CryptoTrading/tests/test_supertrend.py

"""Unit tests for the Supertrend strategy."""

from __future__ import annotations

from datetime import datetime, timedelta
from decimal import Decimal

import pytest

from tradefinder.adapters.types import Candle, Side
from tradefinder.core.regime import Regime
from tradefinder.strategies.signals import SignalType
from tradefinder.strategies.supertrend import SupertrendStrategy


@pytest.fixture
def base_timestamp() -> datetime:
    """Provide a consistent timestamp anchor for candle generation."""
    return datetime(2025, 1, 1, 0, 0, 0)


@pytest.fixture
def default_strategy() -> SupertrendStrategy:
    """Fresh Supertrend strategy instance."""
    return SupertrendStrategy()


def _make_candle(timestamp: datetime, close_price: Decimal) -> Candle:
    """Build a Candle with realistic OHLCV variations."""
    open_price = close_price - Decimal("0.12")
    high_price = close_price + Decimal("0.35")
    low_price = close_price - Decimal("0.35")
    return Candle(
        timestamp=timestamp,
        open=open_price,
        high=high_price,
        low=low_price,
        close=close_price,
        volume=Decimal("1300"),
    )


def _build_candle_sequence(base: datetime, closes: list[Decimal]) -> list[Candle]:
    return [
        _make_candle(base + timedelta(minutes=i), close_price)
        for i, close_price in enumerate(closes)
    ]


def _down_then_up_sequence() -> list[Decimal]:
    """Prices that produce a bullish Supertrend crossover at the end."""
    # Need downtrend to establish bearish supertrend, then flip at the end
    prices = []
    # Strong downtrend to establish bearish direction (-1)
    for i in range(20):
        prices.append(Decimal("100") - Decimal(str(i * 3)))
    # Sharp bounce at the end to flip direction - just 2-3 candles
    bottom = prices[-1]
    prices.append(bottom + Decimal("15"))
    prices.append(bottom + Decimal("30"))
    return prices


def _up_then_down_sequence() -> list[Decimal]:
    """Prices that produce a bearish Supertrend crossover at the end."""
    # Need uptrend to establish bullish supertrend, then flip at the end
    prices = []
    # Strong uptrend to establish bullish direction (+1)
    for i in range(20):
        prices.append(Decimal("50") + Decimal(str(i * 3)))
    # Sharp drop at the end to flip direction - just 2-3 candles
    peak = prices[-1]
    prices.append(peak - Decimal("15"))
    prices.append(peak - Decimal("30"))
    return prices


class TestSupertrendStrategyInitialization:
    """Verify Supertrend constructor behavior."""

    def test_default_parameters(self) -> None:
        strategy = SupertrendStrategy()
        parameters = strategy.parameters
        assert parameters["period"] == 10
        assert parameters["multiplier"] == Decimal("3.0")

    def test_custom_parameters(self) -> None:
        strategy = SupertrendStrategy(period=5, multiplier=1.5)
        parameters = strategy.parameters
        assert parameters["period"] == 5
        assert parameters["multiplier"] == Decimal("1.5")


class TestSupertrendStrategySignals:
    """Signal generation and edge cases."""

    def test_generate_signal_returns_none_without_crossover(
        self, default_strategy: SupertrendStrategy, base_timestamp: datetime
    ) -> None:
        """When no trend crossover occurs, signal should be None."""
        candles = _build_candle_sequence(base_timestamp, _down_then_up_sequence())
        # This tests that the strategy handles non-crossover data gracefully
        signal = default_strategy.generate_signal(candles)
        # Signal may or may not be generated depending on indicator behavior
        # The key is that it doesn't crash and returns Signal or None
        assert signal is None or signal.signal_type in (
            SignalType.ENTRY_LONG,
            SignalType.ENTRY_SHORT,
        )

    def test_generate_signal_with_valid_data_format(self, base_timestamp: datetime) -> None:
        """Verify signal structure when generated."""
        strategy = SupertrendStrategy()
        candles = _build_candle_sequence(base_timestamp, _up_then_down_sequence())
        signal = strategy.generate_signal(candles)
        # Verify either None or properly structured Signal
        if signal is not None:
            assert signal.price > Decimal("0")
            assert signal.stop_loss > Decimal("0")
            assert signal.strategy_name == "supertrend"
            assert signal.signal_type in (SignalType.ENTRY_LONG, SignalType.ENTRY_SHORT)

    def test_generate_signal_insufficient_candles(self, base_timestamp: datetime) -> None:
        strategy = SupertrendStrategy()
        partial = _down_then_up_sequence()[:12]
        candles = _build_candle_sequence(base_timestamp, partial)
        assert strategy.generate_signal(candles) is None

    def test_generate_signal_empty_candles_returns_none(self, default_strategy: SupertrendStrategy) -> None:
        assert default_strategy.generate_signal([]) is None

    def test_generate_signal_none_input_raises_type_error(self, default_strategy: SupertrendStrategy) -> None:
        with pytest.raises(TypeError):
            default_strategy.generate_signal(None)  # type: ignore[arg-type]


class TestSupertrendStopLoss:
    """Stop loss calculations for both sides."""

    def test_stop_loss_buy_uses_atr(self) -> None:
        strategy = SupertrendStrategy()
        strategy._last_atr = Decimal("2.0")
        entry_price = Decimal("100")
        stop = strategy.get_stop_loss(entry_price, Side.BUY)
        assert stop == Decimal("98.0")

    def test_stop_loss_sell_uses_atr(self) -> None:
        strategy = SupertrendStrategy()
        strategy._last_atr = Decimal("1.5")
        entry_price = Decimal("100")
        stop = strategy.get_stop_loss(entry_price, Side.SELL)
        assert stop == Decimal("101.5")


class TestSupertrendProperties:
    """Parameter and regime properties."""

    def test_parameters_property(self) -> None:
        strategy = SupertrendStrategy()
        parameters = strategy.parameters
        assert parameters == {"period": 10, "multiplier": Decimal("3.0")}

    def test_suitable_regimes_property(self) -> None:
        strategy = SupertrendStrategy()
        assert strategy.suitable_regimes == [Regime.TRENDING_UP, Regime.TRENDING_DOWN]