Improve backend

services/forecasting/app/models/validation_run.py

@@ -0,0 +1,110 @@
+# ================================================================
+# 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,
+        }