src/train.py

from __future__ import annotations

import argparse
from pathlib import Path

from src.data import load_training_data
from src.modeling import DEFAULT_MODEL_PATH, train_model


def main() -> None:
    parser = argparse.ArgumentParser(description="Train the house price prediction model.")
    parser.add_argument("--data", type=Path, default=None, help="Path to Kaggle train.csv")
    parser.add_argument("--output", type=Path, default=DEFAULT_MODEL_PATH, help="Model artifact path")
    args = parser.parse_args()

    frame = load_training_data(args.data)
    trained = train_model(frame, artifact_path=args.output)
    print(f"Saved model to {args.output}")
    print(f"Metrics: {trained.metrics}")


if __name__ == "__main__":
    main()