django-patterns

name	django-patterns
type	reference
description	Provides expert-level Django development patterns covering App Router (indirectly via REST/GraphQL), async views, DRF, Celery, signals, middleware, and performance optimization. Use when building complex Django 5.x applications or identifying N+1 query issues.
paths	["**/*.py","**/manage.py","**/settings.py","**/urls.py","**/serializers.py"]
effort	3
allowed-tools	Read, Glob, Grep, Write, Edit, Bash
user-invocable	true
when_to_use	When building Django 5.x applications requiring async support, background tasks (Celery), real-time features (Channels), or advanced ORM optimization.

Django & DRF Professional Patterns

Core Expertise

• Modern Django: 5.x features, async views/middleware, ASGI deployment.
• Background & Real-time: Celery integration, Django Channels.
• ORM Optimization: select_related, prefetch_related, custom managers.
• Security: JWT auth, OAuth2, RBAC, protection against SQLi/XSS/CSRF.

Critical rules (non-obvious)

• N+1 queries: always use select_related (FK) / prefetch_related (M2M) — never iterate and query inside loops
• get_or_create race condition: wrap in transaction.atomic() in concurrent environments
• Never call save() inside pre_save signal — causes infinite recursion; use update_fields
• bulk_create skips signals and save() — don't use when signal logic is required
• Migrations on large tables: use RunSQL with CONCURRENTLY index creation to avoid locks

ORM: select_related vs prefetch_related

# FK / OneToOne → select_related (JOIN)
books = Book.objects.select_related("author", "author__publisher").all()

# M2M / reverse FK → prefetch_related (separate query)
authors = Author.objects.prefetch_related("books", "books__tags").all()

# Custom prefetch with queryset
from django.db.models import Prefetch
Author.objects.prefetch_related(
    Prefetch("books", queryset=Book.objects.filter(published=True), to_attr="active_books")
)

ORM: annotations and aggregations

from django.db.models import Count, Avg, Q, F, Value
 django.db.models.functions  Coalesce

Author.objects.annotate(
    book_count=Count(),
    avg_rating=Coalesce(Avg(), Value()),
    high_rated=Count(, =Q(books__rating__gte=)),
).(book_count__gt=).order_by()