import re from datetime import timedelta from pathlib import Path from shutil import copyfile import joblib import pandas as pd import pytest from arrow import Arrow from freqtrade.configuration import TimeRange from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN from freqtrade.data import history from freqtrade.data.btanalysis import (get_latest_backtest_filename, load_backtest_data, load_backtest_stats) from freqtrade.edge import PairInfo from freqtrade.enums import ExitType from freqtrade.optimize.optimize_reports import (_get_resample_from_period, generate_backtest_stats, generate_daily_stats, generate_edge_table, generate_exit_reason_stats, generate_pair_metrics, generate_periodic_breakdown_stats, generate_strategy_comparison, generate_trading_stats, show_sorted_pairlist, store_backtest_signal_candles, store_backtest_stats, text_table_bt_results, text_table_exit_reason, text_table_strategy) from freqtrade.resolvers.strategy_resolver import StrategyResolver from tests.conftest import CURRENT_TEST_STRATEGY from tests.data.test_history import _clean_test_file def _backup_file(file: Path, copy_file: bool = False) -> None: """ Backup existing file to avoid deleting the user file :param file: complete path to the file :param copy_file: keep file in place too. :return: None """ file_swp = str(file) + '.swp' if file.is_file(): file.rename(file_swp) if copy_file: copyfile(file_swp, file) def test_text_table_bt_results(): results = pd.DataFrame( { 'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'], 'profit_ratio': [0.1, 0.2, -0.05], 'profit_abs': [0.2, 0.4, -0.1], 'trade_duration': [10, 30, 20], } ) result_str = ( '| Pair | Entries | Avg Profit % | Cum Profit % | Tot Profit BTC | ' 'Tot Profit % | Avg Duration | Win Draw Loss Win% |\n' '|---------+-----------+----------------+----------------+------------------+' '----------------+----------------+-------------------------|\n' '| ETH/BTC | 3 | 8.33 | 25.00 | 0.50000000 | ' '12.50 | 0:20:00 | 2 0 1 66.7 |\n' '| TOTAL | 3 | 8.33 | 25.00 | 0.50000000 | ' '12.50 | 0:20:00 | 2 0 1 66.7 |' ) pair_results = generate_pair_metrics(['ETH/BTC'], stake_currency='BTC', starting_balance=4, results=results) assert text_table_bt_results(pair_results, stake_currency='BTC') == result_str def test_generate_backtest_stats(default_conf, testdatadir, tmpdir): default_conf.update({'strategy': CURRENT_TEST_STRATEGY}) StrategyResolver.load_strategy(default_conf) results = {'DefStrat': { '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], "is_short": [False, False, False, False], "stake_amount": [0.01, 0.01, 0.01, 0.01], "exit_reason": [ExitType.ROI, ExitType.STOP_LOSS, ExitType.ROI, ExitType.FORCE_EXIT] }), 'config': default_conf, 'locks': [], 'final_balance': 1000.02, 'rejected_signals': 20, 'timedout_entry_orders': 0, 'timedout_exit_orders': 0, 'canceled_trade_entries': 0, 'canceled_entry_orders': 0, 'replaced_entry_orders': 0, 'backtest_start_time': Arrow.utcnow().int_timestamp, 'backtest_end_time': Arrow.utcnow().int_timestamp, 'run_id': '123', } } timerange = TimeRange.parse_timerange('1510688220-1510700340') min_date = Arrow.fromtimestamp(1510688220) max_date = Arrow.fromtimestamp(1510700340) btdata = history.load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange, fill_up_missing=True) stats = generate_backtest_stats(btdata, results, min_date, max_date) assert isinstance(stats, dict) assert 'strategy' in stats assert 'DefStrat' in stats['strategy'] assert 'strategy_comparison' in stats strat_stats = stats['strategy']['DefStrat'] assert strat_stats['backtest_start'] == min_date.strftime(DATETIME_PRINT_FORMAT) assert strat_stats['backtest_end'] == max_date.strftime(DATETIME_PRINT_FORMAT) assert strat_stats['total_trades'] == len(results['DefStrat']['results']) # Above sample had no loosing trade assert strat_stats['max_drawdown_account'] == 0.0 # Retry with losing trade results = {'DefStrat': { '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, 0.0032903, 0.003217], "trade_duration": [123, 34, 31, 14], "is_open": [False, False, False, True], "is_short": [False, False, False, False], "stake_amount": [0.01, 0.01, 0.01, 0.01], "exit_reason": [ExitType.ROI, ExitType.ROI, ExitType.STOP_LOSS, ExitType.FORCE_EXIT] }), 'config': default_conf, 'locks': [], 'final_balance': 1000.02, 'rejected_signals': 20, 'timedout_entry_orders': 0, 'timedout_exit_orders': 0, 'canceled_trade_entries': 0, 'canceled_entry_orders': 0, 'replaced_entry_orders': 0, 'backtest_start_time': Arrow.utcnow().int_timestamp, 'backtest_end_time': Arrow.utcnow().int_timestamp, 'run_id': '124', } } stats = generate_backtest_stats(btdata, results, min_date, max_date) assert isinstance(stats, dict) assert 'strategy' in stats assert 'DefStrat' in stats['strategy'] assert 'strategy_comparison' in stats strat_stats = stats['strategy']['DefStrat'] assert pytest.approx(strat_stats['max_drawdown_account']) == 1.399999e-08 assert strat_stats['drawdown_start'] == '2017-11-14 22:10:00' assert strat_stats['drawdown_end'] == '2017-11-14 22:43:00' assert strat_stats['drawdown_end_ts'] == 1510699380000 assert strat_stats['drawdown_start_ts'] == 1510697400000 assert strat_stats['pairlist'] == ['UNITTEST/BTC'] # Test storing stats filename = Path(tmpdir / 'btresult.json') filename_last = Path(tmpdir / LAST_BT_RESULT_FN) _backup_file(filename_last, copy_file=True) assert not filename.is_file() store_backtest_stats(filename, stats, '2022_01_01_15_05_13') # get real Filename (it's btresult-.json) last_fn = get_latest_backtest_filename(filename_last.parent) assert re.match(r"btresult-.*\.json", last_fn) filename1 = Path(tmpdir / last_fn) assert filename1.is_file() content = filename1.read_text() assert 'max_drawdown_account' in content assert 'strategy' in content assert 'pairlist' in content assert filename_last.is_file() _clean_test_file(filename_last) filename1.unlink() def test_store_backtest_stats(testdatadir, mocker): dump_mock = mocker.patch('freqtrade.optimize.optimize_reports.file_dump_json') store_backtest_stats(testdatadir, {'metadata': {}}, '2022_01_01_15_05_13') assert dump_mock.call_count == 3 assert isinstance(dump_mock.call_args_list[0][0][0], Path) assert str(dump_mock.call_args_list[0][0][0]).startswith(str(testdatadir / 'backtest-result')) dump_mock.reset_mock() filename = testdatadir / 'testresult.json' store_backtest_stats(filename, {'metadata': {}}, '2022_01_01_15_05_13') assert dump_mock.call_count == 3 assert isinstance(dump_mock.call_args_list[0][0][0], Path) # result will be testdatadir / testresult-.json assert str(dump_mock.call_args_list[0][0][0]).startswith(str(testdatadir / 'testresult')) def test_store_backtest_candles(testdatadir, mocker): dump_mock = mocker.patch('freqtrade.optimize.optimize_reports.file_dump_joblib') candle_dict = {'DefStrat': {'UNITTEST/BTC': pd.DataFrame()}} # mock directory exporting store_backtest_signal_candles(testdatadir, candle_dict, '2022_01_01_15_05_13') assert dump_mock.call_count == 1 assert isinstance(dump_mock.call_args_list[0][0][0], Path) assert str(dump_mock.call_args_list[0][0][0]).endswith(str('_signals.pkl')) dump_mock.reset_mock() # mock file exporting filename = Path(testdatadir / 'testresult') store_backtest_signal_candles(filename, candle_dict, '2022_01_01_15_05_13') assert dump_mock.call_count == 1 assert isinstance(dump_mock.call_args_list[0][0][0], Path) # result will be testdatadir / testresult-_signals.pkl assert str(dump_mock.call_args_list[0][0][0]).endswith(str('_signals.pkl')) dump_mock.reset_mock() def test_write_read_backtest_candles(tmpdir): candle_dict = {'DefStrat': {'UNITTEST/BTC': pd.DataFrame()}} # test directory exporting stored_file = store_backtest_signal_candles(Path(tmpdir), candle_dict, '2022_01_01_15_05_13') scp = stored_file.open("rb") pickled_signal_candles = joblib.load(scp) scp.close() assert pickled_signal_candles.keys() == candle_dict.keys() assert pickled_signal_candles['DefStrat'].keys() == pickled_signal_candles['DefStrat'].keys() assert pickled_signal_candles['DefStrat']['UNITTEST/BTC'] \ .equals(pickled_signal_candles['DefStrat']['UNITTEST/BTC']) _clean_test_file(stored_file) # test file exporting filename = Path(tmpdir / 'testresult') stored_file = store_backtest_signal_candles(filename, candle_dict, '2022_01_01_15_05_13') scp = stored_file.open("rb") pickled_signal_candles = joblib.load(scp) scp.close() assert pickled_signal_candles.keys() == candle_dict.keys() assert pickled_signal_candles['DefStrat'].keys() == pickled_signal_candles['DefStrat'].keys() assert pickled_signal_candles['DefStrat']['UNITTEST/BTC'] \ .equals(pickled_signal_candles['DefStrat']['UNITTEST/BTC']) _clean_test_file(stored_file) def test_generate_pair_metrics(): results = pd.DataFrame( { 'pair': ['ETH/BTC', 'ETH/BTC'], 'profit_ratio': [0.1, 0.2], 'profit_abs': [0.2, 0.4], 'trade_duration': [10, 30], 'wins': [2, 0], 'draws': [0, 0], 'losses': [0, 0] } ) pair_results = generate_pair_metrics(['ETH/BTC'], stake_currency='BTC', starting_balance=2, results=results) assert isinstance(pair_results, list) assert len(pair_results) == 2 assert pair_results[-1]['key'] == 'TOTAL' assert ( pytest.approx(pair_results[-1]['profit_mean_pct']) == pair_results[-1]['profit_mean'] * 100) assert ( pytest.approx(pair_results[-1]['profit_sum_pct']) == pair_results[-1]['profit_sum'] * 100) def test_generate_daily_stats(testdatadir): filename = testdatadir / "backtest_results/backtest-result.json" bt_data = load_backtest_data(filename) res = generate_daily_stats(bt_data) assert isinstance(res, dict) assert round(res['backtest_best_day'], 4) == 0.1796 assert round(res['backtest_worst_day'], 4) == -0.1468 assert res['winning_days'] == 19 assert res['draw_days'] == 0 assert res['losing_days'] == 2 # Select empty dataframe! res = generate_daily_stats(bt_data.loc[bt_data['open_date'] == '2000-01-01', :]) assert isinstance(res, dict) assert round(res['backtest_best_day'], 4) == 0.0 assert res['winning_days'] == 0 assert res['draw_days'] == 0 assert res['losing_days'] == 0 def test_generate_trading_stats(testdatadir): filename = testdatadir / "backtest_results/backtest-result.json" bt_data = load_backtest_data(filename) res = generate_trading_stats(bt_data) assert isinstance(res, dict) assert res['winner_holding_avg'] == timedelta(seconds=1440) assert res['loser_holding_avg'] == timedelta(days=1, seconds=21420) assert 'wins' in res assert 'losses' in res assert 'draws' in res # Select empty dataframe! res = generate_trading_stats(bt_data.loc[bt_data['open_date'] == '2000-01-01', :]) assert res['wins'] == 0 assert res['losses'] == 0 def test_text_table_exit_reason(): results = pd.DataFrame( { 'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'], 'profit_ratio': [0.1, 0.2, -0.1], 'profit_abs': [0.2, 0.4, -0.2], 'trade_duration': [10, 30, 10], 'wins': [2, 0, 0], 'draws': [0, 0, 0], 'losses': [0, 0, 1], 'exit_reason': [ExitType.ROI, ExitType.ROI, ExitType.STOP_LOSS] } ) result_str = ( '| Exit Reason | Exits | Win Draws Loss Win% | Avg Profit % | Cum Profit % |' ' Tot Profit BTC | Tot Profit % |\n' '|---------------+---------+--------------------------+----------------+----------------+' '------------------+----------------|\n' '| roi | 2 | 2 0 0 100 | 15 | 30 |' ' 0.6 | 15 |\n' '| stop_loss | 1 | 0 0 1 0 | -10 | -10 |' ' -0.2 | -5 |' ) exit_reason_stats = generate_exit_reason_stats(max_open_trades=2, results=results) assert text_table_exit_reason(exit_reason_stats=exit_reason_stats, stake_currency='BTC') == result_str def test_generate_sell_reason_stats(): results = pd.DataFrame( { 'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'], 'profit_ratio': [0.1, 0.2, -0.1], 'profit_abs': [0.2, 0.4, -0.2], 'trade_duration': [10, 30, 10], 'wins': [2, 0, 0], 'draws': [0, 0, 0], 'losses': [0, 0, 1], 'exit_reason': [ExitType.ROI.value, ExitType.ROI.value, ExitType.STOP_LOSS.value] } ) exit_reason_stats = generate_exit_reason_stats(max_open_trades=2, results=results) roi_result = exit_reason_stats[0] assert roi_result['exit_reason'] == 'roi' assert roi_result['trades'] == 2 assert pytest.approx(roi_result['profit_mean']) == 0.15 assert roi_result['profit_mean_pct'] == round(roi_result['profit_mean'] * 100, 2) assert pytest.approx(roi_result['profit_mean']) == 0.15 assert roi_result['profit_mean_pct'] == round(roi_result['profit_mean'] * 100, 2) stop_result = exit_reason_stats[1] assert stop_result['exit_reason'] == 'stop_loss' assert stop_result['trades'] == 1 assert pytest.approx(stop_result['profit_mean']) == -0.1 assert stop_result['profit_mean_pct'] == round(stop_result['profit_mean'] * 100, 2) assert pytest.approx(stop_result['profit_mean']) == -0.1 assert stop_result['profit_mean_pct'] == round(stop_result['profit_mean'] * 100, 2) def test_text_table_strategy(testdatadir): filename = testdatadir / "backtest_results/backtest-result_multistrat.json" bt_res_data = load_backtest_stats(filename) bt_res_data_comparison = bt_res_data.pop('strategy_comparison') result_str = ( '| Strategy | Entries | Avg Profit % | Cum Profit % | Tot Profit BTC |' ' Tot Profit % | Avg Duration | Win Draw Loss Win% | Drawdown |\n' '|----------------+-----------+----------------+----------------+------------------+' '----------------+----------------+-------------------------+-----------------------|\n' '| StrategyTestV2 | 179 | 0.08 | 14.39 | 0.02608550 |' ' 260.85 | 3:40:00 | 170 0 9 95.0 | 0.00308222 BTC 8.67% |\n' '| TestStrategy | 179 | 0.08 | 14.39 | 0.02608550 |' ' 260.85 | 3:40:00 | 170 0 9 95.0 | 0.00308222 BTC 8.67% |' ) strategy_results = generate_strategy_comparison(bt_stats=bt_res_data['strategy']) assert strategy_results == bt_res_data_comparison assert text_table_strategy(strategy_results, 'BTC') == result_str def test_generate_edge_table(): results = {} results['ETH/BTC'] = PairInfo(-0.01, 0.60, 2, 1, 3, 10, 60) assert generate_edge_table(results).count('+') == 7 assert generate_edge_table(results).count('| ETH/BTC |') == 1 assert generate_edge_table(results).count( '| Risk Reward Ratio | Required Risk Reward | Expectancy |') == 1 def test_generate_periodic_breakdown_stats(testdatadir): filename = testdatadir / "backtest_results/backtest-result.json" bt_data = load_backtest_data(filename).to_dict(orient='records') res = generate_periodic_breakdown_stats(bt_data, 'day') assert isinstance(res, list) assert len(res) == 21 day = res[0] assert 'date' in day assert 'draws' in day assert 'loses' in day assert 'wins' in day assert 'profit_abs' in day # Select empty dataframe! res = generate_periodic_breakdown_stats([], 'day') assert res == [] def test__get_resample_from_period(): assert _get_resample_from_period('day') == '1d' assert _get_resample_from_period('week') == '1w' assert _get_resample_from_period('month') == '1M' with pytest.raises(ValueError, match=r"Period noooo is not supported."): _get_resample_from_period('noooo') def test_show_sorted_pairlist(testdatadir, default_conf, capsys): filename = testdatadir / "backtest_results/backtest-result.json" bt_data = load_backtest_stats(filename) default_conf['backtest_show_pair_list'] = True show_sorted_pairlist(default_conf, bt_data) out, err = capsys.readouterr() assert 'Pairs for Strategy StrategyTestV3: \n[' in out assert 'TOTAL' not in out assert '"ETH/BTC", // ' in out