django-bulk-triggers 0.1.50

Trigger-style triggers for Django bulk operations like bulk_create and bulk_update.

django-bulk-triggers

⚡ Bulk triggers for Django bulk operations and individual model lifecycle events.

django-bulk-triggers brings a declarative, trigger-like experience to Django's bulk_create, bulk_update, and bulk_delete — including support for BEFORE_ and AFTER_ triggers, conditions, batching, and transactional safety. It also provides comprehensive lifecycle triggers for individual model operations.

✨ Features

• Declarative trigger system: @trigger(AFTER_UPDATE, condition=...)
• BEFORE/AFTER triggers for create, update, delete
• Trigger-aware manager that wraps Django's bulk_ operations
• NEW: TriggerModelMixin for individual model lifecycle events
• Trigger chaining, trigger deduplication, and atomicity
• Class-based trigger handlers with DI support
• Support for both bulk and individual model operations

🚀 Quickstart

pip install django-bulk-triggers

Define Your Model

from django.db import models
from django_bulk_triggers.models import TriggerModelMixin

class Account(TriggerModelMixin):
    balance = models.DecimalField(max_digits=10, decimal_places=2)
    # The TriggerModelMixin automatically provides BulkTriggerManager

Create a Trigger Handler

from django_bulk_triggers import trigger, AFTER_UPDATE, Trigger
from django_bulk_triggers.conditions import WhenFieldHasChanged
from .models import Account

class AccountTriggers(Trigger):
    @trigger(AFTER_UPDATE, model=Account, condition=WhenFieldHasChanged("balance"))
    def log_balance_change(self, new_records, old_records):
        print("Accounts updated:", [a.pk for a in new_records])
    
    @trigger(BEFORE_CREATE, model=Account)
    def before_create(self, new_records, old_records):
        for account in new_records:
            if account.balance < 0:
                raise ValueError("Account cannot have negative balance")
    
    @trigger(AFTER_DELETE, model=Account)
    def after_delete(self, new_records, old_records):
        print("Accounts deleted:", [a.pk for a in old_records])

🛠 Supported Trigger Events

• BEFORE_CREATE, AFTER_CREATE
• BEFORE_UPDATE, AFTER_UPDATE
• BEFORE_DELETE, AFTER_DELETE

🔄 Lifecycle Events

Individual Model Operations

The TriggerModelMixin automatically triggers triggers for individual model operations:

# These will trigger BEFORE_CREATE and AFTER_CREATE triggers
account = Account.objects.create(balance=100.00)
account.save()  # for new instances

# These will trigger BEFORE_UPDATE and AFTER_UPDATE triggers
account.balance = 200.00
account.save()  # for existing instances

# This will trigger BEFORE_DELETE and AFTER_DELETE triggers
account.delete()

Bulk Operations

Bulk operations also trigger the same triggers:

# Bulk create - triggers BEFORE_CREATE and AFTER_CREATE triggers
accounts = [
    Account(balance=100.00),
    Account(balance=200.00),
]
Account.objects.bulk_create(accounts)

# Bulk update - triggers BEFORE_UPDATE and AFTER_UPDATE triggers
for account in accounts:
    account.balance *= 1.1
Account.objects.bulk_update(accounts)  # fields are auto-detected

# Bulk delete - triggers BEFORE_DELETE and AFTER_DELETE triggers
Account.objects.bulk_delete(accounts)

Queryset Operations

Queryset operations are also supported:

# Queryset update - triggers BEFORE_UPDATE and AFTER_UPDATE triggers
Account.objects.update(balance=0.00)

# Queryset delete - triggers BEFORE_DELETE and AFTER_DELETE triggers
Account.objects.delete()

Subquery Support in Updates

When using Subquery objects in update operations, the computed values are automatically available in triggers. The system efficiently refreshes all instances in bulk for optimal performance:

from django.db.models import Subquery, OuterRef, Sum

def aggregate_revenue_by_ids(self, ids: Iterable[int]) -> int:
    return self.find_by_ids(ids).update(
        revenue=Subquery(
            FinancialTransaction.objects.filter(daily_financial_aggregate_id=OuterRef("pk"))
            .filter(is_revenue=True)
            .values("daily_financial_aggregate_id")
            .annotate(revenue_sum=Sum("amount"))
            .values("revenue_sum")[:1],
        ),
    )

# In your triggers, you can now access the computed revenue value:
class FinancialAggregateTriggers(Trigger):
    @trigger(AFTER_UPDATE, model=DailyFinancialAggregate)
    def log_revenue_update(self, new_records, old_records):
        for new_record in new_records:
            # This will now contain the computed value, not the Subquery object
            print(f"Updated revenue: {new_record.revenue}")

# Bulk operations are optimized for performance:
def bulk_aggregate_revenue(self, ids: Iterable[int]) -> int:
    # This will efficiently refresh all instances in a single query
    return self.filter(id__in=ids).update(
        revenue=Subquery(
            FinancialTransaction.objects.filter(daily_financial_aggregate_id=OuterRef("pk"))
            .filter(is_revenue=True)
            .values("daily_financial_aggregate_id")
            .annotate(revenue_sum=Sum("amount"))
            .values("revenue_sum")[:1],
        ),
    )

🧠 Why?

Django's bulk_ methods bypass signals and save(). This package fills that gap with:

• Triggers that behave consistently across creates/updates/deletes
• NEW: Individual model lifecycle triggers that work with save() and delete()
• Scalable performance via chunking (default 200)
• Support for @trigger decorators and centralized trigger classes
• NEW: Automatic trigger triggering for admin operations and other Django features
• NEW: Proper ordering guarantees for old/new record pairing in triggers (Salesforce-like behavior)

📦 Usage Examples

Individual Model Operations

# These automatically trigger triggers
account = Account.objects.create(balance=100.00)
account.balance = 200.00
account.save()
account.delete()

Bulk Operations

# These also trigger triggers
Account.objects.bulk_create(accounts)
Account.objects.bulk_update(accounts)  # fields are auto-detected
Account.objects.bulk_delete(accounts)

Advanced Trigger Usage

class AdvancedAccountTriggers(Trigger):
    @trigger(BEFORE_UPDATE, model=Account, condition=WhenFieldHasChanged("balance"))
    def validate_balance_change(self, new_records, old_records):
        for new_account, old_account in zip(new_records, old_records):
            if new_account.balance < 0 and old_account.balance >= 0:
                raise ValueError("Cannot set negative balance")
    
    @trigger(AFTER_CREATE, model=Account)
    def send_welcome_email(self, new_records, old_records):
        for account in new_records:
            # Send welcome email logic here
            pass

Salesforce-like Ordering Guarantees

The system ensures that old_records and new_records are always properly paired, regardless of the order in which you pass objects to bulk operations:

class LoanAccountTriggers(Trigger):
    @trigger(BEFORE_UPDATE, model=LoanAccount)
    def validate_account_number(self, new_records, old_records):
        # old_records[i] always corresponds to new_records[i]
        for new_account, old_account in zip(new_records, old_records):
            if old_account.account_number != new_account.account_number:
                raise ValidationError("Account number cannot be changed")

# This works correctly even with reordered objects:
accounts = [account1, account2, account3]  # IDs: 1, 2, 3
reordered = [account3, account1, account2]  # IDs: 3, 1, 2

# The trigger will still receive properly paired old/new records
LoanAccount.objects.bulk_update(reordered)  # fields are auto-detected

🧩 Integration with Other Managers

You can extend from BulkTriggerManager to work with other manager classes. The manager uses a cooperative approach that dynamically injects bulk trigger functionality into any queryset, ensuring compatibility with other managers.

from django_bulk_triggers.manager import BulkTriggerManager
from queryable_properties.managers import QueryablePropertiesManager

class MyManager(BulkTriggerManager, QueryablePropertiesManager):
    pass

This approach uses the industry-standard injection pattern, similar to how QueryablePropertiesManager works, ensuring both functionalities work seamlessly together without any framework-specific knowledge.

📝 License

MIT © 2024 Augend / Konrad Beck