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bakery-ia/services/procurement/scripts/demo/seed_demo_procurement_plans.py

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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
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Demo Procurement Plans Seeding Script for Procurement Service
Creates realistic procurement plans for demo template tenants using pre-defined UUIDs
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This script runs as a Kubernetes init job inside the procurement-service container.
It populates the template tenants with comprehensive procurement plans.
Usage:
python /app/scripts/demo/seed_demo_procurement_plans.py
Environment Variables Required:
PROCUREMENT_DATABASE_URL - PostgreSQL connection string for procurement database
DEMO_MODE - Set to 'production' for production seeding
LOG_LEVEL - Logging level (default: INFO)
Note: No database lookups needed - all IDs are pre-defined in the JSON file
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"""
import asyncio
import uuid
import sys
import os
import json
from datetime import datetime, timezone, timedelta, date
from pathlib import Path
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import random
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from decimal import Decimal
# Add app to path
sys.path.insert(0, str(Path(__file__).parent.parent.parent))
from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine
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.procurement_plan import ProcurementPlan, ProcurementRequirement
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# Configure logging
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structlog.configure(
processors=[
structlog.stdlib.add_log_level,
structlog.processors.TimeStamper(fmt="iso"),
structlog.dev.ConsoleRenderer()
]
)
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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") # Individual bakery
DEMO_TENANT_LA_ESPIGA = uuid.UUID("b2c3d4e5-f6a7-48b9-c0d1-e2f3a4b5c6d7") # Central bakery
# Base reference date for date calculations
BASE_REFERENCE_DATE = datetime(2025, 1, 15, 12, 0, 0, tzinfo=timezone.utc)
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# Hardcoded SKU to Ingredient ID mapping (no database lookups needed!)
INGREDIENT_ID_MAP = {
"HAR-T55-001": "10000000-0000-0000-0000-000000000001",
"HAR-T65-002": "10000000-0000-0000-0000-000000000002",
"HAR-FUE-003": "10000000-0000-0000-0000-000000000003",
"HAR-INT-004": "10000000-0000-0000-0000-000000000004",
"HAR-CEN-005": "10000000-0000-0000-0000-000000000005",
"HAR-ESP-006": "10000000-0000-0000-0000-000000000006",
"LAC-MAN-001": "10000000-0000-0000-0000-000000000011",
"LAC-LEC-002": "10000000-0000-0000-0000-000000000012",
"LAC-NAT-003": "10000000-0000-0000-0000-000000000013",
"LAC-HUE-004": "10000000-0000-0000-0000-000000000014",
"LEV-FRE-001": "10000000-0000-0000-0000-000000000021",
"LEV-SEC-002": "10000000-0000-0000-0000-000000000022",
"BAS-SAL-001": "10000000-0000-0000-0000-000000000031",
"BAS-AZU-002": "10000000-0000-0000-0000-000000000032",
"ESP-CHO-001": "10000000-0000-0000-0000-000000000041",
"ESP-ALM-002": "10000000-0000-0000-0000-000000000042",
"ESP-VAI-004": "10000000-0000-0000-0000-000000000044",
"ESP-CRE-005": "10000000-0000-0000-0000-000000000045",
}
# Ingredient costs (for requirement generation)
INGREDIENT_COSTS = {
"HAR-T55-001": 0.85,
"HAR-T65-002": 0.95,
"HAR-FUE-003": 1.15,
"HAR-INT-004": 1.20,
"HAR-CEN-005": 1.30,
"HAR-ESP-006": 2.45,
"LAC-MAN-001": 6.50,
"LAC-LEC-002": 0.95,
"LAC-NAT-003": 3.20,
"LAC-HUE-004": 0.25,
"LEV-FRE-001": 4.80,
"LEV-SEC-002": 12.50,
"BAS-SAL-001": 0.60,
"BAS-AZU-002": 0.90,
"ESP-CHO-001": 15.50,
"ESP-ALM-002": 8.90,
"ESP-VAI-004": 3.50,
"ESP-CRE-005": 7.20,
}
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def calculate_date_from_offset(offset_days: int) -> date:
"""Calculate a date based on offset from BASE_REFERENCE_DATE"""
return (BASE_REFERENCE_DATE + timedelta(days=offset_days)).date()
def calculate_datetime_from_offset(offset_days: int) -> datetime:
"""Calculate a datetime based on offset from BASE_REFERENCE_DATE"""
return BASE_REFERENCE_DATE + timedelta(days=offset_days)
def weighted_choice(choices: list) -> dict:
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"""Make a weighted random choice from list of dicts with 'weight' key"""
total_weight = sum(c.get("weight", 1.0) for c in choices)
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r = random.uniform(0, total_weight)
cumulative = 0
for choice in choices:
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cumulative += choice.get("weight", 1.0)
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if r <= cumulative:
return choice
return choices[-1]
def generate_plan_number(tenant_id: uuid.UUID, index: int, plan_type: str) -> str:
"""Generate a unique plan number"""
tenant_prefix = "SP" if tenant_id == DEMO_TENANT_SAN_PABLO else "LE"
type_code = plan_type[0:3].upper()
return f"PROC-{tenant_prefix}-{type_code}-{BASE_REFERENCE_DATE.year}-{index:03d}"
async def generate_procurement_for_tenant(
db: AsyncSession,
tenant_id: uuid.UUID,
tenant_name: str,
business_model: str,
config: dict
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) -> dict:
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"""Generate procurement plans and requirements for a specific tenant"""
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logger.info("" * 80)
logger.info(f"Generating procurement data for: {tenant_name}")
logger.info(f"Tenant ID: {tenant_id}")
logger.info("" * 80)
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# Check if procurement plans already exist
result = await db.execute(
select(ProcurementPlan).where(ProcurementPlan.tenant_id == tenant_id).limit(1)
)
existing = result.scalar_one_or_none()
if existing:
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logger.info(f" ⏭️ Procurement plans already exist for {tenant_name}, skipping seed")
return {
"tenant_id": str(tenant_id),
"plans_created": 0,
"requirements_created": 0,
"skipped": True
}
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proc_config = config["procurement_config"]
total_plans = proc_config["plans_per_tenant"]
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plans_created = 0
requirements_created = 0
for i in range(total_plans):
# Determine temporal distribution
rand_temporal = random.random()
cumulative = 0
temporal_category = None
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for category, details in proc_config["temporal_distribution"].items():
cumulative += details["percentage"]
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if rand_temporal <= cumulative:
temporal_category = details
break
if not temporal_category:
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temporal_category = proc_config["temporal_distribution"]["completed"]
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# Calculate plan date
offset_days = random.randint(
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temporal_category["offset_days_min"],
temporal_category["offset_days_max"]
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)
plan_date = calculate_date_from_offset(offset_days)
# Select status
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status = random.choice(temporal_category["statuses"])
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# Select plan type
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plan_type_choice = weighted_choice(proc_config["plan_types"])
plan_type = plan_type_choice["type"]
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# Select priority
priority_rand = random.random()
cumulative_priority = 0
priority = "normal"
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for p, weight in proc_config["priorities"].items():
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cumulative_priority += weight
if priority_rand <= cumulative_priority:
priority = p
break
# Select procurement strategy
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strategy_choice = weighted_choice(proc_config["procurement_strategies"])
procurement_strategy = strategy_choice["strategy"]
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# Select supply risk level
risk_rand = random.random()
cumulative_risk = 0
supply_risk_level = "low"
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for risk, weight in proc_config["risk_levels"].items():
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cumulative_risk += weight
if risk_rand <= cumulative_risk:
supply_risk_level = risk
break
# Calculate planning horizon
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planning_horizon = proc_config["planning_horizon_days"][business_model]
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# Calculate period dates
period_start = plan_date
period_end = plan_date + timedelta(days=planning_horizon)
# Generate plan number
plan_number = generate_plan_number(tenant_id, i + 1, plan_type)
# Calculate safety stock buffer
safety_stock_buffer = Decimal(str(random.uniform(
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proc_config["safety_stock_percentage"]["min"],
proc_config["safety_stock_percentage"]["max"]
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)))
# Calculate approval/execution dates based on status
approved_at = None
execution_started_at = None
execution_completed_at = None
approved_by = None
if status in ["approved", "in_execution", "completed"]:
approved_at = calculate_datetime_from_offset(offset_days - 1)
approved_by = uuid.uuid4() # Would be actual user ID
if status in ["in_execution", "completed"]:
execution_started_at = calculate_datetime_from_offset(offset_days)
if status == "completed":
execution_completed_at = calculate_datetime_from_offset(offset_days + planning_horizon)
# Calculate performance metrics for completed plans
fulfillment_rate = None
on_time_delivery_rate = None
cost_accuracy = None
quality_score = None
if status == "completed":
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metrics = proc_config["performance_metrics"]
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fulfillment_rate = Decimal(str(random.uniform(
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metrics["fulfillment_rate"]["min"],
metrics["fulfillment_rate"]["max"]
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)))
on_time_delivery_rate = Decimal(str(random.uniform(
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metrics["on_time_delivery"]["min"],
metrics["on_time_delivery"]["max"]
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)))
cost_accuracy = Decimal(str(random.uniform(
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metrics["cost_accuracy"]["min"],
metrics["cost_accuracy"]["max"]
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)))
quality_score = Decimal(str(random.uniform(
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metrics["quality_score"]["min"],
metrics["quality_score"]["max"]
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)))
# Create procurement plan
plan = ProcurementPlan(
id=uuid.uuid4(),
tenant_id=tenant_id,
plan_number=plan_number,
plan_date=plan_date,
plan_period_start=period_start,
plan_period_end=period_end,
planning_horizon_days=planning_horizon,
status=status,
plan_type=plan_type,
priority=priority,
business_model=business_model,
procurement_strategy=procurement_strategy,
total_requirements=0, # Will update after adding requirements
total_estimated_cost=Decimal("0.00"), # Will calculate
total_approved_cost=Decimal("0.00"),
safety_stock_buffer=safety_stock_buffer,
supply_risk_level=supply_risk_level,
demand_forecast_confidence=Decimal(str(random.uniform(7.0, 9.5))),
approved_at=approved_at,
approved_by=approved_by,
execution_started_at=execution_started_at,
execution_completed_at=execution_completed_at,
fulfillment_rate=fulfillment_rate,
on_time_delivery_rate=on_time_delivery_rate,
cost_accuracy=cost_accuracy,
quality_score=quality_score,
created_at=calculate_datetime_from_offset(offset_days - 2),
updated_at=calculate_datetime_from_offset(offset_days)
)
db.add(plan)
await db.flush() # Get plan ID
# Generate requirements for this plan
num_requirements = random.randint(
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proc_config["requirements_per_plan"]["min"],
proc_config["requirements_per_plan"]["max"]
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)
# Select random ingredients
selected_ingredients = random.sample(
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list(INGREDIENT_ID_MAP.keys()),
min(num_requirements, len(INGREDIENT_ID_MAP))
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)
total_estimated_cost = Decimal("0.00")
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for req_num, ingredient_sku in enumerate(selected_ingredients, 1):
# Get ingredient ID from hardcoded mapping
ingredient_id_str = INGREDIENT_ID_MAP.get(ingredient_sku)
if not ingredient_id_str:
logger.warning(f" ⚠️ Ingredient SKU not in mapping: {ingredient_sku}")
continue
# Generate tenant-specific ingredient ID
base_ingredient_id = uuid.UUID(ingredient_id_str)
tenant_int = int(tenant_id.hex, 16)
ingredient_id = uuid.UUID(int=tenant_int ^ int(base_ingredient_id.hex, 16))
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# Get quantity range for category
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category = ingredient_sku.split("-")[0] # HAR, LAC, LEV, BAS, ESP
cantidad_range = proc_config["quantity_ranges"].get(
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category,
{"min": 50.0, "max": 200.0}
)
# Calculate required quantity
required_quantity = Decimal(str(random.uniform(
cantidad_range["min"],
cantidad_range["max"]
)))
# Calculate safety stock
safety_stock_quantity = required_quantity * (safety_stock_buffer / 100)
# Total quantity needed
total_quantity_needed = required_quantity + safety_stock_quantity
# Current stock simulation
current_stock_level = required_quantity * Decimal(str(random.uniform(0.1, 0.4)))
reserved_stock = current_stock_level * Decimal(str(random.uniform(0.0, 0.3)))
available_stock = current_stock_level - reserved_stock
# Net requirement
net_requirement = total_quantity_needed - available_stock
# Demand breakdown
order_demand = required_quantity * Decimal(str(random.uniform(0.5, 0.7)))
production_demand = required_quantity * Decimal(str(random.uniform(0.2, 0.4)))
forecast_demand = required_quantity * Decimal(str(random.uniform(0.05, 0.15)))
buffer_demand = safety_stock_quantity
# Pricing
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estimated_unit_cost = Decimal(str(INGREDIENT_COSTS.get(ingredient_sku, 1.0))) * Decimal(str(random.uniform(0.95, 1.05)))
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estimated_total_cost = estimated_unit_cost * net_requirement
# Timing
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lead_time_days = random.randint(1, 5)
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required_by_date = period_start + timedelta(days=random.randint(3, planning_horizon - 2))
lead_time_buffer_days = random.randint(1, 2)
suggested_order_date = required_by_date - timedelta(days=lead_time_days + lead_time_buffer_days)
latest_order_date = required_by_date - timedelta(days=lead_time_days)
# Requirement status based on plan status
if status == "draft":
req_status = "pending"
elif status == "pending_approval":
req_status = "pending"
elif status == "approved":
req_status = "approved"
elif status == "in_execution":
req_status = random.choice(["ordered", "partially_received"])
elif status == "completed":
req_status = "received"
else:
req_status = "pending"
# Requirement priority
if priority == "critical":
req_priority = "critical"
elif priority == "high":
req_priority = random.choice(["high", "critical"])
else:
req_priority = random.choice(["normal", "high"])
# Risk level
if supply_risk_level == "critical":
req_risk_level = random.choice(["high", "critical"])
elif supply_risk_level == "high":
req_risk_level = random.choice(["medium", "high"])
else:
req_risk_level = "low"
# Create requirement
requirement = ProcurementRequirement(
id=uuid.uuid4(),
plan_id=plan.id,
requirement_number=f"{plan_number}-REQ-{req_num:03d}",
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product_id=ingredient_id,
product_name=f"Ingrediente {ingredient_sku}",
product_sku=ingredient_sku,
product_category=category,
product_type="ingredient",
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required_quantity=required_quantity,
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unit_of_measure="kg",
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safety_stock_quantity=safety_stock_quantity,
total_quantity_needed=total_quantity_needed,
current_stock_level=current_stock_level,
reserved_stock=reserved_stock,
available_stock=available_stock,
net_requirement=net_requirement,
order_demand=order_demand,
production_demand=production_demand,
forecast_demand=forecast_demand,
buffer_demand=buffer_demand,
supplier_lead_time_days=lead_time_days,
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minimum_order_quantity=Decimal(str(random.choice([1, 5, 10, 25]))),
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estimated_unit_cost=estimated_unit_cost,
estimated_total_cost=estimated_total_cost,
required_by_date=required_by_date,
lead_time_buffer_days=lead_time_buffer_days,
suggested_order_date=suggested_order_date,
latest_order_date=latest_order_date,
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shelf_life_days=random.choice([30, 60, 90, 180, 365]),
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status=req_status,
priority=req_priority,
risk_level=req_risk_level,
created_at=plan.created_at,
updated_at=plan.updated_at
)
db.add(requirement)
total_estimated_cost += estimated_total_cost
requirements_created += 1
# Update plan totals
plan.total_requirements = num_requirements
plan.total_estimated_cost = total_estimated_cost
if status in ["approved", "in_execution", "completed"]:
plan.total_approved_cost = total_estimated_cost * Decimal(str(random.uniform(0.95, 1.05)))
plans_created += 1
await db.commit()
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logger.info(f" 📊 Successfully created {plans_created} plans with {requirements_created} requirements for {tenant_name}")
logger.info("")
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return {
"tenant_id": str(tenant_id),
"plans_created": plans_created,
"requirements_created": requirements_created,
"skipped": False
}
async def seed_all(db: AsyncSession):
"""Seed all demo tenants with procurement data"""
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logger.info("=" * 80)
logger.info("🚚 Starting Demo Procurement Plans Seeding")
logger.info("=" * 80)
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# Load configuration
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config = {
"procurement_config": {
"plans_per_tenant": 8,
"requirements_per_plan": {"min": 3, "max": 8},
"planning_horizon_days": {
"individual_bakery": 30,
"central_bakery": 45
},
"safety_stock_percentage": {"min": 15.0, "max": 25.0},
"temporal_distribution": {
"completed": {
"percentage": 0.3,
"offset_days_min": -15,
"offset_days_max": -1,
"statuses": ["completed"]
},
"in_execution": {
"percentage": 0.2,
"offset_days_min": -5,
"offset_days_max": 2,
"statuses": ["in_execution", "partially_received"]
},
"approved": {
"percentage": 0.2,
"offset_days_min": -2,
"offset_days_max": 1,
"statuses": ["approved"]
},
"pending_approval": {
"percentage": 0.15,
"offset_days_min": 0,
"offset_days_max": 3,
"statuses": ["pending_approval"]
},
"draft": {
"percentage": 0.15,
"offset_days_min": 0,
"offset_days_max": 5,
"statuses": ["draft"]
}
},
"plan_types": [
{"type": "regular", "weight": 0.7},
{"type": "seasonal", "weight": 0.2},
{"type": "emergency", "weight": 0.1}
],
"priorities": {
"normal": 0.7,
"high": 0.25,
"critical": 0.05
},
"procurement_strategies": [
{"strategy": "just_in_time", "weight": 0.6},
{"strategy": "bulk", "weight": 0.3},
{"strategy": "mixed", "weight": 0.1}
],
"risk_levels": {
"low": 0.6,
"medium": 0.3,
"high": 0.08,
"critical": 0.02
},
"quantity_ranges": {
"HAR": {"min": 50.0, "max": 500.0}, # Harinas
"LAC": {"min": 20.0, "max": 200.0}, # Lácteos
"LEV": {"min": 5.0, "max": 50.0}, # Levaduras
"BAS": {"min": 10.0, "max": 100.0}, # Básicos
"ESP": {"min": 1.0, "max": 20.0} # Especiales
},
"performance_metrics": {
"fulfillment_rate": {"min": 85.0, "max": 98.0},
"on_time_delivery": {"min": 80.0, "max": 95.0},
"cost_accuracy": {"min": 90.0, "max": 99.0},
"quality_score": {"min": 7.0, "max": 9.5}
}
}
}
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results = []
# Seed San Pablo (Individual Bakery)
result_san_pablo = await generate_procurement_for_tenant(
db,
DEMO_TENANT_SAN_PABLO,
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"Panadería San Pablo (Individual Bakery)",
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"individual_bakery",
config
)
results.append(result_san_pablo)
# Seed La Espiga (Central Bakery)
result_la_espiga = await generate_procurement_for_tenant(
db,
DEMO_TENANT_LA_ESPIGA,
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"Panadería La Espiga (Central Bakery)",
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"central_bakery",
config
)
results.append(result_la_espiga)
total_plans = sum(r["plans_created"] for r in results)
total_requirements = sum(r["requirements_created"] for r in results)
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logger.info("=" * 80)
logger.info("✅ Demo Procurement Plans Seeding Completed")
logger.info("=" * 80)
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return {
"results": results,
"total_plans_created": total_plans,
"total_requirements_created": total_requirements,
"status": "completed"
}
async def main():
"""Main execution function"""
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logger.info("Demo Procurement Plans Seeding Script Starting")
logger.info("Mode: %s", os.getenv("DEMO_MODE", "development"))
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("PROCUREMENT_DATABASE_URL") or os.getenv("DATABASE_URL")
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if not database_url:
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logger.error("❌ PROCUREMENT_DATABASE_URL or DATABASE_URL environment variable must be set")
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return 1
# Ensure asyncpg driver
if database_url.startswith("postgresql://"):
database_url = database_url.replace("postgresql://", "postgresql+asyncpg://", 1)
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logger.info("Connecting to procurement database")
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# Create async engine
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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
)
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try:
async with async_session() as session:
result = await seed_all(session)
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logger.info("")
logger.info("📊 Seeding Summary:")
logger.info(f" ✅ Total Plans: {result['total_plans_created']}")
logger.info(f" ✅ Total Requirements: {result['total_requirements_created']}")
logger.info(f" ✅ Status: {result['status']}")
logger.info("")
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# Print per-tenant details
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for tenant_result in result["results"]:
tenant_id = tenant_result["tenant_id"]
plans = tenant_result["plans_created"]
requirements = tenant_result["requirements_created"]
skipped = tenant_result.get("skipped", False)
status = "SKIPPED (already exists)" if skipped else f"CREATED {plans} plans, {requirements} requirements"
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logger.info(f" Tenant {tenant_id}: {status}")
logger.info("")
logger.info("🎉 Success! Procurement plans are ready for demo sessions.")
logger.info("")
logger.info("Plans created:")
logger.info(" • 8 Regular procurement plans per tenant")
logger.info(" • 3-8 Requirements per plan")
logger.info(" • Various statuses: draft, pending, approved, in execution, completed")
logger.info(" • Different priorities and risk levels")
logger.info("")
logger.info("Note: All IDs are pre-defined and hardcoded for cross-service consistency")
logger.info("")
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return 0
except Exception as e:
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logger.error("=" * 80)
logger.error("❌ Demo Procurement Plans Seeding Failed")
logger.error("=" * 80)
logger.error("Error: %s", str(e))
logger.error("", exc_info=True)
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return 1
finally:
await engine.dispose()
if __name__ == "__main__":
exit_code = asyncio.run(main())
sys.exit(exit_code)