99 lines
2.1 KiB
Python
99 lines
2.1 KiB
Python
from __future__ import annotations
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from typing import Literal
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from pydantic import BaseModel, Field
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Sentiment = Literal["看多", "看空", "中性"]
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class Account(BaseModel):
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id: str
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name: str
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description: str
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class DailyInputAccountPayload(BaseModel):
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account_id: str
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links: list[str] = Field(default_factory=list)
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class DailyInputUpsertPayload(BaseModel):
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accounts: list[DailyInputAccountPayload] = Field(default_factory=list)
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class DailyInputAccount(BaseModel):
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account_id: str
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account_name: str
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links: list[str] = Field(default_factory=list)
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class DailyInputDocument(BaseModel):
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date: str
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updated_at: str
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accounts: list[DailyInputAccount] = Field(default_factory=list)
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class OpinionArticle(BaseModel):
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id: str
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account_id: str
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account_name: str
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title: str
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published_at: str
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summary: str
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source_url: str
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sectors: list[str] = Field(default_factory=list)
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sentiment: Sentiment
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article_type: str
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class ReportDocument(BaseModel):
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date: str
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generated_at: str
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summary: str
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focus_sectors: list[str] = Field(default_factory=list)
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article_count: int
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account_count: int
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articles: list[OpinionArticle] = Field(default_factory=list)
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class ReportListItem(BaseModel):
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date: str
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generated_at: str
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summary: str
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article_count: int
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focus_sectors: list[str] = Field(default_factory=list)
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class ClsNewsItem(BaseModel):
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id: str
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title: str
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published_at: str
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source: str
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summary: str
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reference_url: str
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sectors: list[str] = Field(default_factory=list)
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sentiment: Sentiment
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class ClsNewsSummary(BaseModel):
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overview: str
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hot_topics: str
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watch_list: list[str] = Field(default_factory=list)
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class ClsSectorImpact(BaseModel):
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sector: str
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sentiment: Sentiment
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reason: str
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related_titles: list[str] = Field(default_factory=list)
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class ClsNewsDocument(BaseModel):
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date: str
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updated_at: str
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window_label: str
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summary: ClsNewsSummary
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sector_impacts: list[ClsSectorImpact] = Field(default_factory=list)
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items: list[ClsNewsItem] = Field(default_factory=list)
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