"""Parse FDDB lists_*.csv (name;…;produkte) into recipe + ingredients."""
from __future__ import annotations

import csv
import io
import re
from typing import Any

from data_layer.food_mapping import normalize_food_name, parse_quantity_g

ING_RE = re.compile(
    r"(?P<qty>\d+(?:[.,]\d+)?)\s*(?P<unit>g|kg|ml|l)\b\s*(?P<name>.+?)"
    r"(?=,\s*\d+(?:[.,]\d+)?\s*(?:g|kg|ml|l)\b|$)",
    re.IGNORECASE | re.DOTALL,
)


def parse_fddb_produkte(text: str) -> list[dict[str, Any]]:
    raw = (text or "").strip().strip('"')
    if not raw:
        return []
    out: list[dict[str, Any]] = []
    for i, m in enumerate(ING_RE.finditer(raw)):
        qty = float(m.group("qty").replace(",", "."))
        unit = m.group("unit").lower()
        name = re.sub(r"\s+", " ", m.group("name")).strip(" ,;")
        if not name:
            continue
        grams = qty
        if unit == "kg":
            grams = qty * 1000.0
        elif unit == "l":
            grams = qty * 1000.0
        elif unit == "ml":
            grams = qty
        out.append({
            "source_name_raw": name,
            "source_name_normalized": normalize_food_name(name),
            "quantity_raw": f"{m.group('qty').replace(',', '.')} {unit}",
            "quantity_g": round(grams, 3),
            "sort_order": i,
        })
    return out


def parse_fddb_lists_csv(text: str) -> list[dict[str, Any]]:
    if text.startswith("\ufeff"):
        text = text[1:]
    reader = csv.DictReader(io.StringIO(text), delimiter=";")
    recipes = []
    for row in reader:
        name = (row.get("name") or "").strip().strip('"')
        if not name:
            continue
        try:
            portions = float(str(row.get("anzahl_portionen") or "1").replace(",", "."))
        except ValueError:
            portions = 1.0
        if portions <= 0:
            portions = 1.0
        ingredients = parse_fddb_produkte(row.get("produkte") or "")
        if not ingredients:
            leftover = (row.get("produkte") or "").strip().strip('"')
            if leftover:
                ingredients = [{
                    "source_name_raw": leftover,
                    "source_name_normalized": normalize_food_name(leftover),
                    "quantity_raw": None,
                    "quantity_g": parse_quantity_g(leftover),
                    "sort_order": 0,
                }]
        recipes.append({
            "name_raw": name,
            "name_normalized": normalize_food_name(name),
            "portions": portions,
            "description": (row.get("beschreibung") or "").strip() or None,
            "ingredients": ingredients,
        })
    return recipes