64 lines
2.7 KiB
Python
64 lines
2.7 KiB
Python
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# =============================================================================
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# 企微IT智能服务台 — 会议室预定快照模型（P2统计用）
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# =============================================================================
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# 说明：每日定时拉取预定记录存入本地数据库，作为统计快照（非实时数据源）
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# 实时预定状态仍以企微API为唯一数据源，此表仅用于P2统计分析
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# =============================================================================
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from datetime import date, datetime
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from sqlalchemy import Date, DateTime, Integer, String, func
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from sqlalchemy.orm import Mapped, mapped_column
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from app.database import Base
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class MeetingroomBookingSnapshot(Base):
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"""会议室预定记录快照模型（P2统计用）。
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每日定时拉取企微预定记录，存入本地作为统计快照。
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非实时数据源 — 实时预定状态仍以企微API为准。
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Attributes:
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id: 自增主键
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meetingroom_id: 企微会议室ID
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booking_id: 企微预定ID
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subject: 会议主题
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booker: 预定人userid
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start_time: 会议开始时间
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end_time: 会议结束时间
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status: 预定状态（0=已预定, 1=已取消）
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snapshot_date: 快照日期
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created_at: 记录创建时间
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"""
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__tablename__ = "meetingroom_booking_snapshot"
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# 自增主键
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id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
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# 企微会议室ID
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meetingroom_id: Mapped[int] = mapped_column(Integer, index=True, nullable=False)
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# 企微预定ID
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booking_id: Mapped[str] = mapped_column(String(64), index=True, nullable=False)
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# 会议主题
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subject: Mapped[str] = mapped_column(String(200), nullable=False, default="")
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# 预定人userid
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booker: Mapped[str] = mapped_column(String(64), nullable=False, default="")
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# 会议开始时间
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start_time: Mapped[datetime] = mapped_column(DateTime, nullable=False)
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# 会议结束时间
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end_time: Mapped[datetime] = mapped_column(DateTime, nullable=False)
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# 预定状态（0=已预定, 1=已取消）
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status: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
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# 快照日期（用于按日期统计）
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snapshot_date: Mapped[date] = mapped_column(Date, index=True, nullable=False)
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# 记录创建时间
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created_at: Mapped[datetime] = mapped_column(DateTime, server_default=func.now(), nullable=False)
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def __repr__(self) -> str:
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"""返回模型的可读字符串表示。"""
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return (
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f"<MeetingroomBookingSnapshot(id={self.id}, meetingroom_id={self.meetingroom_id}, "
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f"booking_id='{self.booking_id}', subject='{self.subject}', snapshot_date={self.snapshot_date})>"
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)
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