import json
from types import SimpleNamespace

from tht.mschema.catalog_snapshot import load_catalog_metadata_snapshot
from tht.mschema.context import load_schema_context
from tht.search import SearchResult, schema_tables
from tht.vectorstore.records import catalog_schema_records, qdrant_semantic_kind


def _snapshot():
    return {
        "schemaVersion": 1,
        "workspaceId": "sales",
        "databaseId": "db-1",
        "databaseName": "warehouse",
        "schemaName": "analytics",
        "metadataContentRevision": 7,
        "tables": [
            {
                "id": "table-orders",
                "name": "orders",
                "description": "Customer orders",
                "descriptionSource": "curated",
                "columns": [
                    {
                        "id": "column-customer",
                        "name": "customer_id",
                        "ordinalPosition": 1,
                        "dataType": "uuid",
                        "isNullable": False,
                        "defaultExpression": None,
                        "primaryKeyPosition": None,
                        "sensitive": False,
                        "description": "Ordering customer",
                        "descriptionSource": "generated",
                    }
                ],
            },
            {
                "id": "table-customers",
                "name": "customers",
                "description": None,
                "descriptionSource": None,
                "columns": [
                    {
                        "id": "column-id",
                        "name": "id",
                        "ordinalPosition": 1,
                        "dataType": "uuid",
                        "isNullable": False,
                        "defaultExpression": None,
                        "primaryKeyPosition": 1,
                        "sensitive": True,
                        "description": "Customer identifier",
                        "descriptionSource": "source_comment",
                    }
                ],
            },
        ],
        "relationships": [
            {
                "id": "relationship-1",
                "origin": "physical",
                "sourceTable": "orders",
                "sourceColumns": ["customer_id"],
                "targetTable": "customers",
                "targetColumns": ["id"],
            }
        ],
    }


def test_catalog_snapshot_is_the_schema_context_and_vector_source(tmp_path):
    path = tmp_path / "catalog-metadata.json"
    path.write_text(json.dumps(_snapshot()))
    cfg = SimpleNamespace(
        paths=SimpleNamespace(catalog_metadata_snapshot=path),
        _workspace_id="sales",
    )

    context = load_schema_context(cfg)
    assert context.physical.database == "warehouse"
    assert context.physical.tables["orders"].comment == "Customer orders"
    assert context.physical.tables["customers"].columns["id"].eligibility_reason == "sensitive"
    assert context.effective_relationships["orders"][0].ref_table == "customers"

    snapshot = load_catalog_metadata_snapshot(path, "sales")
    records = catalog_schema_records(snapshot)
    assert [record.kind for record in records].count("schema_relationship") == 1
    relationship = next(record for record in records if record.kind == "schema_relationship")
    assert relationship.metadata["tables"] == ["orders", "customers"]
    assert qdrant_semantic_kind("schema_relationship") == "schema"


def test_relationship_hit_promotes_both_endpoint_tables():
    result = SearchResult(
        key="relationship:orders->customers",
        label="orders->customers",
        kind="schema_relationship",
        signals={"vector": {"rank": 1, "score": 0.9}},
        rrf=0.5,
    )
    assert schema_tables([result], 10) == [("customers", 0.5), ("orders", 0.5)]