from pathlib import Path
from dotenv import load_dotenv
import os
import logging

from src.database import (
    VisualCommunication,
    connect,
    upsert_predictions
)

if __name__ == "__main__":
    # setup logging
    fmt = (
        '%(asctime)s | '
        '%(levelname)s | '
        '%(filename)s | '
        '%(funcName)s | '
        '%(message)s'
    )
    datefmt = '%Y-%m-%d %H:%M:%S'
    logging.basicConfig(format=fmt, datefmt=datefmt, level=logging.INFO)
    # get list of image paths
    test_dir = Path(__file__).parent
    img_dir = test_dir / "imgs"
    img_path_list = [path for path in img_dir.glob("*.jpeg") if path.is_file()]
    # instantiate data object
    vis_com_list = [VisualCommunication.from_file(path) for path in img_path_list]
    # generate random predictions
    [vis_com.generate_random_prediction() for vis_com in vis_com_list]
    # prepare env vars
    env_path = test_dir.parent / "local.env"
    assert env_path.exists()
    load_dotenv(env_path)
    os.environ["MONGO_HOST"] = "localhost"
    # connect to database
    collection, db, client = connect()
    # upload visual communication
    for vis_com in vis_com_list:
        upsert_predictions(
            collection=collection,
            vis_com_name=vis_com.name,
            predictions=vis_com.prediction,
        )