78 lines
3.5 KiB
Python
78 lines
3.5 KiB
Python
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# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
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import logging
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from unittest.mock import MagicMock
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import pandas as pd
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import pytest
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from arrow import get as getdate
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from freqtrade.optimize.backtesting import Backtesting
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from freqtrade.tests.conftest import patch_exchange, log_has
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columns = ['date', 'open', 'high', 'low', 'close', 'volume', 'buy', 'sell']
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data_profit = pd.DataFrame([[getdate('2018-07-08 18:00:00').datetime,
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0.0009910, 0.001011, 0.00098618, 0.001000, 47027.0, 1, 0],
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[getdate('2018-07-08 19:00:00').datetime,
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0.001000, 0.001010, 0.0009900, 0.0009900, 87116.0, 0, 0],
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[getdate('2018-07-08 20:00:00').datetime,
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0.0009900, 0.001011, 0.00091618, 0.0009900, 58539.0, 0, 0],
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[getdate('2018-07-08 21:00:00').datetime,
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0.001000, 0.001011, 0.00098618, 0.001100, 37498.0, 0, 1],
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[getdate('2018-07-08 22:00:00').datetime,
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0.001000, 0.001011, 0.00098618, 0.0009900, 59792.0, 0, 0]],
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columns=columns)
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data_loss = pd.DataFrame([[getdate('2018-07-08 18:00:00').datetime,
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0.0009910, 0.001011, 0.00098618, 0.001000, 47027.0, 1, 0],
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[getdate('2018-07-08 19:00:00').datetime,
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0.001000, 0.001010, 0.0009900, 0.001000, 87116.0, 0, 0],
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[getdate('2018-07-08 20:00:00').datetime,
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0.001000, 0.001011, 0.0010618, 0.00091618, 58539.0, 0, 0],
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[getdate('2018-07-08 21:00:00').datetime,
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0.001000, 0.001011, 0.00098618, 0.00091618, 37498.0, 0, 0],
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[getdate('2018-07-08 22:00:00').datetime,
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0.001000, 0.001011, 0.00098618, 0.00091618, 59792.0, 0, 0]],
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columns=columns)
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@pytest.mark.parametrize("data, stoploss, tradecount, profit_perc, sl", [
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(data_profit, -0.01, 1, 0.10557, False), # should be stoploss - drops 8%
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# (data_profit, -0.10, 1, 0.10557, True), # win
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(data_loss, -0.05, 1, -0.08839, True), # Stoploss ...
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])
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def test_backtest_results(default_conf, fee, mocker, caplog,
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data, stoploss, tradecount, profit_perc, sl) -> None:
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"""
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run functional tests
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"""
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default_conf["stoploss"] = stoploss
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mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
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mocker.patch('freqtrade.analyze.Analyze.populate_sell_trend', MagicMock(return_value=data))
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mocker.patch('freqtrade.analyze.Analyze.populate_buy_trend', MagicMock(return_value=data))
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patch_exchange(mocker)
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backtesting = Backtesting(default_conf)
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caplog.set_level(logging.DEBUG)
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pair = 'UNITTEST/BTC'
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# Dummy data as we mock the analyze functions
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data_processed = {pair: pd.DataFrame()}
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results = backtesting.backtest(
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{
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'stake_amount': default_conf['stake_amount'],
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'processed': data_processed,
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'max_open_trades': 10,
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'realistic': True
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}
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)
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print(results.T)
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assert len(results) == tradecount
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assert round(results["profit_percent"].sum(), 5) == profit_perc
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if sl:
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assert log_has("Stop loss hit.", caplog.record_tuples)
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else:
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assert not log_has("Stop loss hit.", caplog.record_tuples)
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