"""
Test DB layer: load products_300102013.json (already scraped data)
and upsert into MongoDB 'rohlik' database.

No scraping needed — just validates the db.py functions work
with real API response shapes.
"""

import json
import sys
import io
from pathlib import Path
from db import get_db, ensure_indexes, upsert_products, upsert_category

sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding="utf-8", errors="replace")

DATA_FILE = Path(__file__).parent / "products_300102013.json"


def main():
    db = get_db()
    print(f"Connected to: {db.client.address} / {db.name}")

    ensure_indexes(db)
    print("Indexes created.\n")

    # --- test category upsert ---
    upsert_category(db, {
        "_id": 300102013,
        "name": "Okurky, cukety a lilky",
        "slug": "okurky-cukety-a-lilky",
        "path": [300102000, 300102008, 300102013],
        "pathNames": ["Ovoce a zelenina", "Zelenina", "Okurky, cukety a lilky"],
        "parentId": 300102008,
        "isLeaf": True,
    })
    print("Category 300102013 upserted.")

    # --- load scraped products ---
    products = json.loads(DATA_FILE.read_text(encoding="utf-8"))
    print(f"Loaded {len(products)} products from {DATA_FILE.name}\n")

    # split merged records back into the 4 lists that upsert_products expects
    bases = []
    prices_list = []
    stocks = []
    categories_list = []

    for p in products:
        base = p.get("base", {})
        prices = p.get("prices", {})
        stock = p.get("stock", {})
        cats = p.get("categories", {})

        bases.append(base)
        prices_list.append(prices)
        stocks.append(stock)
        categories_list.append(cats)

    upsert_products(db, bases, prices_list, stocks, categories_list)
    print(f"Upserted {len(bases)} products.\n")

    # --- verify ---
    n_products = db.products.count_documents({})
    n_history = db.price_history.count_documents({})
    n_cats = db.categories.count_documents({})

    print(f"DB counts:")
    print(f"  products:      {n_products}")
    print(f"  price_history: {n_history}")
    print(f"  categories:    {n_cats}")

    # show one sample
    sample = db.products.find_one({"_id": 1407650})
    if sample:
        print(f"\nSample product: {sample['name']}")
        print(f"  price:    {sample['currentPrice']} {sample['currency']}")
        print(f"  per unit: {sample['currentPricePerUnit']}/{sample.get('unit', '?')}")
        print(f"  inStock:  {sample['inStock']}")
        print(f"  sale:     {sample['sale']}")
        print(f"  badges:   {[b['title'] for b in sample.get('badges', [])]}")

    # show price_history entry
    hist = db.price_history.find_one({"productId": 1407650})
    if hist:
        print(f"\n  price_history record: price={hist['price']}, "
              f"inStock={hist['inStock']}, scrapedAt={hist['scrapedAt']}")

    print("\nDone.")


if __name__ == "__main__":
    main()