from models import ActionEnum, ConfidenceEnum
from analysis_service import (
    compute_analysis,
    _score_pnl,
    _score_pe,
    _score_revenue_growth,
    _score_target_price,
)


class TestScorePnl:
    def test_large_loss_suggests_buy(self):
        score, reason = _score_pnl(-0.25)
        assert score == 1
        assert "averaging down" in reason

    def test_large_profit_suggests_sell(self):
        score, reason = _score_pnl(0.60)
        assert score == -1
        assert "taking profit" in reason

    def test_moderate_suggests_hold(self):
        score, reason = _score_pnl(0.10)
        assert score == 0


class TestScorePe:
    def test_low_pe(self):
        score, _ = _score_pe(10.0)
        assert score == 1

    def test_high_pe(self):
        score, _ = _score_pe(50.0)
        assert score == -1

    def test_normal_pe(self):
        score, _ = _score_pe(20.0)
        assert score == 0

    def test_negative_pe(self):
        score, _ = _score_pe(-5.0)
        assert score == -1

    def test_none_pe(self):
        score, reason = _score_pe(None)
        assert score == 0
        assert reason is None


class TestScoreRevenueGrowth:
    def test_strong_growth(self):
        score, _ = _score_revenue_growth(0.20)
        assert score == 1

    def test_negative_growth(self):
        score, _ = _score_revenue_growth(-0.05)
        assert score == -1

    def test_moderate_growth(self):
        score, _ = _score_revenue_growth(0.05)
        assert score == 0

    def test_none(self):
        score, reason = _score_revenue_growth(None)
        assert score == 0


class TestScoreTargetPrice:
    def test_big_upside(self):
        score, _ = _score_target_price(100.0, 120.0)
        assert score == 1

    def test_big_downside(self):
        score, _ = _score_target_price(100.0, 85.0)
        assert score == -1

    def test_near_target(self):
        score, _ = _score_target_price(100.0, 105.0)
        assert score == 0

    def test_none_price(self):
        score, _ = _score_target_price(None, 120.0)
        assert score == 0


class TestComputeAnalysis:
    def test_strong_buy_signals(self):
        result = compute_analysis(
            current_price=100.0,
            buy_in_price=130.0,  # loss > 20%
            target_price=120.0,  # upside > 15%
            metrics={"pe_ratio": 10.0, "revenue_growth": 0.20},
        )
        assert result.action == ActionEnum.BUY_MORE
        assert result.confidence == ConfidenceEnum.HIGH

    def test_strong_sell_signals(self):
        result = compute_analysis(
            current_price=200.0,
            buy_in_price=100.0,  # profit > 50%
            target_price=170.0,  # downside
            metrics={"pe_ratio": 50.0, "revenue_growth": -0.10},
        )
        assert result.action == ActionEnum.SELL

    def test_mixed_signals_hold(self):
        result = compute_analysis(
            current_price=100.0,
            buy_in_price=95.0,
            target_price=105.0,
            metrics={"pe_ratio": 20.0, "revenue_growth": 0.05},
        )
        assert result.action == ActionEnum.HOLD

    def test_no_data(self):
        result = compute_analysis(
            current_price=None,
            buy_in_price=100.0,
            target_price=None,
            metrics={},
        )
        assert result.action == ActionEnum.HOLD
        assert result.confidence == ConfidenceEnum.LOW

    def test_reasons_populated(self):
        result = compute_analysis(
            current_price=100.0,
            buy_in_price=90.0,
            target_price=110.0,
            metrics={"pe_ratio": 25.0},
        )
        assert len(result.reasons) > 0