python 50 lines · 2 tabs

Django redis caching strategies

Priya Sharma Jan 2026

2 tabs

CACHES = {
    'default': {
        'BACKEND': 'django_redis.cache.RedisCache',
        'LOCATION': 'redis://127.0.0.1:6379/1',
        'OPTIONS': {
            'CLIENT_CLASS': 'django_redis.client.DefaultClient',
            'PASSWORD': 'your-redis-password',
            'SOCKET_CONNECT_TIMEOUT': 5,
            'SOCKET_TIMEOUT': 5,
            'CONNECTION_POOL_KWARGS': {'max_connections': 50}
        },
        'KEY_PREFIX': 'myapp',
        'VERSION': 1,
    }
}

# Use Redis for sessions
SESSION_ENGINE = 'django.contrib.sessions.backends.cache'
SESSION_CACHE_ALIAS = 'default'

from django.core.cache import cache
from django.views.decorators.cache import cache_page


def get_popular_products():
    """Cache expensive query."""
    cache_key = 'popular_products'
    products = cache.get(cache_key)

    if products is None:
        from products.models import Product
        products = list(Product.objects.filter(
            featured=True
        ).order_by('-sales')[:10])

        cache.set(cache_key, products, 3600)  # Cache for 1 hour

    return products


# Cache view for 15 minutes
@cache_page(60 * 15)
def product_list(request):
    # View implementation
    pass


# Invalidate cache
def clear_product_cache():
    cache.delete('popular_products')
    cache.delete_pattern('product:*')  # Delete by pattern

2 files · python Explain with highlit

Redis provides fast in-memory caching for Django. I configure it as cache backend and use for session storage. I cache expensive querysets, computed values, and API responses. The cache.get_or_set() method simplifies cache-aside pattern. For cache invalidation, I use versioning or targeted deletes. I set appropriate TTLs based on data volatility. Redis also enables rate limiting, message queues, and pub/sub. For distributed systems, Redis centralizes cache across servers. This dramatically improves response times for read-heavy workloads.

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