demo seed change
This commit is contained in:
Urtzi Alfaro
@@ -13,6 +13,7 @@ from typing import Optional
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import os
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from decimal import Decimal
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import sys
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import json
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent.parent.parent.parent))
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@@ -24,7 +25,7 @@ from app.models.sales import SalesData
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from app.core.config import settings
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logger = structlog.get_logger()
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router = APIRouter(prefix="/internal/demo", tags=["internal"])
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router = APIRouter()
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# Base demo tenant IDs
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DEMO_TENANT_PROFESSIONAL = "a1b2c3d4-e5f6-47a8-b9c0-d1e2f3a4b5c6"
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@@ -38,7 +39,7 @@ def verify_internal_api_key(x_internal_api_key: Optional[str] = Header(None)):
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return True
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@router.post("/clone")
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@router.post("/internal/demo/clone")
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async def clone_demo_data(
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base_tenant_id: str,
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virtual_tenant_id: str,
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@@ -102,46 +103,71 @@ async def clone_demo_data(
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"sales_records": 0,
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}
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# Clone Sales Data
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result = await db.execute(
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select(SalesData).where(SalesData.tenant_id == base_uuid)
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)
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base_sales = result.scalars().all()
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# Load seed data from JSON files instead of cloning from database
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try:
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from shared.utils.seed_data_paths import get_seed_data_path
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if demo_account_type == "professional":
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json_file = get_seed_data_path("professional", "09-sales.json")
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elif demo_account_type == "enterprise":
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json_file = get_seed_data_path("enterprise", "09-sales.json")
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else:
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raise ValueError(f"Invalid demo account type: {demo_account_type}")
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except ImportError:
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# Fallback to original path
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seed_data_dir = Path(__file__).parent.parent.parent.parent / "infrastructure" / "seed-data"
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if demo_account_type == "professional":
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json_file = seed_data_dir / "professional" / "09-sales.json"
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elif demo_account_type == "enterprise":
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json_file = seed_data_dir / "enterprise" / "parent" / "09-sales.json"
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else:
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raise ValueError(f"Invalid demo account type: {demo_account_type}")
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if not json_file.exists():
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raise HTTPException(
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status_code=404,
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detail=f"Seed data file not found: {json_file}"
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)
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# Load JSON data
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with open(json_file, 'r', encoding='utf-8') as f:
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seed_data = json.load(f)
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logger.info(
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"Found sales records to clone",
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count=len(base_sales),
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base_tenant=str(base_uuid)
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"Loaded sales seed data",
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sales_records=len(seed_data.get('sales_data', []))
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)
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for sale in base_sales:
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# Load Sales Data from seed data
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for sale_data in seed_data.get('sales_data', []):
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# Adjust date using the shared utility
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adjusted_date = adjust_date_for_demo(
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sale.date,
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datetime.fromisoformat(sale_data['sale_date'].replace('Z', '+00:00')),
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session_time,
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BASE_REFERENCE_DATE
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) if sale.date else None
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) if sale_data.get('sale_date') else None
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# Create new sales record with adjusted date
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new_sale = SalesData(
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id=uuid.uuid4(),
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tenant_id=virtual_uuid,
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date=adjusted_date,
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inventory_product_id=sale.inventory_product_id, # Keep same product refs
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quantity_sold=sale.quantity_sold,
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unit_price=sale.unit_price,
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revenue=sale.revenue,
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cost_of_goods=sale.cost_of_goods,
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discount_applied=sale.discount_applied,
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location_id=sale.location_id,
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sales_channel=sale.sales_channel,
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source="demo_clone", # Mark as cloned
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is_validated=sale.is_validated,
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validation_notes=sale.validation_notes,
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notes=sale.notes,
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weather_condition=sale.weather_condition,
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is_holiday=sale.is_holiday,
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is_weekend=sale.is_weekend,
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inventory_product_id=sale_data.get('product_id'), # Use product_id from seed data
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quantity_sold=sale_data.get('quantity_sold', 0.0),
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unit_price=sale_data.get('unit_price', 0.0),
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revenue=sale_data.get('total_revenue', 0.0),
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cost_of_goods=sale_data.get('cost_of_goods', 0.0),
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discount_applied=sale_data.get('discount_applied', 0.0),
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location_id=sale_data.get('location_id'),
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sales_channel=sale_data.get('sales_channel', 'IN_STORE'),
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source="demo_seed", # Mark as seeded
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is_validated=sale_data.get('is_validated', True),
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validation_notes=sale_data.get('validation_notes'),
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notes=sale_data.get('notes'),
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weather_condition=sale_data.get('weather_condition'),
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is_holiday=sale_data.get('is_holiday', False),
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is_weekend=sale_data.get('is_weekend', False),
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created_at=session_time,
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updated_at=session_time
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)
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@@ -10,7 +10,7 @@ from app.core.database import database_manager
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from shared.service_base import StandardFastAPIService
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# Import API routers
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from app.api import sales_records, sales_operations, analytics, internal_demo, audit, batch
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from app.api import sales_records, sales_operations, analytics, audit, batch, internal_demo
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class SalesService(StandardFastAPIService):
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@@ -151,4 +151,4 @@ service.add_router(batch.router)
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service.add_router(sales_records.router)
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service.add_router(sales_operations.router)
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service.add_router(analytics.router)
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service.add_router(internal_demo.router)
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service.add_router(internal_demo.router, tags=["internal-demo"])
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@@ -1,349 +0,0 @@
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Demo Sales Seeding Script for Sales Service
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Creates realistic historical sales data for demo template tenants
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This script runs as a Kubernetes init job inside the sales-service container.
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It populates the template tenants with historical sales data.
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Usage:
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python /app/scripts/demo/seed_demo_sales.py
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Environment Variables Required:
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SALES_DATABASE_URL - PostgreSQL connection string for sales database
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INVENTORY_DATABASE_URL - PostgreSQL connection string for inventory database (to lookup products)
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DEMO_MODE - Set to 'production' for production seeding
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LOG_LEVEL - Logging level (default: INFO)
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"""
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import asyncio
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import uuid
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import sys
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import os
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from datetime import datetime, timezone, timedelta
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from pathlib import Path
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import random
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from decimal import Decimal
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# Add app to path
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sys.path.insert(0, str(Path(__file__).parent.parent.parent))
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from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine
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from sqlalchemy.orm import sessionmaker
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from sqlalchemy import select, text
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import structlog
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from app.models.sales import SalesData
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# Configure logging
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structlog.configure(
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processors=[
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structlog.stdlib.add_log_level,
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structlog.processors.TimeStamper(fmt="iso"),
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structlog.dev.ConsoleRenderer()
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]
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)
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logger = structlog.get_logger()
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# Fixed Demo Tenant IDs (must match tenant service)
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DEMO_TENANT_PROFESSIONAL = uuid.UUID("a1b2c3d4-e5f6-47a8-b9c0-d1e2f3a4b5c6")
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# Hardcoded product IDs from ingredientes_es.json (finished products)
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PRODUCT_IDS = {
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"PRO-BAG-001": "20000000-0000-0000-0000-000000000001", # Baguette Tradicional
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"PRO-CRO-001": "20000000-0000-0000-0000-000000000002", # Croissant de Mantequilla
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"PRO-PUE-001": "20000000-0000-0000-0000-000000000003", # Pan de Pueblo
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"PRO-NAP-001": "20000000-0000-0000-0000-000000000004", # Napolitana de Chocolate
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}
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# Sample product SKUs and their typical sales patterns
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SAN_PABLO_PRODUCTS = [
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{"sku": "PRO-BAG-001", "name": "Baguette Tradicional", "avg_qty": 80, "variance": 15, "price": 1.20},
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{"sku": "PRO-CRO-001", "name": "Croissant de Mantequilla", "avg_qty": 50, "variance": 10, "price": 1.50},
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{"sku": "PRO-PUE-001", "name": "Pan de Pueblo", "avg_qty": 20, "variance": 5, "price": 3.50},
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{"sku": "PRO-NAP-001", "name": "Napolitana de Chocolate", "avg_qty": 35, "variance": 8, "price": 1.80},
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]
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LA_ESPIGA_PRODUCTS = [
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{"sku": "PRO-BAG-001", "name": "Baguette Tradicional", "avg_qty": 500, "variance": 80, "price": 0.90},
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{"sku": "PRO-CRO-001", "name": "Croissant de Mantequilla", "avg_qty": 300, "variance": 50, "price": 1.10},
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{"sku": "PRO-PUE-001", "name": "Pan de Pueblo", "avg_qty": 100, "variance": 20, "price": 2.80},
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{"sku": "PRO-NAP-001", "name": "Napolitana de Chocolate", "avg_qty": 200, "variance": 40, "price": 1.40},
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]
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def get_product_by_sku(tenant_id: uuid.UUID, sku: str, product_name: str):
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"""
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Get tenant-specific product ID using hardcoded base IDs (no database lookup needed)
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Args:
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tenant_id: Tenant UUID
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sku: Product SKU code
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product_name: Product name
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Returns:
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Tuple of (product_id, product_name) or (None, None) if not found
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"""
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if sku not in PRODUCT_IDS:
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return None, None
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# Generate tenant-specific product ID (same as inventory seed script)
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base_product_id = uuid.UUID(PRODUCT_IDS[sku])
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tenant_int = int(tenant_id.hex, 16)
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product_id = uuid.UUID(int=tenant_int ^ int(base_product_id.hex, 16))
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return product_id, product_name
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async def seed_sales_for_tenant(
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sales_db: AsyncSession,
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tenant_id: uuid.UUID,
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tenant_name: str,
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product_patterns: list,
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days_of_history: int = 90
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) -> dict:
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"""
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Seed sales data for a specific tenant
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Args:
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sales_db: Sales database session
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tenant_id: UUID of the tenant
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tenant_name: Name of the tenant (for logging)
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product_patterns: List of product sales patterns
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days_of_history: Number of days of historical data to generate
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Returns:
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Dict with seeding statistics
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"""
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logger.info("─" * 80)
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logger.info(f"Seeding sales data for: {tenant_name}")
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logger.info(f"Tenant ID: {tenant_id}")
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logger.info(f"Days of history: {days_of_history}")
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logger.info("─" * 80)
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created_sales = 0
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skipped_sales = 0
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# Generate sales data for each day
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for days_ago in range(days_of_history, 0, -1):
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sale_date = datetime.now(timezone.utc) - timedelta(days=days_ago)
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# Skip some random days to simulate closures
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if random.random() < 0.05: # 5% chance of being closed
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continue
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# For each product, generate sales
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for product_pattern in product_patterns:
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sku = product_pattern["sku"]
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product_name = product_pattern["name"]
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# Get tenant-specific product ID using hardcoded base IDs
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product_id, product_name = get_product_by_sku(tenant_id, sku, product_name)
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if not product_id:
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logger.warning(f" ⚠️ Product not found: {sku}")
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continue
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# Check if sales record already exists
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result = await sales_db.execute(
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select(SalesData).where(
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SalesData.tenant_id == tenant_id,
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SalesData.inventory_product_id == product_id,
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SalesData.date == sale_date
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)
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)
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existing = result.scalars().first()
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if existing:
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skipped_sales += 1
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continue
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# Calculate sales quantity with variance
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avg_qty = product_pattern["avg_qty"]
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variance = product_pattern["variance"]
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# Add weekly patterns (weekends sell more)
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weekday = sale_date.weekday()
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if weekday in [5, 6]: # Saturday, Sunday
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multiplier = random.uniform(1.2, 1.5)
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else:
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multiplier = random.uniform(0.8, 1.2)
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quantity = max(0, int((avg_qty + random.uniform(-variance, variance)) * multiplier))
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if quantity == 0:
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continue
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# Calculate revenue
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unit_price = Decimal(str(product_pattern["price"]))
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revenue = Decimal(str(quantity)) * unit_price
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# Check if it's a weekend
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is_weekend = weekday in [5, 6]
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# Create sales record
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sales_record = SalesData(
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id=uuid.uuid4(),
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tenant_id=tenant_id,
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inventory_product_id=product_id,
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date=sale_date,
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quantity_sold=quantity,
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revenue=revenue,
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unit_price=unit_price,
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sales_channel="in_store",
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location_id="main",
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source="demo_seed",
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is_weekend=is_weekend,
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created_at=sale_date,
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updated_at=sale_date
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)
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sales_db.add(sales_record)
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created_sales += 1
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# Commit all changes for this tenant
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await sales_db.commit()
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logger.info(f" 📊 Created: {created_sales}, Skipped: {skipped_sales}")
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logger.info("")
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return {
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"tenant_id": str(tenant_id),
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"tenant_name": tenant_name,
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"sales_records_created": created_sales,
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"sales_records_skipped": skipped_sales,
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"days_of_history": days_of_history
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}
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async def seed_sales(sales_db: AsyncSession):
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"""
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Seed sales for all demo template tenants
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Args:
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sales_db: Sales database session
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Returns:
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Dict with overall seeding statistics
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"""
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logger.info("=" * 80)
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logger.info("💰 Starting Demo Sales Seeding")
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logger.info("=" * 80)
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results = []
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# Seed for San Pablo (Traditional Bakery) - 30 days of history (optimized for fast demo loading)
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logger.info("")
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result_san_pablo = await seed_sales_for_tenant(
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sales_db,
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DEMO_TENANT_PROFESSIONAL,
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"Panadería Professional Bakery",
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SAN_PABLO_PRODUCTS,
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days_of_history=30
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)
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results.append(result_san_pablo)
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# Calculate totals
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total_sales = sum(r["sales_records_created"] for r in results)
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total_skipped = sum(r["sales_records_skipped"] for r in results)
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logger.info("=" * 80)
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logger.info("✅ Demo Sales Seeding Completed")
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logger.info("=" * 80)
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return {
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"service": "sales",
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"tenants_seeded": len(results),
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"total_sales_created": total_sales,
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"total_skipped": total_skipped,
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"results": results
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}
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async def main():
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"""Main execution function"""
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logger.info("Demo Sales Seeding Script Starting")
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logger.info("Mode: %s", os.getenv("DEMO_MODE", "development"))
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logger.info("Log Level: %s", os.getenv("LOG_LEVEL", "INFO"))
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# Get database URL from environment
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sales_database_url = os.getenv("SALES_DATABASE_URL") or os.getenv("DATABASE_URL")
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if not sales_database_url:
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logger.error("❌ SALES_DATABASE_URL or DATABASE_URL environment variable must be set")
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return 1
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# Convert to async URLs if needed
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if sales_database_url.startswith("postgresql://"):
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sales_database_url = sales_database_url.replace("postgresql://", "postgresql+asyncpg://", 1)
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logger.info("Connecting to sales database")
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# Create engine and session
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sales_engine = create_async_engine(
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sales_database_url,
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echo=False,
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pool_pre_ping=True,
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pool_size=5,
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max_overflow=10
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)
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sales_session_maker = sessionmaker(
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sales_engine,
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class_=AsyncSession,
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expire_on_commit=False
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)
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try:
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async with sales_session_maker() as sales_session:
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result = await seed_sales(sales_session)
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logger.info("")
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logger.info("📊 Seeding Summary:")
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logger.info(f" ✅ Tenants seeded: {result['tenants_seeded']}")
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logger.info(f" ✅ Sales records created: {result['total_sales_created']}")
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logger.info(f" ⏭️ Skipped: {result['total_skipped']}")
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logger.info("")
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# Print per-tenant details
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for tenant_result in result['results']:
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logger.info(
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f" {tenant_result['tenant_name']}: "
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f"{tenant_result['sales_records_created']} sales records "
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f"({tenant_result['days_of_history']} days)"
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)
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|
||||
logger.info("")
|
||||
logger.info("🎉 Success! Sales history is ready for cloning.")
|
||||
logger.info("")
|
||||
logger.info("Sales data includes:")
|
||||
logger.info(" • 30 days of historical sales (optimized for demo performance)")
|
||||
logger.info(" • 4 product types per tenant")
|
||||
logger.info(" • Realistic weekly patterns (higher on weekends)")
|
||||
logger.info(" • Random variance and occasional closures")
|
||||
logger.info("")
|
||||
logger.info("Next steps:")
|
||||
logger.info(" 1. Run seed jobs for other services (orders, production, etc.)")
|
||||
logger.info(" 2. Verify sales data in database")
|
||||
logger.info(" 3. Test demo session creation with sales cloning")
|
||||
logger.info("")
|
||||
|
||||
return 0
|
||||
|
||||
except Exception as e:
|
||||
logger.error("=" * 80)
|
||||
logger.error("❌ Demo Sales Seeding Failed")
|
||||
logger.error("=" * 80)
|
||||
logger.error("Error: %s", str(e))
|
||||
logger.error("", exc_info=True)
|
||||
return 1
|
||||
|
||||
finally:
|
||||
await sales_engine.dispose()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
exit_code = asyncio.run(main())
|
||||
sys.exit(exit_code)
|
||||
@@ -1,381 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Demo Retail Sales Seeding Script for Sales Service
|
||||
Creates realistic historical sales data for child retail outlets
|
||||
|
||||
This script runs as a Kubernetes init job inside the sales-service container.
|
||||
It populates child retail tenants with 30 days of sales history.
|
||||
|
||||
Usage:
|
||||
python /app/scripts/demo/seed_demo_sales_retail.py
|
||||
|
||||
Environment Variables Required:
|
||||
SALES_DATABASE_URL - PostgreSQL connection string for sales database
|
||||
DEMO_MODE - Set to 'production' for production seeding
|
||||
LOG_LEVEL - Logging level (default: INFO)
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import uuid
|
||||
import sys
|
||||
import os
|
||||
from datetime import datetime, timezone, timedelta
|
||||
from pathlib import Path
|
||||
import random
|
||||
from decimal import Decimal
|
||||
|
||||
# Add app to path
|
||||
sys.path.insert(0, str(Path(__file__).parent.parent.parent))
|
||||
# Add shared to path for demo utilities
|
||||
sys.path.insert(0, str(Path(__file__).parent.parent.parent.parent.parent))
|
||||
|
||||
from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine
|
||||
from sqlalchemy.orm import sessionmaker
|
||||
from sqlalchemy import select
|
||||
import structlog
|
||||
|
||||
from shared.utils.demo_dates import BASE_REFERENCE_DATE
|
||||
|
||||
from app.models.sales import SalesData
|
||||
|
||||
# Configure logging
|
||||
structlog.configure(
|
||||
processors=[
|
||||
structlog.stdlib.add_log_level,
|
||||
structlog.processors.TimeStamper(fmt="iso"),
|
||||
structlog.dev.ConsoleRenderer()
|
||||
]
|
||||
)
|
||||
|
||||
logger = structlog.get_logger()
|
||||
|
||||
# Fixed Demo Tenant IDs (must match tenant service)
|
||||
DEMO_TENANT_CHILD_1 = uuid.UUID("d4e5f6a7-b8c9-40d1-e2f3-a4b5c6d7e8f9") # Madrid Centro
|
||||
DEMO_TENANT_CHILD_2 = uuid.UUID("e5f6a7b8-c9d0-41e2-f3a4-b5c6d7e8f9a0") # Barcelona Gràcia
|
||||
DEMO_TENANT_CHILD_3 = uuid.UUID("f6a7b8c9-d0e1-42f3-a4b5-c6d7e8f9a0b1") # Valencia Ruzafa
|
||||
|
||||
# Hardcoded product IDs from ingredientes_es.json (finished products)
|
||||
PRODUCT_IDS = {
|
||||
"PRO-BAG-001": "20000000-0000-0000-0000-000000000001", # Baguette Tradicional
|
||||
"PRO-CRO-001": "20000000-0000-0000-0000-000000000002", # Croissant de Mantequilla
|
||||
"PRO-PUE-001": "20000000-0000-0000-0000-000000000003", # Pan de Pueblo
|
||||
"PRO-NAP-001": "20000000-0000-0000-0000-000000000004", # Napolitana de Chocolate
|
||||
}
|
||||
|
||||
# Retail sales patterns for each store
|
||||
# Madrid Centro - Large urban store, high traffic
|
||||
MADRID_CENTRO_PRODUCTS = [
|
||||
{"sku": "PRO-BAG-001", "name": "Baguette Tradicional", "avg_qty": 120, "variance": 20, "price": 1.30},
|
||||
{"sku": "PRO-CRO-001", "name": "Croissant de Mantequilla", "avg_qty": 80, "variance": 15, "price": 1.60},
|
||||
{"sku": "PRO-PUE-001", "name": "Pan de Pueblo", "avg_qty": 35, "variance": 8, "price": 3.80},
|
||||
{"sku": "PRO-NAP-001", "name": "Napolitana de Chocolate", "avg_qty": 60, "variance": 12, "price": 1.90},
|
||||
]
|
||||
|
||||
# Barcelona Gràcia - Medium neighborhood store
|
||||
BARCELONA_GRACIA_PRODUCTS = [
|
||||
{"sku": "PRO-BAG-001", "name": "Baguette Tradicional", "avg_qty": 90, "variance": 15, "price": 1.25},
|
||||
{"sku": "PRO-CRO-001", "name": "Croissant de Mantequilla", "avg_qty": 60, "variance": 12, "price": 1.55},
|
||||
{"sku": "PRO-PUE-001", "name": "Pan de Pueblo", "avg_qty": 25, "variance": 6, "price": 3.70},
|
||||
{"sku": "PRO-NAP-001", "name": "Napolitana de Chocolate", "avg_qty": 45, "variance": 10, "price": 1.85},
|
||||
]
|
||||
|
||||
# Valencia Ruzafa - Smaller boutique store
|
||||
VALENCIA_RUZAFA_PRODUCTS = [
|
||||
{"sku": "PRO-BAG-001", "name": "Baguette Tradicional", "avg_qty": 70, "variance": 12, "price": 1.20},
|
||||
{"sku": "PRO-CRO-001", "name": "Croissant de Mantequilla", "avg_qty": 45, "variance": 10, "price": 1.50},
|
||||
{"sku": "PRO-PUE-001", "name": "Pan de Pueblo", "avg_qty": 20, "variance": 5, "price": 3.60},
|
||||
{"sku": "PRO-NAP-001", "name": "Napolitana de Chocolate", "avg_qty": 35, "variance": 8, "price": 1.80},
|
||||
]
|
||||
|
||||
# Child tenant configurations
|
||||
CHILD_TENANTS = [
|
||||
(DEMO_TENANT_CHILD_1, "Madrid Centro", MADRID_CENTRO_PRODUCTS),
|
||||
(DEMO_TENANT_CHILD_2, "Barcelona Gràcia", BARCELONA_GRACIA_PRODUCTS),
|
||||
(DEMO_TENANT_CHILD_3, "Valencia Ruzafa", VALENCIA_RUZAFA_PRODUCTS)
|
||||
]
|
||||
|
||||
|
||||
def get_product_by_sku(tenant_id: uuid.UUID, sku: str, product_name: str):
|
||||
"""
|
||||
Get tenant-specific product ID using XOR transformation
|
||||
|
||||
Args:
|
||||
tenant_id: Tenant UUID
|
||||
sku: Product SKU code
|
||||
product_name: Product name
|
||||
|
||||
Returns:
|
||||
Tuple of (product_id, product_name) or (None, None) if not found
|
||||
"""
|
||||
if sku not in PRODUCT_IDS:
|
||||
return None, None
|
||||
|
||||
# Generate tenant-specific product ID using XOR (same as inventory seed script)
|
||||
base_product_id = uuid.UUID(PRODUCT_IDS[sku])
|
||||
tenant_int = int(tenant_id.hex, 16)
|
||||
product_id = uuid.UUID(int=tenant_int ^ int(base_product_id.hex, 16))
|
||||
|
||||
return product_id, product_name
|
||||
|
||||
|
||||
async def seed_retail_sales_for_tenant(
|
||||
db: AsyncSession,
|
||||
tenant_id: uuid.UUID,
|
||||
tenant_name: str,
|
||||
product_patterns: list,
|
||||
days_of_history: int = 30
|
||||
) -> dict:
|
||||
"""
|
||||
Seed retail sales data for a specific child tenant
|
||||
|
||||
Args:
|
||||
db: Database session
|
||||
tenant_id: UUID of the child tenant
|
||||
tenant_name: Name of the tenant (for logging)
|
||||
product_patterns: List of product sales patterns
|
||||
days_of_history: Number of days of historical data to generate (default: 30)
|
||||
|
||||
Returns:
|
||||
Dict with seeding statistics
|
||||
"""
|
||||
logger.info("─" * 80)
|
||||
logger.info(f"Seeding retail sales data for: {tenant_name}")
|
||||
logger.info(f"Tenant ID: {tenant_id}")
|
||||
logger.info(f"Days of history: {days_of_history}")
|
||||
logger.info("─" * 80)
|
||||
|
||||
created_sales = 0
|
||||
skipped_sales = 0
|
||||
|
||||
# Generate sales data for each day (working backwards from BASE_REFERENCE_DATE)
|
||||
for days_ago in range(days_of_history, 0, -1):
|
||||
sale_date = BASE_REFERENCE_DATE - timedelta(days=days_ago)
|
||||
|
||||
# Skip some random days to simulate closures/holidays (3% chance)
|
||||
if random.random() < 0.03:
|
||||
continue
|
||||
|
||||
# For each product, generate sales
|
||||
for product_pattern in product_patterns:
|
||||
sku = product_pattern["sku"]
|
||||
product_name = product_pattern["name"]
|
||||
|
||||
# Get tenant-specific product ID using XOR transformation
|
||||
product_id, product_name = get_product_by_sku(tenant_id, sku, product_name)
|
||||
|
||||
if not product_id:
|
||||
logger.warning(f" ⚠️ Product not found: {sku}")
|
||||
continue
|
||||
|
||||
# Check if sales record already exists
|
||||
result = await db.execute(
|
||||
select(SalesData).where(
|
||||
SalesData.tenant_id == tenant_id,
|
||||
SalesData.inventory_product_id == product_id,
|
||||
SalesData.date == sale_date
|
||||
)
|
||||
)
|
||||
existing = result.scalars().first()
|
||||
|
||||
if existing:
|
||||
skipped_sales += 1
|
||||
continue
|
||||
|
||||
# Calculate sales quantity with realistic variance
|
||||
avg_qty = product_pattern["avg_qty"]
|
||||
variance = product_pattern["variance"]
|
||||
|
||||
# Add weekly patterns (weekends sell more for bakeries)
|
||||
weekday = sale_date.weekday()
|
||||
if weekday in [5, 6]: # Saturday, Sunday
|
||||
multiplier = random.uniform(1.3, 1.6) # 30-60% more sales on weekends
|
||||
elif weekday == 4: # Friday
|
||||
multiplier = random.uniform(1.1, 1.3) # 10-30% more on Fridays
|
||||
else: # Weekdays
|
||||
multiplier = random.uniform(0.85, 1.15)
|
||||
|
||||
quantity = max(0, int((avg_qty + random.uniform(-variance, variance)) * multiplier))
|
||||
|
||||
if quantity == 0:
|
||||
continue
|
||||
|
||||
# Calculate revenue
|
||||
unit_price = Decimal(str(product_pattern["price"]))
|
||||
revenue = Decimal(str(quantity)) * unit_price
|
||||
|
||||
# Determine if weekend
|
||||
is_weekend = weekday in [5, 6]
|
||||
|
||||
# Create sales record
|
||||
sales_record = SalesData(
|
||||
id=uuid.uuid4(),
|
||||
tenant_id=tenant_id,
|
||||
inventory_product_id=product_id,
|
||||
date=sale_date,
|
||||
quantity_sold=quantity,
|
||||
revenue=revenue,
|
||||
unit_price=unit_price,
|
||||
sales_channel="in_store", # Retail outlets primarily use in-store sales
|
||||
location_id="main", # Single location per retail outlet
|
||||
source="demo_seed",
|
||||
is_weekend=is_weekend,
|
||||
created_at=sale_date,
|
||||
updated_at=sale_date
|
||||
)
|
||||
|
||||
db.add(sales_record)
|
||||
created_sales += 1
|
||||
|
||||
logger.debug(
|
||||
f" ✅ {sale_date.strftime('%Y-%m-%d')}: {product_name} - "
|
||||
f"{quantity} units @ €{unit_price} = €{revenue:.2f}"
|
||||
)
|
||||
|
||||
# Commit all changes for this tenant
|
||||
await db.commit()
|
||||
|
||||
logger.info(f" 📊 Sales records created: {created_sales}, Skipped: {skipped_sales}")
|
||||
logger.info("")
|
||||
|
||||
return {
|
||||
"tenant_id": str(tenant_id),
|
||||
"tenant_name": tenant_name,
|
||||
"sales_created": created_sales,
|
||||
"sales_skipped": skipped_sales,
|
||||
"days_of_history": days_of_history
|
||||
}
|
||||
|
||||
|
||||
async def seed_retail_sales(db: AsyncSession):
|
||||
"""
|
||||
Seed retail sales for all child tenant templates
|
||||
|
||||
Args:
|
||||
db: Database session
|
||||
|
||||
Returns:
|
||||
Dict with overall seeding statistics
|
||||
"""
|
||||
logger.info("=" * 80)
|
||||
logger.info("💰 Starting Demo Retail Sales Seeding")
|
||||
logger.info("=" * 80)
|
||||
logger.info("Creating 30 days of sales history for retail outlets")
|
||||
logger.info("")
|
||||
|
||||
results = []
|
||||
|
||||
# Seed for each child retail outlet
|
||||
for child_tenant_id, child_tenant_name, product_patterns in CHILD_TENANTS:
|
||||
logger.info("")
|
||||
result = await seed_retail_sales_for_tenant(
|
||||
db,
|
||||
child_tenant_id,
|
||||
f"{child_tenant_name} (Retail Outlet)",
|
||||
product_patterns,
|
||||
days_of_history=30 # 30 days of sales history
|
||||
)
|
||||
results.append(result)
|
||||
|
||||
# Calculate totals
|
||||
total_sales = sum(r["sales_created"] for r in results)
|
||||
total_skipped = sum(r["sales_skipped"] for r in results)
|
||||
|
||||
logger.info("=" * 80)
|
||||
logger.info("✅ Demo Retail Sales Seeding Completed")
|
||||
logger.info("=" * 80)
|
||||
|
||||
return {
|
||||
"service": "sales_retail",
|
||||
"tenants_seeded": len(results),
|
||||
"total_sales_created": total_sales,
|
||||
"total_skipped": total_skipped,
|
||||
"results": results
|
||||
}
|
||||
|
||||
|
||||
async def main():
|
||||
"""Main execution function"""
|
||||
|
||||
logger.info("Demo Retail Sales Seeding Script Starting")
|
||||
logger.info("Mode: %s", os.getenv("DEMO_MODE", "development"))
|
||||
logger.info("Log Level: %s", os.getenv("LOG_LEVEL", "INFO"))
|
||||
|
||||
# Get database URL from environment
|
||||
database_url = os.getenv("SALES_DATABASE_URL") or os.getenv("DATABASE_URL")
|
||||
if not database_url:
|
||||
logger.error("❌ SALES_DATABASE_URL or DATABASE_URL environment variable must be set")
|
||||
return 1
|
||||
|
||||
# Convert to async URL if needed
|
||||
if database_url.startswith("postgresql://"):
|
||||
database_url = database_url.replace("postgresql://", "postgresql+asyncpg://", 1)
|
||||
|
||||
logger.info("Connecting to sales database")
|
||||
|
||||
# Create engine and session
|
||||
engine = create_async_engine(
|
||||
database_url,
|
||||
echo=False,
|
||||
pool_pre_ping=True,
|
||||
pool_size=5,
|
||||
max_overflow=10
|
||||
)
|
||||
|
||||
async_session = sessionmaker(
|
||||
engine,
|
||||
class_=AsyncSession,
|
||||
expire_on_commit=False
|
||||
)
|
||||
|
||||
try:
|
||||
async with async_session() as session:
|
||||
result = await seed_retail_sales(session)
|
||||
|
||||
logger.info("")
|
||||
logger.info("📊 Retail Sales Seeding Summary:")
|
||||
logger.info(f" ✅ Retail outlets seeded: {result['tenants_seeded']}")
|
||||
logger.info(f" ✅ Total sales records: {result['total_sales_created']}")
|
||||
logger.info(f" ⏭️ Total skipped: {result['total_skipped']}")
|
||||
logger.info("")
|
||||
|
||||
# Print per-tenant details
|
||||
for tenant_result in result['results']:
|
||||
logger.info(
|
||||
f" {tenant_result['tenant_name']}: "
|
||||
f"{tenant_result['sales_created']} sales records"
|
||||
)
|
||||
|
||||
logger.info("")
|
||||
logger.info("🎉 Success! Retail sales history is ready for cloning.")
|
||||
logger.info("")
|
||||
logger.info("Sales characteristics:")
|
||||
logger.info(" ✓ 30 days of historical data")
|
||||
logger.info(" ✓ Weekend sales boost (30-60% higher)")
|
||||
logger.info(" ✓ Friday pre-weekend surge (10-30% higher)")
|
||||
logger.info(" ✓ Realistic variance per product")
|
||||
logger.info(" ✓ Store-specific pricing and volumes")
|
||||
logger.info("")
|
||||
logger.info("Next steps:")
|
||||
logger.info(" 1. Seed customer data")
|
||||
logger.info(" 2. Seed retail orders (internal transfers from parent)")
|
||||
logger.info(" 3. Test forecasting with retail sales data")
|
||||
logger.info("")
|
||||
|
||||
return 0
|
||||
|
||||
except Exception as e:
|
||||
logger.error("=" * 80)
|
||||
logger.error("❌ Demo Retail Sales Seeding Failed")
|
||||
logger.error("=" * 80)
|
||||
logger.error("Error: %s", str(e))
|
||||
logger.error("", exc_info=True)
|
||||
return 1
|
||||
|
||||
finally:
|
||||
await engine.dispose()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
exit_code = asyncio.run(main())
|
||||
sys.exit(exit_code)
|
||||
Reference in New Issue
Block a user