import tempfile
import unittest
from pathlib import Path

import build_observed_products
import build_review_queue
from layer_helpers import write_csv_rows


class ReviewQueueTests(unittest.TestCase):
    def test_build_review_queue_preserves_existing_status(self):
        observed_rows = [
            {
                "observed_product_id": "gobs_1",
                "retailer": "giant",
                "representative_upc": "111",
                "representative_image_url": "",
                "representative_name_norm": "GALA APPLE",
                "times_seen": "2",
                "distinct_item_names_count": "2",
                "distinct_upcs_count": "1",
                "is_fee": "false",
            }
        ]
        item_rows = [
            {
                "observed_product_id": "gobs_1",
                "item_name": "SB GALA APPLE 5LB",
                "item_name_norm": "GALA APPLE",
                "line_total": "7.99",
            },
            {
                "observed_product_id": "gobs_1",
                "item_name": "SB GALA APPLE 5 LB",
                "item_name_norm": "GALA APPLE",
                "line_total": "8.49",
            },
        ]
        existing = {
            build_review_queue.stable_id("rvw", "gobs_1|missing_image"): {
                "status": "approved",
                "resolution_notes": "looked fine",
                "created_at": "2026-03-15",
            }
        }

        queue = build_review_queue.build_review_queue(
            observed_rows, item_rows, existing, "2026-03-16"
        )

        self.assertEqual(2, len(queue))
        missing_image = [row for row in queue if row["reason_code"] == "missing_image"][0]
        self.assertEqual("approved", missing_image["status"])
        self.assertEqual("looked fine", missing_image["resolution_notes"])

    def test_review_queue_main_writes_output(self):
        with tempfile.TemporaryDirectory() as tmpdir:
            observed_path = Path(tmpdir) / "products_observed.csv"
            items_path = Path(tmpdir) / "items_enriched.csv"
            output_path = Path(tmpdir) / "review_queue.csv"

            observed_rows = [
                {
                    "observed_product_id": "gobs_1",
                    "retailer": "giant",
                    "observed_key": "giant|upc=111|name=GALA APPLE",
                    "representative_upc": "111",
                    "representative_item_name": "SB GALA APPLE 5LB",
                    "representative_name_norm": "GALA APPLE",
                    "representative_brand": "SB",
                    "representative_variant": "",
                    "representative_size_value": "5",
                    "representative_size_unit": "lb",
                    "representative_pack_qty": "",
                    "representative_measure_type": "weight",
                    "representative_image_url": "",
                    "is_store_brand": "true",
                    "is_fee": "false",
                    "first_seen_date": "2026-01-01",
                    "last_seen_date": "2026-01-10",
                    "times_seen": "2",
                    "example_order_id": "1",
                    "example_item_name": "SB GALA APPLE 5LB",
                    "raw_name_examples": "SB GALA APPLE 5LB | SB GALA APPLE 5 LB",
                    "normalized_name_examples": "GALA APPLE",
                    "example_prices": "7.99 | 8.49",
                    "distinct_item_names_count": "2",
                    "distinct_upcs_count": "1",
                }
            ]
            item_rows = [
                {
                    "retailer": "giant",
                    "order_id": "1",
                    "line_no": "1",
                    "item_name": "SB GALA APPLE 5LB",
                    "item_name_norm": "GALA APPLE",
                    "upc": "111",
                    "size_value": "5",
                    "size_unit": "lb",
                    "pack_qty": "",
                    "measure_type": "weight",
                    "is_store_brand": "true",
                    "is_fee": "false",
                    "line_total": "7.99",
                }
            ]

            write_csv_rows(
                observed_path, observed_rows, build_observed_products.OUTPUT_FIELDS
            )
            write_csv_rows(items_path, item_rows, list(item_rows[0].keys()))

            build_review_queue.main.callback(
                observed_csv=str(observed_path),
                items_enriched_csv=str(items_path),
                output_csv=str(output_path),
            )

            self.assertTrue(output_path.exists())


if __name__ == "__main__":
    unittest.main()