from __future__ import annotations

from uuid import uuid4

import pytest
from pydantic import ValidationError

from app.api.routes.selection_partitions import select_vector_partitions
from app.core.errors import AppError
from app.models import Dataset
from app.schemas.selection_partitions import VectorPartitionSelectionRequest
from app.services.vector_feature_service import VectorFeatureService


class DatasetQuery:
    def __init__(self, datasets):
        self.datasets = datasets

    def filter(self, *_args):
        return self

    def all(self):
        return self.datasets


class DatasetSession:
    def __init__(self, datasets):
        self.datasets = datasets

    def query(self, model):
        assert model is Dataset
        return DatasetQuery(self.datasets)


def make_dataset(project_id, dataset_id, *, source_name="grb", product_key="buildings"):
    return Dataset(
        id=dataset_id,
        project_id=project_id,
        name=f"{source_name}-{product_key}",
        dataset_type="vector",
        source="official",
        dataset_role="reference",
        source_name=source_name,
        reference_layer_name=product_key,
        source_metadata={"product_key": product_key, "theme": product_key},
        provenance_metadata={},
        metadata_json={},
        status="ready",
    )


def test_vector_partition_route_combines_one_governed_product(monkeypatch) -> None:
    project_id = uuid4()
    dataset_ids = [uuid4(), uuid4()]
    db = DatasetSession([make_dataset(project_id, dataset_id) for dataset_id in dataset_ids])
    captured = {}

    def select_features(_db, **kwargs):
        captured.update(kwargs)
        return {
            "selection_bbox": kwargs["bbox"],
            "feature_count": 1,
            "total_feature_count": 3,
            "limit": kwargs["limit"],
            "truncated": False,
            "geojson": {"type": "FeatureCollection", "features": []},
            "summary": None,
        }

    monkeypatch.setattr(VectorFeatureService, "select_features_by_bbox", select_features)
    payload = VectorPartitionSelectionRequest(
        dataset_ids=dataset_ids,
        bbox={"min_x": 5.0, "min_y": 51.0, "max_x": 5.3, "max_y": 51.2},
    )
    response = select_vector_partitions(project_id, payload, db)

    assert captured["dataset_ids"] == dataset_ids
    assert captured["deduplicate_source_features"] is True
    assert response["data"]["partition_count"] == 2
    assert response["data"]["dataset_ids"] == dataset_ids


def test_vector_partition_request_has_a_bounded_fan_out() -> None:
    with pytest.raises(ValidationError):
        VectorPartitionSelectionRequest(
            dataset_ids=[uuid4() for _ in range(4097)],
            bbox={"min_x": 5.0, "min_y": 51.0, "max_x": 5.3, "max_y": 51.2},
        )


def test_vector_partition_route_rejects_mixed_source_products() -> None:
    project_id = uuid4()
    datasets = [
        make_dataset(project_id, uuid4(), source_name="grb", product_key="buildings"),
        make_dataset(project_id, uuid4(), source_name="spw_picc", product_key="picc_buildings"),
    ]
    payload = VectorPartitionSelectionRequest(
        dataset_ids=[dataset.id for dataset in datasets],
        bbox={"min_x": 5.0, "min_y": 51.0, "max_x": 5.3, "max_y": 51.2},
    )
    with pytest.raises(AppError) as exc_info:
        select_vector_partitions(project_id, payload, DatasetSession(datasets))
    assert getattr(exc_info.value, "code", None) == "VECTOR_PARTITION_SOURCE_MISMATCH"