geo/backend/app/models/trend_insight.py

55 lines
2.1 KiB
Python

import uuid
from datetime import datetime
from sqlalchemy import String, Integer, Float, ForeignKey, Index, func, Text
from sqlalchemy import Uuid, JSON
from sqlalchemy.orm import Mapped, mapped_column
from app.database import Base
class TrendInsight(Base):
__tablename__ = "trend_insights"
id: Mapped[uuid.UUID] = mapped_column(
Uuid(as_uuid=True),
primary_key=True,
default=uuid.uuid4,
)
brand_id: Mapped[str] = mapped_column(
String(36),
ForeignKey("brands.id", ondelete="CASCADE"),
nullable=False,
)
trend_type: Mapped[str] = mapped_column(String(20), nullable=False)
keyword: Mapped[str | None] = mapped_column(String(200), nullable=True)
platform: Mapped[str | None] = mapped_column(String(50), nullable=True)
period_start: Mapped[datetime] = mapped_column(nullable=False)
period_end: Mapped[datetime] = mapped_column(nullable=False)
data_points: Mapped[list | None] = mapped_column(JSON, nullable=True)
change_rate: Mapped[float | None] = mapped_column(Float, nullable=True)
absolute_change: Mapped[int | None] = mapped_column(Integer, nullable=True)
sentiment_trend: Mapped[dict | None] = mapped_column(JSON, nullable=True)
cause_analysis: Mapped[str | None] = mapped_column(Text, nullable=True)
recommendations: Mapped[list | None] = mapped_column(JSON, nullable=True)
confidence: Mapped[float] = mapped_column(Float, nullable=False, default=0.5)
severity: Mapped[str] = mapped_column(
String(20), nullable=False, server_default="info",
)
created_at: Mapped[datetime] = mapped_column(
server_default=func.now(),
nullable=False,
)
updated_at: Mapped[datetime] = mapped_column(
server_default=func.now(),
onupdate=func.now(),
nullable=False,
)
__table_args__ = (
Index("idx_trend_insights_brand_id", "brand_id"),
Index("idx_trend_insights_trend_type", "trend_type"),
Index("idx_trend_insights_created_at", "created_at"),
Index("idx_trend_insights_period_start", "period_start"),
)