import os
import sys


import numpy as np
import pandas as pd
import pickle

from sklearn.metrics import r2_score


from src.logger import logging
from src.exception import CustomException

def save_object(file_path, obj):
    try:
        dir_path = os.path.dirname(file_path)
        os.makedirs(dir_path,exist_ok=True)
        with open(file_path, 'wb') as file_obj:
            pickle.dump(obj,file_obj)
    
    except Exception as e:
        raise CustomException(e,sys)
    
def evaluate_models(X_train, y_train, X_test, y_test, models):
    try:
        report = {}

        for i in range(len(list(models))):
            model = list(models.values())[i]
            
            logging.info('training started')
            model.fit(X_train,y_train)

            y_train_pred = model.predict(X_train)

            y_test_pred = model.predict(X_test)

            train_model_score = r2_score(y_train, y_train_pred)

            test_model_score = r2_score(y_test,y_test_pred)

            report[list(models.keys())[i]] = test_model_score
        
        return report

            
    except Exception as e:
        raise ConnectionAbortedError(e,sys)