# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument import random from pathlib import Path from unittest.mock import MagicMock, PropertyMock import numpy as np import pandas as pd import pytest from arrow import Arrow from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_backtesting from freqtrade.configuration import TimeRange from freqtrade.data import history from freqtrade.data.btanalysis import BT_DATA_COLUMNS, evaluate_result_multi from freqtrade.data.converter import clean_ohlcv_dataframe from freqtrade.data.dataprovider import DataProvider from freqtrade.data.history import get_timerange from freqtrade.exceptions import DependencyException, OperationalException from freqtrade.optimize.backtesting import Backtesting from freqtrade.persistence import LocalTrade from freqtrade.resolvers import StrategyResolver from freqtrade.state import RunMode from freqtrade.strategy.interface import SellType from tests.conftest import (get_args, log_has, log_has_re, patch_exchange, patched_configuration_load_config_file) ORDER_TYPES = [ { 'buy': 'limit', 'sell': 'limit', 'stoploss': 'limit', 'stoploss_on_exchange': False }, { 'buy': 'limit', 'sell': 'limit', 'stoploss': 'limit', 'stoploss_on_exchange': True }] def trim_dictlist(dict_list, num): new = {} for pair, pair_data in dict_list.items(): new[pair] = pair_data[num:].reset_index() return new def load_data_test(what, testdatadir): timerange = TimeRange.parse_timerange('1510694220-1510700340') data = history.load_pair_history(pair='UNITTEST/BTC', datadir=testdatadir, timeframe='1m', timerange=timerange, drop_incomplete=False, fill_up_missing=False) base = 0.001 if what == 'raise': data.loc[:, 'open'] = data.index * base data.loc[:, 'high'] = data.index * base + 0.0001 data.loc[:, 'low'] = data.index * base - 0.0001 data.loc[:, 'close'] = data.index * base if what == 'lower': data.loc[:, 'open'] = 1 - data.index * base data.loc[:, 'high'] = 1 - data.index * base + 0.0001 data.loc[:, 'low'] = 1 - data.index * base - 0.0001 data.loc[:, 'close'] = 1 - data.index * base if what == 'sine': hz = 0.1 # frequency data.loc[:, 'open'] = np.sin(data.index * hz) / 1000 + base data.loc[:, 'high'] = np.sin(data.index * hz) / 1000 + base + 0.0001 data.loc[:, 'low'] = np.sin(data.index * hz) / 1000 + base - 0.0001 data.loc[:, 'close'] = np.sin(data.index * hz) / 1000 + base return {'UNITTEST/BTC': clean_ohlcv_dataframe(data, timeframe='1m', pair='UNITTEST/BTC', fill_missing=True)} def simple_backtest(config, contour, mocker, testdatadir) -> None: patch_exchange(mocker) config['timeframe'] = '1m' backtesting = Backtesting(config) data = load_data_test(contour, testdatadir) processed = backtesting.strategy.ohlcvdata_to_dataframe(data) min_date, max_date = get_timerange(processed) assert isinstance(processed, dict) results = backtesting.backtest( processed=processed, start_date=min_date, end_date=max_date, max_open_trades=1, position_stacking=False, enable_protections=config.get('enable_protections', False), ) # results :: return results # FIX: fixturize this? def _make_backtest_conf(mocker, datadir, conf=None, pair='UNITTEST/BTC'): data = history.load_data(datadir=datadir, timeframe='1m', pairs=[pair]) data = trim_dictlist(data, -201) patch_exchange(mocker) backtesting = Backtesting(conf) processed = backtesting.strategy.ohlcvdata_to_dataframe(data) min_date, max_date = get_timerange(processed) return { 'processed': processed, 'start_date': min_date, 'end_date': max_date, 'max_open_trades': 10, 'position_stacking': False, } def _trend(signals, buy_value, sell_value): n = len(signals['low']) buy = np.zeros(n) sell = np.zeros(n) for i in range(0, len(signals['buy'])): if random.random() > 0.5: # Both buy and sell signals at same timeframe buy[i] = buy_value sell[i] = sell_value signals['buy'] = buy signals['sell'] = sell return signals def _trend_alternate(dataframe=None, metadata=None): signals = dataframe low = signals['low'] n = len(low) buy = np.zeros(n) sell = np.zeros(n) for i in range(0, len(buy)): if i % 2 == 0: buy[i] = 1 else: sell[i] = 1 signals['buy'] = buy signals['sell'] = sell return dataframe # Unit tests def test_setup_optimize_configuration_without_arguments(mocker, default_conf, caplog) -> None: patched_configuration_load_config_file(mocker, default_conf) args = [ 'backtesting', '--config', 'config.json', '--strategy', 'DefaultStrategy', ] config = setup_optimize_configuration(get_args(args), RunMode.BACKTEST) 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 not log_has_re('Parameter -i/--ticker-interval detected .*', caplog) assert 'position_stacking' not in config assert not log_has('Parameter --enable-position-stacking detected ...', caplog) assert 'timerange' not in config assert 'export' not in config assert 'runmode' in config assert config['runmode'] == RunMode.BACKTEST def test_setup_bt_configuration_with_arguments(mocker, default_conf, caplog) -> None: patched_configuration_load_config_file(mocker, default_conf) mocker.patch( 'freqtrade.configuration.configuration.create_datadir', lambda c, x: x ) args = [ 'backtesting', '--config', 'config.json', '--strategy', 'DefaultStrategy', '--datadir', '/foo/bar', '--timeframe', '1m', '--enable-position-stacking', '--disable-max-market-positions', '--timerange', ':100', '--export', '/bar/foo', '--export-filename', 'foo_bar.json', '--fee', '0', ] config = setup_optimize_configuration(get_args(args), RunMode.BACKTEST) 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.BACKTEST assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog) assert 'timeframe' in config 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 'export' in config assert log_has('Parameter --export detected: {} ...'.format(config['export']), caplog) assert 'exportfilename' in config assert isinstance(config['exportfilename'], Path) assert log_has('Storing backtest results to {} ...'.format(config['exportfilename']), caplog) assert 'fee' in config assert log_has('Parameter --fee detected, setting fee to: {} ...'.format(config['fee']), caplog) def test_setup_optimize_configuration_stake_amount(mocker, default_conf, caplog) -> None: patched_configuration_load_config_file(mocker, default_conf) args = [ 'backtesting', '--config', 'config.json', '--strategy', 'DefaultStrategy', '--stake-amount', '1', '--starting-balance', '2' ] conf = setup_optimize_configuration(get_args(args), RunMode.BACKTEST) assert isinstance(conf, dict) args = [ 'backtesting', '--config', 'config.json', '--strategy', 'DefaultStrategy', '--stake-amount', '1', '--starting-balance', '0.5' ] with pytest.raises(OperationalException, match=r"Starting balance .* smaller .*"): setup_optimize_configuration(get_args(args), RunMode.BACKTEST) def test_start(mocker, fee, default_conf, caplog) -> None: start_mock = MagicMock() mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) patch_exchange(mocker) mocker.patch('freqtrade.optimize.backtesting.Backtesting.start', start_mock) patched_configuration_load_config_file(mocker, default_conf) args = [ 'backtesting', '--config', 'config.json', '--strategy', 'DefaultStrategy', ] pargs = get_args(args) start_backtesting(pargs) assert log_has('Starting freqtrade in Backtesting mode', caplog) assert start_mock.call_count == 1 @pytest.mark.parametrize("order_types", ORDER_TYPES) def test_backtesting_init(mocker, default_conf, order_types) -> None: """ Check that stoploss_on_exchange is set to False while backtesting since backtesting assumes a perfect stoploss anyway. """ default_conf["order_types"] = order_types patch_exchange(mocker) get_fee = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5)) backtesting = Backtesting(default_conf) assert backtesting.config == default_conf assert backtesting.timeframe == '5m' assert callable(backtesting.strategy.ohlcvdata_to_dataframe) assert callable(backtesting.strategy.advise_buy) assert callable(backtesting.strategy.advise_sell) assert isinstance(backtesting.strategy.dp, DataProvider) get_fee.assert_called() assert backtesting.fee == 0.5 assert not backtesting.strategy.order_types["stoploss_on_exchange"] def test_backtesting_init_no_timeframe(mocker, default_conf, caplog) -> None: patch_exchange(mocker) del default_conf['timeframe'] default_conf['strategy_list'] = ['DefaultStrategy', 'SampleStrategy'] mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5)) with pytest.raises(OperationalException): Backtesting(default_conf) log_has("Ticker-interval needs to be set in either configuration " "or as cli argument `--ticker-interval 5m`", caplog) def test_data_with_fee(default_conf, mocker, testdatadir) -> None: patch_exchange(mocker) default_conf['fee'] = 0.1234 fee_mock = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5)) backtesting = Backtesting(default_conf) assert backtesting.fee == 0.1234 assert fee_mock.call_count == 0 default_conf['fee'] = 0.0 backtesting = Backtesting(default_conf) assert backtesting.fee == 0.0 assert fee_mock.call_count == 0 def test_data_to_dataframe_bt(default_conf, mocker, testdatadir) -> None: patch_exchange(mocker) timerange = TimeRange.parse_timerange('1510694220-1510700340') data = history.load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange, fill_up_missing=True) backtesting = Backtesting(default_conf) processed = backtesting.strategy.ohlcvdata_to_dataframe(data) assert len(processed['UNITTEST/BTC']) == 102 # Load strategy to compare the result between Backtesting function and strategy are the same default_conf.update({'strategy': 'DefaultStrategy'}) strategy = StrategyResolver.load_strategy(default_conf) processed2 = strategy.ohlcvdata_to_dataframe(data) assert processed['UNITTEST/BTC'].equals(processed2['UNITTEST/BTC']) def test_backtesting_start(default_conf, mocker, testdatadir, caplog) -> None: def get_timerange(input1): return Arrow(2017, 11, 14, 21, 17), Arrow(2017, 11, 14, 22, 59) mocker.patch('freqtrade.data.history.get_timerange', get_timerange) patch_exchange(mocker) mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest') mocker.patch('freqtrade.optimize.backtesting.generate_backtest_stats') mocker.patch('freqtrade.optimize.backtesting.show_backtest_results') sbs = mocker.patch('freqtrade.optimize.backtesting.store_backtest_stats') mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist', PropertyMock(return_value=['UNITTEST/BTC'])) default_conf['timeframe'] = '1m' default_conf['datadir'] = testdatadir default_conf['export'] = 'trades' default_conf['exportfilename'] = 'export.txt' default_conf['timerange'] = '-1510694220' backtesting = Backtesting(default_conf) backtesting.strategy.bot_loop_start = MagicMock() backtesting.start() # check the logs, that will contain the backtest result exists = [ 'Backtesting with data from 2017-11-14 21:17:00 ' 'up to 2017-11-14 22:59:00 (0 days)..' ] for line in exists: assert log_has(line, caplog) assert backtesting.strategy.dp._pairlists is not None assert backtesting.strategy.bot_loop_start.call_count == 1 assert sbs.call_count == 1 def test_backtesting_start_no_data(default_conf, mocker, caplog, testdatadir) -> None: def get_timerange(input1): return Arrow(2017, 11, 14, 21, 17), Arrow(2017, 11, 14, 22, 59) mocker.patch('freqtrade.data.history.history_utils.load_pair_history', MagicMock(return_value=pd.DataFrame())) mocker.patch('freqtrade.data.history.get_timerange', get_timerange) patch_exchange(mocker) mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest') mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist', PropertyMock(return_value=['UNITTEST/BTC'])) default_conf['timeframe'] = "1m" default_conf['datadir'] = testdatadir default_conf['export'] = None default_conf['timerange'] = '20180101-20180102' backtesting = Backtesting(default_conf) with pytest.raises(OperationalException, match='No data found. Terminating.'): backtesting.start() def test_backtesting_no_pair_left(default_conf, mocker, caplog, testdatadir) -> None: mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True)) mocker.patch('freqtrade.data.history.history_utils.load_pair_history', MagicMock(return_value=pd.DataFrame())) mocker.patch('freqtrade.data.history.get_timerange', get_timerange) patch_exchange(mocker) mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest') mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist', PropertyMock(return_value=[])) default_conf['timeframe'] = "1m" default_conf['datadir'] = testdatadir default_conf['export'] = None default_conf['timerange'] = '20180101-20180102' with pytest.raises(OperationalException, match='No pair in whitelist.'): Backtesting(default_conf) default_conf['pairlists'] = [{"method": "VolumePairList", "number_assets": 5}] with pytest.raises(OperationalException, match='VolumePairList not allowed for backtesting.'): Backtesting(default_conf) def test_backtesting_pairlist_list(default_conf, mocker, caplog, testdatadir, tickers) -> None: mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True)) mocker.patch('freqtrade.exchange.Exchange.get_tickers', tickers) mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y) mocker.patch('freqtrade.data.history.get_timerange', get_timerange) patch_exchange(mocker) mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest') mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist', PropertyMock(return_value=['XRP/BTC'])) mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.refresh_pairlist') default_conf['ticker_interval'] = "1m" default_conf['datadir'] = testdatadir default_conf['export'] = None # Use stoploss from strategy del default_conf['stoploss'] default_conf['timerange'] = '20180101-20180102' default_conf['pairlists'] = [{"method": "VolumePairList", "number_assets": 5}] with pytest.raises(OperationalException, match='VolumePairList not allowed for backtesting.'): Backtesting(default_conf) default_conf['pairlists'] = [{"method": "StaticPairList"}, {"method": "PerformanceFilter"}] with pytest.raises(OperationalException, match='PerformanceFilter not allowed for backtesting.'): Backtesting(default_conf) default_conf['pairlists'] = [{"method": "StaticPairList"}, {"method": "PrecisionFilter"}, ] Backtesting(default_conf) # Multiple strategies default_conf['strategy_list'] = ['DefaultStrategy', 'TestStrategyLegacy'] with pytest.raises(OperationalException, match='PrecisionFilter not allowed for backtesting multiple strategies.'): Backtesting(default_conf) def test_backtest__enter_trade(default_conf, fee, mocker, testdatadir) -> None: default_conf['ask_strategy']['use_sell_signal'] = False mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) patch_exchange(mocker) default_conf['stake_amount'] = 'unlimited' backtesting = Backtesting(default_conf) pair = 'UNITTEST/BTC' row = [ pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=0), 1, # Sell 0.001, # Open 0.0011, # Close 0, # Sell 0.00099, # Low 0.0012, # High ] trade = backtesting._enter_trade(pair, row=row, max_open_trades=2, open_trade_count=0) assert isinstance(trade, LocalTrade) assert trade.stake_amount == 495 trade = backtesting._enter_trade(pair, row=row, max_open_trades=2, open_trade_count=2) assert trade is None # Stake-amount too high! mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=600.0) trade = backtesting._enter_trade(pair, row=row, max_open_trades=2, open_trade_count=0) assert trade is None # Stake-amount too high! mocker.patch("freqtrade.wallets.Wallets.get_trade_stake_amount", side_effect=DependencyException) trade = backtesting._enter_trade(pair, row=row, max_open_trades=2, open_trade_count=0) assert trade is None def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None: default_conf['ask_strategy']['use_sell_signal'] = False mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) patch_exchange(mocker) backtesting = Backtesting(default_conf) pair = 'UNITTEST/BTC' timerange = TimeRange('date', None, 1517227800, 0) data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=['UNITTEST/BTC'], timerange=timerange) processed = backtesting.strategy.ohlcvdata_to_dataframe(data) min_date, max_date = get_timerange(processed) results = backtesting.backtest( processed=processed, start_date=min_date, end_date=max_date, max_open_trades=10, position_stacking=False, ) assert not results.empty assert len(results) == 2 expected = pd.DataFrame( {'pair': [pair, pair], 'stake_amount': [0.001, 0.001], 'amount': [0.00957442, 0.0097064], 'open_date': pd.to_datetime([Arrow(2018, 1, 29, 18, 40, 0).datetime, Arrow(2018, 1, 30, 3, 30, 0).datetime], utc=True ), 'close_date': pd.to_datetime([Arrow(2018, 1, 29, 22, 35, 0).datetime, Arrow(2018, 1, 30, 4, 10, 0).datetime], utc=True), 'open_rate': [0.104445, 0.10302485], 'close_rate': [0.104969, 0.103541], 'fee_open': [0.0025, 0.0025], 'fee_close': [0.0025, 0.0025], 'trade_duration': [235, 40], 'profit_ratio': [0.0, 0.0], 'profit_abs': [0.0, 0.0], 'sell_reason': [SellType.ROI.value, SellType.ROI.value], 'initial_stop_loss_abs': [0.0940005, 0.09272236], 'initial_stop_loss_ratio': [-0.1, -0.1], 'stop_loss_abs': [0.0940005, 0.09272236], 'stop_loss_ratio': [-0.1, -0.1], 'min_rate': [0.1038, 0.10302485], 'max_rate': [0.10501, 0.1038888], 'is_open': [False, False], }) pd.testing.assert_frame_equal(results, expected) data_pair = processed[pair] for _, t in results.iterrows(): ln = data_pair.loc[data_pair["date"] == t["open_date"]] # Check open trade rate alignes to open rate assert ln is not None assert round(ln.iloc[0]["open"], 6) == round(t["open_rate"], 6) # check close trade rate alignes to close rate or is between high and low ln = data_pair.loc[data_pair["date"] == t["close_date"]] assert (round(ln.iloc[0]["open"], 6) == round(t["close_rate"], 6) or round(ln.iloc[0]["low"], 6) < round( t["close_rate"], 6) < round(ln.iloc[0]["high"], 6)) def test_backtest_1min_timeframe(default_conf, fee, mocker, testdatadir) -> None: default_conf['ask_strategy']['use_sell_signal'] = False mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) patch_exchange(mocker) backtesting = Backtesting(default_conf) # Run a backtesting for an exiting 1min timeframe timerange = TimeRange.parse_timerange('1510688220-1510700340') data = history.load_data(datadir=testdatadir, timeframe='1m', pairs=['UNITTEST/BTC'], timerange=timerange) processed = backtesting.strategy.ohlcvdata_to_dataframe(data) min_date, max_date = get_timerange(processed) results = backtesting.backtest( processed=processed, start_date=min_date, end_date=max_date, max_open_trades=1, position_stacking=False, ) assert not results.empty assert len(results) == 1 def test_processed(default_conf, mocker, testdatadir) -> None: patch_exchange(mocker) backtesting = Backtesting(default_conf) dict_of_tickerrows = load_data_test('raise', testdatadir) dataframes = backtesting.strategy.ohlcvdata_to_dataframe(dict_of_tickerrows) dataframe = dataframes['UNITTEST/BTC'] cols = dataframe.columns # assert the dataframe got some of the indicator columns for col in ['close', 'high', 'low', 'open', 'date', 'ema10', 'rsi', 'fastd', 'plus_di']: assert col in cols def test_backtest_pricecontours_protections(default_conf, fee, mocker, testdatadir) -> None: # While this test IS a copy of test_backtest_pricecontours, it's needed to ensure # results do not carry-over to the next run, which is not given by using parametrize. default_conf['protections'] = [ { "method": "CooldownPeriod", "stop_duration": 3, }] default_conf['enable_protections'] = True mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) tests = [ ['sine', 9], ['raise', 10], ['lower', 0], ['sine', 9], ['raise', 10], ] # While buy-signals are unrealistic, running backtesting # over and over again should not cause different results for [contour, numres] in tests: assert len(simple_backtest(default_conf, contour, mocker, testdatadir)) == numres @pytest.mark.parametrize('protections,contour,expected', [ (None, 'sine', 35), (None, 'raise', 19), (None, 'lower', 0), (None, 'sine', 35), (None, 'raise', 19), ([{"method": "CooldownPeriod", "stop_duration": 3}], 'sine', 9), ([{"method": "CooldownPeriod", "stop_duration": 3}], 'raise', 10), ([{"method": "CooldownPeriod", "stop_duration": 3}], 'lower', 0), ([{"method": "CooldownPeriod", "stop_duration": 3}], 'sine', 9), ([{"method": "CooldownPeriod", "stop_duration": 3}], 'raise', 10), ]) def test_backtest_pricecontours(default_conf, fee, mocker, testdatadir, protections, contour, expected) -> None: if protections: default_conf['protections'] = protections default_conf['enable_protections'] = True mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) # While buy-signals are unrealistic, running backtesting # over and over again should not cause different results assert len(simple_backtest(default_conf, contour, mocker, testdatadir)) == expected def test_backtest_clash_buy_sell(mocker, default_conf, testdatadir): # Override the default buy trend function in our default_strategy def fun(dataframe=None, pair=None): buy_value = 1 sell_value = 1 return _trend(dataframe, buy_value, sell_value) backtest_conf = _make_backtest_conf(mocker, conf=default_conf, datadir=testdatadir) backtesting = Backtesting(default_conf) backtesting.strategy.advise_buy = fun # Override backtesting.strategy.advise_sell = fun # Override results = backtesting.backtest(**backtest_conf) assert results.empty def test_backtest_only_sell(mocker, default_conf, testdatadir): # Override the default buy trend function in our default_strategy def fun(dataframe=None, pair=None): buy_value = 0 sell_value = 1 return _trend(dataframe, buy_value, sell_value) backtest_conf = _make_backtest_conf(mocker, conf=default_conf, datadir=testdatadir) backtesting = Backtesting(default_conf) backtesting.strategy.advise_buy = fun # Override backtesting.strategy.advise_sell = fun # Override results = backtesting.backtest(**backtest_conf) assert results.empty def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir): mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) backtest_conf = _make_backtest_conf(mocker, conf=default_conf, pair='UNITTEST/BTC', datadir=testdatadir) default_conf['timeframe'] = '1m' backtesting = Backtesting(default_conf) backtesting.strategy.advise_buy = _trend_alternate # Override backtesting.strategy.advise_sell = _trend_alternate # Override results = backtesting.backtest(**backtest_conf) # 200 candles in backtest data # won't buy on first (shifted by 1) # 100 buys signals assert len(results) == 100 # One trade was force-closed at the end assert len(results.loc[results['is_open']]) == 0 @pytest.mark.parametrize("pair", ['ADA/BTC', 'LTC/BTC']) @pytest.mark.parametrize("tres", [0, 20, 30]) def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir): def _trend_alternate_hold(dataframe=None, metadata=None): """ Buy every xth candle - sell every other xth -2 (hold on to pairs a bit) """ if metadata['pair'] in ('ETH/BTC', 'LTC/BTC'): multi = 20 else: multi = 18 dataframe['buy'] = np.where(dataframe.index % multi == 0, 1, 0) dataframe['sell'] = np.where((dataframe.index + multi - 2) % multi == 0, 1, 0) return dataframe mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001) mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) patch_exchange(mocker) pairs = ['ADA/BTC', 'DASH/BTC', 'ETH/BTC', 'LTC/BTC', 'NXT/BTC'] data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=pairs) # Only use 500 lines to increase performance data = trim_dictlist(data, -500) # Remove data for one pair from the beginning of the data data[pair] = data[pair][tres:].reset_index() default_conf['timeframe'] = '5m' backtesting = Backtesting(default_conf) backtesting.strategy.advise_buy = _trend_alternate_hold # Override backtesting.strategy.advise_sell = _trend_alternate_hold # Override processed = backtesting.strategy.ohlcvdata_to_dataframe(data) min_date, max_date = get_timerange(processed) backtest_conf = { 'processed': processed, 'start_date': min_date, 'end_date': max_date, 'max_open_trades': 3, 'position_stacking': False, } results = backtesting.backtest(**backtest_conf) # Make sure we have parallel trades assert len(evaluate_result_multi(results, '5m', 2)) > 0 # make sure we don't have trades with more than configured max_open_trades assert len(evaluate_result_multi(results, '5m', 3)) == 0 backtest_conf = { 'processed': processed, 'start_date': min_date, 'end_date': max_date, 'max_open_trades': 1, 'position_stacking': False, } results = backtesting.backtest(**backtest_conf) assert len(evaluate_result_multi(results, '5m', 1)) == 0 def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir): patch_exchange(mocker) mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest') mocker.patch('freqtrade.optimize.backtesting.generate_backtest_stats') mocker.patch('freqtrade.optimize.backtesting.show_backtest_results') mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist', PropertyMock(return_value=['UNITTEST/BTC'])) patched_configuration_load_config_file(mocker, default_conf) args = [ 'backtesting', '--config', 'config.json', '--strategy', 'DefaultStrategy', '--datadir', str(testdatadir), '--timeframe', '1m', '--timerange', '1510694220-1510700340', '--enable-position-stacking', '--disable-max-market-positions' ] args = get_args(args) start_backtesting(args) # check the logs, that will contain the backtest result exists = [ 'Parameter -i/--timeframe detected ... Using timeframe: 1m ...', 'Ignoring max_open_trades (--disable-max-market-positions was used) ...', 'Parameter --timerange detected: 1510694220-1510700340 ...', f'Using data directory: {testdatadir} ...', 'Loading data from 2017-11-14 20:57:00 ' 'up to 2017-11-14 22:58:00 (0 days)..', 'Backtesting with data from 2017-11-14 21:17:00 ' 'up to 2017-11-14 22:58:00 (0 days)..', 'Parameter --enable-position-stacking detected ...' ] for line in exists: assert log_has(line, caplog) @pytest.mark.filterwarnings("ignore:deprecated") def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir): patch_exchange(mocker) backtestmock = MagicMock(return_value=pd.DataFrame(columns=BT_DATA_COLUMNS)) mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist', PropertyMock(return_value=['UNITTEST/BTC'])) mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock) text_table_mock = MagicMock() sell_reason_mock = MagicMock() strattable_mock = MagicMock() strat_summary = MagicMock() mocker.patch.multiple('freqtrade.optimize.optimize_reports', text_table_bt_results=text_table_mock, text_table_strategy=strattable_mock, generate_pair_metrics=MagicMock(), generate_sell_reason_stats=sell_reason_mock, generate_strategy_metrics=strat_summary, generate_daily_stats=MagicMock(), ) patched_configuration_load_config_file(mocker, default_conf) args = [ 'backtesting', '--config', 'config.json', '--datadir', str(testdatadir), '--strategy-path', str(Path(__file__).parents[1] / 'strategy/strats'), '--timeframe', '1m', '--timerange', '1510694220-1510700340', '--enable-position-stacking', '--disable-max-market-positions', '--strategy-list', 'DefaultStrategy', 'TestStrategyLegacy', ] args = get_args(args) start_backtesting(args) # 2 backtests, 4 tables assert backtestmock.call_count == 2 assert text_table_mock.call_count == 4 assert strattable_mock.call_count == 1 assert sell_reason_mock.call_count == 2 assert strat_summary.call_count == 1 # check the logs, that will contain the backtest result exists = [ 'Parameter -i/--timeframe detected ... Using timeframe: 1m ...', 'Ignoring max_open_trades (--disable-max-market-positions was used) ...', 'Parameter --timerange detected: 1510694220-1510700340 ...', f'Using data directory: {testdatadir} ...', 'Loading data from 2017-11-14 20:57:00 ' 'up to 2017-11-14 22:58:00 (0 days)..', 'Backtesting with data from 2017-11-14 21:17:00 ' 'up to 2017-11-14 22:58:00 (0 days)..', 'Parameter --enable-position-stacking detected ...', 'Running backtesting for Strategy DefaultStrategy', 'Running backtesting for Strategy TestStrategyLegacy', ] for line in exists: assert log_has(line, caplog) @pytest.mark.filterwarnings("ignore:deprecated") def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdatadir, capsys): patch_exchange(mocker) backtestmock = MagicMock(side_effect=[ pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC'], 'profit_ratio': [0.0, 0.0], 'profit_abs': [0.0, 0.0], 'open_date': pd.to_datetime(['2018-01-29 18:40:00', '2018-01-30 03:30:00', ], utc=True ), 'close_date': pd.to_datetime(['2018-01-29 20:45:00', '2018-01-30 05:35:00', ], utc=True), 'trade_duration': [235, 40], 'is_open': [False, False], 'stake_amount': [0.01, 0.01], 'open_rate': [0.104445, 0.10302485], 'close_rate': [0.104969, 0.103541], 'sell_reason': [SellType.ROI, SellType.ROI] }), pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC', 'ETH/BTC'], 'profit_ratio': [0.03, 0.01, 0.1], 'profit_abs': [0.01, 0.02, 0.2], 'open_date': pd.to_datetime(['2018-01-29 18:40:00', '2018-01-30 03:30:00', '2018-01-30 05:30:00'], utc=True ), 'close_date': pd.to_datetime(['2018-01-29 20:45:00', '2018-01-30 05:35:00', '2018-01-30 08:30:00'], utc=True), 'trade_duration': [47, 40, 20], 'is_open': [False, False, False], 'stake_amount': [0.01, 0.01, 0.01], 'open_rate': [0.104445, 0.10302485, 0.122541], 'close_rate': [0.104969, 0.103541, 0.123541], 'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS] }), ]) mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist', PropertyMock(return_value=['UNITTEST/BTC'])) mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock) patched_configuration_load_config_file(mocker, default_conf) args = [ 'backtesting', '--config', 'config.json', '--datadir', str(testdatadir), '--strategy-path', str(Path(__file__).parents[1] / 'strategy/strats'), '--timeframe', '1m', '--timerange', '1510694220-1510700340', '--enable-position-stacking', '--disable-max-market-positions', '--strategy-list', 'DefaultStrategy', 'TestStrategyLegacy', ] args = get_args(args) start_backtesting(args) # check the logs, that will contain the backtest result exists = [ 'Parameter -i/--timeframe detected ... Using timeframe: 1m ...', 'Ignoring max_open_trades (--disable-max-market-positions was used) ...', 'Parameter --timerange detected: 1510694220-1510700340 ...', f'Using data directory: {testdatadir} ...', 'Loading data from 2017-11-14 20:57:00 ' 'up to 2017-11-14 22:58:00 (0 days)..', 'Backtesting with data from 2017-11-14 21:17:00 ' 'up to 2017-11-14 22:58:00 (0 days)..', 'Parameter --enable-position-stacking detected ...', 'Running backtesting for Strategy DefaultStrategy', 'Running backtesting for Strategy TestStrategyLegacy', ] for line in exists: assert log_has(line, caplog) captured = capsys.readouterr() assert 'BACKTESTING REPORT' in captured.out assert 'SELL REASON STATS' in captured.out assert 'LEFT OPEN TRADES REPORT' in captured.out assert 'STRATEGY SUMMARY' in captured.out