2018-01-28 07:38:41 +00:00
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# pragma pylint: disable=missing-docstring, C0103
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2018-01-26 16:52:39 +00:00
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import datetime
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2017-11-24 22:58:35 +00:00
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from unittest.mock import MagicMock
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2017-11-20 21:26:32 +00:00
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2017-11-19 03:58:35 +00:00
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import arrow
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2017-09-28 21:26:28 +00:00
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from pandas import DataFrame
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2018-01-26 16:52:39 +00:00
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import freqtrade.tests.conftest as tt # test tools
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2018-01-16 20:21:43 +00:00
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from freqtrade.analyze import (get_signal, parse_ticker_dataframe,
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2018-01-10 07:51:36 +00:00
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populate_buy_trend, populate_indicators,
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populate_sell_trend)
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2018-01-15 08:35:11 +00:00
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from freqtrade.strategy.strategy import Strategy
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2017-09-09 11:48:49 +00:00
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2018-01-06 08:08:25 +00:00
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2017-11-07 19:12:56 +00:00
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def test_dataframe_correct_columns(result):
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2017-10-01 08:02:47 +00:00
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assert result.columns.tolist() == \
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2017-11-06 17:01:13 +00:00
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['close', 'high', 'low', 'open', 'date', 'volume']
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2017-10-01 08:02:47 +00:00
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2017-10-30 23:36:35 +00:00
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2017-11-07 19:12:56 +00:00
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def test_dataframe_correct_length(result):
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2018-01-30 05:26:00 +00:00
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# no idea what this check truly does - should we just remove it?
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assert len(result.index) == 14397
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2017-10-01 08:02:47 +00:00
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2017-10-30 23:36:35 +00:00
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2017-10-01 08:11:20 +00:00
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def test_populates_buy_trend(result):
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2018-01-15 08:35:11 +00:00
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# Load the default strategy for the unit test, because this logic is done in main.py
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Strategy().init({'strategy': 'default_strategy'})
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2018-01-30 14:03:38 +00:00
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dataframe = populate_buy_trend(populate_indicators(result, None), None)
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2017-10-01 08:02:47 +00:00
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assert 'buy' in dataframe.columns
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2017-11-17 10:08:23 +00:00
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2017-11-18 07:19:22 +00:00
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def test_populates_sell_trend(result):
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2018-01-15 08:35:11 +00:00
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# Load the default strategy for the unit test, because this logic is done in main.py
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Strategy().init({'strategy': 'default_strategy'})
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2018-01-30 14:03:38 +00:00
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dataframe = populate_sell_trend(populate_indicators(result, None), None)
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2017-11-17 10:08:23 +00:00
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assert 'sell' in dataframe.columns
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2017-10-01 08:02:47 +00:00
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2017-10-30 23:36:35 +00:00
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2017-10-01 12:25:10 +00:00
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def test_returns_latest_buy_signal(mocker):
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2017-11-24 22:58:35 +00:00
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mocker.patch('freqtrade.analyze.get_ticker_history', return_value=MagicMock())
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mocker.patch(
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'freqtrade.analyze.analyze_ticker',
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2018-01-16 20:18:43 +00:00
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return_value=DataFrame([{'buy': 1, 'sell': 0, 'date': arrow.utcnow()}])
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2017-11-24 22:58:35 +00:00
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)
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2018-01-20 18:25:47 +00:00
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assert get_signal('BTC-ETH', 5) == (True, False)
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2017-10-01 12:25:10 +00:00
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2017-11-24 22:58:35 +00:00
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mocker.patch(
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'freqtrade.analyze.analyze_ticker',
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2018-01-16 20:21:43 +00:00
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return_value=DataFrame([{'buy': 0, 'sell': 1, 'date': arrow.utcnow()}])
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2017-11-24 22:58:35 +00:00
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)
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2018-01-20 18:30:47 +00:00
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assert get_signal('BTC-ETH', 5) == (False, True)
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2017-11-14 18:28:31 +00:00
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def test_returns_latest_sell_signal(mocker):
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2017-11-24 22:58:35 +00:00
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mocker.patch('freqtrade.analyze.get_ticker_history', return_value=MagicMock())
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mocker.patch(
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'freqtrade.analyze.analyze_ticker',
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2018-01-16 20:18:43 +00:00
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return_value=DataFrame([{'sell': 1, 'buy': 0, 'date': arrow.utcnow()}])
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2017-11-24 22:58:35 +00:00
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)
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2018-01-20 18:25:47 +00:00
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assert get_signal('BTC-ETH', 5) == (False, True)
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2017-11-14 18:28:31 +00:00
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2017-11-24 22:58:35 +00:00
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mocker.patch(
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'freqtrade.analyze.analyze_ticker',
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2018-01-16 20:18:43 +00:00
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return_value=DataFrame([{'sell': 0, 'buy': 1, 'date': arrow.utcnow()}])
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2017-11-24 22:58:35 +00:00
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)
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2018-01-20 18:25:47 +00:00
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assert get_signal('BTC-ETH', 5) == (True, False)
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2018-01-05 11:43:56 +00:00
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2018-01-06 08:08:25 +00:00
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2018-01-20 20:24:28 +00:00
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def test_get_signal_empty(default_conf, mocker, caplog):
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2018-01-10 06:40:40 +00:00
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mocker.patch('freqtrade.analyze.get_ticker_history', return_value=None)
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2018-01-20 20:24:28 +00:00
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assert (False, False) == get_signal('foo', int(default_conf['ticker_interval']))
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2018-01-10 08:09:33 +00:00
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assert tt.log_has('Empty ticker history for pair foo',
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caplog.record_tuples)
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2018-01-10 06:40:40 +00:00
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2018-01-20 20:24:28 +00:00
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def test_get_signal_exception_valueerror(default_conf, mocker, caplog):
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2018-01-10 06:40:40 +00:00
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mocker.patch('freqtrade.analyze.get_ticker_history', return_value=1)
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mocker.patch('freqtrade.analyze.analyze_ticker',
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side_effect=ValueError('xyz'))
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2018-01-20 20:24:28 +00:00
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assert (False, False) == get_signal('foo', int(default_conf['ticker_interval']))
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2018-01-10 08:09:33 +00:00
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assert tt.log_has('Unable to analyze ticker for pair foo: xyz',
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caplog.record_tuples)
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2018-01-10 06:40:40 +00:00
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2018-01-20 20:24:28 +00:00
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def test_get_signal_empty_dataframe(default_conf, mocker, caplog):
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2018-01-10 06:40:40 +00:00
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mocker.patch('freqtrade.analyze.get_ticker_history', return_value=1)
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mocker.patch('freqtrade.analyze.analyze_ticker', return_value=DataFrame([]))
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2018-01-20 20:24:28 +00:00
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assert (False, False) == get_signal('xyz', int(default_conf['ticker_interval']))
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2018-01-10 08:09:33 +00:00
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assert tt.log_has('Empty dataframe for pair xyz',
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caplog.record_tuples)
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2018-01-10 06:40:40 +00:00
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2018-01-20 20:24:28 +00:00
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def test_get_signal_old_dataframe(default_conf, mocker, caplog):
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2018-01-10 06:40:40 +00:00
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mocker.patch('freqtrade.analyze.get_ticker_history', return_value=1)
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# FIX: The get_signal function has hardcoded 10, which we must inturn hardcode
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oldtime = arrow.utcnow() - datetime.timedelta(minutes=11)
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ticks = DataFrame([{'buy': 1, 'date': oldtime}])
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mocker.patch('freqtrade.analyze.analyze_ticker', return_value=DataFrame(ticks))
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2018-01-20 20:24:28 +00:00
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assert (False, False) == get_signal('xyz', int(default_conf['ticker_interval']))
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2018-01-10 08:09:33 +00:00
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assert tt.log_has('Too old dataframe for pair xyz',
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caplog.record_tuples)
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2018-01-10 06:40:40 +00:00
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2018-01-05 11:43:56 +00:00
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def test_get_signal_handles_exceptions(mocker):
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mocker.patch('freqtrade.analyze.get_ticker_history', return_value=MagicMock())
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mocker.patch('freqtrade.analyze.analyze_ticker',
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side_effect=Exception('invalid ticker history '))
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2018-01-20 18:25:47 +00:00
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assert get_signal('BTC-ETH', 5) == (False, False)
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2018-01-21 13:25:15 +00:00
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def test_parse_ticker_dataframe(ticker_history, ticker_history_without_bv):
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columns = ['close', 'high', 'low', 'open', 'date', 'volume']
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# Test file with BV data
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dataframe = parse_ticker_dataframe(ticker_history)
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assert dataframe.columns.tolist() == columns
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# Test file without BV data
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dataframe = parse_ticker_dataframe(ticker_history_without_bv)
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assert dataframe.columns.tolist() == columns
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