diff --git a/tests/optimize/test_hyperopt.py b/tests/optimize/test_hyperopt.py index cd405c52f..1b1aaebad 100644 --- a/tests/optimize/test_hyperopt.py +++ b/tests/optimize/test_hyperopt.py @@ -5,7 +5,7 @@ import re from datetime import datetime from pathlib import Path from typing import Dict, List -from unittest.mock import MagicMock +from unittest.mock import ANY, MagicMock import pandas as pd import pytest @@ -18,10 +18,12 @@ from freqtrade.exceptions import OperationalException from freqtrade.optimize.hyperopt import Hyperopt from freqtrade.optimize.hyperopt_auto import HyperOptAuto from freqtrade.optimize.hyperopt_tools import HyperoptTools +from freqtrade.optimize.optimize_reports import generate_strategy_stats from freqtrade.optimize.space import SKDecimal from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver from freqtrade.state import RunMode from freqtrade.strategy.hyper import IntParameter +from freqtrade.strategy.interface import SellType from tests.conftest import (get_args, log_has, log_has_re, patch_exchange, patched_configuration_load_config_file) @@ -433,18 +435,41 @@ def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None: assert hasattr(hyperopt, "position_stacking") -def test_format_results(hyperopt): - # Test with BTC as stake_currency - trades = [ - ('ETH/BTC', 2, 2, 123), - ('LTC/BTC', 1, 1, 123), - ('XPR/BTC', -1, -2, -246) - ] - labels = ['currency', 'profit_ratio', 'profit_abs', 'trade_duration'] - df = pd.DataFrame.from_records(trades, columns=labels) - results_metrics = hyperopt._calculate_results_metrics(df) +def test_hyperopt_format_results(hyperopt): + + bt_result = { + '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], + "stake_amount": [0.01, 0.01, 0.01, 0.01], + "sell_reason": [SellType.ROI, SellType.STOP_LOSS, + SellType.ROI, SellType.FORCE_SELL] + }), + 'config': hyperopt.config, + 'locks': [], + 'final_balance': 0.02, + 'backtest_start_time': 1619718665, + 'backtest_end_time': 1619718665, + } + results_metrics = generate_strategy_stats({'XRP/BTC': None}, '', bt_result, + Arrow(2017, 11, 14, 19, 32, 00), + Arrow(2017, 12, 14, 19, 32, 00), market_change=0) + results_explanation = hyperopt._format_results_explanation_string(results_metrics) - total_profit = results_metrics['total_profit'] + total_profit = results_metrics['profit_total_abs'] results = { 'loss': 0.0, @@ -458,21 +483,9 @@ def test_format_results(hyperopt): } result = HyperoptTools._format_explanation_string(results, 1) - assert result.find(' 66.67%') - assert result.find('Total profit 1.00000000 BTC') - assert result.find('2.0000Σ %') - - # Test with EUR as stake_currency - trades = [ - ('ETH/EUR', 2, 2, 123), - ('LTC/EUR', 1, 1, 123), - ('XPR/EUR', -1, -2, -246) - ] - df = pd.DataFrame.from_records(trades, columns=labels) - results_metrics = hyperopt._calculate_results_metrics(df) - results['total_profit'] = results_metrics['total_profit'] - result = HyperoptTools._format_explanation_string(results, 1) - assert result.find('Total profit 1.00000000 EUR') + assert ' 0.71%' in result + assert 'Total profit 0.00003100 BTC' in result + assert '0:50:00 min' in result @pytest.mark.parametrize("spaces, expected_results", [ @@ -577,22 +590,32 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None: 'hyperopt_min_trades': 1, }) - trades = [ - ('TRX/BTC', 0.023117, 0.000233, 100) - ] - labels = ['currency', 'profit_ratio', 'profit_abs', 'trade_duration'] - backtest_result = pd.DataFrame.from_records(trades, columns=labels) + backtest_result = 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], + "stake_amount": [0.01, 0.01, 0.01, 0.01], + "sell_reason": [SellType.ROI, SellType.STOP_LOSS, + SellType.ROI, SellType.FORCE_SELL] + }) - mocker.patch( - 'freqtrade.optimize.hyperopt.Backtesting.backtest', - MagicMock(return_value=backtest_result) - ) - mocker.patch( - 'freqtrade.optimize.hyperopt.get_timerange', - MagicMock(return_value=(Arrow(2017, 12, 10), Arrow(2017, 12, 13))) - ) + mocker.patch('freqtrade.optimize.hyperopt.Backtesting.backtest', return_value=backtest_result) + mocker.patch('freqtrade.optimize.hyperopt.get_timerange', + return_value=(Arrow(2017, 12, 10), Arrow(2017, 12, 13))) patch_exchange(mocker) - mocker.patch('freqtrade.optimize.hyperopt.load', MagicMock()) + mocker.patch('freqtrade.optimize.hyperopt.load', return_value={'XRP/BTC': None}) optimizer_param = { 'adx-value': 0, @@ -626,11 +649,11 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None: 'trailing_only_offset_is_reached': False, } response_expected = { - 'loss': 1.9840569076926293, - 'results_explanation': (' 1 trades. 1/0/0 Wins/Draws/Losses. ' - 'Avg profit 2.31%. Median profit 2.31%. Total profit ' - '0.00023300 BTC ( 2.31\N{GREEK CAPITAL LETTER SIGMA}%). ' - 'Avg duration 100.0 min.' + 'loss': 1.9147239021396234, + 'results_explanation': (' 4 trades. 4/0/0 Wins/Draws/Losses. ' + 'Avg profit 0.77%. Median profit 0.71%. Total profit ' + '0.00003100 BTC ( 0.00\N{GREEK CAPITAL LETTER SIGMA}%). ' + 'Avg duration 0:50:00 min.' ).encode(locale.getpreferredencoding(), 'replace').decode('utf-8'), 'params_details': {'buy': {'adx-enabled': False, 'adx-value': 0, @@ -660,17 +683,8 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None: 'trailing_stop_positive': 0.02, 'trailing_stop_positive_offset': 0.07}}, 'params_dict': optimizer_param, - 'results_metrics': {'avg_profit': 2.3117, - 'draws': 0, - 'duration': 100.0, - 'losses': 0, - 'winsdrawslosses': ' 1 0 0', - 'median_profit': 2.3117, - 'profit': 2.3117, - 'total_profit': 0.000233, - 'trade_count': 1, - 'wins': 1}, - 'total_profit': 0.00023300 + 'results_metrics': ANY, + 'total_profit': 3.1e-08 } hyperopt = Hyperopt(hyperopt_conf) diff --git a/tests/optimize/test_optimize_reports.py b/tests/optimize/test_optimize_reports.py index b268ebadc..fb4624ca3 100644 --- a/tests/optimize/test_optimize_reports.py +++ b/tests/optimize/test_optimize_reports.py @@ -14,7 +14,8 @@ 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_comparison, generate_trading_stats, store_backtest_stats, + generate_strategy_comparison, + generate_trading_stats, store_backtest_stats, text_table_bt_results, text_table_sell_reason, text_table_strategy) from freqtrade.resolvers.strategy_resolver import StrategyResolver