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https://github.com/freqtrade/freqtrade.git
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ruff format: Update a few test files
This commit is contained in:
Matthias
@@ -9,13 +9,14 @@ from freqtrade.util.datetime_helpers import dt_utc
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tests_start_time = dt_utc(2018, 10, 3)
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tests_timeframe = '1h'
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tests_timeframe = "1h"
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class BTrade(NamedTuple):
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"""
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Minimalistic Trade result used for functional backtesting
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"""
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exit_reason: ExitType
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open_tick: int
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close_tick: int
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@@ -27,6 +28,7 @@ class BTContainer(NamedTuple):
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"""
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Minimal BacktestContainer defining Backtest inputs and results.
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"""
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data: List[List[float]]
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stop_loss: float
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roi: Dict[str, float]
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@@ -51,22 +53,32 @@ def _get_frame_time_from_offset(offset):
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def _build_backtest_dataframe(data):
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columns = ['date', 'open', 'high', 'low', 'close', 'volume', 'enter_long', 'exit_long',
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'enter_short', 'exit_short']
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columns = [
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"date",
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"open",
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"high",
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"low",
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"close",
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"volume",
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"enter_long",
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"exit_long",
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"enter_short",
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"exit_short",
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]
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if len(data[0]) == 8:
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# No short columns
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data = [d + [0, 0] for d in data]
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columns = columns + ['enter_tag'] if len(data[0]) == 11 else columns
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columns = columns + ["enter_tag"] if len(data[0]) == 11 else columns
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frame = DataFrame.from_records(data, columns=columns)
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frame['date'] = frame['date'].apply(_get_frame_time_from_offset)
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frame["date"] = frame["date"].apply(_get_frame_time_from_offset)
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# Ensure floats are in place
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for column in ['open', 'high', 'low', 'close', 'volume']:
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frame[column] = frame[column].astype('float64')
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for column in ["open", "high", "low", "close", "volume"]:
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frame[column] = frame[column].astype("float64")
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# Ensure all candles make kindof sense
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assert all(frame['low'] <= frame['close'])
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assert all(frame['low'] <= frame['open'])
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assert all(frame['high'] >= frame['close'])
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assert all(frame['high'] >= frame['open'])
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assert all(frame["low"] <= frame["close"])
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assert all(frame["low"] <= frame["open"])
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assert all(frame["high"] >= frame["close"])
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assert all(frame["high"] >= frame["open"])
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return frame
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@@ -11,21 +11,23 @@ from freqtrade.optimize.hyperopt import Hyperopt
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from tests.conftest import patch_exchange
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@pytest.fixture(scope='function')
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@pytest.fixture(scope="function")
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def hyperopt_conf(default_conf):
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hyperconf = deepcopy(default_conf)
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hyperconf.update({
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'datadir': Path(default_conf['datadir']),
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'runmode': RunMode.HYPEROPT,
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'strategy': 'HyperoptableStrategy',
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'hyperopt_loss': 'ShortTradeDurHyperOptLoss',
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'hyperopt_path': str(Path(__file__).parent / 'hyperopts'),
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'epochs': 1,
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'timerange': None,
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'spaces': ['default'],
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'hyperopt_jobs': 1,
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'hyperopt_min_trades': 1,
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})
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hyperconf.update(
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{
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"datadir": Path(default_conf["datadir"]),
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"runmode": RunMode.HYPEROPT,
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"strategy": "HyperoptableStrategy",
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"hyperopt_loss": "ShortTradeDurHyperOptLoss",
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"hyperopt_path": str(Path(__file__).parent / "hyperopts"),
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"epochs": 1,
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"timerange": None,
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"spaces": ["default"],
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"hyperopt_jobs": 1,
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"hyperopt_min_trades": 1,
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}
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)
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return hyperconf
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@@ -36,32 +38,29 @@ def backtesting_cleanup():
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Backtesting.cleanup()
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@pytest.fixture(scope='function')
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@pytest.fixture(scope="function")
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def hyperopt(hyperopt_conf, mocker):
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patch_exchange(mocker)
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return Hyperopt(hyperopt_conf)
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@pytest.fixture(scope='function')
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@pytest.fixture(scope="function")
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def hyperopt_results():
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return pd.DataFrame(
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{
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'pair': ['ETH/USDT', 'ETH/USDT', 'ETH/USDT', 'ETH/USDT'],
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'profit_ratio': [-0.1, 0.2, -0.12, 0.3],
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'profit_abs': [-0.2, 0.4, -0.21, 0.6],
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'trade_duration': [10, 30, 10, 10],
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'amount': [0.1, 0.1, 0.1, 0.1],
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'exit_reason': [ExitType.STOP_LOSS, ExitType.ROI, ExitType.STOP_LOSS, ExitType.ROI],
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'open_date':
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[
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"pair": ["ETH/USDT", "ETH/USDT", "ETH/USDT", "ETH/USDT"],
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"profit_ratio": [-0.1, 0.2, -0.12, 0.3],
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"profit_abs": [-0.2, 0.4, -0.21, 0.6],
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"trade_duration": [10, 30, 10, 10],
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"amount": [0.1, 0.1, 0.1, 0.1],
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"exit_reason": [ExitType.STOP_LOSS, ExitType.ROI, ExitType.STOP_LOSS, ExitType.ROI],
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"open_date": [
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datetime(2019, 1, 1, 9, 15, 0),
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datetime(2019, 1, 2, 8, 55, 0),
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datetime(2019, 1, 3, 9, 15, 0),
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datetime(2019, 1, 4, 9, 15, 0),
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],
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'close_date':
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[
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"close_date": [
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datetime(2019, 1, 1, 9, 25, 0),
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datetime(2019, 1, 2, 9, 25, 0),
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datetime(2019, 1, 3, 9, 25, 0),
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File diff suppressed because it is too large
Load Diff
@@ -16,25 +16,26 @@ from tests.conftest import EXMS, patch_exchange
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def test_backtest_position_adjustment(default_conf, fee, mocker, testdatadir) -> None:
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default_conf['use_exit_signal'] = False
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default_conf['max_open_trades'] = 10
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mocker.patch(f'{EXMS}.get_fee', fee)
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mocker.patch('freqtrade.optimize.backtesting.amount_to_contract_precision',
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lambda x, *args, **kwargs: round(x, 8))
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default_conf["use_exit_signal"] = False
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default_conf["max_open_trades"] = 10
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mocker.patch(f"{EXMS}.get_fee", fee)
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mocker.patch(
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"freqtrade.optimize.backtesting.amount_to_contract_precision",
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lambda x, *args, **kwargs: round(x, 8),
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)
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mocker.patch(f"{EXMS}.get_min_pair_stake_amount", return_value=0.00001)
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mocker.patch(f"{EXMS}.get_max_pair_stake_amount", return_value=float('inf'))
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mocker.patch(f"{EXMS}.get_max_pair_stake_amount", return_value=float("inf"))
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patch_exchange(mocker)
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default_conf.update({
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"stake_amount": 100.0,
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"dry_run_wallet": 1000.0,
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"strategy": "StrategyTestV3"
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})
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default_conf.update(
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{"stake_amount": 100.0, "dry_run_wallet": 1000.0, "strategy": "StrategyTestV3"}
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)
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backtesting = Backtesting(default_conf)
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backtesting._set_strategy(backtesting.strategylist[0])
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pair = 'UNITTEST/BTC'
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timerange = TimeRange('date', None, 1517227800, 0)
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data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=['UNITTEST/BTC'],
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timerange=timerange)
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pair = "UNITTEST/BTC"
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timerange = TimeRange("date", None, 1517227800, 0)
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data = history.load_data(
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datadir=testdatadir, timeframe="5m", pairs=["UNITTEST/BTC"], timerange=timerange
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)
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backtesting.strategy.position_adjustment_enable = True
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processed = backtesting.strategy.advise_all_indicators(data)
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min_date, max_date = get_timerange(processed)
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@@ -43,47 +44,50 @@ def test_backtest_position_adjustment(default_conf, fee, mocker, testdatadir) ->
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start_date=min_date,
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end_date=max_date,
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)
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results = result['results']
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results = result["results"]
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assert not results.empty
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assert len(results) == 2
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expected = pd.DataFrame(
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{'pair': [pair, pair],
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'stake_amount': [500.0, 100.0],
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'max_stake_amount': [500.0, 100],
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'amount': [4806.87657523, 970.63960782],
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'open_date': pd.to_datetime([dt_utc(2018, 1, 29, 18, 40, 0),
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dt_utc(2018, 1, 30, 3, 30, 0)], utc=True
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),
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'close_date': pd.to_datetime([dt_utc(2018, 1, 29, 22, 00, 0),
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dt_utc(2018, 1, 30, 4, 10, 0)], utc=True),
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'open_rate': [0.10401764891917063, 0.10302485],
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'close_rate': [0.10453904064307624, 0.10354126528822055],
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'fee_open': [0.0025, 0.0025],
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'fee_close': [0.0025, 0.0025],
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'trade_duration': [200, 40],
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'profit_ratio': [0.0, 0.0],
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'profit_abs': [0.0, 0.0],
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'exit_reason': [ExitType.ROI.value, ExitType.ROI.value],
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'initial_stop_loss_abs': [0.0940005, 0.092722365],
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'initial_stop_loss_ratio': [-0.1, -0.1],
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'stop_loss_abs': [0.0940005, 0.092722365],
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'stop_loss_ratio': [-0.1, -0.1],
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'min_rate': [0.10370188, 0.10300000000000001],
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'max_rate': [0.10481985, 0.10388887000000001],
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'is_open': [False, False],
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'enter_tag': ['', ''],
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'leverage': [1.0, 1.0],
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'is_short': [False, False],
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'open_timestamp': [1517251200000, 1517283000000],
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'close_timestamp': [1517263200000, 1517285400000],
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})
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results_no = results.drop(columns=['orders'])
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{
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"pair": [pair, pair],
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"stake_amount": [500.0, 100.0],
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"max_stake_amount": [500.0, 100],
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"amount": [4806.87657523, 970.63960782],
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"open_date": pd.to_datetime(
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[dt_utc(2018, 1, 29, 18, 40, 0), dt_utc(2018, 1, 30, 3, 30, 0)], utc=True
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),
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"close_date": pd.to_datetime(
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[dt_utc(2018, 1, 29, 22, 00, 0), dt_utc(2018, 1, 30, 4, 10, 0)], utc=True
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),
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"open_rate": [0.10401764891917063, 0.10302485],
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"close_rate": [0.10453904064307624, 0.10354126528822055],
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"fee_open": [0.0025, 0.0025],
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"fee_close": [0.0025, 0.0025],
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"trade_duration": [200, 40],
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"profit_ratio": [0.0, 0.0],
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"profit_abs": [0.0, 0.0],
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"exit_reason": [ExitType.ROI.value, ExitType.ROI.value],
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"initial_stop_loss_abs": [0.0940005, 0.092722365],
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"initial_stop_loss_ratio": [-0.1, -0.1],
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"stop_loss_abs": [0.0940005, 0.092722365],
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"stop_loss_ratio": [-0.1, -0.1],
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"min_rate": [0.10370188, 0.10300000000000001],
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"max_rate": [0.10481985, 0.10388887000000001],
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"is_open": [False, False],
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"enter_tag": ["", ""],
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"leverage": [1.0, 1.0],
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"is_short": [False, False],
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"open_timestamp": [1517251200000, 1517283000000],
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"close_timestamp": [1517263200000, 1517285400000],
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}
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)
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results_no = results.drop(columns=["orders"])
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pd.testing.assert_frame_equal(results_no, expected, check_exact=True)
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data_pair = processed[pair]
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assert len(results.iloc[0]['orders']) == 6
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assert len(results.iloc[1]['orders']) == 2
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assert len(results.iloc[0]["orders"]) == 6
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assert len(results.iloc[1]["orders"]) == 2
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for _, t in results.iterrows():
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ln = data_pair.loc[data_pair["date"] == t["open_date"]]
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@@ -91,65 +95,65 @@ def test_backtest_position_adjustment(default_conf, fee, mocker, testdatadir) ->
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assert ln is not None
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# check close trade rate aligns to close rate or is between high and low
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ln = data_pair.loc[data_pair["date"] == t["close_date"]]
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assert (round(ln.iloc[0]["open"], 6) == round(t["close_rate"], 6) or
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round(ln.iloc[0]["low"], 6) < round(
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t["close_rate"], 6) < round(ln.iloc[0]["high"], 6))
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assert round(ln.iloc[0]["open"], 6) == round(t["close_rate"], 6) or round(
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ln.iloc[0]["low"], 6
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) < round(t["close_rate"], 6) < round(ln.iloc[0]["high"], 6)
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@pytest.mark.parametrize('leverage', [
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1, 2
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])
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@pytest.mark.parametrize("leverage", [1, 2])
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def test_backtest_position_adjustment_detailed(default_conf, fee, mocker, leverage) -> None:
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default_conf['use_exit_signal'] = False
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mocker.patch(f'{EXMS}.get_fee', fee)
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default_conf["use_exit_signal"] = False
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mocker.patch(f"{EXMS}.get_fee", fee)
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mocker.patch(f"{EXMS}.get_min_pair_stake_amount", return_value=10)
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mocker.patch(f"{EXMS}.get_max_pair_stake_amount", return_value=float('inf'))
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mocker.patch(f"{EXMS}.get_max_pair_stake_amount", return_value=float("inf"))
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mocker.patch(f"{EXMS}.get_max_leverage", return_value=10)
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mocker.patch(f"{EXMS}.get_maintenance_ratio_and_amt", return_value=(0.1, 0.1))
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mocker.patch('freqtrade.optimize.backtesting.Backtesting._run_funding_fees')
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mocker.patch("freqtrade.optimize.backtesting.Backtesting._run_funding_fees")
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patch_exchange(mocker)
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default_conf.update({
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"stake_amount": 100.0,
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"dry_run_wallet": 1000.0,
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"strategy": "StrategyTestV3",
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"trading_mode": "futures",
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"margin_mode": "isolated",
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})
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default_conf['pairlists'] = [{'method': 'StaticPairList', 'allow_inactive': True}]
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default_conf.update(
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{
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"stake_amount": 100.0,
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"dry_run_wallet": 1000.0,
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"strategy": "StrategyTestV3",
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"trading_mode": "futures",
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"margin_mode": "isolated",
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}
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)
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default_conf["pairlists"] = [{"method": "StaticPairList", "allow_inactive": True}]
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backtesting = Backtesting(default_conf)
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backtesting._can_short = True
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backtesting._set_strategy(backtesting.strategylist[0])
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pair = 'XRP/USDT:USDT'
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pair = "XRP/USDT:USDT"
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row_enter = [
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pd.Timestamp(year=2020, month=1, day=1, hour=4, minute=0),
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2.1, # Open
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2.2, # High
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1.9, # Low
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2.1, # Close
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1, # enter_long
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0, # exit_long
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0, # enter_short
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0, # exit_short
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'', # enter_tag
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'', # exit_tag
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]
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pd.Timestamp(year=2020, month=1, day=1, hour=4, minute=0),
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2.1, # Open
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2.2, # High
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1.9, # Low
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2.1, # Close
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1, # enter_long
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0, # exit_long
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0, # enter_short
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0, # exit_short
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"", # enter_tag
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"", # exit_tag
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]
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# Exit row - with slightly different values
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row_exit = [
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pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=0),
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2.2, # Open
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2.3, # High
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2.0, # Low
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2.2, # Close
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1, # enter_long
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0, # exit_long
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0, # enter_short
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0, # exit_short
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'', # enter_tag
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'', # exit_tag
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]
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pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=0),
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2.2, # Open
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2.3, # High
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2.0, # Low
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2.2, # Close
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1, # enter_long
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0, # exit_long
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0, # enter_short
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0, # exit_short
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"", # enter_tag
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"", # exit_tag
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]
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backtesting.strategy.leverage = MagicMock(return_value=leverage)
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trade = backtesting._enter_trade(pair, row=row_enter, direction='long')
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trade = backtesting._enter_trade(pair, row=row_enter, direction="long")
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current_time = row_enter[0].to_pydatetime()
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assert trade
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assert pytest.approx(trade.stake_amount) == 100.0
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@@ -164,7 +168,7 @@ def test_backtest_position_adjustment_detailed(default_conf, fee, mocker, levera
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assert pytest.approx(trade.amount) == 47.61904762 * leverage
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assert len(trade.orders) == 1
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# Increase position by 100
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backtesting.strategy.adjust_trade_position = MagicMock(return_value=(100, 'PartIncrease'))
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backtesting.strategy.adjust_trade_position = MagicMock(return_value=(100, "PartIncrease"))
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trade = backtesting._get_adjust_trade_entry_for_candle(trade, row_enter, current_time)
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@@ -173,7 +177,7 @@ def test_backtest_position_adjustment_detailed(default_conf, fee, mocker, levera
|
||||
assert pytest.approx(trade.stake_amount) == 200.0
|
||||
assert pytest.approx(trade.amount) == 95.23809524 * leverage
|
||||
assert len(trade.orders) == 2
|
||||
assert trade.orders[-1].ft_order_tag == 'PartIncrease'
|
||||
assert trade.orders[-1].ft_order_tag == "PartIncrease"
|
||||
assert pytest.approx(trade.liquidation_price) == liq_price
|
||||
|
||||
# Reduce by more than amount - no change to trade.
|
||||
@@ -190,14 +194,14 @@ def test_backtest_position_adjustment_detailed(default_conf, fee, mocker, levera
|
||||
assert pytest.approx(trade.liquidation_price) == liq_price
|
||||
|
||||
# Reduce position by 50
|
||||
backtesting.strategy.adjust_trade_position = MagicMock(return_value=(-100, 'partDecrease'))
|
||||
backtesting.strategy.adjust_trade_position = MagicMock(return_value=(-100, "partDecrease"))
|
||||
trade = backtesting._get_adjust_trade_entry_for_candle(trade, row_exit, current_time)
|
||||
|
||||
assert trade
|
||||
assert pytest.approx(trade.stake_amount) == 100.0
|
||||
assert pytest.approx(trade.amount) == 47.61904762 * leverage
|
||||
assert len(trade.orders) == 3
|
||||
assert trade.orders[-1].ft_order_tag == 'partDecrease'
|
||||
assert trade.orders[-1].ft_order_tag == "partDecrease"
|
||||
assert trade.nr_of_successful_entries == 2
|
||||
assert trade.nr_of_successful_exits == 1
|
||||
assert pytest.approx(trade.liquidation_price) == liq_price
|
||||
|
||||
Reference in New Issue
Block a user