Improve backend
This commit is contained in:
Urtzi Alfaro
@@ -14,6 +14,8 @@ AuditLog = create_audit_log_model(Base)
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# Import all models to register them with the Base metadata
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from .forecasts import Forecast, PredictionBatch
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from .predictions import ModelPerformanceMetric, PredictionCache
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from .validation_run import ValidationRun
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from .sales_data_update import SalesDataUpdate
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# List all models for easier access
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__all__ = [
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@@ -21,5 +23,7 @@ __all__ = [
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"PredictionBatch",
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"ModelPerformanceMetric",
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"PredictionCache",
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"ValidationRun",
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"SalesDataUpdate",
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"AuditLog",
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]
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78
services/forecasting/app/models/sales_data_update.py
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78
services/forecasting/app/models/sales_data_update.py
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@@ -0,0 +1,78 @@
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# ================================================================
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# services/forecasting/app/models/sales_data_update.py
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# ================================================================
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"""
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Sales Data Update Tracking Model
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Tracks when sales data is added or updated for past dates,
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enabling automated historical validation backfill.
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"""
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from sqlalchemy import Column, String, Integer, DateTime, Boolean, Index, Date
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from sqlalchemy.dialects.postgresql import UUID
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from datetime import datetime, timezone
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import uuid
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from shared.database.base import Base
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class SalesDataUpdate(Base):
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"""Track sales data updates for historical validation"""
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__tablename__ = "sales_data_updates"
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__table_args__ = (
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Index('ix_sales_updates_tenant_status', 'tenant_id', 'validation_status', 'created_at'),
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Index('ix_sales_updates_date_range', 'tenant_id', 'update_date_start', 'update_date_end'),
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Index('ix_sales_updates_validation_status', 'validation_status'),
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)
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id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
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tenant_id = Column(UUID(as_uuid=True), nullable=False, index=True)
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# Date range of sales data that was added/updated
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update_date_start = Column(Date, nullable=False, index=True)
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update_date_end = Column(Date, nullable=False, index=True)
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# Update metadata
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created_at = Column(DateTime(timezone=True), default=lambda: datetime.now(timezone.utc))
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update_source = Column(String(100), nullable=True) # import, manual, pos_sync
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records_affected = Column(Integer, default=0)
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# Validation tracking
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validation_status = Column(String(50), default="pending") # pending, processing, completed, failed
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validation_run_id = Column(UUID(as_uuid=True), nullable=True)
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validated_at = Column(DateTime(timezone=True), nullable=True)
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validation_error = Column(String(500), nullable=True)
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# Determines if this update should trigger validation
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requires_validation = Column(Boolean, default=True)
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# Additional context
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import_job_id = Column(String(255), nullable=True) # Link to sales import job if applicable
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notes = Column(String(500), nullable=True)
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def __repr__(self):
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return (
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f"<SalesDataUpdate(id={self.id}, tenant_id={self.tenant_id}, "
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f"date_range={self.update_date_start} to {self.update_date_end}, "
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f"status={self.validation_status})>"
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)
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def to_dict(self):
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"""Convert to dictionary for API responses"""
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return {
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'id': str(self.id),
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'tenant_id': str(self.tenant_id),
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'update_date_start': self.update_date_start.isoformat() if self.update_date_start else None,
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'update_date_end': self.update_date_end.isoformat() if self.update_date_end else None,
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'created_at': self.created_at.isoformat() if self.created_at else None,
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'update_source': self.update_source,
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'records_affected': self.records_affected,
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'validation_status': self.validation_status,
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'validation_run_id': str(self.validation_run_id) if self.validation_run_id else None,
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'validated_at': self.validated_at.isoformat() if self.validated_at else None,
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'validation_error': self.validation_error,
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'requires_validation': self.requires_validation,
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'import_job_id': self.import_job_id,
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'notes': self.notes
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}
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110
services/forecasting/app/models/validation_run.py
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110
services/forecasting/app/models/validation_run.py
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@@ -0,0 +1,110 @@
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# ================================================================
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# services/forecasting/app/models/validation_run.py
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# ================================================================
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"""
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Validation run models for tracking forecast validation executions
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"""
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from sqlalchemy import Column, String, Integer, Float, DateTime, Text, JSON, Index
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from sqlalchemy.dialects.postgresql import UUID
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from datetime import datetime, timezone
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import uuid
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from shared.database.base import Base
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class ValidationRun(Base):
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"""Track forecast validation execution runs"""
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__tablename__ = "validation_runs"
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__table_args__ = (
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Index('ix_validation_runs_tenant_created', 'tenant_id', 'started_at'),
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Index('ix_validation_runs_status', 'status', 'started_at'),
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Index('ix_validation_runs_orchestration', 'orchestration_run_id'),
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)
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id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
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tenant_id = Column(UUID(as_uuid=True), nullable=False, index=True)
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# Link to orchestration run (if triggered by orchestrator)
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orchestration_run_id = Column(UUID(as_uuid=True), nullable=True)
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# Validation period
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validation_start_date = Column(DateTime(timezone=True), nullable=False)
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validation_end_date = Column(DateTime(timezone=True), nullable=False)
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# Execution metadata
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started_at = Column(DateTime(timezone=True), default=lambda: datetime.now(timezone.utc))
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completed_at = Column(DateTime(timezone=True), nullable=True)
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duration_seconds = Column(Float, nullable=True)
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# Status and results
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status = Column(String(50), default="pending") # pending, running, completed, failed
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# Validation statistics
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total_forecasts_evaluated = Column(Integer, default=0)
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forecasts_with_actuals = Column(Integer, default=0)
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forecasts_without_actuals = Column(Integer, default=0)
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# Accuracy metrics summary (across all validated forecasts)
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overall_mae = Column(Float, nullable=True)
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overall_mape = Column(Float, nullable=True)
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overall_rmse = Column(Float, nullable=True)
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overall_r2_score = Column(Float, nullable=True)
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overall_accuracy_percentage = Column(Float, nullable=True)
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# Additional statistics
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total_predicted_demand = Column(Float, default=0.0)
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total_actual_demand = Column(Float, default=0.0)
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# Breakdown by product/location (JSON)
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metrics_by_product = Column(JSON, nullable=True) # {product_id: {mae, mape, ...}}
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metrics_by_location = Column(JSON, nullable=True) # {location: {mae, mape, ...}}
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# Performance metrics created count
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metrics_records_created = Column(Integer, default=0)
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# Error tracking
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error_message = Column(Text, nullable=True)
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error_details = Column(JSON, nullable=True)
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# Execution context
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triggered_by = Column(String(100), default="manual") # manual, orchestrator, scheduled
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execution_mode = Column(String(50), default="batch") # batch, single_day, real_time
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def __repr__(self):
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return (
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f"<ValidationRun(id={self.id}, tenant_id={self.tenant_id}, "
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f"status={self.status}, forecasts_evaluated={self.total_forecasts_evaluated})>"
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)
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def to_dict(self):
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"""Convert to dictionary for API responses"""
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return {
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'id': str(self.id),
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'tenant_id': str(self.tenant_id),
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'orchestration_run_id': str(self.orchestration_run_id) if self.orchestration_run_id else None,
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'validation_start_date': self.validation_start_date.isoformat() if self.validation_start_date else None,
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'validation_end_date': self.validation_end_date.isoformat() if self.validation_end_date else None,
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'started_at': self.started_at.isoformat() if self.started_at else None,
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'completed_at': self.completed_at.isoformat() if self.completed_at else None,
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'duration_seconds': self.duration_seconds,
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'status': self.status,
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'total_forecasts_evaluated': self.total_forecasts_evaluated,
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'forecasts_with_actuals': self.forecasts_with_actuals,
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'forecasts_without_actuals': self.forecasts_without_actuals,
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'overall_mae': self.overall_mae,
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'overall_mape': self.overall_mape,
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'overall_rmse': self.overall_rmse,
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'overall_r2_score': self.overall_r2_score,
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'overall_accuracy_percentage': self.overall_accuracy_percentage,
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'total_predicted_demand': self.total_predicted_demand,
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'total_actual_demand': self.total_actual_demand,
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'metrics_by_product': self.metrics_by_product,
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'metrics_by_location': self.metrics_by_location,
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'metrics_records_created': self.metrics_records_created,
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'error_message': self.error_message,
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'error_details': self.error_details,
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'triggered_by': self.triggered_by,
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'execution_mode': self.execution_mode,
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}
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