# pragma pylint: disable=missing-docstring, C0103, C0330 # pragma pylint: disable=protected-access, too-many-lines, invalid-name, too-many-arguments import logging import math from datetime import timedelta from unittest.mock import MagicMock import numpy as np import pytest from pandas import DataFrame from freqtrade.data.converter import ohlcv_to_dataframe from freqtrade.edge import Edge, PairInfo from freqtrade.enums import ExitType from freqtrade.exceptions import OperationalException from freqtrade.util.datetime_helpers import dt_ts, dt_utc from tests.conftest import EXMS, get_patched_freqtradebot, log_has from tests.optimize import ( BTContainer, BTrade, _build_backtest_dataframe, _get_frame_time_from_offset, ) # Cases to be tested: # 1) Open trade should be removed from the end # 2) Two complete trades within dataframe (with sell hit for all) # 3) Entered, sl 1%, candle drops 8% => Trade closed, 1% loss # 4) Entered, sl 3%, candle drops 4%, recovers to 1% => Trade closed, 3% loss # 5) Stoploss and sell are hit. should sell on stoploss #################################################################### tests_start_time = dt_utc(2018, 10, 3) timeframe_in_minute = 60 # End helper functions # Open trade should be removed from the end tc0 = BTContainer( data=[ # D O H L C V B S [0, 5000, 5025, 4975, 4987, 6172, 1, 0], [1, 5000, 5025, 4975, 4987, 6172, 0, 1], ], # enter trade (signal on last candle) stop_loss=-0.99, roi={"0": float("inf")}, profit_perc=0.00, trades=[], ) # Two complete trades within dataframe(with sell hit for all) tc1 = BTContainer( data=[ # D O H L C V B S [0, 5000, 5025, 4975, 4987, 6172, 1, 0], [1, 5000, 5025, 4975, 4987, 6172, 0, 1], # enter trade (signal on last candle) [2, 5000, 5025, 4975, 4987, 6172, 0, 0], # exit at open [3, 5000, 5025, 4975, 4987, 6172, 1, 0], # no action [4, 5000, 5025, 4975, 4987, 6172, 0, 0], # should enter the trade [5, 5000, 5025, 4975, 4987, 6172, 0, 1], # no action [6, 5000, 5025, 4975, 4987, 6172, 0, 0], # should sell ], stop_loss=-0.99, roi={"0": float("inf")}, profit_perc=0.00, trades=[ BTrade(exit_reason=ExitType.EXIT_SIGNAL, open_tick=1, close_tick=2), BTrade(exit_reason=ExitType.EXIT_SIGNAL, open_tick=4, close_tick=6), ], ) # 3) Entered, sl 1%, candle drops 8% => Trade closed, 1% loss tc2 = BTContainer( data=[ # D O H L C V B S [0, 5000, 5025, 4975, 4987, 6172, 1, 0], [1, 5000, 5025, 4600, 4987, 6172, 0, 0], # enter trade, stoploss hit [2, 5000, 5025, 4975, 4987, 6172, 0, 0], ], stop_loss=-0.01, roi={"0": float("inf")}, profit_perc=-0.01, trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)], ) # 4) Entered, sl 3 %, candle drops 4%, recovers to 1 % = > Trade closed, 3 % loss tc3 = BTContainer( data=[ # D O H L C V B S [0, 5000, 5025, 4975, 4987, 6172, 1, 0], [1, 5000, 5025, 4800, 4987, 6172, 0, 0], # enter trade, stoploss hit [2, 5000, 5025, 4975, 4987, 6172, 0, 0], ], stop_loss=-0.03, roi={"0": float("inf")}, profit_perc=-0.03, trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)], ) # 5) Stoploss and sell are hit. should sell on stoploss tc4 = BTContainer( data=[ # D O H L C V B S [0, 5000, 5025, 4975, 4987, 6172, 1, 0], [1, 5000, 5025, 4800, 4987, 6172, 0, 1], # enter trade, stoploss hit, sell signal [2, 5000, 5025, 4975, 4987, 6172, 0, 0], ], stop_loss=-0.03, roi={"0": float("inf")}, profit_perc=-0.03, trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)], ) TESTS = [tc0, tc1, tc2, tc3, tc4] @pytest.mark.parametrize("data", TESTS) def test_edge_results(edge_conf, mocker, caplog, data) -> None: """ run functional tests """ freqtrade = get_patched_freqtradebot(mocker, edge_conf) edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) frame = _build_backtest_dataframe(data.data) caplog.set_level(logging.DEBUG) edge.fee = 0 trades = edge._find_trades_for_stoploss_range(frame, "TEST/BTC", [data.stop_loss]) results = edge._fill_calculable_fields(DataFrame(trades)) if trades else DataFrame() assert len(trades) == len(data.trades) if not results.empty: assert round(results["profit_ratio"].sum(), 3) == round(data.profit_perc, 3) for c, trade in enumerate(data.trades): res = results.iloc[c] assert res.exit_type == trade.exit_reason assert res.open_date == _get_frame_time_from_offset(trade.open_tick).replace(tzinfo=None) assert res.close_date == _get_frame_time_from_offset(trade.close_tick).replace(tzinfo=None) def test_adjust(mocker, edge_conf): freqtrade = get_patched_freqtradebot(mocker, edge_conf) edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) mocker.patch( "freqtrade.edge.Edge._cached_pairs", mocker.PropertyMock( return_value={ "E/F": PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60), "C/D": PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60), "N/O": PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60), } ), ) pairs = ["A/B", "C/D", "E/F", "G/H"] assert edge.adjust(pairs) == ["E/F", "C/D"] def test_edge_get_stoploss(mocker, edge_conf): freqtrade = get_patched_freqtradebot(mocker, edge_conf) edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) mocker.patch( "freqtrade.edge.Edge._cached_pairs", mocker.PropertyMock( return_value={ "E/F": PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60), "C/D": PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60), "N/O": PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60), } ), ) assert edge.get_stoploss("E/F") == -0.01 def test_nonexisting_get_stoploss(mocker, edge_conf): freqtrade = get_patched_freqtradebot(mocker, edge_conf) edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) mocker.patch( "freqtrade.edge.Edge._cached_pairs", mocker.PropertyMock( return_value={ "E/F": PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60), } ), ) assert edge.get_stoploss("N/O") == -0.1 def test_edge_stake_amount(mocker, edge_conf): freqtrade = get_patched_freqtradebot(mocker, edge_conf) edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) mocker.patch( "freqtrade.edge.Edge._cached_pairs", mocker.PropertyMock( return_value={ "E/F": PairInfo(-0.02, 0.66, 3.71, 0.50, 1.71, 10, 60), } ), ) assert edge._capital_ratio == 0.5 assert ( edge.stake_amount("E/F", free_capital=100, total_capital=100, capital_in_trade=25) == 31.25 ) assert edge.stake_amount("E/F", free_capital=20, total_capital=100, capital_in_trade=25) == 20 assert edge.stake_amount("E/F", free_capital=0, total_capital=100, capital_in_trade=25) == 0 # Test with increased allowed_risk # Result should be no more than allowed capital edge._allowed_risk = 0.4 edge._capital_ratio = 0.5 assert ( edge.stake_amount("E/F", free_capital=100, total_capital=100, capital_in_trade=25) == 62.5 ) assert edge.stake_amount("E/F", free_capital=100, total_capital=100, capital_in_trade=0) == 50 edge._capital_ratio = 1 # Full capital is available assert edge.stake_amount("E/F", free_capital=100, total_capital=100, capital_in_trade=0) == 100 # Full capital is available assert edge.stake_amount("E/F", free_capital=0, total_capital=100, capital_in_trade=0) == 0 def test_nonexisting_stake_amount(mocker, edge_conf): freqtrade = get_patched_freqtradebot(mocker, edge_conf) edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) mocker.patch( "freqtrade.edge.Edge._cached_pairs", mocker.PropertyMock( return_value={ "E/F": PairInfo(-0.11, 0.66, 3.71, 0.50, 1.71, 10, 60), } ), ) # should use strategy stoploss assert edge.stake_amount("N/O", 1, 2, 1) == 0.15 def test_edge_heartbeat_calculate(mocker, edge_conf): freqtrade = get_patched_freqtradebot(mocker, edge_conf) edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) heartbeat = edge_conf["edge"]["process_throttle_secs"] # should not recalculate if heartbeat not reached edge._last_updated = dt_ts() - heartbeat + 1 assert edge.calculate(edge_conf["exchange"]["pair_whitelist"]) is False def mocked_load_data(datadir, pairs=None, timeframe="0m", timerange=None, *args, **kwargs): if pairs is None: pairs = [] hz = 0.1 base = 0.001 NEOBTC = [ [ dt_ts(tests_start_time + timedelta(minutes=(x * timeframe_in_minute))), math.sin(x * hz) / 1000 + base, math.sin(x * hz) / 1000 + base + 0.0001, math.sin(x * hz) / 1000 + base - 0.0001, math.sin(x * hz) / 1000 + base, 123.45, ] for x in range(0, 500) ] hz = 0.2 base = 0.002 LTCBTC = [ [ dt_ts(tests_start_time + timedelta(minutes=(x * timeframe_in_minute))), math.sin(x * hz) / 1000 + base, math.sin(x * hz) / 1000 + base + 0.0001, math.sin(x * hz) / 1000 + base - 0.0001, math.sin(x * hz) / 1000 + base, 123.45, ] for x in range(0, 500) ] pairdata = { "NEO/BTC": ohlcv_to_dataframe(NEOBTC, "1h", pair="NEO/BTC", fill_missing=True), "LTC/BTC": ohlcv_to_dataframe(LTCBTC, "1h", pair="LTC/BTC", fill_missing=True), } return pairdata def test_edge_process_downloaded_data(mocker, edge_conf): freqtrade = get_patched_freqtradebot(mocker, edge_conf) mocker.patch(f"{EXMS}.get_fee", MagicMock(return_value=0.001)) mocker.patch("freqtrade.edge.edge_positioning.refresh_data", MagicMock()) mocker.patch("freqtrade.edge.edge_positioning.load_data", mocked_load_data) edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) assert edge.calculate(edge_conf["exchange"]["pair_whitelist"]) assert len(edge._cached_pairs) == 2 assert edge._last_updated <= dt_ts() + 2 def test_edge_process_no_data(mocker, edge_conf, caplog): freqtrade = get_patched_freqtradebot(mocker, edge_conf) mocker.patch(f"{EXMS}.get_fee", MagicMock(return_value=0.001)) mocker.patch("freqtrade.edge.edge_positioning.refresh_data", MagicMock()) mocker.patch("freqtrade.edge.edge_positioning.load_data", MagicMock(return_value={})) edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) assert not edge.calculate(edge_conf["exchange"]["pair_whitelist"]) assert len(edge._cached_pairs) == 0 assert log_has("No data found. Edge is stopped ...", caplog) assert edge._last_updated == 0 def test_edge_process_no_trades(mocker, edge_conf, caplog): freqtrade = get_patched_freqtradebot(mocker, edge_conf) mocker.patch(f"{EXMS}.get_fee", return_value=0.001) mocker.patch( "freqtrade.edge.edge_positioning.refresh_data", ) mocker.patch("freqtrade.edge.edge_positioning.load_data", mocked_load_data) # Return empty mocker.patch("freqtrade.edge.Edge._find_trades_for_stoploss_range", return_value=[]) edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) assert not edge.calculate(edge_conf["exchange"]["pair_whitelist"]) assert len(edge._cached_pairs) == 0 assert log_has("No trades found.", caplog) def test_edge_process_no_pairs(mocker, edge_conf, caplog): edge_conf["exchange"]["pair_whitelist"] = [] mocker.patch("freqtrade.freqtradebot.validate_config_consistency") freqtrade = get_patched_freqtradebot(mocker, edge_conf) fee_mock = mocker.patch(f"{EXMS}.get_fee", return_value=0.001) mocker.patch("freqtrade.edge.edge_positioning.refresh_data") mocker.patch("freqtrade.edge.edge_positioning.load_data", mocked_load_data) # Return empty mocker.patch("freqtrade.edge.Edge._find_trades_for_stoploss_range", return_value=[]) edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) assert fee_mock.call_count == 0 assert edge.fee is None assert not edge.calculate(["XRP/USDT"]) assert fee_mock.call_count == 1 assert edge.fee == 0.001 def test_edge_init_error(mocker, edge_conf): edge_conf["stake_amount"] = 0.5 mocker.patch(f"{EXMS}.get_fee", MagicMock(return_value=0.001)) with pytest.raises(OperationalException, match="Edge works only with unlimited stake amount"): get_patched_freqtradebot(mocker, edge_conf) @pytest.mark.parametrize( "fee,risk_reward_ratio,expectancy", [ (0.0005, 306.5384615384, 101.5128205128), (0.001, 152.6923076923, 50.2307692308), ], ) def test_process_expectancy(mocker, edge_conf, fee, risk_reward_ratio, expectancy): edge_conf["edge"]["min_trade_number"] = 2 freqtrade = get_patched_freqtradebot(mocker, edge_conf) def get_fee(*args, **kwargs): return fee freqtrade.exchange.get_fee = get_fee edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) trades = [ { "pair": "TEST/BTC", "stoploss": -0.9, "profit_percent": "", "profit_abs": "", "open_date": np.datetime64("2018-10-03T00:05:00.000000000"), "close_date": np.datetime64("2018-10-03T00:10:00.000000000"), "trade_duration": "", "open_rate": 17, "close_rate": 17, "exit_type": "exit_signal", }, { "pair": "TEST/BTC", "stoploss": -0.9, "profit_percent": "", "profit_abs": "", "open_date": np.datetime64("2018-10-03T00:20:00.000000000"), "close_date": np.datetime64("2018-10-03T00:25:00.000000000"), "trade_duration": "", "open_rate": 20, "close_rate": 20, "exit_type": "exit_signal", }, { "pair": "TEST/BTC", "stoploss": -0.9, "profit_percent": "", "profit_abs": "", "open_date": np.datetime64("2018-10-03T00:30:00.000000000"), "close_date": np.datetime64("2018-10-03T00:40:00.000000000"), "trade_duration": "", "open_rate": 26, "close_rate": 34, "exit_type": "exit_signal", }, ] trades_df = DataFrame(trades) trades_df = edge._fill_calculable_fields(trades_df) final = edge._process_expectancy(trades_df) assert len(final) == 1 assert "TEST/BTC" in final assert final["TEST/BTC"].stoploss == -0.9 assert round(final["TEST/BTC"].winrate, 10) == 0.3333333333 assert round(final["TEST/BTC"].risk_reward_ratio, 10) == risk_reward_ratio assert round(final["TEST/BTC"].required_risk_reward, 10) == 2.0 assert round(final["TEST/BTC"].expectancy, 10) == expectancy # Pop last item so no trade is profitable trades.pop() trades_df = DataFrame(trades) trades_df = edge._fill_calculable_fields(trades_df) final = edge._process_expectancy(trades_df) assert len(final) == 0 assert isinstance(final, dict) def test_process_expectancy_remove_pumps(mocker, edge_conf, fee): edge_conf["edge"]["min_trade_number"] = 2 edge_conf["edge"]["remove_pumps"] = True freqtrade = get_patched_freqtradebot(mocker, edge_conf) freqtrade.exchange.get_fee = fee edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) trades = [ { "pair": "TEST/BTC", "stoploss": -0.9, "profit_percent": "", "profit_abs": "", "open_date": np.datetime64("2018-10-03T00:05:00.000000000"), "close_date": np.datetime64("2018-10-03T00:10:00.000000000"), "open_index": 1, "close_index": 1, "trade_duration": "", "open_rate": 17, "close_rate": 15, "exit_type": "sell_signal", }, { "pair": "TEST/BTC", "stoploss": -0.9, "profit_percent": "", "profit_abs": "", "open_date": np.datetime64("2018-10-03T00:20:00.000000000"), "close_date": np.datetime64("2018-10-03T00:25:00.000000000"), "open_index": 4, "close_index": 4, "trade_duration": "", "open_rate": 20, "close_rate": 10, "exit_type": "sell_signal", }, { "pair": "TEST/BTC", "stoploss": -0.9, "profit_percent": "", "profit_abs": "", "open_date": np.datetime64("2018-10-03T00:20:00.000000000"), "close_date": np.datetime64("2018-10-03T00:25:00.000000000"), "open_index": 4, "close_index": 4, "trade_duration": "", "open_rate": 20, "close_rate": 10, "exit_type": "sell_signal", }, { "pair": "TEST/BTC", "stoploss": -0.9, "profit_percent": "", "profit_abs": "", "open_date": np.datetime64("2018-10-03T00:20:00.000000000"), "close_date": np.datetime64("2018-10-03T00:25:00.000000000"), "open_index": 4, "close_index": 4, "trade_duration": "", "open_rate": 20, "close_rate": 10, "exit_type": "sell_signal", }, { "pair": "TEST/BTC", "stoploss": -0.9, "profit_percent": "", "profit_abs": "", "open_date": np.datetime64("2018-10-03T00:20:00.000000000"), "close_date": np.datetime64("2018-10-03T00:25:00.000000000"), "open_index": 4, "close_index": 4, "trade_duration": "", "open_rate": 20, "close_rate": 10, "exit_type": "sell_signal", }, { "pair": "TEST/BTC", "stoploss": -0.9, "profit_percent": "", "profit_abs": "", "open_date": np.datetime64("2018-10-03T00:30:00.000000000"), "close_date": np.datetime64("2018-10-03T00:40:00.000000000"), "open_index": 6, "close_index": 7, "trade_duration": "", "open_rate": 26, "close_rate": 134, "exit_type": "sell_signal", }, ] trades_df = DataFrame(trades) trades_df = edge._fill_calculable_fields(trades_df) final = edge._process_expectancy(trades_df) assert "TEST/BTC" in final assert final["TEST/BTC"].stoploss == -0.9 assert final["TEST/BTC"].nb_trades == len(trades_df) - 1 assert round(final["TEST/BTC"].winrate, 10) == 0.0 def test_process_expectancy_only_wins(mocker, edge_conf, fee): edge_conf["edge"]["min_trade_number"] = 2 freqtrade = get_patched_freqtradebot(mocker, edge_conf) freqtrade.exchange.get_fee = fee edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy) trades = [ { "pair": "TEST/BTC", "stoploss": -0.9, "profit_percent": "", "profit_abs": "", "open_date": np.datetime64("2018-10-03T00:05:00.000000000"), "close_date": np.datetime64("2018-10-03T00:10:00.000000000"), "open_index": 1, "close_index": 1, "trade_duration": "", "open_rate": 15, "close_rate": 17, "exit_type": "sell_signal", }, { "pair": "TEST/BTC", "stoploss": -0.9, "profit_percent": "", "profit_abs": "", "open_date": np.datetime64("2018-10-03T00:20:00.000000000"), "close_date": np.datetime64("2018-10-03T00:25:00.000000000"), "open_index": 4, "close_index": 4, "trade_duration": "", "open_rate": 10, "close_rate": 20, "exit_type": "sell_signal", }, { "pair": "TEST/BTC", "stoploss": -0.9, "profit_percent": "", "profit_abs": "", "open_date": np.datetime64("2018-10-03T00:30:00.000000000"), "close_date": np.datetime64("2018-10-03T00:40:00.000000000"), "open_index": 6, "close_index": 7, "trade_duration": "", "open_rate": 26, "close_rate": 134, "exit_type": "sell_signal", }, ] trades_df = DataFrame(trades) trades_df = edge._fill_calculable_fields(trades_df) final = edge._process_expectancy(trades_df) assert "TEST/BTC" in final assert final["TEST/BTC"].stoploss == -0.9 assert final["TEST/BTC"].nb_trades == len(trades_df) assert round(final["TEST/BTC"].winrate, 10) == 1.0 assert round(final["TEST/BTC"].risk_reward_ratio, 10) == float("inf") assert round(final["TEST/BTC"].expectancy, 10) == float("inf")