862 lines
33 KiB
Python
862 lines
33 KiB
Python
# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
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import random
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from pathlib import Path
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from unittest.mock import MagicMock
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import numpy as np
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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 import DependencyException, OperationalException, constants
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from freqtrade.configuration import TimeRange
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from freqtrade.data import history
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from freqtrade.data.btanalysis import evaluate_result_multi
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from freqtrade.data.converter import clean_ohlcv_dataframe
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from freqtrade.data.dataprovider import DataProvider
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from freqtrade.data.history import get_timerange
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from freqtrade.optimize import setup_configuration, start_backtesting
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from freqtrade.optimize.backtesting import Backtesting
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from freqtrade.state import RunMode
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from freqtrade.strategy.default_strategy import DefaultStrategy
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from freqtrade.strategy.interface import SellType
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from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
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patched_configuration_load_config_file)
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ORDER_TYPES = [
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{
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'buy': 'limit',
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'sell': 'limit',
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'stoploss': 'limit',
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'stoploss_on_exchange': False
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},
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{
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'buy': 'limit',
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'sell': 'limit',
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'stoploss': 'limit',
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'stoploss_on_exchange': True
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}]
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def trim_dictlist(dict_list, num):
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new = {}
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for pair, pair_data in dict_list.items():
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new[pair] = pair_data[num:].reset_index()
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return new
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def load_data_test(what, testdatadir):
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timerange = TimeRange.parse_timerange('1510694220-1510700340')
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data = history.load_pair_history(pair='UNITTEST/BTC', datadir=testdatadir,
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timeframe='1m', timerange=timerange,
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drop_incomplete=False,
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fill_up_missing=False)
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base = 0.001
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if what == 'raise':
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data.loc[:, 'open'] = data.index * base
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data.loc[:, 'high'] = data.index * base + 0.0001
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data.loc[:, 'low'] = data.index * base - 0.0001
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data.loc[:, 'close'] = data.index * base
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if what == 'lower':
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data.loc[:, 'open'] = 1 - data.index * base
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data.loc[:, 'high'] = 1 - data.index * base + 0.0001
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data.loc[:, 'low'] = 1 - data.index * base - 0.0001
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data.loc[:, 'close'] = 1 - data.index * base
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if what == 'sine':
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hz = 0.1 # frequency
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data.loc[:, 'open'] = np.sin(data.index * hz) / 1000 + base
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data.loc[:, 'high'] = np.sin(data.index * hz) / 1000 + base + 0.0001
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data.loc[:, 'low'] = np.sin(data.index * hz) / 1000 + base - 0.0001
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data.loc[:, 'close'] = np.sin(data.index * hz) / 1000 + base
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return {'UNITTEST/BTC': clean_ohlcv_dataframe(data, timeframe='1m', pair='UNITTEST/BTC',
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fill_missing=True)}
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def simple_backtest(config, contour, num_results, mocker, testdatadir) -> None:
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patch_exchange(mocker)
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config['ticker_interval'] = '1m'
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backtesting = Backtesting(config)
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data = load_data_test(contour, testdatadir)
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processed = backtesting.strategy.tickerdata_to_dataframe(data)
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min_date, max_date = get_timerange(processed)
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assert isinstance(processed, dict)
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results = backtesting.backtest(
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{
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'stake_amount': config['stake_amount'],
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'processed': processed,
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'max_open_trades': 1,
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'position_stacking': False,
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'start_date': min_date,
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'end_date': max_date,
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}
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)
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# results :: <class 'pandas.core.frame.DataFrame'>
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assert len(results) == num_results
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# FIX: fixturize this?
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def _make_backtest_conf(mocker, datadir, conf=None, pair='UNITTEST/BTC', record=None):
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data = history.load_data(datadir=datadir, timeframe='1m', pairs=[pair])
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data = trim_dictlist(data, -201)
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patch_exchange(mocker)
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backtesting = Backtesting(conf)
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processed = backtesting.strategy.tickerdata_to_dataframe(data)
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min_date, max_date = get_timerange(processed)
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return {
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'stake_amount': conf['stake_amount'],
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'processed': processed,
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'max_open_trades': 10,
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'position_stacking': False,
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'record': record,
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'start_date': min_date,
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'end_date': max_date,
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}
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def _trend(signals, buy_value, sell_value):
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n = len(signals['low'])
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buy = np.zeros(n)
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sell = np.zeros(n)
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for i in range(0, len(signals['buy'])):
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if random.random() > 0.5: # Both buy and sell signals at same timeframe
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buy[i] = buy_value
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sell[i] = sell_value
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signals['buy'] = buy
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signals['sell'] = sell
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return signals
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def _trend_alternate(dataframe=None, metadata=None):
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signals = dataframe
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low = signals['low']
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n = len(low)
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buy = np.zeros(n)
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sell = np.zeros(n)
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for i in range(0, len(buy)):
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if i % 2 == 0:
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buy[i] = 1
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else:
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sell[i] = 1
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signals['buy'] = buy
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signals['sell'] = sell
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return dataframe
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# Unit tests
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def test_setup_configuration_without_arguments(mocker, default_conf, caplog) -> None:
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patched_configuration_load_config_file(mocker, default_conf)
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args = [
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'backtesting',
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'--config', 'config.json',
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'--strategy', 'DefaultStrategy',
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]
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config = setup_configuration(get_args(args), RunMode.BACKTEST)
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assert 'max_open_trades' in config
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assert 'stake_currency' in config
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assert 'stake_amount' in config
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assert 'exchange' in config
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assert 'pair_whitelist' in config['exchange']
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assert 'datadir' in config
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assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
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assert 'ticker_interval' in config
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assert not log_has_re('Parameter -i/--ticker-interval detected .*', caplog)
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assert 'position_stacking' not in config
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assert not log_has('Parameter --enable-position-stacking detected ...', caplog)
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assert 'timerange' not in config
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assert 'export' not in config
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assert 'runmode' in config
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assert config['runmode'] == RunMode.BACKTEST
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def test_setup_bt_configuration_with_arguments(mocker, default_conf, caplog) -> None:
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patched_configuration_load_config_file(mocker, default_conf)
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mocker.patch(
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'freqtrade.configuration.configuration.create_datadir',
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lambda c, x: x
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)
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args = [
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'backtesting',
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'--config', 'config.json',
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'--strategy', 'DefaultStrategy',
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'--datadir', '/foo/bar',
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'--ticker-interval', '1m',
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'--enable-position-stacking',
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'--disable-max-market-positions',
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'--timerange', ':100',
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'--export', '/bar/foo',
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'--export-filename', 'foo_bar.json',
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'--fee', '0',
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]
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config = setup_configuration(get_args(args), RunMode.BACKTEST)
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assert 'max_open_trades' in config
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assert 'stake_currency' in config
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assert 'stake_amount' in config
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assert 'exchange' in config
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assert 'pair_whitelist' in config['exchange']
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assert 'datadir' in config
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assert config['runmode'] == RunMode.BACKTEST
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assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
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assert 'ticker_interval' in config
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assert log_has('Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
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caplog)
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assert 'position_stacking' in config
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assert log_has('Parameter --enable-position-stacking detected ...', caplog)
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assert 'use_max_market_positions' in config
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assert log_has('Parameter --disable-max-market-positions detected ...', caplog)
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assert log_has('max_open_trades set to unlimited ...', caplog)
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assert 'timerange' in config
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assert log_has('Parameter --timerange detected: {} ...'.format(config['timerange']), caplog)
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assert 'export' in config
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assert log_has('Parameter --export detected: {} ...'.format(config['export']), caplog)
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assert 'exportfilename' in config
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assert log_has('Storing backtest results to {} ...'.format(config['exportfilename']), caplog)
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assert 'fee' in config
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assert log_has('Parameter --fee detected, setting fee to: {} ...'.format(config['fee']), caplog)
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def test_setup_configuration_unlimited_stake_amount(mocker, default_conf, caplog) -> None:
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default_conf['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
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patched_configuration_load_config_file(mocker, default_conf)
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args = [
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'backtesting',
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'--config', 'config.json',
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'--strategy', 'DefaultStrategy',
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]
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with pytest.raises(DependencyException, match=r'.*stake amount.*'):
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setup_configuration(get_args(args), RunMode.BACKTEST)
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def test_start(mocker, fee, default_conf, caplog) -> None:
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start_mock = MagicMock()
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mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
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patch_exchange(mocker)
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mocker.patch('freqtrade.optimize.backtesting.Backtesting.start', start_mock)
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patched_configuration_load_config_file(mocker, default_conf)
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args = [
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'backtesting',
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'--config', 'config.json',
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'--strategy', 'DefaultStrategy',
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]
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args = get_args(args)
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start_backtesting(args)
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assert log_has('Starting freqtrade in Backtesting mode', caplog)
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assert start_mock.call_count == 1
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@pytest.mark.parametrize("order_types", ORDER_TYPES)
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def test_backtesting_init(mocker, default_conf, order_types) -> None:
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"""
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Check that stoploss_on_exchange is set to False while backtesting
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since backtesting assumes a perfect stoploss anyway.
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"""
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default_conf["order_types"] = order_types
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patch_exchange(mocker)
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get_fee = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5))
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backtesting = Backtesting(default_conf)
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assert backtesting.config == default_conf
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assert backtesting.timeframe == '5m'
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assert callable(backtesting.strategy.tickerdata_to_dataframe)
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assert callable(backtesting.strategy.advise_buy)
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assert callable(backtesting.strategy.advise_sell)
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assert isinstance(backtesting.strategy.dp, DataProvider)
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get_fee.assert_called()
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assert backtesting.fee == 0.5
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assert not backtesting.strategy.order_types["stoploss_on_exchange"]
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def test_backtesting_init_no_ticker_interval(mocker, default_conf, caplog) -> None:
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patch_exchange(mocker)
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del default_conf['ticker_interval']
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default_conf['strategy_list'] = ['DefaultStrategy',
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'SampleStrategy']
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mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5))
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with pytest.raises(OperationalException):
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Backtesting(default_conf)
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log_has("Ticker-interval needs to be set in either configuration "
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"or as cli argument `--ticker-interval 5m`", caplog)
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def test_tickerdata_with_fee(default_conf, mocker, testdatadir) -> None:
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patch_exchange(mocker)
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default_conf['fee'] = 0.1234
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fee_mock = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5))
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backtesting = Backtesting(default_conf)
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assert backtesting.fee == 0.1234
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assert fee_mock.call_count == 0
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def test_tickerdata_to_dataframe_bt(default_conf, mocker, testdatadir) -> None:
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patch_exchange(mocker)
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timerange = TimeRange.parse_timerange('1510694220-1510700340')
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tickerlist = history.load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
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fill_up_missing=True)
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backtesting = Backtesting(default_conf)
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data = backtesting.strategy.tickerdata_to_dataframe(tickerlist)
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assert len(data['UNITTEST/BTC']) == 102
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# Load strategy to compare the result between Backtesting function and strategy are the same
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strategy = DefaultStrategy(default_conf)
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data2 = strategy.tickerdata_to_dataframe(tickerlist)
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assert data['UNITTEST/BTC'].equals(data2['UNITTEST/BTC'])
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def test_generate_text_table(default_conf, mocker):
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patch_exchange(mocker)
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default_conf['max_open_trades'] = 2
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backtesting = Backtesting(default_conf)
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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_percent': [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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'profit': [2, 0],
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'loss': [0, 0]
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}
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)
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result_str = (
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'| pair | buy count | avg profit % | cum profit % | '
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'tot profit BTC | tot profit % | avg duration | profit | loss |\n'
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'|:--------|------------:|---------------:|---------------:|'
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'-----------------:|---------------:|:---------------|---------:|-------:|\n'
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'| ETH/BTC | 2 | 15.00 | 30.00 | '
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'0.60000000 | 15.00 | 0:20:00 | 2 | 0 |\n'
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'| TOTAL | 2 | 15.00 | 30.00 | '
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'0.60000000 | 15.00 | 0:20:00 | 2 | 0 |'
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)
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assert backtesting._generate_text_table(data={'ETH/BTC': {}}, results=results) == result_str
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def test_generate_text_table_sell_reason(default_conf, mocker):
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patch_exchange(mocker)
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backtesting = Backtesting(default_conf)
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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_percent': [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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'profit': [2, 0, 0],
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'loss': [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 | Count | Profit | Loss |\n'
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'|:--------------|--------:|---------:|-------:|\n'
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'| roi | 2 | 2 | 0 |\n'
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'| stop_loss | 1 | 0 | 1 |'
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)
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assert backtesting._generate_text_table_sell_reason(
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data={'ETH/BTC': {}}, results=results) == result_str
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def test_generate_text_table_strategyn(default_conf, mocker):
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"""
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Test Backtesting.generate_text_table_sell_reason() method
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"""
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patch_exchange(mocker)
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default_conf['max_open_trades'] = 2
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backtesting = Backtesting(default_conf)
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results = {}
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results['ETH/BTC'] = pd.DataFrame(
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{
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'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
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'profit_percent': [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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'profit': [2, 0, 0],
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'loss': [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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results['LTC/BTC'] = pd.DataFrame(
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{
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'pair': ['LTC/BTC', 'LTC/BTC', 'LTC/BTC'],
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'profit_percent': [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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'profit': [4, 1, 0],
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'loss': [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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'| Strategy | buy count | avg profit % | cum profit % '
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'| tot profit BTC | tot profit % | avg duration | profit | loss |\n'
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'|:-----------|------------:|---------------:|---------------:'
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'|-----------------:|---------------:|:---------------|---------:|-------:|\n'
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'| ETH/BTC | 3 | 20.00 | 60.00 '
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'| 1.10000000 | 30.00 | 0:17:00 | 3 | 0 |\n'
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'| LTC/BTC | 3 | 30.00 | 90.00 '
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'| 1.30000000 | 45.00 | 0:20:00 | 3 | 0 |'
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)
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assert backtesting._generate_text_table_strategy(all_results=results) == result_str
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def test_backtesting_start(default_conf, mocker, testdatadir, caplog) -> None:
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def get_timerange(input1):
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return Arrow(2017, 11, 14, 21, 17), Arrow(2017, 11, 14, 22, 59)
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mocker.patch('freqtrade.data.history.get_timerange', get_timerange)
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mocker.patch('freqtrade.exchange.Exchange.refresh_latest_ohlcv', MagicMock())
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patch_exchange(mocker)
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mocker.patch.multiple(
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'freqtrade.optimize.backtesting.Backtesting',
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backtest=MagicMock(),
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_generate_text_table=MagicMock(return_value='1'),
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)
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default_conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
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default_conf['ticker_interval'] = '1m'
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default_conf['datadir'] = testdatadir
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default_conf['export'] = None
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default_conf['timerange'] = '-1510694220'
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backtesting = Backtesting(default_conf)
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backtesting.start()
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# check the logs, that will contain the backtest result
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exists = [
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'Using stake_currency: BTC ...',
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'Using stake_amount: 0.001 ...',
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'Backtesting with data from 2017-11-14T21:17:00+00:00 '
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'up to 2017-11-14T22:59:00+00:00 (0 days)..'
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]
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for line in exists:
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assert log_has(line, caplog)
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def test_backtesting_start_no_data(default_conf, mocker, caplog, testdatadir) -> None:
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def get_timerange(input1):
|
|
return Arrow(2017, 11, 14, 21, 17), Arrow(2017, 11, 14, 22, 59)
|
|
|
|
mocker.patch('freqtrade.data.history.load_pair_history', MagicMock(return_value=pd.DataFrame()))
|
|
mocker.patch('freqtrade.data.history.get_timerange', get_timerange)
|
|
mocker.patch('freqtrade.exchange.Exchange.refresh_latest_ohlcv', MagicMock())
|
|
patch_exchange(mocker)
|
|
mocker.patch.multiple(
|
|
'freqtrade.optimize.backtesting.Backtesting',
|
|
backtest=MagicMock(),
|
|
_generate_text_table=MagicMock(return_value='1'),
|
|
)
|
|
|
|
default_conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
|
|
default_conf['ticker_interval'] = "1m"
|
|
default_conf['datadir'] = testdatadir
|
|
default_conf['export'] = None
|
|
default_conf['timerange'] = '20180101-20180102'
|
|
|
|
backtesting = Backtesting(default_conf)
|
|
with pytest.raises(OperationalException, match='No data found. Terminating.'):
|
|
backtesting.start()
|
|
|
|
|
|
def test_backtest(default_conf, fee, mocker, testdatadir) -> None:
|
|
default_conf['ask_strategy']['use_sell_signal'] = False
|
|
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
|
|
patch_exchange(mocker)
|
|
backtesting = Backtesting(default_conf)
|
|
pair = 'UNITTEST/BTC'
|
|
timerange = TimeRange('date', None, 1517227800, 0)
|
|
data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=['UNITTEST/BTC'],
|
|
timerange=timerange)
|
|
data_processed = backtesting.strategy.tickerdata_to_dataframe(data)
|
|
min_date, max_date = get_timerange(data_processed)
|
|
results = backtesting.backtest(
|
|
{
|
|
'stake_amount': default_conf['stake_amount'],
|
|
'processed': data_processed,
|
|
'max_open_trades': 10,
|
|
'position_stacking': False,
|
|
'start_date': min_date,
|
|
'end_date': max_date,
|
|
}
|
|
)
|
|
assert not results.empty
|
|
assert len(results) == 2
|
|
|
|
expected = pd.DataFrame(
|
|
{'pair': [pair, pair],
|
|
'profit_percent': [0.0, 0.0],
|
|
'profit_abs': [0.0, 0.0],
|
|
'open_time': pd.to_datetime([Arrow(2018, 1, 29, 18, 40, 0).datetime,
|
|
Arrow(2018, 1, 30, 3, 30, 0).datetime], utc=True
|
|
),
|
|
'close_time': pd.to_datetime([Arrow(2018, 1, 29, 22, 35, 0).datetime,
|
|
Arrow(2018, 1, 30, 4, 10, 0).datetime], utc=True),
|
|
'open_index': [78, 184],
|
|
'close_index': [125, 192],
|
|
'trade_duration': [235, 40],
|
|
'open_at_end': [False, False],
|
|
'open_rate': [0.104445, 0.10302485],
|
|
'close_rate': [0.104969, 0.103541],
|
|
'sell_reason': [SellType.ROI, SellType.ROI]
|
|
})
|
|
pd.testing.assert_frame_equal(results, expected)
|
|
data_pair = data_processed[pair]
|
|
for _, t in results.iterrows():
|
|
ln = data_pair.loc[data_pair["date"] == t["open_time"]]
|
|
# Check open trade rate alignes to open rate
|
|
assert ln is not None
|
|
assert round(ln.iloc[0]["open"], 6) == round(t["open_rate"], 6)
|
|
# check close trade rate alignes to close rate or is between high and low
|
|
ln = data_pair.loc[data_pair["date"] == t["close_time"]]
|
|
assert (round(ln.iloc[0]["open"], 6) == round(t["close_rate"], 6) or
|
|
round(ln.iloc[0]["low"], 6) < round(
|
|
t["close_rate"], 6) < round(ln.iloc[0]["high"], 6))
|
|
|
|
|
|
def test_backtest_1min_ticker_interval(default_conf, fee, mocker, testdatadir) -> None:
|
|
default_conf['ask_strategy']['use_sell_signal'] = False
|
|
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
|
|
patch_exchange(mocker)
|
|
backtesting = Backtesting(default_conf)
|
|
|
|
# Run a backtesting for an exiting 1min timeframe
|
|
timerange = TimeRange.parse_timerange('1510688220-1510700340')
|
|
data = history.load_data(datadir=testdatadir, timeframe='1m', pairs=['UNITTEST/BTC'],
|
|
timerange=timerange)
|
|
processed = backtesting.strategy.tickerdata_to_dataframe(data)
|
|
min_date, max_date = get_timerange(processed)
|
|
results = backtesting.backtest(
|
|
{
|
|
'stake_amount': default_conf['stake_amount'],
|
|
'processed': processed,
|
|
'max_open_trades': 1,
|
|
'position_stacking': False,
|
|
'start_date': min_date,
|
|
'end_date': max_date,
|
|
}
|
|
)
|
|
assert not results.empty
|
|
assert len(results) == 1
|
|
|
|
|
|
def test_processed(default_conf, mocker, testdatadir) -> None:
|
|
patch_exchange(mocker)
|
|
backtesting = Backtesting(default_conf)
|
|
|
|
dict_of_tickerrows = load_data_test('raise', testdatadir)
|
|
dataframes = backtesting.strategy.tickerdata_to_dataframe(dict_of_tickerrows)
|
|
dataframe = dataframes['UNITTEST/BTC']
|
|
cols = dataframe.columns
|
|
# assert the dataframe got some of the indicator columns
|
|
for col in ['close', 'high', 'low', 'open', 'date',
|
|
'ema10', 'rsi', 'fastd', 'plus_di']:
|
|
assert col in cols
|
|
|
|
|
|
def test_backtest_pricecontours(default_conf, fee, mocker, testdatadir) -> None:
|
|
# TODO: Evaluate usefullness of this, the patterns and buy-signls are unrealistic
|
|
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
|
|
tests = [['raise', 19], ['lower', 0], ['sine', 35]]
|
|
|
|
for [contour, numres] in tests:
|
|
simple_backtest(default_conf, contour, numres, mocker, testdatadir)
|
|
|
|
|
|
def test_backtest_clash_buy_sell(mocker, default_conf, testdatadir):
|
|
# Override the default buy trend function in our default_strategy
|
|
def fun(dataframe=None, pair=None):
|
|
buy_value = 1
|
|
sell_value = 1
|
|
return _trend(dataframe, buy_value, sell_value)
|
|
|
|
backtest_conf = _make_backtest_conf(mocker, conf=default_conf, datadir=testdatadir)
|
|
backtesting = Backtesting(default_conf)
|
|
backtesting.strategy.advise_buy = fun # Override
|
|
backtesting.strategy.advise_sell = fun # Override
|
|
results = backtesting.backtest(backtest_conf)
|
|
assert results.empty
|
|
|
|
|
|
def test_backtest_only_sell(mocker, default_conf, testdatadir):
|
|
# Override the default buy trend function in our default_strategy
|
|
def fun(dataframe=None, pair=None):
|
|
buy_value = 0
|
|
sell_value = 1
|
|
return _trend(dataframe, buy_value, sell_value)
|
|
|
|
backtest_conf = _make_backtest_conf(mocker, conf=default_conf, datadir=testdatadir)
|
|
backtesting = Backtesting(default_conf)
|
|
backtesting.strategy.advise_buy = fun # Override
|
|
backtesting.strategy.advise_sell = fun # Override
|
|
results = backtesting.backtest(backtest_conf)
|
|
assert results.empty
|
|
|
|
|
|
def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir):
|
|
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
|
|
mocker.patch('freqtrade.optimize.backtesting.file_dump_json', MagicMock())
|
|
backtest_conf = _make_backtest_conf(mocker, conf=default_conf,
|
|
pair='UNITTEST/BTC', datadir=testdatadir)
|
|
default_conf['ticker_interval'] = '1m'
|
|
backtesting = Backtesting(default_conf)
|
|
backtesting.strategy.advise_buy = _trend_alternate # Override
|
|
backtesting.strategy.advise_sell = _trend_alternate # Override
|
|
results = backtesting.backtest(backtest_conf)
|
|
backtesting._store_backtest_result("test_.json", results)
|
|
# 200 candles in backtest data
|
|
# won't buy on first (shifted by 1)
|
|
# 100 buys signals
|
|
assert len(results) == 100
|
|
# One trade was force-closed at the end
|
|
assert len(results.loc[results.open_at_end]) == 0
|
|
|
|
|
|
@pytest.mark.parametrize("pair", ['ADA/BTC', 'LTC/BTC'])
|
|
@pytest.mark.parametrize("tres", [0, 20, 30])
|
|
def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir):
|
|
|
|
def _trend_alternate_hold(dataframe=None, metadata=None):
|
|
"""
|
|
Buy every xth candle - sell every other xth -2 (hold on to pairs a bit)
|
|
"""
|
|
if metadata['pair'] in('ETH/BTC', 'LTC/BTC'):
|
|
multi = 20
|
|
else:
|
|
multi = 18
|
|
dataframe['buy'] = np.where(dataframe.index % multi == 0, 1, 0)
|
|
dataframe['sell'] = np.where((dataframe.index + multi - 2) % multi == 0, 1, 0)
|
|
return dataframe
|
|
|
|
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
|
|
patch_exchange(mocker)
|
|
|
|
pairs = ['ADA/BTC', 'DASH/BTC', 'ETH/BTC', 'LTC/BTC', 'NXT/BTC']
|
|
data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=pairs)
|
|
# Only use 500 lines to increase performance
|
|
data = trim_dictlist(data, -500)
|
|
|
|
# Remove data for one pair from the beginning of the data
|
|
data[pair] = data[pair][tres:].reset_index()
|
|
default_conf['ticker_interval'] = '5m'
|
|
|
|
backtesting = Backtesting(default_conf)
|
|
backtesting.strategy.advise_buy = _trend_alternate_hold # Override
|
|
backtesting.strategy.advise_sell = _trend_alternate_hold # Override
|
|
|
|
data_processed = backtesting.strategy.tickerdata_to_dataframe(data)
|
|
min_date, max_date = get_timerange(data_processed)
|
|
backtest_conf = {
|
|
'stake_amount': default_conf['stake_amount'],
|
|
'processed': data_processed,
|
|
'max_open_trades': 3,
|
|
'position_stacking': False,
|
|
'start_date': min_date,
|
|
'end_date': max_date,
|
|
}
|
|
|
|
results = backtesting.backtest(backtest_conf)
|
|
|
|
# Make sure we have parallel trades
|
|
assert len(evaluate_result_multi(results, '5m', 2)) > 0
|
|
# make sure we don't have trades with more than configured max_open_trades
|
|
assert len(evaluate_result_multi(results, '5m', 3)) == 0
|
|
|
|
backtest_conf = {
|
|
'stake_amount': default_conf['stake_amount'],
|
|
'processed': data_processed,
|
|
'max_open_trades': 1,
|
|
'position_stacking': False,
|
|
'start_date': min_date,
|
|
'end_date': max_date,
|
|
}
|
|
results = backtesting.backtest(backtest_conf)
|
|
assert len(evaluate_result_multi(results, '5m', 1)) == 0
|
|
|
|
|
|
def test_backtest_record(default_conf, fee, mocker):
|
|
names = []
|
|
records = []
|
|
patch_exchange(mocker)
|
|
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
|
|
mocker.patch(
|
|
'freqtrade.optimize.backtesting.file_dump_json',
|
|
new=lambda n, r: (names.append(n), records.append(r))
|
|
)
|
|
|
|
backtesting = Backtesting(default_conf)
|
|
results = pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
|
|
"UNITTEST/BTC", "UNITTEST/BTC"],
|
|
"profit_percent": [0.003312, 0.010801, 0.013803, 0.002780],
|
|
"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
|
|
"open_time": [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_time": [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],
|
|
"open_index": [1, 119, 153, 185],
|
|
"close_index": [118, 151, 184, 199],
|
|
"trade_duration": [123, 34, 31, 14],
|
|
"open_at_end": [False, False, False, True],
|
|
"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
|
|
SellType.ROI, SellType.FORCE_SELL]
|
|
})
|
|
backtesting._store_backtest_result("backtest-result.json", results)
|
|
assert len(results) == 4
|
|
# Assert file_dump_json was only called once
|
|
assert names == ['backtest-result.json']
|
|
records = records[0]
|
|
# Ensure records are of correct type
|
|
assert len(records) == 4
|
|
|
|
# reset test to test with strategy name
|
|
names = []
|
|
records = []
|
|
backtesting._store_backtest_result(Path("backtest-result.json"), results, "DefStrat")
|
|
assert len(results) == 4
|
|
# Assert file_dump_json was only called once
|
|
assert names == [Path('backtest-result-DefStrat.json')]
|
|
records = records[0]
|
|
# Ensure records are of correct type
|
|
assert len(records) == 4
|
|
|
|
# ('UNITTEST/BTC', 0.00331158, '1510684320', '1510691700', 0, 117)
|
|
# Below follows just a typecheck of the schema/type of trade-records
|
|
oix = None
|
|
for (pair, profit, date_buy, date_sell, buy_index, dur,
|
|
openr, closer, open_at_end, sell_reason) in records:
|
|
assert pair == 'UNITTEST/BTC'
|
|
assert isinstance(profit, float)
|
|
# FIX: buy/sell should be converted to ints
|
|
assert isinstance(date_buy, float)
|
|
assert isinstance(date_sell, float)
|
|
assert isinstance(openr, float)
|
|
assert isinstance(closer, float)
|
|
assert isinstance(open_at_end, bool)
|
|
assert isinstance(sell_reason, str)
|
|
isinstance(buy_index, pd._libs.tslib.Timestamp)
|
|
if oix:
|
|
assert buy_index > oix
|
|
oix = buy_index
|
|
assert dur > 0
|
|
|
|
|
|
def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir):
|
|
default_conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
|
|
|
|
patch_exchange(mocker)
|
|
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', MagicMock())
|
|
mocker.patch('freqtrade.optimize.backtesting.Backtesting._generate_text_table', MagicMock())
|
|
patched_configuration_load_config_file(mocker, default_conf)
|
|
|
|
args = [
|
|
'backtesting',
|
|
'--config', 'config.json',
|
|
'--strategy', 'DefaultStrategy',
|
|
'--datadir', str(testdatadir),
|
|
'--ticker-interval', '1m',
|
|
'--timerange', '1510694220-1510700340',
|
|
'--enable-position-stacking',
|
|
'--disable-max-market-positions'
|
|
]
|
|
args = get_args(args)
|
|
start_backtesting(args)
|
|
# check the logs, that will contain the backtest result
|
|
exists = [
|
|
'Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
|
|
'Ignoring max_open_trades (--disable-max-market-positions was used) ...',
|
|
'Parameter --timerange detected: 1510694220-1510700340 ...',
|
|
f'Using data directory: {testdatadir} ...',
|
|
'Using stake_currency: BTC ...',
|
|
'Using stake_amount: 0.001 ...',
|
|
'Loading data from 2017-11-14T20:57:00+00:00 '
|
|
'up to 2017-11-14T22:58:00+00:00 (0 days)..',
|
|
'Backtesting with data from 2017-11-14T21:17:00+00:00 '
|
|
'up to 2017-11-14T22:58:00+00:00 (0 days)..',
|
|
'Parameter --enable-position-stacking detected ...'
|
|
]
|
|
|
|
for line in exists:
|
|
assert log_has(line, caplog)
|
|
|
|
|
|
def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
|
|
default_conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
|
|
|
|
patch_exchange(mocker)
|
|
backtestmock = MagicMock()
|
|
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock)
|
|
gen_table_mock = MagicMock()
|
|
mocker.patch('freqtrade.optimize.backtesting.Backtesting._generate_text_table', gen_table_mock)
|
|
gen_strattable_mock = MagicMock()
|
|
mocker.patch('freqtrade.optimize.backtesting.Backtesting._generate_text_table_strategy',
|
|
gen_strattable_mock)
|
|
patched_configuration_load_config_file(mocker, default_conf)
|
|
|
|
args = [
|
|
'backtesting',
|
|
'--config', 'config.json',
|
|
'--datadir', str(testdatadir),
|
|
'--strategy-path', str(Path(__file__).parents[2] / 'freqtrade/templates'),
|
|
'--ticker-interval', '1m',
|
|
'--timerange', '1510694220-1510700340',
|
|
'--enable-position-stacking',
|
|
'--disable-max-market-positions',
|
|
'--strategy-list',
|
|
'DefaultStrategy',
|
|
'SampleStrategy',
|
|
]
|
|
args = get_args(args)
|
|
start_backtesting(args)
|
|
# 2 backtests, 4 tables
|
|
assert backtestmock.call_count == 2
|
|
assert gen_table_mock.call_count == 4
|
|
assert gen_strattable_mock.call_count == 1
|
|
|
|
# check the logs, that will contain the backtest result
|
|
exists = [
|
|
'Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
|
|
'Ignoring max_open_trades (--disable-max-market-positions was used) ...',
|
|
'Parameter --timerange detected: 1510694220-1510700340 ...',
|
|
f'Using data directory: {testdatadir} ...',
|
|
'Using stake_currency: BTC ...',
|
|
'Using stake_amount: 0.001 ...',
|
|
'Loading data from 2017-11-14T20:57:00+00:00 '
|
|
'up to 2017-11-14T22:58:00+00:00 (0 days)..',
|
|
'Backtesting with data from 2017-11-14T21:17:00+00:00 '
|
|
'up to 2017-11-14T22:58:00+00:00 (0 days)..',
|
|
'Parameter --enable-position-stacking detected ...',
|
|
'Running backtesting for Strategy DefaultStrategy',
|
|
'Running backtesting for Strategy SampleStrategy',
|
|
]
|
|
|
|
for line in exists:
|
|
assert log_has(line, caplog)
|