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DriverEffortModel database model.
Stores per-driver XGBoost models for personalized effort prediction.
"""
import uuid
from datetime import datetime
from typing import Optional
from sqlalchemy import Boolean, Float, Integer, DateTime, ForeignKey, LargeBinary, JSON
from sqlalchemy.orm import Mapped, mapped_column
from app.database import Base, GUID
class DriverEffortModel(Base):
"""
DriverEffortModel stores serialized XGBoost models per driver.
Each driver gets their own personalized effort prediction model.
"""
__tablename__ = "driver_effort_models"
driver_id: Mapped[uuid.UUID] = mapped_column(
GUID(),
ForeignKey("drivers.id", ondelete="CASCADE"),
primary_key=True,
)
model_version: Mapped[int] = mapped_column(
Integer,
default=1,
nullable=False,
)
# Serialized XGBoost model (pickle format)
model_pickle: Mapped[Optional[bytes]] = mapped_column(
LargeBinary,
nullable=True,
)
# Training metadata
training_samples: Mapped[int] = mapped_column(
Integer,
default=0,
)
feature_names: Mapped[Optional[dict]] = mapped_column(
JSON,
nullable=True,
)
# Performance tracking
mse_history: Mapped[Optional[dict]] = mapped_column(
JSON,
nullable=True,
default=list,
) # List of last 10 MSE values
current_mse: Mapped[Optional[float]] = mapped_column(
Float,
nullable=True,
)
r2_score: Mapped[Optional[float]] = mapped_column(
Float,
nullable=True,
)
# Model state
active: Mapped[bool] = mapped_column(
Boolean,
default=True,
index=True,
)
last_trained_at: Mapped[Optional[datetime]] = mapped_column(
DateTime,
nullable=True,
)
created_at: Mapped[datetime] = mapped_column(
DateTime,
default=datetime.utcnow,
nullable=False,
)
updated_at: Mapped[datetime] = mapped_column(
DateTime,
default=datetime.utcnow,
onupdate=datetime.utcnow,
nullable=False,
)
def __repr__(self) -> str:
return f"<DriverEffortModel(driver_id={self.driver_id}, v{self.model_version})>"
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