kx_guo
1d58bb8913
- 统一供应商异常统计为近3年数据口径 - 以近3年异常记录数作为合作频次代理值并明确提示 - 实现 A/B 缺陷占比与 S/A/B/C 层级判定 - 按供应商层级输出正常合作、加强巡检、驻厂及备选供应商等管理建议 - 完善风险卡片和供应商卡片的频次、层级、建议展示 - 补充供应商画像接口、测试和历史会话卡片兼容处理
75 lines
1.7 KiB
Python
75 lines
1.7 KiB
Python
"""Dashboard aggregation response contracts."""
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from typing import Literal
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from pydantic import Field
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from app.schemas.common import ApiSchema
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class DashboardMetric(ApiSchema):
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value: int | float | None = None
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label: str
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change_percent: float | None = None
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class DashboardStage(ApiSchema):
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name: str
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count: int
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share: float
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risk_level: str
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class DashboardCategory(ApiSchema):
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name: str
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count: int
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share: float
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risk_level: str
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top_material: str | None = None
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class DashboardMatrixRow(ApiSchema):
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name: str
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party_type: str
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categories: dict[str, int]
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cooperation_total: int | None
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anomaly_count: int
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anomaly_rate: float | None
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tier: str
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class DashboardDefect(ApiSchema):
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level: str
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label: str
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count: int
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share: float
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class DashboardSupplierRank(ApiSchema):
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name: str
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party_type: str
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count: int
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tier: str
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top_problem: str | None = None
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class DashboardTrendPoint(ApiSchema):
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month: str
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label: str
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count: int
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class DashboardData(ApiSchema):
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year: Literal["all", "2024", "2025", "2026"]
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total_cases: int
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metrics: list[DashboardMetric] = Field(default_factory=list)
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stages: list[DashboardStage] = Field(default_factory=list)
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categories: list[DashboardCategory] = Field(default_factory=list)
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matrix_categories: list[str] = Field(default_factory=list)
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matrix: list[DashboardMatrixRow] = Field(default_factory=list)
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defects: list[DashboardDefect] = Field(default_factory=list)
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supplier_ranking: list[DashboardSupplierRank] = Field(default_factory=list)
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trend: list[DashboardTrendPoint] = Field(default_factory=list)
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insight: str
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warnings: list[str] = Field(default_factory=list)
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