ouzhou
da7ce69494
- 新增 POST /api/v1/ad/ecpm-report:激励视频展示后客户端上报本次 eCPM,落 ad_ecpm_record 做内部收益统计(model/repository/schema/alembic 迁移 + 接口文档) - 看广告冷却策略抽到 app/core/ad_cooldown.py 纯函数;ad_reward.today_status 只取数据,换策略只改这一处 - savings.dishes 改 JSON().with_variant(JSONB,"postgresql"):SQLite 无 visit_JSONB 会让 create_all 编译崩,修复后测试套件恢复 Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> --------- Co-authored-by: OuYingJun1024 <1034284404@qq.com> Reviewed-on: #8 Co-authored-by: ouzhou <ouzhou@wonderable.ai> Co-committed-by: ouzhou <ouzhou@wonderable.ai>
102 lines
5.0 KiB
Python
102 lines
5.0 KiB
Python
"""比价记录表。
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每完成一次比价(外卖/电商/领券),客户端在 done 帧后用带 JWT 的通道上报一条,落这里。
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是未来「我的比价记录」页的数据源,也沉淀用户级行为画像(哪个用户在哪两家之间比了什么)。
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与 savings_record 的区别:savings_record 是「省了多少钱」的视角(只有省到才有意义,当前由
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demo seeder 灌),本表是「每一次比价的完整明细」——不省钱、甚至失败的比价也照记一条。
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两表独立,互不影响。
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「越详细越好」的落地:结构化列给查询/排序/聚合用,raw_payload(JSONB)把客户端上报的
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原始 calibration + done.params 原样存一份,未来前端要展示什么都能拿到、不丢信息。
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"""
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from __future__ import annotations
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from datetime import datetime
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from sqlalchemy import (
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JSON,
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Boolean,
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DateTime,
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ForeignKey,
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Integer,
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String,
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UniqueConstraint,
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func,
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)
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from sqlalchemy.dialects.postgresql import JSONB
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from sqlalchemy.orm import Mapped, mapped_column
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from app.db.base import Base
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# PG 上用 JSONB(可建 GIN 索引),SQLite(本地/测试)退化为通用 JSON——
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# 否则 SQLite 无 JSONB,Base.metadata.create_all 编译报错(同 savings_record.dishes)。
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_JSON = JSON().with_variant(JSONB(), "postgresql")
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class ComparisonRecord(Base):
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__tablename__ = "comparison_record"
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__table_args__ = (
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# 同一用户同一次比价(trace_id)只存一条:客户端重试/误点重复上报时幂等覆盖。
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UniqueConstraint("user_id", "trace_id", name="uq_comparison_user_trace"),
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)
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id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
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user_id: Mapped[int] = mapped_column(
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Integer, ForeignKey("user.id"), index=True, nullable=False
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)
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# 仍记录设备号(同一用户多设备的行为区分 / 与不鉴权期 device_id 数据对账)
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device_id: Mapped[str | None] = mapped_column(String(64), nullable=True)
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# 业务类型:food(外卖,当前唯一接通)/ ecom(电商)/ coupon(领券)。预留扩展。
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business_type: Mapped[str] = mapped_column(
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String(16), nullable=False, default="food", index=True
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)
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# pricebot 侧 trace_id:关联调试落盘 + 幂等去重键
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trace_id: Mapped[str] = mapped_column(String(64), nullable=False)
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# ===== 源平台(发起比价的那家)=====
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source_platform_id: Mapped[str | None] = mapped_column(String(32), nullable=True)
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source_platform_name: Mapped[str | None] = mapped_column(String(32), nullable=True)
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source_package: Mapped[str | None] = mapped_column(String(128), nullable=True)
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source_price_cents: Mapped[int | None] = mapped_column(Integer, nullable=True)
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# ===== 最优结果(全平台最便宜的一家,= comparison_results 里 rank=1)=====
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best_platform_id: Mapped[str | None] = mapped_column(String(32), nullable=True)
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best_platform_name: Mapped[str | None] = mapped_column(String(32), nullable=True)
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best_price_cents: Mapped[int | None] = mapped_column(Integer, nullable=True)
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# 源价 - 最优价(可为 0 / 负:源平台本来就最便宜时没省到)
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saved_amount_cents: Mapped[int | None] = mapped_column(Integer, nullable=True)
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# 源平台就是最便宜的一家(= 这次没省到钱)
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is_source_best: Mapped[bool | None] = mapped_column(Boolean, nullable=True)
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# ===== 订单概要 =====
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store_name: Mapped[str | None] = mapped_column(String(128), nullable=True)
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total_dish_count: Mapped[int | None] = mapped_column(Integer, nullable=True)
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skipped_dish_count: Mapped[int | None] = mapped_column(Integer, nullable=True)
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# success(拿到有效对比)/ failed(出错或没采到目标价)
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status: Mapped[str] = mapped_column(String(16), nullable=False, default="success")
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# done 帧 information 文案。成功:"在美团找到同店,到手价 ¥X…";
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# 失败:具体原因(如"美团、京东外卖均未找到该商品")。前端在比价失败时当原因展示。
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information: Mapped[str | None] = mapped_column(String(256), nullable=True)
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# ===== 明细(JSON,越详细越好)=====
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# 下单菜品 [{name, qty, specs?}]
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items: Mapped[list] = mapped_column(_JSON, nullable=False, default=list)
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# 逐平台对比 [{platform_id, platform_name, package, price, is_source, rank}](price 单位:元,原样存)
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comparison_results: Mapped[list] = mapped_column(_JSON, nullable=False, default=list)
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# 目标平台未找到、跳过的菜名
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skipped_dish_names: Mapped[list] = mapped_column(_JSON, nullable=False, default=list)
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# 客户端上报的原始 payload(calibration + done.params 全量),未来取数兜底
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raw_payload: Mapped[dict | None] = mapped_column(_JSON, nullable=True)
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created_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True), server_default=func.now(), index=True, nullable=False
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)
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def __repr__(self) -> str: # pragma: no cover
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return (
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f"<ComparisonRecord id={self.id} user_id={self.user_id} "
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f"trace_id={self.trace_id} status={self.status}>"
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)
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