stable/freqtrade/tests/optimize/test_backtesting.py
2018-06-03 10:35:56 +02:00

626 lines
21 KiB
Python

# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
import json
import math
import random
from copy import deepcopy
from typing import List
from unittest.mock import MagicMock
import numpy as np
import pandas as pd
from arrow import Arrow
from freqtrade import optimize
from freqtrade.analyze import Analyze
from freqtrade.arguments import Arguments
from freqtrade.optimize.backtesting import Backtesting, start, setup_configuration
from freqtrade.tests.conftest import log_has
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='1m',
pairs=['UNITTEST/BTC'], timerange=timerange)
pair = data['UNITTEST/BTC']
datalen = len(pair)
# Depending on the what parameter we now adjust the
# loaded data looks:
# pair :: [[ 1509836520000, unix timestamp in ms
# 0.00162008, open
# 0.00162008, high
# 0.00162008, low
# 0.00162008, close
# 108.14853839 base volume
# ]]
base = 0.001
if what == 'raise':
return {'UNITTEST/BTC': [
[
pair[x][0], # Keep old dates
x * base, # But replace O,H,L,C
x * base + 0.0001,
x * base - 0.0001,
x * base,
pair[x][5], # Keep old volume
] for x in range(0, datalen)
]}
if what == 'lower':
return {'UNITTEST/BTC': [
[
pair[x][0], # Keep old dates
1 - x * base, # But replace O,H,L,C
1 - x * base + 0.0001,
1 - x * base - 0.0001,
1 - x * base,
pair[x][5] # Keep old volume
] for x in range(0, datalen)
]}
if what == 'sine':
hz = 0.1 # frequency
return {'UNITTEST/BTC': [
[
pair[x][0], # Keep old dates
math.sin(x * hz) / 1000 + base, # But replace O,H,L,C
math.sin(x * hz) / 1000 + base + 0.0001,
math.sin(x * hz) / 1000 + base - 0.0001,
math.sin(x * hz) / 1000 + base,
pair[x][5] # Keep old volume
] for x in range(0, datalen)
]}
return data
def simple_backtest(config, contour, num_results, mocker) -> None:
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
backtesting = Backtesting(config)
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='0m', refresh_pairs=False, timerange=None):
tickerdata = optimize.load_tickerdata_file(datadir, 'UNITTEST/BTC', '1m', timerange=timerange)
pairdata = {'UNITTEST/BTC': tickerdata}
return pairdata
# use for mock freqtrade.exchange.get_ticker_history'
def _load_pair_as_ticks(pair, tickfreq):
ticks = optimize.load_data(None, ticker_interval=tickfreq, pairs=[pair])
ticks = trim_dictlist(ticks, -200)
return ticks[pair]
# FIX: fixturize this?
def _make_backtest_conf(mocker, conf=None, pair='UNITTEST/BTC', record=None):
data = optimize.load_data(None, ticker_interval='8m', pairs=[pair])
data = trim_dictlist(data, -200)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
backtesting = Backtesting(conf)
return {
'stake_amount': conf['stake_amount'],
'processed': backtesting.tickerdata_to_dataframe(data),
'max_open_trades': 10,
'realistic': True,
'record': record
}
def _trend(signals, buy_value, sell_value):
n = len(signals['low'])
buy = np.zeros(n)
sell = np.zeros(n)
for i in range(0, len(signals['buy'])):
if random.random() > 0.5: # Both buy and sell signals at same timeframe
buy[i] = buy_value
sell[i] = sell_value
signals['buy'] = buy
signals['sell'] = sell
return signals
def _trend_alternate(dataframe=None):
signals = dataframe
low = signals['low']
n = len(low)
buy = np.zeros(n)
sell = np.zeros(n)
for i in range(0, len(buy)):
if i % 2 == 0:
buy[i] = 1
else:
sell[i] = 1
signals['buy'] = buy
signals['sell'] = sell
return dataframe
# 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', 'DefaultStrategy',
'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 log_has(
'Using data folder: {} ...'.format(config['datadir']),
caplog.record_tuples
)
assert 'ticker_interval' in config
assert not log_has('Parameter -i/--ticker-interval detected ...', caplog.record_tuples)
assert 'live' not in config
assert not log_has('Parameter -l/--live detected ...', caplog.record_tuples)
assert 'realistic_simulation' not in config
assert not log_has('Parameter --realistic-simulation detected ...', caplog.record_tuples)
assert 'refresh_pairs' not in config
assert not 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', 'DefaultStrategy',
'--datadir', '/foo/bar',
'backtesting',
'--ticker-interval', '1m',
'--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 log_has(
'Using data folder: {} ...'.format(config['datadir']),
caplog.record_tuples
)
assert 'ticker_interval' in config
assert log_has('Parameter -i/--ticker-interval detected ...', caplog.record_tuples)
assert log_has(
'Using ticker_interval: 1m ...',
caplog.record_tuples
)
assert 'live' in config
assert log_has('Parameter -l/--live detected ...', caplog.record_tuples)
assert 'realistic_simulation' in config
assert log_has('Parameter --realistic-simulation detected ...', caplog.record_tuples)
assert log_has('Using max_open_trades: 1 ...', caplog.record_tuples)
assert 'refresh_pairs' in config
assert log_has('Parameter -r/--refresh-pairs-cached detected ...', caplog.record_tuples)
assert 'timerange' in config
assert log_has(
'Parameter --timerange detected: {} ...'.format(config['timerange']),
caplog.record_tuples
)
assert 'export' in config
assert log_has(
'Parameter --export detected: {} ...'.format(config['export']),
caplog.record_tuples
)
def test_start(mocker, fee, default_conf, caplog) -> None:
"""
Test start() function
"""
start_mock = MagicMock()
mocker.patch('freqtrade.exchange.get_fee', fee)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
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', 'DefaultStrategy',
'backtesting'
]
args = get_args(args)
start(args)
assert 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
"""
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
backtesting = Backtesting(default_conf)
assert backtesting.config == default_conf
assert isinstance(backtesting.analyze, Analyze)
assert backtesting.ticker_interval == '5m'
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, mocker) -> None:
"""
Test Backtesting.tickerdata_to_dataframe() method
"""
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
timerange = ((None, 'line'), None, -100)
tick = optimize.load_tickerdata_file(None, 'UNITTEST/BTC', '1m', timerange=timerange)
tickerlist = {'UNITTEST/BTC': tick}
backtesting = Backtesting(default_conf)
data = backtesting.tickerdata_to_dataframe(tickerlist)
assert len(data['UNITTEST/BTC']) == 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['UNITTEST/BTC'].equals(data2['UNITTEST/BTC'])
def test_get_timeframe(default_conf, mocker) -> None:
"""
Test Backtesting.get_timeframe() method
"""
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
backtesting = Backtesting(default_conf)
data = backtesting.tickerdata_to_dataframe(
optimize.load_data(
None,
ticker_interval='1m',
pairs=['UNITTEST/BTC']
)
)
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(default_conf, mocker):
"""
Test Backtesting.generate_text_table() method
"""
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
backtesting = Backtesting(default_conf)
results = pd.DataFrame(
{
'currency': ['ETH/BTC', 'ETH/BTC'],
'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'
'| ETH/BTC | 2 | 15.00 | '
'0.60000000 | 20.0 | 2 | 0 |\n'
'| TOTAL | 2 | 15.00 | '
'0.60000000 | 20.0 | 2 | 0 |'
)
assert backtesting._generate_text_table(data={'ETH/BTC': {}}, 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('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
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'] = ['UNITTEST/BTC']
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 log_has(line, caplog.record_tuples)
def test_backtest(default_conf, fee, mocker) -> None:
"""
Test Backtesting.backtest() method
"""
mocker.patch('freqtrade.exchange.get_fee', fee)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
backtesting = Backtesting(default_conf)
data = optimize.load_data(None, ticker_interval='5m', pairs=['UNITTEST/BTC'])
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, fee, mocker) -> None:
"""
Test Backtesting.backtest() method with 1 min ticker
"""
mocker.patch('freqtrade.exchange.get_fee', fee)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
backtesting = Backtesting(default_conf)
# Run a backtesting for an exiting 5min ticker_interval
data = optimize.load_data(None, ticker_interval='1m', pairs=['UNITTEST/BTC'])
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(default_conf, mocker) -> None:
"""
Test Backtesting.backtest() method with offline data
"""
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
backtesting = Backtesting(default_conf)
dict_of_tickerrows = load_data_test('raise')
dataframes = backtesting.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',
'ema50', 'ao', 'macd', 'plus_dm']:
assert col in cols
def test_backtest_pricecontours(default_conf, fee, mocker) -> None:
mocker.patch('freqtrade.optimize.backtesting.exchange.get_fee', fee)
tests = [['raise', 17], ['lower', 0], ['sine', 17]]
for [contour, numres] in tests:
simple_backtest(default_conf, contour, numres, mocker)
# Test backtest using offline data (testdata directory)
def test_backtest_ticks(default_conf, fee, mocker):
mocker.patch('freqtrade.exchange.get_fee', fee)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
ticks = [1, 5]
fun = Backtesting(default_conf).populate_buy_trend
for _ in ticks:
backtest_conf = _make_backtest_conf(mocker, conf=default_conf)
backtesting = Backtesting(default_conf)
backtesting.populate_buy_trend = fun # Override
backtesting.populate_sell_trend = fun # Override
results = backtesting.backtest(backtest_conf)
assert not results.empty
def test_backtest_clash_buy_sell(mocker, default_conf):
# Override the default buy trend function in our default_strategy
def fun(dataframe=None):
buy_value = 1
sell_value = 1
return _trend(dataframe, buy_value, sell_value)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
backtest_conf = _make_backtest_conf(mocker, conf=default_conf)
backtesting = Backtesting(default_conf)
backtesting.populate_buy_trend = fun # Override
backtesting.populate_sell_trend = fun # Override
results = backtesting.backtest(backtest_conf)
assert results.empty
def test_backtest_only_sell(mocker, default_conf):
# Override the default buy trend function in our default_strategy
def fun(dataframe=None):
buy_value = 0
sell_value = 1
return _trend(dataframe, buy_value, sell_value)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
backtest_conf = _make_backtest_conf(mocker, conf=default_conf)
backtesting = Backtesting(default_conf)
backtesting.populate_buy_trend = fun # Override
backtesting.populate_sell_trend = fun # Override
results = backtesting.backtest(backtest_conf)
assert results.empty
def test_backtest_alternate_buy_sell(default_conf, fee, mocker):
mocker.patch('freqtrade.optimize.backtesting.exchange.get_fee', fee)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
backtest_conf = _make_backtest_conf(mocker, conf=default_conf, pair='UNITTEST/BTC')
backtesting = Backtesting(default_conf)
backtesting.populate_buy_trend = _trend_alternate # Override
backtesting.populate_sell_trend = _trend_alternate # Override
results = backtesting.backtest(backtest_conf)
assert len(results) == 3
def test_backtest_record(default_conf, fee, mocker):
names = []
records = []
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
mocker.patch('freqtrade.optimize.backtesting.exchange.get_fee', fee)
mocker.patch(
'freqtrade.optimize.backtesting.file_dump_json',
new=lambda n, r: (names.append(n), records.append(r))
)
backtest_conf = _make_backtest_conf(
mocker,
conf=default_conf,
pair='UNITTEST/BTC',
record="trades"
)
backtesting = Backtesting(default_conf)
backtesting.populate_buy_trend = _trend_alternate # Override
backtesting.populate_sell_trend = _trend_alternate # Override
results = backtesting.backtest(backtest_conf)
assert len(results) == 3
# 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) == 3
# ('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) in records:
assert pair == 'UNITTEST/BTC'
isinstance(profit, float)
# FIX: buy/sell should be converted to ints
isinstance(date_buy, str)
isinstance(date_sell, str)
isinstance(buy_index, pd._libs.tslib.Timestamp)
if oix:
assert buy_index > oix
oix = buy_index
assert dur > 0
def test_backtest_start_live(default_conf, mocker, caplog):
conf = deepcopy(default_conf)
conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
mocker.patch('freqtrade.exchange.get_ticker_history',
new=lambda n, i: _load_pair_as_ticks(n, i))
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock())
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', MagicMock())
mocker.patch('freqtrade.optimize.backtesting.Backtesting._generate_text_table', MagicMock())
mocker.patch('freqtrade.configuration.open', mocker.mock_open(
read_data=json.dumps(conf)
))
args = MagicMock()
args.ticker_interval = 1
args.level = 10
args.live = True
args.datadir = None
args.export = None
args.strategy = 'DefaultStrategy'
args.timerange = '-100' # needed due to MagicMock malleability
args = [
'--config', 'config.json',
'--strategy', 'DefaultStrategy',
'backtesting',
'--ticker-interval', '1m',
'--live',
'--timerange', '-100'
]
args = get_args(args)
start(args)
# check the logs, that will contain the backtest result
exists = [
'Parameter -i/--ticker-interval detected ...',
'Using ticker_interval: 1m ...',
'Parameter -l/--live detected ...',
'Using max_open_trades: 1 ...',
'Parameter --timerange detected: -100 ..',
'Using data folder: freqtrade/tests/testdata ...',
'Using stake_currency: BTC ...',
'Using stake_amount: 0.001 ...',
'Downloading data for all pairs in whitelist ...',
'Measuring data from 2017-11-14T19:32:00+00:00 up to 2017-11-14T22:59:00+00:00 (0 days)..'
]
for line in exists:
log_has(line, caplog.record_tuples)