structure updated

src/components/data_ingestion.py

@@ -0,0 +1,26 @@
+import pandas as pd
+import numpy as np
+from src.logger.logging import logging
+from src.exception.exception import customexception
+
+
+import os
+import sys
+from sklearn.model_selection import train_test_splits
+from dataclasses import dataclass
+from pathlib import Path
+
+@dataclass
+class DataIngestionConfig:
+    pass
+
+class DataIngestion:
+    def __init__(self):
+        pass
+
+    def initiate_data_ingestion(self):
+        try:
+            pass
+        except Exception as e:
+            logging.info()
+            raise customexception(e,sys)

src/components/data_transformation.py

@@ -0,0 +1,31 @@
+import pandas as pd
+import numpy as np
+from src.logger.logging import logging
+from src.exception.exception import customexception
+import os
+import sys
+from dataclasses import dataclass
+from pathlib import Path
+
+
+from sklearn.compose import ColumnTransformer
+from sklearn.impute import SimpleImputer
+from sklearn.pipeline import Pipeline
+from sklearn.preprocessing import OrdinalEncoder,StandardScaler
+
+from src.utils.utils import save_object
+
+@dataclass
+class DataTransformationConfig:
+    pass
+
+class DataTransformation:
+    def __init__(self):
+        pass
+
+    def initiate_data_ingestion(self):
+        try:
+            pass
+        except Exception as e:
+            logging.info()
+            raise customexception(e,sys)

src/components/model_evaluation.py

@@ -0,0 +1,24 @@
+import os
+import sys
+from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score
+from urllib.parse import urlparse
+import mlflow
+import mlflow.sklearn
+import numpy as np
+import pickle
+from src.DimondPricePrediction.utils.utils import load_object
+
+@dataclass
+class ModelEvaluationConfig:
+    pass
+
+class ModelEvaluation:
+    def __init__(self):
+        pass
+
+    def initiate_model_evaluation(self):
+        try:
+            pass
+        except Exception as e:
+            logging.info()
+            raise customexception(e,sys)

src/components/model_trainer.py

@@ -0,0 +1,28 @@
+import pandas as pd
+import numpy as np
+from src.logger.logging import logging
+from src.exception.exception import customexception
+import os
+import sys
+from dataclasses import dataclass
+from pathlib import Path
+
+from src.utils.utils import save_object,evaluate_model
+
+from sklearn.linear_model import LinearRegression, Ridge,Lasso,ElasticNet
+
+
+@dataclass
+class  ModelTrainerConfig:
+    pass
+
+class ModelTrainer:
+    def __init__(self):
+        pass
+
+    def initate_model_training(self):
+        try:
+            pass
+        except Exception as e:
+            logging.info()
+            raise customexception(e,sys)

src/logger/logging.py

@@ -16,5 +16,6 @@
                     format="[%(asctime)s] %(lineno)d %(name)s - %(levelname)s - %(message)s"
 
 )
+            #[2024-01-10 15:57:26,997] 6 root - INFO -  this my second tesgting
 
 

src/utils/utils.py

@@ -0,0 +1,56 @@
+import os
+import sys
+import pickle
+import numpy as np
+import pandas as pd
+from src.logger.logging import logging
+from src.exception.exception import customexception
+
+from sklearn.metrics import r2_score, mean_absolute_error,mean_squared_error
+
+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_model(X_train,y_train,X_test,y_test,models):
+    try:
+        report = {}
+        for i in range(len(models)):
+            model = list(models.values())[i]
+            # Train model
+            model.fit(X_train,y_train)
+
+
+
+            # Predict Testing data
+            y_test_pred =model.predict(X_test)
+
+            # Get R2 scores for train and test data
+            #train_model_score = r2_score(ytrain,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:
+        logging.info('Exception occured during model training')
+        raise customexception(e,sys)
+
+def load_object(file_path):
+    try:
+        with open(file_path,'rb') as file_obj:
+            return pickle.load(file_obj)
+    except Exception as e:
+        logging.info('Exception Occured in load_object function utils')
+        raise customexception(e,sys)
+
+