"""Unified market schema for prediction market data."""
from datetime import datetime
from pydantic import BaseModel, Field, computed_field, field_validator
class Outcome(BaseModel):
"""A possible outcome in a multi-outcome market."""
name: str
probability: float = Field(ge=0.0, le=1.0)
class PricePoint(BaseModel):
"""A historical price point for tracking."""
timestamp: datetime
probability: float = Field(ge=0.0, le=1.0)
class Market(BaseModel):
"""Unified market representation across all platforms."""
# Identity
platform: str
native_id: str
url: str
# Content
title: str
description: str
category: str
# Pricing
probability: float = Field(ge=0.0, le=1.0)
outcomes: list[Outcome] = Field(default_factory=list)
# Metadata
volume: float | None = None
liquidity: float | None = None
created_at: datetime
closes_at: datetime | None = None
resolved: bool = False
resolution: str | None = None
# Tracking
last_fetched: datetime
price_history: list[PricePoint] = Field(default_factory=list)
@computed_field
@property
def id(self) -> str:
"""Unique ID across platforms: platform:native_id."""
return f"{self.platform}:{self.native_id}"
@field_validator("probability")
@classmethod
def validate_probability(cls, v: float) -> float:
if not 0.0 <= v <= 1.0:
raise ValueError("Probability must be between 0 and 1")
return v
