from __future__ import annotations

import json
from hashlib import sha256
from pathlib import Path
from uuid import uuid4

from app.models import Dataset, SourceRegistry, SourceSnapshot
from app.services.qa_service import QaService


class FakeSession:
    def __init__(self, datasets=None, areas=None):
        self.datasets = {item.id: item for item in (datasets or [])}
        self.areas = {item.id: item for item in (areas or [])}

    def get(self, model, item_id):
        if model.__name__ == "Dataset":
            return self.datasets.get(item_id)
        if model.__name__ == "Area":
            return self.areas.get(item_id)
        return None


def _feature(feature_id: str, coordinates: list[list[list[float]]]) -> dict:
    return {
        "type": "Feature",
        "id": feature_id,
        "properties": {"source_feature_id": feature_id},
        "geometry": {
            "type": "Polygon",
            "coordinates": coordinates,
        },
    }


def _write_dataset(path: Path, coordinates: list[list[list[float]]]) -> None:
    payload = {
        "type": "FeatureCollection",
        "features": [_feature("feature-1", coordinates)],
    }
    path.write_text(json.dumps(payload), encoding="utf-8")


def _write_features(path: Path, features: list[dict]) -> None:
    path.write_text(json.dumps({"type": "FeatureCollection", "features": features}), encoding="utf-8")


def _authoritative_reference(dataset: Dataset) -> Dataset:
    """Give QA reference fixtures the same durable authority proof as GRB."""

    source_id = uuid4()
    snapshot_id = uuid4()
    checksum = sha256(Path(str(dataset.storage_path)).read_bytes()).hexdigest()
    source = SourceRegistry(
        id=source_id,
        source_key="grb",
        display_name="GRB test reference",
        classification="authoritative",
        authority_name="Digitaal Vlaanderen",
        authority_scope_json={"zone": "Flanders"},
        usage_policy_json={"ground_truth_allowed": True, "validation_authority": {"building_validation": "primary"}},
    )
    snapshot = SourceSnapshot(
        id=snapshot_id,
        source_registry_id=source_id,
        snapshot_key=f"qa-grb-{dataset.id}",
        checksum_sha256=checksum,
        ingest_status="ingested",
        freshness_status="current",
    )
    dataset.source = "grb"
    dataset.source_name = "grb"
    dataset.dataset_role = "reference"
    dataset.status = "ready"
    dataset.checksum_sha256 = checksum
    dataset.source_registry_id = source_id
    dataset.source_snapshot_id = snapshot_id
    dataset.data_contract_key = "geointel.vector.geojson"
    dataset.data_contract_version = "1.0.0"
    dataset.validation_status = "passed"
    dataset.provenance_status = "complete"
    dataset.lineage_status = "complete"
    dataset.quarantine_status = "not_quarantined"
    dataset.source_registry = source
    dataset.source_snapshot = snapshot
    return dataset


def test_qa_compare_candidate_with_reference_returns_metrics(tmp_path) -> None:
    project_id = uuid4()
    candidate_id = uuid4()
    reference_id = uuid4()
    candidate_path = tmp_path / "candidate.geojson"
    reference_path = tmp_path / "reference.geojson"
    polygon = [[[4.0, 51.0], [4.1, 51.0], [4.1, 51.1], [4.0, 51.1], [4.0, 51.0]]]
    _write_dataset(candidate_path, polygon)
    _write_dataset(reference_path, polygon)

    candidate = Dataset(
        id=candidate_id,
        project_id=project_id,
        name="candidate.geojson",
        dataset_type="vector",
        source="test",
        storage_path=str(candidate_path),
        crs="EPSG:4326",
        metadata_json={"crs_assumed": False},
    )
    reference = _authoritative_reference(Dataset(
        id=reference_id,
        project_id=project_id,
        name="reference.geojson",
        dataset_type="vector",
        source="test",
        storage_path=str(reference_path),
        crs="EPSG:4326",
        metadata_json={"crs_assumed": False},
    ))

    result = QaService.compare_candidate_with_reference(
        db=FakeSession([candidate, reference]),
        project_id=project_id,
        candidate_dataset_id=candidate_id,
        reference_dataset_id=reference_id,
        iou_threshold=0.5,
    )

    assert result.status == "ok"
    assert result.matches == 1
    assert result.false_positives == 0
    assert result.false_negatives == 0
    assert result.precision == 1.0
    assert result.recall == 1.0
    assert result.f1_score == 1.0


def test_qa_compare_candidate_with_reference_returns_feature_level_evidence(tmp_path) -> None:
    project_id = uuid4()
    candidate_id = uuid4()
    reference_id = uuid4()
    candidate_path = tmp_path / "candidate.geojson"
    reference_path = tmp_path / "reference.geojson"
    matched_candidate = [[[4.0, 51.0], [4.1, 51.0], [4.1, 51.1], [4.0, 51.1], [4.0, 51.0]]]
    matched_reference = [[[4.0, 51.0], [4.1, 51.0], [4.1, 51.1], [4.0, 51.1], [4.0, 51.0]]]
    false_positive = [[[4.5, 51.5], [4.6, 51.5], [4.6, 51.6], [4.5, 51.6], [4.5, 51.5]]]
    false_negative = [[[4.8, 51.8], [4.9, 51.8], [4.9, 51.9], [4.8, 51.9], [4.8, 51.8]]]
    _write_features(candidate_path, [_feature("candidate-match", matched_candidate), _feature("candidate-extra", false_positive)])
    _write_features(reference_path, [_feature("reference-match", matched_reference), _feature("reference-missing", false_negative)])

    candidate = Dataset(
        id=candidate_id,
        project_id=project_id,
        name="candidate.geojson",
        dataset_type="vector",
        source="test",
        storage_path=str(candidate_path),
        crs="EPSG:4326",
        metadata_json={"crs_assumed": False},
    )
    reference = _authoritative_reference(Dataset(
        id=reference_id,
        project_id=project_id,
        name="reference.geojson",
        dataset_type="vector",
        source="test",
        storage_path=str(reference_path),
        crs="EPSG:4326",
        metadata_json={"crs_assumed": False},
    ))

    result = QaService.compare_candidate_with_reference(
        db=FakeSession([candidate, reference]),
        project_id=project_id,
        candidate_dataset_id=candidate_id,
        reference_dataset_id=reference_id,
        iou_threshold=0.5,
    )

    assert result.matches == 1
    assert result.false_positives == 1
    assert result.false_negatives == 1
    assert result.match_evidence == [
        {
            "candidate_feature_id": "candidate-match",
            "reference_feature_id": "reference-match",
            "iou": 1.0,
        }
    ]
    assert result.false_positive_evidence == [{"candidate_feature_id": "candidate-extra"}]
    assert result.false_negative_evidence == [{"reference_feature_id": "reference-missing"}]


def test_dataset_reference_metadata_migration_declares_required_columns() -> None:
    migration_path = Path(__file__).parents[1] / "alembic" / "versions" / "202606120001_add_dataset_reference_metadata.py"
    migration_text = migration_path.read_text(encoding="utf-8")
    for column_name in (
        "dataset_role",
        "source_name",
        "reference_layer_name",
        "source_metadata",
        "provenance_metadata",
        "imported_at",
    ):
        assert column_name in migration_text