125 lines
4.8 KiB
Python
125 lines
4.8 KiB
Python
# pragma pylint: disable=missing-docstring, C0103
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import datetime
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from unittest.mock import MagicMock
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import arrow
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from pandas import DataFrame
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import freqtrade.tests.conftest as tt # test tools
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from freqtrade.analyze import (get_signal, parse_ticker_dataframe,
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populate_buy_trend, populate_indicators,
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populate_sell_trend)
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from freqtrade.strategy.strategy import Strategy
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def test_dataframe_correct_columns(result):
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assert result.columns.tolist() == \
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['close', 'high', 'low', 'open', 'date', 'volume']
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def test_dataframe_correct_length(result):
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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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def test_populates_buy_trend(result):
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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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dataframe = populate_buy_trend(populate_indicators(result, None), None)
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assert 'buy' in dataframe.columns
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def test_populates_sell_trend(result):
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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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dataframe = populate_sell_trend(populate_indicators(result, None), None)
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assert 'sell' in dataframe.columns
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def test_returns_latest_buy_signal(mocker):
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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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return_value=DataFrame([{'buy': 1, 'sell': 0, 'date': arrow.utcnow()}])
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)
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assert get_signal('BTC-ETH', 5) == (True, False)
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mocker.patch(
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'freqtrade.analyze.analyze_ticker',
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return_value=DataFrame([{'buy': 0, 'sell': 1, 'date': arrow.utcnow()}])
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)
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assert get_signal('BTC-ETH', 5) == (False, True)
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def test_returns_latest_sell_signal(mocker):
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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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return_value=DataFrame([{'sell': 1, 'buy': 0, 'date': arrow.utcnow()}])
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)
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assert get_signal('BTC-ETH', 5) == (False, True)
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mocker.patch(
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'freqtrade.analyze.analyze_ticker',
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return_value=DataFrame([{'sell': 0, 'buy': 1, 'date': arrow.utcnow()}])
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)
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assert get_signal('BTC-ETH', 5) == (True, False)
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def test_get_signal_empty(default_conf, mocker, caplog):
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mocker.patch('freqtrade.analyze.get_ticker_history', return_value=None)
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assert (False, False) == get_signal('foo', int(default_conf['ticker_interval']))
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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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def test_get_signal_exception_valueerror(default_conf, mocker, caplog):
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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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assert (False, False) == get_signal('foo', int(default_conf['ticker_interval']))
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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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def test_get_signal_empty_dataframe(default_conf, mocker, caplog):
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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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assert (False, False) == get_signal('xyz', int(default_conf['ticker_interval']))
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assert tt.log_has('Empty dataframe for pair xyz',
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caplog.record_tuples)
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def test_get_signal_old_dataframe(default_conf, mocker, caplog):
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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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assert (False, False) == get_signal('xyz', int(default_conf['ticker_interval']))
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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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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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assert get_signal('BTC-ETH', 5) == (False, False)
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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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