Files
evotraders/backend/data/schema.py
cillin 12de93aa30 feat: initial commit - EvoTraders project
量化交易多智能体系统,包含:
- 分析师、投资组合经理、风险经理等智能体
- 股票分析、投资组合管理、风险控制工具
- React 前端界面
- FastAPI 后端服务

Co-Authored-By: Claude <noreply@anthropic.com>
2026-03-13 04:34:06 +08:00

185 lines
4.8 KiB
Python

# -*- coding: utf-8 -*-
from pydantic import BaseModel
class Price(BaseModel):
open: float
close: float
high: float
low: float
volume: int
time: str
class PriceResponse(BaseModel):
ticker: str
prices: list[Price]
class FinancialMetrics(BaseModel):
ticker: str
report_period: str
period: str
currency: str
market_cap: float | None
enterprise_value: float | None
price_to_earnings_ratio: float | None
price_to_book_ratio: float | None
price_to_sales_ratio: float | None
enterprise_value_to_ebitda_ratio: float | None
enterprise_value_to_revenue_ratio: float | None
free_cash_flow_yield: float | None
peg_ratio: float | None
gross_margin: float | None
operating_margin: float | None
net_margin: float | None
return_on_equity: float | None
return_on_assets: float | None
return_on_invested_capital: float | None
asset_turnover: float | None
inventory_turnover: float | None
receivables_turnover: float | None
days_sales_outstanding: float | None
operating_cycle: float | None
working_capital_turnover: float | None
current_ratio: float | None
quick_ratio: float | None
cash_ratio: float | None
operating_cash_flow_ratio: float | None
debt_to_equity: float | None
debt_to_assets: float | None
interest_coverage: float | None
revenue_growth: float | None
earnings_growth: float | None
book_value_growth: float | None
earnings_per_share_growth: float | None
free_cash_flow_growth: float | None
operating_income_growth: float | None
ebitda_growth: float | None
payout_ratio: float | None
earnings_per_share: float | None
book_value_per_share: float | None
free_cash_flow_per_share: float | None
class FinancialMetricsResponse(BaseModel):
financial_metrics: list[FinancialMetrics]
class LineItem(BaseModel):
ticker: str
report_period: str
period: str
currency: str
# Allow additional fields dynamically
model_config = {"extra": "allow"}
class LineItemResponse(BaseModel):
search_results: list[LineItem]
class InsiderTrade(BaseModel):
ticker: str
issuer: str | None
name: str | None
title: str | None
is_board_director: bool | None
transaction_date: str | None
transaction_shares: float | None
transaction_price_per_share: float | None
transaction_value: float | None
shares_owned_before_transaction: float | None
shares_owned_after_transaction: float | None
security_title: str | None
filing_date: str
class InsiderTradeResponse(BaseModel):
insider_trades: list[InsiderTrade]
class CompanyNews(BaseModel):
category: str | None = None
ticker: str
title: str
related: str | None = None
source: str
date: str | None = None
url: str
summary: str | None = None
class CompanyNewsResponse(BaseModel):
news: list[CompanyNews]
class CompanyFacts(BaseModel):
ticker: str
name: str
cik: str | None = None
industry: str | None = None
sector: str | None = None
category: str | None = None
exchange: str | None = None
is_active: bool | None = None
listing_date: str | None = None
location: str | None = None
market_cap: float | None = None
number_of_employees: int | None = None
sec_filings_url: str | None = None
sic_code: str | None = None
sic_industry: str | None = None
sic_sector: str | None = None
website_url: str | None = None
weighted_average_shares: int | None = None
class CompanyFactsResponse(BaseModel):
company_facts: CompanyFacts
class Position(BaseModel):
"""Position information - for Portfolio mode"""
long: int = 0 # Long position quantity (shares)
short: int = 0 # Short position quantity (shares)
long_cost_basis: float = 0.0 # Long position average cost
short_cost_basis: float = 0.0 # Short position average cost
class Portfolio(BaseModel):
"""Portfolio - for Portfolio mode"""
cash: float = 100000.0 # Available cash
positions: dict[str, Position] = {} # ticker -> Position mapping
# Margin requirement (0.0 means shorting disabled, 0.5 means 50% margin)
margin_requirement: float = 0.0
margin_used: float = 0.0 # Margin used
class AnalystSignal(BaseModel):
signal: str | None = None
confidence: float | None = None
reasoning: dict | str | None = None
max_position_size: float | None = None # For risk management signals
class TickerAnalysis(BaseModel):
ticker: str
analyst_signals: dict[str, AnalystSignal] # agent_name -> signal mapping
class AgentStateData(BaseModel):
tickers: list[str]
portfolio: Portfolio
start_date: str
end_date: str
ticker_analyses: dict[str, TickerAnalysis] # ticker -> analysis mapping
class AgentStateMetadata(BaseModel):
show_reasoning: bool = False
model_config = {"extra": "allow"}