"""Unit tests для nspd_client (#94). Без сетевых запросов — только parsing.

Network calls (search_by_cad / get_feature_info / list_layers) проверяются
вручную через `python -c "from app.services.scrapers.nspd_client import
NSPDClient; print(NSPDClient().search_by_cad('66:41:0204016:10'))"` —
проверяется в production smoke test после deploy.
"""

from __future__ import annotations

from typing import Any

import pytest

from app.services.scrapers.nspd_client import (
    LAYERS,
    NSPDClient,
    NSPDFeature,
    NSPDLayer,
    NSPDSearchResult,
    QuarterDump,
    _geojson_bbox_3857,
    _walk_layer_tree,
    bbox_around_point_m,
    lonlat_to_3857,
)


def test_layers_catalog_has_critical_ids() -> None:
    """Sanity check: TIER 1 critical layers зарегистрированы."""
    # Из #94: TIER 1 включает 875838 (территориальные зоны / ПЗЗ G1)
    assert LAYERS["territorial_zones"] == 875838
    assert LAYERS["parcels"] == 36048
    assert LAYERS["buildings"] == 36049
    assert LAYERS["quarters"] == 36071
    # TIER 2 ЗОУИТ (G3)
    assert LAYERS["zouit_okn"] == 37577
    assert LAYERS["zouit_engineering"] == 37578
    assert LAYERS["zouit_natural"] == 37580


def test_lonlat_to_3857_zero() -> None:
    """0,0 → ~0,0 (with tiny floating error)."""
    x, y = lonlat_to_3857(0.0, 0.0)
    assert abs(x) < 1.0
    assert abs(y) < 1.0


def test_lonlat_to_3857_ekb_center() -> None:
    """ЕКБ центр (60.605, 56.838) — known approximate projection."""
    x, y = lonlat_to_3857(60.605, 56.838)
    # Sanity: положительный x (восточная долгота), положительный y (северная)
    assert x > 6_700_000
    assert x < 6_800_000
    assert y > 7_700_000
    assert y < 7_800_000


def test_bbox_around_point_m_basic() -> None:
    """100m buffer вокруг точки → bbox с side ≈ 200m."""
    xmin, ymin, xmax, ymax = bbox_around_point_m(60.605, 56.838, 100)
    assert abs((xmax - xmin) - 200) < 1.0
    assert abs((ymax - ymin) - 200) < 1.0


def test_nspd_feature_from_raw_minimal() -> None:
    """Парсинг минимального GeoJSON Feature."""
    raw = {
        "id": "feat-1",
        "geometry": {"type": "Point", "coordinates": [1, 2]},
        "properties": {"cad_num": "66:41:0204016:10"},
    }
    feat = NSPDFeature.from_raw(raw)
    assert feat.feature_id == "feat-1"
    assert feat.geometry is not None
    assert feat.geometry["type"] == "Point"
    assert feat.properties["cad_num"] == "66:41:0204016:10"
    assert feat.crs == "EPSG:3857"


def test_nspd_feature_from_raw_missing_id() -> None:
    """Feature без id → feature_id is None."""
    feat = NSPDFeature.from_raw({"geometry": None, "properties": {}})
    assert feat.feature_id is None
    assert feat.geometry is None
    assert feat.properties == {}


def test_nspd_search_result_empty() -> None:
    """Empty result → first is None, is_empty True."""
    result = NSPDSearchResult(cad_num="x", features=[], raw={})
    assert result.first is None
    assert result.is_empty is True


def test_nspd_search_result_nonempty() -> None:
    """First feature accessible через .first."""
    feat = NSPDFeature.from_raw({"id": "x", "geometry": None, "properties": {}})
    result = NSPDSearchResult(cad_num="x", features=[feat], raw={})
    assert result.first is feat
    assert result.is_empty is False


def test_walk_layer_tree_flat() -> None:
    """Flat list of layers — все попадают в output."""
    tree: list[dict[str, Any]] = [
        {"id": 1, "title": "A", "children": []},
        {"id": 2, "title": "B", "children": []},
    ]
    out = _walk_layer_tree(tree)
    ids = sorted(x["id"] for x in out)
    assert ids == [1, 2]


def test_walk_layer_tree_nested() -> None:
    """Nested tree — все leaves вытаскиваются."""
    tree = {
        "id": 1,
        "title": "root",
        "children": [
            {"id": 2, "title": "child", "children": []},
            {
                "id": 3,
                "title": "branch",
                "children": [
                    {"id": 4, "title": "grandchild", "children": []},
                ],
            },
        ],
    }
    out = _walk_layer_tree(tree)
    ids = sorted(x["id"] for x in out)
    # Все уровни включены — root, child, branch, grandchild
    assert ids == [1, 2, 3, 4]


def test_walk_layer_tree_empty() -> None:
    """Empty input → empty output, no crash."""
    assert _walk_layer_tree({}) == []
    assert _walk_layer_tree([]) == []
    assert _walk_layer_tree(None) == []  # type: ignore[arg-type]


def test_nspd_client_search_by_cad_parses_response(monkeypatch: pytest.MonkeyPatch) -> None:
    """search_by_cad оборачивает fetch_geoportal в NSPDSearchResult."""
    fake_raw = {
        "data": {
            "type": "FeatureCollection",
            "features": [
                {
                    "id": "f1",
                    "geometry": {"type": "Polygon", "coordinates": []},
                    "properties": {
                        "cad_num": "66:41:0204016:10",
                        "land_record_area": 1500,
                        "permitted_use_established_by_document": "Многоэтажная жилая",
                    },
                }
            ],
        }
    }

    def fake_fetch(query: str, **kwargs: Any) -> dict[str, Any]:
        assert query == "66:41:0204016:10"
        return fake_raw

    # Patch the imported reference in nspd_client (it was imported by name)
    monkeypatch.setattr(
        "app.services.scrapers.nspd_client.fetch_geoportal",
        fake_fetch,
    )

    client = NSPDClient()
    result = client.search_by_cad("66:41:0204016:10")
    assert result.cad_num == "66:41:0204016:10"
    assert len(result.features) == 1
    assert result.first is not None
    assert result.first.properties["permitted_use_established_by_document"] == "Многоэтажная жилая"
    assert result.raw is fake_raw  # preserved для debugging


def test_nspd_client_search_by_cad_empty(monkeypatch: pytest.MonkeyPatch) -> None:
    """Empty response → is_empty True, no crash."""
    monkeypatch.setattr(
        "app.services.scrapers.nspd_client.fetch_geoportal",
        lambda *a, **kw: {"data": {"type": "FeatureCollection", "features": []}},
    )
    result = NSPDClient().search_by_cad("99:99:9999999")
    assert result.is_empty is True
    assert result.first is None


def test_nspd_layer_dataclass() -> None:
    """NSPDLayer immutable, hashable (frozen + slots)."""
    layer = NSPDLayer(layer_id=875838, title="Терр.зоны", layer_type="wms", metadata={})
    assert layer.layer_id == 875838
    # Frozen
    with pytest.raises(AttributeError):
        layer.title = "x"  # type: ignore[misc]


# ── Mock tests for WMS/layers methods (no network) ──────────────────────────


def test_get_feature_info_parses_response(monkeypatch: pytest.MonkeyPatch) -> None:
    """get_feature_info вызывает _http_get_json с правильным URL + парсит features."""
    captured_urls: list[str] = []

    def fake_http(url: str, **kwargs: Any) -> dict[str, Any]:
        captured_urls.append(url)
        return {
            "type": "FeatureCollection",
            "features": [
                {
                    "id": "tz-1",
                    "geometry": {"type": "Polygon", "coordinates": []},
                    "properties": {"zone_code": "Ж-1"},
                }
            ],
        }

    monkeypatch.setattr("app.services.scrapers.nspd_client._http_get_json", fake_http)
    client = NSPDClient()
    feats = client.get_feature_info(875838, lon=60.605, lat=56.838, buffer_m=100)
    assert len(feats) == 1
    assert feats[0].properties["zone_code"] == "Ж-1"
    # Verify URL structure
    assert len(captured_urls) == 1
    url = captured_urls[0]
    assert "/api/aeggis/v4/875838/wms?" in url
    assert "REQUEST=GetFeatureInfo" in url
    assert "INFO_FORMAT=application%2Fjson" in url
    assert "STYLES=" in url  # required per NSPD WAF
    assert "CRS=EPSG%3A3857" in url
    # bbox should reflect 100m buffer (200m side)
    assert "BBOX=" in url


def test_get_features_in_bbox_url_builds_correctly(monkeypatch: pytest.MonkeyPatch) -> None:
    """get_features_in_bbox использует переданный bbox без преобразования."""
    captured_urls: list[str] = []

    def fake_http(url: str, **kwargs: Any) -> dict[str, Any]:
        captured_urls.append(url)
        return {"features": []}

    monkeypatch.setattr("app.services.scrapers.nspd_client._http_get_json", fake_http)
    client = NSPDClient()
    bbox = (6700000.0, 7700000.0, 6800000.0, 7800000.0)  # ЕКБ region in 3857
    feats = client.get_features_in_bbox(875838, bbox)
    assert feats == []
    assert len(captured_urls) == 1
    url = captured_urls[0]
    # bbox passed directly into BBOX param (URL-encoded comma = %2C)
    assert "BBOX=6700000.0%2C7700000.0%2C6800000.0%2C7800000.0" in url
    # Large width/height для bulk fetch
    assert "WIDTH=4096" in url
    assert "HEIGHT=4096" in url
    # I/J pointer в центр виртуального тайла
    assert "I=2048" in url
    assert "J=2048" in url


def test_list_layers_walks_tree_response(monkeypatch: pytest.MonkeyPatch) -> None:
    """list_layers вызывает /layers-theme-tree и распаковывает в NSPDLayer."""
    fake_tree = [
        {
            "id": 1,
            "title": "PKK тема",
            "children": [
                {
                    "id": 875838,
                    "title": "Территориальные зоны",
                    "layerType": "wms",
                    "children": [],
                },
                {
                    "id": 37577,
                    "title": "ЗОУИТ ОКН",
                    "layerType": "wms",
                    "children": [],
                },
            ],
        }
    ]
    monkeypatch.setattr(
        "app.services.scrapers.nspd_client._http_get_json",
        lambda url, **kw: fake_tree,
    )
    client = NSPDClient()
    layers = client.list_layers(theme_id=1)
    layer_ids = [layer.layer_id for layer in layers]
    # Root + 2 children = 3 leaves
    assert 875838 in layer_ids
    assert 37577 in layer_ids
    # Sample layer metadata preserved
    tz_layer = next(layer for layer in layers if layer.layer_id == 875838)
    assert tz_layer.title == "Территориальные зоны"
    assert tz_layer.layer_type == "wms"


def test_list_layers_handles_data_wrapper(monkeypatch: pytest.MonkeyPatch) -> None:
    """Shape defense — NSPD иногда оборачивает в {"data": [...]}."""
    fake_wrapped = {
        "data": [{"id": 36048, "title": "ЗУ", "children": []}],
        "meta": {"count": 1},
    }
    monkeypatch.setattr(
        "app.services.scrapers.nspd_client._http_get_json",
        lambda url, **kw: fake_wrapped,
    )
    layers = NSPDClient().list_layers(theme_id=1)
    assert len(layers) >= 1
    assert any(layer.layer_id == 36048 for layer in layers)


def test_list_layers_handles_garbage_response(monkeypatch: pytest.MonkeyPatch) -> None:
    """Не dict/list response → empty list + warning log (no crash)."""
    monkeypatch.setattr(
        "app.services.scrapers.nspd_client._http_get_json",
        lambda url, **kw: "garbage string",
    )
    assert NSPDClient().list_layers(theme_id=1) == []


# ── _geojson_bbox_3857 tests ──────────────────────────────────────────────────


def test_geojson_bbox_3857_polygon() -> None:
    """Простой Polygon → bbox охватывает все vertices."""
    geom = {
        "type": "Polygon",
        "coordinates": [[[0, 0], [100, 0], [100, 100], [0, 100], [0, 0]]],
    }
    result = _geojson_bbox_3857(geom)
    assert result == (0.0, 0.0, 100.0, 100.0)


def test_geojson_bbox_3857_multipolygon() -> None:
    """MultiPolygon с двумя кусками → bbox охватывает оба."""
    geom = {
        "type": "MultiPolygon",
        "coordinates": [
            [[[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]]],
            [[[20, 30], [50, 30], [50, 60], [20, 60], [20, 30]]],
        ],
    }
    result = _geojson_bbox_3857(geom)
    assert result is not None
    xmin, ymin, xmax, ymax = result
    assert xmin == 0.0
    assert ymin == 0.0
    assert xmax == 50.0
    assert ymax == 60.0


def test_geojson_bbox_3857_linestring() -> None:
    """LineString из 2 точек → bbox прямоугольник вокруг них."""
    geom = {
        "type": "LineString",
        "coordinates": [[10, 20], [30, 40]],
    }
    result = _geojson_bbox_3857(geom)
    assert result == (10.0, 20.0, 30.0, 40.0)


def test_geojson_bbox_3857_point() -> None:
    """Point → bbox с шириной и высотой 0 (один пиксель)."""
    geom = {
        "type": "Point",
        "coordinates": [60.0, 56.0],
    }
    result = _geojson_bbox_3857(geom)
    assert result == (60.0, 56.0, 60.0, 56.0)


def test_geojson_bbox_3857_empty() -> None:
    """Polygon с пустым coordinates → None."""
    geom = {"type": "Polygon", "coordinates": []}
    assert _geojson_bbox_3857(geom) is None


def test_geojson_bbox_3857_no_type() -> None:
    """Нет поля type → None (не можем определить геометрию)."""
    geom: dict[str, Any] = {"coordinates": [[0, 0]]}
    assert _geojson_bbox_3857(geom) is None


# ── QuarterDump tests ─────────────────────────────────────────────────────────


def _make_feat(fid: str = "x") -> NSPDFeature:
    """Вспомогательная фабрика NSPDFeature для тестов."""
    return NSPDFeature.from_raw({"id": fid, "geometry": None, "properties": {}})


def test_quarter_dump_total_features() -> None:
    """total_features корректно суммирует features по всем layers."""
    dump = QuarterDump(
        quarter_cad="66:41:0204016",
        quarter=_make_feat("q"),
        parcels=[_make_feat("p1"), _make_feat("p2"), _make_feat("p3")],  # 3
        buildings=[_make_feat("b1")],  # 1
        territorial_zones=[_make_feat("tz1"), _make_feat("tz2")],  # 2
        red_lines=[],  # 0
        engineering_structures=[_make_feat("e1")],  # 1
        zouit={
            "okn": [_make_feat("ok1"), _make_feat("ok2")],  # 2
            "natural": [_make_feat("nat1")],  # 1
        },
        risks={
            "flooding": [_make_feat("fl1"), _make_feat("fl2"), _make_feat("fl3")],  # 3
            "landslide": [_make_feat("ls1")],  # 1
        },
        layers_fetched=("search", "parcels", "buildings"),
        bbox_3857=(6700000.0, 7700000.0, 6800000.0, 7800000.0),
        fetched_at_utc="2026-05-12T00:00:00+00:00",
    )
    # 3+1+2+0+1 (core) + 2+1 (zouit) + 3+1 (risks) = 14
    assert dump.total_features == 14


def test_quarter_dump_frozen() -> None:
    """QuarterDump frozen=True: попытка assign → AttributeError."""
    dump = QuarterDump(
        quarter_cad="66:41:0204016",
        quarter=None,
        parcels=[],
        buildings=[],
        territorial_zones=[],
        red_lines=[],
        engineering_structures=[],
        zouit={},
        risks={},
        layers_fetched=("search",),
        bbox_3857=None,
        fetched_at_utc="2026-05-12T00:00:00+00:00",
    )
    with pytest.raises(AttributeError):
        dump.parcels = []  # type: ignore[misc]


# ── search_by_quarter mock tests ──────────────────────────────────────────────

# Квартал в районе ЕКБ (EPSG:3857 метры)
_QUARTER_COORDS = [
    [6700000.0, 7700000.0],
    [6800000.0, 7700000.0],
    [6800000.0, 7800000.0],
    [6700000.0, 7800000.0],
    [6700000.0, 7700000.0],
]
_QUARTER_BBOX = (6700000.0, 7700000.0, 6800000.0, 7800000.0)

_FAKE_QUARTER_SEARCH = {
    "data": {
        "type": "FeatureCollection",
        "features": [
            {
                "id": "q-1",
                "geometry": {"type": "Polygon", "coordinates": [_QUARTER_COORDS]},
                "properties": {"cad_num": "66:41:0204016"},
            }
        ],
    }
}

_LAYER_FEATURE_COUNTS: dict[str, int] = {
    "parcels": 4,
    "buildings": 2,
    "territorial_zones": 1,
    "red_lines": 0,
    "engineering_structures": 3,
}


def _make_fake_http(
    layer_feature_counts: dict[str, int] | None = None,
) -> Any:
    """Возвращает fake _http_get_json который генерирует N features по layer ID.

    layer_feature_counts: {layer_name: count} — если None, возвращает 1 feature.
    """
    counts = layer_feature_counts or {}
    # Строим reverse-map layer_id → count для подстановки в URL
    from app.services.scrapers.nspd_client import LAYERS as _LAYERS

    id_to_name: dict[int, str] = {v: k for k, v in _LAYERS.items()}

    def fake_http(url: str, **kwargs: Any) -> dict[str, Any]:
        # Извлекаем layer_id из URL вида /api/aeggis/v4/{id}/wms?...
        parts = url.split("/")
        layer_id_str = parts[6] if len(parts) > 6 else "0"
        try:
            layer_id = int(layer_id_str.split("?")[0])
        except ValueError:
            layer_id = 0
        layer_name = id_to_name.get(layer_id, "unknown")
        n = counts.get(layer_name, 1)
        return {
            "type": "FeatureCollection",
            "features": [
                {"id": f"{layer_name}-{i}", "geometry": None, "properties": {}} for i in range(n)
            ],
        }

    return fake_http


def _make_fake_grid_walk(
    layer_feature_counts: dict[str, int] | None = None,
) -> Any:
    """Возвращает fake `NSPDClient.get_features_in_bbox_grid`.

    После Sub-PR B (#260) area/linear layers (territorial_zones, red_lines,
    engineering_structures, zouit_*, risk_*) идут через grid-walk вместо
    legacy `_http_get_json` → тесты обязаны мокать оба пути, иначе грид-walk
    бьёт по живому NSPD API.
    """
    counts = layer_feature_counts or {}
    from app.services.scrapers.nspd_client import LAYERS as _LAYERS
    from app.services.scrapers.nspd_client import NSPDFeature

    id_to_name: dict[int, str] = {v: k for k, v in _LAYERS.items()}

    def fake_grid(
        self: Any,
        layer_id: int,
        bbox: tuple[float, float, float, float],
        *,
        grid_n: int = 7,
        step_m: float = 50.0,
    ) -> list[NSPDFeature]:
        layer_name = id_to_name.get(layer_id, "unknown")
        n = counts.get(layer_name, 1)
        return [
            NSPDFeature.from_raw({"id": f"{layer_name}-{i}", "geometry": None, "properties": {}})
            for i in range(n)
        ]

    return fake_grid


def test_search_by_quarter_core_only(monkeypatch: pytest.MonkeyPatch) -> None:
    """core_only (include_zouit=False, include_risks=False): 1 search + 5 bulk."""
    search_calls: list[str] = []

    def fake_fetch(query: str, **kwargs: Any) -> dict[str, Any]:
        search_calls.append(query)
        return _FAKE_QUARTER_SEARCH

    monkeypatch.setattr("app.services.scrapers.nspd_client.fetch_geoportal", fake_fetch)
    monkeypatch.setattr(
        "app.services.scrapers.nspd_client._http_get_json",
        _make_fake_http(_LAYER_FEATURE_COUNTS),
    )
    # Sub-PR B (#260): area layers идут через grid-walk — мокаем оба пути.
    monkeypatch.setattr(
        "app.services.scrapers.nspd_client.NSPDClient.get_features_in_bbox_grid",
        _make_fake_grid_walk(_LAYER_FEATURE_COUNTS),
    )

    result = NSPDClient().search_by_quarter(
        "66:41:0204016", include_zouit=False, include_risks=False
    )

    # Quarter populated
    assert result.quarter is not None
    assert result.quarter.feature_id == "q-1"

    # Core layer lengths match mock counts
    assert len(result.parcels) == 4
    assert len(result.buildings) == 2
    assert len(result.territorial_zones) == 1
    assert len(result.red_lines) == 0
    assert len(result.engineering_structures) == 3

    # ЗОУИТ / risks пусты
    assert result.zouit == {}
    assert result.risks == {}

    # layers_fetched: search + 5 core (red_lines тоже: _fetch_layer вызывается,
    # но возвращает пустой список — имя всё равно добавляется). tuple, not list
    # — frozen-dataclass immutability invariant.
    assert result.layers_fetched == (
        "search",
        "parcels",
        "buildings",
        "territorial_zones",
        "red_lines",
        "engineering_structures",
    )

    # bbox вычислен из четырёхугольного polygon
    assert result.bbox_3857 == _QUARTER_BBOX


def test_search_by_quarter_with_zouit(monkeypatch: pytest.MonkeyPatch) -> None:
    """include_zouit=True → zouit dict содержит 5 ключей."""
    monkeypatch.setattr(
        "app.services.scrapers.nspd_client.fetch_geoportal",
        lambda *a, **kw: _FAKE_QUARTER_SEARCH,
    )
    monkeypatch.setattr(
        "app.services.scrapers.nspd_client._http_get_json",
        _make_fake_http(),
    )
    # Sub-PR B (#260): zouit_* и area layers идут через grid-walk.
    monkeypatch.setattr(
        "app.services.scrapers.nspd_client.NSPDClient.get_features_in_bbox_grid",
        _make_fake_grid_walk(),
    )

    result = NSPDClient().search_by_quarter(
        "66:41:0204016", include_zouit=True, include_risks=False
    )

    assert set(result.zouit.keys()) == {"okn", "engineering", "natural", "protected", "other"}
    assert result.risks == {}

    # layers_fetched содержит search + 5 core + 5 zouit = 11 записей
    assert len(result.layers_fetched) == 11


def test_search_by_quarter_empty_quarter(monkeypatch: pytest.MonkeyPatch) -> None:
    """Пустой FeatureCollection → quarter=None, все layer feature lists пустые.

    При bbox=None `_fetch_layer` возвращает [] без HTTP вызовов. ЗОУИТ-словарь
    всё равно создаётся (с пустыми списками) — ключи присутствуют, features нет.
    """
    http_calls: list[str] = []

    def fake_http(url: str, **kwargs: Any) -> dict[str, Any]:
        http_calls.append(url)
        return {"type": "FeatureCollection", "features": []}

    monkeypatch.setattr(
        "app.services.scrapers.nspd_client.fetch_geoportal",
        lambda *a, **kw: {"data": {"type": "FeatureCollection", "features": []}},
    )
    monkeypatch.setattr("app.services.scrapers.nspd_client._http_get_json", fake_http)

    result = NSPDClient().search_by_quarter("66:41:9999999", include_zouit=True)

    assert result.quarter is None
    assert result.parcels == []
    assert result.buildings == []
    assert result.territorial_zones == []
    assert result.red_lines == []
    assert result.engineering_structures == []

    # include_zouit=True: ключи созданы, но все списки пустые (bbox=None → _fetch_layer → [])
    assert set(result.zouit.keys()) == {"okn", "engineering", "natural", "protected", "other"}
    assert all(v == [] for v in result.zouit.values())

    assert result.risks == {}
    assert result.bbox_3857 is None

    # Никаких bulk HTTP запросов — bbox=None ⇒ ранний выход из _fetch_layer
    assert http_calls == []
    # layers_fetched содержит только "search" (tuple, no bulk fetches happened)
    assert result.layers_fetched == ("search",)


def test_search_by_quarter_layers_fetched_with_risks(monkeypatch: pytest.MonkeyPatch) -> None:
    """include_risks=True (без zouit) → layers_fetched включает 11 risk layer имён."""
    monkeypatch.setattr(
        "app.services.scrapers.nspd_client.fetch_geoportal",
        lambda *a, **kw: _FAKE_QUARTER_SEARCH,
    )
    monkeypatch.setattr(
        "app.services.scrapers.nspd_client._http_get_json",
        _make_fake_http(),
    )
    # Sub-PR B (#260): risk_* и area layers идут через grid-walk.
    monkeypatch.setattr(
        "app.services.scrapers.nspd_client.NSPDClient.get_features_in_bbox_grid",
        _make_fake_grid_walk(),
    )

    result = NSPDClient().search_by_quarter(
        "66:41:0204016", include_zouit=False, include_risks=True
    )

    assert result.zouit == {}
    assert set(result.risks.keys()) == {
        "flooding_underground",
        "flooding",
        "swampification",
        "landslide",
        "abrasion",
        "erosion_water",
        "erosion_linear",
        "erosion_wind",
        "desertification",
        "clutter",
        "burns",
    }

    # layers_fetched: search + 5 core + 11 risks = 17
    assert len(result.layers_fetched) == 17
    # Убедимся что risk имена действительно присутствуют в layers_fetched
    assert "risk_flooding" in result.layers_fetched
    assert "risk_landslide" in result.layers_fetched
    assert "risk_burns" in result.layers_fetched