157 lines
5.1 KiB
Python
157 lines
5.1 KiB
Python
# pragma pylint: disable=missing-docstring,W0212
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import math
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import pandas as pd
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from freqtrade import exchange, optimize
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from freqtrade.exchange import Bittrex
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from freqtrade.optimize.backtesting import backtest, generate_text_table, get_timeframe
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def test_generate_text_table():
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results = pd.DataFrame(
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{
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'currency': ['BTC_ETH', 'BTC_ETH'],
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'profit_percent': [0.1, 0.2],
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'profit_BTC': [0.2, 0.4],
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'duration': [10, 30]
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}
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)
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assert generate_text_table({'BTC_ETH': {}}, results, 'BTC', 5) == (
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'pair buy count avg profit total profit avg duration\n'
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'------- ----------- ------------ -------------- --------------\n'
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'BTC_ETH 2 15.00% 0.60000000 BTC 100\n'
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'TOTAL 2 15.00% 0.60000000 BTC 100')
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def test_get_timeframe():
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data = optimize.load_data(ticker_interval=1, pairs=['BTC_UNITEST'])
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min_date, max_date = get_timeframe(data)
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assert min_date.isoformat() == '2017-11-04T23:02:00+00:00'
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assert max_date.isoformat() == '2017-11-14T22:59:00+00:00'
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def test_backtest(default_conf, mocker):
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mocker.patch.dict('freqtrade.main._CONF', default_conf)
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exchange._API = Bittrex({'key': '', 'secret': ''})
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data = optimize.load_data(ticker_interval=5, pairs=['BTC_ETH'])
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results = backtest(default_conf['stake_amount'], optimize.preprocess(data), 10, True)
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assert not results.empty
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def test_backtest_1min_ticker_interval(default_conf, mocker):
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mocker.patch.dict('freqtrade.main._CONF', default_conf)
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exchange._API = Bittrex({'key': '', 'secret': ''})
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# Run a backtesting for an exiting 5min ticker_interval
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data = optimize.load_data(ticker_interval=1, pairs=['BTC_UNITEST'])
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results = backtest(default_conf['stake_amount'], optimize.preprocess(data), 1, True)
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assert not results.empty
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def trim_dataframe(df, num):
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new = dict()
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for pair, pair_data in df.items():
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new[pair] = pair_data[-num:] # last 50 rows
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return new
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def load_data_test(what):
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data = optimize.load_data(ticker_interval=1, pairs=['BTC_UNITEST'])
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data = trim_dataframe(data, -40)
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pair = data['BTC_UNITEST']
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# Depending on the what parameter we now adjust the
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# loaded data:
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# pair :: [{'O': 0.123, 'H': 0.123, 'L': 0.123,
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# 'C': 0.123, 'V': 123.123,
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# 'T': '2017-11-04T23:02:00', 'BV': 0.123}]
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if what == 'raise':
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o = 0.001
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h = 0.001
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ll = 0.001
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c = 0.001
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ll -= 0.0001
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h += 0.0001
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for frame in pair:
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o += 0.0001
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h += 0.0001
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ll += 0.0001
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c += 0.0001
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# save prices rounded to satoshis
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frame['O'] = round(o, 9)
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frame['H'] = round(h, 9)
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frame['L'] = round(ll, 9)
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frame['C'] = round(c, 9)
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if what == 'lower':
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o = 0.001
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h = 0.001
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ll = 0.001
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c = 0.001
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ll -= 0.0001
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h += 0.0001
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for frame in pair:
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o -= 0.0001
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h -= 0.0001
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ll -= 0.0001
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c -= 0.0001
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# save prices rounded to satoshis
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frame['O'] = round(o, 9)
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frame['H'] = round(h, 9)
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frame['L'] = round(ll, 9)
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frame['C'] = round(c, 9)
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if what == 'sine':
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i = 0
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o = (2 + math.sin(i/10)) / 1000
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h = o
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ll = o
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c = o
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h += 0.0001
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ll -= 0.0001
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for frame in pair:
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o = (2 + math.sin(i/10)) / 1000
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h = (2 + math.sin(i/10)) / 1000 + 0.0001
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ll = (2 + math.sin(i/10)) / 1000 - 0.0001
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c = (2 + math.sin(i/10)) / 1000 - 0.000001
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# save prices rounded to satoshis
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frame['O'] = round(o, 9)
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frame['H'] = round(h, 9)
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frame['L'] = round(ll, 9)
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frame['C'] = round(c, 9)
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i += 1
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return data
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def simple_backtest(config, contour, num_results):
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data = load_data_test(contour)
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processed = optimize.preprocess(data)
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assert isinstance(processed, dict)
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results = backtest(config['stake_amount'], processed, 1, True)
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# results :: <class 'pandas.core.frame.DataFrame'>
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assert len(results) == num_results
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# Test backtest on offline data
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# loaded by freqdata/optimize/__init__.py::load_data()
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def test_backtest2(default_conf, mocker):
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mocker.patch.dict('freqtrade.main._CONF', default_conf)
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data = optimize.load_data(ticker_interval=5, pairs=['BTC_ETH'])
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results = backtest(default_conf['stake_amount'], optimize.preprocess(data), 10, True)
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num_resutls = len(results)
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assert num_resutls > 0
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def test_processed(default_conf, mocker):
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mocker.patch.dict('freqtrade.main._CONF', default_conf)
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data = load_data_test('raise')
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assert optimize.preprocess(data)
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def test_raise(default_conf, mocker):
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mocker.patch.dict('freqtrade.main._CONF', default_conf)
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tests = [['raise', 359], ['lower', 0], ['sine', 1734]]
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for [contour, numres] in tests:
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simple_backtest(default_conf, contour, numres)
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