Initial commit - production deployment
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344
shared/clients/sales_client.py
Executable file
344
shared/clients/sales_client.py
Executable file
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# shared/clients/sales_client.py
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"""
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Sales Service Client
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Handles all API calls to the sales service
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"""
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import httpx
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import structlog
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from datetime import date
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from typing import Dict, Any, Optional, List, Union
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from .base_service_client import BaseServiceClient
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from shared.config.base import BaseServiceSettings
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logger = structlog.get_logger()
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class SalesServiceClient(BaseServiceClient):
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"""Client for communicating with the sales service"""
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def __init__(self, config: BaseServiceSettings, calling_service_name: str = "unknown"):
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super().__init__(calling_service_name, config)
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self.service_url = config.SALES_SERVICE_URL
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def get_service_base_path(self) -> str:
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return "/api/v1"
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# ================================================================
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# SALES DATA (with advanced pagination support)
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# ================================================================
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async def get_sales_data(
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self,
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tenant_id: str,
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start_date: Optional[str] = None,
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end_date: Optional[str] = None,
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product_id: Optional[str] = None,
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aggregation: str = "daily"
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) -> Optional[List[Dict[str, Any]]]:
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"""Get sales data for a date range"""
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params = {"aggregation": aggregation}
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if start_date:
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params["start_date"] = start_date
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if end_date:
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params["end_date"] = end_date
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if product_id:
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params["product_id"] = product_id
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result = await self.get("sales/sales", tenant_id=tenant_id, params=params)
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# Handle both list and dict responses
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if result is None:
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return None
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elif isinstance(result, list):
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return result
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elif isinstance(result, dict):
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return result.get("sales", [])
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else:
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return None
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async def get_all_sales_data(
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self,
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tenant_id: str,
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start_date: Optional[str] = None,
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end_date: Optional[str] = None,
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product_id: Optional[str] = None,
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aggregation: str = "daily",
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page_size: int = 1000,
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max_pages: int = 100
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) -> List[Dict[str, Any]]:
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"""
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Get ALL sales data using pagination (equivalent to original fetch_sales_data)
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Retrieves all records without pagination limits
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"""
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params = {"aggregation": aggregation}
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if start_date:
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params["start_date"] = start_date
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if end_date:
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params["end_date"] = end_date
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if product_id:
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params["product_id"] = product_id
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# Use the inherited paginated request method
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try:
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all_records = await self.get_paginated(
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"sales/sales",
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tenant_id=tenant_id,
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params=params,
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page_size=page_size,
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max_pages=max_pages,
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timeout=2000.0
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)
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logger.info(f"Successfully fetched {len(all_records)} total sales records via sales service",
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tenant_id=tenant_id)
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return all_records
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except Exception as e:
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logger.error(f"Failed to fetch paginated sales data: {e}")
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return []
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async def upload_sales_data(
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self,
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tenant_id: str,
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sales_data: List[Dict[str, Any]]
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) -> Optional[Dict[str, Any]]:
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"""Upload sales data"""
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data = {"sales": sales_data}
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return await self.post("sales/sales", data=data, tenant_id=tenant_id)
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# ================================================================
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# PRODUCTS
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# ================================================================
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async def get_products(self, tenant_id: str) -> Optional[List[Dict[str, Any]]]:
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"""Get all products for a tenant"""
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result = await self.get("sales/products", tenant_id=tenant_id)
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return result.get("products", []) if result else None
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async def get_product(self, tenant_id: str, product_id: str) -> Optional[Dict[str, Any]]:
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"""Get a specific product"""
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return await self.get(f"sales/products/{product_id}", tenant_id=tenant_id)
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async def create_product(
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self,
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tenant_id: str,
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name: str,
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category: str,
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price: float,
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**kwargs
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) -> Optional[Dict[str, Any]]:
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"""Create a new product"""
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data = {
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"name": name,
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"category": category,
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"price": price,
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**kwargs
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}
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return await self.post("sales/products", data=data, tenant_id=tenant_id)
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async def update_product(
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self,
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tenant_id: str,
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product_id: str,
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**updates
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) -> Optional[Dict[str, Any]]:
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"""Update a product"""
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return await self.put(f"sales/products/{product_id}", data=updates, tenant_id=tenant_id)
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async def create_sales_record(
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self,
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tenant_id: str,
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sales_data: Dict[str, Any]
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) -> Optional[Dict[str, Any]]:
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"""Create a new sales record
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Args:
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tenant_id: Tenant ID
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sales_data: Sales record data including:
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- inventory_product_id: Optional UUID for inventory tracking
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- product_name: Product name
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- product_category: Product category
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- quantity_sold: Quantity sold
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- unit_price: Unit price
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- total_amount: Total amount
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- sale_date: Sale date (YYYY-MM-DD)
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- sales_channel: Sales channel (retail, wholesale, online, pos, etc.)
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- source: Data source (manual, pos_sync, import, etc.)
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- payment_method: Payment method
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- notes: Optional notes
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Returns:
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Created sales record or None if failed
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"""
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try:
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result = await self.post("sales/sales", data=sales_data, tenant_id=tenant_id)
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if result:
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logger.info("Created sales record via client",
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tenant_id=tenant_id,
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product=sales_data.get("product_name"))
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return result
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except Exception as e:
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logger.error("Failed to create sales record",
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error=str(e),
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tenant_id=tenant_id)
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return None
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async def get_sales_summary(
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self,
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tenant_id: str,
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start_date: date,
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end_date: date
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) -> Dict[str, Any]:
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"""
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Get sales summary/analytics for a tenant.
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This method calls the sales analytics summary endpoint which provides
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aggregated sales metrics over a date range.
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Args:
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tenant_id: The tenant UUID
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start_date: Start date for summary range
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end_date: End date for summary range
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Returns:
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Sales summary data including metrics like total sales, revenue, etc.
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"""
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params = {
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"start_date": start_date.isoformat(),
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"end_date": end_date.isoformat()
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}
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return await self.get(
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"sales/analytics/summary",
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tenant_id=tenant_id,
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params=params
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)
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async def get_sales_summary_batch(
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self,
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tenant_ids: List[str],
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start_date: date,
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end_date: date
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) -> Dict[str, Any]:
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"""
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Get sales summaries for multiple tenants in a single request.
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Phase 2 optimization: Eliminates N+1 query patterns for enterprise dashboards.
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Args:
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tenant_ids: List of tenant IDs to fetch
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start_date: Start date for summary range
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end_date: End date for summary range
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Returns:
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Dict mapping tenant_id -> sales summary
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"""
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try:
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if not tenant_ids:
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return {}
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if len(tenant_ids) > 100:
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logger.warning("Batch request exceeds max tenant limit", requested=len(tenant_ids))
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tenant_ids = tenant_ids[:100]
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data = {
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"tenant_ids": tenant_ids,
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"start_date": start_date.isoformat(),
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"end_date": end_date.isoformat()
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}
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result = await self.post(
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"sales/batch/sales-summary",
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data=data,
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tenant_id=tenant_ids[0] # Use first tenant for auth context
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)
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summaries = result if isinstance(result, dict) else {}
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logger.info(
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"Batch retrieved sales summaries",
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requested=len(tenant_ids),
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found=len(summaries),
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start_date=start_date.isoformat(),
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end_date=end_date.isoformat()
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)
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return summaries
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except Exception as e:
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logger.error(
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"Error batch fetching sales summaries",
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error=str(e),
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tenant_count=len(tenant_ids)
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)
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return {}
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async def get_product_demand_patterns(
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self,
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tenant_id: str,
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product_id: str,
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start_date: Optional[date] = None,
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end_date: Optional[date] = None,
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min_history_days: int = 90
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) -> Dict[str, Any]:
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"""
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Get demand pattern analysis for a specific product.
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Args:
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tenant_id: Tenant identifier
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product_id: Product identifier (inventory_product_id)
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start_date: Start date for analysis
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end_date: End date for analysis
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min_history_days: Minimum days of history required
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Returns:
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Demand pattern analysis including trends, seasonality, and statistics
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"""
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try:
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params = {"min_history_days": min_history_days}
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if start_date:
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params["start_date"] = start_date.isoformat()
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if end_date:
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params["end_date"] = end_date.isoformat()
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result = await self.get(
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f"sales/analytics/products/{product_id}/demand-patterns",
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tenant_id=tenant_id,
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params=params
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)
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logger.info(
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"Retrieved product demand patterns",
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tenant_id=tenant_id,
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product_id=product_id
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)
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return result if result else {}
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except Exception as e:
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logger.error(
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"Failed to get product demand patterns",
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error=str(e),
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tenant_id=tenant_id,
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product_id=product_id
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)
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return {}
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# ================================================================
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# DATA IMPORT
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# ================================================================
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async def import_sales_data(
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self,
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tenant_id: str,
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file_content: str,
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file_format: str,
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filename: Optional[str] = None
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) -> Optional[Dict[str, Any]]:
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"""Import sales data from CSV/Excel/JSON"""
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data = {
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"content": file_content,
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"format": file_format,
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"filename": filename
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}
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return await self.post("sales/operations/import", data=data, tenant_id=tenant_id)
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