from scripts.reference_transparency_contract import (
    build_reference_transparency_contract,
    select_similar_public_cases,
)
from pathlib import Path


ROOT = Path(__file__).resolve().parents[1]


def _chart(ascendant: str, moon: str, domain_lord_sign: str) -> dict:
    return {
        "ascendant": {"sign": ascendant},
        "planets": {
            "Moon": {"sign": moon},
            "Saturn": {"sign": domain_lord_sign},
        },
        "houses": {"house_7": {"lord": "Venus"}, "house_10": {"lord": "Saturn"}},
    }


def _varga_chart() -> dict:
    return {
        "ascendant": {"sign": "Leo", "lon": 149.0634},
        "planets": {
            "Moon": {"sign": "Pisces", "lon": 344.5165},
            "Saturn": {"sign": "Libra", "lon": 207.9320},
            "Sun": {"sign": "Aquarius", "lon": 312.5175},
            "Venus": {"sign": "Sagittarius", "lon": 267.9412},
            "Rahu": {"sign": "Sagittarius", "lon": 249.2743},
            "Ketu": {"sign": "Gemini", "lon": 69.2743},
        },
        "houses": {"house_10": {"lord": "Saturn"}},
    }


def test_select_similar_cases_shares_only_high_similarity_same_domain() -> None:
    user_chart = _chart("Leo", "Pisces", "Libra")
    cases = [
        {
            "case_id": "matching_career_case",
            "subject": {"name": "Public Example"},
            "chart": _chart("Leo", "Pisces", "Libra"),
            "source": {"url": "https://example.com/birth", "source_grade": "primary"},
            "event_outcomes": [{
                "domain": "career", "event_type": "career_breakthrough", "event_date": "2007-01-09",
                "outcome": "Public career event", "source": {"url": "https://example.com/event", "source_grade": "primary"},
            }],
            "replay": {"outcome_replay_status": "replayed", "do_not_use_for_prediction": False},
        },
        {
            "case_id": "wrong_domain_case",
            "subject": {"name": "Different Example"},
            "chart": _chart("Aries", "Aries", "Aries"),
            "source": {"url": "https://example.com/birth-2", "source_grade": "primary"},
            "event_outcomes": [{
                "domain": "marriage", "event_type": "legal_marriage", "event_date": "2011-04-29",
                "outcome": "Public marriage event", "source": {"url": "https://example.com/event-2", "source_grade": "primary"},
            }],
            "replay": {"outcome_replay_status": "replayed", "do_not_use_for_prediction": False},
        },
    ]

    selected = select_similar_public_cases(user_chart, ["career"], cases=cases)

    assert selected["status"] == "high_similarity_public_references_available"
    assert [case["case_id"] for case in selected["cases"]] == ["matching_career_case"]
    assert selected["cases"][0]["similarity"]["score"] == 1.0
    assert "node_axis" not in selected["cases"][0]["similarity"]["matching_factors"]
    assert selected["cases"][0]["event_source"]["url"] == "https://example.com/event"
    assert selected["does_not_predict_user_outcome"] is True
    assert selected["coverage"] == {
        "available_event_domains": ["career", "marriage"],
        "requested_uncovered_domains": [],
    }


def test_reference_contract_preserves_dates_and_discloses_parallel_methods() -> None:
    contract = build_reference_transparency_contract(
        _chart("Leo", "Pisces", "Libra"),
        ["career"],
        timing={"candidate_windows": [{"start": "2026-08-12", "end": "2026-08-16"}]},
        cases=[],
    )

    assert contract["timing_display"]["exact_triggers"] == "display_as_technical_trigger_not_guarantee"
    assert contract["external_engine_observations"]["VedAstro hosted"]["deployment_identity"] == "not_publicly_proven"
    assert contract["method_variants"]["display"] == "show_parallel_methods_with_sources"
    assert contract["similar_public_cases"]["status"] == "no_high_similarity_public_reference"
    assert contract["similar_public_cases"]["coverage"]["requested_uncovered_domains"] == ["career"]


def test_default_public_manifest_can_surface_a_matching_replayed_case() -> None:
    from scripts.domain_calculation_service import compute_chart

    jobs_chart = compute_chart({
        "year": 1955, "month": 2, "day": 24, "hour": 19, "minute": 15,
        "lat": 37.7833, "lon": -122.4167, "tz": -8.0,
        "ayanamsa": "lahiri", "node_mode": "mean",
    })

    selected = select_similar_public_cases(jobs_chart, ["career"])

    assert selected["status"] == "high_similarity_public_references_available"
    assert selected["cases"][0]["case_id"] == "jobs_iphone_2007"
    assert selected["cases"][0]["reference_only"] is True


def test_same_event_date_compares_vimshottari_mahadasha() -> None:
    from scripts.domain_calculation_service import compute_chart

    jobs_chart = compute_chart({
        "year": 1955, "month": 2, "day": 24, "hour": 19, "minute": 15,
        "lat": 37.7833, "lon": -122.4167, "tz": -8.0,
        "ayanamsa": "lahiri", "node_mode": "mean",
    })

    selected = select_similar_public_cases(
        jobs_chart,
        ["career"],
        reference_date="2007-01-09",
    )

    similarity = selected["cases"][0]["similarity"]
    assert {
        "vimshottari_mahadasha",
        "vimshottari_antardasha",
        "narayana_mahadasha_sign",
        "narayana_antardasha_sign",
        "jupiter_transit_house",
        "saturn_transit_house",
    }.issubset(similarity["matching_factors"])
    assert similarity["timing_state"]["status"] == "matched"
    assert similarity["timing_state"]["narayana_status"] == "matched"
    assert similarity["timing_state"]["transit_status"] == "matched"
    assert "vimshottari_antardasha" not in similarity["uncompared_layers"]
    assert "narayana_dasha" not in similarity["uncompared_layers"]
    assert "transit_event_state" not in similarity["uncompared_layers"]


def test_pending_health_case_is_context_only_not_calibration() -> None:
    user_chart = _chart("Leo", "Pisces", "Libra")
    cases = [{
        "case_id": "public_health_context",
        "subject": {"name": "Public Example"},
        "chart": _chart("Leo", "Pisces", "Libra"),
        "source": {"url": "https://example.com/birth", "source_grade": "primary"},
        "event_outcomes": [{
            "domain": "health", "event_type": "serious_injury", "event_date": "1925-09",
            "outcome": "Public health event", "source": {"url": "https://example.com/event", "source_grade": "verified_secondary"},
        }],
        "replay": {"outcome_replay_status": "pending", "do_not_use_for_prediction": True},
    }]

    selected = select_similar_public_cases(user_chart, ["health"], cases=cases)

    assert selected["status"] == "high_similarity_public_references_available"
    assert selected["cases"][0]["reference_status"] == "public_context_only"
    assert selected["cases"][0]["reference_only"] is True
    assert selected["coverage"]["available_event_domains"] == ["health"]


def test_default_public_context_catalog_covers_wealth_as_reference_only() -> None:
    selected = select_similar_public_cases(_chart("Leo", "Pisces", "Libra"), ["wealth"])

    assert "wealth" in selected["coverage"]["available_event_domains"]
    assert "wealth" not in selected["coverage"]["requested_uncovered_domains"]


def test_career_similarity_adds_d10_only_when_both_charts_have_longitudes() -> None:
    chart = _varga_chart()
    cases = [{
        "case_id": "d10_match", "subject": {"name": "Public Example"}, "chart": chart,
        "source": {"url": "https://example.com/birth", "source_grade": "primary"},
        "event_outcomes": [{
            "domain": "career", "event_type": "career_breakthrough", "event_date": "2007-01-09",
            "outcome": "Public career event", "source": {"url": "https://example.com/event", "source_grade": "primary"},
        }],
        "replay": {"outcome_replay_status": "replayed", "do_not_use_for_prediction": False},
    }]

    selected = select_similar_public_cases(chart, ["career"], cases=cases)

    similarity = selected["cases"][0]["similarity"]
    assert {"d10_ascendant", "d10_sun"}.issubset(similarity["matching_factors"])
    assert "D10" not in similarity["uncompared_layers"]


def test_marriage_similarity_adds_d9_only_when_both_charts_have_longitudes() -> None:
    chart = _varga_chart()
    cases = [{
        "case_id": "d9_match", "subject": {"name": "Public Example"}, "chart": chart,
        "source": {"url": "https://example.com/birth", "source_grade": "primary"},
        "event_outcomes": [{
            "domain": "marriage", "event_type": "legal_marriage", "event_date": "2011-04-29",
            "outcome": "Public marriage event", "source": {"url": "https://example.com/event", "source_grade": "primary"},
        }],
        "replay": {"outcome_replay_status": "replayed", "do_not_use_for_prediction": False},
    }]

    selected = select_similar_public_cases(chart, ["marriage"], cases=cases)

    similarity = selected["cases"][0]["similarity"]
    assert {"d9_ascendant", "d9_venus"}.issubset(similarity["matching_factors"])
    assert "D9" not in similarity["uncompared_layers"]


def test_api_house_shape_keeps_theme_lord_in_similarity() -> None:
    chart = _varga_chart()
    chart["houses"] = {10: {"sign": "Taurus", "sign_idx": 1}}
    cases = [{
        "case_id": "api_house_shape", "subject": {"name": "Public Example"}, "chart": chart,
        "source": {"url": "https://example.com/birth", "source_grade": "primary"},
        "event_outcomes": [{
            "domain": "career", "event_type": "career_breakthrough", "event_date": "2007-01-09",
            "outcome": "Public career event", "source": {"url": "https://example.com/event", "source_grade": "primary"},
        }],
        "replay": {"outcome_replay_status": "replayed", "do_not_use_for_prediction": False},
    }]

    selected = select_similar_public_cases(chart, ["career"], cases=cases)

    assert "domain_lord_sign" in selected["cases"][0]["similarity"]["matching_factors"]


def test_default_manifest_exposes_kahlo_health_as_context_only() -> None:
    from scripts.domain_calculation_service import compute_chart

    kahlo_chart = compute_chart({
        "year": 1907, "month": 7, "day": 6, "hour": 8, "minute": 30,
        "lat": 19.3333, "lon": -99.1667, "tz": -6.6111,
        "ayanamsa": "lahiri", "node_mode": "mean",
    })

    selected = select_similar_public_cases(kahlo_chart, ["health"])

    assert [case["case_id"] for case in selected["cases"]] == ["kahlo_bus_injury_1925"]
    assert selected["cases"][0]["reference_status"] == "public_context_only"
    assert selected["coverage"]["available_event_domains"] == ["career", "health", "marriage", "wealth"]


def test_consultation_api_exposes_reference_transparency_contract() -> None:
    source = (ROOT / "scripts" / "jyotish_api_server.py").read_text(encoding="utf-8")
    assert "result['reference_transparency'] = build_reference_transparency_contract(" in source
    assert "reference_date=_consultation_reference_date(body).date().isoformat()" in source