Files
bakery-ia/services/forecasting/app/models/validation_run.py
2025-11-18 07:17:17 +01:00

111 lines
4.8 KiB
Python

# ================================================================
# services/forecasting/app/models/validation_run.py
# ================================================================
"""
Validation run models for tracking forecast validation executions
"""
from sqlalchemy import Column, String, Integer, Float, DateTime, Text, JSON, Index
from sqlalchemy.dialects.postgresql import UUID
from datetime import datetime, timezone
import uuid
from shared.database.base import Base
class ValidationRun(Base):
"""Track forecast validation execution runs"""
__tablename__ = "validation_runs"
__table_args__ = (
Index('ix_validation_runs_tenant_created', 'tenant_id', 'started_at'),
Index('ix_validation_runs_status', 'status', 'started_at'),
Index('ix_validation_runs_orchestration', 'orchestration_run_id'),
)
id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
tenant_id = Column(UUID(as_uuid=True), nullable=False, index=True)
# Link to orchestration run (if triggered by orchestrator)
orchestration_run_id = Column(UUID(as_uuid=True), nullable=True)
# Validation period
validation_start_date = Column(DateTime(timezone=True), nullable=False)
validation_end_date = Column(DateTime(timezone=True), nullable=False)
# Execution metadata
started_at = Column(DateTime(timezone=True), default=lambda: datetime.now(timezone.utc))
completed_at = Column(DateTime(timezone=True), nullable=True)
duration_seconds = Column(Float, nullable=True)
# Status and results
status = Column(String(50), default="pending") # pending, running, completed, failed
# Validation statistics
total_forecasts_evaluated = Column(Integer, default=0)
forecasts_with_actuals = Column(Integer, default=0)
forecasts_without_actuals = Column(Integer, default=0)
# Accuracy metrics summary (across all validated forecasts)
overall_mae = Column(Float, nullable=True)
overall_mape = Column(Float, nullable=True)
overall_rmse = Column(Float, nullable=True)
overall_r2_score = Column(Float, nullable=True)
overall_accuracy_percentage = Column(Float, nullable=True)
# Additional statistics
total_predicted_demand = Column(Float, default=0.0)
total_actual_demand = Column(Float, default=0.0)
# Breakdown by product/location (JSON)
metrics_by_product = Column(JSON, nullable=True) # {product_id: {mae, mape, ...}}
metrics_by_location = Column(JSON, nullable=True) # {location: {mae, mape, ...}}
# Performance metrics created count
metrics_records_created = Column(Integer, default=0)
# Error tracking
error_message = Column(Text, nullable=True)
error_details = Column(JSON, nullable=True)
# Execution context
triggered_by = Column(String(100), default="manual") # manual, orchestrator, scheduled
execution_mode = Column(String(50), default="batch") # batch, single_day, real_time
def __repr__(self):
return (
f"<ValidationRun(id={self.id}, tenant_id={self.tenant_id}, "
f"status={self.status}, forecasts_evaluated={self.total_forecasts_evaluated})>"
)
def to_dict(self):
"""Convert to dictionary for API responses"""
return {
'id': str(self.id),
'tenant_id': str(self.tenant_id),
'orchestration_run_id': str(self.orchestration_run_id) if self.orchestration_run_id else None,
'validation_start_date': self.validation_start_date.isoformat() if self.validation_start_date else None,
'validation_end_date': self.validation_end_date.isoformat() if self.validation_end_date else None,
'started_at': self.started_at.isoformat() if self.started_at else None,
'completed_at': self.completed_at.isoformat() if self.completed_at else None,
'duration_seconds': self.duration_seconds,
'status': self.status,
'total_forecasts_evaluated': self.total_forecasts_evaluated,
'forecasts_with_actuals': self.forecasts_with_actuals,
'forecasts_without_actuals': self.forecasts_without_actuals,
'overall_mae': self.overall_mae,
'overall_mape': self.overall_mape,
'overall_rmse': self.overall_rmse,
'overall_r2_score': self.overall_r2_score,
'overall_accuracy_percentage': self.overall_accuracy_percentage,
'total_predicted_demand': self.total_predicted_demand,
'total_actual_demand': self.total_actual_demand,
'metrics_by_product': self.metrics_by_product,
'metrics_by_location': self.metrics_by_location,
'metrics_records_created': self.metrics_records_created,
'error_message': self.error_message,
'error_details': self.error_details,
'triggered_by': self.triggered_by,
'execution_mode': self.execution_mode,
}