303 lines
11 KiB
Python
Executable File
303 lines
11 KiB
Python
Executable File
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Demo Production Batches Seeding Script for Production Service
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Creates production batches for demo template tenants
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This script runs as a Kubernetes init job inside the production-service container.
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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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import json
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from datetime import datetime, timezone, timedelta
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from pathlib import Path
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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
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import structlog
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from app.models.production import ProductionBatch, ProductionStatus, ProductionPriority, ProcessStage
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# Configure logging
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logger = structlog.get_logger()
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# Base demo tenant IDs
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DEMO_TENANT_SAN_PABLO = uuid.UUID("a1b2c3d4-e5f6-47a8-b9c0-d1e2f3a4b5c6") # Individual bakery
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DEMO_TENANT_LA_ESPIGA = uuid.UUID("b2c3d4e5-f6a7-48b9-c0d1-e2f3a4b5c6d7") # Central bakery
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# Base reference date for date calculations
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BASE_REFERENCE_DATE = datetime(2025, 1, 15, 12, 0, 0, tzinfo=timezone.utc)
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def load_batches_data():
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"""Load production batches data from JSON file"""
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data_file = Path(__file__).parent / "lotes_produccion_es.json"
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if not data_file.exists():
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raise FileNotFoundError(f"Production batches data file not found: {data_file}")
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with open(data_file, 'r', encoding='utf-8') as f:
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return json.load(f)
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def calculate_datetime_from_offset(offset_days: int, hour: int, minute: int) -> datetime:
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"""Calculate a datetime based on offset from BASE_REFERENCE_DATE"""
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base_date = BASE_REFERENCE_DATE.replace(hour=hour, minute=minute, second=0, microsecond=0)
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return base_date + timedelta(days=offset_days)
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def map_status(status_str: str) -> ProductionStatus:
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"""Map status string to enum"""
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mapping = {
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"PENDING": ProductionStatus.PENDING,
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"IN_PROGRESS": ProductionStatus.IN_PROGRESS,
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"COMPLETED": ProductionStatus.COMPLETED,
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"CANCELLED": ProductionStatus.CANCELLED,
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"ON_HOLD": ProductionStatus.ON_HOLD,
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"QUALITY_CHECK": ProductionStatus.QUALITY_CHECK,
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"FAILED": ProductionStatus.FAILED
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}
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return mapping.get(status_str, ProductionStatus.PENDING)
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def map_priority(priority_str: str) -> ProductionPriority:
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"""Map priority string to enum"""
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mapping = {
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"LOW": ProductionPriority.LOW,
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"MEDIUM": ProductionPriority.MEDIUM,
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"HIGH": ProductionPriority.HIGH,
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"URGENT": ProductionPriority.URGENT
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}
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return mapping.get(priority_str, ProductionPriority.MEDIUM)
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def map_process_stage(stage_str: str) -> ProcessStage:
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"""Map process stage string to enum"""
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if not stage_str:
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return None
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mapping = {
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"mixing": ProcessStage.MIXING,
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"proofing": ProcessStage.PROOFING,
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"shaping": ProcessStage.SHAPING,
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"baking": ProcessStage.BAKING,
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"cooling": ProcessStage.COOLING,
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"packaging": ProcessStage.PACKAGING,
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"finishing": ProcessStage.FINISHING
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}
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return mapping.get(stage_str, None)
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async def seed_batches_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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batches_list: list
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):
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"""Seed production batches for a specific tenant"""
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logger.info(f"Seeding production batches for: {tenant_name}", tenant_id=str(tenant_id))
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# Check if batches already exist
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result = await db.execute(
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select(ProductionBatch).where(ProductionBatch.tenant_id == tenant_id).limit(1)
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)
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existing = result.scalar_one_or_none()
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if existing:
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logger.info(f"Production batches already exist for {tenant_name}, skipping seed")
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return {"tenant_id": str(tenant_id), "batches_created": 0, "skipped": True}
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count = 0
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for batch_data in batches_list:
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# Calculate planned start and end times
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planned_start = calculate_datetime_from_offset(
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batch_data["planned_start_offset_days"],
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batch_data["planned_start_hour"],
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batch_data["planned_start_minute"]
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)
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planned_end = planned_start + timedelta(minutes=batch_data["planned_duration_minutes"])
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# Calculate actual times for completed batches
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actual_start = None
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actual_end = None
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completed_at = None
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actual_duration = None
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if batch_data["status"] in ["COMPLETED", "QUALITY_CHECK"]:
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actual_start = planned_start # Assume started on time
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actual_duration = batch_data["planned_duration_minutes"]
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actual_end = actual_start + timedelta(minutes=actual_duration)
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completed_at = actual_end
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elif batch_data["status"] == "IN_PROGRESS":
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actual_start = planned_start
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actual_duration = None
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actual_end = None
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# For San Pablo, use original IDs. For La Espiga, generate new UUIDs
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if tenant_id == DEMO_TENANT_SAN_PABLO:
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batch_id = uuid.UUID(batch_data["id"])
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else:
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# Generate deterministic UUID for La Espiga based on original ID
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base_uuid = uuid.UUID(batch_data["id"])
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# Add a fixed offset to create a unique but deterministic ID
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batch_id = uuid.UUID(int=base_uuid.int + 0x10000000000000000000000000000000)
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# Map enums
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status = map_status(batch_data["status"])
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priority = map_priority(batch_data["priority"])
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current_stage = map_process_stage(batch_data.get("current_process_stage"))
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# Create unique batch number for each tenant
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if tenant_id == DEMO_TENANT_SAN_PABLO:
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batch_number = batch_data["batch_number"]
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else:
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# For La Espiga, append tenant suffix to make batch number unique
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batch_number = batch_data["batch_number"] + "-LE"
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# Create production batch
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batch = ProductionBatch(
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id=batch_id,
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tenant_id=tenant_id,
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batch_number=batch_number,
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product_id=uuid.UUID(batch_data["product_id"]),
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product_name=batch_data["product_name"],
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recipe_id=uuid.UUID(batch_data["recipe_id"]) if batch_data.get("recipe_id") else None,
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planned_start_time=planned_start,
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planned_end_time=planned_end,
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planned_quantity=batch_data["planned_quantity"],
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planned_duration_minutes=batch_data["planned_duration_minutes"],
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actual_start_time=actual_start,
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actual_end_time=actual_end,
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actual_quantity=batch_data.get("actual_quantity"),
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actual_duration_minutes=actual_duration,
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status=status,
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priority=priority,
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current_process_stage=current_stage,
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yield_percentage=batch_data.get("yield_percentage"),
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quality_score=batch_data.get("quality_score"),
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waste_quantity=batch_data.get("waste_quantity"),
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defect_quantity=batch_data.get("defect_quantity"),
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estimated_cost=batch_data.get("estimated_cost"),
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actual_cost=batch_data.get("actual_cost"),
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labor_cost=batch_data.get("labor_cost"),
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material_cost=batch_data.get("material_cost"),
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overhead_cost=batch_data.get("overhead_cost"),
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equipment_used=batch_data.get("equipment_used"),
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station_id=batch_data.get("station_id"),
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is_rush_order=batch_data.get("is_rush_order", False),
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is_special_recipe=batch_data.get("is_special_recipe", False),
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production_notes=batch_data.get("production_notes"),
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quality_notes=batch_data.get("quality_notes"),
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created_at=BASE_REFERENCE_DATE,
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updated_at=BASE_REFERENCE_DATE,
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completed_at=completed_at
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)
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db.add(batch)
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count += 1
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logger.debug(f"Created production batch: {batch.batch_number}", batch_id=str(batch.id))
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await db.commit()
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logger.info(f"Successfully created {count} production batches for {tenant_name}")
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return {
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"tenant_id": str(tenant_id),
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"batches_created": count,
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"skipped": False
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}
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async def seed_all(db: AsyncSession):
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"""Seed all demo tenants with production batches"""
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logger.info("Starting demo production batches seed process")
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# Load batches data
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data = load_batches_data()
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results = []
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# Both tenants get the same production batches
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result_san_pablo = await seed_batches_for_tenant(
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db,
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DEMO_TENANT_SAN_PABLO,
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"San Pablo - Individual Bakery",
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data["lotes_produccion"]
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)
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results.append(result_san_pablo)
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result_la_espiga = await seed_batches_for_tenant(
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db,
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DEMO_TENANT_LA_ESPIGA,
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"La Espiga - Central Bakery",
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data["lotes_produccion"]
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)
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results.append(result_la_espiga)
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total_created = sum(r["batches_created"] for r in results)
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return {
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"results": results,
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"total_batches_created": total_created,
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"status": "completed"
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}
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async def main():
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"""Main execution function"""
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# Get database URL from environment
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database_url = os.getenv("PRODUCTION_DATABASE_URL")
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if not database_url:
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logger.error("PRODUCTION_DATABASE_URL environment variable must be set")
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return 1
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# Ensure asyncpg driver
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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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# Create async engine
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engine = create_async_engine(database_url, echo=False)
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async_session = sessionmaker(engine, class_=AsyncSession, expire_on_commit=False)
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try:
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async with async_session() as session:
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result = await seed_all(session)
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logger.info(
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"Production batches seed completed successfully!",
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total_batches=result["total_batches_created"],
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status=result["status"]
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)
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# Print summary
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print("\n" + "="*60)
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print("DEMO PRODUCTION BATCHES SEED SUMMARY")
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print("="*60)
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for tenant_result in result["results"]:
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tenant_id = tenant_result["tenant_id"]
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count = tenant_result["batches_created"]
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skipped = tenant_result.get("skipped", False)
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status = "SKIPPED (already exists)" if skipped else f"CREATED {count} batches"
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print(f"Tenant {tenant_id}: {status}")
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print(f"\nTotal Batches Created: {result['total_batches_created']}")
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print("="*60 + "\n")
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return 0
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except Exception as e:
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logger.error(f"Production batches seed failed: {str(e)}", exc_info=True)
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return 1
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finally:
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await engine.dispose()
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if __name__ == "__main__":
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exit_code = asyncio.run(main())
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sys.exit(exit_code)
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