bakery-ia/services/production/app/api/batch.py

# services/production/app/api/batch.py
"""
Production Batch API - Batch operations for enterprise dashboards

Phase 2 optimization: Eliminate N+1 query patterns by fetching production data
for multiple tenants in a single request.
"""

from fastapi import APIRouter, Depends, HTTPException, Body
from typing import List, Dict, Any
from uuid import UUID
from pydantic import BaseModel, Field
import structlog
import asyncio

from fastapi import Request
from app.services.production_service import ProductionService
from app.core.config import settings
from shared.auth.decorators import get_current_user_dep

router = APIRouter(tags=["production-batch"])
logger = structlog.get_logger()


def get_production_service(request: Request) -> ProductionService:
    """Dependency injection for production service"""
    from app.core.database import database_manager
    notification_service = getattr(request.app.state, 'notification_service', None)
    return ProductionService(database_manager, settings, notification_service)


class ProductionSummaryBatchRequest(BaseModel):
    """Request model for batch production summary"""
    tenant_ids: List[str] = Field(..., description="List of tenant IDs", max_length=100)


class ProductionSummary(BaseModel):
    """Production summary for a single tenant"""
    tenant_id: str
    total_batches: int
    pending_batches: int
    in_progress_batches: int
    completed_batches: int
    on_hold_batches: int
    cancelled_batches: int
    total_planned_quantity: float
    total_actual_quantity: float
    efficiency_rate: float


@router.post("/batch/production-summary", response_model=Dict[str, ProductionSummary])
async def get_production_summary_batch(
    request: ProductionSummaryBatchRequest = Body(...),
    current_user: Dict[str, Any] = Depends(get_current_user_dep),
    production_service: ProductionService = Depends(get_production_service)
):
    """
    Get production summary for multiple tenants in a single request.

    Optimized for enterprise dashboards to eliminate N+1 query patterns.
    Fetches production data for all tenants in parallel.

    Args:
        request: Batch request with tenant IDs

    Returns:
        Dictionary mapping tenant_id -> production summary

    Example:
        POST /api/v1/production/batch/production-summary
        {
            "tenant_ids": ["tenant-1", "tenant-2", "tenant-3"]
        }

        Response:
        {
            "tenant-1": {"tenant_id": "tenant-1", "total_batches": 25, ...},
            "tenant-2": {"tenant_id": "tenant-2", "total_batches": 18, ...},
            "tenant-3": {"tenant_id": "tenant-3", "total_batches": 32, ...}
        }
    """
    try:
        if len(request.tenant_ids) > 100:
            raise HTTPException(
                status_code=400,
                detail="Maximum 100 tenant IDs allowed per batch request"
            )

        if not request.tenant_ids:
            return {}

        logger.info(
            "Batch fetching production summaries",
            tenant_count=len(request.tenant_ids)
        )

        async def fetch_tenant_production(tenant_id: str) -> tuple[str, ProductionSummary]:
            """Fetch production summary for a single tenant"""
            try:
                tenant_uuid = UUID(tenant_id)
                summary = await production_service.get_dashboard_summary(tenant_uuid)

                # Calculate efficiency rate
                efficiency_rate = 0.0
                if summary.total_planned_quantity > 0 and summary.total_actual_quantity is not None:
                    efficiency_rate = (summary.total_actual_quantity / summary.total_planned_quantity) * 100

                return tenant_id, ProductionSummary(
                    tenant_id=tenant_id,
                    total_batches=int(summary.total_batches or 0),
                    pending_batches=int(summary.pending_batches or 0),
                    in_progress_batches=int(summary.in_progress_batches or 0),
                    completed_batches=int(summary.completed_batches or 0),
                    on_hold_batches=int(summary.on_hold_batches or 0),
                    cancelled_batches=int(summary.cancelled_batches or 0),
                    total_planned_quantity=float(summary.total_planned_quantity or 0),
                    total_actual_quantity=float(summary.total_actual_quantity or 0),
                    efficiency_rate=efficiency_rate
                )
            except Exception as e:
                logger.warning(
                    "Failed to fetch production for tenant in batch",
                    tenant_id=tenant_id,
                    error=str(e)
                )
                return tenant_id, ProductionSummary(
                    tenant_id=tenant_id,
                    total_batches=0,
                    pending_batches=0,
                    in_progress_batches=0,
                    completed_batches=0,
                    on_hold_batches=0,
                    cancelled_batches=0,
                    total_planned_quantity=0.0,
                    total_actual_quantity=0.0,
                    efficiency_rate=0.0
                )

        # Fetch all tenant production data in parallel
        tasks = [fetch_tenant_production(tid) for tid in request.tenant_ids]
        results = await asyncio.gather(*tasks, return_exceptions=True)

        # Build result dictionary
        result_dict = {}
        for result in results:
            if isinstance(result, Exception):
                logger.error("Exception in batch production fetch", error=str(result))
                continue
            tenant_id, summary = result
            result_dict[tenant_id] = summary

        logger.info(
            "Batch production summaries retrieved",
            requested_count=len(request.tenant_ids),
            successful_count=len(result_dict)
        )

        return result_dict

    except HTTPException:
        raise
    except Exception as e:
        logger.error("Error in batch production summary", error=str(e), exc_info=True)
        raise HTTPException(
            status_code=500,
            detail=f"Failed to fetch batch production summaries: {str(e)}"
        )