Quick Answer
Advanced Python caching: functools.cache (Python 3.9, unlimited LRU). cachetools.LRUCache(maxsize=100), TTLCache(maxsize=100, ttl=300). Redis for distributed caching: cache.set(key, json.dumps(value), ex=300). Django cache framework with RedisCache backend. For ML: cache expensive model predictions. Cache stampede prevention: probabilistic early expiration or Redis SET NX lock during cache population.
Answer
Use in-memory or distributed caches like Redis. Apply eviction strategies and TTL policies. Boosts performance for repeated computations.
S
SugharaIQ Editorial Team
Verified Answer
This answer has been peer-reviewed by industry experts holding senior engineering roles to ensure technical accuracy and relevance for modern interview standards.
