What is caching in Python and how does it work?

What is caching in Python and how does it work?

Caching in Python is a technique to store frequently accessed data in memory to speed up retrieval. It reduces the time taken to fetch data by avoiding repeated calculations or database queries.

Can you explain the different types of caching available in Python?

Sure! There are several types of caching in Python, including in-memory caching, file-based caching, and distributed caching. Libraries like functools.lru_cache and cachetools are commonly used for in-memory caching.

How do I implement caching in my Python application?

You can implement caching using decorators like @lru_cache from the functools module. This allows you to cache the results of function calls based on their input arguments.

What are the benefits of using caching?

The benefits of caching include improved performance, reduced latency, and decreased load on databases or external services. It can significantly enhance the user experience by speeding up response times.