(mocker, hyperopt_conf) -> None:
hyperopt_conf.update({'spaces': 'all',
'hyperopt_min_trades': 1,
})
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backtest_result = {
'results': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC", "UNITTEST/BTC"],
"profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
"open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime],
"close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"trade_duration": [123, 34, 31, 14],
"is_open": [False, False, False, True],
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"is_short": [False, False, False, False],
"stake_amount": [0.01, 0.01, 0.01, 0.01],
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"exit_reason": [ExitType.ROI, ExitType.STOP_LOSS,
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ExitType.ROI, ExitType.FORCE_EXIT]
}),
'config': hyperopt_conf,
'locks': [],
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'rejected_signals': 20,
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'timedout_entry_orders': 0,
'timedout_exit_orders': 0,
'final_balance': 1000,
}
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mocker.patch('freqtrade.optimize.hyperopt.Backtesting.backtest', return_value=backtest_result)
mocker.patch('freqtrade.optimize.hyperopt.get_timerange',
return_value=(Arrow(2017, 12, 10), Arrow(2017, 12, 13)))
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patch_exchange(mocker)
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mocker.patch.object(Path, 'open')
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mocker.patch('freqtrade.configuration.config_validation.validate_config_schema')
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mocker.patch('freqtrade.optimize.hyperopt.load', return_value={'XRP/BTC': None})
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optimizer_param = {
'buy_plusdi': 0.02,
'buy_rsi': 35,
'sell_minusdi': 0.02,
'sell_rsi': 75,
'protection_cooldown_lookback': 20,
'protection_enabled': True,
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'roi_t1': 60.0,
'roi_t2': 30.0,
'roi_t3': 20.0,
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'roi_p1': 0.01,
'roi_p2': 0.01,
'roi_p3': 0.1,
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'stoploss': -0.4,
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'trailing_stop': True,
'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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}
response_expected = {
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'loss': 1.9147239021396234,
'results_explanation': (' 4 trades. 4/0/0 Wins/Draws/Losses. '
'Avg profit 0.77%. Median profit 0.71%. Total profit '
'0.00003100 BTC ( 0.00%). '
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'Avg duration 0:50:00 min.'
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),
'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,
},
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'stoploss': {'stoploss': -0.4},
'trailing': {'trailing_only_offset_is_reached': False,
'trailing_stop': True,
'trailing_stop_positive': 0.02,
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'trailing_stop_positive_offset': 0.07}},
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'params_dict': optimizer_param,
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'params_not_optimized': {'buy': {}, 'protection': {}, 'sell': {}},
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'results_metrics': ANY,
'total_profit': 3.1e-08
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}
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
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generate_optimizer_value = hyperopt.generate_optimizer(list(optimizer_param.values()))
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assert generate_optimizer_value == response_expected
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def test_clean_hyperopt(mocker, hyperopt_conf, caplog):
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patch_exchange(mocker)
mocker.patch("freqtrade.strategy.hyper.HyperStrategyMixin.load_params_from_file",
MagicMock(return_value={}))
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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)
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assert unlinkmock.call_count == 2
assert log_has(f"Removing `{h.data_pickle_file}`.", caplog)
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def test_print_json_spaces_all(mocker, hyperopt_conf, capsys) -> None:
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dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
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',
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)))
)
parallel = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
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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}
},
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'results_metrics': generate_result_metrics(),
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}])
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)
patch_exchange(mocker)
hyperopt_conf.update({'spaces': 'all',
'hyperopt_jobs': 1,
'print_json': True,
})
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hyperopt = Hyperopt(hyperopt_conf)
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
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hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
hyperopt.start()
parallel.assert_called_once()
out, err = capsys.readouterr()
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result_str = (
'{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi"'
':{},"stoploss":null,"trailing_stop":null}'
)
assert result_str in out # noqa: E501
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# Should be called for historical candle data
assert dumper.call_count == 1
assert dumper2.call_count == 1
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def test_print_json_spaces_default(mocker, hyperopt_conf, capsys) -> None:
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dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
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',
MagicMock(return_value=(MagicMock(), None)))
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)))
)
parallel = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
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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}
},
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'results_metrics': generate_result_metrics(),
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}])
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)
patch_exchange(mocker)
hyperopt_conf.update({'print_json': True})
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hyperopt = Hyperopt(hyperopt_conf)
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
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hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
hyperopt.start()
parallel.assert_called_once()
out, err = capsys.readouterr()
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assert '{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi":{},"stoploss":null}' in out # noqa: E501
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# Should be called for historical candle data
assert dumper.call_count == 1
assert dumper2.call_count == 1
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def test_print_json_spaces_roi_stoploss(mocker, hyperopt_conf, capsys) -> None:
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dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
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',
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)))
)
parallel = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
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MagicMock(return_value=[{
'loss': 1, 'results_explanation': 'foo result', 'params': {},
'params_details': {'roi': {}, 'stoploss': {'stoploss': None}},
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'results_metrics': generate_result_metrics(),
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}])
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)
patch_exchange(mocker)
hyperopt_conf.update({'spaces': 'roi stoploss',
'hyperopt_jobs': 1,
'print_json': True,
})
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hyperopt = Hyperopt(hyperopt_conf)
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
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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
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assert dumper.call_count == 1
assert dumper2.call_count == 1
def test_simplified_interface_roi_stoploss(mocker, hyperopt_conf, capsys) -> None:
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dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
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',
MagicMock(return_value=(MagicMock(), None)))
mocker.patch(
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'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=[{
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'loss': 1, 'results_explanation': 'foo result', 'params': {'stoploss': 0.0},
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'results_metrics': generate_result_metrics(),
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}])
)
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
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assert dumper.call_count == 1
assert dumper2.call_count == 1
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assert hasattr(hyperopt.backtesting.strategy, "advise_exit")
assert hasattr(hyperopt.backtesting.strategy, "advise_entry")
assert hasattr(hyperopt, "max_open_trades")
assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
assert hasattr(hyperopt, "position_stacking")
def test_simplified_interface_all_failed(mocker, hyperopt_conf, caplog) -> None:
mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
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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',
MagicMock(return_value=(MagicMock(), None)))
mocker.patch(
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'freqtrade.optimize.hyperopt.get_timerange',
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
)
patch_exchange(mocker)
hyperopt_conf.update({'spaces': 'all', })
mocker.patch('freqtrade.optimize.hyperopt_auto.HyperOptAuto._generate_indicator_space',
return_value=[])
hyperopt = Hyperopt(hyperopt_conf)
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
with pytest.raises(OperationalException, match=r"The 'protection' space is included into *"):
hyperopt.init_spaces()
hyperopt.config['hyperopt_ignore_missing_space'] = True
caplog.clear()
hyperopt.init_spaces()
assert log_has_re(r"The 'protection' space is included into *", caplog)
assert hyperopt.protection_space == []
def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
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dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
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',
MagicMock(return_value=(MagicMock(), None)))
mocker.patch(
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'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',
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MagicMock(return_value=[{
'loss': 1, 'results_explanation': 'foo result', 'params': {},
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'results_metrics': generate_result_metrics(),
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}])
)
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
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assert dumper.call_count == 1
assert dumper2.call_count == 1
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assert hasattr(hyperopt.backtesting.strategy, "advise_exit")
assert hasattr(hyperopt.backtesting.strategy, "advise_entry")
assert hasattr(hyperopt, "max_open_trades")
assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
assert hasattr(hyperopt, "position_stacking")
def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None:
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dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
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',
MagicMock(return_value=(MagicMock(), None)))
mocker.patch(
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'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',
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MagicMock(return_value=[{
'loss': 1, 'results_explanation': 'foo result', 'params': {},
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'results_metrics': generate_result_metrics(),
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}])
)
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
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assert dumper.call_count == 1
assert dumper2.call_count == 1
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assert hasattr(hyperopt.backtesting.strategy, "advise_exit")
assert hasattr(hyperopt.backtesting.strategy, "advise_entry")
assert hasattr(hyperopt, "max_open_trades")
assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
assert hasattr(hyperopt, "position_stacking")
@pytest.mark.parametrize("space", [
('buy'),
('sell'),
('protection'),
])
def test_simplified_interface_failed(mocker, hyperopt_conf, space) -> None:
mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
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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',
MagicMock(return_value=(MagicMock(), None)))
mocker.patch(
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'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)
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(Path(tmpdir) / 'hyperopt_results').mkdir(parents=True)
# No hyperopt needed
hyperopt_conf.update({
'strategy': 'HyperoptableStrategy',
'user_data_dir': Path(tmpdir),
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'hyperopt_random_state': 42,
'spaces': ['all']
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})
hyperopt = Hyperopt(hyperopt_conf)
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hyperopt.backtesting.exchange.get_max_leverage = MagicMock(return_value=1.0)
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assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto)
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assert isinstance(hyperopt.backtesting.strategy.buy_rsi, IntParameter)
assert hyperopt.backtesting.strategy.buy_rsi.in_space is True
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assert hyperopt.backtesting.strategy.buy_rsi.value == 35
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assert hyperopt.backtesting.strategy.sell_rsi.value == 74
assert hyperopt.backtesting.strategy.protection_cooldown_lookback.value == 30
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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
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hyperopt.start()
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# 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
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hyperopt.custom_hyperopt.generate_estimator = lambda *args, **kwargs: 'ET1'
with pytest.raises(OperationalException, match="Estimator ET1 not supported."):
hyperopt.get_optimizer([], 2)
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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]