349 lines
11 KiB
Python
349 lines
11 KiB
Python
# pragma pylint: disable=missing-docstring,W0212,C0103
|
|
import os
|
|
from copy import deepcopy
|
|
from unittest.mock import MagicMock
|
|
|
|
import pandas as pd
|
|
import pytest
|
|
|
|
from freqtrade.optimize.__init__ import load_tickerdata_file
|
|
from freqtrade.optimize.hyperopt import Hyperopt, start
|
|
from freqtrade.strategy.resolver import StrategyResolver
|
|
from freqtrade.tests.conftest import log_has, patch_exchange
|
|
from freqtrade.tests.optimize.test_backtesting import get_args
|
|
|
|
# Avoid to reinit the same object again and again
|
|
_HYPEROPT_INITIALIZED = False
|
|
_HYPEROPT = None
|
|
|
|
|
|
@pytest.fixture(scope='function')
|
|
def init_hyperopt(default_conf, mocker):
|
|
global _HYPEROPT_INITIALIZED, _HYPEROPT
|
|
if not _HYPEROPT_INITIALIZED:
|
|
patch_exchange(mocker)
|
|
_HYPEROPT = Hyperopt(default_conf)
|
|
_HYPEROPT_INITIALIZED = True
|
|
|
|
|
|
# Functions for recurrent object patching
|
|
def create_trials(mocker) -> None:
|
|
"""
|
|
When creating trials, mock the hyperopt Trials so that *by default*
|
|
- we don't create any pickle'd files in the filesystem
|
|
- we might have a pickle'd file so make sure that we return
|
|
false when looking for it
|
|
"""
|
|
_HYPEROPT.trials_file = os.path.join('freqtrade', 'tests', 'optimize', 'ut_trials.pickle')
|
|
|
|
mocker.patch('freqtrade.optimize.hyperopt.os.path.exists', return_value=False)
|
|
mocker.patch('freqtrade.optimize.hyperopt.os.path.getsize', return_value=1)
|
|
mocker.patch('freqtrade.optimize.hyperopt.os.remove', return_value=True)
|
|
mocker.patch('freqtrade.optimize.hyperopt.pickle.dump', return_value=None)
|
|
|
|
return [{'loss': 1, 'result': 'foo', 'params': {}}]
|
|
|
|
|
|
def test_start(mocker, default_conf, caplog) -> None:
|
|
"""
|
|
Test start() function
|
|
"""
|
|
start_mock = MagicMock()
|
|
mocker.patch(
|
|
'freqtrade.configuration.Configuration._load_config_file',
|
|
lambda *args, **kwargs: default_conf
|
|
)
|
|
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
|
|
patch_exchange(mocker)
|
|
|
|
args = [
|
|
'--config', 'config.json',
|
|
'--strategy', 'DefaultStrategy',
|
|
'hyperopt',
|
|
'--epochs', '5'
|
|
]
|
|
args = get_args(args)
|
|
StrategyResolver({'strategy': 'DefaultStrategy'})
|
|
start(args)
|
|
|
|
import pprint
|
|
pprint.pprint(caplog.record_tuples)
|
|
|
|
assert log_has(
|
|
'Starting freqtrade in Hyperopt mode',
|
|
caplog.record_tuples
|
|
)
|
|
assert start_mock.call_count == 1
|
|
|
|
|
|
def test_loss_calculation_prefer_correct_trade_count(init_hyperopt) -> None:
|
|
"""
|
|
Test Hyperopt.calculate_loss()
|
|
"""
|
|
hyperopt = _HYPEROPT
|
|
StrategyResolver({'strategy': 'DefaultStrategy'})
|
|
|
|
correct = hyperopt.calculate_loss(1, hyperopt.target_trades, 20)
|
|
over = hyperopt.calculate_loss(1, hyperopt.target_trades + 100, 20)
|
|
under = hyperopt.calculate_loss(1, hyperopt.target_trades - 100, 20)
|
|
assert over > correct
|
|
assert under > correct
|
|
|
|
|
|
def test_loss_calculation_prefer_shorter_trades(init_hyperopt) -> None:
|
|
"""
|
|
Test Hyperopt.calculate_loss()
|
|
"""
|
|
hyperopt = _HYPEROPT
|
|
|
|
shorter = hyperopt.calculate_loss(1, 100, 20)
|
|
longer = hyperopt.calculate_loss(1, 100, 30)
|
|
assert shorter < longer
|
|
|
|
|
|
def test_loss_calculation_has_limited_profit(init_hyperopt) -> None:
|
|
hyperopt = _HYPEROPT
|
|
|
|
correct = hyperopt.calculate_loss(hyperopt.expected_max_profit, hyperopt.target_trades, 20)
|
|
over = hyperopt.calculate_loss(hyperopt.expected_max_profit * 2, hyperopt.target_trades, 20)
|
|
under = hyperopt.calculate_loss(hyperopt.expected_max_profit / 2, hyperopt.target_trades, 20)
|
|
assert over == correct
|
|
assert under > correct
|
|
|
|
|
|
def test_log_results_if_loss_improves(init_hyperopt, capsys) -> None:
|
|
hyperopt = _HYPEROPT
|
|
hyperopt.current_best_loss = 2
|
|
hyperopt.log_results(
|
|
{
|
|
'loss': 1,
|
|
'current_tries': 1,
|
|
'total_tries': 2,
|
|
'result': 'foo'
|
|
}
|
|
)
|
|
out, err = capsys.readouterr()
|
|
assert ' 1/2: foo. Loss 1.00000'in out
|
|
|
|
|
|
def test_no_log_if_loss_does_not_improve(init_hyperopt, caplog) -> None:
|
|
hyperopt = _HYPEROPT
|
|
hyperopt.current_best_loss = 2
|
|
hyperopt.log_results(
|
|
{
|
|
'loss': 3,
|
|
}
|
|
)
|
|
assert caplog.record_tuples == []
|
|
|
|
|
|
def test_save_trials_saves_trials(mocker, init_hyperopt, caplog) -> None:
|
|
trials = create_trials(mocker)
|
|
mock_dump = mocker.patch('freqtrade.optimize.hyperopt.pickle.dump', return_value=None)
|
|
|
|
hyperopt = _HYPEROPT
|
|
mocker.patch('freqtrade.optimize.hyperopt.open', return_value=hyperopt.trials_file)
|
|
_HYPEROPT.trials = trials
|
|
|
|
hyperopt.save_trials()
|
|
|
|
trials_file = os.path.join('freqtrade', 'tests', 'optimize', 'ut_trials.pickle')
|
|
assert log_has(
|
|
'Saving 1 evaluations to \'{}\''.format(trials_file),
|
|
caplog.record_tuples
|
|
)
|
|
mock_dump.assert_called_once()
|
|
|
|
|
|
def test_read_trials_returns_trials_file(mocker, init_hyperopt, caplog) -> None:
|
|
trials = create_trials(mocker)
|
|
mock_load = mocker.patch('freqtrade.optimize.hyperopt.pickle.load', return_value=trials)
|
|
mock_open = mocker.patch('freqtrade.optimize.hyperopt.open', return_value=mock_load)
|
|
|
|
hyperopt = _HYPEROPT
|
|
hyperopt_trial = hyperopt.read_trials()
|
|
trials_file = os.path.join('freqtrade', 'tests', 'optimize', 'ut_trials.pickle')
|
|
assert log_has(
|
|
'Reading Trials from \'{}\''.format(trials_file),
|
|
caplog.record_tuples
|
|
)
|
|
assert hyperopt_trial == trials
|
|
mock_open.assert_called_once()
|
|
mock_load.assert_called_once()
|
|
|
|
|
|
def test_roi_table_generation(init_hyperopt) -> None:
|
|
params = {
|
|
'roi_t1': 5,
|
|
'roi_t2': 10,
|
|
'roi_t3': 15,
|
|
'roi_p1': 1,
|
|
'roi_p2': 2,
|
|
'roi_p3': 3,
|
|
}
|
|
|
|
hyperopt = _HYPEROPT
|
|
assert hyperopt.generate_roi_table(params) == {0: 6, 15: 3, 25: 1, 30: 0}
|
|
|
|
|
|
def test_start_calls_optimizer(mocker, init_hyperopt, default_conf, caplog) -> None:
|
|
mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
|
|
mocker.patch('freqtrade.optimize.hyperopt.multiprocessing.cpu_count', MagicMock(return_value=1))
|
|
parallel = mocker.patch(
|
|
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
|
|
MagicMock(return_value=[{'loss': 1, 'result': 'foo result', 'params': {}}])
|
|
)
|
|
patch_exchange(mocker)
|
|
|
|
conf = deepcopy(default_conf)
|
|
conf.update({'config': 'config.json.example'})
|
|
conf.update({'epochs': 1})
|
|
conf.update({'timerange': None})
|
|
conf.update({'spaces': 'all'})
|
|
|
|
hyperopt = Hyperopt(conf)
|
|
hyperopt.tickerdata_to_dataframe = MagicMock()
|
|
|
|
hyperopt.start()
|
|
parallel.assert_called_once()
|
|
|
|
assert 'Best result:\nfoo result\nwith values:\n{}' in caplog.text
|
|
|
|
|
|
def test_format_results(init_hyperopt):
|
|
"""
|
|
Test Hyperopt.format_results()
|
|
"""
|
|
|
|
# Test with BTC as stake_currency
|
|
trades = [
|
|
('ETH/BTC', 2, 2, 123),
|
|
('LTC/BTC', 1, 1, 123),
|
|
('XPR/BTC', -1, -2, -246)
|
|
]
|
|
labels = ['currency', 'profit_percent', 'profit_abs', 'trade_duration']
|
|
df = pd.DataFrame.from_records(trades, columns=labels)
|
|
|
|
result = _HYPEROPT.format_results(df)
|
|
assert result.find(' 66.67%')
|
|
assert result.find('Total profit 1.00000000 BTC')
|
|
assert result.find('2.0000Σ %')
|
|
|
|
# Test with EUR as stake_currency
|
|
trades = [
|
|
('ETH/EUR', 2, 2, 123),
|
|
('LTC/EUR', 1, 1, 123),
|
|
('XPR/EUR', -1, -2, -246)
|
|
]
|
|
df = pd.DataFrame.from_records(trades, columns=labels)
|
|
result = _HYPEROPT.format_results(df)
|
|
assert result.find('Total profit 1.00000000 EUR')
|
|
|
|
|
|
def test_has_space(init_hyperopt):
|
|
"""
|
|
Test Hyperopt.has_space() method
|
|
"""
|
|
_HYPEROPT.config.update({'spaces': ['buy', 'roi']})
|
|
assert _HYPEROPT.has_space('roi')
|
|
assert _HYPEROPT.has_space('buy')
|
|
assert not _HYPEROPT.has_space('stoploss')
|
|
|
|
_HYPEROPT.config.update({'spaces': ['all']})
|
|
assert _HYPEROPT.has_space('buy')
|
|
|
|
|
|
def test_populate_indicators(init_hyperopt) -> None:
|
|
"""
|
|
Test Hyperopt.populate_indicators()
|
|
"""
|
|
tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m')
|
|
tickerlist = {'UNITTEST/BTC': tick}
|
|
dataframes = _HYPEROPT.tickerdata_to_dataframe(tickerlist)
|
|
dataframe = _HYPEROPT.populate_indicators(dataframes['UNITTEST/BTC'])
|
|
|
|
# Check if some indicators are generated. We will not test all of them
|
|
assert 'adx' in dataframe
|
|
assert 'mfi' in dataframe
|
|
assert 'rsi' in dataframe
|
|
|
|
|
|
def test_buy_strategy_generator(init_hyperopt) -> None:
|
|
"""
|
|
Test Hyperopt.buy_strategy_generator()
|
|
"""
|
|
tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m')
|
|
tickerlist = {'UNITTEST/BTC': tick}
|
|
dataframes = _HYPEROPT.tickerdata_to_dataframe(tickerlist)
|
|
dataframe = _HYPEROPT.populate_indicators(dataframes['UNITTEST/BTC'])
|
|
|
|
populate_buy_trend = _HYPEROPT.buy_strategy_generator(
|
|
{
|
|
'adx-value': 20,
|
|
'fastd-value': 20,
|
|
'mfi-value': 20,
|
|
'rsi-value': 20,
|
|
'adx-enabled': True,
|
|
'fastd-enabled': True,
|
|
'mfi-enabled': True,
|
|
'rsi-enabled': True,
|
|
'trigger': 'bb_lower'
|
|
}
|
|
)
|
|
result = populate_buy_trend(dataframe)
|
|
# Check if some indicators are generated. We will not test all of them
|
|
assert 'buy' in result
|
|
assert 1 in result['buy']
|
|
|
|
|
|
def test_generate_optimizer(mocker, init_hyperopt, default_conf) -> None:
|
|
"""
|
|
Test Hyperopt.generate_optimizer() function
|
|
"""
|
|
conf = deepcopy(default_conf)
|
|
conf.update({'config': 'config.json.example'})
|
|
conf.update({'timerange': None})
|
|
conf.update({'spaces': 'all'})
|
|
|
|
trades = [
|
|
('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-value': 0,
|
|
'fastd-value': 35,
|
|
'mfi-value': 0,
|
|
'rsi-value': 0,
|
|
'adx-enabled': False,
|
|
'fastd-enabled': True,
|
|
'mfi-enabled': False,
|
|
'rsi-enabled': False,
|
|
'trigger': 'macd_cross_signal',
|
|
'roi_t1': 60.0,
|
|
'roi_t2': 30.0,
|
|
'roi_t3': 20.0,
|
|
'roi_p1': 0.01,
|
|
'roi_p2': 0.01,
|
|
'roi_p3': 0.1,
|
|
'stoploss': -0.4,
|
|
}
|
|
|
|
response_expected = {
|
|
'loss': 1.9840569076926293,
|
|
'result': ' 1 trades. Avg profit 2.31%. Total profit 0.00023300 BTC '
|
|
'(0.0231Σ%). Avg duration 100.0 mins.',
|
|
'params': optimizer_param
|
|
}
|
|
|
|
hyperopt = Hyperopt(conf)
|
|
generate_optimizer_value = hyperopt.generate_optimizer(list(optimizer_param.values()))
|
|
assert generate_optimizer_value == response_expected
|