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Learn efficient caching strategies in Python through this 26-minute conference talk that explores both local in-memory and external caching solutions. Discover how to implement caching using Python's built-in libraries like functools.lru_cache, cachetools, and joblib, while understanding the fundamentals of cache warming, expiry, and invalidation techniques. Explore when and how to transition from local caching to external solutions like Redis, and master the decision-making process for choosing the right caching strategy for specific use cases. Gain practical insights into optimizing application performance without introducing unnecessary complexity, comparing multiple caching strategies, and integrating Redis into Python applications for scalable caching solutions. Understand how proper caching implementation can drastically improve seemingly simple code while avoiding the pitfalls of improper or excessive caching that can impact deployment, performance, scalability, and maintenance.
