import logging

# Configure logging
logging.basicConfig(
    level=logging.INFO,
    format="%(asctime)s [%(levelname)s] %(name)s - %(message)s",
)
logger = logging.getLogger(__name__)

def processing(data: dict) -> dict:
    try:
        hd_score_s1 = (
            min(1225 + (data["cluster_size_users_v2"] * 5), 1390)
            if data["cluster_size_users_v2"] >= 3 and data["hd_score_m1"] >= 1140
            else 0
        )
        logger.info(f"score_s1 calculated: {hd_score_s1}")
    except Exception as e:
        logger.error(f"Error processing score_s1 calculations: {e}")
        return {}

    try:
        hd_score_s2 = (
            min(1215 + (data["cluster_size_users_v2"] * 5), 1380)
            if data["cluster_size_users_v2"] >= 2 and data["app_dt_day_cnt"] == 1
            else 0
        )
        logger.info(f"score_s2 calculated: {hd_score_s2}")
    except Exception as e:
        logger.error(f"Error processing score_s2 calculations: {e}")
        return {}

    try:
        target_connected_30_sum = data.get("target_connected_30_sum", 0) or 0  # Handling None case
        hd_score_s3 = (
            min(1250 + (target_connected_30_sum * 5), 1400)
            if target_connected_30_sum >= 1
            else 0
        )
        logger.info(f"score_s3 calculated: {hd_score_s3}")
    except Exception as e:
        logger.error(f"Error processing score_s3 calculations: {e}")
        return {}

    # Return the final results as a dictionary
    return {
        "hd_score_m1": data["hd_score_m1"],
        "hd_score_g1": data["hd_score_g1"],
        "hd_score_s1": hd_score_s1,
        "hd_score_s2": hd_score_s2,
        "hd_score_s3": hd_score_s3,
    }