New enterprise feature
This commit is contained in:
Urtzi Alfaro
@@ -21,20 +21,18 @@ from shared.utils.demo_dates import adjust_date_for_demo, BASE_REFERENCE_DATE
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from app.core.database import get_db
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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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# Internal API key for service-to-service auth
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INTERNAL_API_KEY = os.getenv("INTERNAL_API_KEY", "dev-internal-key-change-in-production")
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# Base demo tenant IDs
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DEMO_TENANT_SAN_PABLO = "a1b2c3d4-e5f6-47a8-b9c0-d1e2f3a4b5c6"
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DEMO_TENANT_LA_ESPIGA = "b2c3d4e5-f6a7-48b9-c0d1-e2f3a4b5c6d7"
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DEMO_TENANT_PROFESSIONAL = "a1b2c3d4-e5f6-47a8-b9c0-d1e2f3a4b5c6"
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def verify_internal_api_key(x_internal_api_key: Optional[str] = Header(None)):
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"""Verify internal API key for service-to-service communication"""
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if x_internal_api_key != INTERNAL_API_KEY:
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if x_internal_api_key != settings.INTERNAL_API_KEY:
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logger.warning("Unauthorized internal API access attempted")
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raise HTTPException(status_code=403, detail="Invalid internal API key")
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return True
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@@ -48,8 +48,7 @@ structlog.configure(
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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_SAN_PABLO = uuid.UUID("a1b2c3d4-e5f6-47a8-b9c0-d1e2f3a4b5c6")
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DEMO_TENANT_LA_ESPIGA = uuid.UUID("b2c3d4e5-f6a7-48b9-c0d1-e2f3a4b5c6d7")
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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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@@ -240,23 +239,12 @@ async def seed_sales(sales_db: AsyncSession):
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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_SAN_PABLO,
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"Panadería San Pablo (Traditional)",
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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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# Seed for La Espiga (Central Workshop) - 30 days of history (optimized for fast demo loading)
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result_la_espiga = await seed_sales_for_tenant(
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sales_db,
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DEMO_TENANT_LA_ESPIGA,
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"Panadería La Espiga (Central Workshop)",
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LA_ESPIGA_PRODUCTS,
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days_of_history=30
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)
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results.append(result_la_espiga)
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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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381
services/sales/scripts/demo/seed_demo_sales_retail.py
Normal file
381
services/sales/scripts/demo/seed_demo_sales_retail.py
Normal file
@@ -0,0 +1,381 @@
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Demo Retail Sales Seeding Script for Sales Service
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Creates realistic historical sales data for child retail outlets
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This script runs as a Kubernetes init job inside the sales-service container.
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It populates child retail tenants with 30 days of sales history.
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Usage:
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python /app/scripts/demo/seed_demo_sales_retail.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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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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# Add shared to path for demo utilities
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sys.path.insert(0, str(Path(__file__).parent.parent.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
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import structlog
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from shared.utils.demo_dates import BASE_REFERENCE_DATE
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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_CHILD_1 = uuid.UUID("d4e5f6a7-b8c9-40d1-e2f3-a4b5c6d7e8f9") # Madrid Centro
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DEMO_TENANT_CHILD_2 = uuid.UUID("e5f6a7b8-c9d0-41e2-f3a4-b5c6d7e8f9a0") # Barcelona Gràcia
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DEMO_TENANT_CHILD_3 = uuid.UUID("f6a7b8c9-d0e1-42f3-a4b5-c6d7e8f9a0b1") # Valencia Ruzafa
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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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# Retail sales patterns for each store
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# Madrid Centro - Large urban store, high traffic
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MADRID_CENTRO_PRODUCTS = [
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{"sku": "PRO-BAG-001", "name": "Baguette Tradicional", "avg_qty": 120, "variance": 20, "price": 1.30},
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{"sku": "PRO-CRO-001", "name": "Croissant de Mantequilla", "avg_qty": 80, "variance": 15, "price": 1.60},
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{"sku": "PRO-PUE-001", "name": "Pan de Pueblo", "avg_qty": 35, "variance": 8, "price": 3.80},
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{"sku": "PRO-NAP-001", "name": "Napolitana de Chocolate", "avg_qty": 60, "variance": 12, "price": 1.90},
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]
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# Barcelona Gràcia - Medium neighborhood store
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BARCELONA_GRACIA_PRODUCTS = [
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{"sku": "PRO-BAG-001", "name": "Baguette Tradicional", "avg_qty": 90, "variance": 15, "price": 1.25},
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{"sku": "PRO-CRO-001", "name": "Croissant de Mantequilla", "avg_qty": 60, "variance": 12, "price": 1.55},
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{"sku": "PRO-PUE-001", "name": "Pan de Pueblo", "avg_qty": 25, "variance": 6, "price": 3.70},
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{"sku": "PRO-NAP-001", "name": "Napolitana de Chocolate", "avg_qty": 45, "variance": 10, "price": 1.85},
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]
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# Valencia Ruzafa - Smaller boutique store
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VALENCIA_RUZAFA_PRODUCTS = [
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{"sku": "PRO-BAG-001", "name": "Baguette Tradicional", "avg_qty": 70, "variance": 12, "price": 1.20},
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{"sku": "PRO-CRO-001", "name": "Croissant de Mantequilla", "avg_qty": 45, "variance": 10, "price": 1.50},
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{"sku": "PRO-PUE-001", "name": "Pan de Pueblo", "avg_qty": 20, "variance": 5, "price": 3.60},
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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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# Child tenant configurations
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CHILD_TENANTS = [
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(DEMO_TENANT_CHILD_1, "Madrid Centro", MADRID_CENTRO_PRODUCTS),
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(DEMO_TENANT_CHILD_2, "Barcelona Gràcia", BARCELONA_GRACIA_PRODUCTS),
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(DEMO_TENANT_CHILD_3, "Valencia Ruzafa", VALENCIA_RUZAFA_PRODUCTS)
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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 XOR transformation
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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 using XOR (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_retail_sales_for_tenant(
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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 = 30
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) -> dict:
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"""
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Seed retail sales data for a specific child tenant
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Args:
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db: Database session
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tenant_id: UUID of the child 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 (default: 30)
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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 retail 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 (working backwards from BASE_REFERENCE_DATE)
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for days_ago in range(days_of_history, 0, -1):
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sale_date = BASE_REFERENCE_DATE - timedelta(days=days_ago)
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# Skip some random days to simulate closures/holidays (3% chance)
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if random.random() < 0.03:
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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 XOR transformation
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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 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 realistic 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 for bakeries)
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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(1.3, 1.6) # 30-60% more sales on weekends
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elif weekday == 4: # Friday
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multiplier = random.uniform(1.1, 1.3) # 10-30% more on Fridays
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else: # Weekdays
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multiplier = random.uniform(0.85, 1.15)
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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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# Determine if 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", # Retail outlets primarily use in-store sales
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location_id="main", # Single location per retail outlet
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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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db.add(sales_record)
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created_sales += 1
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logger.debug(
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f" ✅ {sale_date.strftime('%Y-%m-%d')}: {product_name} - "
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f"{quantity} units @ €{unit_price} = €{revenue:.2f}"
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)
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# Commit all changes for this tenant
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await db.commit()
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logger.info(f" 📊 Sales records 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_created": created_sales,
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"sales_skipped": skipped_sales,
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"days_of_history": days_of_history
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}
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async def seed_retail_sales(db: AsyncSession):
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"""
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Seed retail sales for all child tenant templates
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Args:
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db: 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 Retail Sales Seeding")
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logger.info("=" * 80)
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logger.info("Creating 30 days of sales history for retail outlets")
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logger.info("")
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results = []
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# Seed for each child retail outlet
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for child_tenant_id, child_tenant_name, product_patterns in CHILD_TENANTS:
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logger.info("")
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result = await seed_retail_sales_for_tenant(
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db,
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child_tenant_id,
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f"{child_tenant_name} (Retail Outlet)",
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product_patterns,
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days_of_history=30 # 30 days of sales history
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)
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results.append(result)
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# Calculate totals
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total_sales = sum(r["sales_created"] for r in results)
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total_skipped = sum(r["sales_skipped"] for r in results)
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logger.info("=" * 80)
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logger.info("✅ Demo Retail Sales Seeding Completed")
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logger.info("=" * 80)
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return {
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"service": "sales_retail",
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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 Retail 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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database_url = os.getenv("SALES_DATABASE_URL") or os.getenv("DATABASE_URL")
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if not 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 URL if needed
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if database_url.startswith("postgresql://"):
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database_url = 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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engine = create_async_engine(
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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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async_session = sessionmaker(
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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 async_session() as session:
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result = await seed_retail_sales(session)
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logger.info("")
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logger.info("📊 Retail Sales Seeding Summary:")
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logger.info(f" ✅ Retail outlets seeded: {result['tenants_seeded']}")
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logger.info(f" ✅ Total sales records: {result['total_sales_created']}")
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logger.info(f" ⏭️ Total 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_created']} sales records"
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)
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logger.info("")
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logger.info("🎉 Success! Retail sales history is ready for cloning.")
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logger.info("")
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logger.info("Sales characteristics:")
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logger.info(" ✓ 30 days of historical data")
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logger.info(" ✓ Weekend sales boost (30-60% higher)")
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logger.info(" ✓ Friday pre-weekend surge (10-30% higher)")
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logger.info(" ✓ Realistic variance per product")
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logger.info(" ✓ Store-specific pricing and volumes")
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logger.info("")
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logger.info("Next steps:")
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logger.info(" 1. Seed customer data")
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logger.info(" 2. Seed retail orders (internal transfers from parent)")
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logger.info(" 3. Test forecasting with retail sales data")
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logger.info("")
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return 0
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except Exception as e:
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||||
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