Caching Strategies

Introduction

Implement caching to improve application performance and reduce database load.

Function Caching

from functools import lru_cache
from datetime import timedelta

@lru_cache(maxsize=128)
def expensive_computation(n):
    return n ** 2

# With TTL (time-to-live)
from functools import wraps
import time

def cache_with_ttl(ttl_seconds):
    def decorator(func):
        cache = {}
        @wraps(func)
        def wrapper(*args):
            now = time.time()
            if args in cache:
                value, timestamp = cache[args]
                if now - timestamp < ttl_seconds:
                    return value
            result = func(*args)
            cache[args] = (result, now)
            return result
        return wrapper
    return decorator

Django Caching

# settings.py
CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.redis.RedisCache",
        "LOCATION": "redis://127.0.0.1:6379/1",
    }
}

# Views
from django.views.decorators.cache import cache_page

@cache_page(60 * 15)  # 15 minutes
def my_view(request):
    pass

Practice Problems

1. Implement function memoization
2. Use Redis for application caching
3. Cache database queries
4. Implement cache invalidation
5. Create cache decorator with TTL