stable/freqtrade/tests/optimize/test_backtesting.py
2018-03-03 09:33:54 +08:00

421 lines
14 KiB
Python

# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
import json
import math
from typing import List
from copy import deepcopy
from unittest.mock import MagicMock
from arrow import Arrow
import pandas as pd
from freqtrade import optimize
from freqtrade.optimize.backtesting import Backtesting, start, setup_configuration
from freqtrade.arguments import Arguments
from freqtrade.analyze import Analyze
import freqtrade.tests.conftest as tt # test tools
# Avoid to reinit the same object again and again
_BACKTESTING = Backtesting(tt.default_conf())
def get_args(args) -> List[str]:
return Arguments(args, '').get_parsed_arg()
def trim_dictlist(dict_list, num):
new = {}
for pair, pair_data in dict_list.items():
new[pair] = pair_data[num:]
return new
def load_data_test(what):
timerange = ((None, 'line'), None, -100)
data = optimize.load_data(None, ticker_interval=1, pairs=['BTC_UNITEST'], timerange=timerange)
pair = data['BTC_UNITEST']
datalen = len(pair)
# Depending on the what parameter we now adjust the
# loaded data looks:
# pair :: [{'O': 0.123, 'H': 0.123, 'L': 0.123,
# 'C': 0.123, 'V': 123.123,
# 'T': '2017-11-04T23:02:00', 'BV': 0.123}]
base = 0.001
if what == 'raise':
return {'BTC_UNITEST':
[{'T': pair[x]['T'], # Keep old dates
'V': pair[x]['V'], # Keep old volume
'BV': pair[x]['BV'], # keep too
'O': x * base, # But replace O,H,L,C
'H': x * base + 0.0001,
'L': x * base - 0.0001,
'C': x * base} for x in range(0, datalen)]}
if what == 'lower':
return {'BTC_UNITEST':
[{'T': pair[x]['T'], # Keep old dates
'V': pair[x]['V'], # Keep old volume
'BV': pair[x]['BV'], # keep too
'O': 1 - x * base, # But replace O,H,L,C
'H': 1 - x * base + 0.0001,
'L': 1 - x * base - 0.0001,
'C': 1 - x * base} for x in range(0, datalen)]}
if what == 'sine':
hz = 0.1 # frequency
return {'BTC_UNITEST':
[{'T': pair[x]['T'], # Keep old dates
'V': pair[x]['V'], # Keep old volume
'BV': pair[x]['BV'], # keep too
# But replace O,H,L,C
'O': math.sin(x * hz) / 1000 + base,
'H': math.sin(x * hz) / 1000 + base + 0.0001,
'L': math.sin(x * hz) / 1000 + base - 0.0001,
'C': math.sin(x * hz) / 1000 + base} for x in range(0, datalen)]}
return data
def simple_backtest(config, contour, num_results) -> None:
backtesting = _BACKTESTING
data = load_data_test(contour)
processed = backtesting.tickerdata_to_dataframe(data)
assert isinstance(processed, dict)
results = backtesting.backtest(
{
'stake_amount': config['stake_amount'],
'processed': processed,
'max_open_trades': 1,
'realistic': True
}
)
# results :: <class 'pandas.core.frame.DataFrame'>
assert len(results) == num_results
def mocked_load_data(datadir, pairs=[], ticker_interval=0, refresh_pairs=False, timerange=None):
tickerdata = optimize.load_tickerdata_file(datadir, 'BTC_UNITEST', 1, timerange=timerange)
pairdata = {'BTC_UNITEST': tickerdata}
return pairdata
# Unit tests
def test_setup_configuration_without_arguments(mocker, default_conf, caplog) -> None:
"""
Test setup_configuration() function
"""
mocker.patch('freqtrade.configuration.open', mocker.mock_open(
read_data=json.dumps(default_conf)
))
args = [
'--config', 'config.json',
'--strategy', 'default_strategy',
'backtesting'
]
config = setup_configuration(get_args(args))
assert 'max_open_trades' in config
assert 'stake_currency' in config
assert 'stake_amount' in config
assert 'exchange' in config
assert 'pair_whitelist' in config['exchange']
assert 'datadir' in config
assert tt.log_has(
'Parameter --datadir detected: {} ...'.format(config['datadir']),
caplog.record_tuples
)
assert 'ticker_interval' in config
assert not tt.log_has('Parameter -i/--ticker-interval detected ...', caplog.record_tuples)
assert 'live' not in config
assert not tt.log_has('Parameter -l/--live detected ...', caplog.record_tuples)
assert 'realistic_simulation' not in config
assert not tt.log_has('Parameter --realistic-simulation detected ...', caplog.record_tuples)
assert 'refresh_pairs' not in config
assert not tt.log_has('Parameter -r/--refresh-pairs-cached detected ...', caplog.record_tuples)
assert 'timerange' not in config
assert 'export' not in config
def test_setup_configuration_with_arguments(mocker, default_conf, caplog) -> None:
"""
Test setup_configuration() function
"""
mocker.patch('freqtrade.configuration.open', mocker.mock_open(
read_data=json.dumps(default_conf)
))
args = [
'--config', 'config.json',
'--strategy', 'default_strategy',
'--datadir', '/foo/bar',
'backtesting',
'--ticker-interval', '1',
'--live',
'--realistic-simulation',
'--refresh-pairs-cached',
'--timerange', ':100',
'--export', '/bar/foo'
]
config = setup_configuration(get_args(args))
assert 'max_open_trades' in config
assert 'stake_currency' in config
assert 'stake_amount' in config
assert 'exchange' in config
assert 'pair_whitelist' in config['exchange']
assert 'datadir' in config
assert tt.log_has(
'Parameter --datadir detected: {} ...'.format(config['datadir']),
caplog.record_tuples
)
assert 'ticker_interval' in config
assert tt.log_has('Parameter -i/--ticker-interval detected ...', caplog.record_tuples)
assert tt.log_has(
'Using ticker_interval: 1 ...',
caplog.record_tuples
)
assert 'live' in config
assert tt.log_has('Parameter -l/--live detected ...', caplog.record_tuples)
assert 'realistic_simulation'in config
assert tt.log_has('Parameter --realistic-simulation detected ...', caplog.record_tuples)
assert tt.log_has('Using max_open_trades: 1 ...', caplog.record_tuples)
assert 'refresh_pairs'in config
assert tt.log_has('Parameter -r/--refresh-pairs-cached detected ...', caplog.record_tuples)
assert 'timerange' in config
assert tt.log_has(
'Parameter --timerange detected: {} ...'.format(config['timerange']),
caplog.record_tuples
)
assert 'export' in config
assert tt.log_has(
'Parameter --export detected: {} ...'.format(config['export']),
caplog.record_tuples
)
def test_start(mocker, default_conf, caplog) -> None:
"""
Test start() function
"""
start_mock = MagicMock()
mocker.patch('freqtrade.optimize.backtesting.Backtesting.start', start_mock)
mocker.patch('freqtrade.configuration.open', mocker.mock_open(
read_data=json.dumps(default_conf)
))
args = [
'--config', 'config.json',
'--strategy', 'default_strategy',
'backtesting'
]
args = get_args(args)
start(args)
assert tt.log_has(
'Starting freqtrade in Backtesting mode',
caplog.record_tuples
)
assert start_mock.call_count == 1
def test_backtesting__init__(mocker, default_conf) -> None:
"""
Test Backtesting.__init__() method
"""
init_mock = MagicMock()
mocker.patch('freqtrade.optimize.backtesting.Backtesting._init', init_mock)
backtesting = Backtesting(default_conf)
assert backtesting.config == default_conf
assert backtesting.analyze is None
assert backtesting.ticker_interval is None
assert backtesting.tickerdata_to_dataframe is None
assert backtesting.populate_buy_trend is None
assert backtesting.populate_sell_trend is None
assert init_mock.call_count == 1
def test_backtesting_init(default_conf) -> None:
"""
Test Backtesting._init() method
"""
backtesting = Backtesting(default_conf)
assert backtesting.config == default_conf
assert isinstance(backtesting.analyze, Analyze)
assert backtesting.ticker_interval == 5
assert callable(backtesting.tickerdata_to_dataframe)
assert callable(backtesting.populate_buy_trend)
assert callable(backtesting.populate_sell_trend)
def test_tickerdata_to_dataframe(default_conf) -> None:
"""
Test Backtesting.tickerdata_to_dataframe() method
"""
timerange = ((None, 'line'), None, -100)
tick = optimize.load_tickerdata_file(None, 'BTC_UNITEST', 1, timerange=timerange)
tickerlist = {'BTC_UNITEST': tick}
backtesting = _BACKTESTING
data = backtesting.tickerdata_to_dataframe(tickerlist)
assert len(data['BTC_UNITEST']) == 100
# Load Analyze to compare the result between Backtesting function and Analyze are the same
analyze = Analyze(default_conf)
data2 = analyze.tickerdata_to_dataframe(tickerlist)
assert data['BTC_UNITEST'].equals(data2['BTC_UNITEST'])
def test_get_timeframe() -> None:
"""
Test Backtesting.get_timeframe() method
"""
backtesting = _BACKTESTING
data = backtesting.tickerdata_to_dataframe(
optimize.load_data(
None,
ticker_interval=1,
pairs=['BTC_UNITEST']
)
)
min_date, max_date = backtesting.get_timeframe(data)
assert min_date.isoformat() == '2017-11-04T23:02:00+00:00'
assert max_date.isoformat() == '2017-11-14T22:59:00+00:00'
def test_generate_text_table():
"""
Test Backtesting.generate_text_table() method
"""
backtesting = _BACKTESTING
results = pd.DataFrame(
{
'currency': ['BTC_ETH', 'BTC_ETH'],
'profit_percent': [0.1, 0.2],
'profit_BTC': [0.2, 0.4],
'duration': [10, 30],
'profit': [2, 0],
'loss': [0, 0]
}
)
result_str = (
'pair buy count avg profit % '
'total profit BTC avg duration profit loss\n'
'------- ----------- -------------- '
'------------------ -------------- -------- ------\n'
'BTC_ETH 2 15.00 '
'0.60000000 100.0 2 0\n'
'TOTAL 2 15.00 '
'0.60000000 100.0 2 0'
)
assert backtesting._generate_text_table(data={'BTC_ETH': {}}, results=results) == result_str
def test_backtesting_start(default_conf, mocker, caplog) -> None:
"""
Test Backtesting.start() method
"""
def get_timeframe(input1, input2):
return Arrow(2017, 11, 14, 21, 17), Arrow(2017, 11, 14, 22, 59)
mocker.patch('freqtrade.freqtradebot.Analyze', MagicMock())
mocker.patch('freqtrade.optimize.load_data', mocked_load_data)
mocker.patch('freqtrade.exchange.get_ticker_history')
mocker.patch.multiple(
'freqtrade.optimize.backtesting.Backtesting',
backtest=MagicMock(),
_generate_text_table=MagicMock(return_value='1'),
get_timeframe=get_timeframe,
)
conf = deepcopy(default_conf)
conf['exchange']['pair_whitelist'] = ['BTC_UNITEST']
conf['ticker_interval'] = 1
conf['live'] = False
conf['datadir'] = None
conf['export'] = None
conf['timerange'] = '-100'
backtesting = Backtesting(conf)
backtesting.start()
# check the logs, that will contain the backtest result
exists = [
'Using local backtesting data (using whitelist in given config) ...',
'Using stake_currency: BTC ...',
'Using stake_amount: 0.001 ...',
'Measuring data from 2017-11-14T21:17:00+00:00 '
'up to 2017-11-14T22:59:00+00:00 (0 days)..'
]
for line in exists:
assert tt.log_has(line, caplog.record_tuples)
def test_backtest(default_conf) -> None:
"""
Test Backtesting.backtest() method
"""
backtesting = _BACKTESTING
data = optimize.load_data(None, ticker_interval=5, pairs=['BTC_ETH'])
data = trim_dictlist(data, -200)
results = backtesting.backtest(
{
'stake_amount': default_conf['stake_amount'],
'processed': backtesting.tickerdata_to_dataframe(data),
'max_open_trades': 10,
'realistic': True
}
)
assert not results.empty
def test_backtest_1min_ticker_interval(default_conf) -> None:
"""
Test Backtesting.backtest() method with 1 min ticker
"""
backtesting = _BACKTESTING
# Run a backtesting for an exiting 5min ticker_interval
data = optimize.load_data(None, ticker_interval=1, pairs=['BTC_UNITEST'])
data = trim_dictlist(data, -200)
results = backtesting.backtest(
{
'stake_amount': default_conf['stake_amount'],
'processed': backtesting.tickerdata_to_dataframe(data),
'max_open_trades': 1,
'realistic': True
}
)
assert not results.empty
def test_processed() -> None:
"""
Test Backtesting.backtest() method with offline data
"""
backtesting = _BACKTESTING
dict_of_tickerrows = load_data_test('raise')
dataframes = backtesting.tickerdata_to_dataframe(dict_of_tickerrows)
dataframe = dataframes['BTC_UNITEST']
cols = dataframe.columns
# assert the dataframe got some of the indicator columns
for col in ['close', 'high', 'low', 'open', 'date',
'ema50', 'ao', 'macd', 'plus_dm']:
assert col in cols
def test_backtest_pricecontours(default_conf) -> None:
tests = [['raise', 17], ['lower', 0], ['sine', 17]]
for [contour, numres] in tests:
simple_backtest(default_conf, contour, numres)