What caching tools or techniques have you used in your projects?

In Python projects, various tools and techniques are used for caching:

• functools.lru_cache module: a simple way to cache function results with size limitation.

from functools import lru_cache

@lru_cache(maxsize=128)
def fibonacci(n):
    if n < 2:
        return n
    return fibonacci(n-1) + fibonacci(n-2)

• Using external caches, such as Redis or Memcached: for caching data between application runs or in distributed systems.

• Web framework-level caching: for example, Django provides built-in caching with various backends.

• In-memory caching: using dictionaries or specialized libraries (e.g., cachetools).

• Query result caching in databases: to reduce load and speed up responses.

The choice of technique depends on requirements for cache size, lifetime, and application architecture.