from __future__ import annotations

import gzip
import importlib.util
import json
from pathlib import Path
import sys

from shapely.geometry import box, mapping, shape
from shapely.ops import transform as transform_geometry

from app.models import Dataset
from app.services.vector_feature_service import VectorFeatureService


ROOT = Path(__file__).resolve().parents[2]
SCRIPTS = ROOT / "scripts"
if str(SCRIPTS) not in sys.path:
    sys.path.insert(0, str(SCRIPTS))


def load_script():
    path = SCRIPTS / "provision_regional_soil_map.py"
    spec = importlib.util.spec_from_file_location("test_provision_regional_soil_map", path)
    assert spec is not None and spec.loader is not None
    module = importlib.util.module_from_spec(spec)
    sys.modules[spec.name] = module
    spec.loader.exec_module(module)
    return module


class FakeResponse:
    status_code = 200
    ok = True
    text = ""

    def __init__(self, payload):
        self.payload = payload

    def json(self):
        return self.payload


class FakeApiSession:
    def __init__(self, payload):
        self.payload = payload
        self.calls = []

    def post(self, url, **kwargs):
        self.calls.append((url, kwargs))
        return FakeResponse({"data": self.payload})


def source_feature(feature_id: str, geometry) -> dict:
    return {
        "type": "Feature",
        "id": feature_id,
        "geometry": mapping(geometry),
        "properties": {
            "gid": 1,
            "id_kaartvlak": 10,
            "Bodemtype": "Zeg",
            "Unibodemtype": "Zeg",
            "Bodemserie": "Zeg",
            "Beknopte_omschrijving_bodemserie": "Natte zandbodem",
            "Gegeneraliseerde_legende": "Nat zand",
            "Textuurklasse_code": "Z",
            "Textuurklasse": "zand",
            "Drainageklasse_code": "e",
            "Drainageklasse": "nat",
            "Profielontwikkelingsgroep_code": "g",
            "Profielontwikkelingsgroep": "humus B horizont",
            "Eenduidige_legende_titel": "bodemserie Zeg",
        },
    }


def test_normalized_regional_features_keep_member_identity_and_unique_ids() -> None:
    module = load_script()
    boundary = box(5.0, 51.0, 5.1, 51.1)
    boundary_lambert72 = transform_geometry(module.soil.TO_LAMBERT72.transform, boundary)
    feature = source_feature("bodemtypes.1", box(4.98, 51.02, 5.05, 51.08))

    left, _ = module.soil.normalize_feature(
        feature,
        boundary_lambert72,
        municipality="Mol",
        nis_code="13025",
        coverage_scope="test-region",
        feature_id_suffix="13025",
    )
    right, _ = module.soil.normalize_feature(
        feature,
        boundary_lambert72,
        municipality="Balen",
        nis_code="13003",
        coverage_scope="test-region",
        feature_id_suffix="13003",
    )

    assert left is not None and right is not None
    assert left["id"] == "bodemtypes.1:13025"
    assert right["id"] == "bodemtypes.1:13003"
    assert left["properties"]["municipality"] == "Mol"
    assert left["properties"]["coverage_scope"] == "test-region"
    assert shape(left["geometry"]).within(boundary.buffer(1e-7))


def test_partition_retains_gzipped_source_and_is_checksum_reusable(tmp_path: Path, monkeypatch) -> None:
    module = load_script()
    scope = module.GeographicScope(
        key="test-region",
        display_name="Test region",
        project_name="Test",
        project_region="Test",
        area_name="Test area",
        authority_name="Test",
        authority_url="https://example.test",
        scope_type="test",
        limitation_message="Test",
        members=(module.ScopeMember("Mol", "13025"),),
    )
    boundary = box(5.0, 51.0, 5.1, 51.1)
    payload = {
        "type": "FeatureCollection",
        "features": [source_feature("bodemtypes.1", box(4.98, 51.02, 5.05, 51.08))],
    }
    raw_bytes = json.dumps(payload, separators=(",", ":")).encode("utf-8")
    monkeypatch.setattr(
        module.soil,
        "iter_wfs_pages",
        lambda *_args, **_kwargs: iter([(payload, "https://example.test/page", raw_bytes)]),
    )

    manifest = module.prepare_partition(
        object(),
        output_root=tmp_path,
        scope=scope,
        member=scope.members[0],
        boundary_wgs84=boundary,
        page_limit=100,
        max_features=1000,
        timeout=30,
        force=False,
    )
    output = json.loads(Path(manifest["output_path"]).read_text(encoding="utf-8"))
    raw_path = Path(manifest["manifest_path"]).parent / manifest["raw_pages"][0]["artifact_path"]

    assert manifest["feature_count"] == 1
    assert output["features"][0]["id"] == "bodemtypes.1:13025"
    assert gzip.decompress(raw_path.read_bytes()) == raw_bytes

    cached = module.prepare_partition(
        object(),
        output_root=tmp_path,
        scope=scope,
        member=scope.members[0],
        boundary_wgs84=boundary,
        page_limit=100,
        max_features=1000,
        timeout=30,
        force=False,
    )
    assert cached["output_sha256"] == manifest["output_sha256"]


def test_snapshot_assembles_all_partitions_with_governed_area_metrics(tmp_path: Path) -> None:
    module = load_script()
    scope = module.GeographicScope(
        key="test-region",
        display_name="Test region",
        project_name="Test",
        project_region="Test",
        area_name="Test area",
        authority_name="Test",
        authority_url="https://example.test",
        scope_type="test",
        limitation_message="Test",
        members=(module.ScopeMember("Left", "10001"), module.ScopeMember("Right", "10002")),
    )
    partitions = []
    for index, member in enumerate(scope.members):
        output_path, manifest_path, _raw_dir = module.partition_paths(tmp_path / scope.key, member.nis_code)
        feature = source_feature(f"bodemtypes.{index}", box(5.0 + index * 0.1, 51.0, 5.05 + index * 0.1, 51.05))
        feature["id"] = f"bodemtypes.{index}:{member.nis_code}"
        feature["properties"].update(
            {
                "clipped_area_ha": 1.0 + index,
                "soil_generalized_legend": "Nat zand",
                "soil_texture_class": "zand",
                "soil_drainage_class": "nat",
            }
        )
        module.soil.write_json_atomic(output_path, {"type": "FeatureCollection", "features": [feature]})
        partitions.append(
            {
                "municipality": member.name,
                "nis_code": member.nis_code,
                "feature_count": 1,
                "raw_source_feature_count": 1,
                "page_count": 1,
                "output_path": str(output_path),
                "output_sha256": module.soil.sha256_file(output_path),
                "manifest_path": str(manifest_path),
            }
        )

    output_path, _manifest_path, manifest = module.assemble_snapshot(
        output_root=tmp_path,
        scope=scope,
        partitions=partitions,
        member_boundaries_sha256="boundaries-hash",
        max_total_features=10,
    )
    output = json.loads(output_path.read_text(encoding="utf-8"))

    assert manifest["coverage_complete"] is True
    assert manifest["feature_count"] == 2
    assert manifest["area_by_generalized_legend_ha"]["Nat zand"] == 3.0
    assert manifest["area_by_texture_ha"]["zand"] == 3.0
    assert len({feature["id"] for feature in output["features"]}) == 2


def test_upload_contract_is_regional_historical_and_canonical(tmp_path: Path) -> None:
    module = load_script()
    scope = module.GEOGRAPHIC_SCOPES["kempen-transport-region"]
    path = tmp_path / "soil.geojson"
    path.write_text('{"type":"FeatureCollection","features":[]}', encoding="utf-8")
    manifest_path = tmp_path / "manifest.json"
    manifest = {
        "coverage_complete": True,
        "feature_count": 42,
        "output_sha256": "output-hash",
        "partition_identity_sha256": "partition-hash",
        "partitions": [{} for _ in scope.members],
        "generated_at": "2026-07-16T00:00:00+00:00",
        "limitations": ["historical"],
    }
    session = FakeApiSession({"id": "dataset-id", "feature_count": 42})

    result = module.upload_snapshot(
        session,
        base_url="http://backend:8000",
        project_id="project-id",
        area_id="area-id",
        scope=scope,
        path=path,
        manifest_path=manifest_path,
        manifest=manifest,
        timeout=30,
    )
    data = session.calls[0][1]["data"]
    source_metadata = json.loads(data["source_metadata_json"])
    provenance = json.loads(data["provenance_metadata_json"])

    assert result["id"] == "dataset-id"
    assert data["area_id"] == "area-id"
    assert data["temporal_series_key"] == "dov:digital-soil-map:kempen-transport-region"
    assert data["valid_from"] == module.soil.VALID_FROM
    assert data["valid_to"] == module.soil.VALID_TO
    assert source_metadata["coverage_scope"] == "kempen-transport-region"
    assert source_metadata["member_count"] == 28
    assert source_metadata["authority_level"] == "authoritative_historical_baseline"
    assert provenance["operator_tool"] == "provision_regional_soil_map.py"
    assert provenance["raw_source_responses_retained"] is True


def test_regional_operator_is_packaged_release_checked_and_query_optimized() -> None:
    dockerfile = (ROOT / "deploy/unraid/Dockerfile.all-in-one").read_text(encoding="utf-8")
    readiness = (ROOT / "scripts/run_readiness_check.sh").read_text(encoding="utf-8")
    service = (ROOT / "backend/app/services/vector_feature_service.py").read_text(encoding="utf-8")

    assert "COPY scripts/provision_regional_soil_map.py" in dockerfile
    assert "py_compile scripts/provision_regional_soil_map.py" in readiness
    assert '"provision_regional_soil_map.py"' in service

    dataset = Dataset(
        name="regional-soil.geojson",
        dataset_type="vector",
        status="ready",
        source_metadata={"partitioned_source_audit": True, "geometry_clipped_to_area": True},
        provenance_metadata={"operator_tool": "provision_regional_soil_map.py"},
    )
    assert VectorFeatureService.preclipped_partition_filter(
        dataset, "Gemeente Mol - officiele grens"
    ) == ("municipality", "Mol")
    assert VectorFeatureService.preclipped_partition_filter(dataset, "Vervoerregio Kempen") is None