import logging
import gc
import os

# Configure logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')

def reduce_memory(threshold: float = 0.9) -> None:
    """
    Reduces memory usage by clearing garbage collected objects and unreferencing large objects.

    Args:
        threshold (float): Memory usage threshold (0.0 to 1.0) above which memory optimization is triggered. Default is 0.9.

    Returns:
        None
    """
    try:
        # Check available memory
        # This is a placeholder. In a real system, use psutil or similar to get accurate memory usage.
        # For demonstration, we'll use a simple environment variable.
        try:
            memory_usage = float(os.environ.get("MEMORY_USAGE", "0.5"))  # Default to 50% if not set
        except ValueError:
            logging.error("Invalid MEMORY_USAGE environment variable. Using default value of 0.5.")
            memory_usage = 0.5

        if memory_usage > threshold:
            logging.info(f"Memory usage ({memory_usage}) is above threshold ({threshold}). Initiating memory optimization.")

            # 1. Force garbage collection
            collected = gc.collect()
            logging.info(f"Garbage collector: Collected {collected} objects.")

            # 2. Unreference large objects (placeholder - implement as needed)
            #    This would involve identifying and releasing references to large data structures
            #    that are no longer needed.  This is highly application-specific.
            logging.info("Unreferencing large objects (placeholder - implement application-specific logic).")

            # 3. Trigger garbage collection again to clean up unreferenced objects
            collected = gc.collect()
            logging.info(f"Garbage collector (2nd pass): Collected {collected} objects.")

            logging.info("Memory optimization completed.")
        else:
            logging.info(f"Memory usage ({memory_usage}) is below threshold ({threshold}). No memory optimization needed.")

    except Exception as e:
        logging.error(f"An error occurred during memory optimization: {e}")


if __name__ == '__main__':
    # Example usage (demonstration)
    # Set MEMORY_USAGE environment variable to simulate high memory usage
    os.environ["MEMORY_USAGE"] = "0.95"
    reduce_memory()

    os.environ["MEMORY_USAGE"] = "0.7"
    reduce_memory()