import re from datetime import timedelta from pathlib import Path import pandas as pd import pytest from arrow import Arrow from freqtrade.configuration import TimeRange from freqtrade.constants import LAST_BT_RESULT_FN from freqtrade.data import history from freqtrade.data.btanalysis import (get_latest_backtest_filename, load_backtest_data) from freqtrade.edge import PairInfo from freqtrade.optimize.optimize_reports import (generate_backtest_stats, generate_daily_stats, generate_edge_table, generate_pair_metrics, generate_sell_reason_stats, generate_strategy_metrics, store_backtest_stats, text_table_bt_results, text_table_sell_reason, text_table_strategy) from freqtrade.strategy.interface import SellType from tests.data.test_history import _backup_file, _clean_test_file def test_text_table_bt_results(default_conf, mocker): results = pd.DataFrame( { 'pair': ['ETH/BTC', 'ETH/BTC'], 'profit_percent': [0.1, 0.2], 'profit_abs': [0.2, 0.4], 'trade_duration': [10, 30], 'wins': [2, 0], 'draws': [0, 0], 'losses': [0, 0] } ) result_str = ( '| Pair | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC |' ' Tot Profit % | Avg Duration | Wins | Draws | Losses |\n' '|---------+--------+----------------+----------------+------------------+' '----------------+----------------+--------+---------+----------|\n' '| ETH/BTC | 2 | 15.00 | 30.00 | 0.60000000 |' ' 15.00 | 0:20:00 | 2 | 0 | 0 |\n' '| TOTAL | 2 | 15.00 | 30.00 | 0.60000000 |' ' 15.00 | 0:20:00 | 2 | 0 | 0 |' ) pair_results = generate_pair_metrics(data={'ETH/BTC': {}}, stake_currency='BTC', max_open_trades=2, results=results) assert text_table_bt_results(pair_results, stake_currency='BTC') == result_str def test_generate_backtest_stats(default_conf, testdatadir): results = {'DefStrat': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC"], "profit_percent": [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], "open_at_end": [False, False, False, True], "sell_reason": [SellType.ROI, SellType.STOP_LOSS, SellType.ROI, SellType.FORCE_SELL] })} 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(default_conf, 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.datetime assert strat_stats['backtest_end'] == max_date.datetime assert strat_stats['total_trades'] == len(results['DefStrat']) # Above sample had no loosing trade assert strat_stats['max_drawdown'] == 0.0 results = {'DefStrat': pd.DataFrame( {"pair": ["UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC"], "profit_percent": [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], "open_at_end": [False, False, False, True], "sell_reason": [SellType.ROI, SellType.STOP_LOSS, SellType.ROI, SellType.FORCE_SELL] })} assert strat_stats['max_drawdown'] == 0.0 assert strat_stats['drawdown_start'] == Arrow.fromtimestamp(0).datetime assert strat_stats['drawdown_end'] == Arrow.fromtimestamp(0).datetime assert strat_stats['drawdown_end_ts'] == 0 assert strat_stats['drawdown_start_ts'] == 0 assert strat_stats['pairlist'] == ['UNITTEST/BTC'] # Test storing stats filename = Path(testdatadir / 'btresult.json') filename_last = Path(testdatadir / LAST_BT_RESULT_FN) _backup_file(filename_last, copy_file=True) assert not filename.is_file() store_backtest_stats(filename, stats) # 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 = (testdatadir / last_fn) assert filename1.is_file() content = filename1.read_text() assert 'max_drawdown' 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, {}) assert dump_mock.call_count == 2 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, {}) assert dump_mock.call_count == 2 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_generate_pair_metrics(default_conf, mocker): results = pd.DataFrame( { 'pair': ['ETH/BTC', 'ETH/BTC'], 'profit_percent': [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(data={'ETH/BTC': {}}, stake_currency='BTC', max_open_trades=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-result_new.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'] == 14 assert res['draw_days'] == 4 assert res['losing_days'] == 3 assert res['winner_holding_avg'] == timedelta(seconds=1440) assert res['loser_holding_avg'] == timedelta(days=1, seconds=21420) def test_text_table_sell_reason(default_conf): results = pd.DataFrame( { 'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'], 'profit_percent': [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], 'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS] } ) result_str = ( '| Sell Reason | Sells | Wins | Draws | Losses |' ' Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % |\n' '|---------------+---------+--------+---------+----------+' '----------------+----------------+------------------+----------------|\n' '| roi | 2 | 2 | 0 | 0 |' ' 15 | 30 | 0.6 | 15 |\n' '| stop_loss | 1 | 0 | 0 | 1 |' ' -10 | -10 | -0.2 | -5 |' ) sell_reason_stats = generate_sell_reason_stats(max_open_trades=2, results=results) assert text_table_sell_reason(sell_reason_stats=sell_reason_stats, stake_currency='BTC') == result_str def test_generate_sell_reason_stats(default_conf): results = pd.DataFrame( { 'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'], 'profit_percent': [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], 'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS] } ) sell_reason_stats = generate_sell_reason_stats(max_open_trades=2, results=results) roi_result = sell_reason_stats[0] assert roi_result['sell_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 = sell_reason_stats[1] assert stop_result['sell_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(default_conf, mocker): results = {} results['TestStrategy1'] = pd.DataFrame( { 'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'], 'profit_percent': [0.1, 0.2, 0.3], 'profit_abs': [0.2, 0.4, 0.5], 'trade_duration': [10, 30, 10], 'wins': [2, 0, 0], 'draws': [0, 0, 0], 'losses': [0, 0, 1], 'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS] } ) results['TestStrategy2'] = pd.DataFrame( { 'pair': ['LTC/BTC', 'LTC/BTC', 'LTC/BTC'], 'profit_percent': [0.4, 0.2, 0.3], 'profit_abs': [0.4, 0.4, 0.5], 'trade_duration': [15, 30, 15], 'wins': [4, 1, 0], 'draws': [0, 0, 0], 'losses': [0, 0, 1], 'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS] } ) result_str = ( '| Strategy | Buys | Avg Profit % | Cum Profit % | Tot' ' Profit BTC | Tot Profit % | Avg Duration | Wins | Draws | Losses |\n' '|---------------+--------+----------------+----------------+------------------+' '----------------+----------------+--------+---------+----------|\n' '| TestStrategy1 | 3 | 20.00 | 60.00 | 1.10000000 |' ' 30.00 | 0:17:00 | 3 | 0 | 0 |\n' '| TestStrategy2 | 3 | 30.00 | 90.00 | 1.30000000 |' ' 45.00 | 0:20:00 | 3 | 0 | 0 |' ) strategy_results = generate_strategy_metrics(stake_currency='BTC', max_open_trades=2, all_results=results) assert text_table_strategy(strategy_results, 'BTC') == result_str def test_generate_edge_table(edge_conf, mocker): 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