import logging
from typing import List, Dict
from graph_pre_processing import pre_processing
from graph_processing import processing
from graph_post_processing import post_processing

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


def __main__(results: List[Dict]) -> List[Dict]:
    logger.info(f"data receiving in g1v1 block: {results}")
    data = pre_processing(results)
    logger.info(f"pre_processed_data, new_user_app_data: {data}")

    # df = processing(data)
    if data.get("cluster_size", 2) < 2:
        data["prediction"] = 0
    else:
        data = processing(data)
    logger.info("prediction: %.8f", float(data['prediction']))

    # Post-processing: calculate the Final Score and update the dataframe.
    final = post_processing(data)
    logger.info(final)

    return final

# testing :
# __main__