jdZddlmZmZddlmZmZmZddlm Z ddl m Z ddl m Z ddlmZddlmZmZdd lmZmZmZmZGd d Zy ) z Occupancy service for Aimantis dashboard. Calculates occupancy percentages for: - Today - Next 7 days - Next 30 days Uses optimized SQL aggregation to avoid Python loops. )date timedelta)DictAnyOptional)Q)timezone)Booking)Property)OCCUPANCY_WINDOWSOCCUPANCY_ROUNDING)calculate_overlapping_nights get_today safe_divideround_occupancyceZdZdZddeefdZdeee ffdZ defdZ de d e defd Z defd Zdefd Zdefd ZdeeeffdZy)OccupancyServicez Service for calculating occupancy percentages. Uses efficient overlap calculations and avoids N+1 queries by batching all bookings for a given window. N structure_idc0||_t|_y)z Initialize the occupancy service. Args: structure_id: Optional structure ID for multi-tenant filtering N)rrtoday)selfrs 0/backend/dashboard/services/occupancy_service.py__init__zOccupancyService.__init__&s)[ returnc:|jrd|jiSiS)z&Get structure filter dict for queries.rrrs r_get_structure_filterz&OccupancyService._get_structure_filter0s 6:6G6G 1 12OROrctjj}|jr|j |j}|j S)z'Get total room count for the structure.r)r objectsallrfiltercount)rqss r_get_total_roomsz!OccupancyService._get_total_rooms4sA    ! ! #   (9(9:Bxxzr window_start window_endc>|j}|dk(ry||z j}||z}|dk(rytjjd ||d|j j ddd}t}|D]f}t|j|} t|j|} | | ks5|j| |jf| tdz } | | kr2ht|} t!| dz|d } t| d} t#| t$S) a Calculate occupancy percentage for a date window. CRITICAL BUSINESS RULE: - Counts DISTINCT occupied properties per day (not booking rows) - Occupancy can NEVER exceed 100% - Multiple bookings for the same room on the same day = 1 occupied room Algorithm: 1. For each day in window, count DISTINCT property_ids with active bookings 2. Sum daily occupied rooms across all days 3. Divide by (total_rooms * window_days) Args: window_start: Start date (inclusive) window_end: End date (exclusive) Returns: Occupancy percentage (0-100), capped at 100 r)check_in_date__ltcheck_out_date__gt property_id check_in_datecheck_out_datedaysdg)default)r&r1r r!r#ronlysetmaxr-minr.addr,rlenrrr )rr'r( total_rooms window_daystotal_possible_nightsbookingsoccupied_room_nightsbooking current_date booking_endtotal_reserved_nights occupancyoccupancy_cappeds r_calculate_occupancy_for_windowz0OccupancyService._calculate_occupancy_for_window;sI2++- ! "L066 +k 9 A %??)) (+ ((*  $     #uGw44lCLg44jAK,$((,8K8K)LM q 11 ,  !$$8 9 !C ' ! y#./1CDDrch|j|j|jtdzS)zu Calculate occupancy for today. Returns: Occupancy percentage for today r/r0rFrrrs rget_today_occupancyz$OccupancyService.get_today_occupancy/33 JJ JJ* *  rch|j|j|jtdzS)z Calculate occupancy forecast for next 7 days. Returns: Average occupancy percentage for next 7 days r0rHrs rget_next_7_days_occupancyz*OccupancyService.get_next_7_days_occupancyrJrch|j|j|jtdzS)z Calculate occupancy forecast for next 30 days. Returns: Average occupancy percentage for next 30 days r0rHrs rget_next_30_days_occupancyz+OccupancyService.get_next_30_days_occupancys/33 JJ JJ+ +  rcb|j|j|jdS)z Get all occupancy metrics in a single call. Returns: Dict with occupancy percentages for different time windows )r next_7_days next_30_days)rIrMrPrs r get_occupancyzOccupancyService.get_occupancys2--/99; ;;=  r)N)__name__ __module__ __qualname____doc__rintrrstrrrr&rrFrIrMrPrTr4rrrrs!Xc]!PtCH~P#RERERE REh  S    3    C    tCH~  rrN)rXdatetimerrtypingrrrdjango.db.modelsr django.utilsr bookings.modelsr properties.modelsr dashboard.constantsr r dashboard.services.utilsrrrrrr4rrrcs: %&&!#&E` ` r