Caching in Python With lru_cache
There are many ways to achieve fast and responsive applications. Caching is one approach that, when used correctly, makes things much faster while decreasing the load on computing resources.
Python’s functools
module comes with the @lru_cache
decorator, which gives you the ability to cache the result of your functions using the Least Recently Used (LRU) strategy. This is a simple yet powerful technique that you can use to leverage the power of caching in your code.
In this video course, you’ll learn:
- What caching strategies are available and how to implement them using Python decorators
- What the LRU strategy is and how it works
- How to improve performance by caching with the
@lru_cache
decorator - How to expand