import pandas as pd
from pathlib import Path
from typing import List, Dict, Any
from models import Product, RowOut
import hashlib, json, datetime
import re

# ---- Price parsing helpers ----
_PLN_PRICE_RE = re.compile(
    r'(?<!\d)(\d{1,3}(?:[ \u00A0]?\d{3})*(?:[.,]\d{2})?)(?:\s*(?:zł|PLN))',
    re.IGNORECASE,
)

def parse_pln_price_to_float(price_text: str | None) -> float | None:
    """
    Из строки вида '1 299,00 zł' / '1299 zł' / '1 299 zł' достаём float 1299.00.
    Возвращает None, если распарсить не удалось.
    """
    if not price_text:
        return None
    t = (
        price_text.replace("\u00a0", " ")  # NBSP
        .replace("\u2009", " ")            # thin space
        .strip()
    )
    m = _PLN_PRICE_RE.search(t)
    if not m:
        return None
    num = m.group(1)
    num = num.replace(" ", "").replace("\u00a0", "").replace("\u2009", "")
    num = num.replace(",", ".")
    try:
        return float(num)
    except Exception:
        return None
    
def _as_str(v):
    return str(v) if v is not None else ""

def _key_from_fields(product_id: str | None, url: str | None) -> str:
    base = f"{_as_str(product_id)}|{_as_str(url)}"
    return hashlib.md5(base.encode("utf-8")).hexdigest()

def _key(p: Product) -> str:
    return _key_from_fields(p.product_id, _as_str(p.url))

def build_rows(category_name: str, category_url: str, products: List[Product]) -> List[Dict[str, Any]]:
    """Построить список строк RowOut (dict) из продуктов."""
    rows: List[Dict[str, Any]] = []
    seen: set[str] = set()
    for p in products:
        k = _key(p)
        if k in seen:
            continue
        seen.add(k)
        rows.append(RowOut(
            category_name=category_name,
            category_url=category_url,
            product_id=_as_str(p.product_id) or None,
            url=_as_str(p.url) or None,
            name=p.name,
            price=p.price,
            currency=p.currency,
            color=p.color,
            images_joined="\n".join(p.image_urls) if p.image_urls else None
        ).model_dump())
    return rows

def write_outputs(category_name: str, category_url: str, products: List[Product], out_folder: str, excel_prefix: str, csv_also: bool, jsonl_also: bool):
    """Запись per‑category файлов (xlsx + опционально csv/jsonl). Возвращает (excel_path, nrows, rows)."""
    Path(out_folder).mkdir(parents=True, exist_ok=True)
    rows = build_rows(category_name, category_url, products)

    ts = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
    excel_path = Path(out_folder) / f"{excel_prefix}_{ts}.xlsx"
    df = pd.DataFrame(rows)
    with pd.ExcelWriter(excel_path, engine="openpyxl") as w:
        df.to_excel(w, sheet_name="Products", index=False)

    if csv_also:
        df.to_csv(Path(out_folder) / f"{excel_prefix}_{ts}.csv", index=False)

    if jsonl_also:
        with open(Path(out_folder) / f"{excel_prefix}_{ts}.jsonl", "w", encoding="utf-8") as f:
            for r in rows:
                f.write(json.dumps(r, ensure_ascii=False) + "\n")

    return str(excel_path), len(rows), rows

def write_master_excel(all_path: str, rows: List[Dict[str, Any]]):
    """Записать общий XLSX (один лист AllProducts). Перезаписывает файл целиком один раз в конце."""
    Path(all_path).parent.mkdir(parents=True, exist_ok=True)
    if not rows:
        # ничего не писать — пусто
        return str(all_path), 0
    # дедуп на всякий случай (по product_id|url)
    seen: set[str] = set()
    deduped: List[Dict[str, Any]] = []
    for r in rows:
        k = _key_from_fields(r.get("product_id"), r.get("url"))
        if k in seen:
            continue
        seen.add(k)
        deduped.append(r)
    df = pd.DataFrame(deduped)
    with pd.ExcelWriter(all_path, engine="openpyxl") as w:
        df.to_excel(w, sheet_name="AllProducts", index=False)
    return str(all_path), len(deduped)