diff --git a/tests/optimize/test_backtesting.py b/tests/optimize/test_backtesting.py index c396e1135..5bc113a62 100644 --- a/tests/optimize/test_backtesting.py +++ b/tests/optimize/test_backtesting.py @@ -1656,38 +1656,6 @@ def test_backtest_multi_pair_detail( else: assert bl_spy.call_count < 2495 - # List of calls pair args - in batches of 5 (s) - calls_per_candle = defaultdict(list) - for call in vr_spy.call_args_list: - calls_per_candle[call[0][3]].append(call[0][1]) - - all_orients = [x for _, x in calls_per_candle.items()] - - distinct_calls = [list(x) for x in set(tuple(x) for x in all_orients)] - - # All calls must be made for the full pairlist - assert all(len(x) == 5 for x in distinct_calls) - - # order varied - and is not always identical - assert not all( - x == ["ADA/USDT", "DASH/USDT", "ETH/USDT", "LTC/USDT", "NXT/USDT"] for x in distinct_calls - ) - # But some calls should've kept the original ordering - assert any( - x == ["ADA/USDT", "DASH/USDT", "ETH/USDT", "LTC/USDT", "NXT/USDT"] for x in distinct_calls - ) - assert ( - # Ordering can be different, but should be one of the following - any( - x == ["ETH/USDT", "ADA/USDT", "DASH/USDT", "LTC/USDT", "NXT/USDT"] - for x in distinct_calls - ) - or any( - x == ["ETH/USDT", "LTC/USDT", "ADA/USDT", "DASH/USDT", "NXT/USDT"] - for x in distinct_calls - ) - ) - # Make sure we have parallel trades assert len(evaluate_result_multi(results["results"], "5m", 2)) > 0 # make sure we don't have trades with more than configured max_open_trades @@ -1713,6 +1681,112 @@ def test_backtest_multi_pair_detail( assert len(evaluate_result_multi(results["results"], "5m", 1)) == 0 +@pytest.mark.parametrize("use_detail", [True, False]) +def test_backtest_multi_pair_long_short_switch( + default_conf_usdt, + fee, + mocker, + use_detail, +): + """ + literally the same as test_backtest_multi_pair - but with artificial data + and detail timeframe. + """ + + def _trend_alternate_hold(dataframe=None, metadata=None): + """ + Buy every xth candle - sell every other xth -2 (hold on to pairs a bit) + """ + if metadata["pair"] in ("ETH/USDT", "LTC/USDT"): + multi = 20 + else: + multi = 18 + dataframe["enter_long"] = np.where(dataframe.index % multi == 0, 1, 0) + dataframe["exit_long"] = np.where((dataframe.index + multi - 2) % multi == 0, 1, 0) + dataframe["enter_short"] = dataframe["exit_long"] + dataframe["exit_short"] = dataframe["enter_long"] + return dataframe + + default_conf_usdt.update( + { + "runmode": "backtest", + "timeframe": "5m", + "max_open_trades": 1, + "stoploss": -1.0, + "minimal_roi": {"0": 100}, + "margin_mode": "isolated", + "trading_mode": "futures", + } + ) + + if use_detail: + default_conf_usdt["timeframe_detail"] = "1m" + + mocker.patch(f"{EXMS}.get_min_pair_stake_amount", return_value=0.00001) + mocker.patch(f"{EXMS}.get_max_pair_stake_amount", return_value=float("inf")) + mocker.patch(f"{EXMS}.get_fee", fee) + patch_exchange(mocker) + + raw_candles_1m = generate_test_data("1m", 2500, "2022-01-03 12:00:00+00:00") + raw_candles = ohlcv_fill_up_missing_data(raw_candles_1m, "5m", "dummy") + + pairs = [ + "ETH/USDT:USDT", + ] + default_conf_usdt["exchange"]["pair_whitelist"] = pairs + # Fake whitelist to avoid some mock data issues + mocker.patch(f"{EXMS}.get_maintenance_ratio_and_amt", return_value=(0.01, 0.01)) + + data = {pair: raw_candles for pair in pairs} + detail_data = {pair: raw_candles_1m for pair in pairs} + + # Only use 500 lines to increase performance + data = trim_dictlist(data, -500) + + backtesting = Backtesting(default_conf_usdt) + vr_spy = mocker.spy(backtesting, "validate_row") + bl_spy = mocker.spy(backtesting, "backtest_loop") + backtesting.detail_data = detail_data + backtesting.funding_fee_timeframe_secs = 3600 * 8 # 8h + backtesting.futures_data = {pair: pd.DataFrame() for pair in pairs} + + backtesting.strategylist[0].can_short = True + backtesting._set_strategy(backtesting.strategylist[0]) + backtesting.strategy.bot_loop_start = MagicMock() + backtesting.strategy.advise_entry = _trend_alternate_hold # Override + backtesting.strategy.advise_exit = _trend_alternate_hold # Override + + processed = backtesting.strategy.advise_all_indicators(data) + min_date, max_date = get_timerange(processed) + + backtest_conf = { + "processed": deepcopy(processed), + "start_date": min_date, + "end_date": max_date, + } + + results = backtesting.backtest(**backtest_conf) + + # bot_loop_start is called once per candle. + assert backtesting.strategy.bot_loop_start.call_count == 499 + # Validated row once per candle and pair + assert vr_spy.call_count == 499 + + if use_detail: + # Backtest loop is called once per candle per pair + assert bl_spy.call_count == 1071 + else: + assert bl_spy.call_count == 479 + + # Make sure we have parallel trades + assert len(evaluate_result_multi(results["results"], "5m", 0)) > 0 + # make sure we don't have trades with more than configured max_open_trades + assert len(evaluate_result_multi(results["results"], "5m", 1)) == 0 + + # Expect 26 results initially + assert len(results["results"]) == 30 + + def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir): patch_exchange(mocker) mocker.patch("freqtrade.optimize.backtesting.Backtesting.backtest")