Nhom

Notes

I'll explain the tour operators signals.py file in detail, including its purpose, functionality, and how it maintains data consistency across the system.

Tour Operators Signals System - Detailed Analysis

File Overview

Purpose: Automatic data consistency maintenance and statistics updates Location: signals.py Pattern: Django signals with receivers for real-time data synchronization

Imports and Dependencies

from django.db.models.signals import post_save, post_delete

from django.dispatch import receiver

from django.db.models import Avg, Count

from .models import TourBooking, Tour, TourOperator

Signal Types Used:

• post_save: Triggered after a model instance is saved (create/update)
• post_delete: Triggered after a model instance is deleted

Models Involved:

• TourBooking: Individual tour reservations
• Tour: Tour offerings from operators
• TourOperator: Companies providing tours

Signal Handlers Detailed Analysis

1. Booking Statistics Handler (post_save)

@receiver(post_save, sender=TourBooking)

def update_tour_booking_stats(sender, instance, created, **kwargs):

    """Update tour booking statistics when a booking is created or updated"""

    tour = instance.tour

    # Update total bookings count

    tour.total_bookings = TourBooking.objects.filter(

        tour=tour,

        booking_status__in=['confirmed', 'paid', 'completed']

    ).count()

    tour.save(update_fields=['total_bookings'])

    # Update tour operator statistics

    operator = tour.tour_operator

    operator.total_tours = Tour.objects.filter(tour_operator=operator, is_active=True).count()

    operator.save(update_fields=['total_tours'])

Trigger Conditions:

• When a new TourBooking is created
• When an existing TourBooking is updated (status changes, modifications)

Functionality Breakdown:

1. Tour Booking Count Update:
   • Counts only bookings with valid statuses: 'confirmed', 'paid', 'completed'
   • Excludes cancelled, pending, or failed bookings
   • Updates the total_bookings field on the related Tour model
2. Operator Statistics Update:
   • Counts active tours (is_active=True) for the tour operator
   • Updates the total_tours field on the TourOperator model
   • Maintains consistency between operator and tour data

Business Impact:

• Real-time statistics for tour popularity
• Accurate booking counts for business analytics
• Automatic maintenance of aggregate data

2. Booking Deletion Handler (post_delete)

@receiver(post_delete, sender=TourBooking)

def update_tour_booking_stats_on_delete(sender, instance, **kwargs):

    """Update tour booking statistics when a booking is deleted"""

    tour = instance.tour

    # Update total bookings count

    tour.total_bookings = TourBooking.objects.filter(

        tour=tour,

        booking_status__in=['confirmed', 'paid', 'completed']

    ).count()

    tour.save(update_fields=['total_bookings'])

Trigger Conditions:

• When a TourBooking instance is permanently deleted from the database

Functionality:

• Recalculates the total booking count for the affected tour
• Ensures statistics remain accurate after booking deletions
• Uses the same filtering logic (confirmed/paid/completed statuses)

Use Cases:

• Administrative booking removals
• Data cleanup operations
• Cancelled booking permanent deletion

3. Tour Count Handler (post_save)

@receiver(post_save, sender=Tour)

def update_operator_tour_count(sender, instance, created, **kwargs):

    """Update tour operator's total tours count when a tour is created/updated"""

    operator = instance.tour_operator

    operator.total_tours = Tour.objects.filter(tour_operator=operator, is_active=True).count()

    operator.save(update_fields=['total_tours'])

Trigger Conditions:

• When a new Tour is created
• When an existing Tour is updated (including status changes)

Functionality:

• Recalculates active tour count for the tour operator
• Updates operator's total_tours field
• Only counts tours with is_active=True

Business Scenarios:

• New tour launches
• Tour activation/deactivation
• Tour status changes
• Operator profile updates

4. Tour Deletion Handler (post_delete)

@receiver(post_delete, sender=Tour)

def update_operator_tour_count_on_delete(sender, instance, **kwargs):

    """Update tour operator's total tours count when a tour is deleted"""

    operator = instance.tour_operator

    operator.total_tours = Tour.objects.filter(tour_operator=operator, is_active=True).count()

    operator.save(update_fields=['total_tours'])

Trigger Conditions:

• When a Tour instance is permanently deleted

Functionality:

• Decrements the operator's tour count automatically
• Maintains data consistency after tour removal
• Prevents orphaned statistics

Signal System Architecture Benefits

Data Consistency

• Automatic Updates: No manual intervention required for statistics
• Real-time Accuracy: Statistics update immediately with data changes
• Referential Integrity: Maintains relationships between models

Performance Optimization

• Efficient Queries: Uses update_fields to minimize database writes
• Targeted Updates: Only updates specific fields that changed
• Avoiding N+1 Queries: Direct count queries instead of iteration

Business Intelligence

• Live Metrics: Tour popularity and operator performance tracking
• Booking Analytics: Real-time booking success rates
• Operator Rankings: Accurate tour counts for comparison

Data Flow Example

Scenario: Customer books a tour

1. TourBooking Created:

TourBooking.objects.create(

    tour=tour_instance,

    booking_status='confirmed',

    customer=user

)

2. Signal Triggered: update_tour_booking_stats fires
3. Cascade Updates:
   • Tour's total_bookings increments
   • Operator's total_tours recalculated (if tour status changed)
4. UI Updates:
   • Tour detail page shows updated booking count
   • Operator profile displays current statistics

Error Handling Considerations

Potential Issues:

• Database transaction failures during signal processing
• Circular signal triggering (avoided by using update_fields)
• High-frequency updates causing performance issues

Current Protections:

• update_fields parameter prevents unnecessary field updates
• Specific field targeting reduces database load
• Status filtering ensures only valid bookings are counted

Integration with Business Logic

Template Usage:

• Statistics displayed in operator cards (operator_list.html)
• Tour popularity shown in tour listings (tour_list.html)
• Booking counts in tour details (tour_detail.html)

Admin Interface:

• Real-time statistics visible in Django admin
• No manual calculation required for aggregate fields

API Endpoints:

• REST API can return accurate statistics without additional queries
• Real-time data for dashboard components

Recommendations for Enhancement

1. Add Error Logging:

import logging

logger = logging.getLogger(__name__)

try:

    tour.save(update_fields=['total_bookings'])

except Exception as e:

    logger.error(f"Failed to update tour stats: {e}")

2. Consider Celery for Heavy Operations:
   • Move complex calculations to background tasks
   • Prevent blocking request processing
3. Add Rating Calculations:

# Add to booking stats handler

tour.average_rating = TourBooking.objects.filter(

    tour=tour, rating__isnull=False

).aggregate(avg_rating=Avg('rating'))['avg_rating'] or 0

4. Implement Caching Strategy:
   • Cache frequently accessed statistics
   • Invalidate cache when signals fire

This signals system provides robust, automatic data consistency maintenance that's essential for a professional tour booking platform, ensuring accurate statistics and seamless user experience