POD 趋势感知 Agent：缓存热点模式 + 三图合成 + 热点去重/风格去重 + review 兜底
- 缓存热点批量流程（有采集缓存不触发 Google） - 简报不足直接从采集缓存生成（轻量补齐） - 三图合成（模特/印花/底图）+ 底图压缩 <2MB - 热点去重→风格去重自动切换 + 不适合类目 review 兜底 - 透明背景（background=transparent）+ 提示词清洗（敏感词/背景描述） - 任务前 basemap 校验 + 模板国家校验 + 模特任务级分配
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# -*- coding: utf-8 -*-
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"""
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从 inkreach PostgreSQL 同步指定国家货盘商品数据到 SQLite (spu_sku.db)
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支持多国累积同步（保留已存在数据）：
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- sync(plate_ids, country, clear_first)
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clear_first=True -> 先 DELETE 整库再插入（重置该次目标）
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clear_first=False -> 仅追加，跳过已存在的 SPU code 与 SKU 组合
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国家货盘 plate_id 映射：
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- 美国 : (2, 3, 4, 5) country="US"
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- 墨西哥: (6,) country="MX"
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- 日本 : (7,) country="JP"
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- 韩国 : (8,) country="KR"
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- 沙特 : (9,) country="SA"
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- 巴西 : (10,) country="BR"
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- 英国 : (11,) country="GB"
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- 加拿大: (12,) country="CA"
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- 波兰 : (13,) country="PL"
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- 西班牙: (14,) country="ES"
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- 德国 : (15,) country="DE"
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- 澳洲 : (16,) country="AU"
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- 意大利: (17,) country="IT"
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SPU = categories（code 去重）
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SKU = 颜色 × 尺码 粒度：
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- code = colors.code 颜色映射编码（脏数据兜底为 款号-颜色的英文名，英文名取自 color_detail_images.color_name_web）
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- color = colors.name 颜色名
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- size = product_extra.product_size JSON 的尺码列（缺 JSON 回退 size_chart）
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- 肩宽/胸围/衣长/袖长 = product_size JSON 对应列（动态识别表头）
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- 最长边/次长边/最短边 = packaging_spec JSON "包装尺寸（cm）" 列 长*宽*高 拆分排序
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- package_weight = packaging_spec JSON "含包装重量（g）" 列（单位: 克）
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- price = 该品类 prices 首条价格（颜色尺码粒度无独立价格）
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- img_url_2~5 = 该品类首颜色 web_sku 的图（seq 2~5）
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"""
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import sqlite3
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import psycopg2
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import re
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import json
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PG = dict(host="localhost", port=5432, user="postgres", password="inkreach", dbname="inkreach")
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SQLITE = r"C:\Users\Admin\Desktop\test模版\design_agent\pod_trend_agent\db\spu_sku.db"
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def clean(v):
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if v is None:
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return None
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s = str(v).strip()
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return s if s else None
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def format_pct(v):
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"""成分比例转百分比形式：'100'/'100.0' -> '100%'，空值保持 None"""
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s = clean(v)
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if s is None:
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return None
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try:
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num = float(s)
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if num == int(num):
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return f"{int(num)}%"
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return f"{num}%"
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except ValueError:
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return s
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# 中文颜色名 -> 英文（color_name_web 缺失时的兜底）
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ZH_TO_EN = {
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"黑": "Black", "黑色": "Black",
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"白": "White", "白色": "White",
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"灰": "Gray", "灰色": "Gray",
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"杏": "Apricot", "杏色": "Apricot",
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"咖色": "Coffee", "咖": "Coffee",
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"藏青": "Navy", "藏青色": "Navy",
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"蓝": "Blue", "蓝色": "Blue", "海蓝": "Blue", "海蓝色": "Ocean Blue",
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"翠绿": "Green", "翠绿色": "Green", "绿": "Green", "绿色": "Green",
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"紫": "Purple", "紫色": "Purple",
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"玫红": "Rose", "玫红色": "Rose", "粉": "Pink", "粉色": "Pink", "粉红": "Pink",
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"红": "Red", "红色": "Red",
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"黄": "Yellow", "黄色": "Yellow",
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"金": "Gold", "金色": "Gold",
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"银": "Silver", "银色": "Silver",
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"棕": "Brown", "棕色": "Brown",
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"米": "Beige", "米色": "Beige", "卡其": "Khaki", "卡其色": "Khaki",
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"橙": "Orange", "橙色": "Orange",
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}
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def clean_color_name(name):
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"""清洗颜色名：
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'S-3XL黑色' -> '黑色'（去开头尺码前缀）
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'灰色（S~XXL）' -> '灰色'（去结尾尺码区间括号）
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'（M~3XL）' -> None（纯尺码无颜色）
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保留中文颜色核心部分。"""
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s = clean(name)
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if not s:
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return None
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# 开头若全是非中文（尺码前缀如 S-3XL / S（4-5）y），取其后中文部分
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m = re.match(r"^[^一-鿿]+([一-鿿].*)$", s)
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if m:
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s = m.group(1).strip()
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# 去掉结尾的尺码区间括号，如 （S~XXL）/（M~5XL）/（XS~3XL）
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s = re.sub(r"[（(][^一-鿿]*[）)]$", "", s).strip()
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# 去掉残留的纯尺码/空白字符
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s = s.strip(" ()（）~ ")
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return s if s else None
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def is_clean_code(ccode, catcode):
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"""判断颜色 code 是否规范：必须以 品类code- 开头，
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且后缀为纯字母数字（如 BL01 / ESPRESSO），不含中文、~ 或括号。
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纯尺码区间（如 JPHM009-（S~XXXL））与多色拼接脏数据会被判为非规范。"""
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if not ccode or not catcode:
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return False
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prefix = catcode + "-"
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if not ccode.startswith(prefix):
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return False
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suffix = ccode[len(prefix):]
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if not suffix or re.search(r"[一-鿿~（(）)]", suffix):
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return False
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return True
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def first_color_en(name):
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"""从可能含多色的脏名称中取首个可识别颜色的英文名，否则原样返回。"""
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if not name:
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return None
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for zh, en in ZH_TO_EN.items():
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if zh in name:
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return en
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return name
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def extract_weight(name):
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if not name:
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return None, None
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m = re.search(r"(\d+(?:\.\d+)?)\s*(?:G|g|克)", name)
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if m:
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return m.group(1), "G"
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return None, None
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def parse_size_json(raw):
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"""product_size JSON -> [{size, shoulder, bust, length, sleeve}...]"""
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if not raw:
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return []
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try:
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data = json.loads(raw)
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except Exception:
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return []
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if not isinstance(data, list) or len(data) < 2:
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return []
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header = [c.get("content", "") for c in data[0]]
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size_i = next((i for i, h in enumerate(header) if "尺码" in h), None)
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sh_i = next((i for i, h in enumerate(header) if "肩宽" in h), None)
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bu_i = next((i for i, h in enumerate(header) if "胸围" in h), None)
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le_i = next((i for i, h in enumerate(header) if "衣长" in h), None)
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sl_i = next((i for i, h in enumerate(header) if "袖长" in h), None)
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if size_i is None:
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return []
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rows = []
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for r in data[1:]:
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if not isinstance(r, list):
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continue
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def cell(i):
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if i is None or i >= len(r):
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return None
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return clean(r[i].get("content", "") if isinstance(r[i], dict) else r[i])
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size = cell(size_i)
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if not size or size == "尺码":
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continue
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rows.append(dict(size=size, shoulder=cell(sh_i), bust=cell(bu_i),
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length=cell(le_i), sleeve=cell(sl_i)))
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return rows
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def parse_pkg_json(raw):
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"""packaging_spec JSON -> {size: (longest, second, shortest)} 按 cm 列拆分排序"""
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if not raw:
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return {}
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try:
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data = json.loads(raw)
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except Exception:
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return {}
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if not isinstance(data, list) or len(data) < 2:
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return {}
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header = data[0]
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size_i = next((i for i, c in enumerate(header) if "尺码" in c.get("content", "")), None)
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cm_i = next((i for i, c in enumerate(header)
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if "包装尺寸" in c.get("content", "") and "cm" in c.get("content", "")), None)
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if size_i is None or cm_i is None:
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return {}
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out = {}
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for r in data[1:]:
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if not isinstance(r, list) or cm_i >= len(r):
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continue
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size = clean(r[size_i].get("content", "")) if isinstance(r[size_i], dict) else clean(r[size_i])
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val = clean(r[cm_i].get("content", "")) if isinstance(r[cm_i], dict) else clean(r[cm_i])
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if not size or not val:
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continue
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parts = re.findall(r"\d+(?:\.\d+)?", val)
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if len(parts) >= 3:
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nums = sorted((float(p) for p in parts[:3]), reverse=True)
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out[size] = (nums[0], nums[1], nums[2])
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return out
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def parse_weight_json(raw):
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"""packaging_spec JSON -> {size: 含包装重量(g)}，取"含包装重量（g）"列"""
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if not raw:
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return {}
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try:
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data = json.loads(raw)
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except Exception:
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return {}
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if not isinstance(data, list) or len(data) < 2:
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return {}
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header = data[0]
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size_i = next((i for i, c in enumerate(header) if "尺码" in c.get("content", "")), None)
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w_i = next((i for i, c in enumerate(header)
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if "重量" in c.get("content", "") and "（g）" in c.get("content", "")), None)
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if size_i is None or w_i is None:
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return {}
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out = {}
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for r in data[1:]:
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if not isinstance(r, list) or w_i >= len(r):
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continue
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size = clean(r[size_i].get("content", "")) if isinstance(r[size_i], dict) else clean(r[size_i])
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val = clean(r[w_i].get("content", "")) if isinstance(r[w_i], dict) else clean(r[w_i])
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if not size or not val:
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continue
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out[size] = val
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return out
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def sync(plate_ids, country, clear_first=True):
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print(f"\n==== 同步 {country} (plate_ids={plate_ids}, clear_first={clear_first}) ====")
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pg = psycopg2.connect(**PG)
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pg.autocommit = True
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pc = pg.cursor()
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# ---------- SPU 数据 ----------
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pc.execute("""
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SELECT c.id, c.plate_id, c.code, c.name, c.sub_category, c.fabric, c.composition, p.display_name
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FROM categories c
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LEFT JOIN plates p ON c.plate_id = p.id
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WHERE c.plate_id IN %s AND c.code IS NOT NULL AND c.code <> ''
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ORDER BY c.plate_id, c.id
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""", (plate_ids,))
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cat_rows = pc.fetchall()
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spu_map = {}
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for cid, plate_id, code, name, sub, fabric, comp, display in cat_rows:
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if code in spu_map:
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prev = spu_map[code]
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prev_score = (0 if prev["sub"] == "组合款" else 1, -prev["plate_id"], -prev["cid"])
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new_score = (0 if sub == "组合款" else 1, -plate_id, -cid)
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if new_score > prev_score:
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spu_map[code] = dict(cid=cid, plate_id=plate_id, name=name, sub=sub,
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fabric=fabric, comp_raw=comp, display=display)
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else:
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spu_map[code] = dict(cid=cid, plate_id=plate_id, name=name, sub=sub,
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fabric=fabric, comp_raw=comp, display=display)
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pc.execute("""
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SELECT category_id, fabric, comp1, comp1_pct, comp2, comp2_pct, comp3, comp3_pct
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FROM composition
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""")
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comp_by_cat = {}
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for cid, fabric, c1, p1, c2, p2, c3, p3 in pc.fetchall():
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comp_by_cat[cid] = dict(c1=c1, p1=p1, c2=c2, p2=p2, c3=c3, p3=p3)
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pc.execute("""
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SELECT code, english_name, washing_instructions, design_explanation, texture,
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product_size, packaging_spec
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FROM product_extra
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""")
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extra_by_code = {}
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for code, en, wash, design, texture, psize, pkg in pc.fetchall():
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extra_by_code[code] = dict(en=en, wash=wash, design=design, texture=texture,
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psize=psize, pkg=pkg)
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# ---------- SKU 数据 ----------
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# 颜色
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pc.execute("""
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SELECT id, category_id, name, code, size_range
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FROM colors
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WHERE category_id IN (SELECT id FROM categories WHERE plate_id IN %s)
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ORDER BY category_id, seq
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""", (plate_ids,))
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colors_by_cat = {}
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for col_id, cid, name, code, sr in pc.fetchall():
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colors_by_cat.setdefault(cid, []).append(dict(id=col_id, name=name, code=code, sr=sr))
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# 颜色英文名（color_detail_images.color_name_web，按 color_id）
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pc.execute("""
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SELECT DISTINCT color_id, color_name_web
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FROM color_detail_images
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WHERE color_id IN (
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SELECT id FROM colors
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WHERE category_id IN (SELECT id FROM categories WHERE plate_id IN %s)
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)
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""", (plate_ids,))
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color_en_by_id = {}
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for col_id, en in pc.fetchall():
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en = clean(en)
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if en:
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color_en_by_id[col_id] = en
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# size_chart 回退
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pc.execute(f"""
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SELECT category_id, size, shoulder, bust, length, sleeve
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FROM size_chart
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WHERE category_id IN (SELECT id FROM categories WHERE plate_id IN %s)
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ORDER BY category_id, seq
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""", (plate_ids,))
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sizechart_by_cat = {}
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for cid, size, sh, bu, le, sl in pc.fetchall():
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sizechart_by_cat.setdefault(cid, []).append(dict(size=size, shoulder=sh, bust=bu,
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length=le, sleeve=sl))
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# prices（首条价格）
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pc.execute("""
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SELECT code, price FROM prices
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WHERE code IN (SELECT DISTINCT code FROM categories WHERE plate_id IN %s)
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ORDER BY code, web_product_id
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""", (plate_ids,))
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price_by_code = {}
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for code, price in pc.fetchall():
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if code not in price_by_code:
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||||
price_by_code[code] = price
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# 图片（按 code，取首个 web_sku 的图）
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pc.execute("""
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SELECT cd.code, cd.web_sku, cd.seq, cd.image_url
|
||||
FROM color_detail_images cd
|
||||
WHERE cd.code IN (SELECT DISTINCT code FROM categories WHERE plate_id IN %s)
|
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ORDER BY cd.code, cd.web_sku, cd.seq
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||||
""", (plate_ids,))
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imgs_by_code = {}
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for code, wsku, seq, url in pc.fetchall():
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imgs_by_code.setdefault(code, []).append((wsku, seq, url))
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pg.close()
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# ---------- 写入 SQLite ----------
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||||
db = sqlite3.connect(SQLITE)
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cur = db.cursor()
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||||
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||||
if clear_first:
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||||
cur.execute("DELETE FROM SKU")
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||||
cur.execute("DELETE FROM SPU")
|
||||
db.commit()
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print("[clear] 已清空 SPU/SKU 旧数据")
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||||
else:
|
||||
print("[append] 保留现有数据，仅追加新国家")
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||||
|
||||
# append 模式：收集已存在的 SPU code 与 SKU 组合，避免重复插入
|
||||
existing_spu_codes = set()
|
||||
existing_sku_keys = set()
|
||||
if not clear_first:
|
||||
existing_spu_codes = {r[0] for r in cur.execute("SELECT code FROM SPU")}
|
||||
existing_sku_keys = {(r[0], r[1], r[2])
|
||||
for r in cur.execute("SELECT spu_id, code, size FROM SKU")}
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||||
print(f"[append] 已有 SPU {len(existing_spu_codes)} 条, SKU {len(existing_sku_keys)} 条")
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||||
|
||||
# SPU
|
||||
spu_id_by_code = {}
|
||||
n_spu = 0
|
||||
n_spu_skip = 0
|
||||
for code, s in sorted(spu_map.items()):
|
||||
# append 模式：若该 SPU code 已存在则跳过（保留首次写入的数据）
|
||||
if code in existing_spu_codes:
|
||||
spu_id = cur.execute("SELECT id FROM SPU WHERE code=?", (code,)).fetchone()[0]
|
||||
spu_id_by_code[code] = spu_id
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||||
n_spu_skip += 1
|
||||
continue
|
||||
comp = comp_by_cat.get(s["cid"], {}) or {}
|
||||
weight, wunit = extract_weight(s["name"])
|
||||
# 业务模板固定值（按用户要求，不随 PG 数据变化）
|
||||
fixed = dict(
|
||||
pattern="印花", details="无", collar_style="圆领", style="休闲",
|
||||
care_Instructions="数码印花类可机洗且不可干洗", fabric="微弹",
|
||||
target_audience="成人", season="四季", is_transparent="否", layout="常规",
|
||||
weaving_method="针织(含钩织、毛织面料)", printing_type="定位印花",
|
||||
fabric_texture_1="光面", fabric_weight_unit_1="g/㎡",
|
||||
lining_texture="无里料/无内衬", mark="1",
|
||||
)
|
||||
cur.execute("""
|
||||
INSERT INTO SPU (
|
||||
code, material, component_1, component_2, component_3,
|
||||
component_proportion_1, component_proportion_2, component_proportion_3,
|
||||
pattern, details, collar_style, style, care_Instructions, fabric,
|
||||
target_audience, season, is_transparent, layout, weaving_method,
|
||||
printing_type, fabric_texture_1, fabric_weight_1, fabric_weight_unit_1,
|
||||
lining_texture, country, mark
|
||||
) VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)
|
||||
""", (
|
||||
code, clean(s["fabric"]),
|
||||
clean(comp.get("c1")), clean(comp.get("c2")), clean(comp.get("c3")),
|
||||
format_pct(comp.get("p1")), format_pct(comp.get("p2")), format_pct(comp.get("p3")),
|
||||
fixed["pattern"], fixed["details"], fixed["collar_style"], fixed["style"],
|
||||
fixed["care_Instructions"], fixed["fabric"], fixed["target_audience"],
|
||||
fixed["season"], fixed["is_transparent"], fixed["layout"], fixed["weaving_method"],
|
||||
fixed["printing_type"], fixed["fabric_texture_1"], weight, fixed["fabric_weight_unit_1"],
|
||||
fixed["lining_texture"],
|
||||
country, fixed["mark"],
|
||||
))
|
||||
spu_id_by_code[code] = cur.lastrowid
|
||||
n_spu += 1
|
||||
|
||||
# SKU（颜色 × 尺码）
|
||||
n_sku = 0
|
||||
n_sku_skip = 0
|
||||
detail = dict(no_color=0, no_size=0, no_pkg=0, no_img=0, color_sku=0)
|
||||
for code, s in sorted(spu_map.items()):
|
||||
spu_id = spu_id_by_code[code]
|
||||
cat_id = s["cid"]
|
||||
extra = extra_by_code.get(code, {})
|
||||
|
||||
# 颜色列表
|
||||
color_list = colors_by_cat.get(cat_id, [])
|
||||
if not color_list:
|
||||
color_list = [dict(name=None, code=code, sr=None)] # 兜底
|
||||
detail["no_color"] += 1
|
||||
# 品类尺码范围（取首个非空）
|
||||
sr = next((c["sr"] for c in color_list if c["sr"]), None)
|
||||
if sr is None:
|
||||
sr = None
|
||||
|
||||
# 尺码表：product_size JSON 优先，回退 size_chart
|
||||
size_rows = parse_size_json(extra.get("psize"))
|
||||
if not size_rows:
|
||||
size_rows = sizechart_by_cat.get(cat_id, [])
|
||||
if not size_rows:
|
||||
detail["no_size"] += 1
|
||||
pkg_map = parse_pkg_json(extra.get("pkg"))
|
||||
weight_map = parse_weight_json(extra.get("pkg"))
|
||||
# 归一化兜底：尺码列可能带英寸后缀（如 '30*40/76.2*101.6' vs '30*40'）
|
||||
pkg_map_norm = {k.split("/")[0]: v for k, v in pkg_map.items()}
|
||||
weight_map_norm = {k.split("/")[0]: v for k, v in weight_map.items()}
|
||||
|
||||
def lookup_pkg(size):
|
||||
v = pkg_map.get(size) or pkg_map_norm.get(size.split("/")[0])
|
||||
if v is None and ("one" in size.lower() or "均码" in size):
|
||||
v = pkg_map.get("均码") or pkg_map.get("Onesize") or pkg_map.get("OneSize")
|
||||
return v
|
||||
|
||||
def lookup_weight(size):
|
||||
v = weight_map.get(size) or weight_map_norm.get(size.split("/")[0])
|
||||
if v is None and ("one" in size.lower() or "均码" in size):
|
||||
v = weight_map.get("均码") or weight_map.get("Onesize") or weight_map.get("OneSize")
|
||||
return v
|
||||
|
||||
# 图片
|
||||
imgs = imgs_by_code.get(code, [])
|
||||
if imgs:
|
||||
first_sku = imgs[0][0]
|
||||
urls = [u for ws, _, u in imgs if ws == first_sku]
|
||||
else:
|
||||
urls = []
|
||||
if not urls:
|
||||
detail["no_img"] += 1
|
||||
img2 = urls[1] if len(urls) > 1 else None
|
||||
img3 = urls[2] if len(urls) > 2 else None
|
||||
img4 = urls[3] if len(urls) > 3 else None
|
||||
img5 = urls[4] if len(urls) > 4 else None
|
||||
|
||||
price = price_by_code.get(code)
|
||||
# 按用户要求：size_group 固定为"尺码"，size_type 固定为"欧美尺码常规"
|
||||
sgroup = "尺码"
|
||||
stype = "欧美尺码常规"
|
||||
|
||||
for col in color_list:
|
||||
raw_code = col["code"]
|
||||
raw_name = col["name"]
|
||||
col_id = col["id"]
|
||||
cname = clean_color_name(raw_name) # 清洗颜色名（去尺码前缀/区间）
|
||||
# 颜色英文名：优先 PG color_name_web，否则用中文名查兜底字典/取首个颜色
|
||||
en = None
|
||||
if cname:
|
||||
en = color_en_by_id.get(col_id) or first_color_en(cname)
|
||||
# 命名规则：
|
||||
# 规范 code（品类code-英文/缩写，无中文，如 JPHM009-BL01 / JPTM007-ESPRESSO）
|
||||
# -> 直接使用
|
||||
# 缺失/脏 code（含中文或尺码区间）-> 款号(品类code)-颜色的英文名
|
||||
if not is_clean_code(raw_code, code):
|
||||
ccode = f"{code}-{en}" if en else code
|
||||
else:
|
||||
ccode = raw_code
|
||||
for srow in size_rows:
|
||||
size = clean(srow["size"])
|
||||
if not size:
|
||||
continue
|
||||
# append 模式：跳过已存在的 SKU 组合
|
||||
if (spu_id, ccode, size) in existing_sku_keys:
|
||||
n_sku_skip += 1
|
||||
continue
|
||||
pkg = lookup_pkg(size)
|
||||
pkg_weight = lookup_weight(size)
|
||||
cur.execute("""
|
||||
INSERT INTO SKU (
|
||||
spu_id, code, price, color, size, size_group, size_type,
|
||||
shoulder_width, bust, clothing_length, sleeve_length,
|
||||
longest_side, secondary_long_side, shortest_side,
|
||||
package_weight, img_url_2, img_url_3, img_url_4, img_url_5
|
||||
) VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)
|
||||
""", (
|
||||
spu_id, ccode, price, cname, size, sgroup, stype,
|
||||
clean(srow.get("shoulder")), clean(srow.get("bust")),
|
||||
clean(srow.get("length")), clean(srow.get("sleeve")),
|
||||
str(pkg[0]) if pkg else None,
|
||||
str(pkg[1]) if pkg else None,
|
||||
str(pkg[2]) if pkg else None,
|
||||
pkg_weight,
|
||||
img2, img3, img4, img5,
|
||||
))
|
||||
n_sku += 1
|
||||
|
||||
db.commit()
|
||||
|
||||
# ---------- 验证 ----------
|
||||
print(f" 本次新增 SPU: {n_spu} (跳过已存在 {n_spu_skip})")
|
||||
print(f" 本次新增 SKU: {n_sku} (跳过已存在 {n_sku_skip}) (颜色×尺码展开)")
|
||||
print(f" 无颜色品类: {detail['no_color']}, 无尺码品类: {detail['no_size']}, 无图品类: {detail['no_img']}")
|
||||
print(f" 库内 SPU 总数: {cur.execute('SELECT COUNT(*) FROM SPU').fetchone()[0]}")
|
||||
print(f" 库内 SKU 总数: {cur.execute('SELECT COUNT(*) FROM SKU').fetchone()[0]}")
|
||||
print(f" country 分布: {cur.execute('SELECT country, COUNT(*) FROM SPU GROUP BY country').fetchall()}")
|
||||
db.close()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# 顺序执行：先全量同步美国（重置整库），再依次追加其他国家（保留已有数据）
|
||||
sync((2, 3, 4, 5), "US", clear_first=True)
|
||||
sync((6,), "MX", clear_first=False)
|
||||
sync((7,), "JP", clear_first=False)
|
||||
sync((11,), "GB", clear_first=False)
|
||||
print("\n✅ 同步完成：SPU/SKU 已包含 US + MX + JP + GB 数据")
|
||||
Reference in New Issue
Block a user