liuwenxin和Claude Code
91fc6f6293
- delete_product 补 count_refs 引用检查（业务明细+发货明细 RESTRICT 外键）与并发窗口 IntegrityError→400 兜底（customer 先例同构）， docstring 与两个 api 层过时注释同步更新 - 产品 schema 复用 schemas/business._check_amount：sale_price 走 (PRICE_MAX, scale=4)、stock_quantity 走 AMOUNT_MAX——此前私写 _parse_non_negative 不查小数位与容量，5 位小数被 Numeric(14,4) 静默截断（舍入即算错钱）；新增 6 个秒级 schema 单测锁定口径 - 全局注册 IntegrityError handler：漏补引用保护的删除类操作收敛为 400 通用文案（e2e 撞见一个补一个的模式无法保证全覆盖），完整 异常记日志；rating/customer 的「非 1062 按 500」注释同步更正 Co-Authored-By: Claude Code <noreply@anthropic.com>
136 行
4.6 KiB
Python
136 行
4.6 KiB
Python
"""产品主数据数据访问。
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本层只 flush 不 commit —— 事务边界由 services 层控制。
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"""
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from sqlalchemy import Select, func, or_, select
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from sqlalchemy.orm import Session
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from app.models import BusinessItem, Product, ShipmentItem
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# ==================== 读取 ====================
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def get_by_id(session: Session, product_id: int, *, for_update: bool = False) -> Product | None:
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"""按主键查询。删除校验走 ``for_update`` 锁行（同 business_role_repository
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的理由：校验与删除之间若发生并发引用，锁行使并发写入可见地失败，
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而非引用被静默悬空）。"""
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if for_update:
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stmt = select(Product).where(Product.id == product_id).with_for_update()
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return session.execute(stmt).scalar_one_or_none()
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return session.get(Product, product_id)
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def get_by_name_spec(session: Session, product_name: str, spec_model: str) -> Product | None:
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"""按 (名称, 规格型号) 组合查询。
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组合是 uk_products_name_spec 唯一键的键值，先查用于给出即时业务提示；
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并发窗口仍存在，最终由 IntegrityError 兜底（见 product_service）。
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"""
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stmt = select(Product).where(
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Product.product_name == product_name,
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Product.spec_model == spec_model,
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)
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return session.execute(stmt).scalar_one_or_none()
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def list_products(
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session: Session,
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*,
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offset: int,
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limit: int,
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keyword: str | None = None,
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product_category: str | None = None,
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status: int | None = None,
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) -> list[Product]:
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"""分页查询产品（含停用）。按 id 升序，与 M1 岗位列表的次序口径一致。"""
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stmt = _apply_filters(
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select(Product),
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keyword=keyword,
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product_category=product_category,
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status=status,
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)
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stmt = stmt.order_by(Product.id).offset(offset).limit(limit)
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return list(session.execute(stmt).scalars())
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def count_products(
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session: Session,
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*,
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keyword: str | None = None,
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product_category: str | None = None,
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status: int | None = None,
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) -> int:
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"""统计符合条件的产品总数，供分页使用。"""
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stmt = _apply_filters(
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select(func.count(Product.id)),
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keyword=keyword,
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product_category=product_category,
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status=status,
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)
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return int(session.execute(stmt).scalar_one())
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def _apply_filters(
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stmt: Select,
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*,
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keyword: str | None,
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product_category: str | None,
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status: int | None,
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) -> Select:
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"""应用通用筛选条件。列表与计数共用，避免两处口径不一致。
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关键词对名称/规格两列取 OR 命中。转义与 query_utils.fuzzy 同一机制
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（``contains(autoescape=True)`` 转义 LIKE 通配符并附加 ESCAPE 子句）；
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因 fuzzy 是单列 where 语义（两次调用会叠加成 AND），双列 OR 在此直接
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写 contains —— M1 business_role_repository 的双列关键词同款写法。
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规格型号常含 ``_``（如 DN300_II），不转义会当单字符通配执行。
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"""
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if keyword:
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stmt = stmt.where(
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or_(
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Product.product_name.contains(keyword, autoescape=True),
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Product.spec_model.contains(keyword, autoescape=True),
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)
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)
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if product_category:
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stmt = stmt.where(Product.product_category == product_category)
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if status is not None:
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stmt = stmt.where(Product.status == status)
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return stmt
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def count_refs(session: Session, product_id: int) -> int:
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"""统计引用该产品的业务明细与发货明细行数（删除保护，business_id 先例）。
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两张明细表对 products 均 RESTRICT 外键：先查给出可读的 400；校验与
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删除之间的并发引用由锁行 + FK 兜底（service 层再翻译 IntegrityError）。
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"""
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stmt = select(
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select(func.count())
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.select_from(BusinessItem)
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.where(BusinessItem.product_id == product_id)
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.scalar_subquery()
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+ select(func.count())
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.select_from(ShipmentItem)
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.where(ShipmentItem.product_id == product_id)
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.scalar_subquery()
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)
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return int(session.execute(stmt).scalar_one())
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# ==================== 写入 ====================
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def create(session: Session, product: Product) -> Product:
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"""新增产品。只 flush 以取得自增 id。"""
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session.add(product)
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session.flush()
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return product
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def delete(session: Session, product: Product) -> None:
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"""物理删除产品。调用方须先完成引用保护校验（count_refs + FK 兜底）。"""
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session.delete(product)
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session.flush()
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