485 lines
20 KiB
Python
485 lines
20 KiB
Python
import re
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from datetime import timedelta
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from pathlib import Path
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from shutil import copyfile
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import joblib
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import pandas as pd
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import pytest
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from arrow import Arrow
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from freqtrade.configuration import TimeRange
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from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN
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from freqtrade.data import history
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from freqtrade.data.btanalysis import (get_latest_backtest_filename, load_backtest_data,
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load_backtest_stats)
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from freqtrade.edge import PairInfo
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from freqtrade.enums import ExitType
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from freqtrade.optimize.optimize_reports import (_get_resample_from_period, generate_backtest_stats,
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generate_daily_stats, generate_edge_table,
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generate_exit_reason_stats, generate_pair_metrics,
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generate_periodic_breakdown_stats,
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generate_strategy_comparison,
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generate_trading_stats, show_sorted_pairlist,
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store_backtest_signal_candles,
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store_backtest_stats, text_table_bt_results,
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text_table_exit_reason, text_table_strategy)
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from freqtrade.resolvers.strategy_resolver import StrategyResolver
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from tests.conftest import CURRENT_TEST_STRATEGY
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from tests.data.test_history import _clean_test_file
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def _backup_file(file: Path, copy_file: bool = False) -> None:
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"""
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Backup existing file to avoid deleting the user file
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:param file: complete path to the file
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:param copy_file: keep file in place too.
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:return: None
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"""
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file_swp = str(file) + '.swp'
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if file.is_file():
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file.rename(file_swp)
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if copy_file:
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copyfile(file_swp, file)
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def test_text_table_bt_results():
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results = pd.DataFrame(
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{
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'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
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'profit_ratio': [0.1, 0.2, -0.05],
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'profit_abs': [0.2, 0.4, -0.1],
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'trade_duration': [10, 30, 20],
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}
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)
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result_str = (
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'| Pair | Entries | Avg Profit % | Cum Profit % | Tot Profit BTC | '
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'Tot Profit % | Avg Duration | Win Draw Loss Win% |\n'
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'|---------+-----------+----------------+----------------+------------------+'
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'----------------+----------------+-------------------------|\n'
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'| ETH/BTC | 3 | 8.33 | 25.00 | 0.50000000 | '
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'12.50 | 0:20:00 | 2 0 1 66.7 |\n'
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'| TOTAL | 3 | 8.33 | 25.00 | 0.50000000 | '
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'12.50 | 0:20:00 | 2 0 1 66.7 |'
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)
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pair_results = generate_pair_metrics(['ETH/BTC'], stake_currency='BTC',
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starting_balance=4, results=results)
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assert text_table_bt_results(pair_results, stake_currency='BTC') == result_str
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def test_generate_backtest_stats(default_conf, testdatadir, tmpdir):
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default_conf.update({'strategy': CURRENT_TEST_STRATEGY})
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StrategyResolver.load_strategy(default_conf)
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results = {'DefStrat': {
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'results': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
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"UNITTEST/BTC", "UNITTEST/BTC"],
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"profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780],
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"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
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"open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
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Arrow(2017, 11, 14, 21, 36, 00).datetime,
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Arrow(2017, 11, 14, 22, 12, 00).datetime,
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Arrow(2017, 11, 14, 22, 44, 00).datetime],
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"close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
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Arrow(2017, 11, 14, 22, 10, 00).datetime,
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Arrow(2017, 11, 14, 22, 43, 00).datetime,
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Arrow(2017, 11, 14, 22, 58, 00).datetime],
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"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
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"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
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"trade_duration": [123, 34, 31, 14],
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"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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}),
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'config': default_conf,
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'locks': [],
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'final_balance': 1000.02,
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'rejected_signals': 20,
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'timedout_entry_orders': 0,
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'timedout_exit_orders': 0,
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'canceled_trade_entries': 0,
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'canceled_entry_orders': 0,
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'replaced_entry_orders': 0,
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'backtest_start_time': Arrow.utcnow().int_timestamp,
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'backtest_end_time': Arrow.utcnow().int_timestamp,
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'run_id': '123',
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}
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}
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timerange = TimeRange.parse_timerange('1510688220-1510700340')
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min_date = Arrow.fromtimestamp(1510688220)
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max_date = Arrow.fromtimestamp(1510700340)
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btdata = history.load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
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fill_up_missing=True)
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stats = generate_backtest_stats(btdata, results, min_date, max_date)
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assert isinstance(stats, dict)
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assert 'strategy' in stats
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assert 'DefStrat' in stats['strategy']
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assert 'strategy_comparison' in stats
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strat_stats = stats['strategy']['DefStrat']
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assert strat_stats['backtest_start'] == min_date.strftime(DATETIME_PRINT_FORMAT)
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assert strat_stats['backtest_end'] == max_date.strftime(DATETIME_PRINT_FORMAT)
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assert strat_stats['total_trades'] == len(results['DefStrat']['results'])
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# Above sample had no loosing trade
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assert strat_stats['max_drawdown_account'] == 0.0
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# Retry with losing trade
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results = {'DefStrat': {
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'results': pd.DataFrame(
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{"pair": ["UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC"],
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"profit_ratio": [0.003312, 0.010801, -0.013803, 0.002780],
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"profit_abs": [0.000003, 0.000011, -0.000014, 0.000003],
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"open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
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Arrow(2017, 11, 14, 21, 36, 00).datetime,
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Arrow(2017, 11, 14, 22, 12, 00).datetime,
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Arrow(2017, 11, 14, 22, 44, 00).datetime],
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"close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
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Arrow(2017, 11, 14, 22, 10, 00).datetime,
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Arrow(2017, 11, 14, 22, 43, 00).datetime,
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Arrow(2017, 11, 14, 22, 58, 00).datetime],
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"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
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"close_rate": [0.002546, 0.003014, 0.0032903, 0.003217],
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"trade_duration": [123, 34, 31, 14],
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"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.ROI,
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ExitType.STOP_LOSS, ExitType.FORCE_EXIT]
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}),
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'config': default_conf,
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'locks': [],
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'final_balance': 1000.02,
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'rejected_signals': 20,
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'timedout_entry_orders': 0,
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'timedout_exit_orders': 0,
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'canceled_trade_entries': 0,
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'canceled_entry_orders': 0,
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'replaced_entry_orders': 0,
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'backtest_start_time': Arrow.utcnow().int_timestamp,
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'backtest_end_time': Arrow.utcnow().int_timestamp,
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'run_id': '124',
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}
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}
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stats = generate_backtest_stats(btdata, results, min_date, max_date)
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assert isinstance(stats, dict)
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assert 'strategy' in stats
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assert 'DefStrat' in stats['strategy']
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assert 'strategy_comparison' in stats
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strat_stats = stats['strategy']['DefStrat']
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assert pytest.approx(strat_stats['max_drawdown_account']) == 1.399999e-08
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assert strat_stats['drawdown_start'] == '2017-11-14 22:10:00'
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assert strat_stats['drawdown_end'] == '2017-11-14 22:43:00'
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assert strat_stats['drawdown_end_ts'] == 1510699380000
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assert strat_stats['drawdown_start_ts'] == 1510697400000
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assert strat_stats['pairlist'] == ['UNITTEST/BTC']
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# Test storing stats
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filename = Path(tmpdir / 'btresult.json')
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filename_last = Path(tmpdir / LAST_BT_RESULT_FN)
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_backup_file(filename_last, copy_file=True)
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assert not filename.is_file()
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store_backtest_stats(filename, stats, '2022_01_01_15_05_13')
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# get real Filename (it's btresult-<date>.json)
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last_fn = get_latest_backtest_filename(filename_last.parent)
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assert re.match(r"btresult-.*\.json", last_fn)
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filename1 = Path(tmpdir / last_fn)
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assert filename1.is_file()
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content = filename1.read_text()
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assert 'max_drawdown_account' in content
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assert 'strategy' in content
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assert 'pairlist' in content
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assert filename_last.is_file()
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_clean_test_file(filename_last)
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filename1.unlink()
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def test_store_backtest_stats(testdatadir, mocker):
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dump_mock = mocker.patch('freqtrade.optimize.optimize_reports.file_dump_json')
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store_backtest_stats(testdatadir, {'metadata': {}}, '2022_01_01_15_05_13')
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assert dump_mock.call_count == 3
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assert isinstance(dump_mock.call_args_list[0][0][0], Path)
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assert str(dump_mock.call_args_list[0][0][0]).startswith(str(testdatadir / 'backtest-result'))
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dump_mock.reset_mock()
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filename = testdatadir / 'testresult.json'
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store_backtest_stats(filename, {'metadata': {}}, '2022_01_01_15_05_13')
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assert dump_mock.call_count == 3
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assert isinstance(dump_mock.call_args_list[0][0][0], Path)
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# result will be testdatadir / testresult-<timestamp>.json
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assert str(dump_mock.call_args_list[0][0][0]).startswith(str(testdatadir / 'testresult'))
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def test_store_backtest_candles(testdatadir, mocker):
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dump_mock = mocker.patch('freqtrade.optimize.optimize_reports.file_dump_joblib')
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candle_dict = {'DefStrat': {'UNITTEST/BTC': pd.DataFrame()}}
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# mock directory exporting
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store_backtest_signal_candles(testdatadir, candle_dict, '2022_01_01_15_05_13')
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assert dump_mock.call_count == 1
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assert isinstance(dump_mock.call_args_list[0][0][0], Path)
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assert str(dump_mock.call_args_list[0][0][0]).endswith(str('_signals.pkl'))
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dump_mock.reset_mock()
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# mock file exporting
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filename = Path(testdatadir / 'testresult')
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store_backtest_signal_candles(filename, candle_dict, '2022_01_01_15_05_13')
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assert dump_mock.call_count == 1
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assert isinstance(dump_mock.call_args_list[0][0][0], Path)
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# result will be testdatadir / testresult-<timestamp>_signals.pkl
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assert str(dump_mock.call_args_list[0][0][0]).endswith(str('_signals.pkl'))
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dump_mock.reset_mock()
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def test_write_read_backtest_candles(tmpdir):
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candle_dict = {'DefStrat': {'UNITTEST/BTC': pd.DataFrame()}}
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# test directory exporting
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stored_file = store_backtest_signal_candles(Path(tmpdir), candle_dict, '2022_01_01_15_05_13')
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scp = open(stored_file, "rb")
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pickled_signal_candles = joblib.load(scp)
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scp.close()
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assert pickled_signal_candles.keys() == candle_dict.keys()
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assert pickled_signal_candles['DefStrat'].keys() == pickled_signal_candles['DefStrat'].keys()
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assert pickled_signal_candles['DefStrat']['UNITTEST/BTC'] \
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.equals(pickled_signal_candles['DefStrat']['UNITTEST/BTC'])
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_clean_test_file(stored_file)
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# test file exporting
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filename = Path(tmpdir / 'testresult')
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stored_file = store_backtest_signal_candles(filename, candle_dict, '2022_01_01_15_05_13')
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scp = open(stored_file, "rb")
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pickled_signal_candles = joblib.load(scp)
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scp.close()
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assert pickled_signal_candles.keys() == candle_dict.keys()
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assert pickled_signal_candles['DefStrat'].keys() == pickled_signal_candles['DefStrat'].keys()
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assert pickled_signal_candles['DefStrat']['UNITTEST/BTC'] \
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.equals(pickled_signal_candles['DefStrat']['UNITTEST/BTC'])
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_clean_test_file(stored_file)
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def test_generate_pair_metrics():
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results = pd.DataFrame(
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{
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'pair': ['ETH/BTC', 'ETH/BTC'],
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'profit_ratio': [0.1, 0.2],
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'profit_abs': [0.2, 0.4],
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'trade_duration': [10, 30],
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'wins': [2, 0],
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'draws': [0, 0],
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'losses': [0, 0]
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}
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)
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pair_results = generate_pair_metrics(['ETH/BTC'], stake_currency='BTC',
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starting_balance=2, results=results)
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assert isinstance(pair_results, list)
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assert len(pair_results) == 2
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assert pair_results[-1]['key'] == 'TOTAL'
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assert (
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pytest.approx(pair_results[-1]['profit_mean_pct']) == pair_results[-1]['profit_mean'] * 100)
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assert (
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pytest.approx(pair_results[-1]['profit_sum_pct']) == pair_results[-1]['profit_sum'] * 100)
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def test_generate_daily_stats(testdatadir):
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filename = testdatadir / "backtest_results/backtest-result_new.json"
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bt_data = load_backtest_data(filename)
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res = generate_daily_stats(bt_data)
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assert isinstance(res, dict)
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assert round(res['backtest_best_day'], 4) == 0.1796
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assert round(res['backtest_worst_day'], 4) == -0.1468
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assert res['winning_days'] == 19
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assert res['draw_days'] == 0
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assert res['losing_days'] == 2
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# Select empty dataframe!
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res = generate_daily_stats(bt_data.loc[bt_data['open_date'] == '2000-01-01', :])
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assert isinstance(res, dict)
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assert round(res['backtest_best_day'], 4) == 0.0
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assert res['winning_days'] == 0
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assert res['draw_days'] == 0
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assert res['losing_days'] == 0
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def test_generate_trading_stats(testdatadir):
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filename = testdatadir / "backtest_results/backtest-result_new.json"
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bt_data = load_backtest_data(filename)
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res = generate_trading_stats(bt_data)
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assert isinstance(res, dict)
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assert res['winner_holding_avg'] == timedelta(seconds=1440)
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assert res['loser_holding_avg'] == timedelta(days=1, seconds=21420)
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assert 'wins' in res
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assert 'losses' in res
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assert 'draws' in res
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# Select empty dataframe!
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res = generate_trading_stats(bt_data.loc[bt_data['open_date'] == '2000-01-01', :])
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assert res['wins'] == 0
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assert res['losses'] == 0
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def test_text_table_exit_reason():
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results = pd.DataFrame(
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{
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'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
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'profit_ratio': [0.1, 0.2, -0.1],
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'profit_abs': [0.2, 0.4, -0.2],
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'trade_duration': [10, 30, 10],
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'wins': [2, 0, 0],
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'draws': [0, 0, 0],
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'losses': [0, 0, 1],
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'exit_reason': [ExitType.ROI, ExitType.ROI, ExitType.STOP_LOSS]
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}
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)
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result_str = (
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'| Exit Reason | Exits | Win Draws Loss Win% | Avg Profit % | Cum Profit % |'
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' Tot Profit BTC | Tot Profit % |\n'
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'|---------------+---------+--------------------------+----------------+----------------+'
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'------------------+----------------|\n'
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'| roi | 2 | 2 0 0 100 | 15 | 30 |'
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' 0.6 | 15 |\n'
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'| stop_loss | 1 | 0 0 1 0 | -10 | -10 |'
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' -0.2 | -5 |'
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)
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exit_reason_stats = generate_exit_reason_stats(max_open_trades=2,
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results=results)
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assert text_table_exit_reason(exit_reason_stats=exit_reason_stats,
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stake_currency='BTC') == result_str
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def test_generate_sell_reason_stats():
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results = pd.DataFrame(
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{
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'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
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'profit_ratio': [0.1, 0.2, -0.1],
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'profit_abs': [0.2, 0.4, -0.2],
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'trade_duration': [10, 30, 10],
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'wins': [2, 0, 0],
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'draws': [0, 0, 0],
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'losses': [0, 0, 1],
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'exit_reason': [ExitType.ROI.value, ExitType.ROI.value, ExitType.STOP_LOSS.value]
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}
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)
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exit_reason_stats = generate_exit_reason_stats(max_open_trades=2,
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results=results)
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roi_result = exit_reason_stats[0]
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assert roi_result['exit_reason'] == 'roi'
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assert roi_result['trades'] == 2
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assert pytest.approx(roi_result['profit_mean']) == 0.15
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assert roi_result['profit_mean_pct'] == round(roi_result['profit_mean'] * 100, 2)
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assert pytest.approx(roi_result['profit_mean']) == 0.15
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assert roi_result['profit_mean_pct'] == round(roi_result['profit_mean'] * 100, 2)
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stop_result = exit_reason_stats[1]
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assert stop_result['exit_reason'] == 'stop_loss'
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assert stop_result['trades'] == 1
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assert pytest.approx(stop_result['profit_mean']) == -0.1
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assert stop_result['profit_mean_pct'] == round(stop_result['profit_mean'] * 100, 2)
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assert pytest.approx(stop_result['profit_mean']) == -0.1
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assert stop_result['profit_mean_pct'] == round(stop_result['profit_mean'] * 100, 2)
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def test_text_table_strategy(testdatadir):
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filename = testdatadir / "backtest_results/backtest-result_multistrat.json"
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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_new.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_new.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
|