Python Trick: Using functools.lru_cache for Easy Memoization

The functools module in Python provides a powerful yet underutilized decorator called lru_cache. This decorator enables memoization, which stores the results of expensive function calls and reuses them when the same inputs occur again. It's perfect for improving performance with minimal effort!

How It Works:

The lru_cache decorator caches the results of a function based on its inputs.
When the function is called with the same arguments, the cached result is returned instead of recomputing it.
You can control the cache size and even clear it when needed.

Why It's Cool:

Effortless Optimization: Add a single decorator to improve performance.
Configurable Cache Size: Control memory usage with the maxsize parameter.
Built-in Features: Includes cache clearing and cache usage statistics.
When to Use:

Expensive Functions: Useful for functions with high computation cost.
Frequent Calls: Ideal for scenarios with repeated calls to the same function with the same arguments.
Recursive Algorithms: Great for recursive functions like Fibonacci or dynamic programming problems.

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