Fix DB issue 2s

2025-09-30 21:58:10 +02:00
parent 147893015e
commit 7cc4b957a5
77 changed files with 4385 additions and 1211 deletions
--- a/services/forecasting/Dockerfile
+++ b/services/forecasting/Dockerfile
@@ -1,3 +1,4 @@
+# Forecasting Dockerfile
 # Add this stage at the top of each service Dockerfile
 FROM python:3.11-slim AS shared
 WORKDIR /shared
@@ -32,6 +33,7 @@ COPY scripts/ /app/scripts/
 # Add shared libraries to Python path
 ENV PYTHONPATH="/app:/app/shared:${PYTHONPATH:-}"

+
 # Expose port
 EXPOSE 8000

@@ -40,4 +42,4 @@ HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
    CMD curl -f http://localhost:8000/health || exit 1

 # Run application
-CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]
--- a/services/forecasting/app/main.py
+++ b/services/forecasting/app/main.py
@@ -19,7 +19,7 @@ from shared.service_base import StandardFastAPIService
 class ForecastingService(StandardFastAPIService):
    """Forecasting Service with standardized setup"""

-    expected_migration_version = "001_initial_forecasting"
+    expected_migration_version = "00001"

    async def on_startup(self, app):
        """Custom startup logic including migration verification"""
--- a/services/forecasting/migrations/versions/00001_initial_schema.py
+++ b/services/forecasting/migrations/versions/00001_initial_schema.py
@@ -0,0 +1,160 @@
+"""Initial schema for forecasting service
+
+Revision ID: 000001
+Revises: 
+Create Date: 2025-09-30 18:00:00.00000
+
+"""
+from alembic import op
+import sqlalchemy as sa
+from sqlalchemy.dialects import postgresql
+
+# revision identifiers, used by Alembic.
+revision = '0001'
+down_revision = None
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    op.create_table('forecasts',
+        sa.Column('id', sa.UUID(), nullable=False),
+        sa.Column('tenant_id', sa.UUID(), nullable=False),
+        sa.Column('inventory_product_id', sa.UUID(), nullable=False),
+        sa.Column('product_name', sa.String(255), nullable=False),
+        sa.Column('location', sa.String(255), nullable=False),
+        sa.Column('forecast_date', sa.DateTime(timezone=True), nullable=False),
+        sa.Column('created_at', sa.DateTime(timezone=True), server_default=sa.text('timezone(\'utc\', now())'), nullable=True),
+        sa.Column('predicted_demand', sa.Float, nullable=False),
+        sa.Column('confidence_lower', sa.Float, nullable=False),
+        sa.Column('confidence_upper', sa.Float, nullable=False),
+        sa.Column('confidence_level', sa.Float, nullable=True),
+        sa.Column('model_id', sa.String(255), nullable=False),
+        sa.Column('model_version', sa.String(50), nullable=False),
+        sa.Column('algorithm', sa.String(50), nullable=True),
+        sa.Column('business_type', sa.String(50), nullable=True),
+        sa.Column('day_of_week', sa.Integer, nullable=False),
+        sa.Column('is_holiday', sa.Boolean, nullable=True),
+        sa.Column('is_weekend', sa.Boolean, nullable=True),
+        sa.Column('weather_temperature', sa.Float, nullable=True),
+        sa.Column('weather_precipitation', sa.Float, nullable=True),
+        sa.Column('weather_description', sa.String(100), nullable=True),
+        sa.Column('traffic_volume', sa.Integer, nullable=True),
+        sa.Column('processing_time_ms', sa.Integer, nullable=True),
+        sa.Column('features_used', postgresql.JSON(astext_type=sa.Text()), nullable=True),
+        sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_forecasts_tenant_id'), 'forecasts', ['tenant_id'], unique=False)
+    op.create_index(op.f('ix_forecasts_inventory_product_id'), 'forecasts', ['inventory_product_id'], unique=False)
+    op.create_index(op.f('ix_forecasts_product_name'), 'forecasts', ['product_name'], unique=False)
+    op.create_index(op.f('ix_forecasts_location'), 'forecasts', ['location'], unique=False)
+    op.create_index(op.f('ix_forecasts_forecast_date'), 'forecasts', ['forecast_date'], unique=False)
+    
+    op.create_table('predictions',
+        sa.Column('id', sa.UUID(), nullable=False),
+        sa.Column('tenant_id', sa.UUID(), nullable=False),
+        sa.Column('model_id', sa.String(100), nullable=False),
+        sa.Column('input_data', postgresql.JSON(astext_type=sa.Text()), nullable=False),
+        sa.Column('prediction_value', sa.Float(), nullable=False),
+        sa.Column('prediction_confidence', sa.Float(), nullable=True),
+        sa.Column('prediction_date', sa.DateTime(), nullable=False),
+        sa.Column('created_at', sa.DateTime(), server_default=sa.text('now()'), nullable=True),
+        sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_predictions_tenant_id'), 'predictions', ['tenant_id'], unique=False)
+    op.create_index(op.f('ix_predictions_model_id'), 'predictions', ['model_id'], unique=False)
+    op.create_index(op.f('ix_predictions_prediction_date'), 'predictions', ['prediction_date'], unique=False)
+    
+    # Create prediction_batches table
+    op.create_table('prediction_batches',
+        sa.Column('id', sa.UUID(), nullable=False),
+        sa.Column('tenant_id', sa.UUID(), nullable=False),
+        sa.Column('batch_name', sa.String(255), nullable=False),
+        sa.Column('requested_at', sa.DateTime(timezone=True), server_default=sa.text('timezone(\'utc\', now())'), nullable=True),
+        sa.Column('completed_at', sa.DateTime(timezone=True), nullable=True),
+        sa.Column('status', sa.String(50), nullable=True),
+        sa.Column('total_products', sa.Integer, nullable=True),
+        sa.Column('completed_products', sa.Integer, nullable=True),
+        sa.Column('failed_products', sa.Integer, nullable=True),
+        sa.Column('forecast_days', sa.Integer, nullable=True),
+        sa.Column('business_type', sa.String(50), nullable=True),
+        sa.Column('error_message', sa.Text(), nullable=True),
+        sa.Column('processing_time_ms', sa.Integer, nullable=True),
+        sa.Column('cancelled_by', sa.String(), nullable=True),
+        sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_prediction_batches_tenant_id'), 'prediction_batches', ['tenant_id'], unique=False)
+    op.create_index(op.f('ix_prediction_batches_status'), 'prediction_batches', ['status'], unique=False)
+    op.create_index(op.f('ix_prediction_batches_requested_at'), 'prediction_batches', ['requested_at'], unique=False)
+    
+    # Create model_performance_metrics table
+    op.create_table('model_performance_metrics',
+        sa.Column('id', sa.UUID(), nullable=False),
+        sa.Column('model_id', sa.UUID(), nullable=False),
+        sa.Column('tenant_id', sa.UUID(), nullable=False),
+        sa.Column('inventory_product_id', sa.UUID(), nullable=False),
+        sa.Column('mae', sa.Float, nullable=True),
+        sa.Column('mape', sa.Float, nullable=True),
+        sa.Column('rmse', sa.Float, nullable=True),
+        sa.Column('accuracy_score', sa.Float, nullable=True),
+        sa.Column('evaluation_date', sa.DateTime(timezone=True), nullable=False),
+        sa.Column('evaluation_period_start', sa.DateTime(timezone=True), nullable=True),
+        sa.Column('evaluation_period_end', sa.DateTime(timezone=True), nullable=True),
+        sa.Column('sample_size', sa.Integer, nullable=True),
+        sa.Column('created_at', sa.DateTime(timezone=True), server_default=sa.text('timezone(\'utc\', now())'), nullable=True),
+        sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_model_performance_metrics_model_id'), 'model_performance_metrics', ['model_id'], unique=False)
+    op.create_index(op.f('ix_model_performance_metrics_tenant_id'), 'model_performance_metrics', ['tenant_id'], unique=False)
+    op.create_index(op.f('ix_model_performance_metrics_inventory_product_id'), 'model_performance_metrics', ['inventory_product_id'], unique=False)
+    op.create_index(op.f('ix_model_performance_metrics_evaluation_date'), 'model_performance_metrics', ['evaluation_date'], unique=False)
+    
+    # Create prediction_cache table
+    op.create_table('prediction_cache',
+        sa.Column('id', sa.UUID(), nullable=False),
+        sa.Column('cache_key', sa.String(255), nullable=False),
+        sa.Column('tenant_id', sa.UUID(), nullable=False),
+        sa.Column('inventory_product_id', sa.UUID(), nullable=False),
+        sa.Column('location', sa.String(255), nullable=False),
+        sa.Column('forecast_date', sa.DateTime(timezone=True), nullable=False),
+        sa.Column('predicted_demand', sa.Float, nullable=False),
+        sa.Column('confidence_lower', sa.Float, nullable=False),
+        sa.Column('confidence_upper', sa.Float, nullable=False),
+        sa.Column('model_id', sa.UUID(), nullable=False),
+        sa.Column('created_at', sa.DateTime(timezone=True), server_default=sa.text('timezone(\'utc\', now())'), nullable=True),
+        sa.Column('expires_at', sa.DateTime(timezone=True), nullable=False),
+        sa.Column('hit_count', sa.Integer, nullable=True),
+        sa.PrimaryKeyConstraint('id'),
+        sa.UniqueConstraint('cache_key')
+    )
+    op.create_index(op.f('ix_prediction_cache_cache_key'), 'prediction_cache', ['cache_key'], unique=False)
+    op.create_index(op.f('ix_prediction_cache_tenant_id'), 'prediction_cache', ['tenant_id'], unique=False)
+    op.create_index(op.f('ix_prediction_cache_inventory_product_id'), 'prediction_cache', ['inventory_product_id'], unique=False)
+    op.create_index(op.f('ix_prediction_cache_forecast_date'), 'prediction_cache', ['forecast_date'], unique=False)
+
+
+def downgrade() -> None:
+    op.drop_index(op.f('ix_prediction_cache_forecast_date'), table_name='prediction_cache')
+    op.drop_index(op.f('ix_prediction_cache_inventory_product_id'), table_name='prediction_cache')
+    op.drop_index(op.f('ix_prediction_cache_tenant_id'), table_name='prediction_cache')
+    op.drop_index(op.f('ix_prediction_cache_cache_key'), table_name='prediction_cache')
+    op.drop_table('prediction_cache')
+    op.drop_index(op.f('ix_model_performance_metrics_evaluation_date'), table_name='model_performance_metrics')
+    op.drop_index(op.f('ix_model_performance_metrics_inventory_product_id'), table_name='model_performance_metrics')
+    op.drop_index(op.f('ix_model_performance_metrics_tenant_id'), table_name='model_performance_metrics')
+    op.drop_index(op.f('ix_model_performance_metrics_model_id'), table_name='model_performance_metrics')
+    op.drop_table('model_performance_metrics')
+    op.drop_index(op.f('ix_prediction_batches_requested_at'), table_name='prediction_batches')
+    op.drop_index(op.f('ix_prediction_batches_status'), table_name='prediction_batches')
+    op.drop_index(op.f('ix_prediction_batches_tenant_id'), table_name='prediction_batches')
+    op.drop_table('prediction_batches')
+    op.drop_index(op.f('ix_predictions_prediction_date'), table_name='predictions')
+    op.drop_index(op.f('ix_predictions_model_id'), table_name='predictions')
+    op.drop_index(op.f('ix_predictions_tenant_id'), table_name='predictions')
+    op.drop_table('predictions')
+    op.drop_index(op.f('ix_forecasts_forecast_date'), table_name='forecasts')
+    op.drop_index(op.f('ix_forecasts_location'), table_name='forecasts')
+    op.drop_index(op.f('ix_forecasts_product_name'), table_name='forecasts')
+    op.drop_index(op.f('ix_forecasts_inventory_product_id'), table_name='forecasts')
+    op.drop_index(op.f('ix_forecasts_tenant_id'), table_name='forecasts')
+    op.drop_table('forecasts')