# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument import logging from unittest.mock import MagicMock from pandas import DataFrame import pytest from freqtrade.optimize.backtesting import Backtesting from freqtrade.strategy.interface import SellType from freqtrade.tests.optimize import (BTrade, BTContainer, _build_backtest_dataframe, _get_frame_time_from_offset) from freqtrade.tests.conftest import patch_exchange # Test 0 Minus 8% Close # Test with Stop-loss at 1% # TC1: Stop-Loss Triggered 1% loss tc0 = BTContainer(data=[ [0, 10000.0, 10050, 9950, 9975, 12345, 1, 0], [1, 10000, 10050, 9950, 9975, 12345, 0, 0], # enter trade (signal on last candle) [2, 9975, 10025, 9200, 9200, 12345, 0, 0], # exit with stoploss hit [3, 9950, 10000, 9960, 9955, 12345, 0, 0], [4, 9955, 9975, 9955, 9990, 12345, 0, 0], [5, 9990, 9990, 9990, 9900, 12345, 0, 0]], stop_loss=-0.01, roi=1, profit_perc=-0.01, trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)] ) # Test 1 Minus 4% Low, minus 1% close # Test with Stop-Loss at 3% # TC2: Stop-Loss Triggered 3% Loss tc1 = BTContainer(data=[ [0, 10000, 10050, 9950, 9975, 12345, 1, 0], [1, 10000, 10050, 9950, 9975, 12345, 0, 0], # enter trade (signal on last candle) [2, 9975, 10025, 9925, 9950, 12345, 0, 0], [3, 9950, 10000, 9600, 9925, 12345, 0, 0], # exit with stoploss hit [4, 9925, 9975, 9875, 9900, 12345, 0, 0], [5, 9900, 9950, 9850, 9900, 12345, 0, 0]], stop_loss=-0.03, roi=1, profit_perc=-0.03, trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=3)] ) # Test 3 Candle drops 4%, Recovers 1%. # Entry Criteria Met # Candle drops 20% # Candle Data for test 3 # Test with Stop-Loss at 2% # TC3: Trade-A: Stop-Loss Triggered 2% Loss # Trade-B: Stop-Loss Triggered 2% Loss tc2 = BTContainer(data=[ [0, 10000, 10050, 9950, 9975, 12345, 1, 0], [1, 10000, 10050, 9950, 9975, 12345, 0, 0], # enter trade (signal on last candle) [2, 9975, 10025, 9600, 9950, 12345, 0, 0], # exit with stoploss hit [3, 9950, 10000, 9900, 9925, 12345, 1, 0], [4, 9950, 10000, 9900, 9925, 12345, 0, 0], # enter trade 2 (signal on last candle) [5, 9925, 9975, 8000, 8000, 12345, 0, 0], # exit with stoploss hit [6, 9900, 9950, 9950, 9900, 12345, 0, 0]], stop_loss=-0.02, roi=1, profit_perc=-0.04, trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2), BTrade(sell_reason=SellType.STOP_LOSS, open_tick=4, close_tick=5)] ) # Test 4 Minus 3% / recovery +15% # Candle Data for test 3 – Candle drops 3% Closed 15% up # Test with Stop-loss at 2% ROI 6% # TC4: Stop-Loss Triggered 2% Loss tc3 = BTContainer(data=[ [0, 10000, 10050, 9950, 9975, 12345, 1, 0], [1, 10000, 10050, 9950, 9975, 12345, 0, 0], # enter trade (signal on last candle) [2, 9975, 11500, 9700, 11500, 12345, 0, 0], # Exit with stoploss hit [3, 9950, 10000, 9900, 9925, 12345, 0, 0], [4, 9925, 9975, 9875, 9900, 12345, 0, 0], [5, 9900, 9950, 9850, 9900, 12345, 0, 0]], stop_loss=-0.02, roi=0.06, profit_perc=-0.02, trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)] ) # Test 4 / Drops 0.5% Closes +20% # Set stop-loss at 1% ROI 3% # TC5: ROI triggers 3% Gain tc4 = BTContainer(data=[ [0, 10000, 10050, 9960, 9975, 12345, 1, 0], [1, 10000, 10050, 9960, 9975, 12345, 0, 0], # enter trade (signal on last candle) [2, 9975, 10050, 9950, 9975, 12345, 0, 0], [3, 9950, 12000, 9950, 12000, 12345, 0, 0], # ROI [4, 9925, 9975, 9945, 9900, 12345, 0, 0], [5, 9900, 9950, 9850, 9900, 12345, 0, 0]], stop_loss=-0.01, roi=0.03, profit_perc=0.03, trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)] ) # Test 6 / Drops 3% / Recovers 6% Positive / Closes 1% positve # Candle Data for test 6 # Set stop-loss at 2% ROI at 5% # TC6: Stop-Loss triggers 2% Loss tc5 = BTContainer(data=[ [0, 10000, 10050, 9950, 9975, 12345, 1, 0], [1, 10000, 10050, 9950, 9975, 12345, 0, 0], # enter trade (signal on last candle) [2, 9975, 10600, 9700, 10100, 12345, 0, 0], # Exit with stoploss [3, 9950, 10000, 9900, 9925, 12345, 0, 0], [4, 9925, 9975, 9945, 9900, 12345, 0, 0], [5, 9900, 9950, 9850, 9900, 12345, 0, 0]], stop_loss=-0.02, roi=0.05, profit_perc=-0.02, trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)] ) # Test 7 - 6% Positive / 1% Negative / Close 1% Positve # Candle Data for test 7 # Set stop-loss at 2% ROI at 3% # TC7: ROI Triggers 3% Gain tc6 = BTContainer(data=[ [0, 10000, 10050, 9950, 9975, 12345, 1, 0], [1, 10000, 10050, 9950, 9975, 12345, 0, 0], # enter trade (signal on last candle) [2, 9975, 10600, 9900, 10100, 12345, 0, 0], # ROI [3, 9950, 10000, 9900, 9925, 12345, 0, 0], [4, 9925, 9975, 9945, 9900, 12345, 0, 0], [5, 9900, 9950, 9850, 9900, 12345, 0, 0]], stop_loss=-0.02, roi=0.03, profit_perc=0.03, trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=2)] ) TESTS = [ tc0, tc1, tc2, tc3, tc4, tc5, tc6, ] @pytest.mark.parametrize("data", TESTS) def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None: """ run functional tests """ default_conf["stoploss"] = data.stop_loss default_conf["minimal_roi"] = {"0": data.roi} mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.0)) patch_exchange(mocker) frame = _build_backtest_dataframe(data.data) backtesting = Backtesting(default_conf) backtesting.advise_buy = lambda a, m: frame backtesting.advise_sell = lambda a, m: frame caplog.set_level(logging.DEBUG) pair = 'UNITTEST/BTC' # Dummy data as we mock the analyze functions data_processed = {pair: DataFrame()} results = backtesting.backtest( { 'stake_amount': default_conf['stake_amount'], 'processed': data_processed, 'max_open_trades': 10, } ) print(results.T) assert len(results) == len(data.trades) assert round(results["profit_percent"].sum(), 3) == round(data.profit_perc, 3) # if data.sell_r == SellType.STOP_LOSS: # assert log_has("Stop loss hit.", caplog.record_tuples) # else: # assert not log_has("Stop loss hit.", caplog.record_tuples) # log_test = (f'Force_selling still open trade UNITTEST/BTC with ' # f'{results.iloc[-1].profit_percent} perc - {results.iloc[-1].profit_abs}') # if data.sell_r == SellType.FORCE_SELL: # assert log_has(log_test, # caplog.record_tuples) # else: # assert not log_has(log_test, # caplog.record_tuples) for c, trade in enumerate(data.trades): res = results.iloc[c] assert res.sell_reason == trade.sell_reason assert res.open_time == _get_frame_time_from_offset(trade.open_tick) assert res.close_time == _get_frame_time_from_offset(trade.close_tick)