"""
AutomatedMemoizer
Generated by Eden via recursive self-improvement
2025-10-28 07:40:17.403419
"""

class AutomatedMemoizer:
    """A decorator class that caches function results to avoid recomputation.
    
    This capability enhances AI efficiency by storing previously computed results,
    allowing for faster responses when the same inputs are encountered again.
    """
    
    def __init__(self):
        self.cache = {}
        
    def __call__(self, func):
        """Decorator method that wraps the target function."""
        def wrapped(*args, **kwargs):
            # Convert arguments to a hashable tuple
            key = (args, frozenset(kwargs.items()))
            if key in self.cache:
                return self.cache[key]
            result = func(*args, **kwargs)
            self.cache[key] = result
            return result
        return wrapped

# Example usage:
# Add this capability to a function like so:

@AutomatedMemoizer()
def compute_expensive_task(data):
    # Simulate an expensive computation
    import time
    time.sleep(1)  # Simulates delay
    return len(data)

# The first call will take time, subsequent calls with same data will be instant:
print(compute_expensive_task("test"))  # Output: 4
print(compute_expensive_task("test"))  # Output: 4 (faster)