"""Script d'entraînement Iris hors-API, utilisable depuis un notebook ou la console.
Sauvegarde le modèle dans /work/models/iris_model.pkl.
"""

from pathlib import Path
import joblib
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression

MODELS_DIR = Path("/work/models")
MODEL_PATH = MODELS_DIR / "iris_model.pkl"


def main():
    iris = load_iris()
    X = iris.data
    y = iris.target

    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

    clf = LogisticRegression(max_iter=1000)
    clf.fit(X_train, y_train)
    acc = clf.score(X_test, y_test)

    MODELS_DIR.mkdir(parents=True, exist_ok=True)
    joblib.dump(clf, MODEL_PATH)
    print({"status": "trained", "accuracy": float(acc), "model_path": str(MODEL_PATH)})


if __name__ == "__main__":
    main()