from unittest.mock import MagicMock import pytest from arrow import Arrow from pandas import DataFrame, DateOffset, to_datetime from freqtrade.configuration import TimeRange from freqtrade.data.btanalysis import (BT_DATA_COLUMNS, combine_tickers_with_mean, create_cum_profit, extract_trades_of_period, load_backtest_data, load_trades, load_trades_from_db, analyze_trade_parallelism) from freqtrade.data.history import load_data, load_pair_history from tests.test_persistence import create_mock_trades def test_load_backtest_data(testdatadir): filename = testdatadir / "backtest-result_test.json" bt_data = load_backtest_data(filename) assert isinstance(bt_data, DataFrame) assert list(bt_data.columns) == BT_DATA_COLUMNS + ["profitabs"] assert len(bt_data) == 179 # Test loading from string (must yield same result) bt_data2 = load_backtest_data(str(filename)) assert bt_data.equals(bt_data2) with pytest.raises(ValueError, match=r"File .* does not exist\."): load_backtest_data(str("filename") + "nofile") @pytest.mark.usefixtures("init_persistence") def test_load_trades_from_db(default_conf, fee, mocker): create_mock_trades(fee) # remove init so it does not init again init_mock = mocker.patch('freqtrade.persistence.init', MagicMock()) trades = load_trades_from_db(db_url=default_conf['db_url']) assert init_mock.call_count == 1 assert len(trades) == 3 assert isinstance(trades, DataFrame) assert "pair" in trades.columns assert "open_time" in trades.columns assert "profitperc" in trades.columns for col in BT_DATA_COLUMNS: if col not in ['index', 'open_at_end']: assert col in trades.columns def test_extract_trades_of_period(testdatadir): pair = "UNITTEST/BTC" # 2018-11-14 06:07:00 timerange = TimeRange('date', None, 1510639620, 0) data = load_pair_history(pair=pair, ticker_interval='1m', datadir=testdatadir, timerange=timerange) trades = DataFrame( {'pair': [pair, pair, pair, pair], 'profit_percent': [0.0, 0.1, -0.2, -0.5], 'profit_abs': [0.0, 1, -2, -5], 'open_time': to_datetime([Arrow(2017, 11, 13, 15, 40, 0).datetime, Arrow(2017, 11, 14, 9, 41, 0).datetime, Arrow(2017, 11, 14, 14, 20, 0).datetime, Arrow(2017, 11, 15, 3, 40, 0).datetime, ], utc=True ), 'close_time': to_datetime([Arrow(2017, 11, 13, 16, 40, 0).datetime, Arrow(2017, 11, 14, 10, 41, 0).datetime, Arrow(2017, 11, 14, 15, 25, 0).datetime, Arrow(2017, 11, 15, 3, 55, 0).datetime, ], utc=True) }) trades1 = extract_trades_of_period(data, trades) # First and last trade are dropped as they are out of range assert len(trades1) == 2 assert trades1.iloc[0].open_time == Arrow(2017, 11, 14, 9, 41, 0).datetime assert trades1.iloc[0].close_time == Arrow(2017, 11, 14, 10, 41, 0).datetime assert trades1.iloc[-1].open_time == Arrow(2017, 11, 14, 14, 20, 0).datetime assert trades1.iloc[-1].close_time == Arrow(2017, 11, 14, 15, 25, 0).datetime def test_analyze_trade_parallelism(default_conf, mocker, testdatadir): filename = testdatadir / "backtest-result_test.json" bt_data = load_backtest_data(filename) res = analyze_trade_parallelism(bt_data, "5m") assert isinstance(res, DataFrame) assert 'open_trades' in res.columns assert res['open_trades'].max() == 3 assert res['open_trades'].min() == 0 def test_load_trades(default_conf, mocker): db_mock = mocker.patch("freqtrade.data.btanalysis.load_trades_from_db", MagicMock()) bt_mock = mocker.patch("freqtrade.data.btanalysis.load_backtest_data", MagicMock()) load_trades("DB", db_url=default_conf.get('db_url'), exportfilename=default_conf.get('exportfilename'), ) assert db_mock.call_count == 1 assert bt_mock.call_count == 0 db_mock.reset_mock() bt_mock.reset_mock() default_conf['exportfilename'] = "testfile.json" load_trades("file", db_url=default_conf.get('db_url'), exportfilename=default_conf.get('exportfilename'),) assert db_mock.call_count == 0 assert bt_mock.call_count == 1 def test_combine_tickers_with_mean(testdatadir): pairs = ["ETH/BTC", "ADA/BTC"] tickers = load_data(datadir=testdatadir, pairs=pairs, ticker_interval='5m' ) df = combine_tickers_with_mean(tickers) assert isinstance(df, DataFrame) assert "ETH/BTC" in df.columns assert "ADA/BTC" in df.columns assert "mean" in df.columns def test_create_cum_profit(testdatadir): filename = testdatadir / "backtest-result_test.json" bt_data = load_backtest_data(filename) timerange = TimeRange.parse_timerange("20180110-20180112") df = load_pair_history(pair="TRX/BTC", ticker_interval='5m', datadir=testdatadir, timerange=timerange) cum_profits = create_cum_profit(df.set_index('date'), bt_data[bt_data["pair"] == 'TRX/BTC'], "cum_profits", timeframe="5m") assert "cum_profits" in cum_profits.columns assert cum_profits.iloc[0]['cum_profits'] == 0 assert cum_profits.iloc[-1]['cum_profits'] == 0.0798005 def test_create_cum_profit1(testdatadir): filename = testdatadir / "backtest-result_test.json" bt_data = load_backtest_data(filename) # Move close-time to "off" the candle, to make sure the logic still works bt_data.loc[:, 'close_time'] = bt_data.loc[:, 'close_time'] + DateOffset(seconds=20) timerange = TimeRange.parse_timerange("20180110-20180112") df = load_pair_history(pair="TRX/BTC", ticker_interval='5m', datadir=testdatadir, timerange=timerange) cum_profits = create_cum_profit(df.set_index('date'), bt_data[bt_data["pair"] == 'TRX/BTC'], "cum_profits", timeframe="5m") assert "cum_profits" in cum_profits.columns assert cum_profits.iloc[0]['cum_profits'] == 0 assert cum_profits.iloc[-1]['cum_profits'] == 0.0798005