178 lines
7.0 KiB
Python
178 lines
7.0 KiB
Python
from collections import defaultdict
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from django.db.models import Sum, Count, Case, When, Q, Value
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from django.db.models.functions import Coalesce
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from apps.authentication.models import Organization
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from apps.authentication.services.service import get_all_org_child
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from apps.core.services.filter.search import DynamicSearchService
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from apps.warehouse.models import InventoryQuotaSaleTransaction, InventoryQuotaSaleItem
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class TransactionDashboardService:
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@staticmethod
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def get_dashboard(org: Organization, start_date: str = None, end_date: str = None, status: str = None):
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orgs_child = get_all_org_child(org=org)
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orgs_child.append(org)
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if org.type.key == 'ADM':
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transactions = InventoryQuotaSaleTransaction.objects.all()
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items = InventoryQuotaSaleItem.objects.all().select_related("gov_product", "free_product")
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else:
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transactions = InventoryQuotaSaleTransaction.objects.filter(
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seller_organization__in=orgs_child
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)
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items = InventoryQuotaSaleItem.objects.filter(
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transaction__seller_organization__in=orgs_child
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).select_related("gov_product", "free_product")
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# filter queryset (transactions & items) by date
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if start_date and end_date:
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transactions = DynamicSearchService(
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queryset=transactions,
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start=start_date,
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end=end_date,
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date_field="create_date",
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).apply()
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items = DynamicSearchService(
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queryset=items,
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start=start_date,
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end=end_date,
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date_field="create_date",
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).apply()
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# filer by transaction status
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if status:
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transactions = transactions.filter(transaction_status=status)
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items = items.filter(transaction__transaction_status=status)
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transaction_stats = transactions.aggregate(
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total_transactions=Count("id"),
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success_transactions=Count("id", filter=Q(transaction_status="success")),
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failed_transactions=Count("id", filter=Q(transaction_status="failed")),
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waiting_transactions=Count("id", filter=Q(transaction_status="waiting")),
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total_amount=Coalesce(
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Sum(
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"price_paid", filter=Q(transaction_status='success' if not status else status)
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), 0
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),
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unique_ranchers=Count("rancher", distinct=True),
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)
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transaction_stats['total_weight'] = items.aggregate(
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total_weight=Coalesce(Sum(
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"weight",
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filter=Q(transaction__transaction_status="success" if not status else status)
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), 0)
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)['total_weight']
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products_stats = items.values(
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product_id=Case(
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When(gov_product__isnull=False, then="gov_product_id"),
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When(free_product__isnull=False, then="free_product_id"),
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),
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product_name=Case(
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When(gov_product__isnull=False, then="gov_product__name"),
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When(free_product__isnull=False, then="free_product__product__name"),
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),
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product_type=Case(
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When(gov_product__isnull=False, then=Value("gov")),
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When(free_product__isnull=False, then=Value("free")),
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)
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).annotate(
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total_sales=Count("id"),
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total_weight=Coalesce(Sum("weight"), 0),
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# total_price=Coalesce(Sum("total_price"), 0),
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# avg_unit_price=Coalesce(Sum("total_price") / Sum("weight"), 0),
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success_sales=Count("id", filter=Q(transaction__transaction_status="success")),
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failed_sales=Count("id", filter=Q(transaction__transaction_status="failed")),
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waiting_sales=Count("id", filter=Q(transaction__transaction_status="waiting")),
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card_payments=Count("id", filter=Q(transaction__price_type="card")),
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cash_payments=Count("id", filter=Q(transaction__price_type="cash")),
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check_payments=Count("id", filter=Q(transaction__price_type="check")),
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credit_payments=Count("id", filter=Q(transaction__price_type="credit")),
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extra_items=Count("id", filter=Q(is_extra=True)),
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pre_sale_items=Count("id", filter=Q(is_pre_sale=True)),
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).order_by("-total_sales")
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# calculate sum of item share percentage by product
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items_by_product = defaultdict(list)
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for item in items:
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pid = item.gov_product_id or item.free_product_id
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items_by_product[pid].append(item)
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for product in products_stats:
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pid = product["product_id"]
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share_totals = defaultdict(lambda: {"total_price": 0, "count": 0})
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for item in items_by_product.get(pid, []):
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if item.item_share:
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for share in item.item_share:
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# share: {"name": "", "price": "", ....}
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name = share.get("name")
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price = share.get("price", 0)
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shaba = share.get("shaba", 0) # noqa
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share_totals[name]["total_price"] += price
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share_totals[name]["count"] += 1
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share_totals[name]["shaba"] = shaba # noqa
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share_totals = merge_by_shaba_single_name(share_totals)
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product["item_share_stats"] = sorted(
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[
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{"name": name, **val}
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for name, val in share_totals.items()
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],
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key=lambda x: -x["total_price"]
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)
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# calculate total statistic of every broker
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share_totals = defaultdict(lambda: {"total_price": 0, "count": 0})
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for product in products_stats:
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for item in product["item_share_stats"]:
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name = item["name"]
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share_totals[name]["total_price"] += item["total_price"]
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share_totals[name]["count"] += item["count"]
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dict_share_total = dict(share_totals)
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share_totals = [{"name": share, **dict_share_total[share]} for share in list(share_totals)]
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return {
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"transaction_summary": transaction_stats,
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"product_summary": list(products_stats),
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"brokers_sharing_summary": share_totals
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}
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def merge_by_shaba_single_name(data): # noqa
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grouped = defaultdict(lambda: {"name": None, "total_price": 0, "count": 0, "shaba": None}) # noqa
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for name, info in data.items(): # noqa
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shaba = info["shaba"] # noqa
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if grouped[shaba]["name"] is None:
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grouped[shaba]["name"] = name
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grouped[shaba]["total_price"] += info["total_price"]
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grouped[shaba]["count"] += info["count"]
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grouped[shaba]["shaba"] = shaba # noqa
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final_result = {}
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for shaba, g in grouped.items(): # noqa
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final_result[g["name"]] = {
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"total_price": g["total_price"],
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"count": g["count"],
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"shaba": g["shaba"], # noqa
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}
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return final_result
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