"""SPU/SKU 数据库查询 + 底图/模特图资源查找（产品图生成流水线的数据层）。

数据关系（已核实 spu_sku.db）：
  - SPU.code = 款号（如 DG004）
  - SKU.code = "款号-颜色编码"（如 DG004-BL01），SKU.color = 中文色名（黑/灰/...）
  - basemap 目录 = basemap/<款号>/<SKU.code>/xxx.jpg
  - material_library/<品类>/ 存放模特图
  - SKU.img_url_2~5 = CDN 图 URL（底图/细节/模特图，仅作参考字段）
"""
import sqlite3
from pathlib import Path
from typing import Any, Dict, List, Optional

from PIL import Image

# 支持的图片格式：模特图/底图均按此识别（png/jpg 等常见格式全覆盖；AVIF/GIF/TIFF 亦支持）
IMG_EXTS = {".jpg", ".jpeg", ".png", ".webp", ".bmp", ".avif", ".gif", ".tiff", ".tif"}


def _connect(db_path) -> sqlite3.Connection:
    conn = sqlite3.connect(str(db_path))
    conn.row_factory = sqlite3.Row
    return conn


def list_spus(db_path, country: Optional[str] = None) -> List[Dict[str, Any]]:
    """全部 SPU（可选按国家过滤）。"""
    conn = _connect(db_path)
    sql = "SELECT id, code, style, material, printing_type, target_audience, pattern, country, mark FROM SPU"
    params: list = []
    if country:
        sql += " WHERE country = ?"
        params.append(country)
    sql += " ORDER BY code"
    rows = conn.execute(sql, params).fetchall()
    conn.close()
    return [dict(r) for r in rows]


def list_colors(db_path, spu_code: str) -> List[Dict[str, Any]]:
    """款号 → 颜色列表（SKU.code 去重，附中文色名、CDN 底图 URL、最低价）。"""
    conn = _connect(db_path)
    rows = conn.execute(
        """SELECT s.code AS sku_code, s.color, s.img_url_2 AS img_url, MIN(s.price) AS price
           FROM SKU s JOIN SPU p ON s.spu_id = p.id
           WHERE p.code = ?
           GROUP BY s.code, s.color ORDER BY s.code""", (spu_code,)).fetchall()
    conn.close()
    return [dict(r) for r in rows]


def _norm_name(s: str) -> str:
    """去空格（半角+全角）+ 小写，用于 SKU code 与文件夹名比较。"""
    return str(s or "").replace(" ", "").replace("　", "").strip().lower()


def find_basemap(basemap_root, spu_code: str, sku_code: str) -> Optional[Path]:
    """basemap/<款号>/<SKU.code>/ 下第一张图片；无返回 None。

    SKU code 与文件夹名比较时两边都去空格（兼容 db code 或文件夹名带空格）。
    """
    root = Path(basemap_root) / spu_code
    if not root.exists():
        return None
    target = _norm_name(sku_code)
    if not target:
        return None
    d = root / sku_code
    if not (d.exists() and d.is_dir()):
        d = None
        for cand in sorted(root.iterdir()):
            if cand.is_dir() and _norm_name(cand.name) == target:
                d = cand
                break
        if d is None:
            return None
    for f in sorted(d.iterdir()):
        if f.is_file() and f.suffix.lower() in IMG_EXTS:
            return f
    return None


def list_model_images(material_root, category: str = "T-shirt") -> List[Path]:
    """material_library/<品类>/ 下所有图片；无返回空列表。"""
    d = Path(material_root) / category
    if not d.exists():
        return []
    return [f for f in sorted(d.iterdir()) if f.is_file() and f.suffix.lower() in IMG_EXTS]


def find_first_model_folder(material_root, preferred: Optional[str] = None):
    """material_library 下「第一个有图片的子目录」及其图片列表。

    - preferred（如 config 的 model_category）优先：该目录有图就直接用；
    - 否则按子目录名排序，取第一个有图的目录；
    - 全空返回 (None, [])。
    返回 (dir_name or None, images: List[Path])。
    """
    root = Path(material_root)
    if not root.exists():
        return None, []
    candidates = []
    if preferred:
        d = root / preferred
        if d.is_dir():
            candidates.append(d)
    candidates += [d for d in sorted(root.iterdir()) if d.is_dir()]
    seen = set()
    for d in candidates:
        if d in seen:
            continue
        seen.add(d)
        imgs = [f for f in sorted(d.iterdir()) if f.is_file() and f.suffix.lower() in IMG_EXTS]
        if imgs:
            return d.name, imgs
    return None, []


def image_ratio_ok(path, target_ratio: float = 3 / 4, tolerance: float = 0.06) -> bool:
    """图片宽高比是否接近目标比例（默认 3:4，相对容差 6%）。

    相对容差：接受 [target*(1-tol), target*(1+tol)]，对 3:4 即 0.705~0.795。
    无法解析的图片（损坏/非标准）按不通过处理，避免坏图被当模特。
    """
    try:
        with Image.open(path) as im:
            w, h = im.size
        if w <= 0 or h <= 0:
            return False
        ratio = w / h
        lo = target_ratio * (1 - tolerance)
        hi = target_ratio * (1 + tolerance)
        return lo <= ratio <= hi
    except Exception:  # noqa: BLE001
        return False


def build_mark_model_map(db_path, material_root) -> Dict[str, str]:
    """启动任务前检测 spu.mark 字段，建立 {mark: 模特文件夹名} 字典。

    规则：
    - 读取 spu 表全部 mark 值（去重）；
    - 每个 mark 映射到 material_library/<mark> 目录（目录名与 mark 一致）；
    - 目录不存在时回退到 category 默认目录（T-shirt）；
    - 目前库中 mark=1 → 映射到 material_library/T-shirt。
    """
    mark_map: Dict[str, str] = {}
    try:
        root = Path(material_root)
        if not root.exists():
            return mark_map
        folders = [d.name for d in sorted(root.iterdir()) if d.is_dir()]
        if not folders:
            return mark_map
        # 读 spu.mark 实际值（去重）
        marks: List[str] = []
        try:
            conn = _connect(db_path)
            rows = conn.execute("SELECT DISTINCT mark FROM SPU WHERE mark IS NOT NULL AND mark != ''").fetchall()
            conn.close()
            marks = [str(r["mark"]).strip() for r in rows if str(r["mark"]).strip()]
        except Exception:  # noqa: BLE001
            marks = []
        if not marks:
            marks = ["1"]   # 库无 mark 数据时按默认 1 处理
        for m in marks:
            if m in folders:
                mark_map[m] = m
            else:
                # mark 无同名目录 → 回退默认 T-shirt（当前 mark=1 → T-shirt）
                mark_map[m] = "T-shirt" if "T-shirt" in folders else folders[0]
        print(f"[product] mark→模特目录映射: {mark_map}")
    except Exception as e:  # noqa: BLE001
        print(f"[product] mark→模特目录映射构建失败: {e}")
    return mark_map


def find_model_images_for_mark(db_path, material_root, mark, category: str = "T-shirt",
                               ratio: float = 3 / 4, tolerance: float = 0.06) -> List[Path]:
    """按 spu.mark 定位模特目录，过滤非目标比例图片，返回合格图片列表。

    - mark 有对应目录（material_library/<mark>）→ 用该目录；
    - 否则回退 category（如 T-shirt）；
    - 过滤掉非 3:4 比例（默认容差 6%）的图片；
    - 返回过滤后的图片列表（供调用方随机抽取）。
    """
    root = Path(material_root)
    if not root.exists():
        return []
    d = None
    if mark is not None:
        cand = root / str(mark)
        if cand.is_dir():
            d = cand
    if d is None:
        cand = root / category
        if cand.is_dir():
            d = cand
    if d is None:
        # 兜底：第一个有图的目录（跳过无图目录）
        for sub in sorted(root.iterdir()):
            if not sub.is_dir():
                continue
            if any(f.is_file() and f.suffix.lower() in IMG_EXTS for f in sub.iterdir()):
                d = sub
                break
    if d is None:
        return []
    imgs = [f for f in sorted(d.iterdir()) if f.is_file() and f.suffix.lower() in IMG_EXTS]
    ok = [f for f in imgs if image_ratio_ok(f, ratio, tolerance)]
    if len(ok) < len(imgs):
        print(f"[product] 模特目录 {d.name}/ 过滤非 {int(ratio * 100)}:{int(ratio * 100) + 1} 比例："
              f"{len(imgs)} → {len(ok)} 张")
    return ok


def first_available_sku(db_path, basemap_root, spu_code: str) -> Optional[str]:
    """返回该款号下第一个「本地有底图」的 SKU.code；无则 None。"""
    for c in list_colors(db_path, spu_code):
        if find_basemap(basemap_root, spu_code, c["sku_code"]) is not None:
            return c["sku_code"]
    return None