edfd51b0a7
- backend(financial): 新增 /china/{ts_code}/snapshot API，返回昨日交易日的收盘价/市值/PE/PB/股息率等
- backend(schemas): 新增 TodaySnapshotResponse
- backend(main): 注册 orgs 路由 /api/v1/orgs
- backend(providers:finnhub): 归一化财报字段并计算 gross_margin/net_margin/ROA/ROE
- backend(providers:tushare): 股东户数报告期与财报期对齐
- backend(routers/financial): years 默认改为 10（最大 10）
- config: analysis-config.json 切换到 qwen-flash-2025-07-28
- frontend(report/[symbol]): 新增“昨日快照”卡片、限制展示期数为10、优化增长与阈值高亮、修正类名与标题处理
- frontend(reports/[id]): 统一 period 变量与计算，修正表格 key
- frontend(hooks): 新增 useChinaSnapshot 钩子与类型
- scripts: dev.sh 增加调试输出
85 lines
1.9 KiB
Python
85 lines
1.9 KiB
Python
"""
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Pydantic schemas for financial APIs
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"""
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from typing import Dict, List, Optional
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from pydantic import BaseModel
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class PeriodDataPoint(BaseModel):
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period: str
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value: Optional[float]
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class StepRecord(BaseModel):
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name: str
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start_ts: str # ISO8601
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end_ts: Optional[str] = None
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duration_ms: Optional[int] = None
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status: str # running|done|error
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error: Optional[str] = None
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class FinancialMeta(BaseModel):
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started_at: str # ISO8601
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finished_at: Optional[str] = None
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elapsed_ms: Optional[int] = None
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api_calls_total: int = 0
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api_calls_by_group: Dict[str, int] = {}
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current_action: Optional[str] = None
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steps: List[StepRecord] = []
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class BatchFinancialDataResponse(BaseModel):
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ts_code: str
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name: Optional[str] = None
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series: Dict[str, List[PeriodDataPoint]]
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meta: Optional[FinancialMeta] = None
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class FinancialConfigResponse(BaseModel):
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api_groups: Dict[str, List[dict]]
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class TokenUsage(BaseModel):
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prompt_tokens: int = 0
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completion_tokens: int = 0
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total_tokens: int = 0
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class CompanyProfileResponse(BaseModel):
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ts_code: str
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company_name: Optional[str] = None
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content: str
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model: str
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tokens: TokenUsage
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elapsed_ms: int
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success: bool = True
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error: Optional[str] = None
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class AnalysisResponse(BaseModel):
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ts_code: str
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company_name: Optional[str] = None
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analysis_type: str
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content: str
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model: str
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tokens: TokenUsage
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elapsed_ms: int
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success: bool = True
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error: Optional[str] = None
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class AnalysisConfigResponse(BaseModel):
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analysis_modules: Dict[str, Dict]
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class TodaySnapshotResponse(BaseModel):
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ts_code: str
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trade_date: str
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name: Optional[str] = None
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close: Optional[float] = None
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pe: Optional[float] = None
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pb: Optional[float] = None
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dv_ratio: Optional[float] = None
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total_mv: Optional[float] = None
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