380 lines
16 KiB
Python
380 lines
16 KiB
Python
import datetime
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import re
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from datetime import timedelta
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from pathlib import Path
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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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from freqtrade.edge import PairInfo
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from freqtrade.optimize.optimize_reports import (generate_backtest_stats, generate_daily_stats,
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generate_edge_table, generate_pair_metrics,
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generate_sell_reason_stats,
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generate_strategy_comparison,
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generate_trading_stats, store_backtest_stats,
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text_table_bt_results, text_table_sell_reason,
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text_table_strategy)
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from freqtrade.resolvers.strategy_resolver import StrategyResolver
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from freqtrade.strategy.interface import SellType
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from tests.data.test_history import _backup_file, _clean_test_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 | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % |'
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' 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 | 12.50 |'
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' 0:20:00 | 2 0 1 66.7 |\n'
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'| TOTAL | 3 | 8.33 | 25.00 | 0.50000000 | 12.50 |'
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' 0:20:00 | 2 0 1 66.7 |'
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)
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pair_results = generate_pair_metrics(data={'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):
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default_conf.update({'strategy': 'DefaultStrategy'})
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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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"stake_amount": [0.01, 0.01, 0.01, 0.01],
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"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
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SellType.ROI, SellType.FORCE_SELL]
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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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'backtest_start_time': Arrow.utcnow().int_timestamp,
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'backtest_end_time': Arrow.utcnow().int_timestamp,
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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'] == 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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"stake_amount": [0.01, 0.01, 0.01, 0.01],
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"sell_reason": [SellType.ROI, SellType.ROI,
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SellType.STOP_LOSS, SellType.FORCE_SELL]
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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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'backtest_start_time': Arrow.utcnow().int_timestamp,
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'backtest_end_time': Arrow.utcnow().int_timestamp,
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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 strat_stats['max_drawdown'] == 0.013803
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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(testdatadir / 'btresult.json')
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filename_last = Path(testdatadir / 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)
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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 = (testdatadir / 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' 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, {})
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assert dump_mock.call_count == 2
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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, {})
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assert dump_mock.call_count == 2
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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_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(data={'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-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'] == 14
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assert res['draw_days'] == 4
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assert res['losing_days'] == 3
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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-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_sell_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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'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
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}
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)
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result_str = (
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'| Sell Reason | Sells | 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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sell_reason_stats = generate_sell_reason_stats(max_open_trades=2,
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results=results)
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assert text_table_sell_reason(sell_reason_stats=sell_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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'sell_reason': [SellType.ROI.value, SellType.ROI.value, SellType.STOP_LOSS.value]
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}
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)
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sell_reason_stats = generate_sell_reason_stats(max_open_trades=2,
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results=results)
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roi_result = sell_reason_stats[0]
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assert roi_result['sell_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 = sell_reason_stats[1]
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assert stop_result['sell_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(default_conf):
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default_conf['max_open_trades'] = 2
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default_conf['dry_run_wallet'] = 3
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results = {}
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date = datetime.datetime(year=2020, month=1, day=1, hour=12, minute=30)
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delta = datetime.timedelta(days=1)
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results['TestStrategy1'] = {'results': pd.DataFrame(
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{
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'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
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'close_date': [date, date + delta, date + delta * 2],
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'profit_ratio': [0.1, 0.2, 0.3],
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'profit_abs': [0.2, 0.4, 0.5],
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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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'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
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}
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), 'config': default_conf}
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results['TestStrategy2'] = {'results': pd.DataFrame(
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{
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'pair': ['LTC/BTC', 'LTC/BTC', 'LTC/BTC'],
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'close_date': [date, date + delta, date + delta * 2],
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'profit_ratio': [0.4, 0.2, 0.3],
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'profit_abs': [0.4, 0.4, 0.5],
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'trade_duration': [15, 30, 15],
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'wins': [4, 1, 0],
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'draws': [0, 0, 0],
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'losses': [0, 0, 1],
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'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
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}
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), 'config': default_conf}
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result_str = (
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'| Strategy | Buys | Avg Profit % | Cum Profit % | Tot Profit BTC |'
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' Tot Profit % | Avg Duration | Win Draw Loss Win% | Drawdown |\n'
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'|---------------+--------+----------------+----------------+------------------+'
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'----------------+----------------+-------------------------+-----------------------|\n'
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'| TestStrategy1 | 3 | 20.00 | 60.00 | 1.10000000 |'
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' 36.67 | 0:17:00 | 3 0 0 100 | 0.00000000 BTC 0.00% |\n'
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'| TestStrategy2 | 3 | 30.00 | 90.00 | 1.30000000 |'
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' 43.33 | 0:20:00 | 3 0 0 100 | 0.00000000 BTC 0.00% |'
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)
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strategy_results = generate_strategy_comparison(all_results=results)
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assert text_table_strategy(strategy_results, 'BTC') == result_str
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def test_generate_edge_table():
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results = {}
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results['ETH/BTC'] = PairInfo(-0.01, 0.60, 2, 1, 3, 10, 60)
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assert generate_edge_table(results).count('+') == 7
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assert generate_edge_table(results).count('| ETH/BTC |') == 1
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assert generate_edge_table(results).count(
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'| Risk Reward Ratio | Required Risk Reward | Expectancy |') == 1
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